Universal Ensemble-Embedding Graph Neural Network for Direct Prediction of Optical Spectra from Crystal Structures
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Updated
Oct 1, 2024 - Jupyter Notebook
Universal Ensemble-Embedding Graph Neural Network for Direct Prediction of Optical Spectra from Crystal Structures
Full-potential Linearized Augmented Plane Wave code FLEUR: All-electron DFT (repo mirror)
Full-potential Korringa-Kohn-Rostoker Green function code JuKKR: All-electron DFT (repo mirror)
Structural Constraint Integration in Generative Model for Discovery of Quantum Material Candidates
Interactive tools for the visualization and analysis of multidimensional photoemission data
Numerical effective field theory approach to quantum materials.
Here, we present a framework using large language models (LLMs) to predict synthesis pathways for inorganic materials, including quantum materials.
Quantum Materials Data Acquisition and Processing (QuDAP), a Python-based and open-source software package, is designed to control and automate material characterizations based on the Physical Property Measurement System (PPMS).
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