G. Giupponi

1.3k total citations · 1 hit paper
17 papers, 1.0k citations indexed

About

G. Giupponi is a scholar working on Materials Chemistry, Molecular Biology and Organic Chemistry. According to data from OpenAlex, G. Giupponi has authored 17 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Materials Chemistry, 7 papers in Molecular Biology and 5 papers in Organic Chemistry. Recurrent topics in G. Giupponi's work include Protein Structure and Dynamics (4 papers), Dendrimers and Hyperbranched Polymers (4 papers) and Material Dynamics and Properties (4 papers). G. Giupponi is often cited by papers focused on Protein Structure and Dynamics (4 papers), Dendrimers and Hyperbranched Polymers (4 papers) and Material Dynamics and Properties (4 papers). G. Giupponi collaborates with scholars based in United Kingdom, Spain and Germany. G. Giupponi's co-authors include Gianni De Fabritiis, M J Harvey, D. Martin A. Buzza, Peter V. Coveney, Ignacio Pagonabarraga, Mónica Pickholz, Jens Harting, Nélido González-Segredo, Stefan J. Zasada and Mary-Ann Thyveetil and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and The Journal of Physical Chemistry B.

In The Last Decade

G. Giupponi

17 papers receiving 986 citations

Hit Papers

align trajectories

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.

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

2009 704 citations M J Harvey, G. Giupponi et al. Journal of Chemical Theory and Computation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
G. Giupponi United Kingdom	11	635	200	137	116	99	17	1.0k
Canan Atılgan Türkiye	21	1.0k 1.6×	421 2.1×	113 0.8×	145 1.3×	83 0.8×	67	1.5k
Richard Gowers United States	8	801 1.3×	276 1.4×	50 0.4×	114 1.0×	106 1.1×	18	1.4k
Parbati Biswas India	21	663 1.0×	368 1.8×	540 3.9×	244 2.1×	76 0.8×	87	1.4k
Soohyung Park United States	20	888 1.4×	141 0.7×	32 0.2×	105 0.9×	85 0.9×	41	1.4k
Max Linke Germany	8	908 1.4×	237 1.2×	32 0.2×	92 0.8×	112 1.1×	16	1.4k
Ryan R. Cheng United States	19	1.1k 1.7×	258 1.3×	69 0.5×	67 0.6×	78 0.8×	40	1.4k
Sanghyun Park South Korea	7	741 1.2×	383 1.9×	34 0.2×	75 0.6×	79 0.8×	13	1.5k
Kazuhiko Fukui Japan	21	590 0.9×	204 1.0×	73 0.5×	123 1.1×	197 2.0×	114	1.4k
Dah‐Yen Yang Taiwan	19	554 0.9×	158 0.8×	38 0.3×	83 0.7×	127 1.3×	73	1.4k
Ian M. Kenney United States	6	769 1.2×	196 1.0×	32 0.2×	99 0.9×	91 0.9×	10	1.2k

Countries citing papers authored by G. Giupponi

Since Specialization

Citations

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

Fields of papers citing papers by G. Giupponi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Giupponi

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

All Works

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17 of 17 papers shown

Giupponi, G., M. Florencia Martini, & Mónica Pickholz. (2012). Molecular Dynamics Study on the Encapsulation of Prilocaine in Liposomes at Physiological pH. Journal of Biomaterials and Tissue Engineering. 3(1). 141–147. 3 indexed citations

Giupponi, G. & Ignacio Pagonabarraga. (2011). Colloid Electrophoresis for Strong and Weak Ion Diffusivity. Physical Review Letters. 106(24). 248304–248304. 23 indexed citations

Giupponi, G. & Ignacio Pagonabarraga. (2011). Determination of the zeta potential for highly charged colloidal suspensions. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 369(1945). 2546–2554. 7 indexed citations

Pickholz, Mónica & G. Giupponi. (2010). Coarse Grained Simulations of Local Anesthetics Encapsulated into a Liposome. The Journal of Physical Chemistry B. 114(20). 7009–7015. 17 indexed citations

Harvey, M J, G. Giupponi, & Gianni De Fabritiis. (2009). ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale. Journal of Chemical Theory and Computation. 5(6). 1632–1639. 704 indexed citations breakdown →

Giupponi, G., M J Harvey, & Gianni De Fabritiis. (2008). The impact of accelerator processors for high-throughput molecular modeling and simulation. Drug Discovery Today. 13(23-24). 1052–1058. 26 indexed citations

Harvey, M J, Gianni De Fabritiis, & G. Giupponi. (2008). Accuracy of the lattice-Boltzmann method using the Cell processor. Physical Review E. 78(5). 56702–56702. 4 indexed citations

Giupponi, G., Shantenu Jha, Steven Manos, et al.. (2008). Large scale computational science on federated international grids: The role of switched optical networks. Future Generation Computer Systems. 26(1). 99–110. 7 indexed citations

Harting, Jens, et al.. (2007). Structural transitions and arrest of domain growth in sheared binary immiscible fluids and microemulsions. Physical Review E. 75(4). 41504–41504. 10 indexed citations

10.

Giupponi, G., Gianni De Fabritiis, & Peter V. Coveney. (2007). A COUPLED MOLECULAR-CONTINUUM HYBRID MODEL FOR THE SIMULATION OF MACROMOLECULAR DYNAMICS. International Journal of Modern Physics C. 18(4). 520–527. 4 indexed citations

11.

Giupponi, G., Gianni De Fabritiis, & Peter V. Coveney. (2007). Hybrid method coupling fluctuating hydrodynamics and molecular dynamics for the simulation of macromolecules. The Journal of Chemical Physics. 126(15). 154903–154903. 39 indexed citations

12.

Giupponi, G., et al.. (2007). Are Polyelectrolyte Dendrimers Stimuli Responsive?. Macromolecules. 40(16). 5959–5965. 49 indexed citations

13.

González-Segredo, Nélido, Jens Harting, G. Giupponi, & Peter V. Coveney. (2006). Stress response and structural transitions in sheared gyroidal and lamellar amphiphilic mesophases: Lattice-Boltzmann simulations. Physical Review E. 73(3). 31503–31503. 11 indexed citations

14.

Giupponi, G. & Peter V. Coveney. (2006). Non-Newtonian behaviour of the gyroid mesophase: A lattice-Boltzmann study. Mathematics and Computers in Simulation. 72(2-6). 124–127. 6 indexed citations

15.

Giupponi, G. & D. Martin A. Buzza. (2005). A Monte Carlo study of amphiphilic dendrimers: Spontaneous asymmetry and dendron separation. The Journal of Chemical Physics. 122(19). 194903–194903. 14 indexed citations

16.

Giupponi, G. & D. Martin A. Buzza. (2004). Monte Carlo simulation of dendrimers in variable solvent quality. The Journal of Chemical Physics. 120(21). 10290–10298. 45 indexed citations

17.

Giupponi, G. & D. Martin A. Buzza. (2002). A Monte Carlo Simulation Scheme for Nonideal Dendrimers Satisfying Detailed Balance. Macromolecules. 35(26). 9799–9812. 32 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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