Gaussian-3 theory using reduced Mo/ller-Plesset order

1.1k indexed citations

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This paper, published in 1999, received 1.1k indexed citations. Written by Larry A. Curtiss, Paul C. Redfern, Krishnan Raghavachari, Vitaly A. Rassolov and John A. Pople covering the research area of Organic Chemistry and Atomic and Molecular Physics, and Optics. It is primarily cited by scholars working on Organic Chemistry (571 citations), Atomic and Molecular Physics, and Optics (518 citations) and Materials Chemistry (275 citations). Published in The Journal of Chemical Physics.

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Countries where authors are citing Gaussian-3 theory using reduced Mo/ller-Plesset order

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Citations

This map shows the geographic impact of Gaussian-3 theory using reduced Mo/ller-Plesset order. 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 Gaussian-3 theory using reduced Mo/ller-Plesset order with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gaussian-3 theory using reduced Mo/ller-Plesset order more than expected).

Fields of papers citing Gaussian-3 theory using reduced Mo/ller-Plesset order

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Gaussian-3 theory using reduced Mo/ller-Plesset order. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Gaussian-3 theory using reduced Mo/ller-Plesset order.

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/10.1063/1.478385.

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