Mohamed Laradji

2.9k total citations
84 papers, 2.4k citations indexed

About

Mohamed Laradji is a scholar working on Materials Chemistry, Molecular Biology and Organic Chemistry. According to data from OpenAlex, Mohamed Laradji has authored 84 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Materials Chemistry, 31 papers in Molecular Biology and 26 papers in Organic Chemistry. Recurrent topics in Mohamed Laradji's work include Lipid Membrane Structure and Behavior (30 papers), Surfactants and Colloidal Systems (25 papers) and Material Dynamics and Properties (22 papers). Mohamed Laradji is often cited by papers focused on Lipid Membrane Structure and Behavior (30 papers), Surfactants and Colloidal Systems (25 papers) and Material Dynamics and Properties (22 papers). Mohamed Laradji collaborates with scholars based in United States, Denmark and India. Mohamed Laradji's co-authors include P. B. Sunil Kumar, Martin J. Zuckermann, Michael J. A. Hore, Rashmi C. Desai, Ole G. Mouritsen, Jaan Noolandi, Søren Toxværd, An‐Chang Shi, Martin Grant and Yongmei Wang and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and Physical review. B, Condensed matter.

In The Last Decade

Mohamed Laradji

76 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohamed Laradji United States 29 1.3k 763 677 434 415 84 2.4k
P. I. C. Teixeira Portugal 25 1.1k 0.8× 292 0.4× 430 0.6× 217 0.5× 780 1.9× 104 2.0k
G. J. A. Sevink Netherlands 33 2.9k 2.2× 333 0.4× 1.3k 2.0× 355 0.8× 622 1.5× 91 3.7k
Dominique Ausserré France 25 1.1k 0.8× 134 0.2× 349 0.5× 476 1.1× 539 1.3× 63 2.2k
Anand Yethiraj Canada 23 1.3k 1.0× 155 0.2× 391 0.6× 623 1.4× 603 1.5× 67 2.2k
Ronald Blaak Germany 21 880 0.7× 167 0.2× 378 0.6× 140 0.3× 284 0.7× 54 1.4k
François Detcheverry France 25 2.1k 1.6× 162 0.2× 837 1.2× 279 0.6× 824 2.0× 46 3.0k
P. J. Hoogerbrugge Netherlands 5 2.1k 1.6× 417 0.5× 1.1k 1.7× 255 0.6× 688 1.7× 7 3.3k
Elizabeth K. Mann United States 25 364 0.3× 514 0.7× 414 0.6× 396 0.9× 304 0.7× 81 1.7k
P. Pincus United States 18 713 0.5× 148 0.2× 307 0.5× 370 0.9× 370 0.9× 30 1.6k
René Messina Germany 25 722 0.6× 159 0.2× 168 0.2× 436 1.0× 568 1.4× 61 1.7k

Countries citing papers authored by Mohamed Laradji

Since Specialization
Citations

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

Fields of papers citing papers by Mohamed Laradji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohamed Laradji

This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Laradji. A scholar is included among the top collaborators of Mohamed Laradji 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 Mohamed Laradji. Mohamed Laradji 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.
Zhu, Yu, et al.. (2025). Nanostar self-assemblies of spherical nanoparticles inside lipid vesicles. Soft Matter. 21(10). 1849–1859.
2.
Zhu, Yu, et al.. (2024). Highly Ordered Nanoassemblies of Janus Spherocylindrical Nanoparticles Adhering to Lipid Vesicles. ACS Nano. 18(20). 12957–12969. 6 indexed citations
3.
Zhu, Yu, et al.. (2023). Collective vortical motion and vorticity reversals of self-propelled particles on circularly patterned substrates. Physical review. E. 107(2). 24606–24606. 7 indexed citations
4.
Zhu, Yu, et al.. (2023). Membrane-mediated dimerization of spherocylindrical nanoparticles. Soft Matter. 19(8). 1499–1512. 7 indexed citations
5.
Zhu, Yu, et al.. (2023). Lipid vesicles induced ordered nanoassemblies of Janus nanoparticles. Soft Matter. 19(12). 2204–2213. 9 indexed citations
6.
Haugen, J., Jesse D. Ziebarth, Eugene C. Eckstein, Mohamed Laradji, & Yongmei Wang. (2023). Hydrodynamic and transport behavior of solid nanoparticles simulated with dissipative particle dynamics. Advances in Natural Sciences Nanoscience and Nanotechnology. 14(2). 25006–25006. 2 indexed citations
7.
Zhu, Yu, et al.. (2022). Collective motion of cells modeled as ring polymers. Soft Matter. 18(6). 1228–1238. 7 indexed citations
8.
Laradji, Mohamed, et al.. (2020). Adhesion and Aggregation of Spherical Nanoparticles on Lipid Membranes. Chemistry and Physics of Lipids. 233. 104989–104989. 8 indexed citations
9.
Etesami, S. Alireza, Mohamed Laradji, & Ebrahim Asadi. (2018). Transferability of interatomic potentials in predicting the temperature dependency of elastic constants for titanium, zirconium and magnesium. Modelling and Simulation in Materials Science and Engineering. 27(2). 25005–25005. 4 indexed citations
10.
Laradji, Mohamed, et al.. (2016). Partial wrapping and spontaneous endocytosis of spherical nanoparticles by tensionless lipid membranes. The Journal of Chemical Physics. 144(4). 44901–44901. 37 indexed citations
11.
Modchang, Charin, et al.. (2014). Kinetics of domain registration in multicomponent lipid bilayer membranes. Soft Matter. 10(37). 7306–7315. 9 indexed citations
12.
Kumar, P. B. Sunil, et al.. (2011). Computer simulation of cytoskeleton-induced blebbing in lipid membranes. Physical Review E. 84(5). 51906–51906. 31 indexed citations
13.
Millan, Jaime A. & Mohamed Laradji. (2009). Cross-Stream Migration of Driven Polymer Solutions in Nanoscale Channels: A Numerical Study with Generalized Dissipative Particle Dynamics. Macromolecules. 42(3). 803–810. 29 indexed citations
14.
Laradji, Mohamed & P. B. Sunil Kumar. (2006). Anomalously Slow Domain Growth in Membranes with Asymmetric Transbilayer Lipid Distribution. Bulletin of the American Physical Society. 1 indexed citations
15.
Laradji, Mohamed & P. B. Sunil Kumar. (2004). Dynamics of Domain Growth in Self-Assembled Fluid Vesicles. Physical Review Letters. 93(19). 198105–198105. 200 indexed citations
16.
Laradji, Mohamed. (2004). A Langevin dynamics study of mobile filler particles in phase-separating binary systems. The Journal of Chemical Physics. 120(19). 9330–9334. 31 indexed citations
17.
Léonard, François, Mohamed Laradji, & Rashmi C. Desai. (1997). Molecular beam epitaxy in the presence of phase separation. Physical review. B, Condensed matter. 55(3). 1887–1894. 42 indexed citations
18.
Yao, Jian & Mohamed Laradji. (1993). Dynamics of Ostwald ripening in the presence of surfactants. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 47(4). 2695–2701. 23 indexed citations
19.
Laradji, Mohamed, Hong Guo, Martin Grant, & Martin J. Zuckermann. (1992). The effect of surfactants on the dynamics of phase separation. Journal of Physics Condensed Matter. 4(32). 6715–6728. 109 indexed citations
20.
Laradji, Mohamed, Hong Guo, Martin Grant, & Martin J. Zuckermann. (1991). Dynamics of phase separation in the presence of surfactants. Journal of Physics A Mathematical and General. 24(11). L629–L635. 54 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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