Maxime Munch

479 citations
16 papers · 359 · h-index 10

Impact in

Papers in

Maxime Munch

16 papers receiving 357 citations

Peers

Maxime Munch
Comparison fields: 5 of 43
  • Process Chemistry and Technology 42
  • Pharmaceutical Science 70
  • Physical and Theoretical Chemistry 81
  • Organic Chemistry 144
  • Spectroscopy 60
Replace Ayan Dasgupta with:
Ayan Dasgupta United Kingdom
Jorge Meijide Suárez France
Ka‐Ho Lee Hong Kong
Abolghasem Bakhoda United States
Chris Gendy Canada
Marina Ya. Demakova Russia
Gary J. Balaich United States
James P. Shanahan United States
Luciano Cuesta Spain
Kenneth B. Capps United States
Maxime Munch relative to Ayan Dasgupta United Kingdom Ayan Dasgupta's profile →
Citations per field
00.5×2.6×
Ayan Dasgupta · 1×
Citations per year

Countries citing papers authored by Maxime Munch

Since Specialization
Citations

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

Fields of papers citing papers by Maxime Munch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Maxime Munch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Maxime Munch Line = papers co-authored together Maxime Munch links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 202185
2 201652
3 202049
4 201835
5 202234
6 202226
7 201715
8 202114
9 202013
10 202012
11 20217
12 20246
13 20166
14 20232
15 20222
16
Multimodality imaging to predict calcific aortic valve disease progression in animal models
20201

About Maxime Munch

Maxime Munch is a scholar working on Materials Chemistry, Organic Chemistry, Pharmaceutical Science, Physical and Theoretical Chemistry and Process Chemistry and Technology, having authored 16 papers that have together received 359 indexed citations. Recurring topics across this work include Luminescence and Fluorescent Materials (6 papers), Fluorine in Organic Chemistry (5 papers), Chemical Reactions and Isotopes (4 papers), Photochemistry and Electron Transfer Studies (4 papers), Porphyrin and Phthalocyanine Chemistry (2 papers), Amino Acid Enzymes and Metabolism (2 papers), Carbon dioxide utilization in catalysis (2 papers) and Radical Photochemical Reactions (2 papers). The work is most often cited by research in Process Chemistry and Technology (42 citations), Pharmaceutical Science (70 citations), Physical and Theoretical Chemistry (81 citations), Organic Chemistry (144 citations) and Spectroscopy (60 citations). Maxime Munch has collaborated with scholars based in Canada, France and Germany. Frequent co-authors include Gilles Ulrich, Benjamin H. Rotstein, Julien Massue, Rylan J. Lundgren, Duanyang Kong, Pauline M. Vérité, Denis Jacquemin, Karima Benelhadj, Denis Frath and Pascal Retailleau. Their work appears in journals such as Organic & Biomolecular Chemistry, ChemCatChem, The Journal of Physical Chemistry B, Tetrahedron and Molecular Imaging and Biology.

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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