Samrendra Singh

773 total citations
27 papers, 576 citations indexed

About

Samrendra Singh is a scholar working on Materials Chemistry, Mechanical Engineering and Plant Science. According to data from OpenAlex, Samrendra Singh has authored 27 papers receiving a total of 576 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Materials Chemistry, 6 papers in Mechanical Engineering and 6 papers in Plant Science. Recurrent topics in Samrendra Singh's work include Spectroscopy and Chemometric Analyses (5 papers), Hydrogels: synthesis, properties, applications (5 papers) and Graphene research and applications (4 papers). Samrendra Singh is often cited by papers focused on Spectroscopy and Chemometric Analyses (5 papers), Hydrogels: synthesis, properties, applications (5 papers) and Graphene research and applications (4 papers). Samrendra Singh collaborates with scholars based in United States, China and India. Samrendra Singh's co-authors include Sanket A. Deshmukh, Karteek K. Bejagam, Yaxin An, Sriram K. Vidyarthi, Hong‐Wei Xiao, Fangxi Wang, Soumil Y. Joshi, Maria J. Ferrua, Ferruh Erdoğdu and Rewa Rai and has published in prestigious journals such as The Journal of Physical Chemistry B, Macromolecules and Carbon.

In The Last Decade

Samrendra Singh

25 papers receiving 564 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Samrendra Singh United States 17 203 109 99 94 90 27 576
Boyan Li China 15 209 1.0× 65 0.6× 85 0.9× 130 1.4× 22 0.2× 63 661
Yangli Wang China 13 97 0.5× 40 0.4× 85 0.9× 91 1.0× 131 1.5× 43 751
Kaiqiang Zhang United Kingdom 15 360 1.8× 103 0.9× 91 0.9× 176 1.9× 34 0.4× 37 993
Prince Bawuah United Kingdom 18 104 0.5× 47 0.4× 75 0.8× 340 3.6× 39 0.4× 42 904
Hirohmi Watanabe Japan 19 296 1.5× 136 1.2× 43 0.4× 271 2.9× 219 2.4× 56 1.2k
Yun Wang China 14 95 0.5× 252 2.3× 97 1.0× 145 1.5× 79 0.9× 104 886
Keke Song China 15 448 2.2× 70 0.6× 30 0.3× 101 1.1× 18 0.2× 50 786
Pankaj Doshi United States 22 206 1.0× 240 2.2× 157 1.6× 251 2.7× 32 0.4× 60 1.2k
Ondřej Kašpar Czechia 15 76 0.4× 64 0.6× 110 1.1× 224 2.4× 49 0.5× 27 588

Countries citing papers authored by Samrendra Singh

Since Specialization
Citations

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

Fields of papers citing papers by Samrendra Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samrendra Singh

This figure shows the co-authorship network connecting the top 25 collaborators of Samrendra Singh. A scholar is included among the top collaborators of Samrendra Singh 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 Samrendra Singh. Samrendra Singh 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.
2.
Singh, Samrendra, Soumil Y. Joshi, Emily M. Webb, et al.. (2023). Data Driven Computational Design and Experimental Validation of Drugs for Accelerated Mitigation of Pandemic-like Scenarios. The Journal of Physical Chemistry Letters. 14(42). 9490–9499. 2 indexed citations
3.
Singh, Samrendra, et al.. (2023). Data Driven Discovery of MOFs for Hydrogen Gas Adsorption. Journal of Chemical Theory and Computation. 19(19). 6686–6703. 21 indexed citations
4.
Wang, Fangxi, et al.. (2022). Dual-Force Zone Nonequilibrium Molecular Dynamics Simulations on Nanoporous Metal–Organic Framework Membranes for Separation of H2/CH4 Mixtures. ACS Applied Nano Materials. 5(3). 4048–4061. 14 indexed citations
5.
Joshi, Soumil Y., Samrendra Singh, & Sanket A. Deshmukh. (2022). Coarse-grained molecular dynamics integrated with convolutional neural network for comparing shapes of temperature sensitive bottlebrushes. npj Computational Materials. 8(1). 16 indexed citations
6.
Vidyarthi, Sriram K., et al.. (2021). Deep learnt grading of almond kernels. Journal of Food Process Engineering. 44(4). 7 indexed citations
7.
Singh, Samrendra, et al.. (2021). Lhermitte–Duclos Disease: Case Report and Literature Review. International Journal of Head and Neck Surgery. 12(2). 65–70.
8.
Bejagam, Karteek K., et al.. (2020). Solvation dynamics ofN-substituted acrylamide polymers and the importance for phase transition behavior. Soft Matter. 16(6). 1582–1593. 26 indexed citations
9.
Vidyarthi, Sriram K., et al.. (2020). Classification of first quality fancy cashew kernels using four deep convolutional neural network models. Journal of Food Process Engineering. 43(12). 19 indexed citations
10.
Vidyarthi, Sriram K., et al.. (2020). Prediction of size and mass of pistachio kernels using random Forest machine learning. Journal of Food Process Engineering. 43(9). 28 indexed citations
11.
Singh, Samrendra, et al.. (2020). Designing Next Generation Exhaust Aftertreatment Systems Using Machine Learning. SAE International journal of commercial vehicles. 13(3). 215–220. 1 indexed citations
12.
Vidyarthi, Sriram K., Hamed M. El‐Mashad, Ragab Khir, et al.. (2019). A mathematical model of heat transfer during tomato peeling using selected electric infrared emitters. Biosystems Engineering. 186. 106–117. 16 indexed citations
13.
Singh, Samrendra, Karteek K. Bejagam, Yaxin An, & Sanket A. Deshmukh. (2019). Machine-Learning Based Stacked Ensemble Model for Accurate Analysis of Molecular Dynamics Simulations. The Journal of Physical Chemistry A. 123(24). 5190–5198. 30 indexed citations
14.
Bejagam, Karteek K., et al.. (2019). Development of non-bonded interaction parameters between hexagonal boron-nitride and water. Computational Materials Science. 161. 339–345. 10 indexed citations
15.
Bejagam, Karteek K., et al.. (2019). Unraveling the Conformations of Backbone and Side Chains in Thermosensitive Bottlebrush Polymers. Macromolecules. 52(23). 9398–9408. 34 indexed citations
16.
Singh, Samrendra, et al.. (2018). 3D investigation into the thermal behavior of the wet multi-disk axle brake of an off-highway machinery. Applied Thermal Engineering. 136. 576–588. 14 indexed citations
17.
Bejagam, Karteek K., Samrendra Singh, Yaxin An, & Sanket A. Deshmukh. (2018). Machine-Learned Coarse-Grained Models. The Journal of Physical Chemistry Letters. 9(16). 4667–4672. 50 indexed citations
18.
Bejagam, Karteek K., Yaxin An, Samrendra Singh, & Sanket A. Deshmukh. (2018). Machine-Learning Enabled New Insights into the Coil-to-Globule Transition of Thermosensitive Polymers Using a Coarse-Grained Model. The Journal of Physical Chemistry Letters. 9(22). 6480–6488. 41 indexed citations
19.
Bejagam, Karteek K., Samrendra Singh, & Sanket A. Deshmukh. (2017). Development of non‐bonded interaction parameters between graphene and water using particle swarm optimization. Journal of Computational Chemistry. 39(12). 721–734. 22 indexed citations
20.
Erdoğdu, Ferruh, et al.. (2006). Air-impingement cooling of boiled eggs: Analysis of flow visualization and heat transfer. Journal of Food Engineering. 79(3). 920–928. 24 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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