Mosayeb Naseri

3.8k total citations
128 papers, 3.1k citations indexed

About

Mosayeb Naseri is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Artificial Intelligence. According to data from OpenAlex, Mosayeb Naseri has authored 128 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Materials Chemistry, 36 papers in Atomic and Molecular Physics, and Optics and 34 papers in Artificial Intelligence. Recurrent topics in Mosayeb Naseri's work include 2D Materials and Applications (55 papers), MXene and MAX Phase Materials (45 papers) and Quantum Computing Algorithms and Architecture (28 papers). Mosayeb Naseri is often cited by papers focused on 2D Materials and Applications (55 papers), MXene and MAX Phase Materials (45 papers) and Quantum Computing Algorithms and Architecture (28 papers). Mosayeb Naseri collaborates with scholars based in Iran, Vietnam and Mexico. Mosayeb Naseri's co-authors include D.M. Hoat, Jaafar Jalilian, Shahrokh Heidari, Ahmed Farouk, Fariborz Parandin, J.F. Rivas‐Silva, Gregorio H. Cocoletzi, Josep Amengual i Batle, Tuan V. Vu and R. Ponce‐Pérez and has published in prestigious journals such as Journal of Applied Physics, Scientific Reports and The Journal of Physical Chemistry C.

In The Last Decade

Mosayeb Naseri

125 papers receiving 3.0k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mosayeb Naseri 1.7k 881 715 648 388 128 3.1k
Maxim Ziatdinov 1.9k 1.1× 779 0.9× 211 0.3× 626 1.0× 185 0.5× 143 3.0k
Dohun Kim 1.3k 0.7× 895 1.0× 447 0.6× 1.5k 2.3× 262 0.7× 120 2.9k
Sriram Krishnamoorthy 2.8k 1.6× 1.6k 1.8× 401 0.6× 794 1.2× 2.9k 7.4× 255 6.5k
Jiajun Ma 497 0.3× 390 0.4× 593 0.8× 718 1.1× 313 0.8× 197 2.2k
Mingjun Wang 1.1k 0.6× 2.0k 2.2× 143 0.2× 293 0.5× 1.2k 3.0× 197 4.2k
Minho Park 1.2k 0.7× 1.5k 1.7× 358 0.5× 342 0.5× 236 0.6× 165 3.2k
Junwei Liu 4.2k 2.5× 1.2k 1.3× 499 0.7× 4.0k 6.2× 804 2.1× 102 6.5k
Alexis De Vos 788 0.5× 1.7k 1.9× 684 1.0× 434 0.7× 71 0.2× 158 3.6k
D. A. Allwood 1.8k 1.0× 1.9k 2.1× 217 0.3× 3.7k 5.7× 1.8k 4.6× 111 5.6k
László B. Kish 473 0.3× 1.5k 1.7× 307 0.4× 316 0.5× 88 0.2× 213 3.2k

Countries citing papers authored by Mosayeb Naseri

Since Specialization
Citations

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

Fields of papers citing papers by Mosayeb Naseri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mosayeb Naseri

This figure shows the co-authorship network connecting the top 25 collaborators of Mosayeb Naseri. A scholar is included among the top collaborators of Mosayeb Naseri 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 Mosayeb Naseri. Mosayeb Naseri 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.
Naseri, Mosayeb, Maicon Pierre Lourenço, Gabriela Díaz, et al.. (2025). ABO3 materials clustering with quantum swap-test algorithm. Computational Materials Science. 259. 114178–114178.
2.
Lourenço, Maicon Pierre, et al.. (2025). Seeking metal–organic frameworks for hydrogen storage using classical and quantum active learning. Physical Chemistry Chemical Physics. 27(43). 23365–23379.
3.
Gusarov, Sergey, et al.. (2025). Janus group V1B-based pnictogen-halide monolayers: a new class of multifunctional quantum materials from first-principles predictions. Physical Chemistry Chemical Physics. 27(16). 8158–8166. 1 indexed citations
4.
Naseri, Mosayeb, et al.. (2025). Innovative Quantum Encryption Method for RGB Images Based on Bit-Planes and Logistic Maps. Computation. 13(2). 56–56. 2 indexed citations
5.
Lourenço, Maicon Pierre, et al.. (2025). Quantum Active Learning for Structural Determination of Doped Nanoparticles - A Case Study of 4Al@Si11. Journal of the Brazilian Chemical Society. 1 indexed citations
6.
Gusarov, Sergey, Jaafar Jalilian, Gap Soo Chang, & Mosayeb Naseri. (2024). Comprehensive DFT Study of Two-Dimensional Molybdenene and Molybdenum Carbide Phases. The Journal of Physical Chemistry C. 128(37). 15694–15703. 4 indexed citations
7.
Naseri, Mosayeb, Sergey Gusarov, & Dennis R. Salahub. (2023). Quantum Machine Learning in Materials Prediction: A Case Study on ABO3 Perovskite Structures. The Journal of Physical Chemistry Letters. 14(31). 6940–6947. 13 indexed citations
8.
Naseri, Mosayeb, et al.. (2023). Visible light response in 2D QBi (Q=Si, Ge and Sn) monolayer semiconductors: A DFT based study. Materials Today Communications. 35. 105886–105886. 6 indexed citations
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Bafekry, A., Mosayeb Naseri, Mehrdad Faraji, et al.. (2022). Theoretical prediction of two-dimensional BC2X (X = N, P, As) monolayers: ab initio investigations. Scientific Reports. 12(1). 22269–22269. 80 indexed citations
12.
Hoat, D.M., Võ Văn Ớn, Duy Khanh Nguyen, et al.. (2020). Structural, electronic and optical properties of pristine and functionalized MgO monolayers: a first principles study. RSC Advances. 10(66). 40411–40420. 30 indexed citations
13.
Obeid, Mohammed M., Catherine Stampfl, A. Bafekry, et al.. (2020). First-principles investigation of nonmetal doped single-layer BiOBr as a potential photocatalyst with a low recombination rate. Physical Chemistry Chemical Physics. 22(27). 15354–15364. 88 indexed citations
14.
Hoat, D.M., et al.. (2020). New equiatomic quaternary Heusler compounds without transition metals KCaBX (X = S and Se): Robust half-metallicity and optical properties. Journal of Molecular Graphics and Modelling. 100. 107642–107642. 8 indexed citations
15.
Hoat, D.M., Mosayeb Naseri, Nguyen N. Hieu, et al.. (2019). Structural and electronic properties of chemically functionalized SnC monolayer: a first principles study. Materials Research Express. 7(1). 15013–15013. 24 indexed citations
16.
Naseri, Mosayeb & D.M. Hoat. (2019). First principles investigation on elastic, optoelectronic and thermoelectric properties of KYX (X = Ge, Sn and Pb) half-heusler compounds. Journal of Molecular Graphics and Modelling. 92. 249–255. 22 indexed citations
17.
Naseri, Mosayeb, et al.. (2019). Theoretical prediction of 2D XI2 (X=Si, Ge, Sn, Pb) monolayers by density functional theory. Journal of Molecular Graphics and Modelling. 95. 107501–107501. 24 indexed citations
18.
Naseri, Mosayeb, et al.. (2017). Elektronické a optické vlastnosti pentagonální B2C monovrstvy: výpočet prvních principů. International Journal of Modern Physics B. 11 indexed citations
19.
Rezaee, Sahar, et al.. (2014). Elastic and optical properties of zinc‐blende CrSb and its effective mass. Rare Metals. 33(5). 615–621. 13 indexed citations
20.
Naseri, Mosayeb. (2011). A weak blind signature based on quantum cryptography. International Journal of the Physical Sciences. 6(21). 5051–5053. 17 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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