Pankaj Rajak

1.2k total citations
42 papers, 967 citations indexed

About

Pankaj Rajak is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Pankaj Rajak has authored 42 papers receiving a total of 967 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Materials Chemistry, 11 papers in Electrical and Electronic Engineering and 7 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Pankaj Rajak's work include Machine Learning in Materials Science (19 papers), 2D Materials and Applications (12 papers) and MXene and MAX Phase Materials (7 papers). Pankaj Rajak is often cited by papers focused on Machine Learning in Materials Science (19 papers), 2D Materials and Applications (12 papers) and MXene and MAX Phase Materials (7 papers). Pankaj Rajak collaborates with scholars based in United States, Japan and Thailand. Pankaj Rajak's co-authors include Aiichiro Nakano, Priya Vashishta, Rajiv K. Kalia, Aravind Krishnamoorthy, Fuyuki Shimojo, Ken‐ichi Nomura, Sungwook Hong, Subodh Tiwari, David J. Singh and Lindsay Bassman Oftelie and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and Nano Letters.

In The Last Decade

Pankaj Rajak

40 papers receiving 949 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pankaj Rajak United States 19 689 248 215 110 93 42 967
Christian J. Long United States 18 724 1.1× 349 1.4× 351 1.6× 162 1.5× 132 1.4× 66 1.2k
Kyu‐Hwan Lee South Korea 14 431 0.6× 294 1.2× 65 0.3× 114 1.0× 46 0.5× 63 856
Lance J. Nelson United States 7 1.0k 1.5× 254 1.0× 121 0.6× 133 1.2× 187 2.0× 8 1.3k
Giuseppe Fisicaro Italy 20 479 0.7× 645 2.6× 146 0.7× 254 2.3× 77 0.8× 61 1.1k
Pier Luca Palla France 16 1.2k 1.7× 231 0.9× 239 1.1× 329 3.0× 90 1.0× 33 1.6k
Kazume Nishidate Japan 16 662 1.0× 394 1.6× 84 0.4× 209 1.9× 53 0.6× 51 933
Xinxin Li United States 14 228 0.3× 355 1.4× 145 0.7× 147 1.3× 52 0.6× 52 704
Haoyang Zhang China 14 578 0.8× 289 1.2× 178 0.8× 80 0.7× 59 0.6× 29 991
Tianran Chen United States 15 568 0.8× 494 2.0× 79 0.4× 225 2.0× 84 0.9× 43 990
Haikuan Dong China 20 1.1k 1.5× 326 1.3× 69 0.3× 382 3.5× 87 0.9× 68 1.5k

Countries citing papers authored by Pankaj Rajak

Since Specialization
Citations

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

Fields of papers citing papers by Pankaj Rajak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pankaj Rajak

This figure shows the co-authorship network connecting the top 25 collaborators of Pankaj Rajak. A scholar is included among the top collaborators of Pankaj Rajak 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 Pankaj Rajak. Pankaj Rajak 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.
Rajak, Pankaj, Shogo Fukushima, Rajiv K. Kalia, et al.. (2023). High-throughput computation and machine learning of refractive index of polymers. Applied Physics Letters. 123(12). 4 indexed citations
2.
Nomura, Ken‐ichi, Rajiv K. Kalia, Aravind Krishnamoorthy, et al.. (2022). Exploring far-from-equilibrium ultrafast polarization control in ferroelectric oxides with excited-state neural network quantum molecular dynamics. Science Advances. 8(12). eabk2625–eabk2625. 17 indexed citations
3.
Deshmukh, Ajinkya A., Chao Wu, Omer Yassin, et al.. (2022). Flexible polyolefin dielectric by strategic design of organic modules for harsh condition electrification. Energy & Environmental Science. 15(3). 1307–1314. 133 indexed citations
4.
Rajak, Pankaj, Ken‐ichi Nomura, Aravind Krishnamoorthy, et al.. (2021). Neural Network Quantum Molecular Dynamics, Intermediate Range Order in GeSe2, and Neutron Scattering Experiments. The Journal of Physical Chemistry Letters. 12(25). 6020–6028. 5 indexed citations
5.
Rajak, Pankaj, Beibei Wang, Ken‐ichi Nomura, et al.. (2021). Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials. npj Computational Materials. 7(1). 25 indexed citations
6.
Rajak, Pankaj, Aiichiro Nakano, Priya Vashishta, & Rajiv K. Kalia. (2021). Mechanical behavior of ultralight nickel metamaterial. Applied Physics Letters. 118(8). 2 indexed citations
7.
Rajak, Pankaj, et al.. (2021). Autonomous reinforcement learning agent for chemical vapor deposition synthesis of quantum materials. npj Computational Materials. 7(1). 30 indexed citations
8.
Yang, Liqiu, Rajiv K. Kalia, Ken‐ichi Nomura, et al.. (2021). Dielectric Polymer Property Prediction Using Recurrent Neural Networks with Optimizations. Journal of Chemical Information and Modeling. 61(5). 2175–2186. 38 indexed citations
9.
Hong, Sungwook, Ken‐ichi Nomura, Aravind Krishnamoorthy, et al.. (2019). Defect Healing in Layered Materials: A Machine Learning-Assisted Characterization of MoS2 Crystal Phases. The Journal of Physical Chemistry Letters. 10(11). 2739–2744. 23 indexed citations
10.
Krishnamoorthy, Aravind, Pankaj Rajak, Aiichiro Nakano, Rajiv K. Kalia, & Priya Vashishta. (2019). Machine learning of reaction pathways in chemical vapor deposition of MoS 2 monolayers. Bulletin of the American Physical Society. 2019. 1 indexed citations
11.
Shimojo, Fuyuki, Shogo Fukushima, Hiroyuki Kumazoe, et al.. (2019). QXMD: An open-source program for nonadiabatic quantum molecular dynamics. SoftwareX. 10. 100307–100307. 41 indexed citations
12.
Rajak, Pankaj, Rajiv K. Kalia, Aiichiro Nakano, & Priya Vashishta. (2018). Faceting, Grain Growth, and Crack Healing in Alumina. ACS Nano. 12(9). 9005–9010. 12 indexed citations
13.
Hong, Sungwook, Chunyang Sheng, Aravind Krishnamoorthy, et al.. (2018). Chemical Vapor Deposition Synthesis of MoS2 Layers from the Direct Sulfidation of MoO3 Surfaces Using Reactive Molecular Dynamics Simulations. The Journal of Physical Chemistry C. 122(13). 7494–7503. 44 indexed citations
14.
Apte, Amey, Vidya Kochat, Pankaj Rajak, et al.. (2018). Structural Phase Transformation in Strained Monolayer MoWSe2 Alloy. ACS Nano. 12(4). 3468–3476. 60 indexed citations
15.
Rajak, Pankaj, Aravind Krishnamoorthy, Rajiv K. Kalia, Aiichiro Nakano, & Priya Vashishta. (2018). Structural Phase Transformation in Strained Monolayer MoWSe 2 Alloy. APS. 2018. 1 indexed citations
16.
Krishnamoorthy, Aravind, Pankaj Rajak, Subodh Tiwari, et al.. (2018). Free energy of hydration and heat capacity of calcium dipicolinate in Bacillus spore cores. Applied Physics Letters. 113(11). 1 indexed citations
17.
Oftelie, Lindsay Bassman, Pankaj Rajak, Rajiv K. Kalia, et al.. (2018). Efficient Discovery of Optimal N-Layered TMDC Hetero-Structures. MRS Advances. 3(6-7). 397–402. 6 indexed citations
18.
Rajak, Pankaj, Subodh Tiwari, Aravind Krishnamoorthy, et al.. (2017). Gel phase in hydrated calcium dipicolinate. Applied Physics Letters. 111(21). 4 indexed citations
19.
Shimojo, Fuyuki, Shinnosuke Hattori, Rajiv K. Kalia, et al.. (2014). A divide-conquer-recombine algorithmic paradigm for large spatiotemporal quantum molecular dynamics simulations. The Journal of Chemical Physics. 140(18). 18A529–18A529. 52 indexed citations
20.
Rajak, Pankaj, et al.. (2011). Phases in Zn-coated Fe analyzed through an evolutionary meta-model and multi-objective Genetic Algorithms. Computational Materials Science. 50(8). 2502–2516. 29 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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