Igor Sokolović

494 total citations
18 papers, 361 citations indexed

About

Igor Sokolović is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Electrical and Electronic Engineering. According to data from OpenAlex, Igor Sokolović has authored 18 papers receiving a total of 361 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Materials Chemistry, 9 papers in Atomic and Molecular Physics, and Optics and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Igor Sokolović's work include Electronic and Structural Properties of Oxides (9 papers), Machine Learning in Materials Science (4 papers) and Magnetic and transport properties of perovskites and related materials (4 papers). Igor Sokolović is often cited by papers focused on Electronic and Structural Properties of Oxides (9 papers), Machine Learning in Materials Science (4 papers) and Magnetic and transport properties of perovskites and related materials (4 papers). Igor Sokolović collaborates with scholars based in Austria, Czechia and Italy. Igor Sokolović's co-authors include Ulrike Diebold, Michael Schmid, Martin Setvín, Michele Reticcioli, Cesare Franchini, M. Wagner, Giada Franceschi, Jan Balajka, Jiří Pavelec and Michele Riva and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Angewandte Chemie International Edition.

In The Last Decade

Igor Sokolović

16 papers receiving 358 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Igor Sokolović Austria	10	255	100	94	63	51	18	361
Min‐Ye Zhang China	8	217 0.9×	171 1.7×	200 2.1×	61 1.0×	50 1.0×	15	416
Sen Shao China	10	271 1.1×	59 0.6×	137 1.5×	65 1.0×	51 1.0×	32	450
Péter Rajczy Hungary	3	264 1.0×	77 0.8×	125 1.3×	46 0.7×	37 0.7×	5	372
Héloïse Tissot France	13	238 0.9×	89 0.9×	93 1.0×	71 1.1×	29 0.6×	27	373
Laura Scalfi France	10	100 0.4×	49 0.5×	106 1.1×	78 1.2×	54 1.1×	15	320
Yuichiro Shiozawa Japan	12	288 1.1×	112 1.1×	64 0.7×	71 1.1×	30 0.6×	18	391
İlker Demiroğlu Türkiye	16	564 2.2×	122 1.2×	284 3.0×	70 1.1×	69 1.4×	28	685
H. N. Fernández-Escamilla Mexico	13	327 1.3×	125 1.3×	201 2.1×	36 0.6×	55 1.1×	46	439
Mauricio D. Arce Argentina	13	265 1.0×	105 1.1×	137 1.5×	13 0.2×	72 1.4×	28	373

Countries citing papers authored by Igor Sokolović

Since Specialization

Citations

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

Fields of papers citing papers by Igor Sokolović

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Igor Sokolović

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

All Works

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18 of 18 papers shown

Sokolović, Igor, Michael Schmid, Ulrike Diebold, & Martin Setvín. (2025). How to cleave cubic perovskite oxides. Review of Scientific Instruments. 96(3). 1 indexed citations

Sokolović, Igor, Thomas Waas, Samuel Poncé, et al.. (2025). Duality and degeneracy lifting in two-dimensional electron liquids on SrTiO3(001). Nature Communications. 16(1). 4594–4594.

Sokolović, Igor, Krisztián Palotás, Martin Setvín, et al.. (2024). Machine learning-based prediction of polaron-vacancy patterns on the TiO2(110) surface. npj Computational Materials. 10(1). 6 indexed citations

Söll, Aljoscha, Jan Luxa, Jiří Šturala, et al.. (2024). High-κ Wide-Gap Layered Dielectric for Two-Dimensional van der Waals Heterostructures. ACS Nano. 18(15). 10397–10406. 22 indexed citations

Puppin, Michele, et al.. (2024). Real- and reciprocal space characterization of the three-dimensional charge density wave in quasi-one-dimensional CuTe. Physical review. B.. 110(11).

Franceschi, Giada, Jan Balajka, Igor Sokolović, et al.. (2023). Interaction of surface cations of cleaved mica with water in vapor and liquid forms. Faraday Discussions. 249(0). 84–97. 6 indexed citations

Franceschi, Giada, Pavel Kocán, Jan Balajka, et al.. (2023). Resolving the intrinsic short-range ordering of K+ ions on cleaved muscovite mica. Nature Communications. 14(1). 208–208. 31 indexed citations

Sokolović, Igor, Martin Setvín, Michael Schmid, et al.. (2023). Automated real-space lattice extraction for atomic force microscopy images. Machine Learning Science and Technology. 4(1). 15015–15015. 6 indexed citations

Merte, Lindsay R., Igor Sokolović, Martin Setvín, et al.. (2022). Structure of an Ultrathin Oxide on Pt₃Sn(111) Solved by Machine Learning Enhanced Global Optimization**. Angewandte Chemie. 134(25). e202204244–e202204244. 5 indexed citations

10.

Wang, Zhichang, Michele Reticcioli, Zdeněk Jakub, et al.. (2022). Surface chemistry on a polarizable surface: Coupling of CO with KTaO₃(001). Science Advances. 8(33). eabq1433–eabq1433. 10 indexed citations

11.

Chen, Hao, Igor Sokolović, Francesca Mirabella, et al.. (2022). Water Structures Reveal Local Hydrophobicity on the In₂O₃(111) Surface. ACS Nano. 16(12). 21163–21173. 20 indexed citations

12.

Merte, Lindsay R., Igor Sokolović, Martin Setvín, et al.. (2022). Structure of an Ultrathin Oxide on Pt ₃ Sn(111) Solved by Machine Learning Enhanced Global Optimization**. Angewandte Chemie International Edition. 61(25). e202204244–e202204244. 29 indexed citations

13.

Sokolović, Igor, Giada Franceschi, Zhichang Wang, et al.. (2021). Quest for a pristine unreconstructed SrTiO3(001) surface: An atomically resolved study via noncontact atomic force microscopy. Physical review. B.. 103(24). 19 indexed citations

14.

Sokolović, Igor, Michele Reticcioli, M. Wagner, et al.. (2020). Resolving the adsorption of molecular O ₂ on the rutile TiO ₂ (110) surface by noncontact atomic force microscopy. Proceedings of the National Academy of Sciences. 117(26). 14827–14837. 59 indexed citations

15.

Reticcioli, Michele, Igor Sokolović, Michael Schmid, et al.. (2019). Interplay between Adsorbates and Polarons: CO on Rutile TiO2(110). Physical Review Letters. 122(1). 16805–16805. 90 indexed citations

16.

Jakub, Zdeněk, Florian Kraushofer, Jan Balajka, et al.. (2019). Partially Dissociated Water Dimers at the Water–Hematite Interface. ACS Energy Letters. 4(2). 390–396. 34 indexed citations

17.

Boatner, L. A., et al.. (2019). Defect chemistry of Eu dopants in NaI scintillators studied by atomically resolved force microscopy. Physical Review Materials. 3(7). 2 indexed citations

18.

Sokolović, Igor, et al.. (2017). Devil's staircase and the absence of chaos in the dc- and ac-driven overdamped Frenkel-Kontorova model. Physical review. E. 96(2). 22210–22210. 21 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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