Quantum coherence in photosynthesis for efficient solar-energy conversion

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This paper, published in 1950, received 444 indexed citations. Written by Elisabet Romero, Ramūnas Augulis, Vladimir I. Novoderezhkin, Marco Ferretti, Jos Thieme, Donatas Zigmantas and Rienk van Grondelle covering the research area of Molecular Biology, Cellular and Molecular Neuroscience and Atomic and Molecular Physics, and Optics. It is primarily cited by scholars working on Atomic and Molecular Physics, and Optics (377 citations), Molecular Biology (214 citations) and Cellular and Molecular Neuroscience (139 citations). Published in Nature Physics.

Countries where authors are citing Quantum coherence in photosynthesis for efficient solar-energy conversion

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This map shows the geographic impact of Quantum coherence in photosynthesis for efficient solar-energy conversion. 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 Quantum coherence in photosynthesis for efficient solar-energy conversion with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quantum coherence in photosynthesis for efficient solar-energy conversion more than expected).

Fields of papers citing Quantum coherence in photosynthesis for efficient solar-energy conversion

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Quantum coherence in photosynthesis for efficient solar-energy conversion. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Quantum coherence in photosynthesis for efficient solar-energy conversion.

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/10.1038/nphys3017.

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