Big-Data Analytics for the Thermal and Electrical Conductivity of Materials from First Principles

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Pubblicazioni

Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated with Bulk Properties of Perovskites

Autori: Lucas Foppa, Thomas A. R. Purcell, Sergey V. Levchenko, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Physical Review Letters, Numero 129, 2025, ISSN 0031-9007
Editore: American Physical Society
DOI: 10.1103/physrevlett.129.055301

Interpretable machine learning for materials design

Autori: James Dean, Matthias Scheffler, Thomas A. R. Purcell, Sergey V. Barabash, Rahul Bhowmik, Timur Bazhirov
Pubblicato in: Journal of Materials Research, Numero 38, 2023, Pagina/e 4477-4496, ISSN 0884-2914
Editore: Materials Research Society
DOI: 10.1557/s43578-023-01164-w

Massive-Parallel Implementation of the Resolution-of-Identity Coupled-Cluster Approaches in the Numeric Atom-Centered Orbital Framework for Molecular Systems

Autori: Tonghao Shen, Zhenyu Zhu, Igor Ying Zhang, Matthias Scheffler
Pubblicato in: Journal of Chemical Theory and Computation, Numero 15, 2023, Pagina/e 4721-4734, ISSN 1549-9618
Editore: American Chemical Society
DOI: 10.1021/acs.jctc.8b01294

Carrier mobility of strongly anharmonic materials from first principles

Autori: Jingkai Quan, Christian Carbogno, Matthias Scheffler
Pubblicato in: Physical Review B, Numero 110, 2024, ISSN 2469-9950
Editore: American Physical Society (APS)
DOI: 10.1103/physrevb.110.235202

"All-electron periodic <mml:math xmlns:mml=""http://www.w3.org/1998/Math/MathML""><mml:mrow><mml:msub><mml:mi>G</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:msub><mml:mi>W</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:mrow></mml:math> implementation with numerical atomic orbital basis functions: Algorithm and benchmarks"

Autori: Xinguo Ren, Florian Merz, Hong Jiang, Yi Yao, Markus Rampp, Hermann Lederer, Volker Blum, Matthias Scheffler
Pubblicato in: Physical Review Materials, Numero 5, 2021, ISSN 2475-9953
Editore: American Physical Society (APS)
DOI: 10.1103/physrevmaterials.5.013807

<i>Ab initio</i> Green-Kubo simulations of heat transport in solids: Method and implementation

Autori: Florian Knoop, Matthias Scheffler, Christian Carbogno
Pubblicato in: Physical Review B, Numero 107, 2023, ISSN 2469-9950
Editore: American Physical Society (APS)
DOI: 10.1103/physrevb.107.224304

Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence

Autori: Thomas A. R. Purcell, Matthias Scheffler, Luca M. Ghiringhelli, Christian Carbogno
Pubblicato in: npj Computational Materials, Numero 9, 2023, ISSN 2057-3960
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41524-023-01063-y

Fully anharmonic nonperturbative theory of vibronically renormalized electronic band structures

Autori: Marios Zacharias, Matthias Scheffler, Christian Carbogno
Pubblicato in: Physical Review B, Numero 102, 2020, ISSN 2469-9950
Editore: American Physical Society (APS)
DOI: 10.1103/physrevb.102.045126

The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding

Autori: Luigi Sbailò, Ádám Fekete, Luca M. Ghiringhelli, Matthias Scheffler
Pubblicato in: npj Computational Materials, Numero 8, 2024, ISSN 2057-3960
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41524-022-00935-z

Recent advances in the SISSO method and their implementation in the SISSO++ code

Autori: Thomas A. R. Purcell, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: The Journal of Chemical Physics, Numero 159, 2025, ISSN 0021-9606
Editore: American Institute of Physics
DOI: 10.1063/5.0156620

Finite-Size Effects in Periodic EOM-CCSD for Ionization Energies and Electron Affinities: Convergence Rate and Extrapolation to the Thermodynamic Limit

Autori: Evgeny Moerman, Alejandro Gallo, Andreas Irmler, Tobias Schäfer, Felix Hummel, Andreas Grüneis, Matthias Scheffler
Pubblicato in: Journal of Chemical Theory and Computation, Numero 21, 2025, Pagina/e 1865-1878, ISSN 1549-9618
Editore: American Chemical Society
DOI: 10.1021/acs.jctc.4c01451

FHI-vibes: Ab Initio Vibrational Simulations

Autori: Florian Knoop, Thomas Purcell, Matthias Scheffler, Christian Carbogno
Pubblicato in: Journal of Open Source Software, Numero 5, 2020, Pagina/e 2671, ISSN 2475-9066
Editore: The Open Journal
DOI: 10.21105/joss.02671

Shared metadata for data-centric materials science

Autori: Luca M. Ghiringhelli, Carsten Baldauf, Tristan Bereau, Sandor Brockhauser, Christian Carbogno, Javad Chamanara, Stefano Cozzini, Stefano Curtarolo, Claudia Draxl, Shyam Dwaraknath, Ádám Fekete, James Kermode, Christoph T. Koch, Markus Kühbach, Alvin Noe Ladines, Patrick Lambrix, Maja-Olivia Himmer, Sergey V. Levchenko, Micael Oliveira, Adam Michalchuk, Ronald E. Miller, Berk Onat, Pasquale Pavo
Pubblicato in: Scientific Data, Numero 10, 2023, ISSN 2052-4463
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41597-023-02501-8

Heat flux for semilocal machine-learning potentials

Autori: Marcel F. Langer, Florian Knoop, Christian Carbogno, Matthias Scheffler, Matthias Rupp
Pubblicato in: Physical Review B, Numero 108, 2023, ISSN 2469-9950
Editore: American Physical Society (APS)
DOI: 10.1103/physrevb.108.l100302

DFT exchange: sharing perspectives on the workhorse of quantum chemistry and materials science

Autori: Andrew M. Teale, Trygve Helgaker, Andreas Savin, Carlo Adamo, Bálint Aradi, Alexei V. Arbuznikov, Paul W. Ayers, Evert Jan Baerends, Vincenzo Barone, Patrizia Calaminici, Eric Cancès, Emily A. Carter, Pratim Kumar Chattaraj, Henry Chermette, Ilaria Ciofini, T. Daniel Crawford, Frank De Proft, John F. Dobson, Claudia Draxl, Thomas Frauenheim, Emmanuel Fromager, Patricio Fuentealba, Laura Gagliard
Pubblicato in: Physical Chemistry Chemical Physics, Numero 24, 2024, Pagina/e 28700-28781, ISSN 1463-9076
Editore: Royal Society of Chemistry
DOI: 10.1039/d2cp02827a

Interface to high-performance periodic coupled-clustertheory calculations with atom-centered, localized basisfunctions

Autori: Evgeny Moerman, Felix Hummel, Andreas Grüneis, Andreas Irmler, Matthias Scheffler
Pubblicato in: Journal of Open Source Software, Numero 7, 2022, Pagina/e 4040, ISSN 2475-9066
Editore: The Open Journal
DOI: 10.21105/joss.04040

Identifying domains of applicability of machine learning models for materials science

Autori: Christopher Sutton, Mario Boley, Luca M. Ghiringhelli, Matthias Rupp, Jilles Vreeken, Matthias Scheffler
Pubblicato in: Nature Communications, Numero 11, 2022, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-020-17112-9

OPTIMADE, an API for exchanging materials data

Autori: Casper W. Andersen, Rickard Armiento, Evgeny Blokhin, Gareth J. Conduit, Shyam Dwaraknath, Matthew L. Evans, Ádám Fekete, Abhijith Gopakumar, Saulius Gražulis, Andrius Merkys, Fawzi Mohamed, Corey Oses, Giovanni Pizzi, Gian-Marco Rignanese, Markus Scheidgen, Leopold Talirz, Cormac Toher, Donald Winston, Rossella Aversa, Kamal Choudhary, Pauline Colinet, Stefano Curtarolo, Davide Di Stefano, Cla
Pubblicato in: Scientific Data, Numero 8, 2022, ISSN 2052-4463
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41597-021-00974-z

Self-interaction corrected SCAN functional for molecules and solids in the numeric atom-center orbital framework

Autori: Sheng Bi, Christian Carbogno, Igor Ying Zhang, Matthias Scheffler
Pubblicato in: The Journal of Chemical Physics, Numero 160, 2024, ISSN 0021-9606
Editore: American Institute of Physics
DOI: 10.1063/5.0178075

SISSO++: A C++ Implementation of the Sure-IndependenceScreening and Sparsifying Operator Approach

Autori: Thomas A. R. Purcell, Matthias Scheffler, Christian Carbogno, Luca M. Ghiringhelli
Pubblicato in: Journal of Open Source Software, Numero 7, 2022, Pagina/e 3960, ISSN 2475-9066
Editore: The Open Journal
DOI: 10.21105/joss.03960

Performance of various density-functional approximations for cohesive properties of 64 bulk solids

Autori: Guo-Xu Zhang, Anthony M Reilly, Alexandre Tkatchenko, Matthias Scheffler
Pubblicato in: New Journal of Physics, Numero 20, 2020, Pagina/e 063020, ISSN 1367-2630
Editore: Institute of Physics Publishing
DOI: 10.1088/1367-2630/aac7f0

Numerical quality control for DFT-based materials databases

Autori: Christian Carbogno, Kristian Sommer Thygesen, Björn Bieniek, Claudia Draxl, Luca M. Ghiringhelli, Andris Gulans, Oliver T. Hofmann, Karsten W. Jacobsen, Sven Lubeck, Jens Jørgen Mortensen, Mikkel Strange, Elisabeth Wruss, Matthias Scheffler
Pubblicato in: npj Computational Materials, Numero 8, 2022, ISSN 2057-3960
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41524-022-00744-4

TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions

Autori: Benjamin Regler, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Data Mining and Knowledge Discovery, Numero 36, 2022, Pagina/e 1815-1864, ISSN 1384-5810
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10618-022-00847-y

Extrapolation to the complete basis-set limit in density-functional theory using statistical learning

Autori: Daniel T. Speckhard, Christian Carbogno, Luca M. Ghiringhelli, Sven Lubeck, Matthias Scheffler, Claudia Draxl
Pubblicato in: Physical Review Materials, Numero 9, 2025, ISSN 2475-9953
Editore: American Physical Society (APS)
DOI: 10.1103/physrevmaterials.9.013801

AI guided workflows for efficiently screening the materials space

Autori: Matthias Scheffler
Pubblicato in: Coshare Science, Numero 2, 2024, Pagina/e 1-18, ISSN 3006-8045
Editore: Coshare Academic Press Company Limited
DOI: 10.61109/cs.202403.129

FAIR data enabling new horizons for materials research

Autori: Matthias Scheffler, Martin Aeschlimann, Martin Albrecht, Tristan Bereau, Hans-Joachim Bungartz, Claudia Felser, Mark Greiner, Axel Groß, Christoph T. Koch, Kurt Kremer, Wolfgang E. Nagel, Markus Scheidgen, Christof Wöll, Claudia Draxl
Pubblicato in: Nature, Numero 604, 2022, Pagina/e 635-642, ISSN 0028-0836
Editore: Nature Publishing Group
DOI: 10.1038/s41586-022-04501-x

Beyond Scaling Relations for the Description of Catalytic Materials

Autori: Mie Andersen, Sergey V. Levchenko, Matthias Scheffler, Karsten Reuter
Pubblicato in: ACS Catalysis, Numero 9/4, 2019, Pagina/e 2752-2759, ISSN 2155-5435
Editore: American Chemical Society
DOI: 10.1021/acscatal.8b04478

NOMAD: The FAIR concept for big data-driven materials science

Autori: Claudia Draxl, Matthias Scheffler
Pubblicato in: MRS Bulletin, Numero 43/9, 2018, Pagina/e 676-682, ISSN 0883-7694
Editore: Materials Research Society
DOI: 10.1557/mrs.2018.208

SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates

Autori: Runhai Ouyang, Stefano Curtarolo, Emre Ahmetcik, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Physical Review Materials, Numero 2/8, 2018, ISSN 2475-9953
Editore: American Physical Society
DOI: 10.1103/physrevmaterials.2.083802

Two-to-three dimensional transition in neutral gold clusters: The crucial role of van der Waals interactions and temperature

Autori: Bryan R. Goldsmith, Jacob Florian, Jin-Xun Liu, Philipp Gruene, Jonathan T. Lyon, David M. Rayner, André Fielicke, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Physical Review Materials, Numero 3/1, 2019, ISSN 2475-9953
Editore: APS
DOI: 10.1103/physrevmaterials.3.016002

Simultaneous learning of several materials properties from incomplete databases with multi-task SISSO

Autori: Runhai Ouyang, Emre Ahmetcik, Christian Carbogno, Matthias Scheffler, Luca M Ghiringhelli
Pubblicato in: Journal of Physics: Materials, Numero 2/2, 2019, Pagina/e 024002, ISSN 2515-7639
Editore: IOP Publishing
DOI: 10.1088/2515-7639/ab077b

Crowd-sourcing materials-science challenges with the NOMAD 2018 Kaggle competition

Autori: Christopher Sutton, Luca M. Ghiringhelli, Takenori Yamamoto, Yury Lysogorskiy, Lars Blumenthal, Thomas Hammerschmidt, Jacek R. Golebiowski, Xiangyue Liu, Angelo Ziletti, Matthias Scheffler
Pubblicato in: npj Computational Materials, Numero 5/1, 2019, ISSN 2057-3960
Editore: Nature Research, Springer Nature
DOI: 10.1038/s41524-019-0239-3

Main-group test set for materials science and engineering with user-friendly graphical tools for error analysis: systematic benchmark of the numerical and intrinsic errors in state-of-the-art electronic-structure approximations

Autori: Igor Ying Zhang, Andrew J Logsdail, Xinguo Ren, Sergey V Levchenko, Luca Ghiringhelli, Matthias Scheffler
Pubblicato in: New Journal of Physics, Numero 21/1, 2019, Pagina/e 013025, ISSN 1367-2630
Editore: Institute of Physics Publishing
DOI: 10.1088/1367-2630/aaf751

New tolerance factor to predict the stability of perovskite oxides and halides

Autori: Christopher J. Bartel, Christopher Sutton, Bryan R. Goldsmith, Runhai Ouyang, Charles B. Musgrave, Luca M. Ghiringhelli, Matthias Scheffler
Pubblicato in: Science Advances, Numero 5/2, 2019, Pagina/e eaav0693, ISSN 2375-2548
Editore: American Association for the Advancement of Science
DOI: 10.1126/sciadv.aav0693

(Meta-)stability and Core–Shell Dynamics of Gold Nanoclusters at Finite Temperature

Autori: Diego Guedes-Sobrinho, Weiqi Wang, Ian P. Hamilton, Juarez L. F. Da Silva, Luca M. Ghiringhelli
Pubblicato in: The Journal of Physical Chemistry Letters, Numero 10/3, 2019, Pagina/e 685-692, ISSN 1948-7185
Editore: American Chemical Society
DOI: 10.1021/acs.jpclett.8b03397

Artificial intelligence for high-throughput discovery of topological insulators: The example of alloyed tetradymites

Autori: Guohua Cao, Runhai Ouyang, Luca M. Ghiringhelli, Matthias Scheffler, Huijun Liu, Christian Carbogno, Zhenyu Zhang
Pubblicato in: Physical Review Materials, Numero 4/3, 2020, ISSN 2475-9953
Editore: APS
DOI: 10.1103/physrevmaterials.4.034204

Determining surface phase diagrams including anharmonic effects

Autori: Yuanyuan Zhou, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Physical Review B, Numero 100/17, 2019, ISSN 2469-9950
Editore: APS
DOI: 10.1103/physrevb.100.174106

Electron-phonon coupling in d -electron solids: A temperature-dependent study of rutile Ti O 2 by first-principles theory and two-photon photoemission

Autori: Honghui Shang, Adam Argondizzo, Shijing Tan, Jin Zhao, Patrick Rinke, Christian Carbogno, Matthias Scheffler, Hrvoje Petek
Pubblicato in: Physical Review Research, Numero 1/3, 2019, ISSN 2643-1564
Editore: APS
DOI: 10.1103/physrevresearch.1.033153

Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects

Autori: Andreas Alvermann, Achim Basermann, Hans-Joachim Bungartz, Christian Carbogno, Dominik Ernst, Holger Fehske, Yasunori Futamura, Martin Galgon, Georg Hager, Sarah Huber, Thomas Huckle, Akihiro Ida, Akira Imakura, Masatoshi Kawai, Simone Köcher, Moritz Kreutzer, Pavel Kus, Bruno Lang, Hermann Lederer, Valeriy Manin, Andreas Marek, Kengo Nakajima, Lydia Nemec, Karsten Reuter, Michael Rippl, Melven R
Pubblicato in: Japan Journal of Industrial and Applied Mathematics, Numero 36/2, 2019, Pagina/e 699-717, ISSN 0916-7005
Editore: Kinokuniya Co., Ltd.
DOI: 10.1007/s13160-019-00360-8

Step-flow growth in homoepitaxy of β -Ga 2 O 3 (100)—The influence of the miscut direction and faceting

Autori: R. Schewski, K. Lion, A. Fiedler, C. Wouters, A. Popp, S. V. Levchenko, T. Schulz, M. Schmidbauer, S. Bin Anooz, R. Grüneberg, Z. Galazka, G. Wagner, K. Irmscher, M. Scheffler, C. Draxl, M. Albrecht
Pubblicato in: APL Materials, Numero 7/2, 2019, Pagina/e 022515, ISSN 2166-532X
Editore: American Institute of Physics
DOI: 10.1063/1.5054943

Parametrically constrained geometry relaxations for high-throughput materials science

Autori: Maja-Olivia Lenz, Thomas A. R. Purcell, David Hicks, Stefano Curtarolo, Matthias Scheffler, Christian Carbogno
Pubblicato in: npj Computational Materials, Numero 5/1, 2019, ISSN 2057-3960
Editore: Elsevier
DOI: 10.1038/s41524-019-0254-4

The NOMAD laboratory: from data sharing to artificial intelligence

Autori: Claudia Draxl, Matthias Scheffler
Pubblicato in: Journal of Physics: Materials, Numero 2/3, 2019, Pagina/e 036001, ISSN 2515-7639
Editore: IOP Publishing
DOI: 10.1088/2515-7639/ab13bb

Viewpoint: Atomic-Scale Design Protocols toward Energy, Electronic, Catalysis, and Sensing Applications

Autori: Florian Belviso, Victor E. P. Claerbout, Aleix Comas-Vives, Naresh S. Dalal, Feng-Ren Fan, Alessio Filippetti, Vincenzo Fiorentini, Lucas Foppa, Cesare Franchini, Benjamin Geisler, Luca M. Ghiringhelli, Axel Groß, Shunbo Hu, Jorge Íñiguez, Steven Kaai Kauwe, Janice L. Musfeldt, Paolo Nicolini, Rossitza Pentcheva, Tomas Polcar, Wei Ren, Fabio Ricci, Francesco Ricci, Huseyin Sener Sen, Jonathan M
Pubblicato in: Inorganic Chemistry, Numero 58/22, 2019, Pagina/e 14939-14980, ISSN 0020-1669
Editore: American Chemical Society
DOI: 10.1021/acs.inorgchem.9b01785

AFLOW-CHULL: Cloud-Oriented Platform for Autonomous Phase Stability Analysis

Autori: Corey Oses, Eric Gossett, David Hicks, Frisco Rose, Michael J. Mehl, Eric Perim, Ichiro Takeuchi, Stefano Sanvito, Matthias Scheffler, Yoav Lederer, Ohad Levy, Cormac Toher, Stefano Curtarolo
Pubblicato in: Journal of Chemical Information and Modeling, Numero 58/12, 2018, Pagina/e 2477-2490, ISSN 1549-9596
Editore: American Chemical Society
DOI: 10.1021/acs.jcim.8b00393

Insightful classification of crystal structures using deep learning

Autori: Angelo Ziletti, Devinder Kumar, Matthias Scheffler, Luca M. Ghiringhelli
Pubblicato in: Nature Communications, Numero 9/1, 2018, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.1038/s41467-018-05169-6

Optimizations of the eigensolvers in the ELPA library

Autori: P. Kůs, A. Marek, S.S. Köcher, H.-H. Kowalski, C. Carbogno, Ch. Scheurer, K. Reuter, M. Scheffler, H. Lederer
Pubblicato in: Parallel Computing, Numero 85, 2019, Pagina/e 167-177, ISSN 0167-8191
Editore: Elsevier BV
DOI: 10.1016/j.parco.2019.04.003

Efficient all-electron hybrid density functionals for atomistic simulations beyond 10 000 atoms

Autori: Sebastian Kokott, Florian Merz, Yi Yao, Christian Carbogno, Mariana Rossi, Ville Havu, Markus Rampp, Matthias Scheffler, Volker Blum
Pubblicato in: The Journal of Chemical Physics, Numero 161, 2025, ISSN 0021-9606
Editore: American Institute of Physics
DOI: 10.1063/5.0208103

Roadmap on Machine learning in electronic structure

Autori: H J Kulik, T Hammerschmidt, J Schmidt, S Botti, M A L Marques, M Boley, M Scheffler, M Todorović, P Rinke, C Oses, A Smolyanyuk, S Curtarolo, A Tkatchenko, A P Bartók, S Manzhos, M Ihara, T Carrington, J Behler, O Isayev, M Veit, A Grisafi, J Nigam, M Ceriotti, K T Schütt, J Westermayr, M Gastegger, R J Maurer, B Kalita, K Burke, R Nagai, R Akashi, O Sugino, J Hermann, F Noé, S Pilati, C Draxl
Pubblicato in: Electronic Structure, Numero 4, 2023, Pagina/e 023004, ISSN 2516-1075
Editore: IOP Publishing
DOI: 10.1088/2516-1075/ac572f

Anharmonicity in Thermal Insulators: An Analysis from First Principles

Autori: Florian Knoop, Thomas A. R. Purcell, Matthias Scheffler, Christian Carbogno
Pubblicato in: Physical Review Letters, Numero 130, 2025, ISSN 0031-9007
Editore: American Physical Society
DOI: 10.1103/physrevlett.130.236301

Roadmap on data-centric materials science

Autori: Stefan Bauer, Peter Benner, Tristan Bereau, Volker Blum, Mario Boley, Christian Carbogno, C Richard A Catlow, Gerhard Dehm, Sebastian Eibl, Ralph Ernstorfer, Ádám Fekete, Lucas Foppa, Peter Fratzl, Christoph Freysoldt, Baptiste Gault, Luca M Ghiringhelli, Sajal K Giri, Anton Gladyshev, Pawan Goyal, Jason Hattrick-Simpers, Lara Kabalan, Petr Karpov, Mohammad S Khorrami, Christoph T. Koch, Sebasti
Pubblicato in: Modelling and Simulation in Materials Science and Engineering, Numero 32, 2024, Pagina/e 063301, ISSN 0965-0393
Editore: Institute of Physics Publishing
DOI: 10.1088/1361-651x/ad4d0d

Exploring the accuracy of the equation-of-motion coupled-cluster band gap of solids

Autori: Evgeny Moerman, Henrique Miranda, Alejandro Gallo, Andreas Irmler, Tobias Schäfer, Felix Hummel, Manuel Engel, Georg Kresse, Matthias Scheffler, Andreas Grüneis
Pubblicato in: Physical Review B, Numero 111, 2025, ISSN 2469-9950
Editore: American Physical Society (APS)
DOI: 10.1103/physrevb.111.l121202

Anharmonicity measure for materials

Autori: Florian Knoop, Thomas A. R. Purcell, Matthias Scheffler, Christian Carbogno
Pubblicato in: Physical Review Materials, Numero 4, 2020, ISSN 2475-9953
Editore: American Physical Society (APS)
DOI: 10.1103/physrevmaterials.4.083809

Atomate2: Modular workflows for materials science

Autori: Alex Ganose, Hrushikesh Sahasrabuddhe, Mark Asta, Kevin Beck, Tathagata Biswas, Alexander Bonkowski, Joana Bustamante, Xin Chen, Yuan Chiang, Daryl Chrzan, Jacob Clary, Orion Cohen, Christina Ertural, Max Gallant, Janine George, Sophie Gerits, Rhys Goodall, Rishabh Guha, Geoffroy Hautier, Matthew Horton, Aaron Kaplan, Ryan Kingsbury, Matthew Kuner, Bryant Li, Xavier Linn, Matthew McDermott, Rohith
Pubblicato in: 2025
Editore: American Chemical Society (ACS)
DOI: 10.26434/chemrxiv-2025-tcr5h

On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials

Autori: Shuaihua Lu, Luca M. Ghiringhelli, Christian Carbogno, Jinlan Wang, Matthias Scheffler
Pubblicato in: 2023
Editore: IOP
DOI: 10.48550/arXiv.2309.00195

Materials-Discovery Workflows Guided by Symbolic Regression: Identifying Acid-Stable Oxides for Electrocatalysis

Autori: Akhil S. Nair, Lucas Foppa, Matthias Scheffler
Pubblicato in: 2024
Editore: Preprint
DOI: 10.48550/arxiv.2412.05947

Accelerating the training and improving the reliability of machine-learned interatomic potentials for strongly anharmonic materials through active learning

Autori: Kisung Kang, Thomas A. R. Purcell, Christian Carbogno, Matthias Scheffler
Pubblicato in: 2024
Editore: Preprint
DOI: 10.48550/arxiv.2409.11808

Roadmap on Advancements of the FHI-aims Software Package

Autori: Joseph W. Abbott, Carlos Mera Acosta, Alaa Akkoush, Sebastian Kokott, et al.
Pubblicato in: 2025
Editore: IOP
DOI: 10.48550/arxiv.2505.00125

A high-performance and portable implementation of the SISSO method for CPUs and GPUs

Autori: Sebastian Eibl, Yi Yao, Matthias Scheffler, Markus Rampp, Luca M. Ghiringhelli, Thomas A. R. Purcell
Pubblicato in: 2025
Editore: IOP
DOI: 10.48550/arxiv.2502.20072

Towards a Multi-Objective Optimization of Subgroups for the Discovery of Materials with Exceptional Performance

Autori: Lucas Foppa, Matthias Scheffler
Pubblicato in: 2023
Editore: Preprint
DOI: 10.48550/arxiv.2311.10381

ELPA: A Parallel Solver for the Generalized Eigenvalue Problem1

Autori: null Bungartz Hans-Joachim, null Carbogno Christian, null Galgon Martin, null Huckle Thomas, null Köcher Simone, null Kowalski Hagen-Henrik, null Kus Pavel, null Lang Bruno, null Lederer Hermann, null Manin Valeriy, null Marek Andreas, null Reuter Karsten, null Rippl Michael, null Scheffler Matthias, null Scheurer Christoph
Pubblicato in: Advances in Parallel Computing, Parallel Computing: Technology Trends, 2025
Editore: IOS Press
DOI: 10.3233/apc200095

Big Data-Driven Materials Science and Its FAIR Data Infrastructure

Autori: Claudia Draxl, Matthias Scheffler
Pubblicato in: Handbook of Materials Modeling - Methods: Theory and Modeling, 2020, Pagina/e 49-73, ISBN 978-3-319-44676-9
Editore: Springer International Publishing
DOI: 10.1007/978-3-319-44677-6_104

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