Nimir O. Elbashir

2.3k total citations
79 papers, 1.7k citations indexed

About

Nimir O. Elbashir is a scholar working on Catalysis, Materials Chemistry and Biomedical Engineering. According to data from OpenAlex, Nimir O. Elbashir has authored 79 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Catalysis, 35 papers in Materials Chemistry and 19 papers in Biomedical Engineering. Recurrent topics in Nimir O. Elbashir's work include Catalysts for Methane Reforming (37 papers), Catalytic Processes in Materials Science (32 papers) and Catalysis and Oxidation Reactions (25 papers). Nimir O. Elbashir is often cited by papers focused on Catalysts for Methane Reforming (37 papers), Catalytic Processes in Materials Science (32 papers) and Catalysis and Oxidation Reactions (25 papers). Nimir O. Elbashir collaborates with scholars based in Qatar, United States and Saudi Arabia. Nimir O. Elbashir's co-authors include Mahmoud M. El‐Halwagi, Christopher B. Roberts, Dragomir B. Bukur, Minhaj Ghouri, Buping Bao, Saeed M. Al‐Zahrani, Ahmed E. Abasaeed, Mohamed M. B. Noureldin, Branislav Todić and Anuj Prakash and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Hydrogen Energy.

In The Last Decade

Nimir O. Elbashir

74 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nimir O. Elbashir Qatar 24 1.1k 875 464 387 197 79 1.7k
M. Farsi Iran 24 779 0.7× 589 0.7× 376 0.8× 639 1.7× 199 1.0× 128 1.7k
A. Jahanmiri Iran 29 1.0k 0.9× 573 0.7× 628 1.4× 810 2.1× 413 2.1× 83 2.1k
Kim Aasberg‐Petersen Denmark 11 1.0k 1.0× 886 1.0× 344 0.7× 327 0.8× 59 0.3× 12 1.6k
Davood Iranshahi Iran 22 1.0k 1.0× 687 0.8× 523 1.1× 786 2.0× 315 1.6× 100 1.8k
Akbar Zamaniyan Iran 20 769 0.7× 797 0.9× 330 0.7× 291 0.8× 68 0.3× 58 1.3k
Ahmad Rafiee Iran 16 654 0.6× 621 0.7× 269 0.6× 482 1.2× 118 0.6× 34 1.8k
Mohammad Hasan Khademi Iran 21 533 0.5× 289 0.3× 371 0.8× 354 0.9× 146 0.7× 38 964
Magne Hillestad Norway 29 708 0.7× 579 0.7× 984 2.1× 1.5k 3.9× 300 1.5× 101 2.5k
Pablo Marín Spain 23 608 0.6× 709 0.8× 226 0.5× 427 1.1× 50 0.3× 63 1.2k
S.T. Kolaczkowski United Kingdom 24 654 0.6× 1.0k 1.1× 426 0.9× 428 1.1× 37 0.2× 47 1.8k

Countries citing papers authored by Nimir O. Elbashir

Since Specialization
Citations

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

Fields of papers citing papers by Nimir O. Elbashir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nimir O. Elbashir. 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 Nimir O. Elbashir. The network helps show where Nimir O. Elbashir may publish in the future.

Co-authorship network of co-authors of Nimir O. Elbashir

This figure shows the co-authorship network connecting the top 25 collaborators of Nimir O. Elbashir. A scholar is included among the top collaborators of Nimir O. Elbashir 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 Nimir O. Elbashir. Nimir O. Elbashir 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.
Elbashir, Nimir O., et al.. (2025). Comprehensive evaluation of cyclic steam stimulation for enhanced heavy oil recovery: assessing production and CO2 emissions. Journal of Petroleum Exploration and Production Technology. 15(10).
2.
Mahmoud, Nada, et al.. (2025). Decarbonizing ammonia synthesis plants through retrofitting novel reformer technology. Scientific Reports. 16(1). 661–661.
3.
Dhibi, Khaled, et al.. (2025). Advanced data-driven fault detection in gas-to-liquid plants. Computers & Chemical Engineering. 198. 109098–109098. 1 indexed citations
4.
Ashour, Ahmed, et al.. (2025). Modeling tri-reforming of methane for carbon dioxide utilization and hydrogen production. Energy. 335. 137977–137977.
5.
Choudhury, Hanif A., et al.. (2025). Retrofitting Low Carbon Aviation Fuels Processes From Natural Gas to Renewables Energy‐Based Systems. Greenhouse Gases Science and Technology. 15(5). 601–614. 2 indexed citations
6.
Zang, Guiyan, et al.. (2024). A novel framework for the economic and sustainability assessment of carbon capture and utilization technologies. Gas Science and Engineering. 131. 205462–205462. 4 indexed citations
7.
8.
Choudhury, Hanif A., et al.. (2024). Experimental Verification of Low-Pressure Kinetics Model for Direct Synthesis of Dimethyl Carbonate Over CeO2 Catalyst. Topics in Catalysis. 68(11-12). 1156–1170. 1 indexed citations
9.
Elbashir, Nimir O., et al.. (2024). Utilizing Green-Carbon Nanotubes to Improve Drilling Fluids Rheological Properties: An Experimental Study. SPE Annual Technical Conference and Exhibition. 2 indexed citations
10.
Choudhury, Hanif A., et al.. (2023). Bayesian optimization of multiscale kernel principal component analysis and its application to model Gas-to-liquid (GTL) process data. Energy. 284. 129221–129221. 8 indexed citations
11.
Choudhury, Hanif A., et al.. (2023). Multiscale Bayesian PCA for robust process modeling of a Fischer–Tropsch bench scale process. Chemometrics and Intelligent Laboratory Systems. 240. 104921–104921. 2 indexed citations
12.
Choudhury, Hanif A., et al.. (2023). Bayesian-optimized Neural Networks and their application to model gas-to-liquid plants. Gas Science and Engineering. 113. 204964–204964. 5 indexed citations
13.
Choudhury, Hanif A., et al.. (2021). A novel CO2 utilization technology for the synergistic co-production of multi-walled carbon nanotubes and syngas. Scientific Reports. 11(1). 1417–1417. 31 indexed citations
14.
15.
Minerick, Adrienne, Donald P. Visco, Susan Montgomery, et al.. (2020). Special Session: What Works to Retain Students in Chemical Engineering Programs. Papers on Engineering Education Repository (American Society for Engineering Education). 22.1315.1–22.1315.16. 1 indexed citations
16.
17.
Afzal, Shaik, Anuj Prakash, Patrick Littlewood, et al.. (2020). Controlling the rate of change of Ni dispersion in commercial catalyst by ALD overcoat during dry reforming of methane. International Journal of Hydrogen Energy. 45(23). 12835–12848. 18 indexed citations
18.
Ghouri, Minhaj, et al.. (2016). A combined thermo-kinetic analysis of various methane reforming technologies: Comparison with dry reforming. Journal of CO2 Utilization. 17. 99–111. 106 indexed citations
19.
Noureldin, Mohamed M. B., Nimir O. Elbashir, Kerron J. Gabriel, & Mahmoud M. El‐Halwagi. (2015). A Process Integration Approach to the Assessment of CO2 Fixation through Dry Reforming. ACS Sustainable Chemistry & Engineering. 3(4). 625–636. 58 indexed citations
20.
Elbashir, Nimir O. & Christopher B. Roberts. (2005). Enhanced Incorporation of α-Olefins in the Fischer−Tropsch Synthesis Chain-Growth Process over an Alumina-Supported Cobalt Catalyst in Near-Critical and Supercritical Hexane Media. Industrial & Engineering Chemistry Research. 44(3). 505–521. 41 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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