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Chris G. Van de Walle is the Herbert Kroemer Distinguished Professor in the Department of Materials at the University of California, Santa Barbara's College of Engineering. As a member of the National Academy of Engineering and fellow of multiple prestigious scientific societies including the American Physical Society and Materials Research Society, he leads the Computational Materials Group which is part of UCSB's strong computational science cluster within the Materials Department. His research interests focus on novel electronic materials, particularly wide-band-gap semiconductors (III-V nitrides, II-VI compounds), transparent conductors, complex oxides, loss mechanisms in light emitters, two-dimensional conductors, quantum information science, and the physics and chemistry of hydrogen interactions with solids. His group uses first-principles computational techniques to study atomic and electronic structure of crystalline, polycrystalline and amorphous materials, interfaces, surfaces, defects, and heterojunctions. Analysis of his recent publications reveals a strong focus on semiconductor materials for quantum technologies, with particular emphasis on GaN, Ga 2 O 3 , and related compounds. His work combines computational materials science with applications in optoelectronics, quantum information, and energy technologies, demonstrating consistent innovation in understanding defects and their role in material properties. Major Awards and Recognitions: Aneesur Rahman Prize for Computational Physics (APS) Materials Theory Award (MRS) Vannevar Bush Faculty Fellowship (DoD) John Bardeen Award (TMS) Medard W. Welch Award (AVS) Highly Cited Researcher (Clarivate Analytics) Professor Van de Walle has mentored numerous successful researchers, including Dr. Fangzhou Zhao (Corbett Prize winner) and Dr. Mark Turiansky (APS Nicholas Metropolis Award recipient). His group maintains strong connections with the UCSB Quantum Foundry and the Solid State Lighting and Energy Electronics Center, demonstrating collaborative research efforts across multiple disciplines. The group actively investigates defects for quantum information science, loss mechanisms in light emitters, nitride semiconductors, halide perovskites, oxides, and hydrogen interactions with materials.

• Computational Materials Science
• Semiconductors
• Nitride Materials
• +7 more

Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award

• 3D Printing
• Nanotechnology
• Biomedical Engineering
• +4 more

Dr. Christopher M. Wolverton is a Professor of Materials Science and Engineering at Northwestern University , where he leads the Wolverton Research Group . His work focuses on computational materials science with applications in energy sustainability , particularly in batteries , hydrogen storage , and thermoelectrics . PhD in Physics from University of California, Berkeley BS in Physics (summa cum laude) from University of Texas, Austin His research leverages first-principles quantum mechanical simulations and machine learning to enable virtual materials synthesis before laboratory testing. The group specializes in hybrid computational methods integrating Density Functional Theory (DFT) , Monte Carlo simulations , and phase-field microstructural models . The article portfolio shows leadership in energy storage materials , with recent work on data-driven nanoparticle facet control , mixed-anion semiconductors , and machine learning-accelerated discovery . Publications span top journals including Nature Energy , Nature Materials , and Science . 2006 Ford Motor Company Technical Achievement Award 2005 Ford Patent & Publication Awards 2003 Ford Environmental/Physical Sciences Recognition As advisor to PhD candidates Zhenpeng Yao , Shiqiang Hao , and Shane Patel , he fosters interdisciplinary research connecting materials informatics with experimental validation . The group maintains active collaborations with Argonne National Lab and MIT/Harvard teams.

• Computational Materials Science
• Energy Storage Materials
• First-Principles Quantum Mechanics
• +7 more

Arunima Singh is an Assistant Professor in the Department of Physics at Arizona State University (ASU), with graduate faculty status in the Materials Science and Engineering Department. Her work focuses on computational materials discovery, leveraging first-principics simulations and data science to accelerate the design of materials for energy applications. She leads research at the Computational Materials Design Lab and co-leads a thrust at ULTRA, a DOE-Energy Frontier Research Center, and has received the 2023 Department of Energy Early Career Research Program Award. Ph.D., Cornell University (2014) B.Tech., Indian Institute of Technology Kharagpur (2009) Her research bridges materials science , surface science , and renewable energy , with a strong emphasis on 2D materials , nanostructures , and machine learning for materials design. She also explores electronic properties at material interfaces and phonon behavior at grain boundaries. The 2025–2023 articles highlight her expertise in heterostructures , wide bandgap materials , and data-driven discovery , with recurring themes in solar energy conversion , nanoengineering , and first-principles simulations . These works often involve machine learning and high-throughput workflows for materials optimization. Scientific Awards 2023 Department of Energy (DOE) Early Career Research Program Award She teaches courses such as Quantum Theory of Solids I , University Physics I: Mechanics , and research/dissertation sections (PHY 792, MSE 792, etc.). Her service includes expertise in computational modeling , solar materials , and nanoscience .

• Materials Science
• Computational Physics
• Surface Science
• +7 more

Dr. Xiaofeng Qian is an Associate Professor in the Department of Materials Science & Engineering at Texas A&M University, with joint appointments in Physics and Astronomy, and Electrical & Computer Engineering. His research focuses on materials theory , quantum materials design , and high-throughput computational discovery , particularly for 2D materials and energy applications . Educational Background: Ph.D., Nuclear Science and Engineering, Massachusetts Institute of Technology (2008) B.S., Engineering Physics, Tsinghua University (2001) Research spans first-principles electronic structure methods , nonlinear optical responses , and multiscale modeling of electronic, thermal, and ionic transport. Key areas include quantum spin Hall effect , ferroelectric switching , and machine learning for materials prediction . Notable Awards: Dean of Engineering Excellence Award (2024) Engineering Genesis Multidisciplinary Award (2024) AZZ Faculty Fellow (2021) NSF CAREER Award (2018) Manson Benedict Fellowship (2006) Actively recruiting PhD, MS, and UG researchers with backgrounds in physics, materials science, or computational methods. Collaborates extensively on hybrid AI-materials projects and topological device concepts .

• Materials Theory
• Quantum Materials
• 2D Materials
• +7 more

Regina Ragan is a Professor in the Department of Materials Science and Engineering at the Samueli School of Engineering, University of California, Irvine. Her research focuses on nanomaterials, self-assembly, and surface-enhanced Raman scattering (SERS) for applications in optical communication, energy systems, and biomedical diagnostics. Education: Ph.D. in Applied Physics, California Institute of Technology, 2002 M.S. in Applied Physics, California Institute of Technology, 1998 B.S. in Materials Science and Engineering, University of California, Los Angeles, 1996 Her work integrates scanning probe microscopy and first-principles calculations to study thermodynamic driving forces in self-assembly and structure-function relationships. Recent publications highlight applications in antimicrobial susceptibility testing, environmental monitoring, and plasmonic device fabrication. The Ragan group develops low-cost diagnostic tools using SERS for telemedicine applications. Current lab members include graduate students and postdoctoral researchers working on nanoscale systems from atomic to mesoscale. Scientific Awards: NSF CAREER Award for fundamental studies of biological/inorganic interfaces Research Trends: Recent articles show a focus on SERS-based diagnostics, plasmonic nanoantennas, machine learning-assisted spectral analysis, and scalable synthesis of 3D graphene architectures. Subfields span quantum plasmonics, stress-activated materials, and biofilm monitoring.

• Nanomaterials
• Self-Assembly
• Surface-Enhanced Raman Scattering (SERS)
• +4 more

William A. Goddard, III is the Charles and Mary Ferkel Professor of Chemistry, Materials Science, and Applied Physics at the California Institute of Technology. With a career spanning over five decades, he has held positions from Noyes Research Fellow (1964–66) to his current professorship since 2001. His educational background includes a B.S. from UCLA (1960) and a Ph.D. from Caltech (1965). Quantum chemistry and first-principles simulations Multiscale modeling (QM→MD→mesoscale) Catalysis and protein structure prediction Nanotechnology and bionanotechnology Energy storage (batteries, supercapacitors) Recent publications emphasize applications in metal-organic frameworks , electrocatalysis , and space manufacturing , reflecting his interdisciplinary approach. His work on G-protein coupled receptors and Li-S batteries demonstrates methodological innovation through quantum mechanics and machine learning . Horizon Prize , Royal Society of Chemistry Over 1548 total publications (1967–2022) As Director of Caltech's Material and Process Simulation Center , he leads development of software like ReaxFF for reactive dynamics. He teaches Ch 120 ab (Nature of the Chemical Bond) and Ch 121 ab (Atomic-Level Simulations), emphasizing hands-on computational applications for experimentalists and theorists.

• Quantum Chemistry
• Molecular Dynamics
• Statistical Physics
• +7 more

Dr. Huaxiang Fu is a Professor in the Department of Physics at the University of Arkansas' College of Arts & Sciences, where he has been since 2002. His research focuses on first-principles computational studies of bulk and nanomaterials, particularly ferroelectric materials, quantum dots, and organic-inorganic hybrid materials. Education: Ph.D., Fudan University, China (1994) Postdoctoral Associate, National Renewable Energy Lab, Colorado (1995–1998) Postdoctoral Associate, Geophysical Lab, Carnegie Institution of Washington, DC (1999–2000) Dr. Fu's research spans five key areas: phase transitions in low-dimensional ferroelectrics, finite electric fields in solids, defect physics in ferroelectrics, hyperferroelectricity, and organic-inorganic hybrid materials. His work often employs density functional theory and computational modeling to explore polarization behavior, strain effects, and electronic structure. His recent publications highlight trends in ferroelectricity under strain , defect-induced polarization changes , and spin-orbit coupling effects . Notable collaborations include researchers at Carnegie Institution and University of Arkansas. Teaching: Undergraduate: General Physics, Statics, Mechanics of Materials, University Physics II, Electromagnetism, Fortran Programming, Computational Physics in C++, Physics for Architects II, Thermal Physics. Graduate: Statistical Mechanics, Solid State Physics, Optical Properties of Materials, Advanced Solid State Physics, Physics at the Nanoscale, Quantum Mechanics, Mathematical Methods. Research Contributions: 2004: Nature publication on ferroelectric nanodisks 2000: Nature paper on polarization rotation in piezoelectrics 2013: Pioneering work on electromechanical angular momentum coupling

• Ferroelectric Materials
• Quantum Dots
• Density Functional Theory
• +4 more

Marco Bernardi is a Professor of Applied Physics, Physics and Materials Science at the California Institute of Technology (Caltech). His research focuses on theoretical and computational materials physics , developing first-principles methods to investigate electron transport, ultrafast dynamics, and light-matter interactions in materials. His work has applications in electronics, optoelectronics, ultrafast spectroscopy, energy technologies, and quantum devices. Education : Ph.D. in Materials Science from MIT (2013), M.S. from University of Rome Tor Vergata (2008), B.S. from University of Rome La Sapienza (2004). Research Interests : Electron-phonon interactions, polarons, spin relaxation and decoherence, nonequilibrium electron dynamics, quantum materials, and software development for materials simulations ( PERTURBO code). Scientific Awards : NSF CAREER Award (2018) AFOSR Young Investigator Award (2017) Psi-K Volker Heine Young Investigator Award (2015) Intel Ph.D. Fellowship (2013) Franco Strazzabosco Award (2020) Teaching : Offers graduate courses at Caltech including Structure and Bonding in Materials (MS 131) , Computational Solid State Physics (APh/MS 256) , and Introduction to Computational Methods (APh/MS 141) . Group Members : Mentors current graduate students and postdocs in developing advanced computational techniques for materials research, with former advisees now in academic and industry positions.

• Theoretical Materials Physics
• Computational Materials Science
• Electron Transport
• +7 more

James Chelikowsky is Professor and W. A. "Tex" Moncrief, Jr. Chair in Computational Materials at The University of Texas at Austin's Oden Institute for Computational Engineering and Sciences (ICES). His research pioneers quantum mechanical simulations for materials design and discovery across multiple domains. His educational background includes: B.S. in Physics from Kansas State University (1970) Ph.D. in Physics from University of California at Berkeley (1975) Chelikowsky's research spans computational materials science with focus on quantum models for functionalized nanostructures, simulations of liquids and crystal growth, "green magnetism" in dilute magnetic semiconductors, oxide defects, materials informatics, and high-performance electronic structure algorithms. His work bridges theoretical physics with practical materials engineering to solve complex problems in energy and electronics. Analysis of his 2012-2022 publications reveals evolving focus from fundamental quantum simulations toward machine learning integration for magnetic materials discovery, while maintaining strong contributions to two-dimensional materials and interfacial phenomena. Key trends include increased computational complexity and interdisciplinary collaboration with experimental groups. His distinguished honors include: Feynman Prize for Theory (2022) FMD John Bardeen Award (2021) Aneesur Rahman Prize (2013) Multiple society fellowships (MRS, AAAS, APS) Guggenheim Fellowship (1996) As leader of an active research group, Chelikowsky mentors graduate students in computational methods development. While specific grant details aren't provided, his sustained publication record and named chair position indicate substantial ongoing research funding. His group maintains strong industry and national laboratory collaborations evident in co-authorship patterns. The Computational Materials Group operates through ICES with research facilities supporting high-performance computing for materials simulations. Current projects focus on machine learning-guided materials discovery and quantum mechanical modeling of novel electronic materials.

• Computational Materials Science
• Quantum Mechanical Simulations
• Magnetic Materials
• +4 more

Gyeong Hwang is a Matthew Van Winkle Regents Professor of Chemical Engineering at The University of Texas at Austin. He leads the Hwang Research Group focused on computational materials discovery and design for energy and electronic applications. His work emphasizes multiscale modeling of nanostructured materials, with applications in energy storage/conversion, carbon capture, and semiconductor processing. Educational Qualifications: Ph.D., Chemical Engineering, California Institute of Technology (1999) M.S., Applied Physics, California Institute of Technology (1998) M.S., Chemical Engineering, Seoul National University (1993) B.S., Chemical Engineering, Seoul National University (1991) Research Interests: Hwang's research integrates first-principles modeling with experimental validation to address challenges in: - Surface chemistry and interfacial reactions - Nanostructured materials synthesis - Electrochemical device fabrication - CO₂ capture mechanisms His group develops computational tools for predicting material behaviors at atomic and continuum scales. Recent Publications Trends: Publications (2023-2025) focus on: - Solid-state battery interfaces - Plasma-enhanced material deposition - Ionic liquid interactions - Thermal/spatial transport phenomena - Electrochemical reaction mechanisms Awards: NSF CAREER Award (2005) Electrochemical Society's F.M. Becket Memorial Award (1999) Korean Chemical Engineering Service Award (2010) Advising & Grants: Leads interdisciplinary research funded by NSF, industry partnerships, and regents' endowments. Active in graduate student training through courses like ChE 379 (Molecular Simulation) and ChE 348 (Numerical Methods). Labs/Teams: The Hwang Research Group operates state-of-the-art computational facilities for quantum mechanics simulations and multiscale modeling. Collaborates with experimental groups globally on materials prototyping.

• Multiscale modeling
• Nanomaterials synthesis
• Energy storage systems
• +4 more

Davide Donadio is a Professor of Chemistry at the University of California, Davis. His research focuses on molecular modeling and simulations of materials, particularly in non-equilibrium processes, thermal transport, and nanostructure assembly. He leads the Naotheory Group, which develops predictive multiscale models for energy-related materials. Education : Habilitation in Materials Science, Italian Ministry for University and Research (2013) Ph.D. in Materials Science, University of Milano (2003) M.S. in Physics, University of Milano (1998) Research Interests : His work spans molecular-level understanding of energy conversion, thermal management, and nanostructure formation. Key areas include phononics, thermoelectrics, and interfacial phenomena in materials like ice surfaces, semiconductors, and clathrates. He employs machine learning and first-principles methods to bridge simulation and experiment. Awards : UC Davis Hellman Fellow (2017–2018) Young Scientist Award, Italian Institute for the Physics of Matter (1998) Grants & Labs : His funding and collaborations drive advancements in nanostructured materials and computational tools like PLUMED tutorials. The Naotheory Group actively publishes in high-impact journals and collaborates internationally on thermal transport and materials design.

• Molecular Modelling
• Materials Science
• Thermal Transport
• +4 more

Dr. Alex Mironenko is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign. His research focuses on developing quantum mechanical methods to predict catalytic behaviors for renewable energy and chemical production. He leads the Mironenko Lab, which emphasizes computational models for heterogeneous catalysis, reactive force fields, and nanozyme design. Education: PhD in Chemical Engineering, University of Delaware (2018) Kadanoff-Rice Postdoctoral Scholar, University of Chicago (2018-2020) MS in Chemical Engineering, University of Kansas (2012) Diploma of Engineer, Omsk F.M. Dostoevsky State University, Russia (2009) Research Interests: Computational heterogeneous catalysis Reactive force fields derived from first principles Low-dimensional metal oxide catalysts Nanozymes and biomimetic catalysis Selective C-C coupling for CO₂ valorization Improving density functional theory accuracy Awards: ACS Petroleum Research Fund Doctoral Investigator Award (2021) Allan P. Colburn Outstanding Dissertation Prize (2019) Kadanoff-Rice Postdoctoral Fellowship (2018-2020) Advising and Grants: Advised PhD student Neil Tran (publication on methanol carbonylation mechanisms) Funded by NSF, ACS, and industry partnerships Labs/Teams: Mironenko Virtual Catalysis and Quantum Chemistry Lab Collaborations with institutions like University of Chicago and industry partners

• Catalysis
• Computational Chemistry
• Quantum Mechanics
• +7 more

Xifan Wu is a Professor of Physics at Temple University, specializing in computational methods and materials science. His research focuses on first-principles computational approaches, particularly exploring the locality of Wannier orbitals to address physical problems in solids and liquids. Key interests include superlattice design and applications of order-N exact exchange functionals like PBE0 and GW quasi-particle approximations. He has authored numerous high-impact publications in journals such as Physical Review Letters and Physical Review B , covering topics like ferroelectric superlattices, X-ray absorption spectroscopy, and the dielectric properties of electrolyte solutions. His work bridges quantum mechanical models with machine learning potentials, advancing large-scale simulations of complex materials. Education/Background: Not explicitly detailed in the provided text. Grants/Awards: No specific awards listed, but his research is supported by Temple University’s Center for the Computational Design of Functional Layered Materials (CCDM). Labs/Teams: Collaborates with teams focused on computational design and materials modeling, possibly through Temple’s physics department and affiliated research centers. His recent work explores molecular-scale insights into electrical double layers at oxide-electrolyte interfaces and the impact of ions on X-ray spectra, demonstrating expertise in linking theoretical models with experimental phenomena.

• Computational Physics
• Materials Science
• Condensed Matter Physics
• +3 more

Geoffroy Hautier serves as Adjunct Associate Professor of Engineering at Dartmouth College's Thayer School of Engineering within the Physics and Astronomy Department. His research bridges computational materials science with practical energy applications through high-throughput methodologies and machine learning integration. Previously holding positions at MIT and ULB, he maintains active collaborations across international research networks including the psi-k society. His research expertise spans computational materials design with emphasis on ab initio and high-throughput computing approaches. Key focus areas include opto-electronic properties of materials, transparent conducting oxides, thermoelectrics, photovoltaics, and high entropy alloys for energy applications. His group develops advanced computational frameworks for materials discovery, particularly targeting energy production and storage solutions through quantum mechanical simulations. Analysis of recent publications reveals strong trends in quantum materials discovery (2022-2024), sustainable magnet development (2023), and hydrogen storage technologies (2024). His work consistently integrates machine learning with first-principles calculations to accelerate materials design cycles across photovoltaics, quantum information science, and sustainable energy systems. Scientific recognition includes: Chemistry of Materials Reviewer Excellence Award (2018, 2019) Finalist for Rising Star in Computational Materials Science (2018) Marie Curie Fellowship (2012) As group leader, Hautier mentors multiple PhD students and postdoctoral researchers while directing projects funded by DOE and other agencies. His research portfolio includes significant grants for quantum materials ($2.7M DOE grant), sustainable magnets, and hydrogen storage frameworks. The Hautier Research Group maintains active collaborations with national laboratories and industry partners through the Materials Project initiative. The group operates within Dartmouth's advanced computational infrastructure, focusing on quantum defect engineering for silicon photonics, 2D material design for electrocatalysis, and rare-earth-free permanent magnet development. Current efforts emphasize scalable quantum technologies and decarbonization pathways through advanced materials discovery.

• Computational Materials Design
• Ab Initio Computing
• High-Throughput Computing
• +8 more