Pub Date : 2025-11-21DOI: 10.1038/s44287-025-00230-1
Dongping Wang, Shengzhe Jiang, Hanbin Ma, Jun Yu, Arokia Nathan
Active-matrix digital microfluidics (AM-DMF) leverages semiconductor-derived electrode arrays to dynamically control thousands of micrometre-scale droplets and has emerged as a transformative platform for high-throughput and precise manipulation of liquid samples. This technology enables various programmable operations, such as droplet generation, transport, mixing and dilution, to be performed with unparalleled accuracy and, thereby, overcomes several limitations of conventional microchannel and passive-matrix digital microfluidics. This Review provides a critical analysis of the design principles and transformative potential of AM-DMF, focusing on its potential biomedical applications in genomics, single-cell analysis and drug discovery. Important contributions of artificial intelligence that increase the efficiency and reliability of complex AM-DMF workflows are also discussed. Despite this considerable progress, further innovation is needed to overcome ongoing challenges such as biofouling, reagent selectivity and electrode stability. This Review outlines future directions for AM-DMF as a versatile tool in life sciences and showcases its role in enabling next-generation droplet manipulation and workflow automation. Active-matrix digital microfluidics (AM-DMF) presents a highly scalable and programmable platform for handling microscale liquid samples. Wang et al. describe advances in AM-DMF chip design, circuit optimization and functional integration and discuss its considerable commercial potential for automated high-throughput biomedical sample manipulation.
{"title":"Active-matrix digital microfluidics for high-throughput, precise droplet handling","authors":"Dongping Wang, Shengzhe Jiang, Hanbin Ma, Jun Yu, Arokia Nathan","doi":"10.1038/s44287-025-00230-1","DOIUrl":"10.1038/s44287-025-00230-1","url":null,"abstract":"Active-matrix digital microfluidics (AM-DMF) leverages semiconductor-derived electrode arrays to dynamically control thousands of micrometre-scale droplets and has emerged as a transformative platform for high-throughput and precise manipulation of liquid samples. This technology enables various programmable operations, such as droplet generation, transport, mixing and dilution, to be performed with unparalleled accuracy and, thereby, overcomes several limitations of conventional microchannel and passive-matrix digital microfluidics. This Review provides a critical analysis of the design principles and transformative potential of AM-DMF, focusing on its potential biomedical applications in genomics, single-cell analysis and drug discovery. Important contributions of artificial intelligence that increase the efficiency and reliability of complex AM-DMF workflows are also discussed. Despite this considerable progress, further innovation is needed to overcome ongoing challenges such as biofouling, reagent selectivity and electrode stability. This Review outlines future directions for AM-DMF as a versatile tool in life sciences and showcases its role in enabling next-generation droplet manipulation and workflow automation. Active-matrix digital microfluidics (AM-DMF) presents a highly scalable and programmable platform for handling microscale liquid samples. Wang et al. describe advances in AM-DMF chip design, circuit optimization and functional integration and discuss its considerable commercial potential for automated high-throughput biomedical sample manipulation.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"3 1","pages":"46-60"},"PeriodicalIF":0.0,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145970216","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 : 2025-11-21DOI: 10.1038/s44287-025-00244-9
Miranda L. Vinay
A study in Optics Express reports the design of a simple dielectric metasurface structure composed of lithium niobate defect disks that enhances the generation of entangled photon pairs through spontaneous parametric down-conversion.
{"title":"Enhancing photon pair generation with Quasi-BIC metasurfaces","authors":"Miranda L. Vinay","doi":"10.1038/s44287-025-00244-9","DOIUrl":"10.1038/s44287-025-00244-9","url":null,"abstract":"A study in Optics Express reports the design of a simple dielectric metasurface structure composed of lithium niobate defect disks that enhances the generation of entangled photon pairs through spontaneous parametric down-conversion.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 12","pages":"798-798"},"PeriodicalIF":0.0,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145719849","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 : 2025-11-19DOI: 10.1038/s44287-025-00243-w
Andrew Fearnside
A century after the inception of quantum theory, its unresolved interpretations continue to threaten patent validity and investors’ confidence in quantum technologies.
在量子理论诞生一个世纪之后，其未解决的解释继续威胁着专利的有效性和投资者对量子技术的信心。
{"title":"Patent law and quantum theory","authors":"Andrew Fearnside","doi":"10.1038/s44287-025-00243-w","DOIUrl":"10.1038/s44287-025-00243-w","url":null,"abstract":"A century after the inception of quantum theory, its unresolved interpretations continue to threaten patent validity and investors’ confidence in quantum technologies.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 12","pages":"790-791"},"PeriodicalIF":0.0,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145719840","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 : 2025-11-12DOI: 10.1038/s44287-025-00238-7
Haoran Zhang, Haotao Zhu, Ruihua He, Yan Zhang, Chao Ding, Lajos Hanzo, Weibo Gao
Quantum key distribution (QKD) is a cryptographic technology that supports the negotiation and sharing of private keys with unconditional security between authorized parties. As QKD scales to a global level, it must address performance limitations, high costs and practical security concerns. In this Review, we outline the key technical challenges, applications and prospective developments towards a global QKD network. Advances such as satellite-based QKD and newly developed protocols offer promising solutions for extending QKD over long distances. Field trials have progressively expanded from intercity links to larger-scale networks. Nevertheless, balancing cost–performance and security considerations will continue to challenge advanced research efforts. On the basis of the strategies addressing these obstacles, we highlight future directions that can support the efficient realization of global QKD infrastructures. Information security remains a vital concern for communications technology, and quantum key distribution may offer the highest security theoretically possible. This Review discusses the performance limitations, high costs and practical security concerns for quantum key distribution to scale to a global level.
{"title":"Towards global quantum key distribution","authors":"Haoran Zhang, Haotao Zhu, Ruihua He, Yan Zhang, Chao Ding, Lajos Hanzo, Weibo Gao","doi":"10.1038/s44287-025-00238-7","DOIUrl":"10.1038/s44287-025-00238-7","url":null,"abstract":"Quantum key distribution (QKD) is a cryptographic technology that supports the negotiation and sharing of private keys with unconditional security between authorized parties. As QKD scales to a global level, it must address performance limitations, high costs and practical security concerns. In this Review, we outline the key technical challenges, applications and prospective developments towards a global QKD network. Advances such as satellite-based QKD and newly developed protocols offer promising solutions for extending QKD over long distances. Field trials have progressively expanded from intercity links to larger-scale networks. Nevertheless, balancing cost–performance and security considerations will continue to challenge advanced research efforts. On the basis of the strategies addressing these obstacles, we highlight future directions that can support the efficient realization of global QKD infrastructures. Information security remains a vital concern for communications technology, and quantum key distribution may offer the highest security theoretically possible. This Review discusses the performance limitations, high costs and practical security concerns for quantum key distribution to scale to a global level.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 12","pages":"806-818"},"PeriodicalIF":0.0,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145719842","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 : 2025-11-12DOI: 10.1038/s44287-025-00240-z
Amal Kasry, Rachel Won
Amal Kasry, chief of the Basic Sciences, Research, Innovation and Engineering section at UNESCO’s Natural Sciences Sector, speaks with Nature Reviews Electrical Engineering about how the International Year of Quantum Science and Technology 2025 and UNESCO are working to shape a shared quantum future and close the global science divide. Amal Kasry, Chief of Section for Basic Sciences, Research, Engineering and Innovation at UNESCO’s Natural Sciences Sector, narrates how the International Year of Quantum Science and Technology 2025 and UNESCO are working to shape a shared quantum future and close the global science divide.
{"title":"Democratizing quantum science through sustained action","authors":"Amal Kasry, Rachel Won","doi":"10.1038/s44287-025-00240-z","DOIUrl":"10.1038/s44287-025-00240-z","url":null,"abstract":"Amal Kasry, chief of the Basic Sciences, Research, Innovation and Engineering section at UNESCO’s Natural Sciences Sector, speaks with Nature Reviews Electrical Engineering about how the International Year of Quantum Science and Technology 2025 and UNESCO are working to shape a shared quantum future and close the global science divide. Amal Kasry, Chief of Section for Basic Sciences, Research, Engineering and Innovation at UNESCO’s Natural Sciences Sector, narrates how the International Year of Quantum Science and Technology 2025 and UNESCO are working to shape a shared quantum future and close the global science divide.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 12","pages":"794-795"},"PeriodicalIF":0.0,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145719845","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 : 2025-11-12DOI: 10.1038/s44287-025-00226-x
Damien Querlioz, Elisa Vianello
Artificial intelligence (AI) increasingly powers safety-critical systems that demand robust, energy-efficient computation, often under conditions of data scarcity and uncertainty. Traditional AI approaches are limited in their ability to quantify confidence, leaving them vulnerable to unreliable predictions. In this Perspective, we introduce Bayesian electronics, which harnesses the intrinsic randomness of emerging nanodevices for on-device Bayesian computations. By encoding probability distributions at the hardware level, these devices naturally estimate uncertainty and reduce overhead compared with purely deterministic designs. We examine how Bayesian networks and Bayesian neural networks can be implemented in this framework to enhance sensor fusion and out-of-distribution detection. We also describe how hardware training via Markov chain Monte Carlo or Langevin dynamics yields energy-frugal sampling-based learning. Finally, we draw parallels with biological systems that are hypothesized to similarly exploit noise for probabilistic computation. By integrating device engineering, algorithmic design and system-level optimization, Bayesian electronics offers a path towards more trustworthy and adaptive AI hardware. Bayesian electronics harness the randomness of noisy sensor data to quantify uncertainty and make predictions at low computational cost. This Perspective shows how they can be realized to improve reliability and reduce energy in wearable devices, smart industrial sensors and autonomous robots
{"title":"Bayesian electronics for trustworthy artificial intelligence","authors":"Damien Querlioz, Elisa Vianello","doi":"10.1038/s44287-025-00226-x","DOIUrl":"10.1038/s44287-025-00226-x","url":null,"abstract":"Artificial intelligence (AI) increasingly powers safety-critical systems that demand robust, energy-efficient computation, often under conditions of data scarcity and uncertainty. Traditional AI approaches are limited in their ability to quantify confidence, leaving them vulnerable to unreliable predictions. In this Perspective, we introduce Bayesian electronics, which harnesses the intrinsic randomness of emerging nanodevices for on-device Bayesian computations. By encoding probability distributions at the hardware level, these devices naturally estimate uncertainty and reduce overhead compared with purely deterministic designs. We examine how Bayesian networks and Bayesian neural networks can be implemented in this framework to enhance sensor fusion and out-of-distribution detection. We also describe how hardware training via Markov chain Monte Carlo or Langevin dynamics yields energy-frugal sampling-based learning. Finally, we draw parallels with biological systems that are hypothesized to similarly exploit noise for probabilistic computation. By integrating device engineering, algorithmic design and system-level optimization, Bayesian electronics offers a path towards more trustworthy and adaptive AI hardware. Bayesian electronics harness the randomness of noisy sensor data to quantify uncertainty and make predictions at low computational cost. This Perspective shows how they can be realized to improve reliability and reduce energy in wearable devices, smart industrial sensors and autonomous robots","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 12","pages":"846-855"},"PeriodicalIF":0.0,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145719848","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 : 2025-11-11DOI: 10.1038/s44287-025-00235-w
Neuromorphic devices represent a transformative frontier in electronics, inspired by the architecture and functionality of biological neural systems.
受生物神经系统的结构和功能的启发，神经形态设备代表了电子学的变革前沿。
{"title":"Neuromorphic devices in action","authors":"","doi":"10.1038/s44287-025-00235-w","DOIUrl":"10.1038/s44287-025-00235-w","url":null,"abstract":"Neuromorphic devices represent a transformative frontier in electronics, inspired by the architecture and functionality of biological neural systems.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 11","pages":"703-703"},"PeriodicalIF":0.0,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44287-025-00235-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145480182","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 : 2025-11-10DOI: 10.1038/s44287-025-00241-y
Jiahao Liu
An article in Physical Review X reports a reinforcement learning approach for designing fault-tolerant quantum circuits for scalable, noise-resilient quantum computing.
《物理评论X》上的一篇文章报道了一种用于设计可扩展、抗噪声量子计算的容错量子电路的强化学习方法。
{"title":"Machine learning designs quantum circuits","authors":"Jiahao Liu","doi":"10.1038/s44287-025-00241-y","DOIUrl":"10.1038/s44287-025-00241-y","url":null,"abstract":"An article in Physical Review X reports a reinforcement learning approach for designing fault-tolerant quantum circuits for scalable, noise-resilient quantum computing.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 12","pages":"797-797"},"PeriodicalIF":0.0,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145719847","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 : 2025-11-07DOI: 10.1038/s44287-025-00224-z
Ming Cao, Mengbin Ye, Lorenzo Zino
Cyber–physical–human systems (CPHSs) — characterized by the organic integration of physical components, a computation and communication cyber layer, and humans — are becoming an integral part of daily life, with applications ranging from assistive robots to smart buildings and modern logistics systems. The key role of humans in these complex systems calls for a paradigm shift, from classical machine-oriented control methods to approaches that focus on the explicit modelling and control of the human layer of a CPHS. In this Review, we showcase state-of-the-art research in mathematical modelling and control of CPHSs. We discuss established control-theoretic approaches to model and control cyber–physical systems, explore two mathematical approaches to modelling human behaviour and social influence, utilizing tools from game theory and opinion dynamics, and show how these models are integrated into CPHSs. Moving to control, we focus on the potential and the challenges that are associated with the human layer. We present approaches for control on different layers, paying attention to the fact that humans can typically only be guided or nudged, and then discuss control across layers. Finally, we describe some major open questions in controlling CPHSs, including integrating data-driven approaches and bridging the gap between theoretical and experimental studies. Cyber–physical–human systems (CPHSs) integrate layers of physical components, computation and communication, and humans — in smart buildings, for example. This Review addresses the modelling and control of CPHSs, particularly of the human layer using game theory and opinion dynamics.
{"title":"Control of networked cyber–physical–human systems","authors":"Ming Cao, Mengbin Ye, Lorenzo Zino","doi":"10.1038/s44287-025-00224-z","DOIUrl":"10.1038/s44287-025-00224-z","url":null,"abstract":"Cyber–physical–human systems (CPHSs) — characterized by the organic integration of physical components, a computation and communication cyber layer, and humans — are becoming an integral part of daily life, with applications ranging from assistive robots to smart buildings and modern logistics systems. The key role of humans in these complex systems calls for a paradigm shift, from classical machine-oriented control methods to approaches that focus on the explicit modelling and control of the human layer of a CPHS. In this Review, we showcase state-of-the-art research in mathematical modelling and control of CPHSs. We discuss established control-theoretic approaches to model and control cyber–physical systems, explore two mathematical approaches to modelling human behaviour and social influence, utilizing tools from game theory and opinion dynamics, and show how these models are integrated into CPHSs. Moving to control, we focus on the potential and the challenges that are associated with the human layer. We present approaches for control on different layers, paying attention to the fact that humans can typically only be guided or nudged, and then discuss control across layers. Finally, we describe some major open questions in controlling CPHSs, including integrating data-driven approaches and bridging the gap between theoretical and experimental studies. Cyber–physical–human systems (CPHSs) integrate layers of physical components, computation and communication, and humans — in smart buildings, for example. This Review addresses the modelling and control of CPHSs, particularly of the human layer using game theory and opinion dynamics.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"3 1","pages":"32-45"},"PeriodicalIF":0.0,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145970214","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 : 2025-11-07DOI: 10.1038/s44287-025-00223-0
Yating Wan, William He, James Jaussi, Ling Liao, David Z. Pan, John E. Bowers, Haisheng Rong
Artificial intelligence, machine learning and high-performance computing workloads are pushing electrical input/output to its limits in signal reach, energy efficiency and bandwidth density, turning optics from option to necessity. Complementary metal–oxide–semiconductor-integrated silicon photonics offers a practical path forward by combining high-volume manufacturing with mature photonic building blocks. This Review presents progress across devices (on-chip lasers and semiconductor optical amplifiers, compact modulators, high-speed photodetectors, low-loss routing and efficient chip–fibre couplers), multimaterial integration (hybrid assembly, heterogeneous wafer bonding, microtransfer printing and monolithic epitaxy) and electronics co-design (digital signal processing, serializer/deserializer, stacked-driver topologies, bias control and thermal tuning) to show how total link energy is being driven towards the sub-picojoule per bit regime. We connect these advances to system architectures that are evolving from pluggables to linear-drive pluggables and co-packaged optics, and we discuss the trade-offs among bandwidth density, thermal design, yield and cost. We identify near-term bottlenecks, notably thermal pathways and manufacturing yield, and highlight technologies most likely to unlock the next jump in performance, including on-chip comb sources for dense wavelength-division multiplexing and wafer-scale 3D electronic and photonic stacks. The same platform is poised to impact optical compute input/output, sensing and quantum photonics, linking device-level innovation to system-level gains across computing and communications. Complementary metal–oxide–semiconductor-integrated silicon photonics offers a scalable path to high-bandwidth, low-energy optical interconnects for data centres and artificial intelligence/high-performance computing. This Review surveys device maturity, multimaterial and 3D integration, electronics co-design and packaging trends and maps a path towards comb-enabled dense wavelength-division multiplexing, petabit bandwidth and sub-picojoule per bit efficiency.
{"title":"Integrating silicon photonics with complementary metal–oxide–semiconductor technologies","authors":"Yating Wan, William He, James Jaussi, Ling Liao, David Z. Pan, John E. Bowers, Haisheng Rong","doi":"10.1038/s44287-025-00223-0","DOIUrl":"10.1038/s44287-025-00223-0","url":null,"abstract":"Artificial intelligence, machine learning and high-performance computing workloads are pushing electrical input/output to its limits in signal reach, energy efficiency and bandwidth density, turning optics from option to necessity. Complementary metal–oxide–semiconductor-integrated silicon photonics offers a practical path forward by combining high-volume manufacturing with mature photonic building blocks. This Review presents progress across devices (on-chip lasers and semiconductor optical amplifiers, compact modulators, high-speed photodetectors, low-loss routing and efficient chip–fibre couplers), multimaterial integration (hybrid assembly, heterogeneous wafer bonding, microtransfer printing and monolithic epitaxy) and electronics co-design (digital signal processing, serializer/deserializer, stacked-driver topologies, bias control and thermal tuning) to show how total link energy is being driven towards the sub-picojoule per bit regime. We connect these advances to system architectures that are evolving from pluggables to linear-drive pluggables and co-packaged optics, and we discuss the trade-offs among bandwidth density, thermal design, yield and cost. We identify near-term bottlenecks, notably thermal pathways and manufacturing yield, and highlight technologies most likely to unlock the next jump in performance, including on-chip comb sources for dense wavelength-division multiplexing and wafer-scale 3D electronic and photonic stacks. The same platform is poised to impact optical compute input/output, sensing and quantum photonics, linking device-level innovation to system-level gains across computing and communications. Complementary metal–oxide–semiconductor-integrated silicon photonics offers a scalable path to high-bandwidth, low-energy optical interconnects for data centres and artificial intelligence/high-performance computing. This Review surveys device maturity, multimaterial and 3D integration, electronics co-design and packaging trends and maps a path towards comb-enabled dense wavelength-division multiplexing, petabit bandwidth and sub-picojoule per bit efficiency.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"3 1","pages":"15-31"},"PeriodicalIF":0.0,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145970213","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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