Predicting the adsorption of organic pollutants on boron nitride nanosheets via in silico techniques: DFT computations and QSAR modeling-Reference-Cited by-同舟云学术

Predicting the adsorption of organic pollutants on boron nitride nanosheets via in silico techniques: DFT computations and QSAR modeling

Published:2021 Issue:3 Volume:8 Page:795-805
ISSN:2051-8153
Container-title:Environmental Science: Nano
language:en
Short-container-title:Environ. Sci.: Nano

Author:

Wang Ya¹²³⁴⁵,Tang Weihao⁶⁷⁸⁹⁵,Peng Yue¹²³⁴⁵^ORCID,Chen Zhongfang¹⁰¹¹¹²¹³^ORCID,Chen Jingwen⁶⁷⁸⁹⁵^ORCID,Xiao Zijun⁶⁷⁸⁹⁵,Zhao Xiaoguang¹⁴¹⁵⁵,Qu Yakun¹⁴¹⁵⁵,Li Junhua¹²³⁴⁵^ORCID

Affiliation:

1. State Key Joint Laboratory of Environment Simulation and Pollution Control

2. School of Environment

3. Tsinghua University

4. Beijing 100084

5. China

6. Key Laboratory of Industrial Ecology and Environmental Engineering (MOE)

7. School of Environmental Science and Technology

8. Dalian University of Technology

9. Dalian 116024

10. Department of Chemistry

11. University of Puerto Rico

12. San Juan

13. USA

14. SINOPEC Research Institute of Petroleum Processing (RIPP)

15. Beijing 100083

Abstract

Four quantitative structure–activity relationship (QSAR) models were developed for predicting the log K values of organic pollutants adsorbed onto boron nitride nanosheets in gaseous and aqueous environments.

Funder

National Key Research and Development Program of China

National Aeronautics and Space Administration

National Science Foundation

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Environmental Science,Materials Science (miscellaneous)

Link

http://pubs.rsc.org/en/content/articlepdf/2021/EN/D0EN01145B

Reference63 articles.