José E. Tábora

25 papers receiving 824 citations

Peers

José E. Tábora
Comparison fields: 5 of 78
  • Catalysis 195
  • Inorganic Chemistry 254
  • Materials Chemistry 499
  • Filtration and Separation 18
  • Computational Theory and Mathematics 90
Replace Shailendra Bordawekar with:
Shailendra Bordawekar United States
Geoffrey R. Akien United Kingdom
Marcel Liauw Germany
Zoltán Király Hungary
Chao Qian China
Esther Heid Austria
Théophile Gaudin France
James L. McDonagh United Kingdom
Olga Klimchuk France
José E. Tábora relative to Shailendra Bordawekar United States Shailendra Bordawekar's profile →
Citations per field
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Shailendra Bordawekar · 1×
Citations per year

Countries citing papers authored by José E. Tábora

Since Specialization
Citations

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

Fields of papers citing papers by José E. Tábora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José E. Tábora. 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 José E. Tábora. The network helps show where José E. Tábora may publish in the future.

Co-authorship network

The 25 scholars most cited alongside José E. Tábora, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with José E. Tábora Line = papers co-authored together José E. Tábora links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20243
2 202441
3 20243
4 2022128
5 202026
6 20193
7 201916
8 20174
9 201218
10 20118
11 201029
12 200772
13 200712
14 200620
15 20052
16 199657
17 199672
18 199554
19 1994139
20 199346

About José E. Tábora

José E. Tábora is a scholar working on Filtration and Separation, Statistics, Probability and Uncertainty, Computational Theory and Mathematics, Materials Chemistry and Inorganic Chemistry, having authored 25 papers that have together received 861 indexed citations. Recurring topics across this work include Crystallization and Solubility Studies (9 papers), Computational Drug Discovery Methods (6 papers), Innovative Microfluidic and Catalytic Techniques Innovation (5 papers), Zeolite Catalysis and Synthesis (5 papers), Analytical Chemistry and Chromatography (4 papers), Process Optimization and Integration (4 papers), Machine Learning in Materials Science (3 papers) and Catalytic Processes in Materials Science (3 papers). The work is most often cited by research in Catalysis (195 citations), Inorganic Chemistry (254 citations), Materials Chemistry (499 citations), Filtration and Separation (18 citations) and Computational Theory and Mathematics (90 citations). José E. Tábora has collaborated with scholars based in United States, France and Germany. Frequent co-authors include Robert J. Davis, Zhongfan Liu, Jun Li, Abigail G. Doyle, Jason M. Stevens, Hsien‐Hsin Tung, Alina Borovika, Ryan P. Adams, José Antonio Garrido Torres and Chau‐Chyun Chen. Their work appears in journals such as Organic Process Research & Development, Journal of Pharmaceutical Sciences, Journal of the American Chemical Society, Journal of Catalysis and Journal of Pharmaceutical Innovation.

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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2026