Maxime Moreaud

877 total citations
59 papers, 568 citations indexed

About

Maxime Moreaud is a scholar working on Materials Chemistry, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Maxime Moreaud has authored 59 papers receiving a total of 568 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Materials Chemistry, 13 papers in Biomedical Engineering and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Maxime Moreaud's work include Analytical Chemistry and Chromatography (10 papers), Enhanced Oil Recovery Techniques (7 papers) and Theoretical and Computational Physics (7 papers). Maxime Moreaud is often cited by papers focused on Analytical Chemistry and Chromatography (10 papers), Enhanced Oil Recovery Techniques (7 papers) and Theoretical and Computational Physics (7 papers). Maxime Moreaud collaborates with scholars based in France, Canada and Switzerland. Maxime Moreaud's co-authors include Dominique Jeulin, Vincent Souchon, Loïc Sorbier, Chantal Lorentz, Aleksandra Lelević, C. Geantet, Anne‐Sophie Gay, Pascal Raybaud, Laurent Duval and Ovidiu Ersen and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and ACS Catalysis.

In The Last Decade

Maxime Moreaud

55 papers receiving 558 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maxime Moreaud France 12 202 154 126 87 78 59 568
Bingqian Wang China 15 218 1.1× 60 0.4× 119 0.9× 55 0.6× 80 1.0× 78 709
Ivan M. Uzunov Bulgaria 18 191 0.9× 51 0.3× 134 1.1× 30 0.3× 46 0.6× 108 1.4k
Hongren Chen China 13 137 0.7× 53 0.3× 167 1.3× 39 0.4× 25 0.3× 40 551
Minjie Xu China 14 230 1.1× 172 1.1× 85 0.7× 59 0.7× 109 1.4× 29 664
Hewei Zhang China 13 118 0.6× 92 0.6× 66 0.5× 96 1.1× 28 0.4× 61 543
Martin Kraft Austria 17 91 0.5× 78 0.5× 358 2.8× 40 0.5× 150 1.9× 74 1.0k
Andrea Browning United States 13 569 2.8× 152 1.0× 111 0.9× 123 1.4× 32 0.4× 26 843
Fu Wan China 22 427 2.1× 61 0.4× 304 2.4× 52 0.6× 303 3.9× 98 1.5k
P. Germain France 13 339 1.7× 187 1.2× 239 1.9× 409 4.7× 110 1.4× 30 1.1k
Zijian Chen China 17 586 2.9× 104 0.7× 83 0.7× 94 1.1× 29 0.4× 68 1.0k

Countries citing papers authored by Maxime Moreaud

Since Specialization
Citations

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

Fields of papers citing papers by Maxime Moreaud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxime Moreaud

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

All Works

20 of 20 papers shown
1.
Alloyeau, Damien, Maxime Moreaud, Guillaume Wang, et al.. (2025). aquaDenoising: AI-enhancement of in situ liquid phase STEM video for automated quantification of nanoparticles growth. Ultramicroscopy. 271. 114121–114121. 4 indexed citations
2.
Moreaud, Maxime, et al.. (2025). Digital twin generation for adsorption in porous materials using Stochastic MorphoDeep. Communications Materials. 6(1).
3.
Bauer, D., et al.. (2024). Towards a better comprehension of reactive transport coupling experimental and numerical approaches. SHILAP Revista de lepidopterología. 79. 22–22. 1 indexed citations
4.
Moreaud, Maxime, et al.. (2024). Visualizing the fine structure and dynamics of living cells with temporal polychromatic digital holographic microscopy. Journal of the Optical Society of America A. 41(11). C109–C109.
5.
Goncalves, D. Oliveira, et al.. (2024). IPA: A deep CNN based on Inception for Petroleum Analysis. Fuel. 379. 133016–133016.
6.
Moreaud, Maxime, et al.. (2024). Characterizing microstructures with representative tortuosities. SHILAP Revista de lepidopterología. 79. 31–31. 1 indexed citations
7.
Nieto‐Draghi, Carlos, et al.. (2024). Potential Energy Surface-Based Descriptors for Nanoporous Materials and its Applications to Classification and CO2 Gas Adsorption into Zeolites. ACS Applied Engineering Materials. 2(2). 478–491. 3 indexed citations
8.
Jolimaître, Elsa, et al.. (2024). SEM Image Processing Assisted by Deep Learning to Quantify Mesoporous γ-Alumina Spatial Heterogeneity and Its Predicted Impact on Mass Transfer. The Journal of Physical Chemistry C. 128(20). 8395–8407. 3 indexed citations
9.
Stoltz, Gabriel, et al.. (2023). Computing Surface Reaction Rates by Adaptive Multilevel Splitting Combined with Machine Learning and Ab Initio Molecular Dynamics. Journal of Chemical Theory and Computation. 19(12). 3538–3550. 7 indexed citations
10.
Lelević, Aleksandra, C. Geantet, Chantal Lorentz, Maxime Moreaud, & Vincent Souchon. (2023). Score Function for the Optimization of the Performance of Forward Fill/Flush Differential Flow Modulation for Comprehensive Two-Dimensional Gas Chromatography. Journal of Chromatographic Science. 62(1). 8–20.
11.
Moreaud, Maxime, et al.. (2023). Deep learning ancient map segmentation to assess historical landscape changes. Journal of Maps. 19(1). 3 indexed citations
12.
Humbert, Séverine, et al.. (2022). Small-angle X-ray scattering intensity of multiscale models of spheroids. Journal of Applied Crystallography. 56(1). 237–246. 5 indexed citations
13.
Moreaud, Maxime, Dominique Jeulin, Elsa Jolimaître, et al.. (2022). A novel physisorption model based on mathematical morphology operators preserving exact pore morphology and connectivity. Microporous and Mesoporous Materials. 337. 111847–111847. 7 indexed citations
14.
Rouchon, Virgile, et al.. (2022). Quantification and morphological characterization of microfibers emitted from textile washing. The Science of The Total Environment. 832. 154973–154973. 36 indexed citations
15.
Moreaud, Maxime, et al.. (2021). Scalable morphological accessibility of complex microstructures. Computational Materials Science. 203. 111062–111062. 3 indexed citations
16.
Moreaud, Maxime, et al.. (2021). Simulation of Large Aggregate Particles System With a New Morphological Model. Image Analysis & Stereology. 40(2). 71–84. 11 indexed citations
17.
Lelević, Aleksandra, Vincent Souchon, C. Geantet, Chantal Lorentz, & Maxime Moreaud. (2021). Advanced data preprocessing for comprehensive two‐dimensional gas chromatography with vacuum ultraviolet spectroscopy detection. Journal of Separation Science. 44(22). 4141–4150. 7 indexed citations
18.
19.
Moreaud, Maxime, et al.. (2019). TORTUOSIMETRIC OPERATOR FOR COMPLEX POROUS MEDIA CHARACTERIZATION. Image Analysis & Stereology. 38(1). 25–25. 8 indexed citations
20.
Moreaud, Maxime, et al.. (2009). SIZE OF BOEHMITE NANOPARTICLES BY TEM IMAGES ANALYSIS. SPIRE - Sciences Po Institutional REpository. 1 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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