OpenAlex Citation Counts

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Accuracy Assessment of Atomistic Neural Network Potentials: The Impact of Cutoff Radius and Message Passing
Junfan Xia, Yaolong Zhang, Bin Jiang
The Journal of Physical Chemistry A (2023) Vol. 127, Iss. 46, pp. 9874-9883
Closed Access | Times Cited: 7

Showing 7 citing articles:

Ab Initio Potential Energy Surface for NaCl–H₂ with Correct Long-Range Behavior
Priyanka Pandey, Chen Qu, Apurba Nandi, et al.
The Journal of Physical Chemistry A (2024) Vol. 128, Iss. 5, pp. 902-908
Open Access | Times Cited: 5

The evolution of machine learning potentials for molecules, reactions and materials
Junfan Xia, Yaolong Zhang, Bin Jiang
Chemical Society Reviews (2025)
Open Access

Virtual Special Issue on Machine Learning in Physical Chemistry Volume 2
Andrew L. Ferguson, Jim Pfaendtner
The Journal of Physical Chemistry B (2024) Vol. 128, Iss. 27, pp. 6435-6438
Closed Access | Times Cited: 1

Accurate Modeling of the Potential Energy Surface of Molecular Clusters Boosted by Neural Networks
Jakub Kubečka, Daniel Ayoubi, Zeyuan Tang, et al.
Environmental Science Advances (2024) Vol. 3, Iss. 10, pp. 1438-1451
Open Access | Times Cited: 1

Virtual Special Issue on Machine Learning in Physical Chemistry Volume 2
Andrew L. Ferguson, Jim Pfaendtner
The Journal of Physical Chemistry A (2024) Vol. 128, Iss. 27, pp. 5225-5228
Closed Access

Virtual Special Issue on Machine Learning in Physical Chemistry Volume 2
Andrew L. Ferguson, Jim Pfaendtner
The Journal of Physical Chemistry C (2024) Vol. 128, Iss. 27, pp. 11079-11082
Closed Access

How graph neural network interatomic potentials extrapolate: Role of the message-passing algorithm
Sungwoo Kang
The Journal of Chemical Physics (2024) Vol. 161, Iss. 24
Open Access

Page 1

Cookie	Duration	Description
cookielawinfo-checkbox-advertisement	1 year	Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category .
cookielawinfo-checkbox-analytics	1 year	Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Analytics" category .
cookielawinfo-checkbox-functional	1 year	The cookie is set by the GDPR Cookie Consent plugin to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary	1 year	Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Necessary" category .
cookielawinfo-checkbox-others	1 year	Set by the GDPR Cookie Consent plugin, this cookie is used to store the user consent for cookies in the category "Others".
cookielawinfo-checkbox-performance	1 year	Set by the GDPR Cookie Consent plugin, this cookie is used to store the user consent for cookies in the category "Performance".
CookieLawInfoConsent	1 year	Records the default button state of the corresponding category & the status of CCPA. It works only in coordination with the primary cookie.
PHPSESSID	session	This cookie is native to PHP applications. The cookie is used to store and identify a users' unique session ID for the purpose of managing user session on the website. The cookie is a session cookies and is deleted when all the browser windows are closed.

Requested Article:

Showing 7 citing articles:

Your Privacy