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Polymer descriptor data set for machine learning prediction of specific heat

Rahul Bhowmik1,2*, Sangwook Sihn2,3*, Ruth Pachter2*, Jonathan Vernon2*

1 Polaron Analytics, Suite 450, 4031 Colonel Glenn Highway, Beavercreek, OH 45431, USA

2 Air Force Research Laboratory

3 University of Dayton Research Institute

* Corresponding authors emails: bhowmikrahul@gmail.com, sangwook.sihn.1.ctr@us.af.mil, ruth.pachter@us.af.mil, jonathan.vernon.2@us.af.mil
DOI10.24435/materialscloud:43-js [version v2]

Publication date: Dec 06, 2021

How to cite this record

Rahul Bhowmik, Sangwook Sihn, Ruth Pachter, Jonathan Vernon, Polymer descriptor data set for machine learning prediction of specific heat, Materials Cloud Archive 2021.213 (2021), doi: 10.24435/materialscloud:43-js.


We have developed a polymer descriptor data set from the existing data. The data set has 188 descriptors which describe polymer atomic and molecular behavior. The descriptors are mapped to the specific heat of polymers using supervised and unsupervised machine learning approaches. The mapping helps predict the specific heat of polymers at room temperature. The descriptor data set is useful in synthesizing novel polymers with desired heat capacities.

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File name Size Description
29.6 KiB Polymer descriptor data set is used to map the 188 descriptors to heat capacity using machine learning method, and useful to predict the heat capacities of polymers
546 Bytes The file listed the atom names used in various columns of the file, "Cp_Polymer_Data.csv."
104.6 KiB The folder contains all the structure files of polymers used to generate the descriptors.


Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

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Journal reference (The citation will be updated once accepted for publication.)


polymer specific heat descriptors

Version history:

2021.213 (version v2) [This version] Dec 06, 2021 DOI10.24435/materialscloud:43-js
2020.57 (version v1) Jun 19, 2020 DOI10.24435/materialscloud:18-nr