Package: pqam-dparamhu2021
PyQAlloy-compatible Model for D Parameter prediction based on Hu2021Release:Compatible with:Tests:License:This repository contains a PyQAlloy-compatible compositionalModel, compatible withULTERA Database (ultera.org)infrastructure, for D Parameter Prediction Based onYong-Jie Hu 2021 (10.1016/j.actamat.2021.116800)that
accepts a chemical formula string of an alloy or apymatgen.Compositionobject. It return:Output Order: [gfse,surf,dparam]Output Meaning (all based on10.1016/j.actamat.2021.116800):gfse- Genralized Stacking Fault Energy (GSF) [J/m^2]surf- Surface Energy (Surf) [J/m^2]dparam- D Parameter [unitless] calculated assurf/gfseNote: The predicted energy is actually theUnstableStacking Fault Energy, which is the value of GSFE at a spacific high point, but we keep the naming scheme by the original model authors.Install and useTo run this model you will needPython 3.9+andR 4.1.0+installed on your system, ideallybeforeyou install
this software. For Python, we recommend you use a virtual Conda environment, which chan be created with minimal effort
(seeMiniconda install instructions). For R, it can be downloaded
pre-compiled from aComprehensive R Archive Networkrepository (e.g.Case CRAN) and should
work on most systems, including ARM-based (e.g. Apple M1).If you have Python and R, you can simply install this model with:pip install pqam_dparamhu2021Then, use should be as simple as:import pqam_dparamhu2021

print(pqam_dparamhu2021.predict("W30 Mo25 Ta45"))In some cases, requiredlocfitR package may not be installed automatically. If you get an error message about it,
try to go to your R console, typically by typingRin your terminal, and install it manually with:install.packages("locfit")Or, if you are automating things and need a single-liner, on Mac OS and Linux, the following should work:Rscript -e "install.packages('locfit', repos='http://cran.us.r-project.org')"AttributionThis repository has been created by Adam M. Krajewski (https://orcid.org/0000-0002-2266-0099) and is licensed under the MIT License.Please cite this repository if you use it in your work.The featurizer and predictive model (HEA_pred.R and dependencies) have been optimized across and re-styled by Adam M.
Krajewski based on code originally developed by Young-Jie Hu (https://orcid.org/0000-0003-1500-4015) et al. for their
journal publication and published in Materials Commons athttps://doi.org/10.13011/m3-rkg0-zh65, where original code
can be accessed,  distributed under ODC Open Database License (ODbL) v1.0.Please cite this publication as well:Yong-Jie Hu, Aditya Sundar, Shigenobu Ogata, Liang Qi, Screening of generalized stacking fault energies,
surface energies and intrinsic ductile potency of refractory multicomponent alloys, Acta Materialia,
Volume 210, 2021, 116800,https://doi.org/10.1016/j.actamat.2021.116800The gbm-locfit package (Gradient Boosting Machine-Locfit: A GBM framework using local regresssion via Locfit) has been
developed by Materials Project in 2016 and is distributed under the terms of the MIT License. Details can be found in
its code.Hu's README FileHello, thank you for your interest in our work!
Here we provide a script written in R language to take an alloy composition of interest and correspondingly predict the GSF energy, surface energy, and the >ductility parameter based on the SL models in our manuscript (https://doi.org/10.1016/j.actamat.2021.116800)
To run the script and make predictions, you need to:Download the RStudio platform. (https://www.rstudio.com/) ## No worry, it is open access 😊Put all the files you downloaded from Materials Commons (basically all our files) into one local folderOpen the “predict.R” file in RStudio, input the alloy composition there, execute every line there, and the prediction will jump out in the console window >below.Please contactqiliang@umich.eduoryh593@drexel.eduif you have any questions.P.S.,
“predict_screen_4nary_all.csv” is the original data for plotting Figure 7&8 in the manuscript. Other figures in the manuscript can be reproduced by the data >listed in the tables in the manuscript.MiscellaneousLast maintenance check: January 22nd, 2024