Results 111 to 120 of about 7,211,078 (250)

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Lightweight Neural Network for Holographic Reconstruction of Pseudorandom Binary Data

Technologies
Neural networks are a state-of-the-art technology for fast and accurate holographic image reconstruction. However, at present, neural network-based reconstruction methods are predominantly applied to objects with simple, homogeneous spatial structures ...
Mikhail K. Drozdov, Dmitry A. Rymov, Andrey S. Svistunov, Pavel A. Cheremkhin, Anna V. Shifrina, Semen A. Kiriy, Evgenii Yu. Zlokazov, Elizaveta K. Petrova, Vsevolod A. Nebavskiy, Nikolay N. Evtikhiev, Rostislav S. Starikov   +10 more
doaj   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Quantifying Subsurface Weak in‐Plane Magnetization of Mixed Phase BiFeO3 by Scanning Nitrogen Vacancy Magnetometry

Advanced Functional Materials, EarlyView.
We use scanning nitrogen vacancy magnetometry to directly image the weak in‐plane magnetic moments in mixed phase BiFeO3 at the nanoscale and quantify the local magnetic moments to be 18.8±2.0 μB/nm2 in the rhombohedral‐like phase and 1.5±0.6 μB/nm2 in the well‐known non‐magnetic tetragonal‐like phase.
Lei Wang, Zhewen Xu, Yuwen Xu, Björn Josteinsson, Simon Josephy, Dawei Zhang, Yunlong Sun, Heung‐Sik Park, Jihun Kim, Kanghyun Chu, Kyung Song, Danyang Wang, Chan‐Ho Yang, Andrea Morales, Jan Seidel   +14 more
wiley   +1 more source

Medical analysis and diagnosis by neural networks [PDF]

, 2010
In its first part, this contribution reviews shortly the application of neural network methods to medical problems and characterizes its advantages and problems in the context of the medical background.
Brause, Rüdiger W.
core  

Reconfigurable optical neural networks with Plug-and-Play metasurfaces

Opto-Electronic Advances
In a very recent study, Prof. Lingling Huang and co-workers proposed and demonstrated reconfigurable optical neural networks based on cascaded metasurfaces.
Yongmin Liu, Yuxiao Li
doaj   +1 more source

Biodegradable and Biocompatible Functional Polymers for Biomedical Applications

Advanced Functional Materials, EarlyView.
Biodegradable and biocompatible functional polymers integrate electrical, mechanical, and stimuli‐responsive functionalities while enabling programmed degradation under physiological conditions. This review introduces recent advances in conductive, shape‐memory, self‐healing, photocurable, and adhesive polymer systems, emphasizing material design ...
Won Bae Han, Shuvra Mondal, Sungkeun Han, Chan‐Hwi Eom, Venkata Ramesh Naganaboina, Suk‐Won Hwang   +5 more
wiley   +1 more source

Photonics Breakthroughs 2024: Nonlinear Photonic Computing at Scale

IEEE Photonics Journal
A photonic neural network utilizes photons instead of electrons to process information, with the prospect of higher computing efficiency, lower power consumption, and reduced latency.
Hao Wang, Jianqi Hu, Andrea Morandi, Alfonso Nardi, Fei Xia, Xuanchen Li, Romolo Savo, Qiang Liu, Rachel Grange, Sylvain Gigan   +9 more
doaj   +1 more source

Multimode Oxide‐Based Optoelectronic Memtransistor for In‐Sensor Vision Processing

Advanced Functional Materials, EarlyView.
A multimode optoelectronic memtransistor (OEMT) is demonstrated for vision explainable artificial intelligence (VXAI) hardware. By integrating optical sensing, electrical masking, and non‐volatile memory, the device enables key operations required for generating saliency information.
Min Gu Lee, Geunyoung Kim, Hwa Young Kim, Do Hoon Kim, Hanchan Song, Huisu Noh, Jungwan Noh, Seungwoo Lee, Sang‐Hee Ko Park, Himchan Cho, Kyung Min Kim   +10 more
wiley   +1 more source

Light‐Induced Field‐Tunneling Synapses in Solution‐Processed Van Der Waals Heterostructures for Scalable, Retina‐Inspired Optical Sensing

Advanced Functional Materials, EarlyView.
A scalable, solution‐processed WSe2/ZrO2‐x van der Waals heterostructure realizes a light‐induced field‐tunneling synapse (LIFTS) that activates exclusively under bright illumination, emulating the photopic adaptation of the human retina at the device level.
Kijeong Nam, Jihyun Kim, Soobeen Ji, In Soo Kim, Sejin Kim, Eungseon Yeon, Do Kyung Hwang, Iva Plutnarová, Zdeněk Sofer, Sang Min Won, Joohoon Kang   +10 more
wiley   +1 more source