Results 161 to 170 of about 751,349 (293)

Copper‐based Materials for Photo and Electrocatalytic Process: Advancing Renewable Energy and Environmental Applications

Advanced Functional Materials, EarlyView.
Cu‐based catalysts as a cornerstone in advancing sustainable energy technologies are fully reviewed in this manuscript, highlighting their potential in photo‐ and electrocatalysis. It includes metallic copper, copper oxides, copper sulfides, copper halide perovskites, copper‐based metal–organic frameworks (MOFs), and covalent organic frameworks (COFs),
Jéssica C. de Almeida, Yanjie Wang, Thais A. Rodrigues, Paulo H. H. Nunes, Vagner R. de Mendonça, Paulo H. E. Falsetti, Leticia V. Savazi, Tao He, Alexandra V. Bardakova, Aida V. Rudakova, Jie Tian, Alexei V. Emeline, Osmando F. Lopes, Antonio Otavio T. Patrocínio, Jia Hong Pan, Caue Ribeiro, Detlef W. Bahnemann   +16 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Detection of calibration drift in clinical prediction models to inform model updating. [PDF]

J Biomed Inform, 2020
Davis SE, Greevy RA, Lasko TA, Walsh CG, Matheny ME.   +4 more
europepmc   +1 more source

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

The Need to Prioritize Model-Updating Processes in Clinical Artificial Intelligence (AI) Models: Protocol for a Scoping Review.

JMIR Res Protoc, 2023
Otokiti AU, Ozoude MM, Williams KS, Sadiq-Onilenla RA, Ojo SA, Wasarme LB, Walsh S, Edomwande M.   +7 more
europepmc   +1 more source

Double Helical Plasmonic Antennas

Advanced Functional Materials, EarlyView.
Plasmonic double helical antennas funnel circularly polarized light to the nanoscale, offering strong chiroptical interaction and directional light emission. Extending a single helix design tool, this study combines numerical modeling with experimental validation, revealing large, broadband dissymmetry factors in the visible range.
Aleksei Tsarapkin, Luka Zurak, Krzysztof Maćkosz, Lorenz Löffler, Victor Deinhart, Ivo Utke, Thorsten Feichtner, Katja Höflich   +7 more
wiley   +1 more source

Structural damage analysis using finite element model updating enhanced by response surface methodology. [PDF]

Sci Rep
Mobarhan Zad S, Rahai M, Ranjbar S, Moghadas Nejad F.   +3 more
europepmc   +1 more source

Advanced Flame Retardant Strategies and Fire Performance Assessment for Safer Photovoltaics in Buildings: A Two‐Part Review

Advanced Functional Materials, EarlyView.
The integration of photovoltaic (PV) systems into building structures introduces distinct fire risks with critical implications for occupant safety. This review examines the key fire hazards associated with PV implementation and explores mitigation strategies, including flame‐retardant additives.
Florian Ollagnon, Olaia Aurrekoetxea‐Arratibel, Emma Gottis, Heng‐Yu Li, Xabier Olano‐Azkune, Matthieu Despeisse, Antonin Faes, Christophe Ballif   +7 more
wiley   +1 more source

Tracking the Impact of Age and Dimensional Shifts on Situation Model Updating During Narrative Text Comprehension. [PDF]

J Eye Mov Res
Campos-Rojas C, Ibáñez-Orellana R.
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source