Mohammad Sardarabadi

4.2k total citations
47 papers, 3.5k citations indexed

About

Mohammad Sardarabadi is a scholar working on Mechanical Engineering, Renewable Energy, Sustainability and the Environment and Biomedical Engineering. According to data from OpenAlex, Mohammad Sardarabadi has authored 47 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Mechanical Engineering, 31 papers in Renewable Energy, Sustainability and the Environment and 18 papers in Biomedical Engineering. Recurrent topics in Mohammad Sardarabadi's work include Solar Thermal and Photovoltaic Systems (31 papers), Heat Transfer and Optimization (19 papers) and Nanofluid Flow and Heat Transfer (18 papers). Mohammad Sardarabadi is often cited by papers focused on Solar Thermal and Photovoltaic Systems (31 papers), Heat Transfer and Optimization (19 papers) and Nanofluid Flow and Heat Transfer (18 papers). Mohammad Sardarabadi collaborates with scholars based in Iran, Canada and France. Mohammad Sardarabadi's co-authors include Mohammad Passandideh‐Fard, Mohammad Hosseinzadeh, Saeed Zeinali Heris, Arash Kazemian, Mohammad Javad Maghrebi, Amin Taheri, Mohsen Ghazikhani, Ali Salari, Ali Jabari Moghadam and Meysam Khatibi and has published in prestigious journals such as Journal of Cleaner Production, Energy Conversion and Management and Energy.

In The Last Decade

Mohammad Sardarabadi

46 papers receiving 3.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Sardarabadi Iran 24 2.8k 1.5k 1.0k 462 455 47 3.5k
Lan Xiao China 29 1.6k 0.6× 1.3k 0.8× 326 0.3× 267 0.6× 425 0.9× 117 2.8k
Y.B. Tao China 32 2.4k 0.9× 3.0k 2.0× 659 0.6× 396 0.9× 702 1.5× 83 4.4k
Arash Kazemian China 21 1.6k 0.6× 788 0.5× 256 0.3× 266 0.6× 339 0.7× 31 1.9k
Tahir Abdul Hussain Ratlamwala Pakistan 28 1.2k 0.4× 1.3k 0.8× 507 0.5× 90 0.2× 291 0.6× 107 2.1k
Ehsan Ebrahimnia-Bajestan Iran 15 940 0.3× 610 0.4× 662 0.7× 140 0.3× 267 0.6× 26 1.6k
Husam Abdulrasool Hasan Iraq 20 1.0k 0.4× 793 0.5× 488 0.5× 150 0.3× 436 1.0× 36 1.8k
Mervyn Smyth United Kingdom 18 2.2k 0.8× 2.6k 1.7× 234 0.2× 72 0.2× 211 0.5× 27 3.1k
Jasim M. Mahdi Iraq 36 3.0k 1.1× 3.9k 2.5× 593 0.6× 64 0.1× 229 0.5× 106 4.4k
Zhang‐Jing Zheng China 23 1.3k 0.5× 1.5k 1.0× 286 0.3× 182 0.4× 161 0.4× 35 2.0k
Rehena Nasrin Bangladesh 26 1.5k 0.5× 1.6k 1.0× 1.7k 1.7× 188 0.4× 258 0.6× 126 2.8k

Countries citing papers authored by Mohammad Sardarabadi

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Sardarabadi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Sardarabadi

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Sardarabadi. A scholar is included among the top collaborators of Mohammad Sardarabadi 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 Mohammad Sardarabadi. Mohammad Sardarabadi 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.
2.
Niazmand, Hamid, et al.. (2025). Machine learning regression modeling of liquid jet impingement cooling: Based on computational fluid dynamics (CFD). International Journal of Thermal Sciences. 217. 110086–110086. 1 indexed citations
3.
Jamshidi, Mohammad, et al.. (2025). Experimental evaluation of surface roughness impact on thermal efficiency in electronic cooling systems: A comparative study of jet vs. spray cooling techniques. International Journal of Thermal Sciences. 213. 109795–109795. 4 indexed citations
4.
Moghaddam, Amir, et al.. (2025). Efficiency Enhancement of Photovoltaic-Thermal Systems Using Micro-Encapsulated Phase Change Material Slurry and Twisted Tape Inserts: A 4E Analysis. Applied Thermal Engineering. 278. 127272–127272. 1 indexed citations
5.
Passandideh‐Fard, Mohammad, et al.. (2024). The influence of porous media on the melting ability of phase change materials used in a heatsink: An experimental investigation. Journal of Energy Storage. 98. 112935–112935. 2 indexed citations
6.
Salari, Ali, et al.. (2024). Predicting the performance of a heat sink utilized with an energy storage unit using machine learning approach. Journal of Energy Storage. 83. 110470–110470. 6 indexed citations
7.
Shakibi, Hamid, et al.. (2024). Enhancing the thermal performance of an electronic chipset using an innovative cooling system: Insights from machine learning models. International Communications in Heat and Mass Transfer. 160. 108293–108293. 1 indexed citations
8.
Sardarabadi, Mohammad, et al.. (2023). Performance enhancement of triplex-tube heat storage unit using branched fins during solidification and melting processes: A 2D numerical parametric investigation. Thermal Science and Engineering Progress. 38. 101653–101653. 16 indexed citations
9.
Davoodi, Ali, et al.. (2023). Synergistic effect of active-passive methods using fins surface roughness and fluid flow for improving cooling performance of heat sink heat pipes. Experimental Heat Transfer. 37(6). 649–664. 8 indexed citations
10.
Kalani, Hadi, et al.. (2022). An experimental study integrated with prediction using deep learning method for active/passive cooling of a modified heat sink. Applied Thermal Engineering. 221. 119522–119522. 24 indexed citations
11.
Khoshvaght-Aliabadi, M., et al.. (2022). Experimental study of utilizing springs on absorber plate of solar air heaters: Subjected to axial-flow and cross-flow. Sustainable Energy Technologies and Assessments. 53. 102661–102661. 12 indexed citations
12.
Maghrebi, Mohammad Javad, et al.. (2022). Thermal performance prediction of a phase change material based heat-sink cooling system for a printed circuit board, using response surface method. Journal of Energy Storage. 55. 105499–105499. 7 indexed citations
13.
Taheri, Amin, et al.. (2020). A new design of liquid-cooled heat sink by altering the heat sink heat pipe application: Experimental approach and prediction via artificial neural network. Energy Conversion and Management. 206. 112485–112485. 50 indexed citations
14.
Hosseinzadeh, Mohammad, Ali Salari, Mohammad Sardarabadi, & Mohammad Passandideh‐Fard. (2018). Optimization and parametric analysis of a nanofluid based photovoltaic thermal system: 3D numerical model with experimental validation. Energy Conversion and Management. 160. 93–108. 174 indexed citations
15.
16.
Kazemian, Arash, Mohammad Hosseinzadeh, Mohammad Sardarabadi, & Mohammad Passandideh‐Fard. (2018). Experimental study of using both ethylene glycol and phase change material as coolant in photovoltaic thermal systems (PVT) from energy, exergy and entropy generation viewpoints. Energy. 162. 210–223. 115 indexed citations
17.
Sardarabadi, Mohammad, Mohammad Passandideh‐Fard, Mohammad Javad Maghrebi, & Mohsen Ghazikhani. (2016). Experimental study of using both ZnO/ water nanofluid and phase change material (PCM) in photovoltaic thermal systems. Solar Energy Materials and Solar Cells. 161. 62–69. 269 indexed citations
18.
Naghavi, Nadia, et al.. (2016). Simulation of tumor induced angiogenesis using an analytical adaptive modeling including dynamic sprouting and blood flow modeling. Microvascular Research. 107. 51–64. 6 indexed citations
19.
Kalani, Hadi, Mohammad Sardarabadi, & Mohammad Passandideh‐Fard. (2016). Using artificial neural network models and particle swarm optimization for manner prediction of a photovoltaic thermal nanofluid based collector. Applied Thermal Engineering. 113. 1170–1177. 68 indexed citations
20.
Sardarabadi, Mohammad & Mohammad Passandideh‐Fard. (2016). Experimental and numerical study of metal-oxides/water nanofluids as coolant in photovoltaic thermal systems (PVT). Solar Energy Materials and Solar Cells. 157. 533–542. 262 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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