Riccardo Conte

2.0k total citations
81 papers, 1.5k citations indexed

About

Riccardo Conte is a scholar working on Atomic and Molecular Physics, and Optics, Spectroscopy and Materials Chemistry. According to data from OpenAlex, Riccardo Conte has authored 81 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Atomic and Molecular Physics, and Optics, 37 papers in Spectroscopy and 17 papers in Materials Chemistry. Recurrent topics in Riccardo Conte's work include Advanced Chemical Physics Studies (51 papers), Spectroscopy and Quantum Chemical Studies (43 papers) and Quantum, superfluid, helium dynamics (16 papers). Riccardo Conte is often cited by papers focused on Advanced Chemical Physics Studies (51 papers), Spectroscopy and Quantum Chemical Studies (43 papers) and Quantum, superfluid, helium dynamics (16 papers). Riccardo Conte collaborates with scholars based in Italy, United States and Luxembourg. Riccardo Conte's co-authors include Joel M. Bowman, Paul L. Houston, Chen Qu, Michele Ceotto, Apurba Nandi, Qi Yu, Alessandro Rognoni, Giovanni Di Liberto, Alán Aspuru‐Guzik and Zahra Homayoon and has published in prestigious journals such as Journal of the American Chemical Society, Physical Review Letters and The Journal of Chemical Physics.

In The Last Decade

Riccardo Conte

75 papers receiving 1.5k citations

Peers

Riccardo Conte

AMPO

SPECT

CTM

Scott Habershon United Kingdom

Yury V. Suleimanov United States

Péter R. Nagy Hungary

Keiran C. Thompson Australia

Kasper Kristensen Denmark

Peter Pinski Germany

Bina Fu China

Jeremy O. Richardson Switzerland

Laimutis Bytautas United States

Aude Simon France

Scott Habershon United Kingdom

Riccardo Conte

1.5k ×1.3

AMPO

743 ×1.4

436 ×0.9

SPECT

180 ×0.9

CTM

214 ×1.3

Citations per year, relative to Riccardo Conte Riccardo Conte (= 1×) peers Scott Habershon

Countries citing papers authored by Riccardo Conte

Since Specialization

Citations

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

Fields of papers citing papers by Riccardo Conte

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Riccardo Conte

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

All Works

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20 of 20 papers shown

Mani, Devendra, et al.. (2026). Spectral Fingerprints of Hydrogen-Bonding in Water Solvation of Amino Acids. The Journal of Physical Chemistry Letters. 17(4). 888–895.

Nandi, Apurba, Riccardo Conte, Priyanka Pandey, et al.. (2025). Quantum Nature of Ubiquitous Vibrational Features Revealed for Ethylene Glycol. Journal of Chemical Theory and Computation. 21(10). 5208–5220. 4 indexed citations

Conte, Riccardo, et al.. (2025). Quantumness of classical-trajectory-based methods for vibrational spectroscopy. The Journal of Chemical Physics. 163(19).

Conte, Riccardo, et al.. (2025). A Single-Molecule Quantum Heat Engine. Nano Letters. 26(3). 984–989. 1 indexed citations

Yu, Qi, Chen Qu, Riccardo Conte, et al.. (2025). Extending atomic decomposition and many-body representation with a chemistry-motivated approach to machine learning potentials. Nature Computational Science. 5(5). 418–426. 2 indexed citations

Qu, Chen, Paul L. Houston, Riccardo Conte, et al.. (2025). Revisiting the H₅O₂⁺ IR Spectrum with VSCF/VCI and the Influence of Mark Johnson’s Experiments in Advancing the Theory of Protonated Water Clusters. The Journal of Physical Chemistry A. 129(31). 7051–7060. 1 indexed citations

Conte, Riccardo, et al.. (2024). A Perspective on the Investigation of Spectroscopy and Kinetics of Complex Molecular Systems with Semiclassical Approaches. The Journal of Physical Chemistry Letters. 15(30). 7566–7576. 14 indexed citations

Nandi, Apurba, Priyanka Pandey, Paul L. Houston, et al.. (2024). Δ-Machine Learning to Elevate DFT-Based Potentials and a Force Field to the CCSD(T) Level Illustrated for Ethanol. Journal of Chemical Theory and Computation. 20(20). 8807–8819. 9 indexed citations

Houston, Paul L., Chen Qu, Qi Yu, et al.. (2024). Formic Acid–Ammonia Heterodimer: A New Δ-Machine Learning CCSD(T)-Level Potential Energy Surface Allows Investigation of the Double Proton Transfer. Journal of Chemical Theory and Computation. 20(5). 1821–1828. 5 indexed citations

10.

Houston, Paul L., Chen Qu, Qi Yu, et al.. (2024). A New A Priori Method to Avoid Calculation of Negligible Hamiltonian Matrix Elements in CI Calculation. The Journal of Physical Chemistry A. 128(2). 479–487. 3 indexed citations

11.

Houston, Paul L., Chen Qu, Qi Yu, et al.. (2024). No Headache for PIPs: A PIP Potential for Aspirin Runs Much Faster and with Similar Precision Than Other Machine-Learned Potentials. Journal of Chemical Theory and Computation. 20(8). 3008–3018. 8 indexed citations

12.

Pandey, Priyanka, Chen Qu, Apurba Nandi, et al.. (2024). Ab Initio Potential Energy Surface for NaCl–H₂ with Correct Long-Range Behavior. The Journal of Physical Chemistry A. 128(5). 902–908. 5 indexed citations

13.

Olivieri, Gianfranco, Riccardo Conte, Serena Zanzoni, et al.. (2024). Structural dynamics of calcium and integrin-binding protein 2 (CIB2) reveal uncommon flexibility and heterogeneous calcium and magnesium loading. International Journal of Biological Macromolecules. 286. 138003–138003.

14.

Qu, Chen, Paul L. Houston, Qi Yu, et al.. (2023). Machine learning classification can significantly reduce the cost of calculating the Hamiltonian matrix in CI calculations. The Journal of Chemical Physics. 159(7). 6 indexed citations

15.

Bertaina, Gianluca, et al.. (2023). Anharmonic Assignment of the Water Octamer Spectrum in the OH Stretch Region. The Journal of Physical Chemistry A. 127(30). 6213–6221. 5 indexed citations

16.

Nandi, Apurba, Chen Qu, Riccardo Conte, et al.. (2023). Ring-Polymer Instanton Tunneling Splittings of Tropolone and Isotopomers using a Δ-Machine Learned CCSD(T) Potential: Theory and Experiment Shake Hands. Journal of the American Chemical Society. 145(17). 9655–9664. 24 indexed citations

17.

Zhao, Bin, Riccardo Conte, Christopher L. Malbon, et al.. (2022). Nonadiabatic Reactive Quenching of OH(A²Σ⁺) by H₂: Origin of High Vibrational Excitation in the H₂O Product. The Journal of Physical Chemistry A. 126(39). 6944–6952. 1 indexed citations

18.

Qu, Chen, Riccardo Conte, Paul L. Houston, & Joel M. Bowman. (2020). Full-dimensional potential energy surface for acetylacetone and tunneling splittings. Physical Chemistry Chemical Physics. 23(13). 7758–7767. 32 indexed citations

19.

Conte, Riccardo & Eli Pollak. (2010). Comparison between different Gaussian series representations of the imaginary time propagator. Physical Review E. 81(3). 36704–36704. 14 indexed citations

20.

Conte, Riccardo. (2009). Government Bond Yield Spreads: A Survey. RePEc: Research Papers in Economics. 68(3). 341–370.

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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