Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks-Reference-Cited by-同舟云学术

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Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Published:2021-03-19 Issue:5 Volume:17 Page:3052-3064
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Kancharlapalli Srinivasu¹²^ORCID,Gopalan Arun¹,Haranczyk Maciej³,Snurr Randall Q.¹^ORCID

Affiliation:

1. Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States

2. Theoretical Chemistry Section, Bhabha Atomic Research Centre, Trombay, Mumbai-400085, India

3. IMDEA Materials Institute, C/Eric Kandel 2, 28906 Getafe, Madrid, Spain

Funder

Basic Energy Sciences

United States - India Educational Foundation

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.0c01229

Reference97 articles.

1. Isoreticular Expansion of Metal–Organic Frameworks via Pillaring of Metal Templated Tunable Building Layers: Hydrogen Storage and Selective CO 2 Capture

2. Metal–Organic Frameworks and Their Applications

3. Application of natural zeolites in the purification and separation of gases

4. Screening Zeolites for Gas Separation Applications Involving Methane, Nitrogen, and Carbon Dioxide

5. Sustainable porous carbons with a superior performance for CO2 capture

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