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SRAM security concerns are intensifying as a combination of new and existing techniques allow hackers to tap into data for longer periods of time after a device is powered down.

This is particularly alarming as the leading edge of design shifts from planar SoCs to heterogeneous systems in package, such as those used in AI or edge processing, where chiplets frequently have their own memory hierarchy. Until now, most cybersecurity concerns involving volatile memory have focused on DRAM, because it is often external and easier to attack. SRAM, in contrast, does not contain a component as obviously vulnerable as a heat-sensitive capacitor, and in the past it has been harder to pinpoint. But as SoCs are disaggregated and more features are added into devices, SRAM is becoming a much bigger security concern.

The attack scheme is well understood. Known as cold boot, it was first identified in 2008, and is essentially a variant of a side-channel attack. In a cold boot approach, an attacker dumps data from internal SRAM to an external device, and then restarts the system from the external device with some code modification. “Cold boot is primarily targeted at SRAM, with the two primary defenses being isolation and in-memory encryption,” said Vijay Seshadri, distinguished engineer at Cycuity.

Compared with network-based attacks, such as DRAM’s rowhammer, cold boot is relatively simple. It relies on physical proximity and a can of compressed air.

The vulnerability was first described by Edward Felton, director of Princeton University’s Center for Information Technology Policy, J. Alex Halderman, currently director of the Center for Computer Security & Society at the University of Michigan, and colleagues. The breakthrough in their research was based on the growing realization in the engineering research community that data does not vanish from memory the moment a device is turned off, which until then was a common assumption. Instead, data in both DRAM and SRAM has a brief “remanence.”[1]

Using a cold boot approach, data can be retrieved, especially if an attacker sprays the chip with compressed air, cooling it enough to slow the degradation of the data. As the researchers described their approach, “We obtained surface temperatures of approximately −50°C with a simple cooling technique — discharging inverted cans of ‘canned air’ duster spray directly onto the chips. At these temperatures, we typically found that fewer than 1% of bits decayed even after 10 minutes without power.”

Unfortunately, despite nearly 20 years of security research since the publication of the Halderman paper, the authors’ warning still holds true. “Though we discuss several strategies for mitigating these risks, we know of no simple remedy that would eliminate them.”

However unrealistic, there is one simple and obvious remedy to cold boot — never leave a device unattended. But given human behavior, it’s safer to assume that every device is vulnerable, from smart watches to servers, as well as automotive chips used for increasingly autonomous driving.

While the original research exclusively examined DRAM, within the last six years cold boot has proven to be one of the most serious vulnerabilities for SRAM. In 2018, researchers at Germany’s Technische Universität Darmstadt published a paper describing a cold boot attack method that is highly resistant to memory erasure techniques, and which can be used to manipulate the cryptographic keys produced by the SRAM physical unclonable function (PUF).

As with so many security issues, it’s been a cat-and-mouse game between remedies and counter-attacks. And because cold boot takes advantage of slowing down memory degradation, in 2022 Yang-Kyu Choi and colleagues at the Korea Advanced Institute of Science and Technology (KAIST), described a way to undo the slowdown with an ultra-fast data sanitization method that worked within 5 ns, using back bias to control the device parameters of CMOS.

Fig. 1: Asymmetric forward back-biasing scheme for permanent erasing. (a) All the data are reset to 1. (b) All the data are reset to 0. Whether all the data where reset to 1 or 0 is determined by the asymmetric forward back-biasing scheme. Source: KAIST/Creative Commons [2]

Their paper, as well as others, have inspired new approaches to combating cold boot attacks.

“To mitigate the risk of unauthorized access from unknown devices, main devices, or servers, check the authenticated code and unique identity of each accessing device,” said Jongsin Yun, memory technologist at Siemens EDA. “SRAM PUF is one of the ways to securely identify each device. SRAM is made of two inverters cross-coupled to each other. Although each inverter is designed to be the same device, normally one part of the inverter has a somewhat stronger NMOS than the other due to inherent random dopant fluctuation. During the initial power-on process, SRAM data will be either data 1 or 0, depending on which side has a stronger device. In other words, the initial data state of the SRAM array at the power on is decided by this unique random process variation and most of the bits maintain this property for life. One can use this unique pattern as a fingerprint of a device. The SRAM PUF data is reconstructed with other coded data to form a cryptographic key. SRAM PUF is a great way to anchor its secure data into hardware. Hackers may use a DFT circuit to access the memory. To avoid insecurely reading the SRAM information through DFT, the security-critical design makes DFT force delete the data as an initial process of TEST mode.”

However, there can be instances where data may be required to be kept in a non-volatile memory (NVM). “Data is considered insecure if the NVM is located outside of the device,” said Yun. “Therefore, secured data needs to be stored within the device with write protection. One-time programmable (OTP) memory or fuses are good storage options to prevent malicious attackers from tampering with the modified information. OTP memory and fuses are used to store cryptographic keys, authentication information, and other critical settings for operation within the device. It is useful for anti-rollback, which prevents hackers from exploiting old vulnerabilities that have been fixed in newer versions.”

Chiplet vulnerabilities
Chiplets also could present another vector for attack, due to their complexity and interconnections. “A chiplet has memory, so it’s going to be attacked,” said Cycuity’s Seshadri. “Chiplets, in general, are going to exacerbate the problem, rather than keeping it status quo, because you’re going to have one chiplet talking to another. Could an attack on one chiplet have a side effect on another? There need to be standards to address this. In fact, they’re coming into play already. A chiplet provider has to say, ‘Here’s what I’ve done for security. Here’s what needs to be done when interfacing with another chiplet.”

Yun notes there is a further physical vulnerability for those working with chiplets and SiPs. “When multiple chiplets are connected to form a SiP, we have to trust data coming from an external chip, which creates further complications. Verification of the chiplet’s authenticity becomes very important for SiPs, as there is a risk of malicious counterfeit chiplets being connected to the package for hacking purposes. Detection of such counterfeit chiplets is imperative.”

These precautions also apply when working with DRAM. In all situations, Seshardi said, thinking about security has to go beyond device-level protection. “The onus of protecting DRAM is not just on the DRAM designer or the memory designer,” he said. “It has to be secured by design principles when you are developing. In addition, you have to look at this holistically and do it at a system level. You must consider all the other things that communicate with DRAM or that are placed near DRAM. You must look at a holistic solution, all the way from software down to things like the memory controller and then finally, the DRAM itself.”

Encryption as a backup
Data itself always must be encrypted as second layer of protection against known and novel attacks, so an organization’s assets will still be protected even if someone breaks in via cold boot or another method.

“The first and primary method of preventing a cold boot attack is limiting physical access to the systems, or physically modifying the systems case or hardware preventing an attacker’s access,” said Jim Montgomery, market development director, semiconductor at TXOne Networks. “The most effective programmatic defense against an attack is to ensure encryption of memory using either a hardware- or software-based approach. Utilizing memory encryption will ensure that regardless of trying to dump the memory, or physically removing the memory, the encryption keys will remain secure.”

Montgomery also points out that TXOne is working with the Semiconductor Manufacturing Cybersecurity Consortium (SMCC) to develop common criteria based upon SEMI E187 and E188 standards to assist DM’s and OEM’s to implement secure procedures for systems security and integrity, including controlling the physical environment.

What kind and how much encryption will depend on use cases, said Jun Kawaguchi, global marketing executive for Winbond. “Encryption strength for a traffic signal controller is going to be different from encryption for nuclear plants or medical devices, critical applications where you need much higher levels,” he said. “There are different strengths and costs to it.”

Another problem, in the post-quantum era, is that encryption itself may be vulnerable. To defend against those possibilities, researchers are developing post-quantum encryption schemes. One way to stay a step ahead is homomorphic encryption [HE], which will find a role in data sharing, since computations can be performed on encrypted data without first having to decrypt it.

Homomorphic encryption could be in widespread use as soon as the next few years, according to Ronen Levy, senior manager for IBM’s Cloud Security & Privacy Technologies Department, and Omri Soceanu, AI Security Group manager at IBM.  However, there are still challenges to be overcome.

“There are three main inhibitors for widespread adoption of homomorphic encryption — performance, consumability, and standardization,” according to Levy. “The main inhibitor, by far, is performance. Homomorphic encryption comes with some latency and storage overheads. FHE hardware acceleration will be critical to solving these issues, as well as algorithmic and cryptographic solutions, but without the necessary expertise it can be quite challenging.”

An additional issue is that most consumers of HE technology, such as data scientists and application developers, do not possess deep cryptographic skills, HE solutions that are designed for cryptographers can be impractical. A few HE solutions require algorithmic and cryptographic expertise that inhibit adoption by those who lack these skills.

Finally, there is a lack of standardization. “Homomorphic encryption is in the process of being standardized,” said Soceanu. “But until it is fully standardized, large organizations may be hesitant to adopt a cryptographic solution that has not been approved by standardization bodies.”

Once these issues are resolved, they predicted widespread use as soon as the next few years. “Performance is already practical for a variety of use cases, and as hardware solutions for homomorphic encryption become a reality, more use cases would become practical,” said Levy. “Consumability is addressed by creating more solutions, making it easier and hopefully as frictionless as possible to move analytics to homomorphic encryption. Additionally, standardization efforts are already in progress.”

A new attack and an old problem
Unfortunately, security never will be as simple as making users more aware of their surroundings. Otherwise, cold boot could be completely eliminated as a threat. Instead, it’s essential to keep up with conference talks and the published literature, as graduate students keep probing SRAM for vulnerabilities, hopefully one step ahead of genuine attackers.

For example, SRAM-related cold boot attacks originally targeted discrete SRAM. The reason is that it’s far more complicated to attack on-chip SRAM, which is isolated from external probing and has minimal intrinsic capacitance. However, in 2022, Jubayer Mahmod, then a graduate student at Virginia Tech and his advisor, associate professor Matthew Hicks, demonstrated what they dubbed “Volt Boot,” a new method that could penetrate on-chip SRAM. According to their paper, “Volt Boot leverages asymmetrical power states (e.g., on vs. off) to force SRAM state retention across power cycles, eliminating the need for traditional cold boot attack enablers, such as low-temperature or intrinsic data retention time…Unlike other forms of SRAM data retention attacks, Volt Boot retrieves data with 100% accuracy — without any complex post-processing.”

Conclusion
While scientists and engineers continue to identify vulnerabilities and develop security solutions, decisions about how much security to include in a design is an economic one. Cost vs. risk is a complex formula that depends on the end application, the impact of a breach, and the likelihood that an attack will occur.

“It’s like insurance,” said Kawaguchi. “Security engineers and people like us who are trying to promote security solutions get frustrated because, similar to insurance pitches, people respond with skepticism. ‘Why would I need it? That problem has never happened before.’ Engineers have a hard time convincing their managers to spend that extra dollar on the costs because of this ‘it-never-happened-before’ attitude. In the end, there are compromises. Yet ultimately, it’s going to cost manufacturers a lot of money when suddenly there’s a deluge of demands to fix this situation right away.”

References

1. S. Skorobogatov, “Low temperature data remanence in static RAM”, Technical report UCAM-CL-TR-536, University of Cambridge Computer Laboratory, June 2002.
2. Han, SJ., Han, JK., Yun, GJ. et al. Ultra-fast data sanitization of SRAM by back-biasing to resist a cold boot attack. Sci Rep 12, 35 (2022). https://doi.org/10.1038/s41598-021-03994-2

The post SRAM Security Concerns Grow appeared first on Semiconductor Engineering.

SRAM security concerns are intensifying as a combination of new and existing techniques allow hackers to tap into data for longer periods of time after a device is powered down.

This is particularly alarming as the leading edge of design shifts from planar SoCs to heterogeneous systems in package, such as those used in AI or edge processing, where chiplets frequently have their own memory hierarchy. Until now, most cybersecurity concerns involving volatile memory have focused on DRAM, because it is often external and easier to attack. SRAM, in contrast, does not contain a component as obviously vulnerable as a heat-sensitive capacitor, and in the past it has been harder to pinpoint. But as SoCs are disaggregated and more features are added into devices, SRAM is becoming a much bigger security concern.

The attack scheme is well understood. Known as cold boot, it was first identified in 2008, and is essentially a variant of a side-channel attack. In a cold boot approach, an attacker dumps data from internal SRAM to an external device, and then restarts the system from the external device with some code modification. “Cold boot is primarily targeted at SRAM, with the two primary defenses being isolation and in-memory encryption,” said Vijay Seshadri, distinguished engineer at Cycuity.

Compared with network-based attacks, such as DRAM’s rowhammer, cold boot is relatively simple. It relies on physical proximity and a can of compressed air.

The vulnerability was first described by Edward Felton, director of Princeton University’s Center for Information Technology Policy, J. Alex Halderman, currently director of the Center for Computer Security & Society at the University of Michigan, and colleagues. The breakthrough in their research was based on the growing realization in the engineering research community that data does not vanish from memory the moment a device is turned off, which until then was a common assumption. Instead, data in both DRAM and SRAM has a brief “remanence.”[1]

Using a cold boot approach, data can be retrieved, especially if an attacker sprays the chip with compressed air, cooling it enough to slow the degradation of the data. As the researchers described their approach, “We obtained surface temperatures of approximately −50°C with a simple cooling technique — discharging inverted cans of ‘canned air’ duster spray directly onto the chips. At these temperatures, we typically found that fewer than 1% of bits decayed even after 10 minutes without power.”

Unfortunately, despite nearly 20 years of security research since the publication of the Halderman paper, the authors’ warning still holds true. “Though we discuss several strategies for mitigating these risks, we know of no simple remedy that would eliminate them.”

However unrealistic, there is one simple and obvious remedy to cold boot — never leave a device unattended. But given human behavior, it’s safer to assume that every device is vulnerable, from smart watches to servers, as well as automotive chips used for increasingly autonomous driving.

While the original research exclusively examined DRAM, within the last six years cold boot has proven to be one of the most serious vulnerabilities for SRAM. In 2018, researchers at Germany’s Technische Universität Darmstadt published a paper describing a cold boot attack method that is highly resistant to memory erasure techniques, and which can be used to manipulate the cryptographic keys produced by the SRAM physical unclonable function (PUF).

As with so many security issues, it’s been a cat-and-mouse game between remedies and counter-attacks. And because cold boot takes advantage of slowing down memory degradation, in 2022 Yang-Kyu Choi and colleagues at the Korea Advanced Institute of Science and Technology (KAIST), described a way to undo the slowdown with an ultra-fast data sanitization method that worked within 5 ns, using back bias to control the device parameters of CMOS.

Fig. 1: Asymmetric forward back-biasing scheme for permanent erasing. (a) All the data are reset to 1. (b) All the data are reset to 0. Whether all the data where reset to 1 or 0 is determined by the asymmetric forward back-biasing scheme. Source: KAIST/Creative Commons [2]

Their paper, as well as others, have inspired new approaches to combating cold boot attacks.

“To mitigate the risk of unauthorized access from unknown devices, main devices, or servers, check the authenticated code and unique identity of each accessing device,” said Jongsin Yun, memory technologist at Siemens EDA. “SRAM PUF is one of the ways to securely identify each device. SRAM is made of two inverters cross-coupled to each other. Although each inverter is designed to be the same device, normally one part of the inverter has a somewhat stronger NMOS than the other due to inherent random dopant fluctuation. During the initial power-on process, SRAM data will be either data 1 or 0, depending on which side has a stronger device. In other words, the initial data state of the SRAM array at the power on is decided by this unique random process variation and most of the bits maintain this property for life. One can use this unique pattern as a fingerprint of a device. The SRAM PUF data is reconstructed with other coded data to form a cryptographic key. SRAM PUF is a great way to anchor its secure data into hardware. Hackers may use a DFT circuit to access the memory. To avoid insecurely reading the SRAM information through DFT, the security-critical design makes DFT force delete the data as an initial process of TEST mode.”

However, there can be instances where data may be required to be kept in a non-volatile memory (NVM). “Data is considered insecure if the NVM is located outside of the device,” said Yun. “Therefore, secured data needs to be stored within the device with write protection. One-time programmable (OTP) memory or fuses are good storage options to prevent malicious attackers from tampering with the modified information. OTP memory and fuses are used to store cryptographic keys, authentication information, and other critical settings for operation within the device. It is useful for anti-rollback, which prevents hackers from exploiting old vulnerabilities that have been fixed in newer versions.”

Chiplet vulnerabilities
Chiplets also could present another vector for attack, due to their complexity and interconnections. “A chiplet has memory, so it’s going to be attacked,” said Cycuity’s Seshadri. “Chiplets, in general, are going to exacerbate the problem, rather than keeping it status quo, because you’re going to have one chiplet talking to another. Could an attack on one chiplet have a side effect on another? There need to be standards to address this. In fact, they’re coming into play already. A chiplet provider has to say, ‘Here’s what I’ve done for security. Here’s what needs to be done when interfacing with another chiplet.”

Yun notes there is a further physical vulnerability for those working with chiplets and SiPs. “When multiple chiplets are connected to form a SiP, we have to trust data coming from an external chip, which creates further complications. Verification of the chiplet’s authenticity becomes very important for SiPs, as there is a risk of malicious counterfeit chiplets being connected to the package for hacking purposes. Detection of such counterfeit chiplets is imperative.”

These precautions also apply when working with DRAM. In all situations, Seshardi said, thinking about security has to go beyond device-level protection. “The onus of protecting DRAM is not just on the DRAM designer or the memory designer,” he said. “It has to be secured by design principles when you are developing. In addition, you have to look at this holistically and do it at a system level. You must consider all the other things that communicate with DRAM or that are placed near DRAM. You must look at a holistic solution, all the way from software down to things like the memory controller and then finally, the DRAM itself.”

Encryption as a backup
Data itself always must be encrypted as second layer of protection against known and novel attacks, so an organization’s assets will still be protected even if someone breaks in via cold boot or another method.

“The first and primary method of preventing a cold boot attack is limiting physical access to the systems, or physically modifying the systems case or hardware preventing an attacker’s access,” said Jim Montgomery, market development director, semiconductor at TXOne Networks. “The most effective programmatic defense against an attack is to ensure encryption of memory using either a hardware- or software-based approach. Utilizing memory encryption will ensure that regardless of trying to dump the memory, or physically removing the memory, the encryption keys will remain secure.”

Montgomery also points out that TXOne is working with the Semiconductor Manufacturing Cybersecurity Consortium (SMCC) to develop common criteria based upon SEMI E187 and E188 standards to assist DM’s and OEM’s to implement secure procedures for systems security and integrity, including controlling the physical environment.

What kind and how much encryption will depend on use cases, said Jun Kawaguchi, global marketing executive for Winbond. “Encryption strength for a traffic signal controller is going to be different from encryption for nuclear plants or medical devices, critical applications where you need much higher levels,” he said. “There are different strengths and costs to it.”

Another problem, in the post-quantum era, is that encryption itself may be vulnerable. To defend against those possibilities, researchers are developing post-quantum encryption schemes. One way to stay a step ahead is homomorphic encryption [HE], which will find a role in data sharing, since computations can be performed on encrypted data without first having to decrypt it.

Homomorphic encryption could be in widespread use as soon as the next few years, according to Ronen Levy, senior manager for IBM’s Cloud Security & Privacy Technologies Department, and Omri Soceanu, AI Security Group manager at IBM.  However, there are still challenges to be overcome.

“There are three main inhibitors for widespread adoption of homomorphic encryption — performance, consumability, and standardization,” according to Levy. “The main inhibitor, by far, is performance. Homomorphic encryption comes with some latency and storage overheads. FHE hardware acceleration will be critical to solving these issues, as well as algorithmic and cryptographic solutions, but without the necessary expertise it can be quite challenging.”

An additional issue is that most consumers of HE technology, such as data scientists and application developers, do not possess deep cryptographic skills, HE solutions that are designed for cryptographers can be impractical. A few HE solutions require algorithmic and cryptographic expertise that inhibit adoption by those who lack these skills.

Finally, there is a lack of standardization. “Homomorphic encryption is in the process of being standardized,” said Soceanu. “But until it is fully standardized, large organizations may be hesitant to adopt a cryptographic solution that has not been approved by standardization bodies.”

Once these issues are resolved, they predicted widespread use as soon as the next few years. “Performance is already practical for a variety of use cases, and as hardware solutions for homomorphic encryption become a reality, more use cases would become practical,” said Levy. “Consumability is addressed by creating more solutions, making it easier and hopefully as frictionless as possible to move analytics to homomorphic encryption. Additionally, standardization efforts are already in progress.”

A new attack and an old problem
Unfortunately, security never will be as simple as making users more aware of their surroundings. Otherwise, cold boot could be completely eliminated as a threat. Instead, it’s essential to keep up with conference talks and the published literature, as graduate students keep probing SRAM for vulnerabilities, hopefully one step ahead of genuine attackers.

For example, SRAM-related cold boot attacks originally targeted discrete SRAM. The reason is that it’s far more complicated to attack on-chip SRAM, which is isolated from external probing and has minimal intrinsic capacitance. However, in 2022, Jubayer Mahmod, then a graduate student at Virginia Tech and his advisor, associate professor Matthew Hicks, demonstrated what they dubbed “Volt Boot,” a new method that could penetrate on-chip SRAM. According to their paper, “Volt Boot leverages asymmetrical power states (e.g., on vs. off) to force SRAM state retention across power cycles, eliminating the need for traditional cold boot attack enablers, such as low-temperature or intrinsic data retention time…Unlike other forms of SRAM data retention attacks, Volt Boot retrieves data with 100% accuracy — without any complex post-processing.”

Conclusion
While scientists and engineers continue to identify vulnerabilities and develop security solutions, decisions about how much security to include in a design is an economic one. Cost vs. risk is a complex formula that depends on the end application, the impact of a breach, and the likelihood that an attack will occur.

“It’s like insurance,” said Kawaguchi. “Security engineers and people like us who are trying to promote security solutions get frustrated because, similar to insurance pitches, people respond with skepticism. ‘Why would I need it? That problem has never happened before.’ Engineers have a hard time convincing their managers to spend that extra dollar on the costs because of this ‘it-never-happened-before’ attitude. In the end, there are compromises. Yet ultimately, it’s going to cost manufacturers a lot of money when suddenly there’s a deluge of demands to fix this situation right away.”

References

1. S. Skorobogatov, “Low temperature data remanence in static RAM”, Technical report UCAM-CL-TR-536, University of Cambridge Computer Laboratory, June 2002.
2. Han, SJ., Han, JK., Yun, GJ. et al. Ultra-fast data sanitization of SRAM by back-biasing to resist a cold boot attack. Sci Rep 12, 35 (2022). https://doi.org/10.1038/s41598-021-03994-2

The post SRAM Security Concerns Grow appeared first on Semiconductor Engineering.

Successive versions of vertical transistors are emerging as the likely successor to finFETs, combining lower leakage with significant area reduction.

A stacked nanosheet transistor, introduced at N3, uses multiple channel layers to maintain the overall channel length and necessary drive current while continuing to reduce the standard cell footprint. The follow-on technology, the CFET, pushes further up the z axis, stacking n-channel and p-channel transistors on top of each other, rather than side by side.

In work presented at December’s IEEE Electron Device Meeting, researchers at TSMC estimated that CFETs give a 1.5X to 2X overall size reduction at constant gate dimensions. [1] Those are significant area benefits for any digital logic, but manufacturing these new transistor structures will be a challenge.

Monolithic 3D integration is the simplest integration scheme, and the one likely to see production first. In monolithic 3D integration, the entire structure is assembled on a single piece of silicon. This approach can also be used to fabricate compute-in-memory designs where memory devices are fabricated as part of the metallization layers for a conventional CMOS circuit. While individual layers in monolithic 3D designs can incorporate new technologies — the integration of ReRAM devices, for example — the overall CMOS flow is preserved. All of the materials and processes used must be compatible with that rubric.

Adding more nanosheets for complementary devices
The overall process in this kind of scheme is similar to a stacked nanosheet transistor flow. It starts with a stack of eight or more alternating silicon and silicon germanium layers (four pairs), compared to a stacked nanosheet NFET or PFET, which might have only four such layers (two pairs). In a CFET flow, however, middle dielectric layer is inserted halfway through the stack.

This layer, separating the n-type and p-type transistors, is probably the most important difference from a standard nanosheet transistor flow. To minimize parasitic capacitance, the middle dielectric layer should be as thin as possible, said imec’s Naoto Horiguchi. If it’s too thin, though, edge placement errors can cause isolation failures, landing contacts for the top devices onto bottom devices. [2]

In TSMC’s process, the Si/SiGe superlattice includes a high-germanium SiGe layer as a placeholder for the middle dielectric. After the source/drain etch, a highly selective etch removes this layer and oxidizes the silicon on either side of it to form the middle dielectric.

The inner spacer recess etch, which follows middle dielectric formation in the TSMC process, indents the SiGe layers relative to the silicon nanosheets, defining the gate length and junction overlap.

While TSMC emphasized it has not yet made fully metallized integrated CFET circuits, it did report that more than 90% of the transistors survived.

Fig. 1: TSMC used monolithic integration to stack NFET and PFET devices. [1]

Depositing the nanosheet stack is straightforward. Etching it with the precision required is not. A less-than-vertical etch profile will change the relative channel lengths of the top and bottom devices, leading to asymmetric switching characteristics.

Stacking wafers for more flexibility
The alternative, sequential 3D integration is a bit more flexible. While monolithic 3D integration uses a single device layer, sequential 3D integration bonds an additional tier on top of the first. Sequential 3D integration is different from three-dimensional wafer-level packaging and chip stacking, though. In WLP, the component devices are finished, passivated, and tested. The component chips are fully functional as independent circuits. In sequential 3D integration, the two tiers are part of a single integrated circuit.

Often, though not always, the second tier is an unprocessed bare wafer with no devices at all. Ionut Radu, director of research and external collaborations at Soitec, said his company used its SmartCut process to transfer sub-micron silicon layers. [3] One of the advantages of sequential integration, though, is that it opens the door to other possibilities. For example, the second layer could use a different silicon lattice orientation to facilitate stress engineering for improved carrier mobility. It also could use an alternative channel material, such as GaAs or a two-dimensional semiconductor. And up until the transfer occurs, processing of the second wafer has no effect on the thermal budget of the first.

After bonding, the second tier’s process temperature generally must remain below 500° C. Tadeu Mota-Frutuoso, process integration engineer at CEA-Leti, said researchers were able to achieve this benchmark in a conventional CMOS process by using laser annealing for the source/drain activation steps. [4]

While sequential 3D integration can be used to realize CFET devices, the top layers also can contain independent circuitry. Still, as in monolithic integration, the dielectric layer between the two circuit tiers is a critical process step. Analysts at KAIST found that reducing the thickness of the interlayer dielectric improves heat dissipation. It also facilitates the use of a bottom gate to control the top tier devices. On the other hand, the dielectric layer lies at the interface between the original wafer and the transferred layer. Thickness control depends on the polishing step used to prepare the transfer surface. Such precise control is extremely challenging for CMP. [5]

Re-driving wafers without contamination
While the second circuit tier can be added at any point in the process flow, the insertion point constrains not only the first and second tier devices, but also the fab as a whole. When the second layer does not yet contain devices, alignment to the first layer is relatively easy. In contrast, Horiguchi said, aligning one device wafer on top of another imposes an area penalty to accommodate potential overlay error. The total device thickness of sequential 3D structures tends to be greater, as well.

Returning a first-tier wafer with contacts and other metallization to FEOL tools for fabrication of a second transistor layer poses a substantial cross contamination risk. Even if the top surface is well encapsulated, Mota-Frutuoso explained in an interview that the sidewalls and bevels of the bottom tier can still expose metal layers to FEOL processes. CEA-Leti’s proposed bevel contamination wrap (BCW) scheme first cleans the wafer edge, then encapsulates it and the sidewall in a protective oxide layer.

Fig. 2: CEA-Leti’s sequential 3D integration stacked silicon CMOS on an industrial 28nm FDSOI wafer. [4]

Controlling heat dissipation
Heat dissipation is a major challenge for both monolithic and sequential 3D devices. Generalizations are difficult because thermal characteristics depend on the specific integration scheme and even the circuit design. Wei-Yen Woon, senior manager at TSMC, and his colleagues evaluated AlN and diamond as possible thermal dissipation layers. While both have been used in power devices, they are new to CMOS process flows. They achieved good quality columnar AlN films with a low temperature sputtering process, though the columnar structure did impede in-plane heat transport. While diamond offers extremely high thermal conductivity, it also can require extremely high process temperatures. The TSMC group deposited thin films with acceptable quality at BEOL compatible temperatures by using pre-deposited diamond nuclei, but they have not yet attempted to integrate these films with working devices.^[6]

What’s next?
In the short term, monolithic 3D integration offers a relatively straightforward path to CFET fabrication, building on existing nanosheet transistor process flows. Even proponents of sequential 3D integration expect the monolithic approach to reach production first. For the longer term, though, the ability to use a completely different material for the second device layer gives device designers many more process optimization knobs.

However it is achieved, the idea that active devices no longer need to confine themselves to a single planar layer has implications far beyond logic transistors. From compute-in-memory modules to image sensors, 3D integration is an important tool for “More than Moore” devices.

References

^[1] S. Liao et al., “Complementary Field-Effect Transistor (CFET) Demonstration at 48nm Gate Pitch for Future Logic Technology Scaling,” 2023 International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2023, pp. 1-4, doi: 10.1109/IEDM45741.2023.10413672.

^[2] N. Horiguchi et al., “3D Stacked Devices and MOL Innovations for Post-Nanosheet CMOS Scaling,” 2023 International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2023, pp. 1-4, doi: 10.1109/IEDM45741.2023.10413701.

^[3] I. Radu et al., “Ultimate Layer Stacking Technology for High Density Sequential 3D Integration,” 2023 International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2023, pp. 1-4, doi: 10.1109/IEDM45741.2023.10413807.

^[4] T. Mota-Frutuoso et al., “3D sequential integration with Si CMOS stacked on 28nm industrial FDSOI with Cu-ULK iBEOL featuring RO and HDR pixel,” 2023 International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2023, pp. 1-4, doi: 10.1109/IEDM45741.2023.10413864.

^[5] S. K. Kim et al., “Role of Inter-Layer Dielectric on the Electrical and Heat Dissipation Characteristics in the Heterogeneous 3D Sequential CFETs with Ge p-FETs on Si n-FETs,” 2023 International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2023, pp. 1-4, doi: 10.1109/IEDM45741.2023.10413845.

^[6] W. Y. Woon et al., “Thermal dissipation in stacked devices,” 2023 International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2023, pp. 1-4, doi: 10.1109/IEDM45741.2023.10413721.

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