:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Lou, Yuchen, Ganose, Alex M.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Materials Science
Accesso online:	https://arxiv.org/abs/2405.07915
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

An equivariant graph neural network for the elasticity tensors of all seven crystal systems
di: Wen, Mingjian, et al.
Pubblicazione: (2023)

Representing Born effective charges with equivariant graph convolutional neural networks
di: Kutana, Alex, et al.
Pubblicazione: (2024)

Dielectric tensor of perovskite oxides at finite temperature using equivariant graph neural network potentials
di: Kutana, Alex, et al.
Pubblicazione: (2024)

Dopability limits in Al-rich AlGaN alloys for far-UVC LEDs
di: Zhang, Ling, et al.
Pubblicazione: (2026)

Phonon predictions with E(3)-equivariant graph neural networks
di: Fang, Shiang, et al.
Pubblicazione: (2024)

AnisoGNN: graph neural networks generalizing to anisotropic properties of polycrystals
di: Hu, Guangyu, et al.
Pubblicazione: (2024)

Chemical-motif characterization of short-range order with E(3)-equivariant graph neural networks
di: Sheriff, Killian, et al.
Pubblicazione: (2024)

Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks
di: Bochkarev, Anton, et al.
Pubblicazione: (2026)

Accelerated prediction of dielectric functions in solar cell materials with graph neural networks
di: Ginter, Caden, et al.
Pubblicazione: (2025)

On the possibility of hybrid chalcogenide perovskite photovoltaics
di: Wu, Ruiqi, et al.
Pubblicazione: (2026)

Hyperbolic phonon polaritons and wave vector direction dependent dielectric tensors in anisotropic crystals
di: Fang, Yue, et al.
Pubblicazione: (2024)

Coarse-grained crystal graph neural networks for reticular materials design
di: Korolev, Vadim, et al.
Pubblicazione: (2023)

Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response
di: Patel, Ravi, et al.
Pubblicazione: (2024)

DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules
di: Du, Hongwei, et al.
Pubblicazione: (2025)

Machine learning Hubbard parameters with equivariant neural networks
di: Uhrin, Martin, et al.
Pubblicazione: (2024)

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

Giant dielectric permittivity in Nb-doped rutile crystals
di: Nuzhnyy, D., et al.
Pubblicazione: (2026)

General Learning of the Electric Response of Inorganic Materials
di: Martin, Bradley A. A., et al.
Pubblicazione: (2025)

General time-reversal equivariant neural network potential for magnetic materials
di: Yu, Hongyu, et al.
Pubblicazione: (2022)

Facet: highly efficient E(3)-equivariant networks for interatomic potentials
di: Miklaucic, Nicholas, et al.
Pubblicazione: (2025)

Microstructure sensitive recurrent neural network surrogate model of crystal plasticity
di: Atkinson, Michael D., et al.
Pubblicazione: (2025)

Broad-band ellipsometry study of the anisotropic dielectric response of YAlO3
di: Bugnon, Laurent, et al.
Pubblicazione: (2024)

Liquid-crystal-like dynamic transition in ferroelectric/dielectric superlattices
di: Gómez-Ortiz, Fernando, et al.
Pubblicazione: (2024)

Direct synthesis of single-crystal bilayer graphene on dielectric substrate
di: Tan, Zuoquan, et al.
Pubblicazione: (2022)

Modeling crystal defects using defect-informed neural networks
di: Yang, Ziduo, et al.
Pubblicazione: (2025)

Active tuning of highly anisotropic phonon polaritons in van der Waals crystal slabs by gated graphene
di: Álvarez-Pérez, Gonzalo, et al.
Pubblicazione: (2021)

Precise, efficient and flexible modeling of crystallizing elastomers based on physics-augmented neural networks
di: Friedrichs, Konrad, et al.
Pubblicazione: (2025)

Enhancing crystal structure prediction by combining computational and experimental data via graph networks
di: Qin, Chenglong, et al.
Pubblicazione: (2023)

Order induces toughness in anisotropic colloidal crystal composites
di: Vilchez, Victoria, et al.
Pubblicazione: (2024)

Graph neural network coarse-grain force field for the molecular crystal RDX
di: Lee, Brian H., et al.
Pubblicazione: (2024)

Room temperature exciton-polariton neural network with perovskite crystal
di: Opala, Andrzej, et al.
Pubblicazione: (2024)

Iterative charge equilibration for fourth-generation high-dimensional neural network potentials
di: Kocer, Emir, et al.
Pubblicazione: (2025)

Seamlessly joining length scales: From atomistic thermal graphs to anisotropic continuum conductivity
di: Ugwumadu, C., et al.
Pubblicazione: (2026)

Assessing zero-shot generalisation behaviour in graph-neural-network interatomic potentials
di: Mahmoud, Chiheb Ben, et al.
Pubblicazione: (2025)

Equivariant graph neural network surrogates for predicting the properties of relaxed atomic configurations
di: Holber, Jamie, et al.
Pubblicazione: (2025)

A finite element method for anisotropic crystal growth on surfaces
di: Garcke, Harald, et al.
Pubblicazione: (2024)

Direct derivation of anisotropic atomic displacement parameters from molecular dynamics simulations in extended solids with substitutional disorder using a neural network potential
di: Hinuma, Yoyo
Pubblicazione: (2025)

Ultrathin natural biotite crystals as a dielectric layer for van der Waals heterostructure applications
di: de Oliveira, Raphaela, et al.
Pubblicazione: (2024)

Gadolinium scandate by high-pressure sputtering for future generations of high-k dielectrics
di: Feijoo, Pedro Carlos, et al.
Pubblicazione: (2024)

Heteroepitaxial growth of highly anisotropic $Sb_{2}Se_{3}$ films on GaAs
di: Xiao, Kelly, et al.
Pubblicazione: (2025)