A Deep-learning Model for Fast Prediction of Vacancy Formation in Diverse Materials
Fuente:
arXiv
Guardado en:
| Autores principales: | Choudhary, Kamal, Sumpter, Bobby G. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
AtomGPT: Atomistic Generative Pre-trained Transformer for Forward and Inverse Materials Design
por: Choudhary, Kamal
Publicado: (2024)
por: Choudhary, Kamal
Publicado: (2024)
InterMat: Accelerating Band Offset Prediction in Semiconductor Interfaces with DFT and Deep Learning
por: Choudhary, Kamal, et al.
Publicado: (2024)
por: Choudhary, Kamal, et al.
Publicado: (2024)
The JARVIS Infrastructure is All You Need for Materials Design
por: Choudhary, Kamal
Publicado: (2025)
por: Choudhary, Kamal
Publicado: (2025)
Deciphering the Scattering of Mechanically Driven Polymers using Deep Learning
por: Ding, Lijie, et al.
Publicado: (2025)
por: Ding, Lijie, et al.
Publicado: (2025)
DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns using Generative Pre-trained Transformer
por: Choudhary, Kamal
Publicado: (2025)
por: Choudhary, Kamal
Publicado: (2025)
CHIPS-FF: Evaluating Universal Machine Learning Force Fields for Material Properties
por: Wines, Daniel, et al.
Publicado: (2024)
por: Wines, Daniel, et al.
Publicado: (2024)
Data-driven Design of High Pressure Hydride Superconductors using DFT and Deep Learning
por: Wines, Daniel, et al.
Publicado: (2023)
por: Wines, Daniel, et al.
Publicado: (2023)
ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data
por: Choudhary, Kamal, et al.
Publicado: (2022)
por: Choudhary, Kamal, et al.
Publicado: (2022)
CHIPS-TB: Evaluating Tight-Binding Models For Metals, Semiconductors, and Insulators
por: Park, In Jun, et al.
Publicado: (2025)
por: Park, In Jun, et al.
Publicado: (2025)
M-CODE: Materials Categorization via Ontology, Dimensionality and Evolution
por: Biryukov, Vsevolod, et al.
Publicado: (2026)
por: Biryukov, Vsevolod, et al.
Publicado: (2026)
Effect of Exchange-Correlation Functionals on Schottky Barriers at Si/Metal Interfaces
por: Dovale-Farelo, Viviana, et al.
Publicado: (2026)
por: Dovale-Farelo, Viviana, et al.
Publicado: (2026)
Simulation of 24,000 Electrons Dynamics: Real-Time Time-Dependent Density Functional Theory (TDDFT) with the Real-Space Multigrids (RMG)
por: Jakowski, Jacek, et al.
Publicado: (2024)
por: Jakowski, Jacek, et al.
Publicado: (2024)
Formation Energy Prediction of Material Crystal Structures using Deep Learning
por: Torlao, V., et al.
Publicado: (2024)
por: Torlao, V., et al.
Publicado: (2024)
Machine Learning Inversion from Scattering for Mechanically Driven Polymers
por: Ding, Lijie, et al.
Publicado: (2024)
por: Ding, Lijie, et al.
Publicado: (2024)
Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning
por: Choudhary, Kamal, et al.
Publicado: (2020)
por: Choudhary, Kamal, et al.
Publicado: (2020)
Efficient first principles based modeling via machine learning: from simple representations to high entropy materials
por: Li, Kangming, et al.
Publicado: (2024)
por: Li, Kangming, et al.
Publicado: (2024)
Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers
por: Ding, Lijie, et al.
Publicado: (2024)
por: Ding, Lijie, et al.
Publicado: (2024)
Accelerated prediction of dielectric functions in solar cell materials with graph neural networks
por: Ginter, Caden, et al.
Publicado: (2025)
por: Ginter, Caden, et al.
Publicado: (2025)
Scattering-Based Structural Inversion of Soft Materials via Kolmogorov-Arnold Networks
por: Tung, Chi-Huan, et al.
Publicado: (2024)
por: Tung, Chi-Huan, et al.
Publicado: (2024)
Vacancy-Enhanced $N-N$ Bonding and Deep Level Complex Defect Formation in $β-Ga_2O_3$
por: Shokri, Asiyeh, et al.
Publicado: (2026)
por: Shokri, Asiyeh, et al.
Publicado: (2026)
AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org
por: Lee, Jaehyung, et al.
Publicado: (2025)
por: Lee, Jaehyung, et al.
Publicado: (2025)
Machine Learning for Predicting Magnetization from X-ray Diffraction of Iron Oxide Nanoparticles Using Simple Physics-Based Data Generation
por: Abel, Frank M., et al.
Publicado: (2025)
por: Abel, Frank M., et al.
Publicado: (2025)
AI-ready design of realistic 2D materials and interfaces with Mat3ra-2D
por: Biryukov, Vsevolod, et al.
Publicado: (2026)
por: Biryukov, Vsevolod, et al.
Publicado: (2026)
Probing out-of-distribution generalization in machine learning for materials
por: Li, Kangming, et al.
Publicado: (2024)
por: Li, Kangming, et al.
Publicado: (2024)
Emulating 2D Materials with Magnons
por: Kaman, Bobby, et al.
Publicado: (2026)
por: Kaman, Bobby, et al.
Publicado: (2026)
Featurized Materials Dataset for Formation Energy Prediction (derived from Materials Project)
por: Torlao, Virginio
Publicado: (2025)
por: Torlao, Virginio
Publicado: (2025)
Deep learning of spectra: Predicting the dielectric function of semiconductors
por: Grunert, Malte, et al.
Publicado: (2024)
por: Grunert, Malte, et al.
Publicado: (2024)
Physically Interpretable Interatomic Potentials via Symbolic Regression and Reinforcement Learning
por: Varughese, Bilvin, et al.
Publicado: (2025)
por: Varughese, Bilvin, et al.
Publicado: (2025)
In context learning Foundation models for Materials Property Prediction with Small datasets
por: Li, Qinyang, et al.
Publicado: (2025)
por: Li, Qinyang, et al.
Publicado: (2025)
Unveiling the Optoelectronic Potential of Vacancy-Ordered Double Perovskites: A Computational Deep Dive
por: Adhikari, Surajit, et al.
Publicado: (2024)
por: Adhikari, Surajit, et al.
Publicado: (2024)
Multiscale Modeling of Vacancy-Cluster Interactions and Solute Clustering Kinetics in Multicomponent Alloys
por: Xi, Zhucong, et al.
Publicado: (2025)
por: Xi, Zhucong, et al.
Publicado: (2025)
Physical Encoding Improves OOD Performance in Deep Learning Materials Property Prediction
por: Fu, Nihang, et al.
Publicado: (2024)
por: Fu, Nihang, et al.
Publicado: (2024)
Formation of Lattice Vacancies and their Effects on Lithium-ion Transport in LiBO2 Crystals: Comparative Ab Initio Studies
por: Ziemke, Carson, et al.
Publicado: (2024)
por: Ziemke, Carson, et al.
Publicado: (2024)
Kolmogorov-Arnold Networks in Thermoelectric Materials Design
por: Fronzi, Marco, et al.
Publicado: (2025)
por: Fronzi, Marco, et al.
Publicado: (2025)
From Photons to Electrons: Accelerated Materials Discovery via Random Libraries and Automated Scanning Transmission Electron Microscopy
por: Slautin, Boris, et al.
Publicado: (2026)
por: Slautin, Boris, et al.
Publicado: (2026)
Intrinsic Direct Air Capture
por: McDannald, Austin, et al.
Publicado: (2025)
por: McDannald, Austin, et al.
Publicado: (2025)
Machine Learning Based Prediction of Polaron-Vacancy Patterns on the TiO$_2$(110) Surface
por: Birschitzky, Viktor C., et al.
Publicado: (2024)
por: Birschitzky, Viktor C., et al.
Publicado: (2024)
Understanding and Controlling V-Doping and S-Vacancy Behavior in Two-Dimensional Semiconductors- Toward Predictive Design
por: Mathela, Shreya, et al.
Publicado: (2025)
por: Mathela, Shreya, et al.
Publicado: (2025)
MoMa: A Modular Deep Learning Framework for Material Property Prediction
por: Wang, Botian, et al.
Publicado: (2025)
por: Wang, Botian, et al.
Publicado: (2025)
A Foundation Model for Material Fracture Prediction
por: Marcato, Agnese, et al.
Publicado: (2025)
por: Marcato, Agnese, et al.
Publicado: (2025)
Ejemplares similares
-
AtomGPT: Atomistic Generative Pre-trained Transformer for Forward and Inverse Materials Design
por: Choudhary, Kamal
Publicado: (2024) -
InterMat: Accelerating Band Offset Prediction in Semiconductor Interfaces with DFT and Deep Learning
por: Choudhary, Kamal, et al.
Publicado: (2024) -
The JARVIS Infrastructure is All You Need for Materials Design
por: Choudhary, Kamal
Publicado: (2025) -
Deciphering the Scattering of Mechanically Driven Polymers using Deep Learning
por: Ding, Lijie, et al.
Publicado: (2025) -
DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns using Generative Pre-trained Transformer
por: Choudhary, Kamal
Publicado: (2025)