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A flux-jump preserved gradient recovery technique for accurately predicting the electrostatic field of an immersed biomolecule

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成果类型:
期刊论文
作者:
Li, Jiao;Ying, Jinyong*;Lu, Benzhuo
通讯作者:
Ying, Jinyong
作者机构:
[Li, Jiao] Changsha Univ Sci & Technol, Sch Math & Stat, Hunan Prov Key Lab Math Modeling & Anal Engn, Changsha 410114, Hunan, Peoples R China.
[Ying, Jinyong] Cent S Univ, Sch Math & Stat, Changsha 410083, Hunan, Peoples R China.
[Lu, Benzhuo] Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Acad Math & Syst Sci, State Key Lab Sci Engn Comp, Beijing 100190, Peoples R China.
通讯机构:
[Ying, Jinyong] C
Cent S Univ, Sch Math & Stat, Changsha 410083, Hunan, Peoples R China.
语种:
英文
关键词:
Biomolecules;Boltzmann equation;Continuum mechanics;Dissociation;Electrostatic force;Forecasting;Poisson equation;Recovery;Software testing;Continuum model;Flux jump;Flux preserving;Gradient recovery;Gradient recovery technique;Implicit continuum model;Poisson-Boltzmann equations;Recovery techniques;Solvated biomolecules;Total electrostatic force;Numerical methods
期刊:
Journal of Computational Physics
ISSN:
0021-9991
年:
2019
卷:
396
页码:
193-208
基金类别:
The authors would like to thank the referees for the valuable comments. This work was supported by the Science Challenge Program ( TZ2016003 ), the National Key Research and Development Program of Ministry of Science and Technology ( 2016YFB0201304 ), the National Natural Science Foundation of China (Grant No. 11701576 , 11501053 , 21573274 and 11771435 ), the Natural Science Foundation of Hunan Province (Grant No. 2019JJ50786 ), and the Education Department of Hunan Province (Grant No. 15C0026 ). The authors would like to thank the referees for the valuable comments. This work was supported by the Science Challenge Program (TZ2016003), the National Key Research and Development Program of Ministry of Science and Technology (2016YFB0201304), the National Natural Science Foundation of China (Grant No. 11701576, 11501053, 21573274 and 11771435), the Natural Science Foundation of Hunan Province (Grant No. 2019JJ50786), and the Education Department of Hunan Province (Grant No. 15C0026).
机构署名:
本校为第一机构
院系归属:
数学与统计学院
摘要:
Poisson-Boltzmann equation (PBE) and its variants are important implicit continuum models for predicting the electrostatics of solvated biomolecules. In this paper, in order to accurately predict the gradient of electrostatics, we propose a new flux-jump preserved gradient recovery method and then fulfill it in the program using Python and Fortran. Two numerical tests with available analytical solutions are presented to well validate the new program. Then the new proposed method is applied to recover the gradient of a simple dipole case as well as two protein cases usin...

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