Forschungsbereich Theoretische Chemie

Organization Name (de) Name der Organisation (de)
E165-03 - Forschungsbereich Theoretische Chemie
 
Code Kennzahl
E165-03
 
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Research Division
Parent OrgUnit Übergeordnete Organisation
 
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PreviewAuthor(s)TitleTypeIssue Date
1Wanzenboeck-2024-Computer Physics Communications-vor.pdf.jpgWanzenböck, Ralf ; Buchner, Florian ; Kovács, Péter ; Madsen, Georg Kent Hellerup ; Carrete, Jesús Clinamen2: Functional-style evolutionary optimization in Python for atomistic structure searchesArticle Artikel Apr-2024
2Kovács, Péter ; Blaha, Peter ; Madsen, Georg K H Origin of the success of mGGAs for bandgapsArticle Artikel 29-Dec-2023
3Heid-2023-Chemical Science-vor.pdf.jpgHeid, Esther ; Probst, Daniel ; Green, William H ; Madsen, Georg Kent Hellerup EnzymeMap: curation, validation and data-driven prediction of enzymatic reactionsArticle Artikel 28-Dec-2023
4Heid, Esther ; Greenman, Kevin P ; Chung, Yunsie ; Li, Shih-Cheng ; Graff, David E ; Vermeire, Florence ; Wu, Haoyang ; Green, William H ; McGill, Charles J Chemprop: A Machine Learning Package for Chemical Property PredictionArticle Artikel 26-Dec-2023
5Unglert, Nico ; Carrete, Jesús ; Pártay, Livia B. ; Madsen, Georg K.H. Neural-network force field backed nested sampling: Study of the silicon 𝑝-𝑇 phase diagramArticle Artikel 20-Dec-2023
6Wittwer, Benjamin ; Leitner, Daniel ; Neururer, Florian Rochus ; Schoch, Roland ; Seidl, Michael ; Pecak, Jan ; Podewitz, Maren ; Hohloch, Stephan Scrutinizing the Redox Chemistry of Group 10 Complexes Supported by a Redox-Active bis-Phenolate Mesoionic CarbeneArticle Artikel 13-Dec-2023
7Usuga, A. F. ; Praveen, C. S. ; Comas-Vives, A. Local descriptors-based machine learning model refined by cluster analysis for accurately predicting adsorption energies on bimetallic alloysArticle Artikel 4-Dec-2023
8Siebenhofer, Matthäus ; Nenning, Andreas ; Kubicek, Markus ; Blaha, Peter ; Fleig, Jürgen Engineering Surface Dipoles on Mixed Conducting Oxides with Ultra-Thin Oxide Decoration LayersPresentation Vortrag29-Nov-2023
9Díaz López, Estefanía ; Comas-Vives, Aleix CO₂ activation dominating the dry reforming of methane catalyzed by Rh(111) based on multiscale modellingArticle Artikel 15-Nov-2023
10Bosoni, Emanuele ; Beal, Louis ; Bercx, Marnik ; Blaha, Peter ; Blügel, Stefan ; Bröder, Jens ; Callsen, Martin ; Cottenier, Stefaan ; Degomme, Augustin ; Dikan, Vladimir ; Eimre, Kristjan ; Flage-Larsen, Espen ; Fornari, Marco ; Garcia, Alberto ; Genovese, Luigi ; Giantomassi, Matteo ; Huber, Sebastiaan P. ; Janssen, Henning ; Kastlunger, Georg ; Krack, Matthias ; Kresse, Georg ; Kühne, Thomas D. ; Lejaeghere, Kurt ; Madsen, Georg Kent Hellerup ; Marsman, Martijn ; Marzari, Nicola ; Michalicek, Gregor ; Mirhosseini, Hossein ; Müller, Tiziano M. A. ; Petretto, Guido ; Pickard, Chris J. ; Poncé, Samuel ; Rignanese, Gian-Marco ; Rubel, Oleg ; Ruh, Thomas ; Sluydts, Michael ; Vanpoucke, Danny E. P. ; Vijay, Sudarshan ; Wolloch, Michael ; Wortmann, Daniel ; Yakutovich, Aliaksandr V. ; Yu, Jusong ; Zadoks, Austin ; Zhu, Bonan ; Pizzi, Giovanni How to verify the precision of density-functional-theory implementations via reproducible and universal workflowsArticle Artikel 14-Nov-2023
11Podewitz, Maren Modelling Solution ChemistryPresentation Vortrag6-Nov-2023
12Käfer, Matthias ; Eder, Wolfgang ; Pecak, Jan ; Stöger, Berthold ; Pignitter, Marc ; Veiros, Luis F ; Kirchner, Karl Cr(II) and Cr(III) NCN pincer complexes: synthesis, structure, and catalytic reactivityArticle Artikel 10-Oct-2023
13Heid, Esther Carina ; McGill, Charles ; Vermeire, Florence ; Green, William H ; Madsen, Georg Kent Hellerup Errors and Uncertainty in Machine Learning ModelsPresentation Vortrag25-Sep-2023
14Schörghuber, Johannes ; Carrete Montana, Jesús ; Madsen, Georg Kent Hellerup Electron‐Passing Neural NetworksInproceedings Konferenzbeitrag24-Sep-2023
15Chen-2023-The Journal of Physical Chemistry C-vor.pdf.jpgChen, Jia-Li ; Blaha, Peter ; Kaltsoyannis, Nikolas DFT + U simulation of the X-ray absorption near-edge structure of bulk UO₂ and PuO₂Article Artikel 14-Sep-2023
16Talmazan, Radu Alexandru ; Podewitz, Maren Tackling Dynamics and Solvation in CatalysisInproceedings Konferenzbeitrag12-Sep-2023
17Talmazan-2023-Journal of Chemical Information and Modeling-vor.pdf.jpgTalmazan, Radu Alexandru ; Podewitz, Maren PyConSolv: A Python Package for Conformer Generation of (Metal-Containing) Systems in Explicit SolventArticle Artikel 11-Sep-2023
18Heid, Esther Carina Deep learning of reaction properties via graph-convolutional neural netsPresentation Vortrag6-Sep-2023
19Talmazan, Radu Alexandru ; Podewitz, Maren Tackling Dynamics and Solvation in Transition-Metal CatalysisInproceedings Konferenzbeitrag4-Sep-2023
20Mähr, Martin ; Talmazan, Radu Alexandru ; Podewitz, Maren Localizing Transition-States of Diffusion Controlled Reactions – Application to Inorganic ComplexesInproceedings KonferenzbeitragSep-2023