The Large Hadron Collider has transformed our understanding of physics since it began operating in 2008, enabling researchers to investigate the fundamental building blocks of the universe. Some 100 meters below the border between France and Switzerland, particles accelerate along the LHC’s 27-kilometer circumference, nearly reaching the speed of light before smashing together.

The LHC is often described as the biggest machine ever built. And while the physicists who carry out experiments at the facility tend to garner most of the attention, it takes hundreds of engineers and technicians to keep the LHC running. One such engineer is Irene Degl’Innocenti, who works in digital electronics at the European Organization for Nuclear Research (CERN), which operates the LHC. As a member of CERN’s beam instrumentation group, Degl’Innocenti creates custom electronics that measure the position of the particle beams as they travel.

Irene Degl’Innocenti

Employer:

CERN

Occupation:

Digital electronics engineer

Education:

Bachelor’s and master’s degrees in electrical engineering; Ph.D. in electrical, electronics, and communications engineering, University of Pisa, in Italy

“It’s a huge machine that does very challenging things, so the amount of expertise needed is vast,” Degl’Innocenti says.

The electronics she works on make up only a tiny part of the overall operation, something Degl’Innocenti is keenly aware of when she descends into the LHC’s cavernous tunnels to install or test her equipment. But she gets great satisfaction from working on such an important endeavor.

“You’re part of something that is very huge,” she says. “You feel part of this big community trying to understand what is actually going on in the universe, and that is very fascinating.”

Opportunities to Work in High-energy Physics

Growing up in Italy, Degl’Innocenti wanted to be a novelist. Throughout high school she leaned toward the humanities, but she had a natural affinity for math, thanks in part to her mother, who is a science teacher.

“I’m a very analytical person, and that has always been part of my mind-set, but I just didn’t find math charming when I was little,” Degl’Innocenti says. “It took a while to realize the opportunities it could open up.”

She started exploring electronics around age 17 because it seemed like the most direct way to translate her logical, mathematical way of thinking into a career. In 2011, she enrolled in the University of Pisa, in Italy, earning a bachelor’s degree in electrical engineering in 2014 and staying on to earn a master’s degree in the same subject.

At the time, Degl’Innocenti had no idea there were opportunities for engineers to work in high-energy physics. But she learned that a fellow student had attended a summer internship at Fermilab, the participle physics and accelerator laboratory in Batavia, Ill. So she applied for and won an internship there in 2015. Since Fermilab and CERN closely collaborate, she was able to help design a data-processing board for LHC’s Compact Muon Solenoid experiment.

Next she looked for an internship closer to home and discovered CERN’s technical student program, which allows students to work on a project over the course of a year. Working in the beam-instrumentation group, Degl’Innocenti designed a digital-acquisition system that became the basis for her master’s thesis.

Measuring the Position of Particle Beams

After receiving her master’s in 2017, Degl’Innocenti went on to pursue a Ph.D., also at the University of Pisa. She conducted her research at CERN’s beam-position section, which builds equipment to measure the position of particle beams within CERN’s accelerator complex. The LHC has roughly 1,000 monitors spaced around the accelerator ring. Each monitor typically consists of two pairs of sensors positioned on opposite sides of the accelerator pipe, and it is possible to measure the beam’s horizontal and vertical positions by comparing the strength of the signal at each sensor.

The underlying concept is simple, Degl’Innocenti says, but these measurements must be precise. Bunches of particles pass through the monitors every 25 nanoseconds, and their position must be tracked to within 50 micrometers.

“We start developing a system years in advance, and then it has to work for a couple of decades.”

Most of the signal processing is normally done in analog, but during her Ph.D., she focused on shifting as much of this work as possible to the digital domain because analog circuits are finicky, she says. They need to be precisely calibrated, and their accuracy tends to drift over time or when temperatures fluctuate.

“It’s complex to maintain,” she says. “It becomes particularly tricky when you have 1,000 monitors, and they are located in an accelerator 100 meters underground.”

Information is lost when analog is converted to digital, however, so Degl’Innocenti analyzed the performance of the latest analog-to-digital converters (ADCs) and investigated their effect on position measurements.

Designing Beam-Monitor Electronics

After completing her Ph.D. in electrical, electronics, and communications engineering in 2021, Degl’Innocenti joined CERN as a senior postdoctoral fellow. Two years later, she became a full-time employee there, applying the results of her research to developing new hardware. She’s currently designing a new beam-position monitor for the High-Luminosity upgrade to the LHC, expected to be completed in 2028. This new system will likely use a system-on-chip to house most of the electronics, including several ADCs and a field-programmable gate array (FPGA) that Degl’Innocenti will program to run a new digital signal-processing algorithm.

She’s part of a team of just 15 who handle design, implementation, and ongoing maintenance of CERN’s beam-position monitors. So she works closely with the engineers who design sensors and software for those instruments and the physicists who operate the accelerator and set the instruments’ requirements.

“We start developing a system years in advance, and then it has to work for a couple of decades,” Degl’Innocenti says.

Opportunities in High-Energy Physics

High-energy physics has a variety of interesting opportunities for engineers, Degl’Innocenti says, including high-precision electronics, vacuum systems, and cryogenics.

“The machines are very large and very complex, but we are looking at very small things,” she says. “There are a lot of big numbers involved both at the large scale and also when it comes to precision on the small scale.”

FPGA design skills are in high demand at all kinds of research facilities, and embedded systems are also becoming more important, Degl’Innocenti says. The key is keeping an open mind about where to apply your engineering knowledge, she says. She never thought there would be opportunities for people with her skill set at CERN.

“Always check what technologies are being used,” she advises. “Don’t limit yourself by assuming that working somewhere would not be possible.”

This article appears in the August 2024 print issue as “Irene Degl’Innocenti.”

When it comes to motorsports, the need for speed isn’t only on the racetrack. Engineers who support race teams also need to work at a breakneck pace to fix problems, and that’s something Aakhilesh Singhania relishes.

Singhania is a senior applications engineer at Bosch Engineering, in Novi, Mich. He develops and supports electronic control systems for hybrid race cars, which feature combustion engines and battery-powered electric motors.

Aakhilesh Singhania

Employer:

Bosch Engineering

Occupation:

Senior applications engineer

Education:

Bachelor’s degree in mechanical engineering, Manipal Institute of Technology, India; master’s degree in automotive engineering, University of Michigan, Ann Arbor

His vehicles compete in two iconic endurance races: the Rolex 24 at Daytona in Daytona Beach, Fla., and the 24 Hours of Le Mans in France. He splits his time between refining the underlying technology and providing trackside support on competition day. Given the relentless pace of the racing calendar and the intense time pressure when cars are on the track, the job is high octane. But Singhania says he wouldn’t have it any other way.

“I’ve done jobs where the work gets repetitive and mundane,” he says. “Here, I’m constantly challenged. Every second counts, and you have to be very quick at making decisions.”

An Early Interest in Motorsports

Growing up in Kolkata, India, Singhania picked up a fascination with automobiles from his father, a car enthusiast.

In 2010, when Singhania began his mechanical engineering studies at India’s Manipal Institute of Technology, he got involved in the Formula Student program, an international engineering competition that challenges teams of university students to design, build, and drive a small race car. The cars typically weigh less than 250 kilograms and can have an engine no larger than 710 cubic centimeters.

“It really hooked me,” he says. “I devoted a lot of my spare time to the program, and the experience really motivated me to dive further into motorsports.”

One incident in particular shaped Singhania’s career trajectory. In 2013, he was leading Manipal’s Formula Student team and was one of the drivers for a competition in Germany. When he tried to start the vehicle, smoke poured out of the battery, and the team had to pull out of the race.

“I asked myself what I could have done differently,” he says. “It was my lack of knowledge of the electrical system of the car that was the problem.” So, he decided to get more experience and education.

Learning About Automotive Electronics

After graduating in 2014, Singhania began working on engine development for Indian car manufacturer Tata Motors in Pune. In 2016, determined to fill the gaps in his knowledge about automotive electronics, he left India to begin a master’s degree program in automotive engineering at the University of Michigan in Ann Arbor.

He took courses in battery management, hybrid controls, and control-system theory, parlaying this background into an internship with Bosch in 2017. After graduation in 2018, he joined Bosch full-time as a calibration engineer, developing technology for hybrid and electric vehicles.

Transitioning into motorsports required perseverance, Singhania says. He became friendly with the Bosch team that worked on electronics for race cars. Then in 2020 he got his big break.

That year, the U.S.-based International Motor Sports Association and the France-based Automobile Club de l’Ouest created standardized rules to allow the same hybrid race cars to compete in both the Sportscar Championship in North America, host of the famous Daytona race, and the global World Endurance Championship, host of Le Mans.

The Bosch motorsports team began preparing a proposal to provide the standardized hybrid system. Singhania, whose job already included creating simulations of how vehicles could be electrified, volunteered to help.

“I’m constantly challenged. Every second counts, and you have to be very quick at making decisions.”

The competition organizers selected Bosch as lead developer of the hybrid system that would be provided to all teams. Bosch engineers would also be required to test the hardware they supplied to each team to ensure none had an advantage.

“The performance of all our parts in all the cars has to fall within 1 percent of each other,” Singhania says.

After Bosch won the contract, Singhania officially became a motorsports calibration engineer, responsible for tweaking the software to fit the idiosyncrasies of each vehicle.

In 2022 he stepped up to his current role: developing software for the hybrid control unit (HCU), which is essentially the brains of the vehicle. The HCU helps coordinate all of the different subsystems such as the engine, battery, and electric motor and is responsible for balancing power requirements among these different components to maximize performance and lifetime.

Bosch’s engineers also designed software known as an equity model, which runs on the HCU. It is based on historical data collected from the operation of the hybrid systems’ various components, and controls their performance in real time to ensure all the teams’ hardware operates at the same level.

In addition, Singhania creates simulations of the race cars, which are used to better understand how the different components interact and how altering their configuration would affect performance.

Troubleshooting Problems on Race Day

Technology development is only part of Singhania’s job. On race days, he works as a support engineer, helping troubleshoot problems with the hybrid system as they crop up. Singhania and his colleagues monitor each team’s hardware using computers on Bosch’s race-day trailer, a mobile nerve center hardwired to the organizers’ control center on the race track.

“We are continuously looking at all the telemetry data coming from the hybrid system and analyzing [the system’s] health and performance,” he says.

If the Bosch engineers spot an issue or a team notifies them of a problem, they rush to the pit stall to retrieve a USB stick from the vehicle, which contains detailed data to help them diagnose and fix the issue.

After the race, the Bosch engineers analyze the telemetry data to identify ways to boost the standardized hybrid system’s performance for all the teams. In motorsports, where the difference between winning and losing can come down to fractions of a second, that kind of continual improvement is crucial.

Customers “put lots of money into this program, and they are there to win,” Singhania says.

Breaking Into Motorsports Engineering

Many engineers dream about working in the fast-paced and exciting world of motorsports, but it’s not easy breaking in. The biggest lesson Singhania learned is that if you don’t ask, you don’t get invited.

“Keep pursuing them because nobody’s going to come to you with an offer,” he says. “You have to keep talking to people and be ready when the opportunity presents itself.”

Demonstrating that you have experience contributing to challenging projects is a big help. Many of the engineers Bosch hires have been involved in Formula Student or similar automotive-engineering programs, such as the EcoCAR EV Challenge, says Singhania.

The job isn’t for everyone, though, he says. It’s demanding and requires a lot of travel and working on weekends during race season. But if you thrive under pressure and have a knack for problem solving, there are few more exciting careers.

Arthur Erickson discovered drones during his first year at college studying aerospace engineering. He immediately thought the sky was the limit for how the machines could be used, but it took years of hard work and some nimble decisions to turn that enthusiasm into a successful startup.

Today, Erickson is the CEO of Houston-based Hylio, a company that builds crop-spraying drones for farmers. Launched in 2015, the company has its own factory and employs more than 40 people.

Arthur Erickson

Occupation:

Aerospace engineer and founder, Hylio

Location:

Houston

Education:

Bachelor’s degree in aerospace, specializing in aeronautics, from the University of Texas at Austin

Erickson founded Hylio with classmates while they were attending the University of Texas at Austin. They were eager to quit college and launch their business, which he admits was a little presumptuous.

“We were like, ‘Screw all the school stuff—drones are the future,’” Erickson says. “I already thought I had all the requisite technical skills and had learned enough after six months of school, which obviously was arrogant.”

His parents convinced him to finish college, but Erickson and the other cofounders spent all their spare time building a multipurpose drone from off-the-shelf components and parts they made using their university’s 3D printers and laser cutters.

By the time he graduated in 2017 with a bachelor’s degree in aerospace, specializing in aeronautics, the group’s prototype was complete, and they began hunting for customers. The next three years were a wild ride of testing their drones in Costa Rica and other countries across Central America.

A grocery delivery service

A promotional video about the company that Erickson posted on Instagram led to the first customer, the now-defunct Costa Rican food and grocery delivery startup GoPato. The company wanted to use the drones to make deliveries in the capital, San José, but rather than purchase the machines, GoPato offered to pay for the founders’ meals and lodging and give them a percentage of delivery fees collected.

For the next nine months, Hylio’s team spent their days sending their drones on deliveries and their nights troubleshooting problems in a makeshift workshop in their shared living room.

“We had a lot of sleepless nights,” Erickson says. “It was a trial by fire, and we learned a lot.”

One lesson was the need to build in redundant pieces of key hardware, particularly the GPS unit. “When you have a drone crash in the middle of a Costa Rican suburb, the importance of redundancy really hits home,” Erickson says.

“Drones are great for just learning, iterating, crashing things, and then rebuilding them.”

The small cut of delivery fees Hylio received wasn’t covering costs, Erickson says, so eventually the founders parted ways with GoPato. Meanwhile, they had been looking for new business opportunities in Costa Rica. They learned from local farmers that the terrain was too rugged for tractors, so most sprayed crops by hand. This was both grueling and hazardous because it brought the farmers into close proximity to the pesticides.

The Hylio team realized its drones could do this type of work faster and more safely. They designed a spray system and made some software tweaks, and by 2018 the company began offering crop-spraying services, Erickson says. The company expanded its business to El Salvador, Guatemala, and Honduras, starting with just a pair of drones but eventually operating three spraying teams of four drones each.

The work was tough, Erickson says, but the experience helped the team refine their technology, working out which sensors operated best in the alternately dusty and moist conditions found on farms. Even more important, by the end of 2019 they were finally turning a profit.

Drones are cheaper than tractors

In hindsight, agriculture was an obvious market, Erickson says, even in the United States, where spraying with herbicides, pesticides, and fertilizers is typically done using large tractors. These tractors can cost up to half a million dollars to purchase and about US $7 a hectare to operate.

A pair of Hylio’s drones cost a fifth of that, Erickson says, and operating them costs about a quarter of the price. The company’s drones also fly autonomously; an operator simply marks GPS waypoints on a map to program the drone where to spray and then sits back and lets it do the job. In this way, one person can oversee multiple drones working at once, covering more fields than a single tractor could.

Arthur Erickson inspects the company’s largest spray drone, the AG-272. It can cover thousands of hectares per day.Hylio

Convincing farmers to use drones instead of tractors was tough, Erickson says. Farmers tend to be conservative and are wary of technology companies that promise too much.

“Farmers are used to people coming around every few years with some newfangled idea, like a laser that’s going to kill all their weeds or some miracle chemical,” he says.

In 2020, Hylio opened a factory in Houston and started selling drones to American farmers. The first time Hylio exhibited its machines at an agricultural trade show, Erickson says, a customer purchased one on the spot.

“It was pretty exciting,” he says. “It was a really good feeling to find out that our product was polished enough, and the pitch was attractive enough, to immediately get customers.”

Today, selling farmers on the benefits of drones is a big part of Erickson’s job. But he’s still involved in product development, and his daily meetings with the sales team have become an invaluable source of customer feedback. “They inform a lot of the features that we add to the products,” he says.

He’s currently leading development of a new type of drone—a scout—designed to quickly inspect fields for pest infestations or poor growth or to assess crop yields. But these days his job is more about managing his team of engineers than about doing hands-on engineering himself. “I’m more of a translator between the engineers and the market needs,” he says.

Focus on users’ needs

Erickson advises other founders of startups not to get too caught up in the excitement of building cutting-edge technology, because you can lose sight of what the user actually needs.

“I’ve become a big proponent of not trying to outsmart the customers,” he says. “They tell us what their pain points are and what they want to see in the product. Don’t overengineer it. Always check with the end users that what you’re building is going to be useful.”

Working with drones forces you to become a generalist, Erickson says. You need a basic understanding of structural mechanics and aerodynamics to build something airworthy. But you also need to be comfortable working with sensors, communications systems, and power electronics, not to mention the software used to control and navigate the vehicles.

Erickson advises students who want to get into the field to take courses in mechatronics, which provide a good blend of mechanical and electrical engineering. Deep knowledge of the individual parts is generally not as important as understanding how to fit all the pieces together to create a system that works well as a whole.

And if you’re a tinkerer like he is, Erickson says, there are few better ways to hone your engineering skills than building a drone. “It’s a cheap, fast way to get something up in the air,” he says. “They’re great for just learning, iterating, crashing things, and then rebuilding them.”

This article appears in the June 2024 print issue as “Careers: Arthur Erickson.”

Making breakthroughs in artificial intelligence these days requires huge amounts of computing power. In January, Meta CEO Mark Zuckerberg announced that by the end of this year, the company will have installed 350,000 Nvidia GPUs—the specialized computer chips used to train AI models—to power its AI research.

As a data-center network engineer with Meta’s network infrastructure team, Susana Contrera is playing a leading role in this unprecedented technology rollout. Her job is about “bringing designs to life,” she says. Contrera and her colleagues take high-level plans for the company’s AI infrastructure and turn those blueprints into reality by working out how to wire, power, cool, and house the GPUs in the company’s data centers.

Susana Contrera

Employer:

Meta

Occupation:

Data-center network engineer

Education:

Bachelor’s degree in telecommunications engineering, Andrés Bello Catholic University in Caracas, Venezuela

Contrera, who now works remotely from Florida, has been at Meta since 2013, spending most of that time helping to build the computer systems that support its social media networks, including Facebook and Instagram. But she says that AI infrastructure has become a growing priority, particularly in the past two years, and represents an entirely new challenge. Not only is Meta building some of the world’s first AI supercomputers, it is racing against other companies like Google and OpenAI to be the first to make breakthroughs.

“We are sitting right at the forefront of the technology,” Contrera says. “It’s super challenging, but it’s also super interesting, because you see all these people pushing the boundaries of what we thought we could do.”

Cisco Certification Opened Doors

Growing up in Caracas, Venezuela, Contrera says her first introduction to technology came from playing video games with her older brother. But she decided to pursue a career in engineering because of her parents, who were small-business owners.

“They were always telling me how technology was going to be a game changer in the future, and how a career in engineering could open many doors,” she says.

She enrolled at Andrés Bello Catholic University in Caracas in 2001 to study telecommunications engineering. In her final year, she signed up for the training and certification program to become a Cisco Certified Network Associate. The program covered topics such as the fundamentals of networking and security, IP services, and automation and programmability.

The certificate opened the door to her first job in 2006—managing the computer network of a business-process outsourcing company, Atento, in Caracas.

“Getting your hands dirty can give you a lot of perspective.”

“It was a very large enterprise network that had just the right amount of complexity for a very small team,” she says. “That gave me a lot of freedom to put my knowledge into practice.”

At the time, Venezuela was going through a period of political unrest. Contrera says she didn’t see a future for herself in the country, so she decided to leave for Europe.

She enrolled in a master’s degree program in project management in 2009 at Spain’s Pontifical University of Salamanca, continuing to collect additional certifications through Cisco in her free time. In 2010, partway through the program, she left for a job as a support engineer at the Madrid-based law firm Ecija, which provides legal advice to technology, media, and telecommunications companies. Following that with a stint as a network engineer at Amazon’s facility in Dublin from 2011 to 2013, she then joined Meta and “the rest is history,” she says.

Starting From the Edge Network

Contrera first joined Meta as a network deployment engineer, helping build the company’s “edge” network. In this type of network design, user requests go out to small edge servers dotted around the world instead of to Meta’s main data centers. Edge systems can deal with requests faster and reduce the load on the company’s main computers.

After several years traveling around Europe setting up this infrastructure, she took a managerial position in 2016. But after a couple of years she decided to return to a hands-on role at the company.

“I missed the satisfaction that you get when you’re part of a project, and you can clearly see the impact of solving a complex technical problem,” she says.

Because of the rapid growth of Meta’s services, her work primarily involved scaling up the capacity of its data centers as quickly as possible and boosting the efficiency with which data flowed through the network. But the work she is doing today to build out Meta’s AI infrastructure presents very different challenges, she says.

Designing Data Centers for AI

Training Meta’s largest AI models involves coordinating computation over large numbers of GPUs split into clusters. These clusters are often housed in different facilities, often in distant cities. It’s crucial that messages passing back and forth have very low latency and are lossless—in other words, they move fast and don’t drop any information.

Building data centers that can meet these requirements first involves Meta’s network engineering team deciding what kind of hardware should be used and how it needs to be connected.

“They have to think about how those clusters look from a logical perspective,” Contrera says.

Then Contrera and other members of the network infrastructure team take this plan and figure out how to fit it into Meta’s existing data centers. They consider how much space the hardware needs, how much power and cooling it will require, and how to adapt the communications systems to support the additional data traffic it will generate. Crucially, this AI hardware sits in the same facilities as the rest of Meta’s computing hardware, so the engineers have to make sure it doesn’t take resources away from other important services.

“We help translate these ideas into the real world,” Contrera says. “And we have to make sure they fit not only today, but they also make sense for the long-term plans of how we are scaling our infrastructure.”

Working on a Transformative Technology

Planning for the future is particularly challenging when it comes to AI, Contrera says, because the field is moving so quickly.

“It’s not like there is a road map of how AI is going to look in the next five years,” she says. “So we sometimes have to adapt quickly to changes.”

With today’s heated competition among companies to be the first to make AI advances, there is a lot of pressure to get the AI computing infrastructure up and running. This makes the work much more demanding, she says, but it’s also energizing to see the entire company rallying around this goal.

While she sometimes gets lost in the day-to-day of the job, she loves working on a potentially transformative technology. “It’s pretty exciting to see the possibilities and to know that we are a tiny piece of that big puzzle,” she says.

Hands-on Data Center Experience

For those interested in becoming a network engineer, Contrera says the certification programs run by companies like Cisco are useful. But she says it’s also important not to focus just on simply ticking boxes or rushing through courses just to earn credentials. “Take your time to understand the topics because that’s where the value is,” she says.

It’s good to get some experience working in data centers on infrastructure deployment, she says, because “getting your hands dirty can give you a lot of perspective.” And increasingly, coding can be another useful skill to develop to complement more traditional network engineering capabilities.

Mainly, she says, just “enjoy the ride” because networking can be a truly fascinating topic once you delve in. “There’s this orchestra of protocols and different technologies playing together and interacting,” she says. “I think that’s beautiful.”

Working in an ice cream factory is a dream for anyone who enjoys the frozen dessert. For control systems engineer Patryk Borkowski, a job at the biggest ice cream company in the world is also a great way to put his automation expertise to use.

Patryk Borkowski

Employer:

Unilever, Colworth Science Park, in Sharnbrook, England

Occupation:

Control systems engineer

Education:

Bachelor’s degree in automation and robotics from the West Pomeranian University of Technology in Szczecin, Poland

Borkowski works at the Advanced Prototype and Engineering Centre of the multinational consumer goods company Unilever. Unilever’s corporate umbrella covers such ice cream brands as Ben & Jerry’s, Breyers, Good Humor, Magnum, and Walls.

Borkowski maintains and updates equipment at the innovation center’s pilot plant at Colworth Science Park in Sharnbrook, England. The company’s food scientists and engineers use this small-scale factory to experiment with new ice cream formulations and novel production methods.

The reality of the job might not exactly live up to an ice cream lover’s dream. For safety reasons, eating the product in the plant is prohibited.

“You can’t just put your mouth underneath the nozzle of an ice cream machine and fill your belly,” he says.

For an engineer, though, the complex chemistry and processing required to create ice cream products make for fascinating problem-solving. Much of Borkowski’s work involves improving the environmental impact of ice cream production by cutting waste and reducing the amount of energy needed to keep products frozen.

And he loves working on a product that puts a smile on the faces of customers. “Ice cream is a deeply indulgent and happy product,” he says. “We love working to deliver a superior taste and a superior way to experience ice cream.”

Ice Cream Innovation

Borkowski joined Unilever as a control systems engineer in 2021. While he’s not allowed to discuss many of the details of his research, he says one of the projects he has worked on is a modular manufacturing line that the company uses to develop new kinds of ice cream. The setup allows pieces of equipment such as sauce baths, nitrogen baths for quickly freezing layers, and chocolate deposition systems to be seamlessly switched in and out so that food scientists can experiment and create new products.

Ice cream is a fascinating product to work on for an engineer, Borkowski says, because it’s inherently unstable. “Ice cream doesn’t want to be frozen; it pretty much wants to be melted on the floor,” he says. “We’re trying to bend the chemistry to bind all the ingredients into a semistable mixture that gives you that great taste and feeling on the tongue.”

Making Production More Sustainable

Helping design new products is just one part of Borkowski’s job. Unilever is targeting sustainability across the company, so cutting waste and improving energy efficiency are key. He recently helped develop a testing rig to simulate freezer doors being repeatedly opened and closed in shops. This helped collect temperature data that was used to design new freezers that run at higher temperatures to save electricity.

In 2022, he was temporarily transferred to one of Unilever’s ice cream factories in Hellendoorn, Netherlands, to uncover inefficiencies in the production process. He built a system that collected and collated operational data from all the factory’s machines to identify the causes of stoppages and waste.

“There’s a deep pride in knowing the machines that we’ve programmed make something that people buy and enjoy.”

It wasn’t easy. Some of the machines were older and no longer supported by their manufacturers. Also, they ran legacy code written in Dutch—a language Borkowski doesn’t speak.

Borkowski ended up reverse-engineering the machines to figure out their operating systems, then reprogrammed them to communicate with the new data-collection system. Now the data-collection system can be easily adapted to work at any Unilever factory.

Discovering a Love for Technology

As a child growing up in Stargard, Poland, Borkowski says there was little to indicate that he would become an engineer. At school, he loved writing, drawing, and learning new languages. He imagined himself having a career in the creative industries.

But in the late 1990s, his parents got a second-hand computer and a modem. He quickly discovered online communities for technology enthusiasts and began learning about programming.

Because of his growing fascination with technology, at 16, Borkowski opted to attend a technical high school, pursuing a technical diploma in electronics and learning about components, soldering, and assembly language. In 2011, he enrolled at the West Pomeranian University of Technology in Szczecin, Poland, where he earned a bachelor’s degree in automation and robotics.

When he graduated in 2015, there were few opportunities in Poland to put his skills to use, so he moved to London. There, Borkowski initially worked odd jobs in warehouses and production facilities. After a brief stint as an electronic technician assembling ultrasonic scanners, he joined bakery company Brioche Pasquier in Milton Keynes, England, as an automation engineer.

This was an exciting move, Borkowski says, because he was finally doing control engineering, the discipline he’d always wanted to pursue. Part of his duties involved daily maintenance, but he also joined a team building new production lines from the ground up, linking together machinery such as mixers, industrial ovens, coolers, and packaging units. They programmed the machines so they all worked together seamlessly without human intervention.

When the COVID-19 pandemic struck, new projects went on hold and work slowed down, Borkowski says. There seemed to be little opportunity to advance his career at Brioche Pasquier, so he applied for the control systems job at Unilever.

“When I was briefed on the work, they told me it was all R&D and every project was different,” he says. “I thought that sounded like a challenge.”

The Importance of a Theoretical Foundation

Control engineers require a broad palette of skills in both electronics and programming, Borkowski says. Some of these can be learned on the job, he says, but a degree in subjects like automation or robotics provides an important theoretical foundation.

The biggest piece of advice he has for fledgling control engineers is to stay calm, which he admits can be difficult when a manager is pressuring you to quickly get a line back up to avoid production delays.

“Sometimes it’s better to step away and give yourself a few minutes to think before you do anything,” he says. Rushing can often result in mistakes that cause more problems in the long run.

While working in production can sometimes be stressful, “There’s a deep pride in knowing the machines that we’ve programmed make something that people buy and enjoy,” Borkowski says.

The dream of fusion power inched closer to reality in December 2022, when researchers at Lawrence Livermore National Laboratory (LLNL) revealed that a fusion reaction had produced more energy than what was required to kick-start it. According to new research, the momentary fusion feat required exquisite choreography and extensive preparations, whose high degree of difficulty reveals a long road ahead before anyone dares hope a practicable power source could be at hand.

The groundbreaking result was achieved at the California lab’s National Ignition Facility (NIF), which uses an array of 192 high-power lasers to blast tiny pellets of deuterium and tritium fuel in a process known as inertial confinement fusion. This causes the fuel to implode, smashing its atoms together and generating higher temperatures and pressures than are found at the center of the sun. The atoms then fuse together, releasing huge amounts of energy.

“It showed there’s nothing fundamentally limiting us from being able to harness fusion in the laboratory.” —Annie Kritcher, Lawrence Livermore National Laboratory

The facility has been running since 2011, and for a long time the amount of energy produced by these reactions was significantly less than the amount of laser energy pumped into the fuel. But on 5 December 2022, researchers at NIF announced that they had finally achieved breakeven by generating 1.5 times more energy than was required to start the fusion reaction.

A new paper published yesterday in Physical Review Letters confirms the team’s claims and details the complex engineering required to make it possible. While the results underscore the considerable work ahead, Annie Kritcher, a physicist at LLNL who led design of the experiment, says it still signals a major milestone in fusion science. “It showed there’s nothing fundamentally limiting us from being able to harness fusion in the laboratory,” she says.

While the experiment was characterized as a breakthrough, Kritcher says it was actually the result of painstaking incremental improvements to the facility’s equipment and processes. In particular, the team has spent years perfecting the design of the fuel pellet and the cylindrical gold container that houses it, known as a “hohlraum”.

Why is fusion so hard?

When lasers hit the outside of this capsule, their energy is converted into X-rays that then blast the fuel pellet, which consists of a diamond outer shell coated on the inside with deuterium and tritium fuel. It’s crucial that the hohlraum is as symmetrical as possible, says Kritcher, so it distributes X-rays evenly across the pellet. This ensures the fuel is compressed equally from all sides, allowing it to reach the temperatures and pressures required for fusion. “If you don’t do that, you can basically imagine your plasmas squirting out in one direction, and you can’t squeeze it and heat it enough,” she says.

The team has since carried out six more experiments—two that have generated roughly the same amount of energy as was put in and four that significantly exceeded it.

Carefully tailoring the laser beams is also important, Kritcher says, because laser light can scatter off the hohlraum, reducing efficiency and potentially damaging laser optics. In addition, as soon as the laser starts to hit the capsule, it starts giving off a plume of plasma that interferes with the beam. “It’s a race against time,” says Kritcher. “We’re trying to get the laser pulse in there before this happens, because then you can’t get the laser energy to go where you want it to go.”

The design process is slowgoing, because the facility is capable of carrying out only a few shots a year, limiting the team’s ability to iterate. And predicting how those changes will pan out ahead of time is challenging because of our poor understanding of the extreme physics at play. “We’re blasting a tiny target with the biggest laser in the world, and a whole lot of crap is flying all over the place,” says Kritcher. “And we’re trying to control that to very, very precise levels.”

Nonetheless, by analyzing the results of previous experiments and using computer modeling, the team was able to crack the problem. They worked out that using a slightly higher power laser coupled with a thicker diamond shell around the fuel pellet could overcome the destabilizing effects of imperfections on the pellet’s surface. Moreover, they found these modifications could also help confine the fusion reaction for long enough for it to become self-sustaining. The resulting experiment ended up producing 3.15 megajoules, considerably more than the 2.05 MJ produced by the lasers.

Since then, the team has carried out six more experiments—two that have generated roughly the same amount of energy as was put in and four that significantly exceeded it. Consistently achieving breakeven is a significant feat, says Kritcher. However, she adds that the significant variability in the amount of energy produced remains something the researchers need to address.

This kind of inconsistency is unsurprising, though, says Saskia Mordijck, an associate professor of physics at the College of William & Mary in Virginia. The amount of energy generated is strongly linked to how self-sustaining the reactions are, which can be impacted by very small changes in the setup, she says. She compares the challenge to landing on the moon—we know how to do it, but it’s such an enormous technical challenge that there’s no guarantee you’ll stick the landing.

Relatedly, researchers from the University of Rochester’s Laboratory for Laser Energetics today reported in the journal Nature Physics that they have developed an inertial confinement fusion system that’s one-hundredth the size of NIF’s. Their 28 kilojoule laser system, the team noted, can at least yield more fusion energy than what is contained in the central plasma—an accomplishment that’s on the road toward NIF’s success, but still a distance away. They’re calling what they’ve developed a “spark plug“ toward more energetic reactions.

Both NIF’s and LLE’s newly reported results represent steps along a development path—where in both cases that path remains long and challenging if inertial confinement fusion is to ever become more than a research curiosity, though.

Plenty of other obstacles remain than those noted above, too. Current calculations compare energy generated against the NIF laser’s output, but that brushes over the fact that the lasers draw more than 100 times the power from the grid than any fusion reaction yields. That means either energy gains or laser efficiency would need to improve by two orders of magnitude to break even in any practical sense. The NIF’s fuel pellets are also extremely expensive, says Kritcher, each one pricing in at an estimated $100,000. Then, producing a reasonable amount of power would mean dramatically increasing the frequency of NIF’s shots—a feat barely on the horizon for a reactor that requires months to load up the next nanosecond-long burst.

“Those are the biggest challenges,” Kritcher says. “But I think if we overcome those, it’s really not that hard at that point.”

UPDATE: 8 Feb. 2024: The story was corrected to attribute the final quote to Annie Kritcher, not Saskia Mordijck, as the story originally stated.
6 Feb. 2024 6 p.m. ET: The story was updated to include news of the University of Rochester’s Laboratory for Laser Energetics new research findings.