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Peihong ZhangView profile

Professor

• Condensed Matter Theory
• Ab Initio Calculations
• Materials Design
• +7 more

Peihong Zhang is a Professor in the Department of Physics at the University at Buffalo, SUNY. He holds a PhD in Condensed Matter Physics from Pennsylvania State University (2001) and has held academic positions since 2005, advancing from Assistant Professor (2005-2011) to Associate Professor (2011-2016) before becoming a full Professor in 2016. His research focuses on computational materials design, ab initio electronic structure calculations, and the study of nanostructured materials. Key areas include quasiparticle properties, excitonic effects, and phase transitions in 2D materials. He has contributed to the development of efficient GW methods for large-scale simulations and has explored applications in energy materials, optoelectronics, and defect physics. Education : B.S., Physics, Xiamen University, China (1993) M.S., Atomic & Molecular Physics, Institute of Physics, Chinese Academy of Sciences (1996) Ph.D., Condensed Matter Physics, Pennsylvania State University (2001) Ph.D. minor, High-Performance Computing, Penn State (2001) Research Interests : Zhang’s work integrates theoretical and computational methods to predict and design novel materials. His team investigates electronic and structural properties using advanced techniques like GW approximations and LSDA+U methods, with applications to semiconductors, MXenes, and layered materials. Recent studies highlight excitonic effects in monolayers (e.g., C₃N and C₃B), strain-induced phase transitions in SnSe, and machine-learning approaches to materials discovery. His research emphasizes bridging fundamental theory with practical applications in energy and optoelectronics. Awards & Honors : NSF CAREER Award (2010) American Chemical Society Doctoral New Investigator Award (2009) Xerox Award for Outstanding PhD Thesis in Materials (2001) Grants & Collaborations : Zhang has received funding from NSF, DOE, and the Petroleum Research Fund. His collaborations include projects on materials informatics, thermoelectric materials, and defect engineering. His lab actively contributes to open-source computational tools for electronic structure analysis. Labs & Teams : Zhang leads a research group focused on computational materials science. His team’s work is housed in the Department of Physics at UB, with affiliations to the RENEW Institute and the Center for Materials Informatics.

Christian Simonsen FiskerView profile

Part-Time Lecturer

• Materials Science
• Optics
• Renewable Energy
• +4 more

Christian Simonsen Fisker is a Part-time Lecturer at the Department of Materials and Production within the Faculty of Engineering and Science at Aalborg University. His research spans interdisciplinary fields including materials science, optics, and social dynamics. He holds a PhD in Architecture and Media Technology (2011), focusing on mobility patterns among seniors in car-centric cities. Expertise: Thin-film solar cells, nanostructuring, and senior mobility case studies Part-time academic with active publication record from 2007-2014 Key research interests include: Optimization of photovoltaic materials through nanoimprinting and FDTD simulations Social implications of mobility loss among aging populations Material defect modeling using advanced computational methods Publications demonstrate focus on: 6 articles on solar cell technology (2011-2014) 1 PhD thesis analyzing urban mobility challenges No awards listed but maintains active research output across multiple disciplinary areas.

Matthew GieslerView profile

Researcher

• Computational Astrophysics
• Theoretical Astrophysics
• Numerical Relativity
• +3 more

Matthew Giesler is a postdoctoral scholar in the TAPIR group at the California Institute of Technology (Caltech), specializing in computational and theoretical astrophysics. His research focuses on numerical relativity, particularly using the Spectral Einstein Code (SpEC) as part of the Simulating eXtreme Spacetimes (SXS) collaboration to study black holes and gravitational waves. He contributes to large-scale simulations of binary black hole mergers and neutron star collisions, emphasizing high-precision modeling and waveform analysis. His work involves advancing numerical methods like discontinuous Galerkin techniques and investigating topics such as black hole ringdown overtones, small mass-ratio corrections, and gravitational wave parameter estimation. Giesler collaborates extensively with international teams including LIGO, Virgo, and KAGRA to analyze observational data from gravitational wave detectors. Key projects include the SXS Collaboration's catalogs of binary black hole simulations and studies of extreme mass ratio systems. His research bridges theoretical predictions with observational data, contributing to tests of general relativity and cosmological parameter constraints. Despite no listed formal awards, his contributions to gravitational wave astronomy are highlighted through high-impact publications and collaborative efforts in multi-messenger astrophysics. His work supports the development of SpECTRE, a multi-physics simulation framework, and informs future gravitational wave detectors' data analysis methods.

• Multiscale Modeling
• Machine Learning
• Surface Science
• +4 more

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.

Jefferson BatesView profile

Associate Professor

• Theoretical Chemistry
• Quantum Chemistry
• Computational Chemistry
• +3 more

Dr. Jefferson Bates serves as Associate Professor in the Department of Chemistry and Fermentation Sciences at Appalachian State University, teaching general and physical chemistry since joining in 2017. His academic trajectory includes postdoctoral research at Temple University (focusing on solid-state chemistry) and Northwestern University. His educational background includes: Ph.D. in Chemical and Material Physics, University of California Irvine (Mentor: Dr. Filipp Furche) Research centers on theoretical and computational chemistry with expertise in density functional theory (DFT) , time-dependent DFT , and many-body perturbation methods . Key contributions involve developing quantum mechanical approaches for predicting UV/Vis spectra and reaction energies, applied to novel lanthanide species and extended metal atom chain (EMAC) complexes. Current work investigates metal-metal bonding and single-molecule magnet phenomena. Recent publications (2019-2022) reveal consistent advancement in electronic structure methodologies, particularly in addressing ground state/excitation energy challenges through TDDFT and GW approximations. Applications span alloy systems (Au-Cu), fluorescent nerve agent sensors, and molecular magnetism, demonstrating interdisciplinary impact across materials science and analytical chemistry. Dr. Bates leads an NSF RUI-funded collaborative project with Dr. Gary Guillet at Furman University, where his computational group characterizes EMAC complexes through electronic structure calculations. This work bridges molecular structure prediction, UV/Vis spectrum modeling, and metal-metal bonding analysis to explain single-molecule magnet behavior. His research operates within a collaborative framework connecting Appalachian State's computational team with Furman University's experimental synthesis group, creating an integrated pipeline for discovering and characterizing novel magnetic materials through combined theoretical-experimental approaches.