Dr. Muhammad Iqbal | Computational Methods | Research Excellence Award

Dr. Muhammad Iqbal | Computational Methods | Research Excellence Award

Associate Professor | Bacha Khan University | Pakistan

Dr. Muhammad Iqbal is a distinguished researcher whose scholarly profile reflects sustained excellence in chemistry with strong integration of Computational Methods in advanced scientific inquiry. His work demonstrates authoritative use of Computational Methods to analyze molecular systems, interpret coordination chemistry behavior, and enhance predictive accuracy, where Computational Methods consistently guide hypothesis development, data interpretation, and validation. Through extensive peer reviewed publications indexed in SCI and Scopus, he has contributed impactful knowledge supported by rigorous Computational Methods that strengthen reproducibility and translational relevance. His research output shows meaningful citation influence and international visibility, while Computational Methods enable collaborative alignment with interdisciplinary researchers and institutional partners. By applying Computational Methods to complex chemical challenges, his contributions advance analytical efficiency, resource optimization, and knowledge driven innovation with tangible societal and scientific benefits. His academic service and research dissemination reflect a commitment to quality, integrity, and global standards, with Computational Methods remaining central to methodology, collaboration, and impact across his scholarly endeavors. Google Scholar profile of 380 Citations, 13 h-index, 13 i10 index.

Citation Metrics (Google Scholar)

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380
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i10-index

                       ■ Citations                        ■ h-index                       ■ i10-index

Featured Publications

Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

Prof. Dr. Jinju Sun | Computational Methods | Best Researcher Award

Professor | Xi'an Jiaotong University | China

Prof. Dr. Jinju Sun is a distinguished scholar in the School of Energy and Power Engineering at Xi’an Jiaotong University, renowned for her pioneering contributions to fluid mechanics, turbomachinery, and multiphase flow systems through advanced Computational Methods. Her educational journey spans cryogenic engineering to a PhD in turbomachinery and engineering mechanics, which laid the foundation for her expertise in Computational Methods applied to turbomachinery optimization, Lattice Boltzmann modeling, and Vortex Method simulations. Throughout her professional career, she has served as a researcher, lecturer, and professor, advancing research through numerous national and international collaborations emphasizing Computational Methods in fluid dynamics and green energy system design. She has received prestigious honors, including the Donald Julius Groen Prize and the Arthur Charles Main Award from the Institution of Mechanical Engineers (UK), in recognition of her outstanding achievements utilizing Computational Methods for energy system modeling and flow optimization. Her research interests include cryogenic liquid turbines, compressor instabilities, and innovative Computational Methods for fluid-structure interaction and multiphase flow behavior. She has authored numerous high-impact publications and holds multiple international patents that demonstrate her excellence in Computational Methods-based innovation. Prof. Dr. Jinju Sun’s research skills encompass CFD modeling, LBM, topology optimization, and Computational Methods-driven analysis for turbomachinery and green energy systems. In conclusion, her dedication to advancing Computational Methods in engineering has positioned her as a global leader driving innovation, sustainability, and scientific excellence in modern energy and power engineering.

Profile: ORCID

Featured Publications

1. Qu, Y., Sun, J., Song, P., & Wang, J. (2025). Enhancing efficiency and economic viability in Rectisol system with cryogenic liquid expander. Asia-Pacific Journal of Chemical Engineering.

2. Ge, Y., Peng, J., Chen, F., Liu, L., Zhang, W., Liu, W., & Sun, J. (2023). Performance analysis of a novel small-scale radial turbine with adjustable nozzle for ocean thermal energy conversion. AIP Advances.

3. Fu, X., & Sun, J. (2023). Three-dimensional color-gradient lattice Boltzmann model for simulating droplet ringlike migration under an omnidirectional thermal gradient. International Journal of Thermal Sciences.

4. Song, P., Sun, J., Wang, S., & Wang, X. (2022). Multipoint design optimization of a radial-outflow turbine for Kalina cycle system considering flexible operating conditions and variable ammonia-water mass fraction. Energies.

5. Song, P., Wang, S., & Sun, J. (2022). Numerical investigation and performance enhancement by means of geometric sensitivity analysis and parametric tuning of a radial-outflow high-pressure oil–gas turbine. Energies.