Copertina

Unveiling the critical factors in crystal structure graph representation: a comparative analysis using streamlined MLPSets frameworks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Du, Hongwei, Wang, Hong
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Materials Science
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

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

Con-CDVAE: A method for the conditional generation of crystal structures
di: Ye, Cai-Yuan, et al.
Pubblicazione: (2024)

A probabilistic framework for crystal structure denoising, phase classification, and order parameters
di: Kwon, Hyuna, et al.
Pubblicazione: (2025)

Machine learning the screening factor in the soft bond valence approach for rapid crystal structure estimation
di: Kameda, Keisuke, et al.
Pubblicazione: (2024)

Unveiling the early stage evolution of local atomic structures in the crystallization process of a metallic glass
di: Ma, Lin, et al.
Pubblicazione: (2024)

Universal Machine Learning Interatomic Potentials are Ready for Solid Ion Conductors
di: Du, Hongwei, et al.
Pubblicazione: (2025)

Revisiting the matrix elements of the position operator in the crystal momentum representation
di: Si, M. S., et al.
Pubblicazione: (2025)

PRISM: Periodic Representation with multIscale and Similarity graph Modelling for enhanced crystal structure property prediction
di: Solé, Àlex, et al.
Pubblicazione: (2025)

Training models using forces computed by stochastic electronic structure methods
di: Ceperley, David M., et al.
Pubblicazione: (2023)

Discovery of highly anisotropic dielectric crystals with equivariant graph neural networks
di: Lou, Yuchen, et al.
Pubblicazione: (2024)

Acceleration of crystal structure relaxation with Deep Reinforcement Learning
di: Trukhan, Elena, et al.
Pubblicazione: (2025)

Deep learning generative model for crystal structure prediction
di: Luo, Xiaoshan, et al.
Pubblicazione: (2024)

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

On the ambient conditions crystal structure of AgSbTe2
di: Sun, Baihong, et al.
Pubblicazione: (2025)

Determination of bonding radii from small-molecule crystal structures
di: Šidlauskaitė, Eglė, et al.
Pubblicazione: (2026)

The effect of pressure in the crystal and magnetic structure of FeWO4
di: Fabelo, Oscar, et al.
Pubblicazione: (2026)

Stability of Wigner crystals and Mott insulators in twisted moiré structures
di: Erkensten, Daniel, et al.
Pubblicazione: (2024)

Unveiling the interplay of magnetic order and electronic band structure on the evolution of anomalous Hall effect in MnPtGa single crystal
di: Dwari, Gourav, et al.
Pubblicazione: (2025)

A symmetry-oriented crystal structure prediction method for crystals with rigid bodies
di: Zhang, Qi, et al.
Pubblicazione: (2024)

Re-understanding of the deformation potential constant in the single crystal silicon
di: Sun, Feng, et al.
Pubblicazione: (2023)

Unveiling the thermal transport mechanism in compressed plastic crystals assisted by deep potential
di: Qin, Yangjun, et al.
Pubblicazione: (2025)

Unveiling defect motifs in amorphous GeSe using machine learning interatomic potentials
di: Moon, Minseok, et al.
Pubblicazione: (2025)

Mapping the intrinsic photocurrent streamlines through micromagnetic heterostructure devices
di: Mayes, Morgan, et al.
Pubblicazione: (2020)

Deformation band patterns and dislocation structures in finite strain crystal viscoplasticity
di: Scherer, Jean-Michel
Pubblicazione: (2025)

Unveiling the effect of Ni on the formation and structure of Earth's inner core
di: Sun, Yang, et al.
Pubblicazione: (2023)

Local structural features elucidate crystallization of complex structures
di: Martirossyan, Maya M., et al.
Pubblicazione: (2024)

Accelerating structure search using atomistic graph-based classifiers
di: Slavensky, Andreas Møller, et al.
Pubblicazione: (2024)

Exciton fine structure in CdSe nanoplatelets using a quasi-2D screened configuration-interaction framework
di: Patra, Sumanti, et al.
Pubblicazione: (2026)

Illuminating the property space in crystal structure prediction using Quality-Diversity algorithms
di: Wolinska, Marta, et al.
Pubblicazione: (2024)

Isomorph invariance of classical crystals' structure and dynamics
di: Albrechtsen, Dan E., et al.
Pubblicazione: (2014)

Optimized growth of large-size, high quality $\text{ZrTe}_5$ single crystals enabling clear quantum oscillations in electrical transport
di: Du, Hong, et al.
Pubblicazione: (2026)

Shotgun crystal structure prediction using machine-learned formation energies
di: Liu, Chang, et al.
Pubblicazione: (2023)

AlphaCrystal-II: Distance matrix based crystal structure prediction using deep learning
di: Song, Yuqi, et al.
Pubblicazione: (2024)

Data-driven prediction of structure of metal-organic frameworks
di: Yakovenko, Elizaveta, et al.
Pubblicazione: (2024)

Mathematical crystal chemistry II: Random search for ionic crystals and analysis on oxide crystals registered in ICSD
di: Koshoji, Ryotaro
Pubblicazione: (2025)

The Fe-N system: crystal structure prediction, phase stability, and mechanical properties
di: Bao, Ergen, et al.
Pubblicazione: (2024)

Two-dimensional photonic crystal cavities in ZnSe quantum well structures
di: Qiao, Siqi, et al.
Pubblicazione: (2024)

Evolution of radiation-induced damage in nuclear graphite -- a comparative structural and microstructural study
di: Wilczopolska, Magdalena, et al.
Pubblicazione: (2025)

Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions
di: Riebesell, Janosh, et al.
Pubblicazione: (2023)