Publications "Margraf, Johannes T."

Jakob, Konstantin S. ; Walsh, Aron ; Reuter, Karsten ; Margraf, Johannes T.:
Learning Crystallographic Disorder : Bridging Prediction and Experiment in Materials Discovery.
In: Advanced Materials. Vol. 38 (2026) Issue 5 . - e14226.
ISSN 1521-4095
DOI der Verlagsversion: https://doi.org/10.1002/adma.202514226

Strothmann, Robert ; Amanpur, Mehran ; Neveselý, Tomáš ; Hecht, Stefan ; Reuter, Karsten ; Margraf, Johannes T.:
Machine learning driven design of spiropyran photoswitches.
In: Digital Discovery. Vol. 4 (2025) Issue 11 . - pp. 3098-3108.
ISSN 2635-098X
DOI der Verlagsversion: https://doi.org/10.1039/D5DD00327J

Cui, Mengnan ; Reuter, Karsten ; Margraf, Johannes T.:
Multi-fidelity transfer learning for quantum chemical data using a robust density functional tight binding baseline.
In: Machine Learning: Science and Technology. Vol. 6 (2025) Issue 1 . - 015071.
ISSN 2632-2153
DOI der Verlagsversion: https://doi.org/10.1088/2632-2153/adc222

Keller, Elisabeth ; Blum, Volker ; Reuter, Karsten ; Margraf, Johannes T.:
Exploring atom-pairwise and many-body dispersion corrections for the BEEF-vdW functional.
In: The Journal of Chemical Physics. Vol. 162 (2025) Issue 7 . - 074111.
ISSN 0021-9606
DOI der Verlagsversion: https://doi.org/10.1063/5.0248728

Ulrich, Anke Silvia ; Kasatikov, Sergey ; König, Till ; Fantin, Andrea ; Margraf, Johannes T. ; Galetz, Mathias C.:
Decreased Metal Dusting Resistance of Ni-Cu Alloys by Fe and Mn Additions.
In: High Temperature Corrosion of Materials. Vol. 101 (2024) . - pp. 1301-1314.
ISSN 2731-8400
DOI der Verlagsversion: https://doi.org/10.1007/s11085-024-10263-w

Margraf, Johannes T.:
Neural graph distance embedding for molecular geometry generation.
In: Journal of Computational Chemistry. Vol. 45 (2024) Issue 21 . - pp. 1784-1790.
ISSN 1096-987X
DOI der Verlagsversion: https://doi.org/10.1002/jcc.27349

Keller, Elisabeth ; Morgenstein, Jack ; Reuter, Karsten ; Margraf, Johannes T.:
Small basis set density functional theory method for cost-efficient, large-scale condensed matter simulations.
In: The Journal of Chemical Physics. Vol. 161 (2024) Issue 7 . - 074104.
ISSN 0021-9606
DOI der Verlagsversion: https://doi.org/10.1063/5.0222649