Zvonimir Dogic

9.1k total citations · 3 hit papers
84 papers, 6.8k citations indexed

About

Zvonimir Dogic is a scholar working on Condensed Matter Physics, Mechanical Engineering and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Zvonimir Dogic has authored 84 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Condensed Matter Physics, 25 papers in Mechanical Engineering and 21 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Zvonimir Dogic's work include Micro and Nano Robotics (41 papers), Liquid Crystal Research Advancements (21 papers) and Advanced Materials and Mechanics (21 papers). Zvonimir Dogic is often cited by papers focused on Micro and Nano Robotics (41 papers), Liquid Crystal Research Advancements (21 papers) and Advanced Materials and Mechanics (21 papers). Zvonimir Dogic collaborates with scholars based in United States, Germany and Netherlands. Zvonimir Dogic's co-authors include Seth Fraden, Tim Sanchez, Stephen J. DeCamp, Daniel Needleman, Michaël Heymann, Edward Barry, Sarah L. Keller, David A. Weitz, Gijsje H. Koenderink and Daniela Nicastro and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Zvonimir Dogic

84 papers receiving 6.7k citations

Hit Papers

Spontaneous motion in hie... 2012 2026 2016 2021 2012 2017 2014 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zvonimir Dogic United States 40 2.8k 2.1k 1.5k 1.3k 1.3k 84 6.8k
Davide Marenduzzo United Kingdom 58 4.1k 1.5× 2.2k 1.1× 2.4k 1.6× 724 0.5× 3.9k 2.9× 252 10.2k
Corey S. O’Hern United States 40 1.3k 0.4× 3.9k 1.8× 1.2k 0.8× 286 0.2× 1.1k 0.8× 158 7.0k
Holger Stark Germany 41 3.3k 1.2× 2.1k 1.0× 2.4k 1.6× 148 0.1× 1.2k 0.9× 180 7.5k
Jean‐François Joanny France 58 2.5k 0.9× 2.1k 1.0× 3.8k 2.6× 3.7k 2.7× 2.5k 1.9× 194 12.2k
Madan Rao India 32 3.4k 1.2× 1.2k 0.6× 1.7k 1.2× 1.7k 1.3× 3.1k 2.4× 113 7.4k
Seth Fraden United States 44 910 0.3× 2.3k 1.1× 1.8k 1.2× 167 0.1× 1.1k 0.8× 110 6.1k
Randall D. Kamien United States 39 824 0.3× 2.0k 0.9× 1.4k 1.0× 214 0.2× 796 0.6× 147 5.9k
Vincenzo Vitelli United States 40 1.9k 0.7× 1.8k 0.9× 1.8k 1.2× 172 0.1× 388 0.3× 101 7.4k
Michael F. Hagan United States 41 1.9k 0.7× 1.3k 0.6× 971 0.7× 257 0.2× 1.9k 1.4× 114 5.4k
Bela M. Mulder Netherlands 38 568 0.2× 1.7k 0.8× 683 0.5× 641 0.5× 1.4k 1.1× 106 4.3k

Countries citing papers authored by Zvonimir Dogic

Since Specialization
Citations

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

Fields of papers citing papers by Zvonimir Dogic

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zvonimir Dogic

This figure shows the co-authorship network connecting the top 25 collaborators of Zvonimir Dogic. A scholar is included among the top collaborators of Zvonimir Dogic 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 Zvonimir Dogic. Zvonimir Dogic 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.
Tran, P., Yunrui Li, Aparna Baskaran, et al.. (2024). Deep-learning optical flow for measuring velocity fields from experimental data. Soft Matter. 20(36). 7246–7257. 3 indexed citations
2.
Wang, Shuxu, Louis Kang, Péter Salamon, et al.. (2024). Stimuli-responsive self-regulating assembly of chiral colloids for robust size and shape control. Nature Communications. 15(1). 9891–9891. 2 indexed citations
3.
Ems-McClung, Stephanie C., et al.. (2024). Structure and dynamics of motor-driven microtubule bundles. Soft Matter. 20(29). 5715–5723. 4 indexed citations
4.
Foster, Peter, Jinhye Bae, Juanjuan Zheng, et al.. (2023). Dissipation and energy propagation across scales in an active cytoskeletal material. Proceedings of the National Academy of Sciences. 120(14). e2207662120–e2207662120. 14 indexed citations
5.
Subramanian, Radhika, et al.. (2022). Engineering stability, longevity, and miscibility of microtubule-based active fluids. Soft Matter. 18(9). 1825–1835. 20 indexed citations
6.
Mitchell, Noah, et al.. (2022). Active Microphase Separation in Mixtures of Microtubules and Tip-Accumulating Molecular Motors. Physical Review X. 12(3). 22 indexed citations
7.
Mitchell, Noah, et al.. (2022). Controlling the shape and topology of two-component colloidal membranes. ePrints@IISc (Indian Institute of Science). 7 indexed citations
8.
Dogic, Zvonimir, et al.. (2020). Shear-Induced Gelation of Self-Yielding Active Networks. Physical Review Letters. 125(17). 178003–178003. 19 indexed citations
9.
Norton, Michael M., et al.. (2019). Self-organized dynamics and the transition to turbulence of confined active nematics. Proceedings of the National Academy of Sciences. 116(11). 4788–4797. 125 indexed citations
10.
Foster, Peter, Stephanie C. Ems-McClung, Claire Walczak, et al.. (2019). Actively crosslinked microtubule networks: mechanics, dynamics and filament sliding. Bulletin of the American Physical Society. 2019. 1 indexed citations
11.
Fürthauer, Sebastian, Peter Foster, Stephanie C. Ems-McClung, et al.. (2019). Self-straining of actively crosslinked microtubule networks. Nature Physics. 15(12). 1295–1300. 35 indexed citations
12.
Morris, Margaret, et al.. (2018). Microtubules soften due to cross-sectional flattening. eLife. 7. 33 indexed citations
13.
Fraden, Seth, et al.. (2016). Measuring the equation of state for a 2D colloidal membrane: A microfluidic approach to buffer exchange. Bulletin of the American Physical Society. 2016. 1 indexed citations
14.
Wang, Miao, et al.. (2014). Effects of ionic strength on nonlinear electrophoretic mobility of fd virus in solid-state nanopore. Bulletin of the American Physical Society. 2014. 2 indexed citations
15.
Gibaud, Thomas, Edward Barry, Mark J. Zakhary, et al.. (2012). Reconfigurable self-assembly through chiral control of interfacial tension. 2 indexed citations
16.
Okada, Kyoko, Francesca Bartolini, Alexandra M. Deaconescu, et al.. (2010). Adenomatous polyposis coli protein nucleates actin assembly and synergizes with the formin mDia1. The Journal of Cell Biology. 189(7). 1087–1096. 133 indexed citations
17.
Barry, Edward & Zvonimir Dogic. (2010). Entropy driven self-assembly of nonamphiphilic colloidal membranes. Proceedings of the National Academy of Sciences. 107(23). 10348–10353. 115 indexed citations
18.
Brangwynne, Clifford P., et al.. (2007). Bending Dynamics of Fluctuating Biopolymers Probed by Automated High-Resolution Filament Tracking. Biophysical Journal. 93(1). 346–359. 118 indexed citations
19.
Lettinga, M. P., Edward Barry, & Zvonimir Dogic. (2005). Self-diffusion of rod-like viruses in the nematic phase. Europhysics Letters (EPL). 71(4). 692–698. 66 indexed citations
20.
Dogic, Zvonimir. (2001). Liquid crystalline phase transitions in virus and virus/polymer suspensions. PhDT. 2 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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