Francesca Tavazza

6.7k total citations · 1 hit paper
81 papers, 3.7k citations indexed

About

Francesca Tavazza is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Electrical and Electronic Engineering. According to data from OpenAlex, Francesca Tavazza has authored 81 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Materials Chemistry, 33 papers in Atomic and Molecular Physics, and Optics and 31 papers in Electrical and Electronic Engineering. Recurrent topics in Francesca Tavazza's work include Machine Learning in Materials Science (25 papers), Surface and Thin Film Phenomena (20 papers) and 2D Materials and Applications (17 papers). Francesca Tavazza is often cited by papers focused on Machine Learning in Materials Science (25 papers), Surface and Thin Film Phenomena (20 papers) and 2D Materials and Applications (17 papers). Francesca Tavazza collaborates with scholars based in United States, Italy and Switzerland. Francesca Tavazza's co-authors include Kamal Choudhary, Brian DeCost, Ankit Agrawal, Alok Choudhary, Chandler A. Becker, Kevin F. Garrity, Zachary Trautt, Ryan Beams, Irina Kalish and Lyle E. Levine and has published in prestigious journals such as Science, Physical Review Letters and Nature Communications.

In The Last Decade

Francesca Tavazza

80 papers receiving 3.6k citations

Hit Papers

align trajectories sort by overperformance

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.

Recent advances and applications of deep learning methods in materials science

2022 652 citations Kamal Choudhary, Brian DeCost et al. npj Computational Materials profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Francesca Tavazza United States	31	2.6k	934	727	420	411	81	3.7k
Kamal Choudhary United States	31	3.1k 1.2×	806 0.9×	356 0.5×	456 1.1×	441 1.1×	101	4.1k
Jonathan Schmidt Germany	18	2.0k 0.8×	699 0.7×	466 0.6×	273 0.7×	344 0.8×	33	3.1k
Luca M. Ghiringhelli Germany	30	3.2k 1.2×	1.4k 1.4×	561 0.8×	366 0.9×	216 0.5×	74	4.1k
Alexander V. Shapeev Russia	36	5.1k 1.9×	1.2k 1.3×	576 0.8×	545 1.3×	902 2.2×	98	6.1k
Jun Yuan China	30	2.0k 0.7×	1.2k 1.3×	1.0k 1.4×	726 1.7×	226 0.5×	197	4.0k
Ohad Levy United States	26	4.5k 1.7×	1.2k 1.3×	687 0.9×	725 1.7×	894 2.2×	56	6.0k
Daniel W. Davies United Kingdom	17	2.6k 1.0×	810 0.9×	422 0.6×	393 0.9×	386 0.9×	49	3.9k
Maxim Ziatdinov United States	29	1.9k 0.7×	779 0.8×	626 0.9×	387 0.9×	163 0.4×	143	3.0k
V.V. Zhirnov United States	31	2.1k 0.8×	1.9k 2.1×	770 1.1×	608 1.4×	235 0.6×	105	3.8k
Shyam Dwaraknath United States	24	2.7k 1.0×	996 1.1×	152 0.2×	309 0.7×	379 0.9×	44	3.6k

Countries citing papers authored by Francesca Tavazza

Since Specialization

Citations

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

Fields of papers citing papers by Francesca Tavazza

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesca Tavazza

This figure shows the co-authorship network connecting the top 25 collaborators of Francesca Tavazza. A scholar is included among the top collaborators of Francesca Tavazza 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 Francesca Tavazza. Francesca Tavazza 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

Gupta, Vishu, Kamal Choudhary, Brian DeCost, et al.. (2024). Structure-aware graph neural network based deep transfer learning framework for enhanced predictive analytics on diverse materials datasets. npj Computational Materials. 10(1). 44 indexed citations

Choudhary, Kamal, et al.. (2023). Unified graph neural network force-field for the periodic table: solid state applications. Digital Discovery. 2(2). 346–355. 72 indexed citations

Wines, Daniel, Ramya Gurunathan, Kevin F. Garrity, et al.. (2023). Recent progress in the JARVIS infrastructure for next-generation data-driven materials design. Applied Physics Reviews. 10(4). 23 indexed citations

Hasan, Mahmudul, Arindam Paul, Vishu Gupta, et al.. (2023). An AI-driven microstructure optimization framework for elastic properties of titanium beyond cubic crystal systems. npj Computational Materials. 9(1). 12 indexed citations

Gurunathan, Ramya, Kamal Choudhary, & Francesca Tavazza. (2023). Rapid prediction of phonon structure and properties using the atomistic line graph neural network (ALIGNN). Physical Review Materials. 7(2). 20 indexed citations

Choudhary, Kamal, et al.. (2023). Efficient computational design of two-dimensional van der Waals heterostructures: Band alignment, lattice mismatch, and machine learning. Physical Review Materials. 7(1). 30 indexed citations

Choudhary, Kamal, Brian DeCost, Chi Chen, et al.. (2022). Recent advances and applications of deep learning methods in materials science. npj Computational Materials. 8(1). 652 indexed citations breakdown →

Chowdhury, Sugata, Albert F. Rigosi, Heather M. Hill, et al.. (2022). Computational Methods for Charge Density Waves in 2D Materials. Nanomaterials. 12(3). 504–504. 9 indexed citations

Gupta, Vishu, Kamal Choudhary, Francesca Tavazza, et al.. (2021). Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data. Nature Communications. 12(1). 6595–6595. 109 indexed citations

10.

Choudhary, Kamal & Francesca Tavazza. (2019). Convergence and machine learning predictions of Monkhorst-Pack k-points and plane-wave cut-off in high-throughput DFT calculations. Computational Materials Science. 161. 300–308. 106 indexed citations

11.

Rigosi, Albert F., Heather M. Hill, Sugata Chowdhury, et al.. (2018). Probing the Dielectric Response of the Interfacial Buffer Layer in Epitaxial Graphene via Optical Spectroscopy. Bulletin of the American Physical Society. 1 indexed citations

12.

Tavazza, Francesca, et al.. (2017). Ni Nanoindentation at the Nanoscale: Atomic Rearrangements at the Ni–C Interface. The Journal of Physical Chemistry C. 121(5). 2643–2651. 7 indexed citations

13.

Mathew, Kiran, Arunima K. Singh, Kamal Choudhary, et al.. (2016). MPInterfaces: A Materials Project based Python tool for high-throughput computational screening of interfacial systems. Computational Materials Science. 122. 183–190. 97 indexed citations

14.

Becker, Chandler A., et al.. (2013). Considerations for choosing and using force fields and interatomic potentials in materials science and engineering. Current Opinion in Solid State and Materials Science. 17(6). 277–283. 203 indexed citations

15.

Barzilai, S., Francesca Tavazza, & Lyle E. Levine. (2013). Structure stability and electronic transport of gold nanowires on a BeO (0 0 0 1) surface. Modelling and Simulation in Materials Science and Engineering. 21(7). 75003–75003. 3 indexed citations

16.

Barzilai, S., Francesca Tavazza, & Lyle E. Levine. (2012). First-principle modeling of gold adsorption on BeO (0001). Surface Science. 609. 39–43. 5 indexed citations

17.

Wagner, Richard J., Li Ma, Francesca Tavazza, & Lyle E. Levine. (2008). Dislocation nucleation during nanoindentation of aluminum. Journal of Applied Physics. 104(11). 38 indexed citations

18.

Tavazza, Francesca, et al.. (2004). Hybrid Monte Carlo–molecular dynamics algorithm for the study of islands and step edges on semiconductor surfaces: Application toSi∕Si(001). Physical Review E. 70(3). 36701–36701. 7 indexed citations

19.

Tavazza, Francesca, et al.. (2003). Comparative study of Si(001) surface structure and interatomic potentials in finite-temperature simulations. Physical review. B, Condensed matter. 67(3). 24 indexed citations

20.

Schärer, Urs, et al.. (1997). Competitive metastable phase in low-temperature epitaxy ofCoSi2/Si(111). Physical review. B, Condensed matter. 55(11). 7213–7221. 9 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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