Unraveling Structure and Spectroscopic Signatures of Pt/γ-Al2O3 via an AI-enabled Simulation Framework

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Authors: Piaoping Yang, Alfred Worrad, Dionisios G. Vlachos
Cited by: 0

Abstract

The uploaded dataset contains the data and codes used in this study, including:1. Training set and the final potential for MTP-based MLFF (MLFF-MD.zip);2. Training dataset and scripts for the XANES ML model (XANES_training.zip);3. AIMD trajectories (MLFF-MD.zip);4. Structural features extracted along the MD trajectories (Structural_features_Raw_data.zip);5. MD trajectories, model weights, and scripts used for IR and XANES spectral analyses (MDtraj_for_IR&XANES.zip & Scripts.zip);6. Raw data used to generate all figures presented in the manuscript (Raw_data_forFigures.zip)

Fields of Study & Subjects

Machine Learning in Materials Science Advanced Chemical Physics Studies Catalytic Processes in Materials Science

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
8 March 2026
Language
EN