Imagen de Portada

Machine learning method to determine concentrations of structural defects in irradiated materials

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Johnson, Landon, Malone, Walter, Rizk, Jason, Chen, Renai, Gibson, Tammie, Cooper, Michael W. D., Craven, Galen T.
Formato:	Preprint
Publicado:	2025
Materias:	Materials Science
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Molecular heat transport across a time-periodic temperature gradient
por: Chen, Renai, et al.
Publicado: (2024)

Neuromorphic heat transport effects in a molecular junction
por: Chen, Renai, et al.
Publicado: (2025)

Heat Transport Hysteresis Generated through Frequency Switching of a Time-Dependent Temperature Gradient
por: Chen, Renai, et al.
Publicado: (2025)

The effect of temperature oscillations on energy storage rectification in harmonic systems
por: Chen, Renai, et al.
Publicado: (2024)

Atomistic modeling of uranium monocarbide with a machine learning interatomic potential
por: Alzate-Vargas, Lorena, et al.
Publicado: (2025)

Toward machine learning interatomic potentials for modeling uranium mononitride
por: Alzate-Vargas, Lorena, et al.
Publicado: (2024)

Machine-learning structural reconstructions for accelerated point defect calculations
por: Mosquera-Lois, Irea, et al.
Publicado: (2024)

Optical and Transport Properties of Plasma Mixtures from Ab Initio Molecular Dynamics
por: White, Alexander J., et al.
Publicado: (2024)

Machine learning for structure-guided materials and process design
por: Morand, Lukas, et al.
Publicado: (2023)

Machine-learning interatomic potential for AlN for epitaxial simulation
por: Taormina, Nicholas, et al.
Publicado: (2025)

Quantum bath augmented stochastic nonequilibrium atomistic simulations for molecular heat conduction
por: Chen, Renai, et al.
Publicado: (2023)

Machine learning driven search of hydrogen storage materials
por: Banerjee, Tanumoy, et al.
Publicado: (2025)

Parameter-free prediction of irradiation defect structures in tungsten at room temperature using stochastic cluster dynamics
por: He, Sicong, et al.
Publicado: (2025)

Screening of material defects using universal machine-learning interatomic potentials
por: Berger, Ethan, et al.
Publicado: (2025)

Self-organized defect-phases along dislocations in irradiated alloys
por: Saunders, N., et al.
Publicado: (2026)

Machine-learned models for magnetic materials
por: Leszczyński, Paweł, et al.
Publicado: (2023)

Going beyond density functional theory accuracy: Leveraging experimental data to refine pre-trained machine learning interatomic potentials
por: Gumber, Shriya, et al.
Publicado: (2025)

Machine learned potential for defected single layer hexagonal boron nitride
por: Janisch, John, et al.
Publicado: (2025)

Machine-learning potential for phonon transport in AlN with defects in multiple charge states
por: Dou, Ying, et al.
Publicado: (2024)

Points defects produced by irradiation: influence of boundary conditions on their biased elimination
por: Bocquet, Jean-louis
Publicado: (2024)

A hundred years of consciousness: “a long training in absurdity”
por: Galen Strawson
Publicado: (2019)

Symmetry breaking structural relaxation and optical transitions of native defects and carbon impurities in LiGa$_5$O$_8$
por: Dabsamut, Klichchupong, et al.
Publicado: (2026)

Diamond-defect engineering of NV- centers using ion beam irradiation
por: Toural, J. L. Sánchez, et al.
Publicado: (2024)

Atomic and electronic structure of defects in hBN: enhancing single-defect functionalities
por: Qiu, Z., et al.
Publicado: (2021)

Site-projected Thermal Conductivity: Application to defects, interfaces, and homogeneously disordered materials
por: Gautam, A., et al.
Publicado: (2024)

"One defect, one potential" strategy for accurate machine learning prediction of defect phonons
por: Zhou, Junjie, et al.
Publicado: (2025)

Machine learning descriptors for predicting the high temperature oxidation of refractory complex concentrated alloys
por: Bejjipurapu, Akhil, et al.
Publicado: (2025)

Fast low-temperature irradiation creep driven by athermal defect dynamics
por: Feichtmayer, Alexander, et al.
Publicado: (2024)

Efficient first principles based modeling via machine learning: from simple representations to high entropy materials
por: Li, Kangming, et al.
Publicado: (2024)

First-principles computational methods for quantum defects in two-dimensional materials: A perspective
por: Seo, Hosung, et al.
Publicado: (2024)

Atomistic insights into Cu segregation effects on irradiation-induced defect dynamics in medium-entropy alloys
por: Rahman, Kazi Tawseef, et al.
Publicado: (2024)

Symbolic regression for defect interactions in 2D materials
por: Lazarev, Mikhail, et al.
Publicado: (2025)

Machine‐learning‐assisted intelligent synthesis of UiO‐66(Ce): Balancing the trade‐off between structural defects and thermal stability for efficient hydrogenation of Dicyclopentadiene
por: Jing Lin, et al.
Publicado: (2024)

Probing out-of-distribution generalization in machine learning for materials
por: Li, Kangming, et al.
Publicado: (2024)

Tunable ferroelectric topological defects on 2D topological surfaces: strain engineering skyrmion-like polar structures in 2D materials
por: Xu, Bo, et al.
Publicado: (2022)

Machine learning Hamiltonian enables scalable and accurate defect calculations: The case of oxygen vacancies in amorphous SiO$_2$
por: Dai, Zhenxing, et al.
Publicado: (2026)

A method for the automatic generation of a minimal basis set of structural templates for material phase-space exploration
por: Annweiler, Caja, et al.
Publicado: (2024)

Machine learning assisted screening of metal binary alloys for anode materials
por: Shi, Xingyue, et al.
Publicado: (2024)

Machine learning for predicting ultralow thermal conductivity and high ZT in complex thermoelectric materials
por: Hao, Yuzhou, et al.
Publicado: (2024)

Physics guided dual Self-supervised learning for structure-based materials property prediction
por: Fu, Nihang, et al.
Publicado: (2024)