Clémence Corminbœuf

18.6k total citations · 3 hit papers
253 papers, 15.1k citations indexed

About

Clémence Corminbœuf is a scholar working on Materials Chemistry, Organic Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Clémence Corminbœuf has authored 253 papers receiving a total of 15.1k indexed citations (citations by other indexed papers that have themselves been cited), including 107 papers in Materials Chemistry, 88 papers in Organic Chemistry and 63 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Clémence Corminbœuf's work include Machine Learning in Materials Science (54 papers), Advanced Chemical Physics Studies (52 papers) and Synthesis and Properties of Aromatic Compounds (39 papers). Clémence Corminbœuf is often cited by papers focused on Machine Learning in Materials Science (54 papers), Advanced Chemical Physics Studies (52 papers) and Synthesis and Properties of Aromatic Compounds (39 papers). Clémence Corminbœuf collaborates with scholars based in Switzerland, United States and Germany. Clémence Corminbœuf's co-authors include Paul von Ragué Schleyer, Chaitanya S. Wannere, Ralph Puchta, Zhongfang Chen, Stephan N. Steinmann, Matthew D. Wodrich, Thomas Heine, Hossain Fallah‐Bagher‐Shaidaei, Alberto Fabrizio and Michael Busch and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Clémence Corminbœuf

251 papers receiving 15.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Nucleus-Independent Chemical Shifts (NICS) as an Aromaticity Criterion

2005 3.2k citations Clémence Corminbœuf et al. profile →
Which NICS Aromaticity Index for Planar π Rings Is Best?

2006 1.1k citations Clémence Corminbœuf et al. profile →
Comprehensive Benchmarking of a Density-Dependent Dispersion Correction

2011 400 citations Stephan N. Steinmann, Clémence Corminbœuf profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Clémence Corminbœuf Switzerland	59	7.8k	6.2k	2.7k	2.5k	2.4k	253	15.1k
Shubin Liu United States	55	7.6k 1.0×	4.7k 0.8×	3.6k 1.3×	2.3k 0.9×	3.8k 1.6×	300	17.5k
Christoph Bannwarth Germany	35	4.2k 0.5×	4.8k 0.8×	1.6k 0.6×	2.0k 0.8×	2.9k 1.2×	77	12.9k
Andreas Hansen Germany	43	5.0k 0.6×	5.5k 0.9×	1.7k 0.7×	3.1k 1.3×	5.1k 2.1×	115	15.9k
Miquel Solà Spain	74	14.1k 1.8×	6.2k 1.0×	2.0k 0.7×	3.7k 1.5×	4.3k 1.8×	521	20.5k
Ralf Ludwig Germany	66	4.2k 0.5×	3.6k 0.6×	1.3k 0.5×	3.3k 1.3×	2.9k 1.2×	381	17.1k
Nadia Rega Italy	35	5.3k 0.7×	3.2k 0.5×	1.6k 0.6×	1.7k 0.7×	2.9k 1.2×	102	12.9k
Paul C. Redfern United States	50	7.5k 1.0×	6.8k 1.1×	3.9k 1.5×	2.0k 0.8×	7.6k 3.1×	117	20.8k
William J. Pietro Canada	29	4.7k 0.6×	3.8k 0.6×	2.3k 0.9×	2.6k 1.1×	3.0k 1.2×	92	12.3k
Ilaria Ciofini France	56	3.9k 0.5×	5.9k 1.0×	3.0k 1.1×	992 0.4×	2.5k 1.0×	273	12.8k
Frank De Proft Belgium	60	10.6k 1.4×	5.6k 0.9×	2.3k 0.9×	2.8k 1.1×	5.7k 2.4×	432	19.7k

Countries citing papers authored by Clémence Corminbœuf

Since Specialization

Citations

This map shows the geographic impact of Clémence Corminbœuf'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 Clémence Corminbœuf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clémence Corminbœuf more than expected).

Fields of papers citing papers by Clémence Corminbœuf

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Clémence Corminbœuf. 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 Clémence Corminbœuf. The network helps show where Clémence Corminbœuf may publish in the future.

Co-authorship network of co-authors of Clémence Corminbœuf

This figure shows the co-authorship network connecting the top 25 collaborators of Clémence Corminbœuf. A scholar is included among the top collaborators of Clémence Corminbœuf 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 Clémence Corminbœuf. Clémence Corminbœuf is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Laplaza, Rubén, et al.. (2024). Cost-informed Bayesian reaction optimization. Digital Discovery. 3(11). 2289–2297. 5 indexed citations

Das, Shubhajit, et al.. (2024). Engineering Frustrated Lewis Pair Active Sites in Porous Organic Scaffolds for Catalytic CO ₂ Hydrogenation. Journal of the American Chemical Society. 146(23). 15806–15814. 10 indexed citations

Corminbœuf, Clémence, et al.. (2024). Benchmarking machine-readable vectors of chemical reactions on computed activation barriers. Digital Discovery. 3(5). 932–943. 6 indexed citations

Bunne, Charlotte, et al.. (2024). 3DReact: Geometric Deep Learning for Chemical Reactions. Journal of Chemical Information and Modeling. 64(15). 5771–5785. 7 indexed citations

Laplaza, Rubén, et al.. (2024). Microkinetic Molecular Volcano Plots for Enhanced Catalyst Selectivity and Activity Predictions. ACS Catalysis. 14(13). 9829–9839. 4 indexed citations

Laplaza, Rubén, et al.. (2024). Inverse Design of Singlet‐Fission Materials with Uncertainty‐Controlled Genetic Optimization. Angewandte Chemie. 137(3). 3 indexed citations

Das, Shubhajit, et al.. (2023). Theory-guided development of homogeneous catalysts for the reduction of CO₂to formate, formaldehyde, and methanol derivatives. Chemical Science. 14(11). 2799–2807. 17 indexed citations

Laplaza, Rubén, et al.. (2023). Genetic Algorithms for the Discovery of Homogeneous Catalysts. CHIMIA International Journal for Chemistry. 77(1/2). 39–39. 8 indexed citations

Wodrich, Matthew D., et al.. (2023). Reply to Comment on ‘Physics-based representations for machine learning properties of chemical reactions’. Machine Learning Science and Technology. 4(4). 48002–48002. 3 indexed citations

10.

Wodrich, Matthew D., et al.. (2022). Mapping Catalyst–Solvent Interplay in Competing Carboamination/Cyclopropanation Reactions. Chemistry - A European Journal. 28(41). e202200399–e202200399. 4 indexed citations

11.

Laplaza, Rubén, et al.. (2022). The (not so) simple prediction of enantioselectivity – a pipeline for high-fidelity computations. Chemical Science. 13(23). 6858–6864. 16 indexed citations

12.

Garner, Marc H., Rubén Laplaza, & Clémence Corminbœuf. (2022). Helical versus linear Jahn–Teller distortions in allene and spiropentadiene radical cations. Physical Chemistry Chemical Physics. 24(42). 26134–26143. 5 indexed citations

13.

Schwaller, Philippe, Alain C. Vaucher, Rubén Laplaza, et al.. (2022). Machine intelligence for chemical reaction space. Wiley Interdisciplinary Reviews Computational Molecular Science. 12(5). 61 indexed citations

14.

Laplaza, Rubén, Shubhajit Das, Matthew D. Wodrich, & Clémence Corminbœuf. (2022). Constructing and interpreting volcano plots and activity maps to navigate homogeneous catalyst landscapes. Nature Protocols. 17(11). 2550–2569. 27 indexed citations

15.

Fabrizio, Alberto, et al.. (2022). Physics-based representations for machine learning properties of chemical reactions. Machine Learning Science and Technology. 3(4). 45005–45005. 21 indexed citations

16.

Laplaza, Rubén, et al.. (2021). Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts. Chemical Science. 12(20). 6879–6889. 73 indexed citations

17.

Sawatlon, Boodsarin, Matthew D. Wodrich, Benjamin Meyer, Alberto Fabrizio, & Clémence Corminbœuf. (2019). Data Mining the C−C Cross‐Coupling Genome. ChemCatChem. 11(16). 4096–4107. 21 indexed citations

18.

Wodrich, Matthew D., Boodsarin Sawatlon, Ephrath Solel, Sebastian Kozuch, & Clémence Corminbœuf. (2019). Activity-Based Screening of Homogeneous Catalysts through the Rapid Assessment of Theoretically Derived Turnover Frequencies. ACS Catalysis. 9(6). 5716–5725. 56 indexed citations

19.

Palumbo, Chad T., Luciano Barluzzi, Rosario Scopelliti, et al.. (2019). Tuning the structure, reactivity and magnetic communication of nitride-bridged uranium complexes with the ancillary ligands. Chemical Science. 10(38). 8840–8849. 33 indexed citations

20.

Luisier, Nicolas, et al.. (2012). A ratiometric fluorescence sensor for caffeine. Organic & Biomolecular Chemistry. 10(37). 7487–7487. 20 indexed citations

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.

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