Sergey A. Piletsky

23.3k total citations · 4 hit papers
344 papers, 18.8k citations indexed

About

Sergey A. Piletsky is a scholar working on Analytical Chemistry, Biomedical Engineering and Spectroscopy. According to data from OpenAlex, Sergey A. Piletsky has authored 344 papers receiving a total of 18.8k indexed citations (citations by other indexed papers that have themselves been cited), including 204 papers in Analytical Chemistry, 126 papers in Biomedical Engineering and 103 papers in Spectroscopy. Recurrent topics in Sergey A. Piletsky's work include Analytical chemistry methods development (199 papers), Analytical Chemistry and Chromatography (79 papers) and Analytical Chemistry and Sensors (62 papers). Sergey A. Piletsky is often cited by papers focused on Analytical chemistry methods development (199 papers), Analytical Chemistry and Chromatography (79 papers) and Analytical Chemistry and Sensors (62 papers). Sergey A. Piletsky collaborates with scholars based in United Kingdom, Ukraine and Italy. Sergey A. Piletsky's co-authors include Anthony Turner, Elena Piletska, António Guerreiro, Michael J. Whitcombe, Iva Chianella, Alessandro Poma, Alessandra Bossi, Nicholas W. Turner, Francesco Canfarotta and Sreenath Subrahmanyam and has published in prestigious journals such as Chemical Society Reviews, Advanced Materials and Angewandte Chemie International Edition.

In The Last Decade

Sergey A. Piletsky

340 papers receiving 18.5k citations

Hit Papers

Analytical methods for de... 2008 2026 2014 2020 2008 2010 2018 2016 200 400 600

Author Peers

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

Author Last Decade Papers Cites
Sergey A. Piletsky 11.3k 7.0k 5.3k 3.9k 3.7k 344 18.8k
Klaus Mosbach 14.9k 1.3× 8.5k 1.2× 11.0k 2.1× 8.0k 2.1× 3.3k 0.9× 425 27.3k
Jinhua Li 8.7k 0.8× 4.1k 0.6× 4.7k 0.9× 3.6k 0.9× 2.6k 0.7× 171 15.9k
Karsten Haupt 8.3k 0.7× 5.2k 0.7× 4.0k 0.8× 2.7k 0.7× 1.7k 0.5× 194 13.3k
Anthony Turner 4.3k 0.4× 8.7k 1.2× 2.6k 0.5× 8.1k 2.1× 10.6k 2.9× 360 22.8k
Yu‐Qi Feng 6.2k 0.5× 4.0k 0.6× 7.4k 1.4× 8.8k 2.3× 1.6k 0.4× 687 22.4k
Xiaoyan Wang 5.2k 0.5× 4.1k 0.6× 3.3k 0.6× 3.8k 1.0× 2.9k 0.8× 388 15.8k
Xiwen He 4.4k 0.4× 3.5k 0.5× 3.0k 0.6× 3.9k 1.0× 2.2k 0.6× 327 12.6k
Börje Sellergren 9.5k 0.8× 4.3k 0.6× 6.8k 1.3× 1.7k 0.4× 956 0.3× 214 12.8k
Shouzhuo Yao 3.2k 0.3× 7.2k 1.0× 4.4k 0.8× 11.3k 2.9× 10.5k 2.8× 730 29.4k
Chunhui Deng 3.1k 0.3× 4.3k 0.6× 7.1k 1.4× 7.7k 2.0× 2.1k 0.6× 396 18.0k

Countries citing papers authored by Sergey A. Piletsky

Since Specialization
Citations

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

Fields of papers citing papers by Sergey A. Piletsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sergey A. Piletsky. 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 Sergey A. Piletsky. The network helps show where Sergey A. Piletsky may publish in the future.

Co-authorship network of co-authors of Sergey A. Piletsky

This figure shows the co-authorship network connecting the top 25 collaborators of Sergey A. Piletsky. A scholar is included among the top collaborators of Sergey A. Piletsky 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 Sergey A. Piletsky. Sergey A. Piletsky 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
2.
Muhammad, Turghun, António Guerreiro, Muhammad Imran, et al.. (2025). Solid phase synthesis of molecularly imprinted polymers for analytical and life science applications. TrAC Trends in Analytical Chemistry. 184. 118134–118134. 17 indexed citations
3.
Masi, Sabrina Di, Álvaro García‐Cruz, Giuseppe Mele, et al.. (2025). Adsorption Isotherm Analysis for Hybrid Molecularly Imprinted Polymeric Gold-Decorated Nanoparticles Suitable for Reliable Quantification of Gluconic Acid in Wine. Nanomaterials. 15(3). 211–211. 2 indexed citations
4.
Tertiş, Mihaela, Natalie Allcock, Maria Suciu, et al.. (2023). NanoMIPs-based electrochemical sensors for selective detection of amphetamine. Microchemical Journal. 191. 108821–108821. 19 indexed citations
6.
Cowen, Todd, Mihaela Tertiş, Kaseb D. Alanazi, et al.. (2023). Integration of smart nanomaterials for highly selective disposable sensors and their forensic applications in amphetamine determination. Electrochimica Acta. 446. 142009–142009. 10 indexed citations
8.
Bezděková, Jaroslava, et al.. (2023). Molecularly imprinted nanoparticles for pathogen visualisation. Nanoscale Advances. 5(9). 2602–2609. 9 indexed citations
9.
Lach, Patrycja, Álvaro García‐Cruz, Francesco Canfarotta, et al.. (2023). Electroactive molecularly imprinted polymer nanoparticles for selective glyphosate determination. Biosensors and Bioelectronics. 236. 115381–115381. 28 indexed citations
10.
Piletska, Elena, Dana L. Thompson, Rebecca M. Jones, et al.. (2022). Snapshot imprinting as a tool for surface mapping and identification of novel biomarkers of senescent cells. Nanoscale Advances. 4(24). 5304–5311. 5 indexed citations
11.
Piletsky, Stanislav, Álvaro García‐Cruz, Elena Piletska, et al.. (2022). Iodo Silanes as Superior Substrates for the Solid Phase Synthesis of Molecularly Imprinted Polymer Nanoparticles. Polymers. 14(8). 1595–1595. 11 indexed citations
12.
Piletsky, Stanislav, Hasan Yeşilkaya, Francesco Canfarotta, et al.. (2022). Assessing the In Vivo Biocompatibility of Molecularly Imprinted Polymer Nanoparticles. Polymers. 14(21). 4582–4582. 17 indexed citations
13.
Piletsky, Stanislav, Elena Piletska, Marta Poblocka, et al.. (2021). Snapshot imprinting: rapid identification of cancer cell surface proteins and epitopes using molecularly imprinted polymers. Nano Today. 41. 101304–101304. 37 indexed citations
14.
Singh, Rajinder, Frederick W. Muskett, Alessandro Rufini, et al.. (2021). Mass spectrometric detection of KRAS protein mutations using molecular imprinting. Nanoscale. 13(48). 20401–20411. 11 indexed citations
15.
Canfarotta, Francesco, Elisabetta Mazzotta, Cosimino Malitesta, et al.. (2019). NanoMIP-based approach for the suppression of interference signals in electrochemical sensors. The Analyst. 144(24). 7290–7295. 11 indexed citations
16.
Farghali, Ahmed A., et al.. (2019). Strategies for Molecular Imprinting and the Evolution of MIP Nanoparticles as Plastic Antibodies—Synthesis and Applications. International Journal of Molecular Sciences. 20(24). 6304–6304. 144 indexed citations
17.
Smolińska-Kempisty, Katarzyna, Álvaro García‐Cruz, Francesco Canfarotta, et al.. (2018). Molecularly imprinted polymer nanoparticle-based assay (MINA): application for fumonisin B1 determination. The Analyst. 143(14). 3481–3488. 38 indexed citations
18.
Piletska, Elena, Joanna Czulak, Stanislav Piletsky, et al.. (2018). Novel assay format for proteins based on magnetic molecularly imprinted polymer nanoparticles—detection of pepsin. 6(4). 341–351. 6 indexed citations
19.
Tang, Siping, Francesco Canfarotta, Katarzyna Smolińska-Kempisty, et al.. (2017). A pseudo-ELISA based on molecularly imprinted nanoparticles for detection of gentamicin in real samples. Analytical Methods. 9(19). 2853–2858. 35 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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