August 17, 2018 article Open access Predicting glass transition temperatures using neural networks Acta Materialia DOI: 10.1016/j.actamat.2018.08.022 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 3 stored of 184 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Data driven development of iron-based metallic glasses using artificial neural networks 2023 Journal of Alloys and Compounds article Engineering Metallic Glasses and Amorphous Alloys 10 citations Prediction of Specific Volume of Polypropylene at High Cooling Rates by Artificial Neural Networks 2021 Industrial & Engineering Chemistry Research article Materials Science Machine Learning in Materials Science 3 citations Shallow neural networks to predict glass transition, crystallization and liquidus temperature of iron-based metallic glasses 2021 IOP Conference Series Materials Science and Engineering conference-paper Engineering Metallic Glasses and Amorphous Alloys Open access 2 citations 3 results References 0