Cyrille Lavigne
- Materials Chemistry top 10%
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
- Organic Chemistry
- Atomic and Molecular Physics, and Optics
- Co-authors
- Alán Aspuru‐GuzikRobert PolliceGabriel dos Passos GomesRiley J. HickmanCher Tian SerMario KrennMatteo AldeghiAkshatKumar Nigam
- Topics
- Machine Learning in Materials Science (5 papers)Computational Drug Discovery Methods (3 papers)Liquid Crystal Research Advancements (3 papers)
- Cited by
- Materials ChemistryElectronic, Optical and Magnetic MaterialsPhysical and Theoretical Chemistry
- Partner nations
- CanadaUnited KingdomJapan
In The Last Decade
Cyrille Lavigne
15 papers receiving 672 citations
Hit Papers
Peers
Comparison fields: 5 of 76
- Materials Chemistry 377
- Electrical and Electronic Engineering 222
- Electronic, Optical and Magnetic Materials 136
- Organic Chemistry 100
- Atomic and Molecular Physics, and Optics 86
Countries citing papers authored by Cyrille Lavigne
This map shows the geographic impact of Cyrille Lavigne's research. 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 Cyrille Lavigne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cyrille Lavigne more than expected).
Fields of papers citing papers by Cyrille Lavigne
This network shows the impact of papers produced by Cyrille Lavigne. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cyrille Lavigne. The network helps show where Cyrille Lavigne may publish in the future.
Co-authorship network of co-authors of Cyrille Lavigne
This figure shows the co-authorship network connecting the top 25 collaborators of Cyrille Lavigne. A scholar is included among the top collaborators of Cyrille Lavigne based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cyrille Lavigne. Cyrille Lavigne is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 31 | |
| 2 | 1 | |
| 3 | 8 | |
| 4 | 35 | |
| 5 | 11 | |
| 6 | 13 | |
| 7 | 126 | |
| 8 | 1 | |
| 9 | Data-Driven Strategies for Accelerated Materials Designbreakdown → | 299 |
| 10 | 3 | |
| 11 | 14 | |
| 12 | 5 | |
| 13 | 7 | |
| 14 | 53 | |
| 15 | 73 |
About Cyrille Lavigne
Cyrille Lavigne is a scholar working on Physical and Theoretical Chemistry, Computational Theory and Mathematics and Biophysics, having authored 15 papers that have together received 680 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (5 papers), Computational Drug Discovery Methods (3 papers) and Liquid Crystal Research Advancements (3 papers). The work is most often cited by research in Materials Chemistry (377 citations), Electronic, Optical and Magnetic Materials (136 citations) and Physical and Theoretical Chemistry (58 citations). Cyrille Lavigne has collaborated with scholars based in Canada, United Kingdom and Japan. Frequent co-authors include Alán Aspuru‐Guzik, Robert Pollice, Gabriel dos Passos Gomes, Riley J. Hickman, Cher Tian Ser, Mario Krenn, Matteo Aldeghi, AkshatKumar Nigam, Zhenpeng Yao and Pascal Friederich. Their work appears in journals such as Journal of the American Chemical Society, Advanced Materials and The Journal of Chemical Physics.
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.