Martin Lı́sal

3.9k total citations
148 papers, 3.2k citations indexed

About

Martin Lı́sal is a scholar working on Biomedical Engineering, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Martin Lı́sal has authored 148 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Biomedical Engineering, 69 papers in Materials Chemistry and 46 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Martin Lı́sal's work include Phase Equilibria and Thermodynamics (55 papers), Block Copolymer Self-Assembly (37 papers) and Thermodynamic properties of mixtures (27 papers). Martin Lı́sal is often cited by papers focused on Phase Equilibria and Thermodynamics (55 papers), Block Copolymer Self-Assembly (37 papers) and Thermodynamic properties of mixtures (27 papers). Martin Lı́sal collaborates with scholars based in Czechia, United States and Canada. Martin Lı́sal's co-authors include John K. Brennan, William R. Smith, Ivó Nezbeda, Filip Moučka, Jiřı́ Kolafa, Zuzana Limpouchová, Karel Procházka, Keith E. Gubbins, V. Vacek and Pavel Izák and has published in prestigious journals such as The Journal of Chemical Physics, The Journal of Physical Chemistry B and Macromolecules.

In The Last Decade

Martin Lı́sal

144 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Lı́sal Czechia 32 1.4k 1.2k 848 811 488 148 3.2k
Patrice Malfreyt France 44 1.8k 1.3× 1.7k 1.4× 1.2k 1.4× 780 1.0× 421 0.9× 171 4.6k
José Alejandre Mexico 34 1.9k 1.3× 2.0k 1.7× 1.6k 1.9× 508 0.6× 624 1.3× 95 4.4k
Fernando Bresme United Kingdom 39 1.7k 1.2× 1.4k 1.1× 1.3k 1.6× 823 1.0× 156 0.3× 161 4.9k
H. D. Cochran United States 34 943 0.7× 1.7k 1.4× 874 1.0× 525 0.6× 759 1.6× 85 3.1k
In‐Chul Yeh United States 20 1.1k 0.8× 1.1k 0.9× 1.2k 1.4× 222 0.3× 280 0.6× 40 3.6k
Leo Lue United Kingdom 32 1.1k 0.8× 1.2k 1.0× 619 0.7× 334 0.4× 392 0.8× 124 2.7k
R. Triolo Italy 29 831 0.6× 712 0.6× 525 0.6× 958 1.2× 540 1.1× 132 3.0k
S. Karaborni Netherlands 20 700 0.5× 902 0.8× 780 0.9× 874 1.1× 364 0.7× 36 2.5k
Eric Tyrode Sweden 33 788 0.6× 550 0.5× 1.5k 1.7× 604 0.7× 198 0.4× 60 3.3k
John K. Brennan United States 27 1.2k 0.9× 759 0.6× 353 0.4× 341 0.4× 159 0.3× 86 2.2k

Countries citing papers authored by Martin Lı́sal

Since Specialization
Citations

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

Fields of papers citing papers by Martin Lı́sal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Lı́sal

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Lı́sal. A scholar is included among the top collaborators of Martin Lı́sal 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 Martin Lı́sal. Martin Lı́sal 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.
Lı́sal, Martin, et al.. (2025). Molecular simulations of cesium halide aqueous solutions and crystalline salts using phase-transferable polarizable force fields. Journal of Molecular Liquids. 424. 127121–127121.
2.
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Lı́sal, Martin, et al.. (2025). Confined active particles: wall accumulation and correspondence between active and fluid systems. Soft Matter. 21(38). 7544–7564. 1 indexed citations
4.
Malaspina, David C., Martin Lı́sal, James P. Larentzos, et al.. (2023). Green–Kubo expressions for transport coefficients from dissipative particle dynamics simulations revisited. Physical Chemistry Chemical Physics. 26(2). 1328–1339. 2 indexed citations
5.
Boccardo, Gianluca, et al.. (2023). Development of an automated reliable method to compute transport properties from DPD equilibrium simulations: Application to simple fluids. Computer Physics Communications. 291. 108843–108843. 3 indexed citations
6.
Kowalski, Adam, et al.. (2023). Interactions of cationic surfactant-fatty alcohol monolayers with natural human hair surface: Insights from dissipative particle dynamics. Journal of Molecular Liquids. 375. 121385–121385. 6 indexed citations
7.
Malaspina, David C., Martin Lı́sal, James P. Larentzos, et al.. (2023). Transport coefficients from Einstein–Helfand relations using standard and energy-conserving dissipative particle dynamics methods. Physical Chemistry Chemical Physics. 25(17). 12025–12040. 5 indexed citations
8.
Procházka, Karel, et al.. (2022). DPD Modelling of the Self- and Co-Assembly of Polymers and Polyelectrolytes in Aqueous Media: Impact on Polymer Science. Polymers. 14(3). 404–404. 23 indexed citations
9.
Horsch, Martin, Silvia Chiacchiera, Michael A. Seaton, et al.. (2020). Ontologies for the Virtual Materials Marketplace. ePubs (Science and Technology Facilities Council, Research Councils UK). 13 indexed citations
10.
Lı́sal, Martin, et al.. (2020). Interplay between surfactant self-assembly and adsorption at hydrophobic surfaces: insights from dissipative particle dynamics. Molecular Physics. 119(15-16). 10 indexed citations
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12.
Nakajima, K., et al.. (2016). Perfect Composition Depth Profiling of Ionic Liquid Surfaces Using High-resolution RBS/ERDA. Analytical Sciences. 32(10). 1089–1094. 4 indexed citations
13.
Sellers, Michael S., Martin Lı́sal, & John K. Brennan. (2014). Exponential-six potential scaling for the calculation of free energies in molecular simulations. Molecular Physics. 113(1). 45–54. 7 indexed citations
14.
Lı́sal, Martin, et al.. (2012). Air–liquid interfaces of imidazolium-based [TF2N−] ionic liquids: insight from molecular dynamics simulations. Physical Chemistry Chemical Physics. 14(15). 5164–5164. 69 indexed citations
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Lı́sal, Martin, William R. Smith, & Jiřı́ Kolafa. (2005). Molecular Simulations of Aqueous Electrolyte Solubility:  1. The Expanded-Ensemble Osmotic Molecular Dynamics Method for the Solution Phase. The Journal of Physical Chemistry B. 109(26). 12956–12965. 66 indexed citations
17.
Smith, William R. & Martin Lı́sal. (2002). Direct Monte Carlo simulation methods for nonreacting and reacting systems at fixed total internal energy or enthalpy. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 66(1). 11104–11104. 12 indexed citations
18.
Lı́sal, Martin, Karel Aim, & Johann Fischer. (2000). Vapour–Liquid Equilibria of Dipolar Two-Centre Lennard-Jones Fluids from a Physically Based Equation of State and Computer Simulations. Molecular Simulation. 23(6). 363–388. 7 indexed citations
19.
Lı́sal, Martin, et al.. (1999). Fluid–solid boundary of the compressed EXP-6 fluids. Fluid Phase Equilibria. 154(1). 49–54. 6 indexed citations
20.
Lı́sal, Martin. (1999). Pure fluids of homonuclear and heteronuclear square-well diatomics I. Computer simulation study. Molecular Physics. 96(3). 335–347. 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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