Find Academic Supervisors

• Density Functional Theory
• Magnetism
• Chemical Bonding
• +7 more

Olle Eriksson is a Professor in the Department of Physics and Astronomy at Uppsala University, specifically affiliated with the Materials Theory division. His research focuses on theoretical and computational approaches to understanding magnetic materials and their properties. His primary research interests include first principles calculations of bulk materials and surfaces, with particular emphasis on magnetism and chemical bonding. His methodological expertise spans full-potential implementations of density functional theory, dynamical mean-field theory, and self-interaction correction. He also conducts calculations of finite temperature magnetism using Monte Carlo simulations and atomistic spin-dynamics simulations, as well as investigations into lattice dynamics and finite temperature effects on phase stability. Professor Eriksson's recent work demonstrates a strong focus on magnetocaloric materials for magnetic refrigeration applications, two-dimensional magnetic materials including van der Waals magnets, topological magnetic textures such as skyrmions, and computational methods for improving density functional theory. His research has significant implications for energy-efficient cooling technologies, next-generation spintronic devices, and fundamental understanding of quantum magnetic phenomena. Materials Science : Magnetocaloric materials, battery materials, 2D materials Computational Physics : Density functional theory, Monte Carlo simulations, spin dynamics Magnetism : Topological textures, chiral magnets, ultrafast dynamics His extensive publication record shows consistent contributions to high-impact journals across physics and materials science, with a notable increase in interdisciplinary work connecting computational physics with materials design for energy applications.

• Computational Materials Science
• Condensed Matter Physics
• Nanomaterials
• +6 more

Paul Erhart is a Professor in Condensed Matter and Materials Theory at the Department of Physics, Chalmers University. He received his PhD from Technische Universität Darmstadt in 2006, followed by postdoctoral and staff positions at Lawrence Livermore National Laboratory from 2007, before joining Chalmers in 2011. His research bridges computational physics, materials science, and machine learning to tackle fundamental problems in materials design and characterization. Dr. Erhart's research focuses on computational materials science with particular emphasis on condensed matter physics, nanomaterials, and quantum materials. His work spans from developing computational methods like machine-learned potentials (GPUMD, neuroevolution potentials) to studying fundamental phenomena in perovskites, 2D materials, thermal transport, and plasmonics. He has pioneered approaches connecting simulation with experimental techniques through correlation functions and has made significant contributions to understanding phase transitions, defect physics, and electronic structure in complex materials systems. Analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional computational physics methods. His work increasingly focuses on developing and applying neuroevolution potentials to study thermal properties, phase transitions, and optical phenomena in materials. There's also a clear emphasis on connecting computational results with experimental observations, particularly in neutron scattering, Raman spectroscopy, and plasmonic sensing applications. His research spans fundamental materials physics to applied areas like hydrogen sensing and sustainable materials development. Dr. Erhart has contributed to numerous software packages essential to the computational materials science community, including WulffPack for Wulff constructions, Dynasor for extracting dynamical structure factors, calorine for neuroevolution potential models, and ICET for alloy cluster expansions. His collaborative work spans multiple institutions and disciplines, reflecting the interdisciplinary nature of modern materials research. His contributions to understanding perovskite materials, thermal transport phenomena, and plasmonic systems have established him as a leading researcher in computational materials science.

• Theoretical Condensed Matter Physics
• Ultrafast Magnetism
• Orbitronics
• +7 more

Peter Oppeneer is a Professor in the Materials Theory group within the Department of Physics and Astronomy at Uppsala University, Sweden. His research program focuses on theoretical condensed matter physics with emphasis on ultrafast phenomena and magnetic materials. His research interests span femtosecond magnetism, ultrafast spin and orbital currents, out-of-equilibrium magnon and phonon dynamics, unconventional superconductivity, multipolar and hidden order parameters, and orbitronics. The group develops both analytical theories and numerical simulation codes, combining ab initio methods with model Hamiltonian approaches. Key research thrusts include ultrafast demagnetization mechanisms, spin-crossover materials, molecular spintronics, and topological quantum states in magnetic materials. Analysis of recent publications reveals strong focus on altermagnetism, terahertz spin dynamics, Dirac semimetals, and laser-induced phase transitions. The group's work bridges fundamental quantum theory with applications in next-generation spintronic devices and ultrafast magnetic switching technologies. Collaborative activities include work with experimental groups on ultrafast spectroscopy, X-ray magnetic circular dichroism, and terahertz emission studies. The group maintains active collaborations across Europe and internationally, particularly in the areas of femtosecond magnetism and topological materials. Research infrastructure includes development of specialized computational codes for Eliashberg theory, dynamical mean field theory, and ultrafast spin dynamics simulations. The group contributes to major international facilities including synchrotron and free-electron laser sources for time-resolved studies.

• Thermodynamics
• Diffusion
• Phase Transformations
• +3 more

Powder Metallurgy (MH2100) and has expertise in computational materials science. His research emphasizes predictive modeling of material behavior, including precipitation kinetics, sintering processes, and coating interactions. Notable areas include phase field modeling of discontinuous precipitation, spinodal decomposition in Fe-Cr alloys, and high-entropy alloy design. His studies bridge experimental data with computational tools like the YAPFI phase-field framework. Key themes in his publications span cemented carbides, Co-based entropic alloys, and tool wear mechanisms. He combines CALPHAD thermodynamic modeling with first-principles calculations to address challenges in materials processing and corrosion resistance. His work often addresses industrial applications, such as optimizing machining tools and additive-manufactured superalloys.

Igor Di MarcoView profile

Researcher

• Computational Physics
• Condensed Matter Theory
• Strongly Correlated Materials
• +5 more

Igor Di Marco is a Researcher at Uppsala University's Department of Physics and Astronomy, specializing in Materials Theory. He has maintained continuous research activity at Uppsala since 2009, initially as a postdoctoral fellow and subsequently as a researcher, with a temporary leave in 2017 to lead a group at the Asia-Pacific Center for Theoretical Physics in South Korea. Dr. Di Marco earned his PhD in condensed matter theory from Radboud University of Nijmegen in 2009. His academic trajectory has focused on computational approaches to understanding complex quantum materials, particularly those exhibiting strong electron correlations. His research centers on computational physics and condensed matter theory , with emphasis on developing methods to determine electronic and magnetic properties of strongly correlated materials . Dr. Di Marco is one of the principal developers of the all-electron DFT code RSPt (a Sweden-USA-France collaboration), which utilizes the full-potential linearized muffin-tin orbitals method. His expertise spans density-functional theory (DFT) , dynamical mean-field theory (DMFT) , and their integration (DFT+DMFT). Current research extends to X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS) . Analysis of his recent publications reveals a consistent focus on electronic correlations in quantum materials, particularly in kagome metals, van der Waals magnets, and complex alloys. His work bridges theoretical method development with practical materials applications, frequently examining magnetic properties and electronic structure calculations across diverse material systems. Dr. Di Marco has made significant contributions to computational methodologies for strongly correlated electron systems, including the development of the DFT+DMFT framework within RSPt featuring full self-consistency over electron density and self-energy. His research projects have addressed magnetic properties of transition metals, excitation spectra of metal oxides, theoretical frameworks for lanthanides, and prediction of novel 2D materials.

• Condensed Matter Physics
• Materials Science
• Computational Physics
• +4 more

Mattias Klintenberg is a Professor in the Department of Physics and Astronomy at Uppsala University, Sweden, specializing in computational materials theory. His research integrates advanced simulation techniques to address fundamental questions in condensed matter systems and material properties. His core expertise spans Condensed Matter Physics and Materials Science , with specific focus on: Electronic structure calculations for semiconductors and novel materials Defect physics in interfaces and bulk systems Two-dimensional material characterization Electron-phonon coupling models X-ray spectroscopy data interpretation Computational material discovery through data mining Analysis of his 2013-2019 publications reveals a cohesive research trajectory centered on atomic-scale material behavior. Key themes include radiation damage modeling in nuclear materials, defect engineering in semiconductors (particularly CdTe), and methodological advances in molecular dynamics for electron-phonon interactions. His work consistently bridges theoretical computation with experimental validation, especially in spectroscopy and interface science. No scientific awards were documented in the provided information. Details regarding student supervision, grant funding, or laboratory infrastructure were not specified in the source materials.

• Materials Chemistry
• Battery Technology
• Lithium-ion Batteries
• +5 more

Daniel Brandell is a Professor in Materials Chemistry at Uppsala University, working within the Department of Chemistry - Ångström Laboratory, specifically in the Structural Chemistry division. He serves as the responsible professor for the Structural Chemistry programme and is a key researcher within the Ångström Advanced Battery Centre. Professor Brandell's research focuses on advanced battery technologies, with particular emphasis on: Lithium-ion and solid-state battery systems Polymer and ceramic electrolytes Thermal management and safety of battery systems Computational modeling of ion transport mechanisms Next-generation battery materials for electromobility applications His recent publication record demonstrates a strong trend toward understanding fundamental mechanisms in battery operation, with significant focus on thermal runaway phenomena, ion transport in novel electrolyte systems, and the development of safer, more efficient solid-state battery technologies. Much of his work combines experimental approaches with computational modeling to gain deeper insights into battery chemistry and physics at the molecular level. His research spans from fundamental materials science to practical safety testing methodologies. Professor Brandell actively collaborates with researchers across multiple institutions and contributes to advancing battery technology for sustainable energy applications. His work has significant implications for the development of safer, higher-capacity batteries for electric vehicles and grid storage solutions, addressing critical challenges in energy storage technology. His research group appears to collaborate extensively with other researchers at Uppsala University and internationally, as evidenced by the co-authorship patterns in his publications.

• Nuclear Materials
• Radiation Damage Physics
• Computational Materials Science
• +4 more

Pär Olsson is a Professor in the Department of Nuclear Science & Engineering at KTH Royal Institute of Technology. His research focuses on computational and experimental studies of radiation damage in nuclear materials, with particular emphasis on understanding defect dynamics, microstructural evolution under irradiation, and the behavior of advanced nuclear fuels. He leads courses such as Multiscale Modeling of Nuclear Materials and Radiation Damage Physics, emphasizing both theoretical and practical aspects of materials science in nuclear contexts. His research interests include the development of advanced accident-tolerant fuels (e.g., UN-UO2 composites), the computational modeling of radiation effects in metals like Fe and W, and the interplay between solute atoms and defects in irradiated materials. His work combines first-principles calculations, kinetic Monte Carlo simulations, and experimental validation to address challenges in nuclear energy systems. Notable contributions include studies on fission product solubility in nuclear fuels, oxygen’s role in tungsten defect evolution, and the thermal performance of UN-based composites. His team’s projects, such as the M4F initiative (Multiscale Modelling for Fusion and Fission Materials), aim to bridge atomistic and continuum-scale models for material design. Pär Olsson collaborates extensively with international institutions and contributes to nuclear materials education through course coordination and supervision of graduate studies in physics and materials science.

• Industry 4.0
• Resilience Engineering
• Sustainability in Production Systems
• +3 more

Arpita Chari is a Research Fellow at Chalmers University of Technology, specializing in Virtual and Digital Production Systems. Her work bridges Industry 4.0, Resilience Engineering, and Sustainability in Production Systems, focusing on integrating digital technologies to enhance resource efficiency and enable lean circular manufacturing. Her research explores the implementation of resilient and sustainable practices in manufacturing, emphasizing dynamic capabilities, digital platforms, and supply chain optimization. Key projects include the Digitala Stambanan initiative and the Produktion2030 strategic innovation program, which address sustainability transitions and systemic resilience. 2024 Highlights: Analyzed dynamic capabilities for resilience-sustainability integration, characterized battery lifecycle challenges, and modeled risk prioritization in supply chains. 2023 Themes: Digital platform adoption, battery production systems, and value chain sustainability in the Digitala Stambanan project. 2022–2021 Foundations: Developed frameworks for green manufacturing, circular supply chains, and stakeholder-driven sustainability in textiles.

Johan KlarbringView profile

Assistant Professor

• Material Science
• Energy Materials
• Computational Physics
• +6 more

Johan Klarbring is an Assistant Professor in the Department of Physics, Chemistry and Biology (IFM) at Linköping University. His research focuses on theoretical material science using ab initio computational methods to study energy materials such as solid oxide fuel cells, batteries, solar cells, and thermoelectric devices. He combines quantum mechanics and statistical physics to analyze phase stabilities and electronic properties of dynamically disordered solids. His work emphasizes computational approaches to understand material behavior at finite temperatures, including defect formation, ionic transport, and anharmonic effects. Collaborations involve international teams and cutting-edge facilities like supercomputers for large-scale simulations. Key research themes include perovskite materials, machine learning force fields, and thermoelectric properties. Notable contributions address dynamic nanodomains in perovskites and vacancy-driven ion conduction mechanisms. His group (Ab initio methods and energy materials (TEAM)) explores eco-friendly applications of disordered solid materials. Recent projects include studies on lead-free perovskites, superionic transitions, and magnetism in halide double perovskites. He has contributed to over 30 peer-reviewed articles, with high-impact work in Nature Nanotechnology and Chemical Science .

• Density Functional Theory
• Van der Waals Interactions
• Molecular Binding
• +4 more

Per Hyldgaard is a Professor at the Quantum Component Physics department of Chalmers University of Technology . His research focuses on developing and applying van der Waals density functionals (vdW-DF) to study molecular binding, nanomaterials, and condensed matter systems. Key areas include nonlocal correlation effects, electronic structure analysis, and material properties under extreme conditions. Research Interests: Hybrids of van der Waals functionals, quantum materials, adsorption mechanisms, and computational materials science. His work bridges theoretical frameworks with experimental validation, addressing challenges in predicting CO₂ adsorption, metallic surface interactions, and polymeric systems. Recent Projects: 2019–2022: VR-funded study on charge transfer in soft materials. 2015–2018: Consistent vdW-DF studies for molecular systems. 2014–2019: High-speed graphene-based electronics collaboration. Publications: Over 100 peer-reviewed articles, including foundational work on vdW-DF methods and applications in nanotubes, layered materials, and catalytic systems. Recent trends emphasize hybrid functional optimization and energy scaling laws in nanostructures. Grants & Teams: Collaborations with EU and SSF on bio-inspired molecular networks and high-speed electronics. Active in developing libvdwxc , a software library for vdW-DF functionals.

Heike HerperView profile

Researcher

• Magnetic Materials
• Density Functional Theory
• Computational Materials Science
• +3 more

Heike Herper is a Researcher at the Department of Physics and Astronomy (Materials Theory) at Uppsala University . Her work focuses on computational studies of magnetic materials, particularly for permanent magnet applications and magnetocaloric systems, within the NOVAMAG EU project . Affiliation: Uppsala University, Materials Theory Email: heike.herper@physics.uu.se Research involves Density Functional Theory (DFT) calculations combined with Monte Carlo simulations to model finite temperature effects. Key projects include identifying non-hazardous permanent magnet alternatives, studying rare-earth materials, and developing electronic structure databases. Recent publications highlight her expertise in analyzing: Pressure-induced stacking faults in Gd (2024) Giant magnetocaloric effects in Mn,Fe NiSi (2024) Rare-earth-free magnets via high-throughput screening (2023) Magnetic phase diagrams of Heusler alloys (2022) Electronic structure of transition metal complexes (2020)

• Theoretical Physics
• Nuclear Physics
• Particle Physics
• +7 more

Christian Forssén is a Professor in theoretical physics at Chalmers University of Technology, affiliated with the Department of Physics and the Division of Subatomic, High Energy and Plasma Physics. His research focuses on theoretical nuclear and particle physics, employing advanced computational tools like Bayesian methods and machine learning to study low-energy effective field theories, nuclear forces, and astrophysical connections. He is an elected Fellow of the American Physical Society and a member of The Royal Society of Arts and Sciences in Gothenburg. Key research interests include nuclear many-body systems, symmetry energy in neutron-rich matter, and precision calculations of nuclear observables. His work bridges fundamental symmetries and astrophysical phenomena, such as neutron star properties and dark matter interactions. Recent studies emphasize Bayesian parameter estimation in chiral effective field theory and emulation techniques for large-scale ab initio calculations. Publications highlight breakthroughs in neutron skin predictions for 208Pb, first observations of exotic nuclei like 28O, and rigorous constraints on three-nucleon forces. Awards include recognition for contributions to nuclear theory and computational methods. Ongoing projects involve collaborations on dark matter detection and precision measurements of neutron halo nuclei.

Björn AllingView profile

Professor

• Theory of Disordered Materials
• Theoretical Physics
• Materials Science
• +12 more

Björn Alling is a Professor and Head of Unit at Linköping University, where he leads the Theory of Disordered Materials research group within the Department of Physics, Chemistry and Biology (IFM). He also serves as Director of the National Supercomputer Centre (NSC), a national facility providing high-performance computing resources for Swedish and European research. His research focuses on the theoretical modeling of materials under extreme conditions, particularly iron and steels, incorporating magnetic disorder, atomic vibrations, and defects. He employs advanced computational methods such as first-principles calculations, density functional theory, and machine learning to predict material properties and behavior. His recent publications span topics including high-entropy alloys for CO2 conversion, battery materials, catalytic systems for hydrogen and oxygen evolution, and the fundamental magnetic and mechanical properties of metals. These works reflect a strong trend toward sustainable energy materials and computational acceleration of materials discovery. He has supervised several Master’s and PhD students, including Davide Gambino, Marian Arale Brännvall, and Amanda Ehn, whose thesis work has contributed directly to published research. His group collaborates internationally, including with researchers at Université Paris-Saclay. He leads a research unit focused on dynamically disordered solids and is actively involved in national and European supercomputing initiatives, such as the deployment of the Arrhenius supercomputer. His leadership at NSC aims to expand access to computational resources and strengthen Sweden’s role in high-performance computing.

• Computational Materials Science
• Ab Initio Methods
• Condensed Matter Physics
• +7 more

Sergey Simak is a Professor and Head of Unit at Linköping University, affiliated with the Department of Physics, Chemistry and Biology (IFM), specifically within the Theoretical Physics (TEOFY) and Theory and Modelling divisions. His research focuses on computational and theoretical approaches to understanding advanced functional materials. His research interests lie at the intersection of computational materials science and theoretical physics , particularly in ab initio methods , phase transitions , high-pressure materials , and energy-related functional materials . He develops and applies advanced modeling techniques to predict and understand the behavior of complex solid-state systems, including dynamically disordered materials and high-temperature alloys. The recent publications highlight a strong trend in using first-principles simulations combined with machine learning to enhance materials thermodynamics and discover novel compounds under extreme conditions. His work spans from fundamental magnetic phase diagrams in iron to the synthesis of hydrogen-rich silicates and optimization of perovskite optoelectronic devices, reflecting a broad yet cohesive research program in energy materials and sustainable technologies . Scientific recognition includes: Major research funding recipient from the Swedish Research Council (nearly SEK 97 million, 2019) Sergey Simak leads a research unit focused on theory and modeling, contributing to national and international collaborations. He has secured significant grants supporting computational infrastructure and team development. While formal advisees are not listed, his leadership role and publication record suggest active mentorship within the research group. He is part of the Theory and Modelling research environment at IFM, which develops mathematical models and computational methods to understand natural phenomena, particularly in materials science and condensed matter physics.