A cloud platform for sharing and automated analysis of raw data from high throughput polymer MD simulations
Name
046108_1_5.0160937.pdf
Description
Published version
Size
6.02 MB
Format
Adobe PDF
Checksum (MD5)
069f3bcce9cc4ba2a417afdeffdf2db7
Author(s)
Xie, Tian
Kwon, Ha-Kyung
Schweigert, Daniel
Gong, Sheng
France-Lanord, Arthur
Khajeh, Arash
Crabb, Emily
Puzon, Michael
Fajardo, Chris
Powelson, Will
Date Issued
November 17, 2023
Journal
APL Machine Learning
Publisher
AIP Publishing
Citation
Tian Xie, Ha-Kyung Kwon, Daniel Schweigert, Sheng Gong, Arthur France-Lanord, Arash Khajeh, Emily Crabb, Michael Puzon, Chris Fajardo, Will Powelson, Yang Shao-Horn, Jeffrey C. Grossman; A cloud platform for sharing and automated analysis of raw data from high throughput polymer MD simulations. APL Mach. Learn. 1 December 2023; 1 (4): 046108.
Version
Final published version
Abstract
Open material databases storing thousands of material structures and their properties have become the cornerstone of modern computational materials science. Yet, the raw simulation outputs are generally not shared due to their huge size. In this work, we describe a cloud-based platform to enable fast post-processing of the trajectories and to facilitate sharing of the raw data. As an initial demonstration, our database includes 6286 molecular dynamics trajectories for amorphous polymer electrolytes (5.7 terabytes of data). We create a public analysis library at https://github.com/TRI-AMDD/htp_md to extract ion transport properties from the raw data using expert-designed functions and machine learning models. The analysis is run automatically on the cloud, and the results are uploaded onto an open database. Our platform encourages users to contribute both new trajectory data and analysis functions via public interfaces. Finally, we create a front-end user interface at https://www.htpmd.matr.io/ for browsing and visualization of our data. We envision the platform to be a new way of sharing raw data and new insights for the materials science community.
MIT Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1063/5.0160937
