Jun-Qing Yin | Computational Chemistry | Best Researcher Award

Prof. Dr. Jun-Qing Yin | Computational Chemistry | Best Researcher Award

Chengdu University | China

Profiles

Scopus
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Early Academic Pursuits

Dr. Jun-Qing Yin began his academic journey with a Bachelor’s degree in Chemistry, where he developed a strong foundation in physical and theoretical chemistry. His Master’s studies focused on the structural and energetic behaviors of gold clusters and their interaction with formaldehyde, showcasing early specialization in computational modeling and quantum chemical methods. His Ph.D. work advanced his theoretical expertise further, emphasizing surface chemistry and catalytic mechanisms of iron-based systems relevant to Fischer-Tropsch synthesis. These formative academic pursuits laid the groundwork for a career deeply rooted in the theoretical investigation of catalytic processes at the atomic level.

Professional Endeavors

Currently serving as a Research Fellow at the Institute of Advanced Study at Chengdu University, Dr. Yin has also held a postdoctoral position in the prestigious group of Professor Shigeyoshi Sakaki at Kyoto University. His career trajectory is marked by a consistent focus on the quantum chemical study of catalytic systems, with a specialization in transition metal surfaces, single-atom alloys, and interface chemistry. His work bridges the gap between theoretical predictions and experimental observables, forming key collaborations with experimentalists in the catalysis community.

Contributions and Research Focus

Dr. Yin’s research contributions are centered on surface catalysis, alloy stability, and reaction mechanisms. He has developed theoretical models for understanding the behavior of single-atom and phase-separated alloys in reactions such as NO-CO and dry reforming of methane. Additionally, his investigations into the performance of iron carbides, metal-support interactions, and the modification of catalytic surfaces using ligands contribute valuable insights to Fischer-Tropsch synthesis. His use of density functional theory (DFT) and other quantum mechanical tools reflects a deep understanding of electronic structures and catalytic behavior, advancing the design of more selective and efficient catalytic systems.

Impact and Influence

With a growing list of publications in top-tier journals such as Nature, Science, Journal of Catalysis, and ACS Catalysis, Dr. Yin’s work has gained substantial visibility in the fields of physical chemistry and catalysis. His collaboration in a landmark study on rhodium-zeolite catalysts for regioselective hydroformylation has positioned him at the forefront of molecular catalysis. His theoretical insights into metal-ligand interactions and catalyst support effects continue to influence both theoretical and applied research in sustainable energy and green chemistry.

Academic Citations

Although the precise citation metrics are not provided here, Dr. Yin’s publications in high-impact journals suggest a strong citation record. His involvement in collaborative research published in globally respected outlets like Nature and Science indicates a significant academic footprint. These works are likely to be highly cited within the communities of catalysis, surface chemistry, and computational materials science.

Technical Skills

Dr. Yin possesses advanced skills in quantum chemical modeling, particularly density functional theory (DFT), periodic boundary condition modeling, and computational catalysis. He is proficient in using simulation software such as VASP, Gaussian, and Materials Studio for the investigation of reaction mechanisms, adsorption behaviors, and surface reactivity. His ability to interpret complex electronic structures and reaction energy profiles makes him a valuable asset in any research setting focused on materials and energy applications.

Teaching Experience

While no formal teaching roles are specified, Dr. Yin has likely been involved in mentoring graduate students and collaborating with experimental teams, given his postdoctoral and research fellow positions. His ability to translate theoretical concepts into practical guidance for experimental interpretation reflects pedagogical strength, which may extend into future academic teaching responsibilities.

Legacy and Future Contributions

Dr. Yin is on a trajectory to make lasting contributions to the field of heterogeneous catalysis and materials chemistry. His research on alloy systems, particularly single-atom catalysts and metal-support interactions, provides foundational knowledge for the rational design of next-generation catalysts. As his collaborations and publication record expand, he is well-positioned to take on leadership roles in interdisciplinary research networks and contribute to global challenges in sustainable energy conversion.

Notable Publications

Regioselective hydroformylation of propene catalysed by rhodium-zeolite

Authors: Xiang-Jie Zhang, Tao Yan, Hua-Ming Hou, Jun-Qing Yin, Hong-Liu Wan, Xiao-Dong Sun, Qing Zhang, Fan-Fei Sun, Yao Wei, Mei Dong, Wei-Bin Fan, Jianguo Wang, Yu-Jie Sun, Xiong Zhou, Kai Wu, Yong Yang, Yong-Wang Li, Zhi Cao
Journal: Nature
Year: 2024

Catalysis of Nickel-Based gold single-atom alloy for NO-CO reaction: Theoretical insight into role of gold atom in enhancing catalytic activity

Authors: Jun-Qing Yin, Masahiro Ehara, Shigeyoshi Sakaki
Journal: Journal of Catalysis
Year: 2024

Surface modification of Fe5C2 by binding silica-based ligand: A theoretical explanation of enhanced C2 oxygenate selectivity

Authors: Jun-Qing Yin, Shu-Yuan Wang, Dan Xu, Yong You, Xing-Chen Liu, Qing Peng
Journal: Molecular Catalysis
Year: 2023

A new reaction mode of 3-halooxindoles: acting as C–C–O three-atom components for (3+3) cycloaddition to access indolenine-fused 2H-1,4-oxathiines

Authors: Ting-Jia Sun, Xue-Song Peng, Wei Sun, Yan-Ping Zhang, Xiao-Min Ma, Jian-Qiang Zhao, Zhen-Hua Wang, Yong You, Ming-Qiang Zhou, Jun-Qing Yin, Wei-Cheng Yuan
Journal: Organic Letters
Year: 2023

Theoretical exploration of properties of iron-silicon interface constructed by depositing Fe on Si(111)-(7×7)

Authors: Jun-Qing Yin, Yan-Ping Zhang, Yong You, Zhen-Hua Wang, Jian-Qing Zhao, Qiang Peng
Journal: Molecules
Year: 2023

Conclusion

Dr. Jun-Qing Yin exemplifies the qualities of an innovative and forward-thinking researcher. With a solid theoretical background, prolific scholarly output, and impactful collaborations, he continues to push the boundaries of physical chemistry and catalysis. His work not only advances scientific understanding but also lays the groundwork for technological innovations in green chemistry and energy-efficient catalysis.

 

Arunmozhi Bharathi Achudhan | Computational Chemistry | Best Scholar Award

Mr. Arunmozhi Bharathi Achudhan | Computational Chemistry |  Best Scholar Award

SRM Institute of Science and Technology, India

👨‍🎓Profiles

🧬 Academic and Research Background

Mr. Arunmozhi Bharathi Achudhan is a dynamic early-career researcher specializing in environmental genomics and microbiome analysis, currently pursuing his Ph.D. at SRM Institute of Science and Technology, Chennai, with his thesis submitted for review. His doctoral research, titled “Structural and Functional Genomic Analysis of Coal Microbiome and Machine Learning-Based Recovery of Novel Metagenome-Assembled Genomes (MAGs),” integrates next-generation sequencing (NGS) data analysis with computational biology and machine learning. Originally trained in microbiology, he has independently mastered advanced genomics techniques and computational pipelines, using over 150 workflows to deeply explore microbial communities in extreme environments.

🧪 Research Focus and Innovations

His research focuses on unculturable microbial genomes, recovering novel MAGs from coal microbiomes and evaluating their ecological and industrial significance. By analyzing structural diversity and mining functional genes, he has identified and validated novel enzymes like amidase and nitrilase through comparative structure analysis with protein crystal structures available in the Protein Data Bank. These findings carry high biotechnological potential for industrial applications. He has also developed a read-specific binning strategy for improved MAG reconstruction, now filed as a patent, which addresses limitations in existing metagenomics workflows.

💻 Technical and Computational Skills

Mr. Arunmozhi is adept at working in Linux environments and cloud platforms like AWS. He is highly skilled in coding with Python, R, and Perl, and proficient in setting up automated workflows using Snakemake and Conda. His experience includes using powerful metagenomic and proteomic analysis pipelines such as metaWRAP, MuDoGer, SqueezeMeta, Traitar, GTDB-tk, Prokka, Prodigal, AlphaFold, and Gromacs. He also utilizes AutoDockVina, PyMOL, and Schrödinger Suite for molecular docking and structure analysis. His strong command over bioinformatics tools bridges the gap between raw sequencing data and functional biological insights.

🧫 Laboratory Training and Teaching

In addition to his computational expertise, he has received formal training in Microbiology and Molecular Biology techniques, including GLP, and has instructed undergraduate laboratory courses in these areas. He also taught Computational Biology and delivered academic training in research methods, APA formatting, SPSS, and Sigma Plot, equipping students with both theoretical knowledge and practical scientific skills.

🎓 Education and Early Scientific Engagement

Mr. Arunmozhi holds a Master’s degree in Applied Microbiology and a Bachelor’s degree in Microbiology from Madras Christian College, where he also completed a Postgraduate Diploma in Medical Laboratory Technology. His postgraduate research included the molecular characterization of β-agarase from Sphingomonas paucimobilis, and he actively participated in international and national conferences, presenting research on larvicidal activity, microbial virulence, and antimicrobial agents.

🌍 Broader Contributions to Microbiome Science

His independent project on the Indian healthy human gut microbiome involved shotgun metagenomic analysis of 110 samples, where he employed language-based machine learning to identify hidden probiotic genomes. This study provided new insights into unculturable probiotic microbes and showcased how integrating metagenomics with machine learning can revolutionize microbiome research and gut health diagnostics.

🏅 Awards and Recognition

His academic contributions have been recognized through multiple oral presentation awards, including the Best Oral Presentation at the International Conference on Advances and Applications of Biotechnology (2024), and the Young Scientist Award at the International Conference on Innovation in Science and Technology for Sustainable Development (2023). He has also presented his work at several national and international platforms, including the National Conference on Structural Biology and Drug Discovery, and New Horizons in Bioengineering, among others.

🧠 Innovation and Intellectual Property

Mr. Arunmozhi is an innovator in the domain of metagenomic genome reconstruction. His patented approach, A Read-Specific Binning Strategy for the Recovery of Unculturable MAGs, improves the reliability and efficiency of genome assembly from complex microbial communities. This contribution represents a significant advancement in bioinformatics methodology, with applications across environmental microbiology, health, and industrial biotechnology.

🔮 Future Contributions and Vision

With a multidisciplinary skill set spanning microbiology, computational genomics, structural biology, and AI-driven analysis, Mr. Arunmozhi Bharathi Achudhan is poised to make impactful contributions to sustainable biotechnology, precision microbiome therapeutics, and enzyme discovery. He envisions continuing his journey in postdoctoral research, focused on unraveling complex microbial systems and translating genomic discoveries into real-world applications that benefit health and the environment.

📖Notable Publications

  1. A review on applications of β-glucosidase in food, brewery, pharmaceutical and cosmetic industries
    Contributors: P. Kannan, A.B. Achudhan, A. Gupta, L.M. Saleena
    Journal: Carbohydrate Research, 530, 108855
    Year: 2023

  2. Functional metagenomics uncovers nitrile-hydrolysing enzymes in a coal metagenome
    Contributors: A.B. Achudhan, P. Kannan, L.M. Saleena
    Journal: Frontiers in Molecular Biosciences, 10, 1123902
    Year: 2023

  3. A Review of web-based metagenomics platforms for analysing next-generation sequence data
    Contributors: A.B. Achudhan, P. Kannan, A. Gupta, L.M. Saleena
    Journal: Biochemical Genetics, 62(2), 621–632
    Year: 2024

  4. CRISPR detection in metagenome-assembled genomes (MAGs) of coal mine
    Contributors: A.B. Achudhan, P. Kannan, L.M. Saleena
    Journal: Functional & Integrative Genomics, 23(2), 122
    Year: 2023