Dielectric Polymer Property Prediction Using Recurrent Neural Networks with Optimizations-Reference-Cited by-同舟云学术

Dielectric Polymer Property Prediction Using Recurrent Neural Networks with Optimizations

Published:2021-04-19 Issue:5 Volume:61 Page:2175-2186
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Nazarova Antonina L.¹,Yang Liqiu²,Liu Kuang²,Mishra Ankit²,Kalia Rajiv K.²,Nomura Ken-ichi²,Nakano Aiichiro²^ORCID,Vashishta Priya²^ORCID,Rajak Pankaj³

Affiliation:

1. Department of Chemistry, Loker Hydrocarbon Research Institute, and USC Bridge Institue, University of Southern California, Los Angeles, California 90089, United States

2. Collaboratory of Advanced Computing and Simulations, Department of Computer Science, Department of Physics & Astronomy, Department of Chemical Engineering & Materials Science, and Department of Biological Sciences, University of Southern California, Los Angeles, California 90089, United States

3. Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, Illinois 60439, United States

Funder

Office of Naval Research

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.0c01366

Reference80 articles.

1. Artificial neural network studies in quantitative structure-activity relationships of antifungal azoxy compounds

2. Quantitative Structure–Property Relationship Modeling of Diverse Materials Properties