Pankaj Aggarwal

794 total citations
53 papers, 647 citations indexed

About

Pankaj Aggarwal is a scholar working on Spectroscopy, Polymers and Plastics and Biomedical Engineering. According to data from OpenAlex, Pankaj Aggarwal has authored 53 papers receiving a total of 647 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Spectroscopy, 16 papers in Polymers and Plastics and 14 papers in Biomedical Engineering. Recurrent topics in Pankaj Aggarwal's work include Analytical Chemistry and Chromatography (16 papers), Natural Fiber Reinforced Composites (15 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (12 papers). Pankaj Aggarwal is often cited by papers focused on Analytical Chemistry and Chromatography (16 papers), Natural Fiber Reinforced Composites (15 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (12 papers). Pankaj Aggarwal collaborates with scholars based in India, United States and New Zealand. Pankaj Aggarwal's co-authors include Shakti Chauhan, Milton L. Lee, H. Dennis Tolley, Ajay Karmarkar, John Lawson, Kun Liu, Varinder S. Kanwar, Naveen Kwatra, Krishna K. Pandey and Kun Liu and has published in prestigious journals such as Analytical Chemistry, Journal of Chromatography A and Pharmaceutical Research.

In The Last Decade

Pankaj Aggarwal

49 papers receiving 613 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 Aggarwal India 17 251 243 188 121 113 53 647
Jin Sun China 13 226 0.9× 243 1.0× 38 0.2× 137 1.1× 57 0.5× 44 586
Kirstin Casdorff Switzerland 8 141 0.6× 134 0.6× 21 0.1× 192 1.6× 112 1.0× 9 429
Chunxiang Ding China 13 134 0.5× 167 0.7× 52 0.3× 128 1.1× 158 1.4× 20 650
Tsunehisa Miki Japan 14 251 1.0× 205 0.8× 22 0.1× 221 1.8× 313 2.8× 77 586
Sándor Keszei Hungary 11 493 2.0× 83 0.3× 86 0.5× 129 1.1× 23 0.2× 16 634
Muhammad Awais Pakistan 11 66 0.3× 161 0.7× 25 0.1× 130 1.1× 99 0.9× 46 492
Ian H Parker Bulgaria 12 97 0.4× 240 1.0× 35 0.2× 315 2.6× 68 0.6× 43 591
Chenglong Lv China 11 130 0.5× 72 0.3× 28 0.1× 52 0.4× 153 1.4× 29 439
Qian Ren China 14 63 0.3× 216 0.9× 31 0.2× 153 1.3× 24 0.2× 27 651
Jichun Zhou China 11 127 0.5× 114 0.5× 13 0.1× 149 1.2× 129 1.1× 16 362

Countries citing papers authored by Pankaj Aggarwal

Since Specialization
Citations

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

Fields of papers citing papers by Pankaj Aggarwal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pankaj Aggarwal

This figure shows the co-authorship network connecting the top 25 collaborators of Pankaj Aggarwal. A scholar is included among the top collaborators of Pankaj Aggarwal 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 Aggarwal. Pankaj Aggarwal 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.
Fine, Jonathan, et al.. (2025). Dedenser: A Python Package for Clustering and Downsampling Chemical Libraries. Journal of Chemical Information and Modeling. 65(3). 1053–1060.
2.
Wang, Jun, Jonathan Fine, Erik L. Regalado, et al.. (2025). Purification of Pharmaceuticals via Retention Time Prediction: Leveraging Graph Isomorphism Networks, Limited Data, and Transfer Learning. Journal of Separation Science. 48(6). e70178–e70178. 1 indexed citations
3.
4.
Wang, Heather, Rodell C. Barrientos, Michelle Wong, et al.. (2024). Improved assay development of pharmaceutical modalities using feedback-controlled liquid chromatography optimization. Journal of Chromatography A. 1722. 464830–464830. 4 indexed citations
5.
Hu, Mengwei, Andrew P. J. Brunskill, Yong Liu, et al.. (2024). Islatravir Dimer: Crystal Form Dependence of a Radiation-Induced Degradation Product. Molecular Pharmaceutics. 21(2). 729–734. 1 indexed citations
6.
Fine, Jonathan, et al.. (2024). Machine learning models and performance dependency on 2D chemical descriptor space for retention time prediction of pharmaceuticals. Journal of Chromatography A. 1730. 465109–465109. 6 indexed citations
7.
Barrientos, Rodell C., Mayank Bhavsar, Heather Wang, et al.. (2024). Digitally Enabled Generic Analytical Framework Accelerating the Pace of Liquid Chromatography Method Development for Vaccine Adjuvant Formulations. ACS Pharmacology & Translational Science. 7(10). 3108–3118. 1 indexed citations
8.
Wang, Jun, Rose Yen, Pankaj Aggarwal, et al.. (2024). Predictions of Chromatography Methods by Chemical Structure Similarity to Accelerate High-Throughput Medicinal Chemistry. ACS Medicinal Chemistry Letters. 15(8). 1396–1401. 1 indexed citations
9.
10.
Hicks, Michael B., et al.. (2023). Portable capillary LC for in‐line UV monitoring and MS detection: Comparable sensitivity and much lower solvent consumption. Journal of Separation Science. 46(21). e2300300–e2300300.
11.
Aggarwal, Pankaj, et al.. (2017). Mechanical and thermal properties of wood fibers reinforced poly(lactic acid)/thermoplasticized starch composites. Journal of Applied Polymer Science. 135(15). 23 indexed citations
12.
Gama, Mariana R., Pankaj Aggarwal, Milton L. Lee, & Carla Beatriz Grespan Bottoli. (2017). Controlled crosslinking of trimethylolpropane trimethacrylate for preparation of organic monolithic columns for capillary liquid chromatography. Electrophoresis. 38(22-23). 3029–3035. 3 indexed citations
13.
Gama, Mariana R., Pankaj Aggarwal, Kun Liu, Milton L. Lee, & Carla Beatriz Grespan Bottoli. (2016). Improvement in Liquid Chromatographic Performance of Organic Polymer Monolithic Capillary Columns with Controlled Free-Radical Polymerization. Journal of Chromatographic Science. 55(4). 398–404. 4 indexed citations
14.
Aggarwal, Pankaj, et al.. (2016). Effect of grafting yield and molecular weight of m‐TMI‐grafted‐PP on the mechanical properties of wood fiber filled polypropylene composites. Journal of Applied Polymer Science. 133(46). 5 indexed citations
15.
Aggarwal, Pankaj, John Lawson, H. Dennis Tolley, et al.. (2014). Correlation of chromatographic performance with morphological features of organic polymer monoliths. Journal of Chromatography A. 1334. 20–29. 21 indexed citations
16.
Aggarwal, Pankaj, et al.. (2012). Jute–polypropylene composites using m-TMI-grafted-polypropylene as a coupling agent. Materials & Design (1980-2015). 43. 112–117. 54 indexed citations
17.
Li, Yuanyuan, Pankaj Aggarwal, H. Dennis Tolley, & Milton L. Lee. (2012). Organic Monolith Column Technology for Capillary Liquid Chromatography. PubMed. 50. 237–280. 2 indexed citations
18.
Aggarwal, Pankaj, H. Dennis Tolley, & Milton L. Lee. (2011). Monolithic bed structure for capillary liquid chromatography. Journal of Chromatography A. 1219. 1–14. 71 indexed citations
19.
Aggarwal, Pankaj, Shakti Chauhan, & Ajay Karmarkar. (2006). Growth Strains inAcacia AuriculaeformisTrees of Different Age: Their Relationship with Growth Rate and Height. 17(4). 212–215. 1 indexed citations
20.
Aggarwal, Pankaj, et al.. (2003). Water repellent treatments for catamaran grade Bombax ceiba Linn. (Spermatophyta/Dicotyledoneae) wood. Indian Journal of Marine Sciences. 32(4). 340–343. 1 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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