Cover Image

OmniXAS: A Universal Deep-Learning Framework for Materials X-ray Absorption Spectra

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kharel, Shubha R., Meng, Fanchen, Qu, Xiaohui, Carbone, Matthew R., Lu, Deyu
Format:	Preprint
Published:	2024
Subjects:	Materials Science Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Advancing AI-Driven Analysis in X-ray Absorption Spectroscopy: Spectral Domain Mapping and Universal Models
by: Cao, Nina, et al.
Published: (2025)

Multi-code Benchmark on Simulated Ti K-edge X-ray Absorption Spectra of Ti-O Compounds
by: Meng, Fanchen, et al.
Published: (2023)

CuXASNet: Rapid and Accurate Prediction of Copper L-edge X-Ray Absorption Spectra Using Machine Learning
by: Gleason, Samuel P., et al.
Published: (2024)

Prediction of the Cu Oxidation State from EELS and XAS Spectra Using Supervised Machine Learning
by: Gleason, Samuel P., et al.
Published: (2023)

Predictive autoencoder-transformer model of Cu oxidation state from EELS and XAS spectra
by: Lee, Brian, et al.
Published: (2026)

Universal rapid machine learning models for predicting unconvoluted and convoluted X-ray Absorption Spectra
by: Zhan, Fei, et al.
Published: (2026)

Interpretable Multimodal Machine Learning Analysis of X-ray Absorption Near-Edge Spectra and Pair Distribution Functions
by: Narong, Tanaporn Na, et al.
Published: (2024)

Table-top soft x-ray source for XAS experiments with photon energies up to 350 eV
by: Naranjo-Montoya, O. A., et al.
Published: (2024)

AI-Driven Structure Refinement of X-ray Diffraction
by: Cao, Bin, et al.
Published: (2026)

AI-Driven Phase Identification from X-ray Hyperspectral Imaging of cycled Na-ion Cathode Materials
by: Adrar, Fayçal, et al.
Published: (2026)

Advancing Universal Deep Learning for Electronic-Structure Hamiltonian Prediction of Materials
by: Yin, Shi, et al.
Published: (2025)

Universal Machine Learning Kohn-Sham Hamiltonian for Materials
by: Zhong, Yang, et al.
Published: (2024)

Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials
by: Spurgeon, Steven R., et al.
Published: (2026)

An Agentic Framework for Autonomous Materials Computation
by: Xia, Zeyu, et al.
Published: (2025)

Adaptively Switching Between Amplification and Absorption by an Intelligent Omni‐Metasurface With Nonlinear Spectral Singularity
by: Yinghui Ren, et al.
Published: (2025)

Application of X-ray Absorption Spectroscopy with a laboratory X-ray powder diffractometer
by: Gateshki, Milen, et al.
Published: (2025)

A Shift-Invariant Deep Learning Framework for Automated Analysis of XPS Spectra
by: Saddiq, Issa, et al.
Published: (2026)

X-ray Absorption and Resonant X-ray Emission at the Carbon Edge of Li$_2$CO$_3$
by: Vinson, John, et al.
Published: (2026)

AI-accelerated Discovery of Altermagnetic Materials
by: Gao, Ze-Feng, et al.
Published: (2023)

A Generation Framework with Strict Constraints for Crystal Materials Design
by: Huang, Chao, et al.
Published: (2024)

Effects of Structural Variations to X-ray Absorption Spectra of g-C$_3$N$_4$: Insights from DFT and TDDFT Simulations
by: Zhang, Jun-Rong, et al.
Published: (2024)

OmniSpectra: A Unified Foundation Model for Native Resolution Astronomical Spectra
by: Islam, Md Khairul, et al.
Published: (2026)

Probabilistic Phase Labeling and Lattice Refinement for Autonomous Material Research
by: Chang, Ming-Chiang, et al.
Published: (2023)

OpenAaaS: An Open Agent-as-a-Service Framework for Distributed Materials-Informatics Research
by: Kang, Peng, et al.
Published: (2026)

MatFormBench: A Benchmarking Evaluation Framework for Target-Driven Materials Formulation
by: Wu, Linhan, et al.
Published: (2026)

Automated and Holistic Co-design of Neural Networks and ASICs for Enabling In-Pixel Intelligence
by: Kharel, Shubha R., et al.
Published: (2024)

A New Type Microwave Absorption Materials: Metal–Organic‐Frameworks (MOFs) Used as Non‐Conductive Material Combination with P‐C‐800
by: Guodong Han, et al.
Published: (2025)

X-ray Absorption Linear Dichroism at the Ti K-edge of TiO2 anatase single crystals
by: Rossi, T. C., et al.
Published: (2019)

MSP-LLM: A Unified Large Language Model Framework for Complete Material Synthesis Planning
by: Noh, Heewoong, et al.
Published: (2026)

In Situ X‐ray Absorption Fine Spectroscopy Reveals the Durability of Bismuth‐Coated Zn Metal Anode
by: Zhuo Li, et al.
Published: (2025)

Importance of Electrostatic Effects for Interpretation of X‐ray Photoemission Spectra of Self‐Assembled Monolayers
by: Michael Zharnikov
Published: (2024)

Identifying Crystal Structures Beyond Known Prototypes from X-ray Powder Diffraction Spectra
by: Parackal, Abhijith S., et al.
Published: (2023)

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
by: Vuong, An, et al.
Published: (2026)

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models
by: Barroso-Luque, Luis, et al.
Published: (2024)

Multi-AI Agent Framework Reveals the "Oxide Gatekeeper" in Aluminum Nanoparticle Oxidation
by: Lu, Yiming, et al.
Published: (2025)

Towards Agentic Intelligence for Materials Science
by: Zhang, Huan, et al.
Published: (2026)

LLM Meets Diffusion: A Hybrid Framework for Crystal Material Generation
by: Khastagir, Subhojyoti, et al.
Published: (2025)

Optical Absorption and Emission from Wannier-Stark Spectra of Moiré Superlattices
by: Phong, Vo Tien, et al.
Published: (2024)

XDXD: End-to-end crystal structure determination with low resolution X-ray diffraction
by: Zhao, Jiale, et al.
Published: (2025)

An Absorption Correction for Reliable Pair-Distribution Functions from Low Energy X-ray Sources
by: Chen, Yucong, et al.
Published: (2025)