Extracting thin film structures of energy materials using transformers
<|reference_start|>Extracting thin film structures of energy materials using transformers: Neutron-Transformer Reflectometry and Advanced Computation Engine (N-TRACE ), a neural network model using transformer architecture, is introduced for neutron reflectometry data analysis. It offers fast, accurate initial parameter estimations and efficient refinements, improving efficiency and precision for real-time data analysis of lithium-mediated nitrogen reduction for electrochemical ammonia synthesis, with relevance to other chemical transformations and batteries. Despite limitations in generalizing across systems, it shows promises for the use of transformers as the basis for models that could replace trial-and-error approaches to modeling reflectometry data.<|reference_end|>
@article{zhang2024extracting,
    title={Extracting thin film structures of energy materials using transformers},
    author={Chen Zhang and Valerie A. Niemann and Peter Benedek and Thomas F.
  Jaramillo and Mathieu Doucet},
    journal={arXiv preprint arXiv:2406.16741},
    year={2024},
    doi={10.1021/acsphyschemau.4c00054},
    archivePrefix={arXiv},
    eprint={2406.16741},
    primaryClass={physics.comp-ph cs.AI}
}