Journal of Chemical Information and Modeling, volume 60, issue 3, pages 1184-1193
PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials
Publication type: Journal Article
Publication date: 2020-01-14
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor: 5.6
ISSN: 15499596, 1549960X
General Chemistry
Computer Science Applications
General Chemical Engineering
Library and Information Sciences
Abstract
Atomic neural networks (ANNs) constitute a class of machine learning methods for predicting potential energy surfaces and physico-chemical properties of molecules and materials. Despite many successes, developing interpretable ANN architectures and implementing existing ones efficiently are still challenging. This calls for reliable, general-purpose and open-source codes. Here, we present a python library named PiNN as a solution toward this goal. In PiNN, we designed a new interpretable and high-performing graph convolutional neural network variant, PiNet, as well as implemented the established Behler-Parrinello high-dimensional neural network. These implementations were tested using datasets of isolated small molecules, crystalline materials, liquid water and an aqueous alkaline electrolyte. PiNN comes with a visualizer called PiNNBoard to extract chemical insight ``learned'' by ANNs, provides analytical stress tensor calculations and interfaces to both the Atomic Simulation Environment and a development version of the Amsterdam Modeling Suite. Moreover, PiNN is highly modularized which makes it useful not only as a standalone package but also as a chain of tools to develop and to implement novel ANNs. The code is distributed under a permissive BSD license and is freely accessible at \href{https://github.com/Teoroo-CMC/PiNN/}{https://github.com/Teoroo-CMC/PiNN/} with full documentation and tutorials.
Citations by journals
1
2
3
4
5
6
7
|
|
Journal of Chemical Physics
|
Journal of Chemical Physics
7 publications, 15.56%
|
Journal of Chemical Theory and Computation
|
Journal of Chemical Theory and Computation
3 publications, 6.67%
|
Journal of Physics Energy
|
Journal of Physics Energy
3 publications, 6.67%
|
Journal of Physical Chemistry B
|
Journal of Physical Chemistry B
2 publications, 4.44%
|
Computational Materials Science
|
Computational Materials Science
2 publications, 4.44%
|
Machine Learning Science and Technology
|
Machine Learning Science and Technology
2 publications, 4.44%
|
Chemical Reviews
|
Chemical Reviews
2 publications, 4.44%
|
Scientific Reports
|
Scientific Reports
1 publication, 2.22%
|
ACS Symposium Series
|
ACS Symposium Series
1 publication, 2.22%
|
Scientific data
|
Scientific data
1 publication, 2.22%
|
Nature Reviews Chemistry
|
Nature Reviews Chemistry
1 publication, 2.22%
|
Electronic Structure
|
Electronic Structure
1 publication, 2.22%
|
Journal of Physics Condensed Matter
|
Journal of Physics Condensed Matter
1 publication, 2.22%
|
Batteries & Supercaps
|
Batteries & Supercaps
1 publication, 2.22%
|
Chinese Journal of Chemistry
|
Chinese Journal of Chemistry
1 publication, 2.22%
|
Crystal Research and Technology
|
Crystal Research and Technology
1 publication, 2.22%
|
Energy & Fuels
|
Energy & Fuels
1 publication, 2.22%
|
Journal of Physical Chemistry A
|
Journal of Physical Chemistry A
1 publication, 2.22%
|
ACS Omega
|
ACS Omega
1 publication, 2.22%
|
Journal of Chemical Information and Modeling
|
Journal of Chemical Information and Modeling
1 publication, 2.22%
|
ChemPhysChem
|
ChemPhysChem
1 publication, 2.22%
|
Chemical Science
|
Chemical Science
1 publication, 2.22%
|
Molecular Simulation
|
Molecular Simulation
1 publication, 2.22%
|
Pure and Applied Chemistry
|
Pure and Applied Chemistry
1 publication, 2.22%
|
Scientific Programming
|
Scientific Programming
1 publication, 2.22%
|
Acta Materialia
|
Acta Materialia
1 publication, 2.22%
|
Physical Review B
|
Physical Review B
1 publication, 2.22%
|
Advanced Science
|
Advanced Science
1 publication, 2.22%
|
Concurrency Computation Practice and Experience
|
Concurrency Computation Practice and Experience
1 publication, 2.22%
|
Journal of Physical Chemistry C
|
Journal of Physical Chemistry C
1 publication, 2.22%
|
1
2
3
4
5
6
7
|
Citations by publishers
2
4
6
8
10
12
14
|
|
American Chemical Society (ACS)
|
American Chemical Society (ACS)
13 publications, 28.89%
|
American Institute of Physics (AIP)
|
American Institute of Physics (AIP)
7 publications, 15.56%
|
IOP Publishing
|
IOP Publishing
7 publications, 15.56%
|
Wiley
|
Wiley
6 publications, 13.33%
|
Springer Nature
|
Springer Nature
3 publications, 6.67%
|
Elsevier
|
Elsevier
3 publications, 6.67%
|
Royal Society of Chemistry (RSC)
|
Royal Society of Chemistry (RSC)
2 publications, 4.44%
|
Taylor & Francis
|
Taylor & Francis
1 publication, 2.22%
|
Walter de Gruyter
|
Walter de Gruyter
1 publication, 2.22%
|
Hindawi Limited
|
Hindawi Limited
1 publication, 2.22%
|
American Physical Society (APS)
|
American Physical Society (APS)
1 publication, 2.22%
|
2
4
6
8
10
12
14
|
- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
{"yearsCitations":{"type":"bar","data":{"show":true,"labels":[2020,2021,2022,2023,2024],"ids":[0,0,0,0,0],"codes":[0,0,0,0,0],"imageUrls":["","","","",""],"datasets":[{"label":"Citations number","data":[7,16,12,7,3],"backgroundColor":["#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6"],"percentage":["15.56","35.56","26.67","15.56","6.67"],"barThickness":null}]},"options":{"indexAxis":"x","maintainAspectRatio":true,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":1,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Citations per year","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}},"journals":{"type":"bar","data":{"show":true,"labels":["Journal of Chemical Physics","Journal of Chemical Theory and Computation","Journal of Physics Energy","Journal of Physical Chemistry B","Computational Materials Science","Machine Learning Science and Technology","Chemical Reviews","Scientific Reports","ACS Symposium Series","Scientific data","Nature Reviews Chemistry","Electronic Structure","Journal of Physics Condensed Matter","Batteries & Supercaps","Chinese Journal of Chemistry","Crystal Research and Technology","Energy & Fuels","Journal of Physical Chemistry A","ACS Omega","Journal of Chemical Information and Modeling","ChemPhysChem","Chemical Science","Molecular Simulation","Pure and Applied Chemistry","Scientific Programming","Acta Materialia","Physical Review B","Advanced Science","Concurrency Computation Practice and Experience","Journal of Physical Chemistry C"],"ids":[544,58,27516,14990,3669,26682,13718,13767,23301,2082,6657,26746,4579,26456,7222,23307,10347,15255,18901,13608,16306,9646,2675,11456,10551,6469,25280,4130,770,8859],"codes":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"imageUrls":["\/storage\/images\/resized\/ARM4e6URKRsbRZvIF0vFis9DjxGloBjnBYJXbHmZ_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/LsKy6OnmmmRGcAU6CZgWQvNiP1polbaSLNrN7zqj_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp","\/storage\/images\/resized\/LsKy6OnmmmRGcAU6CZgWQvNiP1polbaSLNrN7zqj_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/voXLqlsvTwv5p3iMQ8Dhs95nqB4AXOG7Taj7G4ra_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/voXLqlsvTwv5p3iMQ8Dhs95nqB4AXOG7Taj7G4ra_medium.webp","\/storage\/images\/resized\/voXLqlsvTwv5p3iMQ8Dhs95nqB4AXOG7Taj7G4ra_medium.webp","\/storage\/images\/resized\/LsKy6OnmmmRGcAU6CZgWQvNiP1polbaSLNrN7zqj_medium.webp","\/storage\/images\/resized\/LsKy6OnmmmRGcAU6CZgWQvNiP1polbaSLNrN7zqj_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/leiAYcRDGTSl5B1eCnwpSGqmDEUEfDPPoYisFGhT_medium.webp","\/storage\/images\/resized\/5YZtvLvkPZuc2JHOaZsjCvGSHFCuC3drUwN3YAc5_medium.webp","\/storage\/images\/resized\/3SpVxcYL33bOvPq4sHxJLH2NeKNeDloahSUpNiO4_medium.webp","\/storage\/images\/resized\/hqfzhQAjTGlNSRs6yzFNITgjSMm9Jr2QuotJHIvE_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp","\/storage\/images\/resized\/nrK64iXHTzj43wMrfN1ZoUQ0vanswGzWPN45K3jA_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp"],"datasets":[{"label":"","data":[7,3,3,2,2,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1],"backgroundColor":["#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6"],"percentage":[15.56,6.67,6.67,4.44,4.44,4.44,4.44,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22,2.22],"barThickness":13}]},"options":{"indexAxis":"y","maintainAspectRatio":false,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":null,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Journals","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}},"publishers":{"type":"bar","data":{"show":true,"labels":["American Chemical Society (ACS)","American Institute of Physics (AIP)","IOP Publishing","Wiley","Springer Nature","Elsevier","Royal Society of Chemistry (RSC)","Taylor & Francis","Walter de Gruyter","Hindawi Limited","American Physical Society (APS)"],"ids":[40,250,2075,11,8,17,123,18,4,6921,1539],"codes":[0,0,0,0,0,0,0,0,0,0,0],"imageUrls":["\/storage\/images\/resized\/iLiQsFqFaSEx6chlGQ5fbAwF6VYU3WWa08hkss0g_medium.webp","\/storage\/images\/resized\/ARM4e6URKRsbRZvIF0vFis9DjxGloBjnBYJXbHmZ_medium.webp","\/storage\/images\/resized\/LsKy6OnmmmRGcAU6CZgWQvNiP1polbaSLNrN7zqj_medium.webp","\/storage\/images\/resized\/bRyGpdm98BkAUYiK1YFNpl5Z7hPu6Gd87gbIeuG3_medium.webp","\/storage\/images\/resized\/voXLqlsvTwv5p3iMQ8Dhs95nqB4AXOG7Taj7G4ra_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp","\/storage\/images\/resized\/leiAYcRDGTSl5B1eCnwpSGqmDEUEfDPPoYisFGhT_medium.webp","\/storage\/images\/resized\/5YZtvLvkPZuc2JHOaZsjCvGSHFCuC3drUwN3YAc5_medium.webp","\/storage\/images\/resized\/3SpVxcYL33bOvPq4sHxJLH2NeKNeDloahSUpNiO4_medium.webp","\/storage\/images\/resized\/hqfzhQAjTGlNSRs6yzFNITgjSMm9Jr2QuotJHIvE_medium.webp","\/storage\/images\/resized\/nrK64iXHTzj43wMrfN1ZoUQ0vanswGzWPN45K3jA_medium.webp"],"datasets":[{"label":"","data":[13,7,7,6,3,3,2,1,1,1,1],"backgroundColor":["#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6","#3B82F6"],"percentage":[28.89,15.56,15.56,13.33,6.67,6.67,4.44,2.22,2.22,2.22,2.22],"barThickness":13}]},"options":{"indexAxis":"y","maintainAspectRatio":false,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":null,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Publishers","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}}}
Metrics
Cite this
GOST |
RIS |
BibTex |
MLA
Cite this
GOST
Copy
Shao Y. et al. PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials // Journal of Chemical Information and Modeling. 2020. Vol. 60. No. 3. pp. 1184-1193.
GOST all authors (up to 50)
Copy
Shao Y., Hellström M., Mitev P., Knijff L., Zhang C. PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials // Journal of Chemical Information and Modeling. 2020. Vol. 60. No. 3. pp. 1184-1193.
Cite this
RIS
Copy
TY - JOUR
DO - 10.1021/acs.jcim.9b00994
UR - https://doi.org/10.1021%2Facs.jcim.9b00994
TI - PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials
T2 - Journal of Chemical Information and Modeling
AU - Knijff, Lisanne
AU - Hellström, Matti
AU - Mitev, Pavlin Dakev
AU - Zhang, Chao
AU - Shao, Yunqi
PY - 2020
DA - 2020/01/14 00:00:00
PB - American Chemical Society (ACS)
SP - 1184-1193
IS - 3
VL - 60
SN - 1549-9596
SN - 1549-960X
ER -
Cite this
BibTex
Copy
@article{2020_Shao
author = {Lisanne Knijff and Matti Hellström and Pavlin Dakev Mitev and Chao Zhang and Yunqi Shao},
title = {PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials},
journal = {Journal of Chemical Information and Modeling},
year = {2020},
volume = {60},
publisher = {American Chemical Society (ACS)},
month = {jan},
url = {https://doi.org/10.1021%2Facs.jcim.9b00994},
number = {3},
pages = {1184--1193},
doi = {10.1021/acs.jcim.9b00994}
}
Cite this
MLA
Copy
Shao, Yunqi, et al. “PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials.” Journal of Chemical Information and Modeling, vol. 60, no. 3, Jan. 2020, pp. 1184-1193. https://doi.org/10.1021%2Facs.jcim.9b00994.
Profiles