Results 101 to 110 of about 57,318 (251)
Further advances in applications can be anticipated through the development of unique and functional materials beyond conventional alloys. Nitrogen enables tailor‐made orbital textures in various transition‐metal hosts, paving the way for devices ranging from spintronics memory to artificial intelligence hardware.
Prabhat Kumar +3 more
wiley +1 more source
Neuromorphic devices for extreme environments are interpreted through the physical states that store and process information. Radiation, temperature extremes, and vacuum can perturb vacancies, filaments, trapped charges, polarization, interfaces, and readout signals.
Taehyun Park +7 more
wiley +1 more source
Bistable Isochoric Chiral Metamaterials with Reprogrammable Multiaxial Responses
An isochoric bistable rotational unit cell enables in situ modification of internal contact conditions post‐fabrication, without altering the global envelope dimensions of the surrounding architecture. By selectively switching between open and closed states, the tessellated chiral metamaterial can reprogram its volumetric response, including bulk ...
Shujia Chen +3 more
wiley +1 more source
Efficient Magnetization Switching Driven by Orbital Torque in Light 3d Transition‐Metal Nitrides
Efficient magnetization switching is demonstrated through orbital torque generated from light 3d transition‐metal nitride. Transition‐metal nitrides are established as effective sources of orbital angular momentum for current‐induced switching, highlighting their potential for low‐power next‐generation orbitronic devices beyond conventional heavy‐metal‐
Gaurav K. Shukla +3 more
wiley +1 more source
Material Coupling in Hybrid Neuromorphic Devices: From Fundamentals to System‐Level Applications
Hybrid neuromorphic devices utilize heterointerfaces between emerging semiconductors, where charge transfer and trapping, ion or defect modulation, and photogating are translated into synaptic functions. This paper discusses coupling strategies that tailor interfacial electronic and ionic properties in organic semiconductors, metal oxides, two ...
Minsu So +5 more
wiley +1 more source
Biodegradable Conductors for Implantable and Wearable Transient Bioelectronics
Biodegradable conductors are essential building blocks for transient bioelectronics, enabling temporary sensing, stimulation, and energy transfer while eliminating the need for device retrieval. This review summarizes biodegradable metals, conducting polymers, ionic conductors, and conductive composites, highlighting degradation mechanisms, material ...
Yicheng Zhu, Yijun Liu, Naoji Matsuhisa
wiley +1 more source
Advancing Human Skin Equivalents: The Crucial Role of Neurovascular Integration
This review discusses the importance of integrating vascular and peripheral nerve systems into human skin equivalents (HSEs) to better recapitulate native skin physiology. Recent advances in vascularized, innervated, and neurovascularized HSEs are highlighted, together with emerging bioengineering strategies, current challenges, and future ...
Hao Wu +4 more
wiley +1 more source
Spatial organization of tissue-resident memory T cells
Tissue-resident memory T (TRM) cells durably reside in peripheral tissues, poised to deliver rapid local immune protection. TRM cells are found in most organs, and they are a core component of immunological memory, complementing circulating memory T cell populations.
Thomas N, Burn, Laura K, Mackay
openaire +2 more sources
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source

