Pub Date : 2024-11-12DOI: 10.1038/s44287-024-00115-9
Tiancheng Song, Xiaodong Xu
The rapid advances in van der Waals magnets provide a platform for exploring spintronics in the 2D limit. Leveraging the unique properties of 2D magnets with new tuning knobs could see 2D spintronics find its applications in both quantum and classic information processing.
{"title":"The future of 2D spintronics","authors":"Tiancheng Song, Xiaodong Xu","doi":"10.1038/s44287-024-00115-9","DOIUrl":"10.1038/s44287-024-00115-9","url":null,"abstract":"The rapid advances in van der Waals magnets provide a platform for exploring spintronics in the 2D limit. Leveraging the unique properties of 2D magnets with new tuning knobs could see 2D spintronics find its applications in both quantum and classic information processing.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"696-697"},"PeriodicalIF":0.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-12DOI: 10.1038/s44287-024-00119-5
Spintronic devices that leverage electron spins for information processing offer a new frontier for ultra-low-power circuits and systems for beyond-CMOS technology. Spintronic devices that leverage electron spins for information processing offer a new frontier for ultra-low-power circuits and systems for beyond-CMOS technology.
{"title":"Spintronics for ultra-low-power circuits and systems","authors":"","doi":"10.1038/s44287-024-00119-5","DOIUrl":"10.1038/s44287-024-00119-5","url":null,"abstract":"Spintronic devices that leverage electron spins for information processing offer a new frontier for ultra-low-power circuits and systems for beyond-CMOS technology. Spintronic devices that leverage electron spins for information processing offer a new frontier for ultra-low-power circuits and systems for beyond-CMOS technology.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"691-691"},"PeriodicalIF":0.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44287-024-00119-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1038/s44287-024-00111-z
Daniel C. Worledge, Guohan Hu
Spin-transfer torque magnetoresistive random access memory (STT-MRAM) is a non-volatile memory technology with a unique combination of speed, endurance, density and ease of fabrication, which has enabled it to recently replace embedded Flash as the embedded non-volatile memory of choice for advanced applications, including automotive microcontroller units. In this Review, we describe the working principles of STT-MRAM, and provide a brief history of its development. We then discuss the requirements, product status and outlook for four key STT-MRAM applications: stand-alone, embedded non-volatile memory, non-volatile working memory and last-level cache. Finally, we review potential future directions beyond STT-MRAM, including spin–orbit torque MRAM (SOT-MRAM) and voltage control of magnetic anisotropy MRAM (VCMA-MRAM), with an emphasis on their technological potential. Spin-transfer torque magnetoresistive random access memory (STT-MRAM) has recently replaced embedded Flash as the embedded non-volatile memory of choice for advanced applications. This Review discusses STT-MRAM history, operation, application requirements, product status and potential future directions.
{"title":"Spin-transfer torque magnetoresistive random access memory technology status and future directions","authors":"Daniel C. Worledge, Guohan Hu","doi":"10.1038/s44287-024-00111-z","DOIUrl":"10.1038/s44287-024-00111-z","url":null,"abstract":"Spin-transfer torque magnetoresistive random access memory (STT-MRAM) is a non-volatile memory technology with a unique combination of speed, endurance, density and ease of fabrication, which has enabled it to recently replace embedded Flash as the embedded non-volatile memory of choice for advanced applications, including automotive microcontroller units. In this Review, we describe the working principles of STT-MRAM, and provide a brief history of its development. We then discuss the requirements, product status and outlook for four key STT-MRAM applications: stand-alone, embedded non-volatile memory, non-volatile working memory and last-level cache. Finally, we review potential future directions beyond STT-MRAM, including spin–orbit torque MRAM (SOT-MRAM) and voltage control of magnetic anisotropy MRAM (VCMA-MRAM), with an emphasis on their technological potential. Spin-transfer torque magnetoresistive random access memory (STT-MRAM) has recently replaced embedded Flash as the embedded non-volatile memory of choice for advanced applications. This Review discusses STT-MRAM history, operation, application requirements, product status and potential future directions.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"730-747"},"PeriodicalIF":0.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1038/s44287-024-00120-y
Olga Bubnova
An article in Nature Communications presents the orbital torque switching in light metal Zr systems with perpendicular magnetic anisotropy ferromagnetic materials.
{"title":"Perpendicularly magnetized materials for energy-efficient orbitronics","authors":"Olga Bubnova","doi":"10.1038/s44287-024-00120-y","DOIUrl":"10.1038/s44287-024-00120-y","url":null,"abstract":"An article in Nature Communications presents the orbital torque switching in light metal Zr systems with perpendicular magnetic anisotropy ferromagnetic materials.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"699-699"},"PeriodicalIF":0.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Neural computing, guided by brain-inspired computational frameworks, promises to realize various cognitive and perception-related tasks. Complementary metal–oxide–semiconductor-based computing machines use orders-of-magnitude more computational resources than the brain on cognitive tasks that humans efficiently perform every day. As a result, we are witnessing a seismic shift in the field of computation. Research efforts are being directed to develop artificial intelligence (AI) hardware that mimics the human brain from a bottom-up perspective — through devices that are more naturally suited to neural computation — and thereby improves the efficiency of performing cognitive tasks. In the attempt to bridge the gap between neuroscience and electronics, here we report on developments in the field of spintronic devices for AI hardware. The dynamics of spintronic devices that can be used for the realization of neural and synaptic functionalities are discussed. A cross-layer perspective extending from the device to the circuit and system levels as a pathway towards efficient neural computing systems is also presented. Spintronic devices for artificial intelligence hardware can bridge the gap between neuroscience and electronics. Here we discuss the dynamics of such devices, enabling neural and synaptic functionalities, alongside a cross-layer approach — from devices to circuits and systems — for efficient neural computing systems.
{"title":"Spintronic neural systems","authors":"Kaushik Roy, Cheng Wang, Sourjya Roy, Anand Raghunathan, Kezhou Yang, Abhronil Sengupta","doi":"10.1038/s44287-024-00107-9","DOIUrl":"10.1038/s44287-024-00107-9","url":null,"abstract":"Neural computing, guided by brain-inspired computational frameworks, promises to realize various cognitive and perception-related tasks. Complementary metal–oxide–semiconductor-based computing machines use orders-of-magnitude more computational resources than the brain on cognitive tasks that humans efficiently perform every day. As a result, we are witnessing a seismic shift in the field of computation. Research efforts are being directed to develop artificial intelligence (AI) hardware that mimics the human brain from a bottom-up perspective — through devices that are more naturally suited to neural computation — and thereby improves the efficiency of performing cognitive tasks. In the attempt to bridge the gap between neuroscience and electronics, here we report on developments in the field of spintronic devices for AI hardware. The dynamics of spintronic devices that can be used for the realization of neural and synaptic functionalities are discussed. A cross-layer perspective extending from the device to the circuit and system levels as a pathway towards efficient neural computing systems is also presented. Spintronic devices for artificial intelligence hardware can bridge the gap between neuroscience and electronics. Here we discuss the dynamics of such devices, enabling neural and synaptic functionalities, alongside a cross-layer approach — from devices to circuits and systems — for efficient neural computing systems.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"714-729"},"PeriodicalIF":0.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1038/s44287-024-00118-6
Silvia Conti
An article in Science Advances presents the three-dimensional characterization of magnetic skyrmions using soft X-ray laminoghraphy.
科学进展》（Science Advances）杂志上的一篇文章介绍了利用软 X 射线层析成像技术对磁性天幕进行三维表征的情况。
{"title":"Three-dimensional characterization of skyrmions","authors":"Silvia Conti","doi":"10.1038/s44287-024-00118-6","DOIUrl":"10.1038/s44287-024-00118-6","url":null,"abstract":"An article in Science Advances presents the three-dimensional characterization of magnetic skyrmions using soft X-ray laminoghraphy.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"698-698"},"PeriodicalIF":0.0,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1038/s44287-024-00103-z
Jean Anne C. Incorvia, T. Patrick Xiao, Nicholas Zogbi, Azad Naeemi, Christoph Adelmann, Francky Catthoor, Mehdi Tahoori, Fèlix Casanova, Markus Becherer, Guillaume Prenat, Sebastien Couet
The demand for data processing in high-performance computing is growing rapidly. Extrapolating these trends to the long term suggests that a switch, which is more energy-efficient than a silicon complementary metal-oxide semiconductor (CMOS) switch, is necessary to support future computing needs. Spintronic logic, which encodes information using spin and magnetism, can theoretically provide an energy-efficient switch; however, it is less mature than CMOS logic and has yet to be realized at the level of a full processor system, thus warranting an informed review of spintronic logic technologies with guidelines for future research directions. In this Review, we contextualize spintronic logic within the broader goals of beyond-CMOS computing. We then provide an overview of five types of spintronic logic, discussing the operating principles, advantages, advancements and challenges of each type. We highlight that future research in spintronic logic should focus on the realization of low-voltage operation, transparent benchmarking for application-level tasks, development of computing architectures that exploit unique features of spintronics such as non-volatility and high endurance, and adaptation of spintronic logic to circuits usable for both computing and memory. This Review provides motivation and direction for high-risk, high-reward research in spintronic logic that should be pursued in parallel with the CMOS road map. This Review showcases the research progress and prospects of spintronic logic, which encodes information using spin and magnetism. Focusing on five exemplary types, we discuss the promise, challenges and future research directions in the context of high-performance computing needs.
{"title":"Spintronics for achieving system-level energy-efficient logic","authors":"Jean Anne C. Incorvia, T. Patrick Xiao, Nicholas Zogbi, Azad Naeemi, Christoph Adelmann, Francky Catthoor, Mehdi Tahoori, Fèlix Casanova, Markus Becherer, Guillaume Prenat, Sebastien Couet","doi":"10.1038/s44287-024-00103-z","DOIUrl":"10.1038/s44287-024-00103-z","url":null,"abstract":"The demand for data processing in high-performance computing is growing rapidly. Extrapolating these trends to the long term suggests that a switch, which is more energy-efficient than a silicon complementary metal-oxide semiconductor (CMOS) switch, is necessary to support future computing needs. Spintronic logic, which encodes information using spin and magnetism, can theoretically provide an energy-efficient switch; however, it is less mature than CMOS logic and has yet to be realized at the level of a full processor system, thus warranting an informed review of spintronic logic technologies with guidelines for future research directions. In this Review, we contextualize spintronic logic within the broader goals of beyond-CMOS computing. We then provide an overview of five types of spintronic logic, discussing the operating principles, advantages, advancements and challenges of each type. We highlight that future research in spintronic logic should focus on the realization of low-voltage operation, transparent benchmarking for application-level tasks, development of computing architectures that exploit unique features of spintronics such as non-volatility and high endurance, and adaptation of spintronic logic to circuits usable for both computing and memory. This Review provides motivation and direction for high-risk, high-reward research in spintronic logic that should be pursued in parallel with the CMOS road map. This Review showcases the research progress and prospects of spintronic logic, which encodes information using spin and magnetism. Focusing on five exemplary types, we discuss the promise, challenges and future research directions in the context of high-performance computing needs.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"700-713"},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Terahertz communication systems for real-world video transmission","authors":"Lishu Wu","doi":"10.1038/s44287-024-00109-7","DOIUrl":"10.1038/s44287-024-00109-7","url":null,"abstract":"An article in Nature Communications presents a terahertz communication system for real-world live video transmission applications.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 10","pages":"638-638"},"PeriodicalIF":0.0,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142431093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1038/s44287-024-00106-w
Qiming Shao, Kevin Garello, Jianshi Tang
The convergence of spintronics and traditional semiconductor technology marks a critical juncture in the evolution of computing architectures, for which the development of foundation cells become indispensable. Here we discuss the current landscape of spintronics and propose a holistic co-design methodology to integrate spintronic devices into silicon platforms.
{"title":"Spintronic foundation cells for large-scale integration","authors":"Qiming Shao, Kevin Garello, Jianshi Tang","doi":"10.1038/s44287-024-00106-w","DOIUrl":"10.1038/s44287-024-00106-w","url":null,"abstract":"The convergence of spintronics and traditional semiconductor technology marks a critical juncture in the evolution of computing architectures, for which the development of foundation cells become indispensable. Here we discuss the current landscape of spintronics and propose a holistic co-design methodology to integrate spintronic devices into silicon platforms.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"694-695"},"PeriodicalIF":0.0,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-30DOI: 10.1038/s44287-024-00094-x
Christoph Busch
Face recognition, as a process of the human visual system, analyses facial properties and contextual information such as body shape. Automated recognition replicates the human process and analyses a face image, which is typically acquired with a visible spectrum sensor. When dealing with automated operational systems, the quality of the captured face image is relevant as it affects the recognition accuracy. Thus, it is necessary to measure the utility of a face sample with both a quality score and complementary measures that can provide actionable feedback. This Perspective addresses challenges and discusses solutions for the optimization of biometric recognition systems specifically related to face image analysis. One of these challenges is the vulnerability to presentation attacks. Consequently, for reliable recognition in non-supervised environments, robust presentation attack detection is required. Moreover, biometric templates must be protected. Finally, acceptability of biometric systems requires fairness of the biometric algorithms and artificial neural networks used. Automated face recognition systems are widely adopted in different operational systems, ranging from authentication with smart personal devices to access control and forensics. This Perspective analyses the critical challenges and proposed solutions for the optimized use of these recognition systems.
{"title":"Challenges for automated face recognition systems","authors":"Christoph Busch","doi":"10.1038/s44287-024-00094-x","DOIUrl":"10.1038/s44287-024-00094-x","url":null,"abstract":"Face recognition, as a process of the human visual system, analyses facial properties and contextual information such as body shape. Automated recognition replicates the human process and analyses a face image, which is typically acquired with a visible spectrum sensor. When dealing with automated operational systems, the quality of the captured face image is relevant as it affects the recognition accuracy. Thus, it is necessary to measure the utility of a face sample with both a quality score and complementary measures that can provide actionable feedback. This Perspective addresses challenges and discusses solutions for the optimization of biometric recognition systems specifically related to face image analysis. One of these challenges is the vulnerability to presentation attacks. Consequently, for reliable recognition in non-supervised environments, robust presentation attack detection is required. Moreover, biometric templates must be protected. Finally, acceptability of biometric systems requires fairness of the biometric algorithms and artificial neural networks used. Automated face recognition systems are widely adopted in different operational systems, ranging from authentication with smart personal devices to access control and forensics. This Perspective analyses the critical challenges and proposed solutions for the optimized use of these recognition systems.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"1 11","pages":"748-757"},"PeriodicalIF":0.0,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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