Ronald G. Larson

39.0k total citations · 11 hit papers
465 papers, 29.8k citations indexed

About

Ronald G. Larson is a scholar working on Fluid Flow and Transfer Processes, Materials Chemistry and Polymers and Plastics. According to data from OpenAlex, Ronald G. Larson has authored 465 papers receiving a total of 29.8k indexed citations (citations by other indexed papers that have themselves been cited), including 216 papers in Fluid Flow and Transfer Processes, 148 papers in Materials Chemistry and 136 papers in Polymers and Plastics. Recurrent topics in Ronald G. Larson's work include Rheology and Fluid Dynamics Studies (216 papers), Polymer crystallization and properties (116 papers) and Surfactants and Colloidal Systems (95 papers). Ronald G. Larson is often cited by papers focused on Rheology and Fluid Dynamics Studies (216 papers), Polymer crystallization and properties (116 papers) and Surfactants and Colloidal Systems (95 papers). Ronald G. Larson collaborates with scholars based in United States, Germany and Ukraine. Ronald G. Larson's co-authors include Hua Hu, Senthil Kumar Kandasamy, Hwankyu Lee, Tom McLeish, Eric S. G. Shaqfeh, Xavier Périole, ‪Siewert J. Marrink, D. Peter Tieleman, Luca Monticelli and D. W. Mead and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Ronald G. Larson

457 papers receiving 28.9k citations

Hit Papers

The Structure and Rheology of Complex Fluids 1990 2026 2002 2014 1998 2008 2002 1992 2005 500 1000 1.5k 2.0k 2.5k
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.

  1. The Structure and Rheology of Complex Fluids
    1998 2.6k citations Ronald G. Larson profile →
  2. The MARTINI Coarse-Grained Force Field: Extension to Proteins
    2008 2.0k citations Ronald G. Larson et al. profile →
  3. Evaporation of a Sessile Droplet on a Substrate
    2002 1.2k citations Ronald G. Larson et al. profile →
  4. Instabilities in viscoelastic flows
    1992 739 citations Ronald G. Larson profile →
  5. Analysis of the Effects of Marangoni Stresses on the Microflow in an Evaporating Sessile Droplet
    2005 721 citations Ronald G. Larson et al. Langmuir profile →
  6. Molecular constitutive equations for a class of branched polymers: The pom-pom polymer
    1998 614 citations Ronald G. Larson et al. Journal of Rheology profile →
  7. Analysis of the Microfluid Flow in an Evaporating Sessile Droplet
    2005 546 citations Ronald G. Larson et al. Langmuir profile →
  8. Stretching of a Single Tethered Polymer in a Uniform Flow
    1995 482 citations Ronald G. Larson et al. profile →
  9. Nonadditivity of nanoparticle interactions
    2015 434 citations Carlos A. Silvera Batista, Ronald G. Larson et al. profile →
  10. A purely elastic instability in Taylor–Couette flow
    1990 415 citations Ronald G. Larson et al. profile →
  11. A review of thixotropy and its rheological modeling
    2019 250 citations Ronald G. Larson et al. Journal of Rheology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ronald G. Larson United States 80 10.3k 8.3k 6.6k 6.5k 4.9k 465 29.8k
Masao Doi Japan 64 8.1k 0.8× 7.9k 0.9× 6.3k 1.0× 5.4k 0.8× 2.1k 0.4× 320 22.6k
Gary S. Grest United States 87 4.9k 0.5× 16.0k 1.9× 5.9k 0.9× 5.4k 0.8× 3.5k 0.7× 449 31.5k
Kurt Kremer Germany 83 5.8k 0.6× 15.9k 1.9× 6.9k 1.1× 6.4k 1.0× 1.1k 0.2× 355 29.2k
Thomas A. Witten United States 49 2.6k 0.3× 11.5k 1.4× 3.3k 0.5× 7.7k 1.2× 4.2k 0.9× 157 32.5k
Juan Pablo United States 100 3.7k 0.4× 18.0k 2.2× 4.2k 0.6× 9.5k 1.5× 1.7k 0.4× 790 37.7k
Jack F. Douglas United States 81 2.5k 0.2× 16.2k 2.0× 8.7k 1.3× 7.1k 1.1× 2.2k 0.5× 548 28.7k
Norman J. Wagner United States 68 4.8k 0.5× 7.9k 0.9× 3.6k 0.6× 3.7k 0.6× 2.0k 0.4× 373 19.0k
S. F. Edwards United Kingdom 59 7.8k 0.8× 9.9k 1.2× 6.1k 0.9× 4.9k 0.8× 2.7k 0.6× 257 25.8k
Michael Rubinstein United States 78 3.1k 0.3× 8.4k 1.0× 6.3k 1.0× 5.4k 0.8× 721 0.1× 286 26.9k
Frank S. Bates United States 111 5.7k 0.6× 31.7k 3.8× 16.3k 2.5× 6.4k 1.0× 1.5k 0.3× 580 54.0k

Countries citing papers authored by Ronald G. Larson

Since Specialization
Citations

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

Fields of papers citing papers by Ronald G. Larson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ronald G. Larson. 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 Ronald G. Larson. The network helps show where Ronald G. Larson may publish in the future.

Co-authorship network of co-authors of Ronald G. Larson

This figure shows the co-authorship network connecting the top 25 collaborators of Ronald G. Larson. A scholar is included among the top collaborators of Ronald G. Larson 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 Ronald G. Larson. Ronald G. Larson 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.
2.
Mateen, Khalid, et al.. (2025). Dependence of rheological behavior of waxy oils on wax composition and cooling and shear histories. Journal of Rheology. 69(5). 713–730.
3.
Larson, Ronald G., et al.. (2025). Interpretable active learning meta-modeling for the association dynamics of telechelic polymers on colloidal particles. Journal of Rheology. 69(2). 183–199. 2 indexed citations
4.
Liu, Gang, et al.. (2024). Multiple Relaxations and Entanglement Behaviors of Polymerized Ionic Liquids with Various Anions/Cations. Macromolecules. 58(1). 627–638. 2 indexed citations
5.
Parthasarathy, Gopal, et al.. (2023). Brownian dynamics simulations of telechelic polymer – latex suspensions under steady shear. Soft Matter. 19(16). 2949–2961. 3 indexed citations
6.
Zou, Weizhong, et al.. (2023). Wormlike Micelles revisited: A comparison of models for linear rheology. Journal of Non-Newtonian Fluid Mechanics. 322. 105149–105149. 9 indexed citations
7.
Sato, Takeshi, et al.. (2023). Testing the Ability of the Slip-Spring Model to Describe Constraint Release Effects Using Experimental Linear and Nonlinear Rheology. Macromolecules. 56(20). 8116–8132. 4 indexed citations
8.
Zou, Weizhong, et al.. (2023). Mesoscopic modeling of the effect of branching on the viscoelasticity of entangled wormlike micellar solutions. Physical Review Research. 5(4). 7 indexed citations
9.
Roy, O., et al.. (2023). On the selection of rheological tests for the prediction of 3D printability. Journal of Rheology. 67(4). 791–791. 27 indexed citations
10.
Liu, Gang, Ronald G. Larson, Lei Li, et al.. (2023). Influence of Chain Entanglement on Rheological and Mechanical Behaviors of Polymerized Ionic Liquids. Macromolecules. 56(7). 2719–2728. 15 indexed citations
11.
Larson, Ronald G., et al.. (2022). A machine learning enabled hybrid optimization framework for efficient coarse-graining of a model polymer. npj Computational Materials. 8(1). 20 indexed citations
12.
Zhang, Wenlin, et al.. (2022). Interfacial Oriented Precursor to Secondary Nucleation of Alkane Oligomer Crystals Revealed by Molecular Dynamic Simulations. Macromolecules. 55(15). 6311–6320. 6 indexed citations
13.
Ginzburg, Valeriy V., et al.. (2020). Strategy for reducing molecular ensemble size for efficient rheological modeling of commercial polymers. Journal of Rheology. 65(1). 43–57. 3 indexed citations
14.
Friedowitz, Sean, et al.. (2018). Role of electrostatic correlations in polyelectrolyte charge association. The Journal of Chemical Physics. 149(16). 163335–163335. 59 indexed citations
15.
Batista, Carlos A. Silvera, et al.. (2017). Controlled Levitation of Colloids through Direct Current Electric Fields. Langmuir. 33(41). 10861–10867. 10 indexed citations
16.
Zou, Weizhong & Ronald G. Larson. (2016). A hybrid Brownian dynamics/constitutive model for yielding, aging, and rejuvenation in deforming polymeric glasses. Soft Matter. 12(32). 6757–6770. 9 indexed citations
17.
Chen, Zheng, R. Graham, Mark A. Burns, & Ronald G. Larson. (2007). Modeling ssDNA electrophoretic migration with band broadening in an entangled or cross‐linked network. Electrophoresis. 28(16). 2783–2800. 6 indexed citations
18.
Goyal, Shreya, et al.. (1999). Modelling Impact Forces In Elastomers. WIT transactions on modelling and simulation. 22. 1 indexed citations
19.
Mead, D. W., Ronald G. Larson, & Mitsunobu Doi. (1998). A Molecular Theory for Fast Flows of Entangled Polymers. Macromolecules. 31(22). 7895–7914. 325 indexed citations
20.
Gleeson, J. T., Ronald G. Larson, D. W. Mead, Gábor Kiss, & P. E. Cladis. (1992). Image analysis of shear-induced textures in liquid-crystalline polymers. Liquid Crystals. 11(3). 341–364. 56 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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