جست‌وجوی استاد و پژوهشگر

• Computational Chemical Physics
• Polymer Physics
• Soft Matter Physics
• +۷ مورد دیگر

W.J. Briels is a Full Professor in Computational Chemical Physics at the University of Twente, Faculty of Science and Technology, Department of Applied Physics. His research spans polymer physics, soft matter, colloidal systems, and non-equilibrium thermodynamics, with a strong focus on simulation and modeling. His research interests lie at the intersection of physics, chemistry, and materials science, particularly in computational modeling of soft matter systems . Key areas include: Thermophoresis and Soret effect in colloidal and electrolyte solutions Coarse-grained simulations of polymers and biomolecules Flow of complex fluids in porous media Non-equilibrium statistical mechanics and irreversible thermodynamics Dynamics of star polymers and polymer melts His recent publications (2023–2025) show a continued focus on thermal diffusion in solutions , colloidal migration under temperature gradients , and entropic effects in confined liquids . The work combines theoretical frameworks with molecular simulations, often in collaboration with experimental groups. Briels has supervised over 25 research activities and 27 student projects, indicating a strong commitment to mentoring. He has delivered numerous invited talks and keynote lectures on coarse-graining and polymer dynamics. His work has been supported by grants related to soft matter and computational physics, though specific funding sources are not detailed here. He is actively involved in collaborative networks, particularly with researchers like J.K.G. Dhont and W.K. den Otter. His lab focuses on developing and applying advanced simulation techniques to complex fluid systems, with applications in materials science and biophysics.

Eva Raulsمشاهده پروفایل

استاد

• Computational Materials Science
• Surface Physics
• Theoretical Physics
• +۷ مورد دیگر

Eva Rauls is a Professor of Materials Physics in the Department of Mathematics and Physics at the University of Stavanger, under the Faculty of Science and Technology. Her research focuses on computational investigations of molecular adsorbates, catalytic properties, and electronic behavior of molecules on surfaces such as metals and graphitic materials. Her research interests include computational materials science, surface physics, supramolecular materials, and applications in CO2 capture and gas separation. She employs first-principles and semi-empirical methods, particularly density functional theory (DFT), to model and predict the behavior of functional materials. Current projects involve the design of supramolecular materials and optimization of metal-organic frameworks (MOFs) for environmental applications. The recent publication trends highlight a strong focus on pillararenes for CO2 adsorption, with detailed DFT studies analyzing functional group effects, cavity size, and molecular interactions. These works span chemistry, materials science, and environmental engineering, demonstrating interdisciplinary impact. Scientific awards include: Feodor-Lynen Fellowship of the Alexander-von-Humboldt-Society (2004–2006) Eva Rauls advises students such as Ho Quoc Duy and collaborates closely with the chemistry department and researchers like Uwe Gerstmann and Christoph Tegenkamp. Her work is supported by active research projects in functional material design for sustainable technologies. She regularly presents at international conferences including ECOSS, VCTP, and European Graphene Forum. She leads research efforts in atomistic modeling and computational studies of 2D heterostructures and molecular systems, indicating an active research group focused on theoretical and computational materials physics.

• Quantum Chemistry
• Density Matrix Theory
• Tensor Networks
• +۵ مورد دیگر

Dimitri Van Neck is a Full Professor (WE05) at Ghent University, Belgium, with his research base at Tech Lane Ghent Science Park (Technologiepark 46, 9052 Zwijnaarde). His academic career spans over three decades with continuous publication output from the 1980s through 2019 across leading physics and chemistry journals including Physical Review B, Journal of Chemical Physics, and Journal of Chemical Theory and Computation. Professor Van Neck's research program centers on theoretical frameworks for quantum many-body systems, with particular emphasis on density matrix theory, tensor network states, and integrable models. His work bridges fundamental theoretical physics with practical applications in quantum chemistry and materials science. Key methodological contributions include the development of three-legged tree tensor network states (T3NS), advanced density matrix embedding techniques, and novel approaches to Richardson-Gaudin integrable models. His research has evolved from nuclear physics in earlier career stages to contemporary focus areas in quantum information-inspired computational chemistry. Analysis of his recent publications (2015-2019) reveals three dominant research threads: (1) Advanced tensor network methodologies for quantum chemistry calculations, (2) Integrable models for topological superconductivity and quantum phase transitions, and (3) Materials science applications focusing on radiation effects in nuclear materials. His work demonstrates exceptional mathematical sophistication while maintaining practical relevance to experimental systems, particularly in understanding strongly correlated electron phenomena. Professor Van Neck maintains an extensive collaborative network across European research institutions, with frequent co-authorship patterns indicating stable research partnerships with S. De Baerdemacker, P. Claeys, P. Bultinck, P.W. Ayers, and S. Wouters. His group appears to develop computational tools like CheMPS2 (a spin-adapted implementation of density matrix renormalization group methods) and contributes to major conferences in quantum chemistry, theoretical physics, and computational materials science.

• Materials Science
• Computational Chemistry
• High-Throughput Simulations
• +۳ مورد دیگر

Dr. Aliaksandr Yakutovich is a Research Scientist at Empa, the Swiss Federal Laboratories for Materials Science and Technology, where he focuses on developing computational methods to study materials properties, particularly carbon-based nanomaterials. His work bridges atomistic simulations with practical applications, emphasizing reproducibility and workflow automation through platforms like AiiDAlab. He earned his PhD in Chemistry from the University of Zurich (2018), with his thesis conducted at Empa under Dr. Daniele Passerone and Prof. Jürg Hutter. His research interests include ab initio and empirical simulations of molecular adsorption, surface reactions, and Scanning Probe Microscopy. After his PhD, he contributed to EPFL's development of AiiDAlab, a web platform for sharing computational workflows, and automated protocols for metal-organic frameworks. His current research at Empa (since 2021) centers on magnetic and excitonic properties of carbon nanomaterials using beyond DFT methods. Notable contributions include workflow standardization, reproducible databases for COFs, and understanding enantioselective surface interactions. His work has been published in Comput. Mater. Sci. , Angew. Chem. Int. Ed. , and J. Am. Chem. Soc. . Yakutovich collaborates with leading groups in computational chemistry and materials science, advancing both fundamental understanding and practical tools for high-throughput simulations. His efforts in open science platforms aim to democratize access to advanced computational methods in materials research.

Irene Ariasمشاهده پروفایل

استاد

• Modeling and simulation of active materials
• Fracture mechanics in electromechanical materials
• Phase-field models of fracture
• +۳ مورد دیگر

Irene Arias is a Professor at the Universitat Politècnica de Catalunya (UPC) and an ICREA Academia Awardee. She holds a PhD in Mechanical Engineering from Northwestern University (2003) and a BS/MS in Civil Engineering from UPC. Her postdoctoral research at Caltech focused on computational solid mechanics under Prof. Michael Ortiz. Her research interests revolve around modeling and simulation of active materials, particularly flexoelectricity in solids. She investigates fracture mechanics in electromechanical systems, phase-field models of fracture, and ferroelectric materials. Recent work emphasizes flexoelectric effects in nanoscale materials and their applications in electromechanical transduction. Publications span computational mechanics, metamaterials, and nanotechnology. Notable contributions include modeling surface effects in flexoelectric materials and developing topology optimization frameworks for apparent piezoelectricity. She also leads the Spanish Association of Numerical Methods in Engineering (SENI-CIMNE).

DIDAC ARMANDمشاهده پروفایل

پژوهشگر

• Electrochemical Energy Storage
• Computational Quantum Chemistry
• Low-Dimensional Semiconductor Materials
• +۶ مورد دیگر

Dídac Armand is a researcher specializing in Electrochemical Energy Storage at the Autonomous University of Barcelona (UAB). He earned his PhD in Chemistry (2024) with a focus on computational characterization of photonic and electrocatalytic materials using first-principles quantum chemistry methods. Education : PhD in Chemistry (2024), UAB. His research spans low-dimensional semiconductor materials , homogeneous/heterogeneous catalysis , and green chemistry , particularly investigating ligand passivation effects and hydrogen evolution reaction (HER) electrocatalysts. He currently works in the Atomistic and Molecular Modelling for Catalysis group under Dr. Max García-Melchor. Scientific Awards : Formación de Personal Universitario grant (2019-2023) Cum Laude PhD honors (2024)

Wei Yangمشاهده پروفایل

استاد

• Computational Chemistry
• Biophysics
• Structural Biology
• +۷ مورد دیگر

Dr. Wei Yang is a Professor and Chair at Florida State University, where he leads research in computational biophysics. He earned his Ph.D. from the State University of New York at Stony Brook in 2001. His laboratory develops advanced atomistic simulation techniques to study complex biomolecular systems, with interdisciplinary applications spanning biochemistry, materials science, and biophysics. Research Focus: Dr. Yang's work centers on three pillars: First-principles protein/ligand design using quantum mechanical approaches Multi-scale simulation of biochemical events (DNA repair, enzyme kinetics, biomolecular recognition) Development of efficient computational methods including QM/MM, free energy sampling, and conformational analysis His recent publications demonstrate strong emphasis on methodological innovations in molecular dynamics (e.g., free energy surface construction, polarizable force fields) with applications to protein dynamics, membrane transport, and catalytic mechanisms. Work frequently integrates machine learning resampling techniques and experimental validation. Dr. Yang directs an active computational research group (Wei Yang Lab) focused on pushing boundaries in biomolecular simulation. While no specific awards or grants are detailed in available sources, his scholarly output reflects sustained contributions to computational chemistry methodology.

Liang Qiمشاهده پروفایل

دانشیار

• Computational Materials Science
• Mechanical Properties of Materials
• Chemical Properties of Materials
• +۳ مورد دیگر

Liang Qi serves as Associate Professor in the Department of Materials Science and Engineering at the University of Michigan's College of Engineering, where he leads computational research on mechanical and chemical properties of advanced materials. Education: Ph.D. in Materials Science and Engineering, University of Pennsylvania (2009) M.S. in Materials Science and Engineering, Ohio State University (2007) B.E. in Materials Science and Engineering, Tsinghua University (2003) Research Interests: Dr. Qi's work integrates first-principles calculations , atomistic simulations , multiscale modeling , and statistical machine learning to investigate deformation mechanisms, phase transformations, and microstructure-property relationships. His research spans titanium alloys, magnesium systems, high-entropy alloys, and semiconductor nanostructures, with emphasis on additive manufacturing processes and computational alloy design. The group develops predictive models for mechanical behavior under extreme conditions while bridging simulation with experimental validation. Analysis of recent publications reveals dominant trends in additive manufacturing of refractory alloys , grain boundary engineering in lightweight metals , and machine learning-accelerated materials discovery . Key focus areas include laser powder bed fusion processing, twinning mechanisms in hexagonal metals, and corrosion modeling in energy-relevant alloys, demonstrating strong alignment with Department of Energy and NSF priority research areas. Scientific Awards: TMS MPMD Young Leaders Professional Development Award (2021) National Science Foundation CAREER Award (2019) Dr. Qi's research is supported by competitive federal funding, notably the NSF CAREER award enabling computationally guided alloy design. His prior postdoctoral positions at MIT (Nuclear Science), University of Pennsylvania (Materials Science), and UC Berkeley (Materials Science) established foundations in multiscale modeling of structural materials. Current work integrates machine learning with physics-based simulations to accelerate development of next-generation structural alloys. His computational materials science group maintains active collaborations with experimental labs across the College of Engineering, particularly in the Center for新材料 Research, focusing on in-situ characterization of deformation mechanisms and additive manufacturing processes.

Mohammadreza Yaghoobiمشاهده پروفایل

پژوهشگر

• Multiscale Computational Plasticity
• Damage Mechanics
• Crystalline Materials
• +۸ مورد دیگر

Mohammadreza Yaghoobi is a Research Investigator in the Department of Materials Science & Engineering at the University of Michigan's College of Engineering. His work bridges computational modeling, experimental validation, and software development for material behavior analysis. Education: Ph.D. in Mechanical Engineering (Materials), Louisiana State University (2017) M.Sc. in Structural Engineering, Sharif University of Technology, Iran (2011) B.Sc. in Civil Engineering, IKIU, Iran (2008) Research Focus: Multiscale computational plasticity, damage mechanics of crystalline materials/composites/ceramics, theoretical modeling, and numerical simulation using tools like PRISMS-Plasticity. His work spans atomistic simulation to continuum plasticity frameworks. Scientific Recognition: Multiple awards at graduate research conferences, including first-place wins in 2016 (Manufacturing & Materials) and 2015 (Civil & Environmental Engineering), and a committee role in ASCE's Nanomechanics and Micromechanics division.

Andreas Lyberatosمشاهده پروفایل

دانشیار

• Numerical Methods in Applied Magnetism
• Magnetic Viscosity
• High-Speed Magnetization Switching
• +۴ مورد دیگر

Andreas Lyberatos is an Associate Professor at the Department of Materials Science and Technology, University of Crete. He obtained his B.Sc. in Physics from the University of London (1982) and a Ph.D. in Physics (1986) from the same institution. His research focuses on Numerical methods in applied magnetism Magnetic viscosity in nanoparticles and thin films High-speed switching dynamics FePt media for heat-assisted magnetic recording (HAMR) Ballistic thermal transport in magnetic multilayers . His recent publications emphasize HAMR media, magnetic reversal mechanisms, and thermal effects in ultrafast switching. Collaborative work with Seagate Technology (2000–2008) and academic roles across the UK and Greece highlight his interdisciplinary expertise.

Andrew A. Petersonمشاهده پروفایل

دانشیار

• Heterogeneous Catalysis
• Electrochemical Energy Conversion
• Computational Chemistry
• +۳ مورد دیگر

Andrew A. Peterson is an Associate Professor of Engineering at Brown University, focusing on heterogeneous catalyst design for fuels and energy applications. He integrates electronic structure theory with experimental approaches to advance catalytic processes. Education: PhD, Massachusetts Institute of Technology (2009) MS, Massachusetts Institute of Technology (2006) BS, University of Minnesota (1999) His research interests include electrochemical CO2 reduction, strain effects in catalysis, amorphous materials, and computational methods for catalyst optimization. He explores scaling relations in adsorption energies and their exceptions to design better catalysts. His recent publications (2014–2018) address: Proton discharge mechanisms on metal surfaces Strain-induced breaking of scaling relations Hydrogen evolution on molybdenum sulfide CO2-to-CO conversion over gold nanowires Competitive reaction pathways in transition metals Solar-driven fuel production from metal oxides Professor Peterson teaches courses such as: ENGN 0150: Principles of Chemical and Molecular Engineering ENGN 1130: Chemical Engineering Thermodynamics ENGN 2770: Atomistic Reaction Engineering He leads the Catalyst Design Lab at Brown, emphasizing atomistic-level catalyst design and electrochemical process optimization for sustainable energy solutions.

Alán Aspuru-Guzikمشاهده پروفایل

استاد

• Quantum Computing
• Theoretical Chemistry
• Machine Learning
• +۳ مورد دیگر

Alán Aspuru-Guzik is Professor of Chemistry and Computer Science at the University of Toronto, holding the Canada 150 Research Chair in Theoretical Chemistry, Canada CIFAR AI Chair at the Vector Institute, and Google Industrial Research Chair in Quantum Computing. He directs the Acceleration Consortium, a strategic initiative uniting industry, government, and academia for pre-competitive research on the 'lab of the future'. His educational background includes a PhD in Physical Chemistry from UC Berkeley and BSc in Chemistry from the National Autonomous University of Mexico. Research spans quantum information, chemistry, and machine learning—pioneering quantum algorithms for chemical simulations, investigating quantum coherence in photosynthesis, and accelerating discovery of organic semiconductors, photovoltaics, and batteries. Current focus centers on autonomous chemical laboratories integrating AI and robotics. Recent publications (2024-2025) reveal dominant trends: self-driving laboratories for materials synthesis, quantum computing applications in molecular simulation, and generative AI for metal-organic frameworks and drug discovery. Key methodologies include reinforcement learning for experimental design and vision-language models for reaction mining. Major awards include: Chemical Engineering Medal (2023) John C. Polanyi Award (2023) MIT TR35 (2010) Sloan Research Fellowship (2009) Canada 150 Research Chair (2018) As Director of the Acceleration Consortium, he leads multi-institutional efforts in autonomous research systems, supported by Canadian government chairs and Google funding. His editorial role at Digital Discovery and co-founding of Zapata AI (quantum software) and Kebotix (robotic labs) demonstrate commitment to transforming scientific discovery through AI-driven automation.

Oswaldo Dieguezمشاهده پروفایل

دانشیار

• Atomistic Simulation of Materials
• Epitaxial Strain Effects
• Magnetoelectric Multiferroics
• +۳ مورد دیگر

Prof. Oswaldo Dieguez is an Associate Professor at the Department of Materials Science and Engineering, Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University. He leads the Atomistic Simulation of Materials Group , focusing on computational studies at the intersection of materials science, physics, and chemistry. His research emphasizes atomistic simulations, epitaxial strain effects, and the design of magnetoelectric multiferroics. Research Areas: Epitaxial strain engineering, magnetoelectric multiferroics, computational materials design, and collaborations with experimentalists on alloys, molecular motors, and clean energy materials. Teaching: Courses in Introduction to Materials Science and Engineering , Physics of Materials , and Atomistic Simulation of Materials . Grants: Supported by the Israel Science Foundation and Tel Aviv University. Scientific Contributions: His work spans first-principles modeling of ferroelectric thin films, strain effects in perovskites, and quantum-mechanical simulations using tools like SIESTA. Recent publications highlight discoveries in ferroelectricity at the nanoscale, magnetic frustration control, and energy storage materials. Students: Mentoring PhD candidates Netanela Cohen, Mariia Mikhailova, and Daniel Potashnikov, alongside MSc student Tatiana Diachenko. Collaborating with experimental teams on metallic alloys, molecular motors, and clean energy materials.

• Multiscale Modeling
• Machine Learning
• Surface Science
• +۴ مورد دیگر

Karsten Reuter is a Director at the Fritz-Haber-Institut der Max-Planck-Gesellschaft in Berlin. His research spans multiple disciplines within computational chemistry and materials science, with a strong focus on heterogeneous catalysis, surface science, and energy conversion processes. With over 32,000 citations and an h-index of 91, he is a highly influential researcher in his field. Dr. Reuter's research interests primarily revolve around multiscale modeling , machine learning applications in materials science , surface science , heterogeneous catalysis , and energy conversion . His work bridges theoretical approaches with practical applications in catalysis and materials design. He has made significant contributions to the development of computational methods for studying surface reactions and catalytic processes at the atomic level. An analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional computational chemistry methods. His work spans from fundamental surface science studies to practical applications in energy conversion and storage. The publications cover diverse subfields including catalysis modeling, quantum chemistry methods, surface adsorption phenomena, and materials informatics. His research increasingly focuses on multiscale approaches that connect atomic-scale simulations with macroscopic phenomena. Dr. Reuter has received numerous citations for his methodological contributions, particularly in kinetic Monte Carlo simulations, first-principles thermodynamics, and the development of computational frameworks for studying heterogeneous catalysis. His work on the 'ab initio molecular simulations with numeric atom-centered orbitals' has been particularly influential with over 3,000 citations. Throughout his career, Dr. Reuter has collaborated extensively with leading researchers in computational chemistry and materials science, including Matthias Scheffler, Volker Blum, and Harald Oberhofer. His research has been supported by various grants focused on advancing computational methods for materials discovery and catalysis research.

Yu Fen Hsiaoمشاهده پروفایل

مدرس پاره‌وقت

• Chinese Language Instruction
• Materials Science
• Nanotechnology
• +۴ مورد دیگر

Yu Fen Hsiao is a Part-Time Lecturer in Chinese language instruction at George Mason University since Fall 2021, teaching Mandarin from a background at Sun Yat-sen University (Taiwan). She has prior teaching experience at Linnaeus University (Sweden), Trinity University of Asia (Philippines), and Manila Science High School. Education : Implied expertise in materials science through publications, though formal degrees are not specified in the provided text. Research Interests : Span materials science, focusing on nanocrystalline alloys, grain boundary diffusion, atomistic simulations, and thermodynamic stabilization of microstructures. Her work bridges mechanical engineering and computational modeling. Publications highlight trends in nanotechnology, grain boundary dynamics, and machine learning potentials for materials modeling. Scientific awards include the NSF-BSF grant for metallic nanoparticle research.