Mohammad A. Halim

122 papers receiving 3.1k citations

Hit Papers

A molecular modeling approach to identify effective antiviral phytochemicals against the main protease of SARS-CoV-2 2020 · 269 citations
2690+2+4Years since publication50100150200250

Peers

Mohammad A. Halim
Comparison fields: 5 of 163
  • Filtration and Separation 259
  • Catalysis 256
  • Organic Chemistry 886
  • Fluid Flow and Transfer Processes 178
  • Computational Theory and Mathematics 429
Replace Prashant Singh with:
Prashant Singh India
Peng Wu China
Alex Avdeef United States
R.A. Ford United States
Neil R. Foster Australia
Pengfei Li China
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Gordon L. Flynn United States
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Citations per field
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Citations per year

Countries citing papers authored by Mohammad A. Halim

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad A. Halim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mohammad A. Halim, 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 Mohammad A. Halim Line = papers co-authored together Mohammad A. Halim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A molecular modeling approach to identify effective antiviral phytochemicals against the main protease of SARS-CoV-2
Hit paper breakdown →
2020269
2 2020132
3 2014109
4 200899
5 202092
6 201792
7 201890
8 201878
9 202075
10 201073
11 201273
12 202069
13 201760
14 201957
15 202057
16 202057
17 201755
18 201855
19 201954
20 201951

About Mohammad A. Halim

Mohammad A. Halim is a scholar working on Molecular Biology, Organic Chemistry, Computational Theory and Mathematics, Materials Chemistry and Spectroscopy, having authored 131 papers that have together received 3.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (23 papers), Surfactants and Colloidal Systems (14 papers), SARS-CoV-2 and COVID-19 Research (12 papers), Thermodynamic properties of mixtures (11 papers), Ionic liquids properties and applications (11 papers), Chemical and Physical Properties in Aqueous Solutions (11 papers), Synthesis and biological activity (9 papers) and Heavy metals in environment (8 papers). The work is most often cited by research in Filtration and Separation (259 citations), Catalysis (256 citations), Organic Chemistry (886 citations), Fluid Flow and Transfer Processes (178 citations) and Computational Theory and Mathematics (429 citations). Mohammad A. Halim has collaborated with scholars based in Bangladesh, United States and Japan. Frequent co-authors include Md Nayeem Hossain, Muhammad Ali, Md Sajjadur Rahman, R. K. Majumder, Md. Rimon Parves, Md. Anamul Hoque, Rajib Islam, Abdulla Al Mamun, Malik Abdul Rub and Douglas E. Raynie. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Journal of Molecular Liquids, ACS Omega, Journal of Applied Sciences and Scientific Reports.

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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