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software
posted on 2025-06-30, 13:09 authored by Lei ZhangLei Zhang<p dir="ltr">NJmat</p><p dir="ltr">(updated 2026/06/30)</p><p dir="ltr">Data-driven machine learning software for materials science and engineering</p><p dir="ltr">Particularly helpful for experimentalists.</p><p dir="ltr">NJmat: main NJmat module (word vectors word2vec/tsne language model, material featurization, machine learning, deep learning, genetic algorithm, SHAP etc.)</p><p dir="ltr">NJmatNLPSetup: Language model submodule to predict materials using MatBERT language model.</p><p dir="ltr">Language_models: MatBERT and word2vec (millions or 50,000 paper abstracts) models.</p><p dir="ltr">NJmat-V2.0: Updated version (V2.0) of NJmat.</p><p dir="ltr">NJmatCDE: NLP (natural language processing) submodule to extract proper chemical formula/name from csv file.</p><p dir="ltr">NJmatCHG: Submodule using machine learning potential for materials property prediction (CHGnet)</p><p dir="ltr">NJmatVIS: Visualizer submodule</p><p dir="ltr">Please check datasets.rar for template .csv formats (train/test and prediction). The dataset templates (4 cases) are available in https://github.com/huangyiru123/NJmat_dataset.</p><p><br></p><p dir="ltr">Please cite: <a href="https://doi.org/10.1021/acs.jcim.4c00493" target="_blank">https://doi.org/10.1021/acs.jcim.4c00493</a> and <a href="https://doi.org/10.32604/cmc.2025.062666" target="_blank">https://doi.org/10.32604/cmc.2025.062666</a></p><p><br></p><p dir="ltr">Citations:</p><ol><li><a href="https://doi.org/10.1021/acs.jcim.4c00493" target="_blank">https://doi.org/10.1021/acs.jcim.4c00493</a></li><li><a href="https://doi.org/10.32604/cmc.2025.062666" target="_blank">https://doi.org/10.32604/cmc.2025.062666</a></li></ol><p dir="ltr">More Citations:</p><ol><li><a href="https://doi.org/10.1063/5.0064875" target="_blank">https://doi.org/10.1063/5.0064875</a></li><li><a href="https://doi.org/10.1063/5.0064875" target="_blank">https://doi.org/10.1088/1361-648X/ac3e1e</a></li><li><a href="https://doi.org/10.1021/acsaem.2c04066" rel="noreferrer" target="_blank">https://doi.org/10.1021/acsaem.2c04066</a></li><li><a href="https://doi.org/10.1021/acsami.2c00564" target="_blank">https://doi.org/10.1021/acsami.2c00564</a></li><li><a href="https://doi.org/10.1021/acsami.2c00568" target="_blank">https://doi.org/10.1021/acsami.2c00568</a></li></ol><p dir="ltr"><br></p>
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