Results 171 to 180 of about 806,463 (274)

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

Advanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source

Evaluating pediatric peripheral neuromuscular disorders using deep neural networks on electrodiagnostic data. [PDF]

Clin Neurophysiol Pract
Cooray GK, Nastasi L, Motan D, Deeb J.
europepmc   +1 more source

Conductance‐Dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing

Advanced Functional Materials, EarlyView.
A nanoscale SrTiO3 memristor is shown to exhibit dynamic synaptic behavior through the interaction of local electrical and global optical signals. Its photoresponse depends quantitatively on the conductance state, which evolves and decays over tunable timescales, enabling ultralow‐power, biorealistic learning mechanisms for advanced in‐memory and ...
Christoph Weilenmann, Hanglin He, Marko Mladenović, Till Zellweger, Kevin Portner, Klemens Bauer, Guillaume Bellec, Mathieu Luisier, Alexandros Emboras   +8 more
wiley   +1 more source

Designing Novel Compound Candidates Against SARS-CoV-2 Using Generative Deep Neural Networks and Cheminformatics. [PDF]

Int J Mol Sci
Li SY, Hung CM, Hung HY, Lai CW, Lee MC.
europepmc   +1 more source

Trap‐Assisted Transport and Neuromorphic Plasticity in Lead‐Free 2D Perovskites PEA2SnI4

Advanced Functional Materials, EarlyView.
An artificial retina built from lead‐free layered perovskite (PEA)2SnI4 converts light input into a persistent photocurrent and sums successive flashes over time. Micro/nanocrystals integrated on electrodes act as synapse‐like pixels that perform temporal integration directly in hardware. This in‐sensor preprocessing merges detection and computation on
Ofelia Durante, Valeria Demontis, Jonas Riisnaes Karl, Lam Hoi Tung, Sebastiano De Stefano, Daniela Marongiu, Adolfo Mazzotti, Aditya Bhardwaj, Francesco Mattana, Elisa Pili, Selene Matta, Federico Paolucci, Michele Saba, Andrea Mura, Giovanni Bongiovanni, Monica F Craciun, Saverio Russo, Antonio Di Bartolomeo   +17 more
wiley   +1 more source

Human-like monocular depth biases in deep neural networks. [PDF]

PLoS Comput Biol
Kubota Y, Fukiage T.
europepmc   +1 more source

Biomaterials‐Based Hydrogel with Superior Bio‐Mimetic Ionic Conductivity and Tissue‐Matching Softness for Bioelectronics

Advanced Functional Materials, EarlyView.
By mimicking the ion‐accelerating effect of ion channel receptors in neuron membranes, a biomaterials‐based ionic hydrogel (BIH) is developed, which offers a high ionic conductivity of 7.04 S m−1, outperforming conventional chitosan, cellulose, agarose, starch, and gelatin based ionic hydrogels.
Baojin Chen, Renjie Yu, Jiaqi Wang, Yunxiang Feng, Yujie Zhang, Yanchao Mao, Chongxin Shan, Xudong Wang   +7 more
wiley   +1 more source

Deep neural networks and deep deterministic policy gradient for early ASD diagnosis and personalized intervention in children. [PDF]

Sci Rep
Zheng Y, Ma S, Liu X, Wang L, Chen M, Yuan J, Wang H.   +6 more
europepmc   +1 more source

Novel Functional Materials via 3D Printing by Vat Photopolymerization

Advanced Functional Materials, EarlyView.
This Perspective systematically analyzes strategies for incorporating functionalities into 3D‐printed materials via Vat Photopolymerization (VP). It explores the spectrum of achievable functionalities in recently reported novel materials—such as conductive, energy‐storing, biodegradable, stimuli‐responsive, self‐healing, shape‐memory, biomaterials, and
Sergey S. Nechausov, Patrick Fesser, Boris A. Bulgakov, Ulrich S. Schubert   +3 more
wiley   +1 more source

Effective methods and framework for energy-based local learning of deep neural networks. [PDF]

Front Artif Intell
Chen H, Yang B, He F, Zhou F, Chen S, Wu C, Li F, Chua Y.   +7 more
europepmc   +1 more source