Results 211 to 220 of about 31,155,536 (302)

Machine Learning for Data-Driven Discovery

JACC: Cardiovascular Imaging, 2019
Partho P, Sengupta, Sirish, Shrestha
openaire   +2 more sources

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 more
wiley   +1 more source

Roadmap for inferring metabolic regulation using multiomics, machine learning, and genome-scale modeling. [PDF]

NPJ Metab Health Dis
Schildcrout R, Rhoads N, Chandrasekaran S.   +2 more
europepmc   +1 more source

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

Advanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar, Haider Abbas, Muhammad Rabeel, Honggyun Kim, Ghulam Dastgeer, Muhammad Nasim, Furqan Zahoor, Yawar Abbas, Waqas Ahmad, Deok‐kee Kim   +9 more
wiley   +1 more source

A hybrid car-following behavior prediction framework for snowy weather based on stacking ensemble learning. [PDF]

PLoS One
Luo Z, Geng F, Zhang Z.
europepmc   +1 more source

Kinetics‐Controlled Architecture of Binder‐Free Organic Electrodes for Enhanced Ion Transport

Advanced Functional Materials, EarlyView.
Pulse reverse electrodeposition controls nucleation and growth to create hierarchically porous Py‐derived oligomeric electrodes with enhanced ionic accessibility and reduced transport resistance. The resulting binder‐free architectures translate these transport advantages into practical sodium‐storage functionality.
Satendra Kumar, María del Carmen Giménez‐López   +1 more
wiley   +1 more source

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source

Electrically Induced Phase Transition and Synaptic Functionality in MoTe2/Graphene Memristors

Advanced Functional Materials, EarlyView.
An electrically induced reversible 2H ↔ 1T′ phase transition is demonstrated in a vertical Au/Ti/MoTe2/graphene memristor with a laterally contacted graphene electrode. Resistive switching proceeds through a compositionally invariant amorphous/2H ↔ amorphous/1T′ transformation, in which a self‐formed amorphous MoTe2 interfacial region is proposed to ...
Chien‐Hua Wang, Mu‐Pai Lee, Jhen‐Dong Tsai, Liang‐Ying Hsieh, Jui‐Yuan Chen, Chun‐Wei Huang, Yen‐Fu Lin, Wen‐Wei Wu   +7 more
wiley   +1 more source

Applications of Artificial Intelligence-Driven Chatbots in University Level Dental Education: A Systematic Review. [PDF]

Int J Dent
B K R, Hashim R, P S K, M A V, Luke AM, C U.   +5 more
europepmc   +1 more source

Optimizing NiMo Electrocatalyst Coatings for Hydrogen Evolution in Alkaline Electrolysis With The Machine Learning‐Guided Autonomous Platform CatBot

Advanced Functional Materials, EarlyView.
This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio, Jonas Elsborg, Elif Coşkun, Andreas Burger, Pradipkumar Manubhai Leuaa, Thu Pham Anh Phan, Jin Hyun Chang, Christodoulos Chatzichristodoulou   +7 more
wiley   +1 more source