Pub Date : 2025-08-18DOI: 10.1038/s44287-025-00194-2
Jong-Ho Lee, Jae-Joon Kim, Cheol Seong Hwang
South Korea has a burgeoning semiconductor industry, representing about one-fifth of the country’s exports by value. In this Viewpoint, three professors at Seoul National University discuss how their departments work in close partnership with the semiconductor industry, sharing the training of graduates and engineers and collaborating on cutting-edge projects.
{"title":"Semiconductor-related research and education at Seoul National University","authors":"Jong-Ho Lee, Jae-Joon Kim, Cheol Seong Hwang","doi":"10.1038/s44287-025-00194-2","DOIUrl":"10.1038/s44287-025-00194-2","url":null,"abstract":"South Korea has a burgeoning semiconductor industry, representing about one-fifth of the country’s exports by value. In this Viewpoint, three professors at Seoul National University discuss how their departments work in close partnership with the semiconductor industry, sharing the training of graduates and engineers and collaborating on cutting-edge projects.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 10","pages":"660-664"},"PeriodicalIF":0.0,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273090","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 : 2025-08-18DOI: 10.1038/s44287-025-00204-3
Kyung Min Kim, Young-Gyu Yoon, Shinhyun Choi, Sung-Yool Choi, Seunghyup Yoo
In this Viewpoint, five professors at Korea Advanced Institute of Science and Technology (KAIST) discuss how this university, with world-class faculty, state-of-the-art research infrastructure and strong partnerships with global industry leaders, drives innovation across the entire semiconductor ecosystem — shaping the future of semiconductors in South Korea and beyond.
{"title":"Semiconductor-related research and education at KAIST","authors":"Kyung Min Kim, Young-Gyu Yoon, Shinhyun Choi, Sung-Yool Choi, Seunghyup Yoo","doi":"10.1038/s44287-025-00204-3","DOIUrl":"10.1038/s44287-025-00204-3","url":null,"abstract":"In this Viewpoint, five professors at Korea Advanced Institute of Science and Technology (KAIST) discuss how this university, with world-class faculty, state-of-the-art research infrastructure and strong partnerships with global industry leaders, drives innovation across the entire semiconductor ecosystem — shaping the future of semiconductors in South Korea and beyond.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 9","pages":"592-597"},"PeriodicalIF":0.0,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123072","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 : 2025-08-18DOI: 10.1038/s44287-025-00198-y
Choon Ki Ahn (, ), Silvia Conti, Alison Wright
Choon Ki Ahn talks to Nature Reviews Electrical Engineering about research and education in Korea University’s School of Electrical Engineering, including work to advance physical artificial intelligence (AI) for autonomous systems by pioneering new control strategies and learning under uncertainty, to create machines that can operate independently and safely in dynamic, unpredictable and often adversarial real-world environments.
Choon Ki Ahn向Nature Reviews Electrical Engineering讲述了高丽大学电气工程学院的研究和教育，包括通过开拓新的控制策略和不确定性下的学习来推进自主系统的物理人工智能（AI），以创造能够在动态，不可预测和经常对抗的现实世界环境中独立安全运行的机器。
{"title":"Research on physical AI for autonomous systems at Korea University","authors":"Choon Ki Ahn \u0000 (, ), Silvia Conti, Alison Wright","doi":"10.1038/s44287-025-00198-y","DOIUrl":"10.1038/s44287-025-00198-y","url":null,"abstract":"Choon Ki Ahn talks to Nature Reviews Electrical Engineering about research and education in Korea University’s School of Electrical Engineering, including work to advance physical artificial intelligence (AI) for autonomous systems by pioneering new control strategies and learning under uncertainty, to create machines that can operate independently and safely in dynamic, unpredictable and often adversarial real-world environments.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 11","pages":"711-712"},"PeriodicalIF":0.0,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145480167","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 : 2025-08-15DOI: 10.1038/s44287-025-00208-z
Silvia Conti
A study in Nature Machine Intelligence presents a foundation model that uses multi-modal images and progressive pretraining to enhance generalizability across diverse Earth observation tasks.
{"title":"Advancing Earth observation with a multi-modal remote sensing foundation model","authors":"Silvia Conti","doi":"10.1038/s44287-025-00208-z","DOIUrl":"10.1038/s44287-025-00208-z","url":null,"abstract":"A study in Nature Machine Intelligence presents a foundation model that uses multi-modal images and progressive pretraining to enhance generalizability across diverse Earth observation tasks.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 9","pages":"590-590"},"PeriodicalIF":0.0,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123070","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 : 2025-08-15DOI: 10.1038/s44287-025-00203-4
Huaping Liu, Di Guo, Kangyao Huang
Learning and embodiment are intertwined, resulting in a mutually reinforcing effect. Research should aim not only for learning to enhance embodiment, but also, more importantly, for embodiment to facilitate learning. Achieving synergy between these two aspects remains an ongoing challenge.
{"title":"Learning for embodiment and embodiment for learning","authors":"Huaping Liu, Di Guo, Kangyao Huang","doi":"10.1038/s44287-025-00203-4","DOIUrl":"10.1038/s44287-025-00203-4","url":null,"abstract":"Learning and embodiment are intertwined, resulting in a mutually reinforcing effect. Research should aim not only for learning to enhance embodiment, but also, more importantly, for embodiment to facilitate learning. Achieving synergy between these two aspects remains an ongoing challenge.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 10","pages":"651-653"},"PeriodicalIF":0.0,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273092","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 : 2025-08-13DOI: 10.1038/s44287-025-00205-2
Sarath Gopalakrishnan, Manish Mamidanna, Bruce Erickson
Designing marketable 6G measurement tools presents technical and logistical challenges, including generating and capturing signals in new spectrum allocations with high speed and low latency, managing wide bandwidths, and ensuring system-level synchronization. Overcoming these challenges requires advances in hardware design and implementation of instrumentation tools tailored for 6G test environments.
{"title":"Hardware design challenges for marketable 6G measurement tools","authors":"Sarath Gopalakrishnan, Manish Mamidanna, Bruce Erickson","doi":"10.1038/s44287-025-00205-2","DOIUrl":"10.1038/s44287-025-00205-2","url":null,"abstract":"Designing marketable 6G measurement tools presents technical and logistical challenges, including generating and capturing signals in new spectrum allocations with high speed and low latency, managing wide bandwidths, and ensuring system-level synchronization. Overcoming these challenges requires advances in hardware design and implementation of instrumentation tools tailored for 6G test environments.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 9","pages":"588-589"},"PeriodicalIF":0.0,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123055","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 : 2025-08-13DOI: 10.1038/s44287-025-00199-x
Inbo Sim, Kyusung Choi, Yongmin Baek, Jun Hee Choi, Jang Jo, Jiwoon Yeom, Boeun Kim, Yongjoo Cho, Heesung Lee, Hyungseok Bang, Jun-Han Han, Dong Hyuk Park, Jongchan Kim, Kyusang Lee
Augmented reality (AR) and virtual reality (VR) technologies enable interactive and immersive user experiences through head-worn devices that contain microdisplays. These microdisplays must have superior pixel density, brightness, contrast and response times, owing to the proximity of the AR glasses or VR headset to the eyes. Advanced microdisplay technologies in light engines such as liquid crystal on silicon (LCoS), organic light-emitting diodes on silicon (OLEDoS) and light-emitting diodes on silicon (LEDoS) have emerged to meet the demands of AR and VR, and are typically integrated with optical components such as free-space, freeform or waveguide combiners. In this Perspective, we explore the key requirements for AR and VR microdisplays, consider the advantages of each light-engine technology and discuss how their performance can be accurately characterized. We also examine how LCoS, OLEDoS and LEDoS technologies are integrated with complementary metal–oxide–semiconductor (CMOS) backplanes, and paired with optical combiners in AR displays, to merge virtual images with real-world scenes. Microdisplays for the glasses and headsets used in augmented reality and virtual reality must provide high pixel density, brightness and contrast, and fast response times. This Perspective explores three advanced technologies — liquid crystal on silicon, organic light-emitting diodes on silicon, and light-emitting diodes on silicon — that can meet the challenge.
{"title":"Microdisplay technologies in augmented reality and virtual reality headsets","authors":"Inbo Sim, Kyusung Choi, Yongmin Baek, Jun Hee Choi, Jang Jo, Jiwoon Yeom, Boeun Kim, Yongjoo Cho, Heesung Lee, Hyungseok Bang, Jun-Han Han, Dong Hyuk Park, Jongchan Kim, Kyusang Lee","doi":"10.1038/s44287-025-00199-x","DOIUrl":"10.1038/s44287-025-00199-x","url":null,"abstract":"Augmented reality (AR) and virtual reality (VR) technologies enable interactive and immersive user experiences through head-worn devices that contain microdisplays. These microdisplays must have superior pixel density, brightness, contrast and response times, owing to the proximity of the AR glasses or VR headset to the eyes. Advanced microdisplay technologies in light engines such as liquid crystal on silicon (LCoS), organic light-emitting diodes on silicon (OLEDoS) and light-emitting diodes on silicon (LEDoS) have emerged to meet the demands of AR and VR, and are typically integrated with optical components such as free-space, freeform or waveguide combiners. In this Perspective, we explore the key requirements for AR and VR microdisplays, consider the advantages of each light-engine technology and discuss how their performance can be accurately characterized. We also examine how LCoS, OLEDoS and LEDoS technologies are integrated with complementary metal–oxide–semiconductor (CMOS) backplanes, and paired with optical combiners in AR displays, to merge virtual images with real-world scenes. Microdisplays for the glasses and headsets used in augmented reality and virtual reality must provide high pixel density, brightness and contrast, and fast response times. This Perspective explores three advanced technologies — liquid crystal on silicon, organic light-emitting diodes on silicon, and light-emitting diodes on silicon — that can meet the challenge.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 9","pages":"634-650"},"PeriodicalIF":0.0,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123074","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 : 2025-08-12DOI: 10.1038/s44287-025-00197-z
Chunghee Kim, Dae-Gyo Seo, Yeongjun Lee, Tae-Woo Lee
Artificial nerves aim to replicate the functioning of the biological nervous system and are expected to lead to important advances in bio-interactive prosthetics. Population ageing is expected to increase the number of patients with neurological deficits or disorders worldwide and to drive increasing global demand for effective prosthetic solutions. Most current bio-interactive prostheses use traditional complementary metal–oxide–semiconductor digital computing and are primarily focused on the restoration or rehabilitation of physiological functions from an electronics perspective. These devices often place little emphasis on neurological compatibility. By contrast, artificial nerve systems consisting of neuromorphic devices offer a promising and neurologically compatible method to either bypass damaged biological nerves or act as an interface between biological nerves and a prosthesis. Artificial nerves are designed to restore lost sensory and motor functions in a similar way to biological nerves by providing biologically plausible and simplified signal processing. Moreover, artificial nerves provide power-efficient control of prostheses and improve users’ interactions with their environment. This Review explores the achievements and limitations of conventional bio-interactive prostheses and describes advances in artificial nerve systems that aim to increase functionality through the seamless integration and neuromorphic processing of biological signals. This Review provides an overview of non-biomimetic, biomimetic and neuromorphic approaches to bio-interactive prosthetics. Kim et al. highlight the advantages and challenges of artificial nerve systems for reducing computational complexity, improving biocompatibility and restoring natural sensory and motor functions in patients with neurological deficits.
{"title":"Artificial nerve systems for use in bio-interactive prostheses","authors":"Chunghee Kim, Dae-Gyo Seo, Yeongjun Lee, Tae-Woo Lee","doi":"10.1038/s44287-025-00197-z","DOIUrl":"10.1038/s44287-025-00197-z","url":null,"abstract":"Artificial nerves aim to replicate the functioning of the biological nervous system and are expected to lead to important advances in bio-interactive prosthetics. Population ageing is expected to increase the number of patients with neurological deficits or disorders worldwide and to drive increasing global demand for effective prosthetic solutions. Most current bio-interactive prostheses use traditional complementary metal–oxide–semiconductor digital computing and are primarily focused on the restoration or rehabilitation of physiological functions from an electronics perspective. These devices often place little emphasis on neurological compatibility. By contrast, artificial nerve systems consisting of neuromorphic devices offer a promising and neurologically compatible method to either bypass damaged biological nerves or act as an interface between biological nerves and a prosthesis. Artificial nerves are designed to restore lost sensory and motor functions in a similar way to biological nerves by providing biologically plausible and simplified signal processing. Moreover, artificial nerves provide power-efficient control of prostheses and improve users’ interactions with their environment. This Review explores the achievements and limitations of conventional bio-interactive prostheses and describes advances in artificial nerve systems that aim to increase functionality through the seamless integration and neuromorphic processing of biological signals. This Review provides an overview of non-biomimetic, biomimetic and neuromorphic approaches to bio-interactive prosthetics. Kim et al. highlight the advantages and challenges of artificial nerve systems for reducing computational complexity, improving biocompatibility and restoring natural sensory and motor functions in patients with neurological deficits.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 10","pages":"665-682"},"PeriodicalIF":0.0,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145273091","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 : 2025-08-07DOI: 10.1038/s44287-025-00196-0
W.-Y. Woon, A. Kasperovich, J.-R. Wen, K. K. Hu, M. Malakoutian, J.-H. Jhang, S. Vaziri, I. Datye, C. C. Shih, J. F. Hsu, X. Y. Bao, Y. Wu, M. Nomura, S. Chowdhury, S. Sandy Liao
As transistor scaling approaches nanometre and even atomic scales, 3D stacking has become a critical enabler for advancement in the semiconductor industry, especially in high-performance computing and artificial intelligence (AI) applications. However, 3D integration introduces substantial thermal management challenges related to the increased power density and constrained heat dissipation pathways, particularly through low thermal conductivity interlayer dielectrics and complex interfaces. In this Review, we discuss state-of-the-art thermal management materials, covering their process compatibility, the critical integration challenges and the need for improved methods to enhance heat transport across interfaces. Advanced thermal characterization metrologies are introduced to highlight the need for non-destructive in-line metrologies. Finally, we provide a road map that outlines future research directions for material growth, integration and characterization methodologies to enable viable thermal solutions for 3D integration and beyond. The shrinking dimensions, the increased structural complexity and the 3D stacking of silicon-based semiconductor devices are intensifying challenges in thermal dissipation. This Review explores thermal management materials, integration challenges and characterization methods, and proposes a road map for efficient heat dissipation solutions in 3D integration.
{"title":"Thermal management materials for 3D-stacked integrated circuits","authors":"W.-Y. Woon, A. Kasperovich, J.-R. Wen, K. K. Hu, M. Malakoutian, J.-H. Jhang, S. Vaziri, I. Datye, C. C. Shih, J. F. Hsu, X. Y. Bao, Y. Wu, M. Nomura, S. Chowdhury, S. Sandy Liao","doi":"10.1038/s44287-025-00196-0","DOIUrl":"10.1038/s44287-025-00196-0","url":null,"abstract":"As transistor scaling approaches nanometre and even atomic scales, 3D stacking has become a critical enabler for advancement in the semiconductor industry, especially in high-performance computing and artificial intelligence (AI) applications. However, 3D integration introduces substantial thermal management challenges related to the increased power density and constrained heat dissipation pathways, particularly through low thermal conductivity interlayer dielectrics and complex interfaces. In this Review, we discuss state-of-the-art thermal management materials, covering their process compatibility, the critical integration challenges and the need for improved methods to enhance heat transport across interfaces. Advanced thermal characterization metrologies are introduced to highlight the need for non-destructive in-line metrologies. Finally, we provide a road map that outlines future research directions for material growth, integration and characterization methodologies to enable viable thermal solutions for 3D integration and beyond. The shrinking dimensions, the increased structural complexity and the 3D stacking of silicon-based semiconductor devices are intensifying challenges in thermal dissipation. This Review explores thermal management materials, integration challenges and characterization methods, and proposes a road map for efficient heat dissipation solutions in 3D integration.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 9","pages":"598-613"},"PeriodicalIF":0.0,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123151","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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