Invited Talks 2021 of the
Emiritus Group Prof. Scheffler

2022 | 2021 | 2020 | 2019

Talk (70)

2021
Talk
Carbogno, Christian et al.: The Role of Anharmonic Effects for Temperature-Dependent Electronic Structures. (GraFOx 4th Semi-Annual Meeting, Online Event, May 2021).
Talk
Carbogno, Christian et al.: Phonon-Phonon and Electron-Phonon Interactions: From Fundamental Developments Towards Predictions. (Seminar, GraFOx, Online Event, Oct 2021).
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Carbogno, Christian et al.: Precise yet Fast High-Throughput Search for Thermal Insulators. (Duke-CAMD/MURI/AFLOW Seminar, Center for Autonomous Materials Design, Duke University, Online Event, Aug 2021).
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Carbogno, Christian et al.: The Key Role of Lattice Anharmonicity for Heat and Charge Transport in Solids: Fundamental Concepts, Novel Methods, and Relevant Applications. (Seminar, Theory Department, Fritz Haber Institute, Online Event, Jun 2021).
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Draxl, Claudia et al.: Recycle the Waste! (APE 2021, Academic Publishing in Europe Nr. 16, Online Event, Jan 2021).
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Draxl, Claudia et al.: Theoretical Toolbox for the Characterization of Organic-Inorganic Interfaces. (Virtual Microscopy Characterisation of Organic-Inorganic Interfaces 2021, Online Event, Mar 2021).
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Draxl, Claudia et al.: New Horizons for Materials Research. (APS March Meeting 2021, Online Event, Mar 2021).
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Draxl, Claudia et al.: Electronic Structure of Complex Materials: The Dilemma of Choosing the Right Method. (734. WE-Heraeus-Seminar, Photoemission Tomography: Applications and Future Developments, Bad Honnef, Germany, Oct 2021).
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Draxl, Claudia et al.: From FAIR Data to Knowledge and Novel Materials. (Conference, Physics For Society: Grand Challenges In The Horizon 2050, European Physical Society (EPS), Berlin, Germany, Oct 2021).
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Draxl, Claudia et al.: Excitations in Complex Oxides. (25. Deutsche Physikerinnentagung, Online Event, Nov 2021).
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Draxl, Claudia et al.: Quantum-Based Materials Modeling and Artificial Intelligence for Tackling Societal Challenges. (Lise-Meitner-Lectures 2021, Deutsche Physikalische Gesellschaft (DPG), Berlin, Germany, Nov 2021).
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Draxl, Claudia et al.: Exciting NEWS. (IX Workshop on Novel Methods for Electronic Structure Calculations, Online Event, Nov 2021).
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Draxl, Claudia et al.: FAIRmat’s Approach to FAIRness. (Workshop, HPC and Data Science for Scientific Discovery, Lake Arrowhead, CA, USA, Dec 2021).
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Draxl, Claudia et al.: Similarity of Materials and Data-Quality Assessment by Unsupervised Learning. (2021 MRS Fall Meeting & Exhibit, Online Event, Dec 2021).
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Draxl, Claudia et al.: Many-Body Approaches for Excitations in Solids - Current Limitations and Perspectives Towards Exascale Performance. (2021 MRS Fall Meeting & Exhibit, Online Event, Dec 2021).
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Draxl, Claudia et al.: A Quantum Puzzle. (Kick-off Meeting, Max Planck Graduate Center for Quantum Materials, Online Event, Nov 2021).
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Draxl, Claudia et al.: Excitations in Complex Oxides. (Colloquium, University College London, London, UK, Nov 2021).
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Draxl, Claudia et al.: Data-Centric Materials Science: Challenges in (Theoretical) Spectroscopy. (Workshop, Materials Science and Chemistry, Berlin-Brandenburgische Akademie der Wissenschaften, Berlin, Germany, Nov 2021).
Talk
Draxl, Claudia et al.: Basics of Density-Functional Theory. (Psi-k GreenALM Hands-on Tutorial 2021, Online Event, Oct 2021).
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Draxl, Claudia et al.: From Physics and Maths to Data and Back. (Symposium on the occasion of Walter Pötz’s retirement, Graz, Austria, Sep 2021).
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Draxl, Claudia et al.: Quantum-Based Materials Modeling and Artificial Intelligence for Tackling Societal Challenges. (Lise-Meitner-Lectures 2021, Österreichische Physikalische Gesellschaft (ÖPG), Online Event, Sep 2021).
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Draxl, Claudia et al.: From Data Mining to Knowledge: Refining a Precious Raw Material of the 21st Century. (International Symposium on Nanoscale Research, Institute of Physics, Montanuniversität Leoben, Leoben, Austria, Sep 2021).
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Draxl, Claudia et al.: FAIR Data and Artificial Intelligence Towards New Horizons in Materials Research. (European Congress and Exhibition on advanced Materials and Processes, EUROMAT 2021, Online Event, Sep 2021).
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Draxl, Claudia et al.: A Theorist’s Perspective on Electron-Loss Spectroscopy. (Joint Meeting, JEELS 2020 : 12es Journées EELS and Arbeitskreistreffen Energiefilterung und EELS, Münster, Germany, Aug 2021).
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Draxl, Claudia et al.: Excitations in Solids: Theoretical Approaches, Benchmarks, Limitations, and Perspectives Towards Exascale Performance. (XXXIII UPAP Conference on Computational Physics (CCP21), Online Event, Aug 2021).
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Draxl, Claudia et al.: FAIRmat’s Approach to Data-Centric Science. (SHU - MGI - FAIR-DI Workshop on FAIR-Data-Driven Materials Research, Online Event, Jun 2021).
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Draxl, Claudia et al.: From Data to Knowledge. (Workshop, Computer-Aided Materials Discover, Materials Square, Online Event, Mar 2021).
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Draxl, Claudia et al.: From Data to Knowledge. (Seminar, FunMat-II AI and machine learning for materials design, Online Event, Mar 2021).
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Draxl, Claudia et al.: From Physics Today to Publishing and Research of Tomorrow. (Colloquium, Christian-Albrechts-Universität zu Kiel, Online Event, Apr 2021).
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Draxl, Claudia et al.: Partial Order-Disorder Transition in Thermoelectric Clathrates Revealed by a Novel Approach for Temperature-Dependent Properties of Alloys. (2021 MRS Spring Meeting & Exhibit, Online Event, Apr 2021).
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Draxl, Claudia et al.: Theoretical Spectroscopy From the UV to the Hard X-Ray Region - Example of Ga2O3. (2021 MRS Spring Meeting & Exhibit, Online Event, Apr 2021).
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Draxl, Claudia et al.: From Data to Knowledge. (Meeting, Mixed-gen Session 4: Data Driven Science, CECAM-HQ, Online Event, Apr 2021).
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Draxl, Claudia et al.: From Raw Data to Material Maps. (Nature Research Round Table – Materials Genome Engineering and its Application in Energy Materials, Online Event, Mar 2021).
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Draxl, Claudia et al.: FAIRmat – Making Materials Data Findable and AI Ready. (Fall Meeting 2021, Deutsche Physikalische Gesellschaft (DPG), Online Event, Oct 2021).
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Foppa, Lucas et al.: Identifying the Materials Genes of Heterogeneous Catalysis With Clean Experiments and Tailored Artificial Intelligence. (Colloquium, ETH Zurich, Department of Chemistry and Applied Biosciences, Online Event, Dec 2021).
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Ghiringhelli, Luca M. et al.: Clusters and Surfaces in Reactive Atmospheres at Realistic Conditions: Beyond the Static, Monostructure Description. (APS March Meeting 2021, Online Event, Mar 2021).
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Ghiringhelli, Luca M. et al.: Ontologies in Computational Materials Science: The NOMAD Experience. (Workshop, Ontologies for Materials-Databases Interoperability (OMDI2021), Online Event, Oct 2021).
Talk
Ghiringhelli, Luca M. et al.: Symbolic Inference for Small-Data-Driven Materials Science. (Workshop, Computational Spintronics Group, Trinity College Dublin, Dublin, Ireland, Aug 2021).
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Ghiringhelli, Luca M. et al.: Symbolic Inference in Materials Science: Towards Human-Friendly Artificial Intelligence. (Physics Colloquium online, Theoretical Chemical Physics group, University of Luxembourg, Online Event, May 2021).
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Ghiringhelli, Luca M. et al.: Compressed Sensing Meets Symbolic Regression: Learning Interpretable Models. (BIG DATA SUMMER – A summer school of the BiGmax Network, Online Event, Sep 2021).
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Ghiringhelli, Luca M. et al.: NOMAD Metainfo: FAIR (Meta)data for Materials Science. (Workshop, Research-Data Management in Biophysics, European Biophysics Conference 2021, Online Event, Jul 2021).
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Ghiringhelli, Luca M. et al.: Data-Driven Materials Maps: Symbolic Inference Applied to Heterogeneous Catalysis. (ACS Fall Meeting 2021, Online Event, Aug 2021).
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Ghiringhelli, Luca M. et al.: Towards Small-Data-Driven Materials Science. (Autumn Meeting, EOSBF 2021, Brasilian Physical Society, Online Event, Jun 2021).
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Ghiringhelli, Luca M. et al.: FAIR Data and Metadata: The NOMAD Experience. (Workshop, Research Data Management, Guidelines, and Standards, BATTERY 2030+, Online Event, Mar 2021).
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Ghiringhelli, Luca M. et al.: Bridging Scales With Symbolic Inference: The Case of Heterogeneous Catalysis. (Symposium, Machine Learning: application to Chemical Reactions, Thomas Young Centre (TYC), Online Event, Feb 2021).
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Ghiringhelli, Luca M. et al.: Bridging Scales With Symbolic Inference: The Case of Heterogeneous Catalysis. (Seminar, NOMAD Laboratory & MA Group, Online Event, Jan 2021).
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Ghiringhelli, Luca M. et al.: Towards Small-Data-Driven Materials Science. (2021 MRS Spring Meeting & Exhibit, Online Event, Apr 2021).
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Ghiringhelli, Luca M. et al.: Ontologies in Computational Materials Science: The NOMAD Experience. (3rd EMMC International Workshop (EMMC 2021), Online Event, Mar 2021).
Talk
Levchenko, Sergey V. et al.: Single-Atom Alloy Catalysts Designed by First-Principles Calculations and Artificial Intelligence. (CECAM/Psi-k Flagship Workshop, Materials Design for Energy Storage and Conversion: Theory and Experiment, Online Event, Feb 2021).
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Levchenko, Sergey V. et al.: Using the Data-Mining Approach Subgroup Discovery for Understanding Mechanisms of Catalytic Reactions. (FHI Theory Department ML Journal Club, Online Event, Feb 2021).
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Levchenko, Sergey V. et al.: Single-Atom Alloy Catalysts Designed by First-Principles Calculations and Artificial Intelligence. (Electronic Materials and Applications 2021, Online Event, Jan 2021).
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Levchenko, Sergey V. et al.: Modelling Materials at Realistic Temperatures and Pressures. (VI International Conference of Young Scientists 2021, Moscow, Russia, Nov 2021).
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Levchenko, Sergey V. et al.: Computational Design of Materials for Heterogeneous Catalysis. (20th Workshop on Crystal Structure Prediction With USPEX Code (20th Lyakhov school), Online Event, Nov 2021).
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Levchenko, Sergey V. et al.: Deriving Descriptors and Physical Understanding From Data in Catalysis Research. (2021 AIChE Annual Meeting, Online Event, Nov 2021).
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Maksimov, Dmitrii et al.: Conformation Prediction for Flexible Molecules at Surfaces Using Ab Initio Random Structure Search. (CRC 951 - HIOS Young Researcher Workshop 2021, Online Event, Oct 2021).
Talk
Purcell, Thomas et al.: Machine-Learning Aided Approaches. (Workshop, Capturing Anharmonic Vibrational Motion in First-Principles Simulations, Centre Européen de Calcul Atomique et Moléculaire (CECAM), Online Event, Dec 2021).
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Sarker, Debalaya et al.: Autonomous Computational Discovery of Catalysts and Energy Materials. (Seminar, Raja Ramanna Center for Advanced Technology, Online Event, Feb 2021).
Talk
Scheffler, Matthias et al.: Subgroup Discovery, Rare-Phenomena Challenge, and Domain of Applicability. (Lecture, Big Data and Artificial Intelligence in Materials Sciences, Online Event, Jan 2021).
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Scheffler, Matthias et al.: The NOMAD Laboratory at the FHI of the Max Planck Society. (Symposium, Max Planck Graduate Center for Quantum Materials, Stuttgart, Germany, Feb 2021).
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Scheffler, Matthias et al.: FAIRMAT – A Proposed Consortium of the German Research-Data Infrastructure. (Spring Meeting, Deutsche Physikalische Gesellschaft (DPG), Online Event, Mar 2021).
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Scheffler, Matthias et al.: Artificial Intelligence, Towards Materials Maps. (2021 MRS Spring Meeting & Exhibit, Online Event, Apr 2021).
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Scheffler, Matthias et al.: Big Data and Statistically Exceptional Materials. (International Conference, Materials for Humanity (MH 21), Materials Research Society Singapore (MRS), Online Event, Jul 2021).
Talk
Scheffler, Matthias et al.: Properties of Materials From First Principles. (Virtual hands-on tutorial, FHI-aims, Online Event, Aug 2021).
Talk
Scheffler, Matthias et al.: Open Data in Naturwissenschaften und Mathematik: Das FAIRmat Konsortium. (Lecture, Berlin-Brandenburgische Akademie der Wissenschaften (BBAW), Online Event, Oct 2021).
Talk
Scheffler, Matthias et al.: Paradigm Shift by Data-Centric Materials Science Jointly Steered With and Enabled by MPCDF. (Symposium, 60th Anniversary of RZG/MPCDF (Max-Planck Computing and Data Facility), Garching, Germany, Oct 2021).
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Scheffler, Matthias et al.: Big Data and Statistically Exceptional Materials. (Symposium, Villum Project Kristian Sommer Thygesen, Copenhagen, Denmark, Nov 2021).
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Scheffler, Matthias et al.: Artificial Intelligence for Surface Science and Heterogeneous Catalysis: Learning Rules and Creating Maps of Materials Properties. (The 9th International Symposium on Surface Science (ISSS-9), Online Event, Nov 2021).
Talk
Scheffler, Matthias et al.: Learning Rules for Materials Properties and Functions by Artificial Intelligence. (2021 MRS Fall Meeting & Exhibit, Online Event, Dec 2021).
Talk
Scheffler, Matthias et al.: Big-Data Driven Materials Science. (Symposium, Aktuelle Methoden der physikalischen Forschung, Technische Universität Berlin, Online Event, Feb 2021).
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Scheffler, Matthias et al.: Learning Rules for Materials Properties and Functions and Creating Materials Maps. (International Workshop on Computer-Aided Materials Discovery, Online Event, Jun 2021).
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