Glass Ternary Landolt Data

Metallic glass formation dataset for ternary alloys, collected from the "Nonequilibrium Phase Diagrams of Ternary Amorphous Alloys,’ a volume of the Landolt– Börnstein collection. This dataset contains experimental measurements of whether it is possible to form a glass using a variety of processing techniques at thousands of compositions from hundreds of ternary systems. The processing techniques are designated in the "processing" column.<br><br>There are originally 7191 experiments in this dataset, will be reduced to 6203 after deduplicated, and will be further reduced to 6118 if combining multiple data for one composition. There are originally 6780 melt-spinning experiments in this dataset, will be reduced to 5800 if deduplicated, and will be further reduced to 5736 if combining multiple experimental data for one composition.<br><br>Available as Monty Encoder encoded JSON and as CSV. Recommended access method for these particular files is with the matminer Python package using the datasets module.<br><br>Note on citations: If you found this dataset useful and would like to cite it in your work, please be sure to cite its original sources below rather than or in addition to this page.<br>Dataset sourced from: Y. Kawazoe, T. Masumoto, A.-P. Tsai, J.-Z. Yu, T. Aihara Jr. (1997) Y. Kawazoe, J.-Z. Yu, A.-P. Tsai, T. Masumoto (ed.) SpringerMaterials <strong>Nonequilibrium Phase Diagrams of Ternary Amorphous Alloys · 1 Introduction </strong> Landolt-Börnstein - Group III Condensed Matter 37A (Nonequilibrium Phase Diagrams of Ternary Amorphous Alloys) https://materials.springer.com/lb/docs/sm_lbs_978-3-540-47679-5_2 10.1007/10510374_2 (Springer-Verlag Berlin Heidelberg © 1997) Accessed: 20-10-2018 <br>Dataset provided for comparison to work in the following paper: <br><br>A general-purpose machine learning framework for predicting properties of inorganic materials Logan Ward, Ankit Agrawal, Alok Choudhary &amp; Christopher Wolverton <i>npj Computational Materials</i> <b>volume 2</b>, Article number: 16028 (2016)<br>