Pub Date : 2026-02-25DOI: 10.1038/s41928-026-01577-5
Zai-Zheng Yang (, ), Cong Wang (, ), Yichen Zhao (, ), Gong-Jie Ruan (, ), Xing-Jian Yangdong (, ), Yuekun Yang (, ), Chen Pan (, ), Bin Cheng (, ), Shi-Jun Liang (, ), Feng Miao (, )
Collaborative computing between edge devices and cloud servers over wireless communication is critical for energy-constrained edge devices to perform complex tasks that exceed their processing capacities. However, current wireless collaborative systems face challenges in terms of energy efficiency and latency due to the separation of memory and computing, the separation of signal processing and transmission and/or reception, and the separation of neural networks and wireless communication. Here we report communication-aware in-memory wireless neural networks. The approach uses analogue in-memory computing technology to implement both edge computing and wireless communication, and integrates wireless communication as a learnable module of the wireless neural network. We build a prototype that comprises an edge inference accelerator and a wireless communication system. The prototype exhibits an experimental inference accuracy of 93.71% on the Street View House Numbers dataset, and can maintain inference accuracy when using low-resolution analogue-to-digital converters in wireless communication. We also show that the approach can adapt to various wireless conditions and can reduce communication costs. By using analogue in-memory computing technology to integrate edge computing and wireless communication into a learnable system, communication-aware in-memory wireless neural networks can be created that can adapt to different wireless conditions.
{"title":"Communication-aware in-memory wireless neural networks","authors":"Zai-Zheng Yang \u0000 (, ), Cong Wang \u0000 (, ), Yichen Zhao \u0000 (, ), Gong-Jie Ruan \u0000 (, ), Xing-Jian Yangdong \u0000 (, ), Yuekun Yang \u0000 (, ), Chen Pan \u0000 (, ), Bin Cheng \u0000 (, ), Shi-Jun Liang \u0000 (, ), Feng Miao \u0000 (, )","doi":"10.1038/s41928-026-01577-5","DOIUrl":"10.1038/s41928-026-01577-5","url":null,"abstract":"Collaborative computing between edge devices and cloud servers over wireless communication is critical for energy-constrained edge devices to perform complex tasks that exceed their processing capacities. However, current wireless collaborative systems face challenges in terms of energy efficiency and latency due to the separation of memory and computing, the separation of signal processing and transmission and/or reception, and the separation of neural networks and wireless communication. Here we report communication-aware in-memory wireless neural networks. The approach uses analogue in-memory computing technology to implement both edge computing and wireless communication, and integrates wireless communication as a learnable module of the wireless neural network. We build a prototype that comprises an edge inference accelerator and a wireless communication system. The prototype exhibits an experimental inference accuracy of 93.71% on the Street View House Numbers dataset, and can maintain inference accuracy when using low-resolution analogue-to-digital converters in wireless communication. We also show that the approach can adapt to various wireless conditions and can reduce communication costs. By using analogue in-memory computing technology to integrate edge computing and wireless communication into a learnable system, communication-aware in-memory wireless neural networks can be created that can adapt to different wireless conditions.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 4","pages":"414-425"},"PeriodicalIF":40.9,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147279785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1038/s41928-026-01570-y
Yi-Chen Liu, Jacklyn Zhu, John Niroula, Hridibrata Pal, Tomás Palacios, Savannah R. Eisner
High-electron-mobility transistors (HEMTs) made with group-III nitride (III nitride) materials are of potential use in high-temperature electronic applications including power electronics, communications, aerospace and space exploration. However, the demands of such applications make it essential to understand the thermal limits and performance evolution of III nitride HEMTs. Here we analyse the high-temperature operation of III nitride HEMTs, examining the impact on material properties, device structure and circuit-level behaviour. We explore the role of critical device layers—including barrier and channel engineering, substrate selection and passivation strategies—in mitigating high-temperature-induced effects, and evaluate the thermal stability of III nitride HEMTs in logic, radiofrequency and power electronics applications. We also highlight key remaining challenges in the design and optimization of III nitride devices for high-temperature applications. This Review examines the degradation mechanisms and lifetime-limiting behaviour of critical device layers in group-III nitride high-electron-mobility transistors under high-temperature operation, considering how these impact device- and circuit-level performance under high thermal stress and highlighting the challenges that need to be addressed to achieve reliable operation in extreme conditions.
{"title":"High-temperature operation of group-III nitride high-electron-mobility transistors","authors":"Yi-Chen Liu, Jacklyn Zhu, John Niroula, Hridibrata Pal, Tomás Palacios, Savannah R. Eisner","doi":"10.1038/s41928-026-01570-y","DOIUrl":"10.1038/s41928-026-01570-y","url":null,"abstract":"High-electron-mobility transistors (HEMTs) made with group-III nitride (III nitride) materials are of potential use in high-temperature electronic applications including power electronics, communications, aerospace and space exploration. However, the demands of such applications make it essential to understand the thermal limits and performance evolution of III nitride HEMTs. Here we analyse the high-temperature operation of III nitride HEMTs, examining the impact on material properties, device structure and circuit-level behaviour. We explore the role of critical device layers—including barrier and channel engineering, substrate selection and passivation strategies—in mitigating high-temperature-induced effects, and evaluate the thermal stability of III nitride HEMTs in logic, radiofrequency and power electronics applications. We also highlight key remaining challenges in the design and optimization of III nitride devices for high-temperature applications. This Review examines the degradation mechanisms and lifetime-limiting behaviour of critical device layers in group-III nitride high-electron-mobility transistors under high-temperature operation, considering how these impact device- and circuit-level performance under high thermal stress and highlighting the challenges that need to be addressed to achieve reliable operation in extreme conditions.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 2","pages":"127-139"},"PeriodicalIF":40.9,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1038/s41928-026-01585-5
Yan Huang
{"title":"A communication system that operates in space","authors":"Yan Huang","doi":"10.1038/s41928-026-01585-5","DOIUrl":"10.1038/s41928-026-01585-5","url":null,"abstract":"","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 2","pages":"119-119"},"PeriodicalIF":40.9,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-19DOI: 10.1038/s41928-026-01584-6
Katharina Zeissler
{"title":"Stirring up vortices with hydrogel cilia","authors":"Katharina Zeissler","doi":"10.1038/s41928-026-01584-6","DOIUrl":"10.1038/s41928-026-01584-6","url":null,"abstract":"","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 2","pages":"118-118"},"PeriodicalIF":40.9,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-18DOI: 10.1038/s41928-026-01586-4
Matthew Parker
{"title":"Long-term health monitoring of poorly plants","authors":"Matthew Parker","doi":"10.1038/s41928-026-01586-4","DOIUrl":"10.1038/s41928-026-01586-4","url":null,"abstract":"","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 2","pages":"120-120"},"PeriodicalIF":40.9,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-12DOI: 10.1038/s41928-026-01569-5
Alberto Tosato, Asser Elsayed, Federico Poggiali, Lucas Erik Adriaan Stehouwer, Davide Costa, Karina Louise Hudson, Davide Degli Esposti, Giordano Scappucci
The large-scale integration of semiconductor spin qubits into quantum processors will require the characterization of quantum components at scale. However, such characterization is challenging and typically requires radio-frequency measurements at millikelvin temperatures and the presence of magnetic fields. Here we report a scalable architecture for characterizing spin qubits using a quantum dot crossbar array. The approach, which we term as the qubit-array research platform for engineering and testing, uses a crossbar array comprising tightly pitched spin-qubit tiles and is implemented in planar germanium, with the potential to host 1,058 single-hole spin qubits. We measure a subset of 40 tiles and demonstrate key device functionality at millikelvin temperatures, including tile addressability, threshold voltage and charge noise statistics, as well as the characterization of hole spin qubits and their coherence times in a single tile. A scalable architecture that is based on a quantum dot crossbar array comprising tightly pitched spin-qubit tiles and implemented in planar germanium, can be used characterize spin qubits.
{"title":"A crossbar chip for benchmarking semiconductor spin qubits","authors":"Alberto Tosato, Asser Elsayed, Federico Poggiali, Lucas Erik Adriaan Stehouwer, Davide Costa, Karina Louise Hudson, Davide Degli Esposti, Giordano Scappucci","doi":"10.1038/s41928-026-01569-5","DOIUrl":"10.1038/s41928-026-01569-5","url":null,"abstract":"The large-scale integration of semiconductor spin qubits into quantum processors will require the characterization of quantum components at scale. However, such characterization is challenging and typically requires radio-frequency measurements at millikelvin temperatures and the presence of magnetic fields. Here we report a scalable architecture for characterizing spin qubits using a quantum dot crossbar array. The approach, which we term as the qubit-array research platform for engineering and testing, uses a crossbar array comprising tightly pitched spin-qubit tiles and is implemented in planar germanium, with the potential to host 1,058 single-hole spin qubits. We measure a subset of 40 tiles and demonstrate key device functionality at millikelvin temperatures, including tile addressability, threshold voltage and charge noise statistics, as well as the characterization of hole spin qubits and their coherence times in a single tile. A scalable architecture that is based on a quantum dot crossbar array comprising tightly pitched spin-qubit tiles and implemented in planar germanium, can be used characterize spin qubits.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 3","pages":"324-333"},"PeriodicalIF":40.9,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41928-026-01569-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146196779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-05DOI: 10.1038/s41928-025-01560-6
Runjiu Fang, Huihui Tian, Yan Du, Yan Zhao, Yinan Yang, Shouliang Guan, Shengguang Li, Mengcheng Liu, Ke Xu, Ying Fang
The development of brain–computer interfaces requires implantable microelectrode arrays that can interface with numerous neurons across large spatial and temporal scales. However, creating arrays that can effectively accommodate the substantial movements and deformations of primate brains remains challenging. Here we report a kirigami-inspired flexible microelectrode array that has a reconfigurable spiral thread design and can be used for large-scale, long-term neuronal activity recordings in the primate brain. Each array can be transferred onto a hydrogel-coated brain surface using a water-dissolvable carrier, providing high-throughput delivery of multiple spiral threads across a large brain area. Stretchable spiral threads can be implanted into the cerebral cortex, with their base floating conformally on the brain surface to accommodate the large movements of the primate brain inside the skull. We show that the implanted array can provide simultaneous activity recordings from over 700 cortical neurons in a macaque monkey brain. We also demonstrate the accurate decoding of upper-limb kinematics from the spiking activity of the primary motor cortex (M1) neurons with a recurrent neural network model. A flexible, floating microelectrode array that has a reconfigurable spiral thread design can be used to create large-scale, long-term brain–computer interfaces in the primate brain.
{"title":"Flexible kirigami microelectrode arrays for neuronal activity recordings in non-human primate brains","authors":"Runjiu Fang, Huihui Tian, Yan Du, Yan Zhao, Yinan Yang, Shouliang Guan, Shengguang Li, Mengcheng Liu, Ke Xu, Ying Fang","doi":"10.1038/s41928-025-01560-6","DOIUrl":"10.1038/s41928-025-01560-6","url":null,"abstract":"The development of brain–computer interfaces requires implantable microelectrode arrays that can interface with numerous neurons across large spatial and temporal scales. However, creating arrays that can effectively accommodate the substantial movements and deformations of primate brains remains challenging. Here we report a kirigami-inspired flexible microelectrode array that has a reconfigurable spiral thread design and can be used for large-scale, long-term neuronal activity recordings in the primate brain. Each array can be transferred onto a hydrogel-coated brain surface using a water-dissolvable carrier, providing high-throughput delivery of multiple spiral threads across a large brain area. Stretchable spiral threads can be implanted into the cerebral cortex, with their base floating conformally on the brain surface to accommodate the large movements of the primate brain inside the skull. We show that the implanted array can provide simultaneous activity recordings from over 700 cortical neurons in a macaque monkey brain. We also demonstrate the accurate decoding of upper-limb kinematics from the spiking activity of the primary motor cortex (M1) neurons with a recurrent neural network model. A flexible, floating microelectrode array that has a reconfigurable spiral thread design can be used to create large-scale, long-term brain–computer interfaces in the primate brain.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 3","pages":"266-278"},"PeriodicalIF":40.9,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-02DOI: 10.1038/s41928-025-01562-4
Jonas Schuff, Miguel J. Carballido, Madeleine Kotzagiannidis, Juan Carlos Calvo, Marco Caselli, Jacob Rawling, David L. Craig, Barnaby van Straaten, Brandon Severin, Federico Fedele, Simon Svab, Pierre Chevalier Kwon, Rafael S. Eggli, Taras Patlatiuk, Nathan Korda, Dominik M. Zumbühl, Natalia Ares
The development of large-scale semiconductor quantum circuits is limited by the difficulties involved in efficiently tuning and operating such circuits. Identifying optimal operating conditions for these qubits is, in particular, complex and involves the exploration of vast parameter spaces. Here we report the autonomous tuning of a semiconductor qubit, from a grounded device to Rabi oscillations. Our approach integrates deep learning, Bayesian optimization and computer vision techniques. We demonstrate this automation in a germanium–silicon core–shell nanowire device. To illustrate the potential of full automation, we characterize how the Rabi frequency and g-factor depend on barrier gate voltages for one of the qubits found by the algorithm. We expect our automation algorithm to be applicable to a range of semiconductor qubit devices, allowing for the statistical studies of qubit-quality metrics. An algorithm that combines deep learning, Bayesian optimization and computer vision techniques can be used to autonomously tune a semiconductor spin qubit from a grounded device to Rabi oscillations.
{"title":"Fully autonomous tuning of a spin qubit","authors":"Jonas Schuff, Miguel J. Carballido, Madeleine Kotzagiannidis, Juan Carlos Calvo, Marco Caselli, Jacob Rawling, David L. Craig, Barnaby van Straaten, Brandon Severin, Federico Fedele, Simon Svab, Pierre Chevalier Kwon, Rafael S. Eggli, Taras Patlatiuk, Nathan Korda, Dominik M. Zumbühl, Natalia Ares","doi":"10.1038/s41928-025-01562-4","DOIUrl":"10.1038/s41928-025-01562-4","url":null,"abstract":"The development of large-scale semiconductor quantum circuits is limited by the difficulties involved in efficiently tuning and operating such circuits. Identifying optimal operating conditions for these qubits is, in particular, complex and involves the exploration of vast parameter spaces. Here we report the autonomous tuning of a semiconductor qubit, from a grounded device to Rabi oscillations. Our approach integrates deep learning, Bayesian optimization and computer vision techniques. We demonstrate this automation in a germanium–silicon core–shell nanowire device. To illustrate the potential of full automation, we characterize how the Rabi frequency and g-factor depend on barrier gate voltages for one of the qubits found by the algorithm. We expect our automation algorithm to be applicable to a range of semiconductor qubit devices, allowing for the statistical studies of qubit-quality metrics. An algorithm that combines deep learning, Bayesian optimization and computer vision techniques can be used to autonomously tune a semiconductor spin qubit from a grounded device to Rabi oscillations.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 3","pages":"304-313"},"PeriodicalIF":40.9,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41928-025-01562-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1038/s41928-025-01552-6
Inkyu Lee, Arielle Berman, Ritu Raman
Biohybrid robots, which rely on living muscles to drive force generation, could be of use in applications ranging from microsurgery to unmanned exploration. But the development of untethered and autonomous machines will require the integration of onboard electronics for sensing, control and power.
{"title":"Using electronics to build biohybrid robots with physical intelligence","authors":"Inkyu Lee, Arielle Berman, Ritu Raman","doi":"10.1038/s41928-025-01552-6","DOIUrl":"10.1038/s41928-025-01552-6","url":null,"abstract":"Biohybrid robots, which rely on living muscles to drive force generation, could be of use in applications ranging from microsurgery to unmanned exploration. But the development of untethered and autonomous machines will require the integration of onboard electronics for sensing, control and power.","PeriodicalId":19064,"journal":{"name":"Nature Electronics","volume":"9 1","pages":"8-10"},"PeriodicalIF":40.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146083449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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