Anup Pandey

420 total citations
11 papers, 317 citations indexed

About

Anup Pandey is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Condensed Matter Physics. According to data from OpenAlex, Anup Pandey has authored 11 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Materials Chemistry, 3 papers in Electrical and Electronic Engineering and 2 papers in Condensed Matter Physics. Recurrent topics in Anup Pandey's work include Thin-Film Transistor Technologies (2 papers), Microstructure and mechanical properties (2 papers) and Machine Learning in Materials Science (2 papers). Anup Pandey is often cited by papers focused on Thin-Film Transistor Technologies (2 papers), Microstructure and mechanical properties (2 papers) and Machine Learning in Materials Science (2 papers). Anup Pandey collaborates with scholars based in United States, Switzerland and Bulgaria. Anup Pandey's co-authors include Reeju Pokharel, D. A. Drabold, Anibal J. Ramirez‐Cuesta, Luke L. Daemen, Yongqiang Cheng, Mykhaylo Ozerov, Craig M. Brown, Komalavalli Thirunavukkuarasu, Duncan H. Moseley and Jonathan Ludwig and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Carbon.

In The Last Decade

Anup Pandey

11 papers receiving 312 citations

Peers

Anup Pandey

MC

EOMM

ME

SPECT

MM

A. Shakin Russia

Yang Ze-Jin China

Ryo Fukaya Japan

Juliana Schell Switzerland

Akitoshi Koreeda Japan

Mickaël Beaudhuin France

Guan-Rong Huang Taiwan

M. A. Singh Canada

H. Mutka France

Christian Litterscheid Germany

A. Shakin Russia

Anup Pandey

119 ×0.5

MC

174 ×1.6

EOMM

22 ×0.4

ME

10 ×0.2

SPECT

9 ×0.3

MM

Citations per year, relative to Anup Pandey Anup Pandey (= 1×) peers A. Shakin

Countries citing papers authored by Anup Pandey

Since Specialization

Citations

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

Fields of papers citing papers by Anup Pandey

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anup Pandey

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

All Works

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11 of 11 papers shown

1.

Pandey, Anup, Jonathan Gigax, & Reeju Pokharel. (2022). Machine Learning Interatomic Potential for High-Throughput Screening of High-Entropy Alloys. JOM. 74(8). 2908–2920. 11 indexed citations

2.

Pokharel, Reeju, Anup Pandey, & Alexander Scheinker. (2021). Physics-Informed Data-Driven Surrogate Modeling for Full-Field 3D Microstructure and Micromechanical Field Evolution of Polycrystalline Materials. JOM. 73(11). 3371–3382. 14 indexed citations

3.

Borgschulte, Andreas, Emanuel Billeter, Luke L. Daemen, et al.. (2020). Inelastic neutron scattering evidence for anomalous H–H distances in metal hydrides. Proceedings of the National Academy of Sciences. 117(8). 4021–4026. 31 indexed citations

4.

Pandey, Anup & Reeju Pokharel. (2020). Machine learning based surrogate modeling approach for mapping crystal deformation in three dimensions. Scripta Materialia. 193. 1–5. 47 indexed citations

5.

Pandey, Anup, et al.. (2019). Theoretical Study of Alkali-Metal Hydrides at High Pressures: A Case of NaH Supported by Inelastic Neutron Scattering (INS) Experiments at 1 and 2 GPa. The Journal of Physical Chemistry A. 123(46). 10079–10085. 1 indexed citations

6.

Moseley, Duncan H., Komalavalli Thirunavukkuarasu, Mykhaylo Ozerov, et al.. (2018). Spin–phonon couplings in transition metal complexes with slow magnetic relaxation. Nature Communications. 9(1). 2572–2572. 110 indexed citations

7.

Pandey, Anup, Ada Sedova, Luke L. Daemen, Yongqiang Cheng, & Anibal J. Ramirez‐Cuesta. (2018). Exposing Key Vibrational Contributions to Properties of Organic Molecular Solids with High Signal, Low Frequency Neutron Spectroscopy and Ab Initio Simulations. Crystal Growth & Design. 18(9). 4815–4821. 5 indexed citations

8.

Pandey, Anup, et al.. (2018). Evolution of amorphous carbon across densities: An inferential study. Carbon. 131. 168–174. 57 indexed citations

9.

Pandey, Anup, et al.. (2016). Density functional theory model of amorphous zinc oxide (a-ZnO) and a-X0.375Z0.625O (X= Al, Ga and In). Journal of Non-Crystalline Solids. 455. 98–101. 11 indexed citations

10.

Pandey, Anup, et al.. (2016). Realistic inversion of diffraction data for an amorphous solid: The case of amorphous silicon. Physical review. B.. 94(23). 21 indexed citations

11.

Pandey, Anup, Bin Cai, Nikolas J. Podraza, & D. A. Drabold. (2014). Electrical Activity of Boron and Phosphorus in Hydrogenated Amorphous Silicon. Physical Review Applied. 2(5). 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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