Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang
Terahertz (THz) communication has emerged as a pivotal research directions for the sixth-generation (6G) mobile communication systems, owing to its outstanding potential in ultra-high data rates, extremely low latency, and massive capacity. Metasurface technology, particularly reconfigurable intelligent surfaces (RIS), as a disruptive approach for electromagnetic wave manipulation, offers a novel pathway to overcome the channel propagation limitations in THz communications. It significantly accelerates the development of dynamic THz functional devices and promotes their practical application in real-world systems. This article provides a systematic review of recent advances in three interconnected areas of RIS-assisted THz communication systems: channel modeling, channel estimation, and localization. In channel modeling, innovative theoretical frameworks address near-field effects in large-scale arrays and complex propagation environments. For channel estimation, efficient methods leverage sparsity and low-rank properties, alongside artificial intelligence-driven joint optimization strategies. Localization research emphasizes high-precision near-field architectures and their integration in sophisticated systems such as integrated sensing and communication, with added analysis of performance potential. This review aims to serve as a comprehensive reference for researchers working on channel-related technologies in THz RIS-assisted communications and to stimulate further research and practical applications toward future intelligent communication systems.
{"title":"Terahertz Channel Modeling, Estimation and Localization in RIS-Assisted Systems","authors":"Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang","doi":"10.1002/aelm.202500590","DOIUrl":"https://doi.org/10.1002/aelm.202500590","url":null,"abstract":"Terahertz (THz) communication has emerged as a pivotal research directions for the sixth-generation (6G) mobile communication systems, owing to its outstanding potential in ultra-high data rates, extremely low latency, and massive capacity. Metasurface technology, particularly reconfigurable intelligent surfaces (RIS), as a disruptive approach for electromagnetic wave manipulation, offers a novel pathway to overcome the channel propagation limitations in THz communications. It significantly accelerates the development of dynamic THz functional devices and promotes their practical application in real-world systems. This article provides a systematic review of recent advances in three interconnected areas of RIS-assisted THz communication systems: channel modeling, channel estimation, and localization. In channel modeling, innovative theoretical frameworks address near-field effects in large-scale arrays and complex propagation environments. For channel estimation, efficient methods leverage sparsity and low-rank properties, alongside artificial intelligence-driven joint optimization strategies. Localization research emphasizes high-precision near-field architectures and their integration in sophisticated systems such as integrated sensing and communication, with added analysis of performance potential. This review aims to serve as a comprehensive reference for researchers working on channel-related technologies in THz RIS-assisted communications and to stimulate further research and practical applications toward future intelligent communication systems.","PeriodicalId":110,"journal":{"name":"Advanced Electronic Materials","volume":"35 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147506540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sungbin Choi, Yeong-sinn Ye, Chanho Jeong, Yujin Mun, Suyoun Oh, Tae-il Kim
Implantable strain sensors offer opportunities for continuous biomechanical monitoring, but their performance deteriorates severely once embedded in soft tissue due to mechanical shielding that suppresses strain transmission to the sensing layer. Here, we present a bio-inspired mechanical amplification (MA) strategy that restores high sensitivity in compliant environments by reengineering the deformation pathway surrounding a crack-based strain sensor. A rigid microscale MA block, positioned on the sensing layer, induces deformation asymmetry under external loading, redirecting compressive forces into localized bending and tensile strain that effectively opens nanoscale cracks. Through theoretical modeling, FEM analysis, and experimental validation, we demonstrate that the amplification magnitude is precisely tunable by MA block height, sensor embedding depth, block shape, and modulus contrast between the block and the surrounding elastomer matrix. This MA design principle enhances single sensor sensitivity by more than an order of magnitude (∼11.08×) and maintains stable performance across multi-pixel arrays, enabling high-resolution tactile mapping even when deeply embedded within soft substrates. The MA strategy thus provides a generalized framework for overcoming mechanical shielding and offers a pathway toward next-generation implantable tactile interfaces and soft bioelectronic systems requiring high sensitivity and robust performance in mechanically dissipative environments.
{"title":"Bio-Inspired Mechanical Amplification Block on Implantable Tactile Sensors","authors":"Sungbin Choi, Yeong-sinn Ye, Chanho Jeong, Yujin Mun, Suyoun Oh, Tae-il Kim","doi":"10.1002/aelm.202500874","DOIUrl":"https://doi.org/10.1002/aelm.202500874","url":null,"abstract":"Implantable strain sensors offer opportunities for continuous biomechanical monitoring, but their performance deteriorates severely once embedded in soft tissue due to mechanical shielding that suppresses strain transmission to the sensing layer. Here, we present a bio-inspired mechanical amplification (MA) strategy that restores high sensitivity in compliant environments by reengineering the deformation pathway surrounding a crack-based strain sensor. A rigid microscale MA block, positioned on the sensing layer, induces deformation asymmetry under external loading, redirecting compressive forces into localized bending and tensile strain that effectively opens nanoscale cracks. Through theoretical modeling, FEM analysis, and experimental validation, we demonstrate that the amplification magnitude is precisely tunable by MA block height, sensor embedding depth, block shape, and modulus contrast between the block and the surrounding elastomer matrix. This MA design principle enhances single sensor sensitivity by more than an order of magnitude (∼11.08×) and maintains stable performance across multi-pixel arrays, enabling high-resolution tactile mapping even when deeply embedded within soft substrates. The MA strategy thus provides a generalized framework for overcoming mechanical shielding and offers a pathway toward next-generation implantable tactile interfaces and soft bioelectronic systems requiring high sensitivity and robust performance in mechanically dissipative environments.","PeriodicalId":110,"journal":{"name":"Advanced Electronic Materials","volume":"26 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147506539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Richard Schroedter, Ahmet Samil Demirkol, Ioannis Messaris, Christian Bruchatz, Eter Mgeladze, Stefan Slesazeck, Thomas Mikolajick, Ronald Tetzlaff
Memristive crossbar arrays are a key technology for analog in-memory computing in AI accelerators and neuromorphic systems. The inherent device nonlinearities are advantageous, suppressing sneak-path currents in selector-less (1R) arrays, enabling 3D back-end-of-line integration, and ensuring read stability against the voltage-time dilemma. However, these same properties, combined with device variability, IR drop, and parasitic effects, severely challenge precise programming. Conventional amplitude-modulated write-verify algorithms are consequently slow, energy-intensive, and limited by write endurance. Here, a time-modulated write algorithm is introduced, specifically designed for analog-switching 1R crossbars. It employs a single programming voltage, varying only the write pulse duration. The algorithm leverages a compact model to estimate an initial optimal write time, which is then refined by a dynamic gain mechanism that rapidly compensates for deviations arising from non-ideal effects. The method's performance is validated through SPICE simulations of a physics-based