Results 81 to 90 of about 8,144,777 (299)
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
This paper presents a comprehensive systematic review examining the application of augmented reality (AR) and sensor technologies for visualizing ionizing radiation in virtual training environments.
Rajiv Khadka +3 more
doaj +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
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh +5 more
wiley +1 more source
Topological insulator–metamaterials integrated with electrically driven terahertz quantum cascade lasers enable parity‐dependent harmonic generation. Bulk‐dominated Bi2Se3 favors third‐harmonic emission at 9.96 THz, whereas topological‐surface‐state‐dominated Bi2Se3, Bi2Te3, and (Bi,Sb)2Te3 generate strong second harmonics near 6.5 THz.
Alessandra Di Gaspare +9 more
wiley +1 more source
Distributed computing methodology for training neural networks in an image-guided diagnostic application [PDF]
Distributed computing is a process through which a set of computers connected by a network is used collectively to solve a single problem. In this paper, we propose a distributed computing methodology for training neural networks for the detection of ...
Plagianakos, V.P. +2 more
core +1 more source
Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng +24 more
wiley +1 more source
The tutoring role of mentors working with adults and elderly people with learning disabilities using virtual environments [PDF]
This article outlines the potential of virtual training environments in the rehabilitation of adults and elderly people with learning disabilities. Before such virtual training environments are developed, tutoring roles for mentors working with adults ...
Brown, DJ, Standen, PJ
core
Dense tactile streams from across the humanoid body converge on collide in a central wiring and data bottleneck. By relocating computation closer to and then into the skin itself, near‐ and in‐sensor architectures, together with neuromorphic computing, chart a path toward perception‐native electronic skin, in which the conversion of stimulus into ...
Mijin Kim +6 more
wiley +1 more source
Still navigating across the Atlantic: a view of a virtual reference service for academic libraries. [PDF]
This paper presents the Via Virtual Project, a virtual reference service designed by the University of Cadiz as a strategy in response to the new educational model in Europe.
Fernández Alfaro, Leonor +4 more
core

