جست‌وجوی استاد و پژوهشگر

Salai C. Ammalمشاهده پروفایل

عضو هیئت علمی

• Heterogeneous Catalysis
• Electrocatalysis
• Multiscale Modeling
• +۳ مورد دیگر

Salai C. Ammal is a Research Associate Professor in the Department of Chemical Engineering at the University of South Carolina, affiliated with the Molinaroli College of Engineering and Computing. His primary research focuses on computational catalysis, multiscale modeling, and electrocatalysis, particularly in energy conversion systems like solid oxide fuel cells (SOFCs). He holds a Ph.D. in Chemistry from Bharathidasan University, India (1998), and has extensive postdoctoral experience in Japan and the U.S., including roles at Rikkyo University, The University of Tokyo, and Osaka University. Ammal’s work emphasizes understanding catalytic mechanisms at metal-oxide interfaces and designing novel materials for energy applications. Education: Ph.D., Bharathidasan University (1998); M.S., Bharathidasan University (1992); B.S., Madurai Kamaraj University (1990). He also completed visiting scholar stints at the Indian Institute of Science and National Chemical Laboratory in India. Research Interests: Heterogeneous catalysis at metal-oxide interfaces, electrocatalysis in SOFCs, multiscale modeling of anode reactions, and rational design of (nano)materials. His studies integrate computational methods like DFT and microkinetic modeling to elucidate reaction pathways and material performance under realistic conditions. Key Contributions: Investigated the unique activity of Pt/TiO₂ catalysts in the water-gas shift reaction, modeled Ni/YSZ anode electrochemical reactions, and explored novel perovskite oxides for SOFC anodes. His publications span topics like interface dynamics, reaction kinetics, and material doping effects. Awards: JSPS Postdoctoral Fellowship (2001–2003), UGC National Predoctoral Fellowship (1993–1998), Outstanding Presentation Award (1996). Advising: Guided graduate students since 2008, with expertise in computational chemistry and catalysis. Labs/Teams: Member of the Heyden Research Group, focusing on computational catalysis and energy materials.

Abdelkader Karaمشاهده پروفایل

استاد

• Surface Science
• Materials Science
• Computational Physics
• +۳ مورد دیگر

Abdelkader Kara is a Professor in the Department of Physics at the University of Central Florida. He earned his Ph.D. in Condensed Matter Physics with Highest Honors from the Technical University of Lille and CEA Saclay, France. His research employs multi-scale computational approaches: First-principles DFT for surface properties and interatomic bonding Model potentials for temperature-dependent dynamics of complex systems Molecular dynamics for structural changes and atom manipulation via SPM Monte Carlo simulations for alloy segregation Development of interatomic potentials bridging ab initio and applied scales Recent publications focus on surface adsorption phenomena, 2D materials (phosphorene, silicene), machine learning applications in materials science, and catalytic surface design. Dr. Kara teaches undergraduate and graduate physics courses and mentors students in computational materials research. He maintains collaborations with experimental groups for validation of computational predictions and development of new characterization methodologies.

Shyam Kattelمشاهده پروفایل

استادیار

• Computational catalysis
• Electrocatalysis
• Density functional theory
• +۳ مورد دیگر

Shyam Kattel is an Assistant Professor in the Department of Physics at the University of Central Florida, where he leads the Computational Catalysis & Material Science group. His research develops computational methods to design materials for sustainable energy technologies. Core research integrates computational techniques across multiple scales: 1) Electronic structure calculations using density functional theory (DFT) to probe atomic-level interactions, 2) Kinetic Monte Carlo simulations to model reaction kinetics, and 3) Machine learning frameworks to predict material properties and degradation. Applications focus on catalysts for renewable fuel production and energy conversion. Dr. Kattel's publications demonstrate innovations in electrocatalyst design, including platinum-nickel systems for hydrogen evolution, molybdenum disulfide modifications, and transition metal nitride catalysts. His work appears in journals such as Soft Robotics and IEEE/ASME Transactions on Mechatronics. Honors include Trailblazer in Engineering (2023) and Robotics: Science and Systems Pioneer (2021). He teaches physics and mentors students in computational materials science. Current projects include developing predictive platforms for catalyst degradation and designing single-atom catalysts for sustainable chemical production.

Wenqiang Yangمشاهده پروفایل

استادیار

• Heterogeneous Catalysis
• Machine Learning
• CO2 Conversion
• +۲ مورد دیگر

Wenqiang Yang is a Research Assistant Professor in the Department of Chemical Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing. His research focuses on heterogeneous catalysis over transition metal surfaces and machine learning applications in catalysis. He investigates biomass conversion, CO2 capture, hydrogen storage, and solvent effects using DFT calculations and kinetic modeling. Education: Ph.D. in Chemical Engineering, University of South Carolina (2020) Master in Material Science and Engineering, University of Science and Technology of China (2015) B.Eng. in Material Science and Engineering, Nanjing University of Science and Technology (2012) Research Interests: Dr. Yang's work combines computational methods and machine learning to design catalysts for sustainable chemical processes. His studies include reaction mechanism elucidation, kinetic modeling, and inverse catalyst design for applications in renewable energy and environmental remediation. Awards: Kokes Award (2019) Best Poster Prize (2014) Academic Scholarships (2009-2010)

Duy Leمشاهده پروفایل

استادیار

• Materials Science
• Electrocatalysis
• Thermocatalysis
• +۳ مورد دیگر

Duy Le is an Assistant Professor at the University of Central Florida (UCF) affiliated with the Computational Materials for Energy and Technology (CoMET) research group. His work focuses on computational modeling of energy materials at the atomistic scale. Research Areas: Electrocatalysis, Thermocatalysis, Battery Materials, Molecular Electronics, Quantum Devices Methods: Density Functional Theory (DFT), Molecular Dynamics, Kinetic Monte Carlo (KMC), Microkinetic Modeling, Machine Learning The CoMET group investigates fundamental behaviors of energy materials through atomistic simulations and develops predictive computational frameworks. Recent publications emphasize CO2 reduction mechanisms, topological surface states, and single-atom catalyst designs using advanced quantum and classical modeling techniques. Key Article Trends: 6/2025-2025 focus on CO2 electroreduction with metallic catalysts (Au/Pt), 2024-2023 studies explore single-atom coordination effects, superconductivity in FeSe films, and solvent models for electrochemical interfaces. Technical Scope: Bridges ab initio calculations with multiscale simulations to address challenges in catalytic efficiency, quantum material properties, and energy storage systems. The research group actively seeks postdoctoral researchers and graduate students. Detailed publications and contact information are available through the UCF website.

Talat S Rahmanمشاهده پروفایل

استاد

• Multi-scale modeling of chemical reactions at surfaces
• Surface science
• Nanomaterials
• +۶ مورد دیگر

Talat S Rahman is a Trustee Chair, Pegasus, and Distinguished Professor in the Department of Physics at the University of Central Florida. Their research focuses on multi-scale modeling of chemical reactions at surfaces, surface coordination chemistry, and the development of advanced computational techniques for studying nanomaterials and catalytic processes. Recent research highlights include studies on 2D materials, CO2 electroreduction mechanisms, spin entanglement in molecular systems, and defect engineering for enhanced catalytic performance. Their work spans surface science, quantum physics, and materials engineering, with particular emphasis on predictive modeling and experimental validation. Scientific awards include the American Vacuum Society (AVS) Recognition for Excellence in Mentoring Award. Their team has published extensively on topics such as catalytic converter materials, ultrafast charge dynamics, and spin interactions in nanostructures.

Mark Finkمشاهده پروفایل

استاد

• Organosilicon chemistry
• Silicon p-conjugation
• Transition-metal catalysis
• +۳ مورد دیگر

Mark Fink is Professor of Chemistry at Tulane University's School of Science and Engineering, directing research in synthetic organosilicon and materials chemistry. His laboratory investigates silicon-based reactive intermediates and ceramic precursors. Research focuses on multiply-bonded silicon compounds exploring p-conjugation effects, mechanistic studies of transition-metal silicon chemistry, and organosilicon photochemistry using molecular beam and matrix isolation techniques. Applications include novel precursors for advanced ceramics. The Fink Group utilizes specialized instrumentation including cryogenic photochemical reactors, vapor pressure osmometry, and high-vacuum synthesis lines. Recent publications characterize sterically congested disilanes and functionalized silicon nanoparticles with biomedical applications.

• Solid State Theory
• Density Functional Theory
• Computational Materials Science
• +۲ مورد دیگر

Dr. Adrienn Ruzsinszky is Professor of Physics at Tulane University's School of Science & Engineering, specializing in solid-state theory and density functional theory (DFT) developments. Her research advances computational methods for quantum materials, focusing on electronic structure, excitonic phenomena, and optoelectronic properties of low-dimensional systems. Research highlights: Development of meta-generalized gradient approximations for quantum materials Excitonic insulator states in 2D materials Strain engineering of electronic properties Advanced time-dependent DFT methods Machine learning-enhanced materials discovery Recent publications demonstrate methodological innovations applied to topological insulators, transition metal dichalcogenides, and cuprate superconductors, with emphasis on exciton physics, charge density waves, and lattice dynamics. Research contributes to fundamental understanding of quantum phenomena in materials for energy and information technologies.

Jianwei Sunمشاهده پروفایل

دانشیار

• Condensed Matter Physics
• Density Functional Theory
• Materials Science
• +۲ مورد دیگر

Jianwei Sun is an Associate Professor at Tulane University's School of Science and Engineering, specializing in condensed matter theory and computational materials science. Research Focus: Develops and applies advanced density functional theory (DFT) methods to study quantum materials, including superconductors, topological states, and transition metal compounds. Pioneered SCAN meta-GGA functional for accurate material property predictions. Key Contributions: Created efficient density functionals achieving chemical accuracy for material stability; revealed electronic mechanisms in nickelate superconductors; resolved long-standing DFT limitations in simulating metal-metal bonding and self-interaction errors. Teaching: Leads graduate courses in Quantum Mechanics, Solid State Physics, and Atomic/Molecular Physics, integrating computational methodologies with theoretical frameworks.

Irmgard Frankمشاهده پروفایل

استاد

• Deterministic quantum mechanics
• Density functional theory
• Ab initio molecular dynamics
• +۳ مورد دیگر

Prof. Dr. rer. nat. Irmgard Frank holds the W2 Professorship for Theoretical Chemistry at the Institute of Physical Chemistry and Electrochemistry , Leibniz University Hannover. With a distinguished career spanning computational chemistry and ab initio molecular dynamics, her research bridges deterministic quantum mechanics, mechanochemistry, and photochemical reaction mechanisms. Education: Diploma in Chemistry (LMU Munich, 1993); Ph.D. under Prof. Peyerimhoff (University of Bonn, 1995). Research Interests: A pioneer in first-principles simulations, she investigates nuclear motion in chemical reactions, mechanochemical bond activation, and photoinduced processes. Her work integrates restricted open-shell Kohn-Sham theory for excited states and explores graphene-based heterostructures for energy applications. Publications: Her recent articles focus on lithium-sulfur batteries, DNA nucleotide translocation, and classical nuclear dynamics. Collaborations span electrochemistry, nanoscience, and catalysis, emphasizing computational-experimental synergy. Scientific Awards: Bavarian Habilitation Prize (2000) DFG Postdoctoral Fellowship (1996–1998) German National Academic Foundation Grant (1992–1993) Cusanuswerk Scholarship (1990–1993) Labs & Committees: Leads the Chemical Dynamics Simulation Group and serves on the Executive Board of her institute, Faculty Council of Natural Sciences, and Examination Boards for Chemistry programs.

Emily Liuمشاهده پروفایل

استاد

• Energy Materials and Systems
• Condensed Matter Physics
• Emergency Communication, Preparedness, and Response
• +۵ مورد دیگر

Emily Liu is the Department Head and Professor of the Department of Industrial and Systems Engineering at Rensselaer Polytechnic Institute (RPI), with a secondary appointment as Professor of Mechanical, Aerospace, and Nuclear Engineering. A condensed matter physicist and nuclear engineer, she bridges experimental and computational methodologies to address energy systems, socio-technical networks, and neutron scattering physics. B.Sc. in Technical Physics, Peking University (1999) Ph.D. in Nuclear Science and Engineering, MIT (2005) Her research integrates neutron/X-ray scattering with simulations (molecular dynamics, DFT) to study energy materials, nuclear fuel cycles, and climate-resilient systems. She emphasizes applications in nuclear data, smart infrastructure, and human health. Recent work focuses on molten salt corrosion , neutron moderator optimization , and socio-technical system design . The 15 most recent publications reflect her expertise in energy economics , material degradation , nuclear reactor design , and data-driven systems analysis . Her studies often involve interdisciplinary collaborations with engineers, economists, and psychologists. Notable scientific awards include: ELATES at Drexel Fellowship (2018-2019) Arab-American Frontiers Fellowship (2017) Cozzarelli Prize (2006) Manson Benedict Fellowship (2003) As an educator, she teaches courses such as Nuclear Phenomena for Engineering Applications and Introduction to Engineering Analysis . She has served as Graduate Program Director for ISE and mentors numerous undergraduate and graduate students, including thesis committees for 35 PhD candidates.

Ravishankar Sundararamanمشاهده پروفایل

دانشیار

• Computational Materials Science
• Electrochemistry
• Plasmonics
• +۹ مورد دیگر

Ravishankar Sundararaman is an Associate Professor in the Department of Materials Science and Engineering at Rensselaer Polytechnic Institute and holds the Priti and Mukesh Chatter '82 Career Development Chair. His research focuses on bridging quantum and classical simulation techniques for materials design in electrochemical, plasmonic, and nano-electronic applications. Ph.D. in Physics (Cornell University, 2013) B.Sc. + M.Sc. in Physics (Indian Institute of Technology, Kanpur, 2007) His group leads the development of the JDFTx open-source software and participates in the BEAST center for electrochemistry research. Key areas include hot carrier dynamics, electrocatalysis, spin relaxation, and quantum-informed material design for energy and semiconductor technologies. Recent publications highlight advancements in Random Phase Approximation methods for catalysis, spin-phonon relaxation mechanisms, and machine-learned functional approximations for multiscale modeling. Awards include the AIME Robert Lansing Hardy Award (2020) and Rensselaer School of Engineering Research Excellence Award (2020). He teaches graduate and undergraduate courses in Electronic Properties of Materials , Material Informatics , and Programming for Materials Engineers , emphasizing accessible quantum mechanics education and data science integration.

Simon Podkolzinمشاهده پروفایل

دانشیار

• Catalysis
• Chemical Kinetics
• Reaction Mechanisms
• +۴ مورد دیگر

Dr. Simon Podkolzin is an Associate Professor in the Department of Chemical Engineering and Materials Science at Stevens Institute of Technology. His research focuses on chemical kinetics and reaction mechanisms on catalytic surfaces, with applications in petroleum refining, chemical processing, pharmaceuticals, and biomass conversion. He leads the Catalytic Nanoparticles Lab, which bridges molecular-level surface reactions with observable kinetics through integrated experimental characterization and quantum chemical modeling. Education: PhD in Chemical Engineering, University of Wisconsin-Madison (2001) MS in Intellectual Property, University of London (1991) MS in Chemical Engineering, State University of Oil & Gas, Moscow (1988) Research interests span catalysis, nanomaterials, and reaction engineering, with specific focus on surface spectroscopy, reaction kinetics, and computational modeling. His work combines infrared spectroscopy, kinetic testing, and density functional theory to understand catalytic transformations at atomic scales. Recent publications demonstrate strong emphasis on sustainable processes, including biomass valorization, environmental remediation, and energy conversion. Research trends show increasing focus on bimetallic catalysts, in-situ characterization techniques, and renewable feedstock conversion. Scientific awards include recognition for graduate student research excellence and contributions to catalysis science. Dr. Podkolzin actively advises PhD students and serves on thesis committees. His funded projects include NSF and DOE grants for biomass upgrading and natural gas conversion research. He leads collaborative research teams focused on catalytic nanomaterials and maintains active partnerships with national laboratories and industry partners for technology development.

• Computational Chemistry
• Sustainable Chemistry
• Drug Synthesis
• +۷ مورد دیگر

Professor Yong Zhang is a tenured full Professor in the Department of Chemistry and Chemical Biology at the Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology. With over 30 years of academic experience, he leads a research group focused on high-accuracy computational chemistry with applications in sustainable chemistry, drug synthesis, and biomedical signaling molecules. PhD in Chemistry from Nanjing University BS in Chemistry from Nanjing University His research develops computational methods to solve experimental problems, achieving 1-3% error margins against experimental data. Key areas include: Mechanistic studies of bioengineered catalysts for sustainable chemistry and drug synthesis AI-driven molecular property prediction at quantum chemistry accuracy Metalloprotein interactions with NO/HNO for biomedical applications Quantum chemical analysis of drug binding structures and activation mechanisms Recent publications focus on biocatalytic C-H functionalization, heme protein mechanisms, and sustainable synthesis using metalloporphyrin systems. Grant support includes multiple NIH, NSF, and institutional awards. Over 50 research grants as Principal Investigator Training of 22 graduate and 40 undergraduate researchers 436-core computational cluster and 880-core school-wide resources Students from his lab have won awards including ACS Undergraduate Awards and gained admission to top graduate programs. His group emphasizes inclusivity with 63% of researchers from underrepresented groups.

Georg Schreckenbachمشاهده پروفایل

استاد

• Theoretical Chemistry
• Computational Chemistry
• Materials Science
• +۷ مورد دیگر

H. Georg Schreckenbach is a Professor and Faculty of Science Research Chair in Fundamental Science (Physical Sciences/Chemistry) at the University of Manitoba's Department of Chemistry. His research focuses on theoretical and computational chemistry, emphasizing quantum chemical method development and applications to materials, actinides, environmental systems, and energy-related materials. He leads a research group developing state-of-the-art computational tools for studying molecular and extended systems. Key research areas include: Materials chemistry (2D materials, nanostructures, conducting polymers) Solar energy (dye-sensitized cells, singlet fission, photocatalysis) Actinide molecular science (uranium/plutonium chemistry, environmental/medical applications) Environmental chemistry (actinide-heavy metal interactions, crude oil component thermodynamics) Quantum chemical method development (solvation models, excited states, high-throughput computing) Recent work highlights include studies on actinide complexation with macrocyclic ligands, 2D chalcogenide materials for photocatalysis, and radiopharmaceutical ligand design for targeted therapies. His research integrates computational simulations with experimental collaborations, addressing both fundamental science and applied challenges in energy and environmental sectors. Dr. Schreckenbach's group maintains active collaborations across disciplines, leveraging advanced computing infrastructure to explore complex systems. He contributes to software development (Amsterdam Modeling Suite) and serves as a research leader in theoretical chemistry at the University of Manitoba.