Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.

But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.

“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”

With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.

Beyond silicon

Silicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.

Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.

In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.

But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.

“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”

“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.

“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.

This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”

According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”

Measuring makes the difference

With Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.

Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.

“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.

“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”

“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”

The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”

Photovoltaics is just the start

The company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”

Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.

“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”

That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO₂ [carbon dioxide] per year in the not-too-distant future.”

The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.”

Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.

But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.

“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”

With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.

Beyond silicon

Silicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.

Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.

In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.

But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.

“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”

“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.

“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.

This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”

According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”

Measuring makes the difference

With Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.

Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.

“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.

“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”

“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”

The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”

Photovoltaics is just the start

The company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”

Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.

“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”

That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO₂ [carbon dioxide] per year in the not-too-distant future.”

The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.”

Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.

But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.

“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”

With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.

Beyond silicon

Silicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.

Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.

In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.

But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.

“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”

“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.

“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.

This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”

According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”

Measuring makes the difference

With Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.

Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.

“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.

“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”

“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”

The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”

Photovoltaics is just the start

The company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”

Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.

“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”

That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO₂ [carbon dioxide] per year in the not-too-distant future.”

The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.”

A new technical paper titled “Experimental demonstration of magnetic tunnel junction-based computational random-access memory” was published by researchers at University of Minnesota and University of Arizona, Tucson.

Abstract

“The conventional computing paradigm struggles to fulfill the rapidly growing demands from emerging applications, especially those for machine intelligence because much of the power and energy is consumed by constant data transfers between logic and memory modules. A new paradigm, called “computational random-access memory (CRAM),” has emerged to address this fundamental limitation. CRAM performs logic operations directly using the memory cells themselves, without having the data ever leave the memory. The energy and performance benefits of CRAM for both conventional and emerging applications have been well established by prior numerical studies. However, there is a lack of experimental demonstration and study of CRAM to evaluate its computational accuracy, which is a realistic and application-critical metric for its technological feasibility and competitiveness. In this work, a CRAM array based on magnetic tunnel junctions (MTJs) is experimentally demonstrated. First, basic memory operations, as well as 2-, 3-, and 5-input logic operations, are studied. Then, a 1-bit full adder with two different designs is demonstrated. Based on the experimental results, a suite of models has been developed to characterize the accuracy of CRAM computation. Scalar addition, multiplication, and matrix multiplication, which are essential building blocks for many conventional and machine intelligence applications, are evaluated and show promising accuracy performance. With the confirmation of MTJ-based CRAM’s accuracy, there is a strong case that this technology will have a significant impact on power- and energy-demanding applications of machine intelligence.”

Find the technical paper here. Published July 2024.  Find the University of Minnesota’s news release here.

Lv, Y., Zink, B.R., Bloom, R.P. et al. Experimental demonstration of magnetic tunnel junction-based computational random-access memory. npj Unconv. Comput. 1, 3 (2024). https://doi.org/10.1038/s44335-024-00003-3.

The post MTJ-Based CRAM Array appeared first on Semiconductor Engineering.

Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.

But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.

“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”

With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.

Beyond silicon

Silicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.

Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.

In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.

But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.

“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”

“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.

“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.

This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”

According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”

Measuring makes the difference

With Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.

Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.

“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.

“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”

“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”

The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”

Photovoltaics is just the start

The company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”

Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.

“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”

That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO₂ [carbon dioxide] per year in the not-too-distant future.”

The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.”

Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.

But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.

“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”

With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.

Beyond silicon

Silicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.

Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.

In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.

But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.

“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”

“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.

“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.

This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”

According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”

Measuring makes the difference

With Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.

Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.

“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.

“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”

“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”

The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”

Photovoltaics is just the start

The company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”

Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.

“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”

That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO₂ [carbon dioxide] per year in the not-too-distant future.”

The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.”

Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.

But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.

“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”

With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.

Beyond silicon

Silicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.

Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.

In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.

But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.

“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”

“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.

“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.

This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”

According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”

Measuring makes the difference

With Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.

Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.

“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.

“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”

“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”

The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”

Photovoltaics is just the start

The company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”

Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.

“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”

That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO₂ [carbon dioxide] per year in the not-too-distant future.”

The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.”

Over just the past couple of years, supercomputing has accelerated into the exascale era—with the world’s most massive machines capable of performing over a billion billion operations per second. But unless big efficiency improvements can intervene along its exponential growth curve, computing is also anticipated to require increasingly impractical and unsustainable amounts of energy—even, according to one widely cited study, by 2040 demanding more energy than the world’s total present-day output.

Fortunately, the high-performance computing community is shifting focus now toward not just increased performance (measured in raw petaflops or exaflops) but also higher efficiency, boosting the number of operations per watt.

The Green500 list saw newcomers enter into the top three spots, suggesting that some of the world’s newest high-performance systems may be chasing efficiency at least as much as sheer power.

The newest ranking of the Top500 supercomputers (a list of the world’s most powerful machines) and its cousin the Green500 (ranking instead the world’s highest-efficiency machines) came out last week. The leading 10 of the Top 500 largest supercomputers remains mostly unchanged, headed up by Oak Ridge National Laboratory’s Frontier exascale computer. There was only one new addition in the top 10, at No. 6: Swiss National Supercomputing Center’s Alps system. Meanwhile, Argonne National Laboratory’s Aurora doubled its size, but kept its second-tier ranking.

On the other hand, The Green500 list saw newcomers enter into the top three spots, suggesting that some of the world’s newest high-performance systems may be chasing efficiency at least as much as sheer power.

Heading up the new Green500 list was JEDI, Jülich Supercomputing Center’s prototype system for its impending JUPITER exascale computer. The No. 2 and No. 3 spots went to the University of Bristol’s Isambard AI, also the first phase of a larger planned system, and the Helios supercomputer from the Polish organization Cyfronet. In fourth place is the previous list’s leader, the Simons Foundation’s Henri.

A Hopper Runs Through It

The top three systems on the Green500 list have one thing in common—they are all built with Nvidia’s Grace Hopper superchips, a combination of the Hopper (H100) GPU and the Grace CPU. There are two main reasons why the Grace Hopper architecture is so efficient, says Dion Harris, director of accelerated data center go-to-market strategy at Nvidia. The first is the Grace CPU, which benefits from the ARM instruction set architecture’s superior power performance. Plus, he says, it incorporates a memory structure, called LPDDR5X, that’s commonly found in cellphones and is optimized for energy efficiency.

Nvidia’s GH200 Grace Hopper superchip, here deployed in Jülich’s JEDI machine, now powers the world’s top three most efficient HPC systems. Jülich Supercomputing Center

The second advantage of the Grace Hopper, Harris says, is a newly developed interconnect between the Hopper GPU and the Grace CPU. The connection takes advantage of the CPU and GPU’s proximity to each other on one board, and achieves a bandwidth of 900 gigabits per second, about 7 times as fast as the latest PCIe gen5 interconnects. This allows the GPU to access the CPU’s memory quickly, which is particularly important for highly parallel applications such as AI training or graph neural networks, Harris says.

All three top systems use Grace Hoppers, but Jülich’s JEDI still leads the pack by a noticeable margin—72.7 gigaflops per watt, as opposed to 68.8 gigaflops per watt for the runner-up (and 65.4 gigaflops per watt for the previous champion). The JEDI team attributes their added success to the way they’ve connected their chips together. Their interconnect fabric was also from Nvidia—Quantum-2 InfiniBand—rather than the HPE Slingshot used by the other two top systems.

The JEDI team also cites specific optimizations they did to accommodate the Green500 benchmark. In addition to using all the latest Nvidia gear, JEDI cuts energy costs with its cooling system. Instead of using air or chilled water, JEDI circulates hot water throughout its compute nodes to take care of the excess heat. “Under normal weather conditions, the excess heat can be taken care of by free cooling units without the need of additional cold-water cooling,” says Benedikt von St. Vieth, head of the division for high-performance computing at Jülich.

JUPITER will use the same architecture as its prototype, JEDI, and von St. Vieth says he aims for it to maintain much of the prototype’s energy efficiency—although with increased scale, he adds, more energy may be lost to interconnecting fabric.

Of course, most crucial is the performance of these systems on real scientific tasks, not just on the Green500 benchmark. “It was really exciting to see these systems come online,” Nvidia’s Harris says, “But more importantly, I think we’re really excited to see the science come out of these systems, because I think [the energy efficiency] will have more impact on the applications even than on the benchmark.”

Attention nowadays has turned to the energy consumption of systems that run on electricity. At the moment, the discussion is focused on electricity consumption in data centers: if this continues to rise at its current rate, it will account for a significant proportion of global electricity consumption in the future. Yet there are other, less visible electricity consumers whose power needs are also constantly growing. One example is mobile communications, where ongoing expansion – especially with the new current 5G standard and the future 6G standard – is pushing up the number of base stations required. This, too, will drive up electricity demand, as the latter increases linearly with the number of stations; at least, if the demand per base station is not reduced. Another example is electronics for the management of household appliances and in the industrial sector: more and more such systems are being installed, and their electronics are becoming significantly more powerful. They are not currently optimized for power consumption, but rather for performance.

This state of affairs simply cannot continue into the future for two reasons: first, the price of electricity will continue to rise worldwide; and second, many companies are committed to becoming carbon neutral. Their desire for carbon neutrality in turn makes electricity yet more expensive and restricts the overall quantity much more severely. As a result, there will be a significant demand for efficient electronics in the coming years, particularly as regards electricity consumption.

This development is already evident today, especially in power electronics, where the use of new semiconductor materials such as GaN or SiC has made it possible to reduce power consumption. A key driver for the development and introduction of such new materials was the electric car market, as reduced losses in the electronics leads directly to increased vehicle range. In the future, these materials will also find their way into other areas; for instance, they are already beginning to establish themselves in voltage transformers in various industries. However, this shift requires more factories and more suppliers for production, and further work also needs to be carried out to develop appropriate circuit concepts for these technologies.

In addition to the use of new materials, other concepts to reduce energy consumption are needed. The data center sector will require increasingly better-adapted circuits – ones that have been developed for a specific task, and as a result can perform this task much more efficiently than universal processors. This involves striking the optimum balance between universal architectures, such as microprocessors and graphics cards, and highly specialized architectures that are suitable for only one use case. Some products will also fall between these two extremes. The increased energy efficiency is then “purchased” through the effort and expense of developing exceptionally specially adapted architectures. It’s important to note that the more specialized an adapted architecture is, the smaller the market for it. That means the only way such architectures will be economically viable is if they can be developed efficiently. This calls for new approaches to derive these architectures directly from high-level hardware/software optimization, without the additional implementation steps that are still necessary today. In sum, the only way to make this approach possible is by using novel concepts and tools to generate circuits directly from a high-level description.

The post Efficient Electronics appeared first on Semiconductor Engineering.

In late April, the Miami-based rail company Brightline Trains broke ground on a project that the company promises will give the United States its first dedicated, high-speed passenger rail service. The 350-kilometer (218-mile) corridor, which the company calls Brightline West, will connect Las Vegas to the suburbs of Los Angeles. Brightline says it hopes to complete the project in time for the 2028 Summer Olympic Games, which will take place in Los Angeles.

Brightline has chosen Siemens American Pioneer 220 engines that will run at speeds averaging 165 kilometers per hour, with an advertised top speed of 320 km/h. That average speed still falls short of the Eurostar network connecting London, Paris, Brussels, and Amsterdam (300 km/h), Germany’s Intercity-Express 3 service (330 km/h), and the world’s fastest train service, China’s Beijing-to-Shanghai regional G trains (350 km/h).

There are currently only two rail lines in the U.S. that ever reach the 200 km/h mark, which is the unofficial minimum speed at which a train can be considered to be high-speed rail. Brightline, the company that is about to construct the L.A.-to-Las-Vegas Brightline West line, also operates a Miami-Orlando rail line that averages 111 km/h. The other is Amtrak’s Acela line between Boston and Washington, D.C.—and that line only qualifies as high-speed rail for just 80 km of its 735-km route. That’s a consequence of the rail status quo in the United States, in which slower freight trains typically have right of way on shared rail infrastructure.

As Vaclav Smil, professor emeritus at the University of Manitoba, noted in IEEE Spectrum in 2018, there has long been hope that the United States would catch up with Europe, China, and Japan, where high-speed regional rail travel has long been a regular fixture. “In a rational world, one that valued convenience, time, low energy intensity and low carbon conversions, the high-speed electric train would always be the first choice for [intercity travel],” Smil wrote at the time. And yet, in the United States, funding and regulatory approval for such projects have been in short supply.

Now, Brightline West, as well as a few preexisting rail projects that are at some stage of development, such as the California High-Speed Rail Network and the Texas Central Line, could be a bellwether for an attitude shift that could—belatedly—put trains closer to equal footing with cars and planes for travelers in the continental United States.

The U.S. government, like many national governments, has pledged to reduce greenhouse gas emissions. Because that generally requires decarbonizing transportation and improving energy efficiency, trains, which can run on electricity generated from fossil-fuel as well as non-fossil-fuel sources, are getting a big push. As Smil noted in 2018, trains use a fraction of a megajoule of energy per passenger-kilometer, while a lone driver in even one of the most efficient gasoline-powered cars will use orders of magnitude more energy per passenger-kilometer.

Brightline and Siemens did not respond to inquiries by Spectrum seeking to find out what innovations they plan to introduce that would make the L.A.-to-Las Vegas passenger line run faster or perhaps use less energy than its Asian and European counterparts. But Karen E. Philbrick, executive director of the Mineta Transportation Institute at San Jose State University, in California, says that’s beside the point. She notes that the United States, having focused on cars for the better part of the past century, already missed the period when major innovations were being made in high-speed rail. “What’s important about Brightline West and, say, the California High-speed Rail project, is not how innovative they are, but the fact that they’re happening at all. I am thrilled to see the U.S. catching up.”

Maybe Brightline or other groups seeking to get Americans off the roadways and onto railways will be able to seize the moment and create high-speed rail lines connecting other intraregional population centers in the United States. With enough of those pieces in place, it might someday be possible to ride the rails from California to New York in a single day, in the same way train passengers in China can get from Beijing to Shanghai between breakfast and lunch.

Scientists have predicted that by 2040, almost 50 percent of the world’s electric power will be used in computing. What’s more, this projection was made before the sudden explosion of generative AI. The amount of computing resources used to train the largest AI models has been doubling roughly every 6 months for more than the past decade. At this rate, by 2030 training a single artificial-intelligence model would take one hundred times as much computing resources as the combined annual resources of the current top ten supercomputers. Simply put, computing will require colossal amounts of power, soon exceeding what our planet can provide.

One way to manage the unsustainable energy requirements of the computing sector is to fundamentally change the way we compute. Superconductors could let us do just that.

Superconductors offer the possibility of drastically lowering energy consumption because they do not dissipate energy when passing current. True, superconductors work only at cryogenic temperatures, requiring some cooling overhead. But in exchange, they offer virtually zero-resistance interconnects, digital logic built on ultrashort pulses that require minimal energy, and the capacity for incredible computing density due to easy 3D chip stacking.

Are the advantages enough to overcome the cost of cryogenic cooling? Our work suggests they most certainly are. As the scale of computing resources gets larger, the marginal cost of the cooling overhead gets smaller. Our research shows that starting at around 10 ¹⁶ floating-point operations per second (tens of petaflops) the superconducting computer handily becomes more power efficient than its classical cousin. This is exactly the scale of typical high-performance computers today, so the time for a superconducting supercomputer is now.

At Imec, we have spent the past two years developing superconducting processing units that can be manufactured using standard CMOS tools. A processor based on this work would be one hundred times as energy efficient as the most efficient chips today, and it would lead to a computer that fits a data-center’s worth of computing resources into a system the size of a shoebox.

The Physics of Energy-Efficient Computation

Superconductivity—that superpower that allows certain materials to transmit electricity without resistance at low enough temperatures—was discovered back in 1911, and the idea of using it for computing has been around since the mid-1950s. But despite the promise of lower power usage and higher compute density, the technology couldn’t compete with the astounding advance of CMOS scaling under Moore’s Law. Research has continued through the decades, with a superconducting CPU demonstrated by a group at Yokohama National University as recently as 2020. However, as an aid to computing, superconductivity has stayed largely confined to the laboratory.

To bring this technology out of the lab and toward a scalable design that stands a chance of being competitive in the real world, we had to change our approach here at Imec. Instead of inventing a system from the bottom up—that is, starting with what works in a physics lab and hoping it is useful—we designed it from the top down—starting with the necessary functionality, and working directly with CMOS engineers and a full-stack development team to ensure manufacturability. The team worked not only on a fabrication process, but also software architectures, logic gates, and standard-cell libraries of logic and memory elements to build a complete technology.

The foundational ideas behind energy-efficient computation, however, have been developed as far back as 1991. In conventional processors, much of the power consumed and heat dissipated comes from moving information among logic units, or between logic and memory elements rather than from actual operations. Interconnects made of superconducting material, however, do not dissipate any energy. The wires have zero electrical resistance, and therefore, little energy is required to move bits within the processor. This property of having extremely low energy losses holds true even at very high communication frequencies, where losses would skyrocket ordinary interconnects.

Further energy savings come from the way logic is done inside the superconducting computer. Instead of the transistor, the basic element in superconducting logic is the Josephson-junction.

A Josephson junction is a sandwich—a thin slice of insulating material squeezed between two superconductors. Connect the two superconductors, and you have yourself a Josephson-junction loop.

Under normal conditions, the insulating “meat” in the sandwich is so thin that it does not deter a supercurrent—the whole sandwich just acts as a superconductor. However, if you ramp up the current past a threshold known as a critical current, the superconducting “bread slices” around the insulator get briefly knocked out of their superconducting state. In this transition period, the junction emits a tiny voltage pulse, lasting just a picosecond and dissipating just 2 x 10 ^-20 joules, a hundred-billionth of what it takes to write a single bit of information into conventional flash memory.

A single flux quantum develops in a Josephson-junction loop via a three-step process. First, a current just above the critical value is passed through the junction. The junction then emits a single-flux-quantum voltage pulse. The voltage pulse passes through the inductor, creating a persistent current in the loop. A Josephson junction is indicated by an x on circuit diagrams. Chris Philpot

The key is that, due to a phenomenon called magnetic flux quantization in the superconducting loop, this pulse is always exactly the same. It is known as a “single flux quantum” (SFQ) of magnetic flux, and it is fixed to have a value of 2.07 millivolt-picoseconds. Put an inductor inside the Josephson-junction loop, and the voltage pulse drives a current. Since the loop is superconducting, this current will continue going around the loop indefinitely, without using any further energy.

Logical operations inside the superconducting computer are made by manipulating these tiny, quantized voltage pulses. A Josephson-junction loop with an SFQ’s worth of persistent current acts as a logical 1, while a current-free loop is a logical 0.

To store information, the Josephson-junction-based version of SRAM in CPU cache, also uses single flux quanta. To store one bit, two Josephson-junction loops need to be placed next to each other. An SFQ with a persistent current in the left-hand loop is a memory element storing a logical 0, whereas no current in the left but a current in the right loop is a logical 1.

Designing a superconductor-based data center required full-stack innovation. Imec’s board design contains three main elements: the input and output, leading data to the room temperature world, the conventional DRAM, stacked high and cooled to 77 kelvins, and the superconducting processing units, also stacked, and cooled to 4 K. Inside the superconducting processing unit, basic logic and memory elements are laid out to perform computations. A magnification of the chip shows the basic building blocks: For logic, a Josephson-junction loop without a persistent current indicates a logical 0, while a loop with one single flux quantum’s worth of current represents a logical 1. For memory, two Josephson junction loops are connected together. An SFQ’s worth of persistent current in the left loop is a memory 0, and a current in the right loop is a memory 1. Chris Philpot

Progress Through Full-Stack Development

To go from a lab curiosity to a chip prototype ready for fabrication, we had to innovate the full stack of hardware. This came in three main layers: engineering the basic materials used, circuit development, and architectural design. The three layers had to go together—a new set of materials requires new circuit designs, and new circuit designs require novel architectures to incorporate them. Codevelopment across all three stages, with a strict adherence to CMOS manufacturing capabilities, was the key to success.

At the materials level, we had to step away from the previous lab-favorite superconducting material: niobium. While niobium is easy to model and behaves very well under predictable lab conditions, it is very difficult to scale down. Niobium is sensitive to both process temperature and its surrounding materials, so it is not compatible with standard CMOS processing. Therefore, we switched to the related compound niobium titanium nitride for our basic superconducting material. Niobium titanium nitride can withstand temperatures used in CMOS fabrication without losing its superconducting capabilities, and it reacts much less with its surrounding layers, making it a much more practical choice.

The basic building block of superconducting logic and memory is the Josephson junction. At Imec, these junctions have been manufactured using a new set of materials, allowing the team to scale down the technology without losing functionality. Here, a tunneling electron microscope image shows a Josephson junction made with alpha-silicon insulator sandwiched between niobium titanium nitride superconductors, achieving a critical dimension of 210 nanometers. Imec

Additionally, we employed a new material for the meat layer of the Josephson-junction sandwich—amorphous, or alpha, silicon. Conventional Josephson-junction materials, most notably aluminum oxide, didn’t scale down well. Aluminum was used because it “wets” the niobium, smoothing the surface, and the oxide was grown in a well-controlled manner. However, to get to the ultrahigh densities that we are targeting, we would have to make the oxide too thin to be practically manufacturable. Alpha silicon, in contrast, allowed us to use a much thicker barrier for the same critical current.

We also had to devise a new way to power the Josephson junctions that would scale down to the size of a chip. Previously, lab-based superconducting computers used transformers to deliver current to their circuit elements. However, having a bulky transformer near each circuit element is unworkable. Instead, we designed a way to deliver power to all the elements on the chip at once by creating a resonant circuit, with specialized capacitors interspersed throughout the chip.

At the circuit level, we had to redesign the entire logic and memory structure to take advantage of the new materials’ capabilities. We designed a novel logic architecture that we call pulse-conserving logic. The key requirement for pulse-conserving logic is that the elements have as many inputs as outputs and that the total number of single flux quanta is conserved. The logic is performed by routing the SFQs through a combination of Josephson-junction loops and inductors to the appropriate outputs, resulting in logical ORs and ANDs. To complement the logic architecture, we also redesigned a compatible Josephson-junction-based SRAM.

Lastly, we had to make architectural innovations to take full advantage of the novel materials and circuit designs. Among these was cooling conventional silicon DRAM down to 77 kelvins and designing a glass bridge between the 77-K section and the main superconducting section. The bridge houses thin wires that allow communication without thermal mixing. We also came up with a way of stacking chips on top of each other and are developing vertical superconducting interconnects to link between circuit boards.

A Data Center the Size of a Shoebox

The result is a superconductor-based chip design that’s optimized for AI processing. A zoom in on one of its boards reveals many similarities with a typical 3D CMOS system-on-chip. The board is populated by computational chips: We call it a superconductor processing unit (SPU), with embedded superconducting SRAM, DRAM memory stacks, and switches, all interconnected on silicon interposer or on glass-bridge advanced packaging technologies.

But there are also some striking differences. First, most of the chip is to be submerged in liquid helium for cooling to a mere 4 K. This includes the SPUs and SRAM, which depend on superconducting logic rather than CMOS, and are housed on an interposer board. Next, there is a glass bridge to a warmer area, a balmy 77 K that hosts the DRAM. The DRAM technology is not superconducting, but conventional silicon cooled down from room temperature, making it more efficient. From there, bespoke connectors lead data to and from the room-temperature world.

Davide Comai

Moore’s law relies on fitting progressively more computing resources into the same space. As scaling down transistors gets more and more difficult, the semiconductor industry is turning toward 3D stacking of chips to keep up the density gains. In classical CMOS-based technology, it is very challenging to stack computational chips on top of each other because of the large amount of power, and therefore heat, that is dissipated within the chips. In superconducting technology, the little power that is dissipated is easily removed by the liquid helium. Logic chips can be directly stacked using advanced 3D integration technologies resulting in shorter and faster connections between the chips, and a smaller footprint.

It is also straightforward to stack multiple boards of 3D superconducting chips on top of each other, leaving only a small space between them. We modeled a stack of 100 such boards, all operating within the same cooling environment and contained in a 20- by 20- by 12-centimeter volume, roughly the size of a shoebox. We calculated that this stack can perform 20 exaflops (in BF16 number format), 20 times the capacity of the largest supercomputer today. What’s more, the system promises to consume only 500 kilowatts of total power. This translates to energy efficiency one hundred times as high as the most efficient supercomputer today.

So far, we’ve scaled down Josephson junctions and interconnect dimensions over three succeeding generations. Going forward, Imec’s road map includes tackling 3D superconducting chip-integration and cooling technologies. For the first generation, the road map envisions the stacking of about 100 boards to obtain the target performance of 20 exaflops. Gradually, more and more logic chips will be stacked, and the number of boards will be reduced. This will further increase performance while reducing complexity and cost.

The Superconducting Vision

We don’t envision that superconducting digital technology will replace conventional CMOS computing, but we do expect it to complement CMOS for specific applications and fuel innovations in new ones. For one, this technology would integrate seamlessly with quantum computers that are also built upon superconducting technology. Perhaps more significantly, we believe it will support the growth in AI and machine learning processing and help provide cloud-based training of big AI models in a much more sustainable way than is currently possible.

In addition, with this technology we can engineer data centers with much smaller footprints. Drastically smaller data centers can be placed close to their target applications, rather than being in some far-off football-stadium-size facility.

Such transformative server technology is a dream for scientists. It opens doors to online training of AI models on real data that are part of an actively changing environment. Take potential robotic farms as an example. Today, training these would be a challenging task, where the required processing capabilities are available only in far-away, power-hungry data centers. With compact, nearby data centers, the data could be processed at once, allowing an AI to learn from current conditions on the farm

Similarly, these miniature data centers can be interspersed in energy grids, learning right away at each node and distributing electricity more efficiently throughout the world. Imagine smart cities, mobile health care systems, manufacturing, farming, and more, all benefiting from instant feedback from adjacent AI learners, optimizing and improving decision making in real time.

This article appears in the June 2024 print issue as “A Data Center in a Shoebox.”

Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.

But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.

“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”

With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.

Beyond silicon

Silicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.

Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.

In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.

But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.

“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”

“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.

“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.

This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”

According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”

Measuring makes the difference

With Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.

Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.

“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.

“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”

“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”

The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”

Photovoltaics is just the start

The company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”

Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.

“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”

That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO₂ [carbon dioxide] per year in the not-too-distant future.”

The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.”

Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.

But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.

“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”

With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.

Beyond silicon

Silicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.

Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.

In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.

But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.

“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”

“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.

“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.

This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”

According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”

Measuring makes the difference

With Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.

Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.

“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.

“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”

“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”

The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”

Photovoltaics is just the start

The company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”

Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.

“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”

That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO₂ [carbon dioxide] per year in the not-too-distant future.”

The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.”

American federalism is struggling. Federal rules are an overwhelming presence in every state government, and some states, due to their size or other leverage, can impose their own policies on much or all of the country. The problem has been made clearer by an under-the-radar plan to phase out diesel locomotives in California. If the federal government provides the state with a helping hand, it would bring nationwide repercussions for a vital, overlooked industry.

Various industry and advocacy groups are lining up against California's costly measure, calling on the U.S. Environmental Protection Agency (EPA) to deny a waiver needed to fully implement it. In the past month, more than 30 leading conservative organizations and individuals, hundreds of state and local chambers of commerce, and the U.S. agricultural sector have pleaded with the EPA to help stop this piece of extremism from escaping one coastal state.

Railroads may not be something most Americans, whose attention is on their own cars and roads, think about often. But rail is the most basic infrastructure of interstate commerce, accounting for around 40 percent of long-distance ton-miles. It's also fairly clean, accounting for less than 1 percent of total U.S. emissions. Private companies, like Union Pacific in the West or CSX in the East, pay for their infrastructure and equipment. These facts haven't stopped the regulatory power grab.

Most importantly, the California Air Resources Board (CARB) regulation would have all freight trains operate in zero-emission configuration by 2035. At the end of the decade, the state is mandating the retirement of diesel locomotives 23 years or older, despite typically useful lives of over 40 years. Starting in 2030, new passenger locomotives must operate with zero emissions, with new engines for long-haul freight trains following by 2035. It limits locomotive idling and increases reporting requirements.

Given the interstate nature of railway operations, California needs the EPA to grant a waiver. If the agency agrees, the policy will inevitably affect the entire continental United States.

The kicker is that no technology exists today to enable railroads to comply with California's diktat, rendering the whole exercise fanciful at best.

The Wall Street Journal's editorial board explained last November that while Wabtec Corp. has introduced a pioneering advance in rail technology with the launch of the world's first battery-powered locomotive, the dream of a freight train fully powered by batteries remains elusive. The challenges of substituting diesel with batteries—primarily due to batteries' substantial weight and volume—make it an impractical solution for long-haul trains. Additionally, the risk of battery overheating and potential explosions, which can emit harmful gases, is a significant safety concern. As the editorial noted, "Even if the technology for zero-emission locomotives eventually arrives, railroads will have to test them over many years to guarantee their safety."

The cost-benefit analysis is woefully unfavorable to the forced displacement of diesel locomotives. To "help" the transition, beginning in 2026, CARB will force all railroads operating in California to deposit dollars into an escrow account managed by the state and frozen for the explicit pursuit of the green agenda. For large railroads, this figure will be a staggering $1.6 billion per year, whereas some smaller railroads will pay up to $5 million.

Many of these smaller companies have signaled that they will simply go out of business. For the large railroads, the requirement will lock up about 20 percent of annual spending, money typically used for maintenance and safety improvements.

Transportation is the largest source of U.S. emissions, yet railroads' contribution amounts to not much more than a rounding error. The industry cites its efficiency improvements over time, allowing railroads today to move a ton of freight more than 500 miles on a single gallon of diesel. Its expensive machines, which last between 30 to 50 years and are retrofitted throughout their life cycles, are about 75 percent more efficient than long-haul trucks that carry a comparative amount of freight.

As Patricia Patnode of the Competitive Enterprise Institute, which signed the aforementioned letter to the EPA, recently remarked, "Rather than abolish diesel trains, CARB should stand in awe of these marvels of energy-efficient transportation."

President Joe Biden talks a lot about trains, but his actions since taking office have consistently punished the private companies we should value far more than state-supported Amtrak. In this case, EPA Administrator Michael Regan and the White House need not think too hard. They should wait for reality to catch up before imposing on the rest of us one state's demands and ambitions.

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