Results 141 to 150 of about 3,282,070 (234)

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

open access: yesAdvanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu   +5 more
wiley   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

open access: yesAdvanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei   +7 more
wiley   +1 more source

On reproducing kernel methods in functional statistics

open access: yes, 2018
Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Matématicas.
openaire   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

open access: yesAdvanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung   +7 more
wiley   +1 more source

Physics-constrained adaptive kernel interpolation for region-to-region acoustic transfer function: a Bayesian approach

open access: yesEURASIP Journal on Audio, Speech, and Music Processing
A kernel interpolation method for the acoustic transfer function (ATF) between regions constrained by the physics of sound while being adaptive to the data is proposed.
Juliano G. C. Ribeiro   +2 more
doaj   +1 more source

Reproducing kernel hilbert spaces and applications in finance

open access: yes, 2016
Ο βασικός στόχος της παρούσας διπλωματικής είναι η μελέτη της λειτουργίας και των βασικών ιδιοτήτων των χώρων hilbert με πυρήνα αναπαραγωγής (RKHS) αλλά και εφαρμογές αυτού στα χρηματοοικονομικά.
Tσολάκη, Nίκη
core  

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

open access: yesAdvanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh   +8 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

open access: yesAdvanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai   +3 more
wiley   +1 more source

Reproducing Kernel Functions

open access: yes, 2018
Ali Akgül, Esra Karatas Akgül
openaire   +2 more sources

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