:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Choudhary, Kamal, Sumpter, Bobby G.
Format:	Preprint
Published:	2022
Subjects:	Materials Science
Online Access:	https://arxiv.org/abs/2205.08366
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AtomGPT: Atomistic Generative Pre-trained Transformer for Forward and Inverse Materials Design
by: Choudhary, Kamal
Published: (2024)

InterMat: Accelerating Band Offset Prediction in Semiconductor Interfaces with DFT and Deep Learning
by: Choudhary, Kamal, et al.
Published: (2024)

The JARVIS Infrastructure is All You Need for Materials Design
by: Choudhary, Kamal
Published: (2025)

Deciphering the Scattering of Mechanically Driven Polymers using Deep Learning
by: Ding, Lijie, et al.
Published: (2025)

CHIPS-FF: Evaluating Universal Machine Learning Force Fields for Material Properties
by: Wines, Daniel, et al.
Published: (2024)

Data-driven Design of High Pressure Hydride Superconductors using DFT and Deep Learning
by: Wines, Daniel, et al.
Published: (2023)

DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns using Generative Pre-trained Transformer
by: Choudhary, Kamal
Published: (2025)

ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data
by: Choudhary, Kamal, et al.
Published: (2022)

CHIPS-TB: Evaluating Tight-Binding Models For Metals, Semiconductors, and Insulators
by: Park, In Jun, et al.
Published: (2025)

M-CODE: Materials Categorization via Ontology, Dimensionality and Evolution
by: Biryukov, Vsevolod, et al.
Published: (2026)

Machine Learning Inversion from Scattering for Mechanically Driven Polymers
by: Ding, Lijie, et al.
Published: (2024)

Simulation of 24,000 Electrons Dynamics: Real-Time Time-Dependent Density Functional Theory (TDDFT) with the Real-Space Multigrids (RMG)
by: Jakowski, Jacek, et al.
Published: (2024)

Effect of Exchange-Correlation Functionals on Schottky Barriers at Si/Metal Interfaces
by: Dovale-Farelo, Viviana, et al.
Published: (2026)

Off-Lattice Markov Chain Monte Carlo Simulations of Mechanically Driven Polymers
by: Ding, Lijie, et al.
Published: (2024)

Formation Energy Prediction of Material Crystal Structures using Deep Learning
by: Torlao, V., et al.
Published: (2024)

Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning
by: Choudhary, Kamal, et al.
Published: (2020)

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

Scattering-Based Structural Inversion of Soft Materials via Kolmogorov-Arnold Networks
by: Tung, Chi-Huan, et al.
Published: (2024)

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

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org
by: Lee, Jaehyung, et al.
Published: (2025)

AI-ready design of realistic 2D materials and interfaces with Mat3ra-2D
by: Biryukov, Vsevolod, et al.
Published: (2026)

Machine Learning for Predicting Magnetization from X-ray Diffraction of Iron Oxide Nanoparticles Using Simple Physics-Based Data Generation
by: Abel, Frank M., et al.
Published: (2025)

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

Vacancy-Enhanced $N-N$ Bonding and Deep Level Complex Defect Formation in $β-Ga_2O_3$
by: Shokri, Asiyeh, et al.
Published: (2026)

Emulating 2D Materials with Magnons
by: Kaman, Bobby, et al.
Published: (2026)

Physically Interpretable Interatomic Potentials via Symbolic Regression and Reinforcement Learning
by: Varughese, Bilvin, et al.
Published: (2025)

Featurized Materials Dataset for Formation Energy Prediction (derived from Materials Project)
by: Torlao, Virginio
Published: (2025)

Deep learning of spectra: Predicting the dielectric function of semiconductors
by: Grunert, Malte, et al.
Published: (2024)

In context learning Foundation models for Materials Property Prediction with Small datasets
by: Li, Qinyang, et al.
Published: (2025)

Unveiling the Optoelectronic Potential of Vacancy-Ordered Double Perovskites: A Computational Deep Dive
by: Adhikari, Surajit, et al.
Published: (2024)

AI for Manufacturing and Healthcare: a chemistry and engineering perspective
by: Chen, Jihua, et al.
Published: (2024)

Intrinsic Direct Air Capture
by: McDannald, Austin, et al.
Published: (2025)

A Panoramic View of MXenes via a New Design Strategy
by: Oyeniran, Noah, et al.
Published: (2025)

From Photons to Electrons: Accelerated Materials Discovery via Random Libraries and Automated Scanning Transmission Electron Microscopy
by: Slautin, Boris, et al.
Published: (2026)

Multiscale Modeling of Vacancy-Cluster Interactions and Solute Clustering Kinetics in Multicomponent Alloys
by: Xi, Zhucong, et al.
Published: (2025)

Kolmogorov-Arnold Networks in Thermoelectric Materials Design
by: Fronzi, Marco, et al.
Published: (2025)

A Systematic Investigation of PbSe Thermoelectric Material
by: Rahman, Md. Moklesur, et al.
Published: (2024)

Physical Encoding Improves OOD Performance in Deep Learning Materials Property Prediction
by: Fu, Nihang, et al.
Published: (2024)

Formation of Lattice Vacancies and their Effects on Lithium-ion Transport in LiBO2 Crystals: Comparative Ab Initio Studies
by: Ziemke, Carson, et al.
Published: (2024)

A Foundation Model for Material Fracture Prediction
by: Marcato, Agnese, et al.
Published: (2025)