Results 91 to 100 of about 8,521,646 (245)

Beyond the Embedded Atom Interatomic Potential

open access: yes, 1988
We briefly discuss some of the advantages and limitations of using embedded atom interatomic potentials for simulating the static configuration and dynamics of lattice defects.
R. Pasianot, Eduardo J. Savino
core   +1 more source

Construction of Sabatier Volcanoes for CO2 Hydrogenation to C1‐2 Oxygenates Using Data‐Efficient Machine Learning

open access: yesAdvanced Science, EarlyView.
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley   +1 more source

GPUMD 4.0: A high‐performance molecular dynamics package for versatile materials simulations with machine‐learned potentials

open access: yesMaterials Genome Engineering Advances
This paper provides a comprehensive overview of the latest stable release of the graphics processing units molecular dynamics (GPUMD) package, GPUMD 4.0. We begin with a brief review of its development history, starting from the initial version.
Ke Xu   +54 more
doaj   +1 more source

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

open access: yesAdvanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su   +13 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

High-quality interatomic potential for Li+ cente ·He

open access: yes, 2001
CCSD(T)/aug-cc-pVQZ and CCSD(T)/aug-cc-pV5Z methods have been employed to obtain accurate interatomic potentials for Li+ . He, from which spectroscopic parameters are, derived.
Jerome Lozeille (16089428)   +14 more
core   +1 more source

Ultra‐Radiostable Covalent Conformationally Interlocked Networks Enabling a Universal Radiometal‐Labeling Platform for Cancer Radioembolization

open access: yesAdvanced Science, EarlyView.
Conjugated poly(imide dioxime)‐based microspheres establish a radiometal coordination‐driven conformational interlocked network with ultra‐high radiostability. This platform enables low‐temperature, multi‐radionuclide labeling for SPECT/PET/MRI imaging and radionuclide therapy. Mechanistic insights from EXAFS and DFT reveal enhanced stability, while in
Xiao Xu   +10 more
wiley   +1 more source

PbTiO3 Second-Principles Interatomic potential

open access: yes
Files related to the second-principles interatomic potential of PbTiO3. The related paper is not published yet, only the validation passeport is available here at this stage.
Ghosez, Philippe, Bastogne, Louis
core   +1 more source

Halide Perovskite: A Rich Source of Thermal Insulator

open access: yesAdvanced Science, EarlyView.
Halide perovskites exhibit ultralow thermal conductivity driven by intrinsic lattice softness and strong anharmonicity, falling below conventional defect‐engineering limits. Weak metavalent bonding, A‐site rattling, and dynamic octahedral tilting drive phonon scattering to the Ioffe–Regel limit, where wave‐like tunneling replaces particle‐like ...
Haolin Ye   +3 more
wiley   +1 more source

Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data

open access: yesMachine Learning: Science and Technology
The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces.
Bowen Han, Yongqiang Cheng
doaj   +1 more source

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