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Samit RoyView profile

Professor

• Composite Materials
• Advanced Materials
• Carbon Nanotubes
• +15 more

Dr. Samit Roy is the William D. Jordan Professor in the Department of Aerospace Engineering and Mechanics at The University of Alabama, College of Engineering. He is actively involved in research through multiple centers including the Center for Advanced Vehicle Technologies and the Polymers and Soft Materials Research Center. Ph.D., Engineering Science and Mechanics, Virginia Tech, 1988 M.S., Aerospace Engineering, Virginia Tech, 1986 B.Tech, Aerospace Engineering, Indian Institute of Technology, Kharagpur, 1981 Dr. Roy's research focuses on advanced composite materials, with a strong emphasis on multiscale modeling, nanotechnology, and self-healing polymers. His work spans computational mechanics, material characterization, and manufacturing of high-performance composites for aerospace applications. He investigates fracture mechanisms, interfacial strength enhancement using carbon nanotubes, and structural health monitoring using embedded sensors. His recent publications highlight a strong trend in nanocomposites, multiscale modeling, and self-healing materials, particularly focusing on carbon nanotube-wrapped fibers and thermoset composites. These works employ molecular dynamics and finite element methods to understand material behavior at micro and nanoscales, contributing to the development of durable, lightweight, and intelligent materials for extreme environments. Dr. Roy has received numerous accolades for his contributions to composites research and academic leadership: ASC/DEStech Award in Composites, 2023 UA President’s Senior Research Scholar Award, 2024 Fellow of ASME, 2010 Associate Fellow of AIAA, 2007 Summer Faculty Fellowship at Air Force Research Laboratory, 2016 He has secured significant research funding, notably from the Air Force Office of Scientific Research, where he served as a program officer. His leadership extends to mentoring Ph.D. students and guiding research teams in composite material innovation. He has been elected to leadership roles in technical divisions of ASC and ASME, reflecting his national impact. Dr. Roy leads research initiatives within interdisciplinary centers focused on advanced materials and vehicle technologies, collaborating with teams on scalable manufacturing, damage prognosis, and smart material systems.

• Computational Chemical Physics
• Polymer Physics
• Soft Matter Physics
• +7 more

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.

• Quantum Chemistry
• Density Matrix Theory
• Tensor Networks
• +5 more

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
• +3 more

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.

Maria KurnikovaView profile

Professor

• Computational Chemistry
• Biophysical Chemistry
• Molecular Modeling
• +3 more

Maria Kurnikova is a Professor of Chemistry at Carnegie Mellon University (CMU), affiliated with the Mellon College of Science. She holds concurrent roles as Co-Director of the Molecular Biophysics & Structural Biology (MBSB) Graduate Program and affiliated faculty in the Joint CMU-Pittsburgh Computational Biology Program. Her research focuses on computational chemistry, molecular modeling, and theoretical biophysics, particularly in understanding protein structure-function relationships through high-performance computing and multi-scale modeling approaches. Education: M.Sc., Moscow Institute of Physics and Technology, 1984–1990 Ph.D., University of Pittsburgh, 1998 Postdoctoral Fellowships: University of Tel Aviv (1998–1999) and University of Pittsburgh/NIST (1999–2001) Research Interests: Dr. Kurnikova's work spans computational modeling of membrane proteins, ion channels, and drug design. Her group develops hierarchical models to bridge atomistic and macroscale processes, with applications in understanding ligand binding, channel gating, and ion selectivity. Current projects include: Membrane protein receptors and ion channel dynamics In silico drug design using machine learning and free energy simulations Development of accurate force fields for molecular interactions Awards: 2024 Department of Chemistry Distinguished Alumni Award (University of Pittsburgh) 2002 Research Corporation Innovation Award Collaborations & Resources: Active user of NSF/NIH supercomputing facilities (e.g., Pittsburgh Supercomputing Center) Collaborations with Olexandr Isayev’s group on drug design methodologies Labs & Teams: The Kurnikova Research Group specializes in theoretical and computational approaches to biological macromolecules, with ongoing projects in TRPM7 channel regulation, AMPA receptor allostery, and heme transfer mechanisms.

Irene AriasView profile

Professor

• Modeling and simulation of active materials
• Fracture mechanics in electromechanical materials
• Phase-field models of fracture
• +3 more

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).

Ioannis KarathanasisView profile

Lecturer

• Cavitation Modeling
• Multiphase Flows
• Computational Fluid Dynamics
• +4 more

Dr. Ioannis Karathanasis is a Lecturer in Mechanical Engineering at City, University of London's School of Science & Technology, where he has been employed since January 2018. Previously, he served as a Research Fellow (2016-2017) and Experienced Marie-Curie Researcher (2015-2016) at the same institution following his PhD completion at the National Technical University of Athens. His educational background includes a PhD in Mechanical Engineering (2015) and a Master's Degree in Mechanical Engineering (2009), both from the National Technical University of Athens. During his doctoral studies, he received a Scholarship for doctoral studies from the Special Account for Research of the National Technical University of Athens (2011-2015). Dr. Karathanasis specializes in cavitation modeling and multiphase flows, with particular expertise in fuel injection systems and heat transfer enhancement techniques. His research focuses on the study of cavitation formation and induced erosion in automotive and energy industry applications, including high-pressure fuel injection systems. He has developed numerical models implemented in both commercial CFD software and in-house codes that have been transferred to industrial partners such as Perkins Engines UK and Caterpillar Fuel Systems. His recent publication record demonstrates a strong focus on sustainable aviation fuels, multi-component fuel systems, and the application of machine learning to spray prediction. The research shows progression from fundamental cavitation studies toward more complex multi-component fuel systems and advanced computational methodologies including machine learning applications. Professional recognition includes the Best PhD Dissertation in Applied Sciences award from NCSR Demokritos (2016). He maintains active professional memberships with both the Society of Automotive Engineers (since 2016) and the Technical Chamber of Greece (since 2010). Dr. Karathanasis has secured significant research funding through multiple EU projects including H2020 ITN-HAoS, H2020 ITN-CAFE, and FP7-FS3000. His collaborative network spans internationally with institutions including Argonne National Laboratory, Caterpillar Fuel Systems (USA), Perkins Engines UK, Lubrizol Ltd. UK, University of Bergamo (Italy), and TU Delft (Netherlands). His experimental expertise includes high-speed imaging, X-ray phase-contrast and absorption imaging, and development of specialized test rigs for complex flow characterization. He has delivered numerous keynote lectures globally on cavitation visualization and modeling techniques.

Jian Xiang LianView profile

Researcher

• Electrochemical Energy Storage
• Solid-State Materials
• Graphene Functionalization
• +6 more

Dr. Jian Xiang Lian is a computational researcher specializing in solid-state materials for energy applications. His career spans multiple institutions, including the University of Mons (UMONS) where he completed his PhD (2013-2017) under Prof. Yoann Olivier and Prof. David Beljonne. He continued postdoctoral work at UMONS (2017), CIC energiGUNE (2018-2021), and now contributes to clean energy research at the University of Calgary (since 2021). University of Mons (PhD, Postdoc) CIC energiGUNE (Postdoc) University of Calgary (Researcher) Research Focus: Atomistic and quantum simulations using Density Functional Theory (DFT) and Molecular Dynamics (MD) for energy storage systems, including: Graphene functionalization for charge transport modulation Room-temperature ionic liquids (RTILs) at graphene interfaces Oxygen and ionic diffusion in layered/mixed transition metal oxides Metal-organic frameworks (MOFs) for CO2 capture Machine learning applications in materials discovery Scientific Contributions: Jian Xiang Lian's work explores fundamental mechanisms in electrochemical systems, advancing sodium-ion batteries, lithium metal batteries, and CO2 reduction technologies. Key findings include Ti-doping effects on Na-ion mobility, oxygen vacancy dynamics in spinels, and electrolyte stability engineering. 2018: Oxygen vacancies in Co3-xMnxO4 spinels 2020: Nitridophosphates for high-voltage cathodes 2021: Perfluoropolyether electrolytes for lithium metal interfaces

Andrey GolovView profile

Researcher

• Theoretical Materials Science
• Computational Chemistry
• Crystal Chemistry
• +4 more

Andrey Golov is a Researcher at CIC energiGUNE, where he contributes to the Atomistic Modelling and Computational Studies group under Dr. Javier Carrasco. His work focuses on advancing computational methodologies for electrochemical energy storage materials, particularly through atomistic simulations and structural analysis of ion-conducting compounds. His academic foundation includes: Master's degree in Chemistry Science from Samara State University (Russia), completed in 2014 PhD from Samara National Research University (2019) under Prof. Vladislav A. Blatov, developing Voronoi partition algorithms for geometrical-topological analysis of crystal structures Postdoctoral research at Samara State Technical University (2019-2020) involving IonExplorer program development for ion diffusion analysis Golov's research integrates theoretical materials science with computational chemistry to address energy storage challenges. He specializes in high-throughput quantum mechanical simulations of fast ion conductors, geometrical-topological characterization of microporous crystalline materials, and graph theory applications for crystal structure design. His work establishes critical correlations between pore descriptors and physical-chemical properties in microporous compounds, directly supporting next-generation battery material development. No scientific awards or honors were documented in the source material. Information regarding graduate student advising, research grants, or collaborative projects beyond his core group activities was not disclosed in the available text. He operates within CIC energiGUNE's specialized research ecosystem, leveraging the Atomistic Modelling and Computational Studies group's infrastructure for electrochemical energy storage innovation, with particular emphasis on computational screening of inorganic conductors and solid-state phase transition modeling.

Eric JohlinView profile

Assistant Professor

• Optoelectronics
• Photovoltaics
• Nanophotonics
• +3 more

Dr. Eric Johlin is an Assistant Professor in the Department of Mechanical and Materials Engineering at Western University, Faculty of Engineering. Education: Ph.D. in Mechanical Engineering and Materials Science, Massachusetts Institute of Technology, 2014 M.Sc. in Mechanical Engineering and Materials Science, Massachusetts Institute of Technology, 2011 B.Sc. in Mechanical Engineering, California Institute of Technology, 2009 Research Interests: Dr. Johlin's research focuses on developing optoelectronic devices for clean energy applications through nanophotonic engineering. His work integrates experimental fabrication, theoretical modeling, and computational simulations across atomic to macroscopic scales, with emphasis on nanostructure-enhanced photovoltaics and algorithmic device design. Key methodologies include atomistic modeling and macroscopic characterization of nanophotonic systems. Professional Experience: Following his doctoral studies, he completed a three-year postdoctoral fellowship at AMOLF's Center for Nanophotonics in Amsterdam before joining Western University. Research Group: He leads a dedicated research team investigating atomic-scale effects in energy conversion devices, with strong emphasis on bridging computational design and experimental validation for next-generation photovoltaic systems.

Wei YangView profile

Professor

• Computational Chemistry
• Biophysics
• Structural Biology
• +7 more

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 QiView profile

Associate Professor

• Computational Materials Science
• Mechanical Properties of Materials
• Chemical Properties of Materials
• +3 more

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 YaghoobiView profile

Researcher

• Multiscale Computational Plasticity
• Damage Mechanics
• Crystalline Materials
• +8 more

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.

Katie Dongmei Li-OakeyView profile

Professor

• Catalytic Membranes
• Functional Membranes
• Thin Films and Coatings
• +7 more

Katie Dongmei Li-Oakey is a Professor in the Department of Chemical and Biomedical Engineering at the University of Wyoming, where she serves as Undergraduate Coordinator. Her research focuses on catalytic membranes, functional thin films, and coatings for liquid filtration, gas processing, and biomedical sensors. She explores novel catalyst-surface interactions to address separation challenges like fouling and poisoning. Ph.D. in Chemical and Biological Engineering (University of Colorado at Boulder, 2003) Postdoctoral Fellow (University of Colorado at Boulder, 2003-2005) Adjunct Assistant Professor (University of Wyoming, 2010-2011) Industry experience: Intel Corporation, DRC Metrigraphics Her work spans fuel cell materials , COF-based membranes , and self-cleaning surfaces , with patents on ultra-low Pt catalysts and durable nanoparticle platforms. Publications emphasize covalent organic frameworks , oxygen-inhibited photopolymerization , and electrochemical performance of carbon electrodes. Current projects include microparticle fabrication , ionic liquid recycling , and environmental sensors . She collaborates on energy exploration filtration and biomedical devices , applying computational modeling to optimize membrane properties.

Andreas LyberatosView profile

Associate Professor

• Numerical Methods in Applied Magnetism
• Magnetic Viscosity
• High-Speed Magnetization Switching
• +4 more

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.