Razi Epsztein

4.6k total citations · 1 hit paper
48 papers, 3.5k citations indexed

About

Razi Epsztein is a scholar working on Biomedical Engineering, Water Science and Technology and Electrical and Electronic Engineering. According to data from OpenAlex, Razi Epsztein has authored 48 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Biomedical Engineering, 37 papers in Water Science and Technology and 13 papers in Electrical and Electronic Engineering. Recurrent topics in Razi Epsztein's work include Membrane Separation Technologies (37 papers), Membrane-based Ion Separation Techniques (36 papers) and Nanopore and Nanochannel Transport Studies (17 papers). Razi Epsztein is often cited by papers focused on Membrane Separation Technologies (37 papers), Membrane-based Ion Separation Techniques (36 papers) and Nanopore and Nanochannel Transport Studies (17 papers). Razi Epsztein collaborates with scholars based in Israel, United States and China. Razi Epsztein's co-authors include Menachem Elimelech, Cody L. Ritt, Ryan M. DuChanois, Mohan Qin, Evyatar Shaulsky, Aleksandr Noy, Nadir Dızge, Akshay Deshmukh, Sohum K. Patel and Zhangxin Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and ACS Nano.

In The Last Decade

Razi Epsztein

46 papers receiving 3.5k citations

Hit Papers

Towards single-species selectivity of membranes with subn... 2020 2026 2022 2024 2020 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Razi Epsztein Israel 26 2.4k 2.3k 1.2k 593 458 48 3.5k
Weihua Qing China 25 1.2k 0.5× 1.4k 0.6× 762 0.6× 810 1.4× 379 0.8× 38 2.7k
Ryan M. DuChanois United States 16 1.4k 0.6× 1.4k 0.6× 724 0.6× 535 0.9× 352 0.8× 19 2.2k
Cody L. Ritt United States 16 1.6k 0.7× 1.7k 0.7× 735 0.6× 543 0.9× 672 1.5× 24 2.5k
Su Liu China 28 883 0.4× 641 0.3× 735 0.6× 284 0.5× 1.4k 3.0× 126 2.6k
Junjun Ma China 26 949 0.4× 1.4k 0.6× 750 0.6× 161 0.3× 562 1.2× 65 2.3k
Xuechen Zhou United States 20 817 0.3× 1.1k 0.5× 575 0.5× 155 0.3× 528 1.2× 29 2.0k
Dariush Bastani Iran 24 738 0.3× 914 0.4× 463 0.4× 650 1.1× 524 1.1× 63 2.1k
Antonio Comite Italy 26 716 0.3× 669 0.3× 393 0.3× 491 0.8× 580 1.3× 78 2.0k
Junsheng Yuan China 29 1.4k 0.6× 1.0k 0.5× 1.4k 1.1× 1.4k 2.4× 437 1.0× 127 3.1k
Xin Yan China 32 749 0.3× 1.1k 0.5× 1.2k 1.0× 274 0.5× 1.4k 3.0× 102 3.6k

Countries citing papers authored by Razi Epsztein

Since Specialization
Citations

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

Fields of papers citing papers by Razi Epsztein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Razi Epsztein

This figure shows the co-authorship network connecting the top 25 collaborators of Razi Epsztein. A scholar is included among the top collaborators of Razi Epsztein 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 Razi Epsztein. Razi Epsztein 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.
Gupta, Nishesh Kumar & Razi Epsztein. (2025). Upcycling Battery Waste into Photocatalysts for Sustainable Energy and Environmental Applications. ACS Sustainable Resource Management. 2(12). 2373–2396.
2.
Birnhack, Liat, et al.. (2025). Partition energy in polyamide membranes and its link to ion-ion selectivity. SHILAP Revista de lepidopterología. 5(1). 100099–100099. 1 indexed citations
4.
Xu, Hengyu, et al.. (2025). Role of Ion Dehydration in Ion–Ion Selectivity of Dense Membranes. Environmental Science & Technology. 59(34). 17997–18009. 1 indexed citations
5.
Kong, Wei, et al.. (2025). Direct Quantification of Ion Partitioning and Diffusion Resistances in Reverse Osmosis Membranes via Electrochemical Impedance Spectroscopy. Environmental Science & Technology. 59(22). 11353–11364. 1 indexed citations
6.
Birnhack, Liat, et al.. (2024). The importance of ionic hydration in the transport of monovalent anions through nanofiltration membranes. Journal of Membrane Science. 716. 123513–123513. 5 indexed citations
7.
Meng, Sheng, Yun Guo, Boreum Lee, et al.. (2024). Electrified desalination processes: Where we are and where to go from performance and economic perspectives. Desalination. 600. 118486–118486. 5 indexed citations
8.
Birnhack, Liat, et al.. (2024). Reliable methods to determine experimental energy barriers for transport in salt-rejecting membranes. SHILAP Revista de lepidopterología. 5(1). 100090–100090. 5 indexed citations
9.
Birnhack, Liat, et al.. (2024). Effect of solution ions on the charge and performance of nanofiltration membranes. npj Clean Water. 7(1). 32 indexed citations
10.
Liu, Kairui, Razi Epsztein, Shihong Lin, Jiuhui Qu, & Meng Sun. (2024). Ion–Ion Selectivity of Synthetic Membranes with Confined Nanostructures. ACS Nano. 18(33). 21633–21650. 37 indexed citations
11.
Jeong, Nohyeong, et al.. (2023). Exploring the Knowledge Attained by Machine Learning on Ion Transport across Polyamide Membranes Using Explainable Artificial Intelligence. Environmental Science & Technology. 57(46). 17851–17862. 31 indexed citations
12.
Shocron, Amit N., et al.. (2022). Comparison of Ion Selectivity in Electrodialysis and Capacitive Deionization. Environmental Science & Technology Letters. 9(11). 889–899. 46 indexed citations
13.
Blotevogel, Jens, et al.. (2022). Indications of ion dehydration in diffusion-only and pressure-driven nanofiltration. Journal of Membrane Science. 648. 120358–120358. 40 indexed citations
14.
Zhou, Xuechen, Mohammad Heiranian, Meiqi Yang, et al.. (2021). Selective Fluoride Transport in Subnanometer TiO2 Pores. ACS Nano. 15(10). 16828–16838. 25 indexed citations
15.
Nativ, Paz, et al.. (2021). Desalinated brackish water with improved mineral composition using monovalent-selective nanofiltration followed by reverse osmosis. Desalination. 520. 115364–115364. 38 indexed citations
16.
Epsztein, Razi, Ryan M. DuChanois, Cody L. Ritt, Aleksandr Noy, & Menachem Elimelech. (2020). Towards single-species selectivity of membranes with subnanometre pores. Nature Nanotechnology. 15(6). 426–436. 590 indexed citations breakdown →
17.
Lester, Yaal, Evyatar Shaulsky, Razi Epsztein, & Ines Zucker. (2019). Capacitive deionization for simultaneous removal of salt and uncharged organic contaminants from water. Separation and Purification Technology. 237. 116388–116388. 23 indexed citations
18.
Epsztein, Razi, Michael Beliavski, Sheldon Tarre, & Michal Green. (2017). Pressurized hydrogenotrophic denitrification reactor for small water systems. Journal of Environmental Management. 216. 315–319. 11 indexed citations
19.
Epsztein, Razi, Michael Beliavski, Sheldon Tarre, & Michal Green. (2016). Submerged bed versus unsaturated flow reactor: A pressurized hydrogenotrophic denitrification reactor as a case study. Chemosphere. 161. 151–156. 4 indexed citations
20.
Epsztein, Razi, Michael Beliavski, Sheldon Tarre, & Michal Green. (2015). High-rate hydrogenotrophic denitrification in a pressurized reactor. Chemical Engineering Journal. 286. 578–584. 25 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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