PySCF: the Python‐based simulations of chemistry framework

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This paper, published in 1950, received 1.1k indexed citations. Written by Qiming Sun, Timothy C. Berkelbach, Nick S. Blunt, George H. Booth, Sheng Guo, Zhendong Li, Junzi Liu, James McClain, Elvira R. Sayfutyarova and Sandeep Sharma covering the research area of Materials Chemistry, Atomic and Molecular Physics, and Optics and Electrical and Electronic Engineering. It is primarily cited by scholars working on Atomic and Molecular Physics, and Optics (757 citations), Materials Chemistry (356 citations) and Artificial Intelligence (265 citations). Published in Wiley Interdisciplinary Reviews Computational Molecular Science.

Countries where authors are citing PySCF: the Python‐based simulations of chemistry framework

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This map shows the geographic impact of PySCF: the Python‐based simulations of chemistry framework. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by PySCF: the Python‐based simulations of chemistry framework with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites PySCF: the Python‐based simulations of chemistry framework more than expected).

Fields of papers citing PySCF: the Python‐based simulations of chemistry framework

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of PySCF: the Python‐based simulations of chemistry framework. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the PySCF: the Python‐based simulations of chemistry framework.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1002/wcms.1340.

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