Jun-Qing Yin | Computational Chemistry | Best Researcher Award

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

Chengdu University | China

Profiles

Scopus
Orcid

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.

 

Arnab Banerjee | Quantum Computation of Materials | Best Researcher Award

Assist. Prof. Dr. Arnab Banerjee | Quantum Computation of Materials | Best Researcher Award

Purdue University, United States

👨‍🎓Profiles

🏫 Early Academic Pursuits

He began his academic journey with a passion for material science and technology. His foundational studies emphasized materials synthesis and analytical properties, laying the groundwork for his later groundbreaking contributions to solid-state quantum computing. His academic curiosity drove him to explore quantum magnetism, fostering an interdisciplinary approach that bridges chemistry, physics, and computational sciences.

💼 Professional Endeavors

Currently an Assistant Professor at Purdue University, Dr. Banerjee is an esteemed researcher and faculty member specializing in quantum materials and computing. He actively manages five funded projects supported by the DOE, Keck Foundation, and NSF-IUCRC/Industry, involving advanced quantum chemistry, crystallography, and quantum Hamiltonian modeling using cutting-edge quantum computers. His collaborations with Los Alamos and Oak Ridge National Laboratories and industry leaders like IBM-Q and D-Wave highlight his integration into global research ecosystems.

🌟 Contributions and Research Focus

His research has revolutionized our understanding of quantum materials. Notably, his discovery of the Kitaev candidate material RuCl₃ and the first evidence of magnetic Majorana fermions earned recognition as one of 2016's top science achievements by Discover Magazine. His innovative work links magnetic material modeling, neutron scattering experiments, and quantum computation, published in leading journals such as Physical Review B (Editor's Suggestion), npj Quantum Information, and Nature Communications.

🌍 Impact and Influence

Dr. Banerjee's contributions to quantum computing and magnetism have a global impact. By collaborating with institutions like Caltech and DOE National Labs, he fosters cross-disciplinary innovation. His efforts to integrate quantum computing into material sciences pave the way for achieving higher quantum coherence, driving advancements in both theoretical and applied sciences.

📈 Academic Citations and Recognitions

With 41 peer-reviewed journal articles and a citation index of 28, He is a highly regarded figure in his field. As a guest editor for MDPI's special issue, he contributes to the scientific community by curating cutting-edge research. His expertise and influence are recognized through memberships in the American Physical Society and the Materials Research Society.

🛠 Technical Skills

His technical repertoire includes quantum chemistry, spin density of state measurements, phonon analysis, and advanced neutron scattering techniques. He excels in quantum Hamiltonian modeling using quantum computers, bridging experimental observations with theoretical predictions to accelerate material discoveries.

👩‍🏫 Teaching and Mentorship

As an educator, Dr. Banerjee is dedicated to cross-training students and staff in quantum materials and computing. He collaborates with national laboratories and industries to create immersive learning experiences that prepare the next generation of researchers to tackle forefront scientific challenges.

🌱 Legacy and Future Contributions

He envisions a future where quantum computing and material sciences converge seamlessly. His ongoing research aims to uncover novel materials and phenomena that enhance quantum coherence, bringing quantum computing closer to practical applications. His commitment to mentoring and collaboration ensures a lasting legacy in advancing science and nurturing innovation.

📖Notable Publications

  1. Gibbs state sampling via cluster expansions
  2. Authors: Eassa, N.M.; Moustafa, M.M.; Banerjee, A.; Cohn, J.
    Journal: npj Quantum Information, 2024.
  3. High-fidelity dimer excitations using quantum hardware
  4. Authors: Eassa, N.M.; Gibbs, J.; Holmes, Z.; Cohn, J.; Banerjee, A.
    Journal: Physical Review B, 2024.
  5. Magnetic interactions and excitations in SrMnSb₂
  6. Authors: Ning, Z.; Li, B.; Tang, W.; McQueeney, R.J.; Ke, L.
    Journal: Physical Review B, 2024.
  7. Experimental evidence for nonspherical magnetic form factor in Ru³⁺
  8. Authors: Sarkis, C.L.; Villanova, J.W.; Eichstaedt, C.; Berlijn, T.; Nagler, S.E.
    Journal: Physical Review B, 2024.
  9. Purely antiferromagnetic frustrated Heisenberg model in the spin-ladder compound
  10. Authors: Roll, A.; Petit, S.; Forget, A.; Foury-Leleykian, P.; Balédent, V.
    Journal: Physical Review B, 2023.
  11. Dynamic Asset Allocation with Expected Shortfall via Quantum Annealing
  12. Authors: Xu, H.; Dasgupta, S.; Pothen, A.; Banerjee, A.
    Journal: Entropy, 2023.
  13. Simulations of frustrated Ising Hamiltonians using quantum approximate optimization
  14. Authors: Lotshaw, P.C.; Xu, H.; Khalid, B.; Humble, T.S.; Banerjee, A.
    Journal: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023.
  15. Planar thermal Hall effect of topological bosons in the Kitaev magnet α-RuCl₃
  16. Authors: Czajka, P.; Gao, T.; Hirschberger, M.; Nagler, S.E.; Ong, N.P.
    Journal: Nature Materials, 2023.
  17. Distinct Acoustic and Optical Phonon Dependences on Particle Size, Oxidation, and Temperature in Silicon Nanocrystals
  18. Authors: Chen, S.; Coleman, D.; Abernathy, D.L.; Mangolini, L.; Li, C.
    Journal: Journal of Physical Chemistry C, 2022.
  19. Extraction of interaction parameters for α-RuCl₃ from neutron data using machine learning
  20. Authors: Samarakoon, A.M.; Laurell, P.; Balz, C.; Okamoto, S.; Tennant, D.A.
    Journal: Physical Review Research, 2022.