Peer-Reviewed Publications

A. Jeindl, L. Hörmann, O. T. Hofmann
How much does surface polymorphism influence the work function of organic/metal interfaces?
Applied Surface Science 2021
https://www.sciencedirect.com/science/article/pii/S0169433221027318
J. J. Cartus, A. Jeindl, O. T. Hofmann
Can We Predict Interface Dipoles from Molecular Properties?
ACS Omega 2021
https://pubs.acs.org/doi/abs/10.1021/acsomega.1c05092

A. Werkovits, A. Jeindl, L. Hörmann, J. J. Cartus, O. T. Hofmann
Toward Targeted Kinetic Trapping of Organic−Inorganic Interfaces: A Computational Case Study
ACS Physical Chemistry Au 2021
https://doi.org/10.1021/acsphyschemau.1c00015

A. Jeindl, J. Domke, L. Hörmann, F. Sojka, R. Forker, T. Fritz, O. T. Hofmann,
Nonintuitive Surface Self-Assembly of Functionalized Molecules on Ag(111)
ACS Nano 2021, acsnano.0c10065.
https://doi.org/10.1021/acsnano.0c10065

O. T. Hofmann, E. Zojer, L. Hörmann, A. Jeindl, R. J. Maurer,
First-Principles Calculations of Hybrid Inorganic-Organic Interfaces: From State-of-the-Art to Best Practice.
Phys. Chem. Chem. Phys. 2021, 10.1039.D0CP06605B.
https://doi.org/10.1039/D0CP06605B

L. Hörmann, A. Jeindl, O. T. Hofmann
Reproducibility of potential energy surfaces of organic/metal interfaces on the example of PTCDA on Ag (111).
The Journal of Chemical Physics. 2020, 14;153(10):104701. 
https://doi.org/10.1063/5.0020736
A. T. Egger, L. Hörmann, A. Jeindl, M. Scherbela, V. Obersteiner, M. Todorović, P. Rinke, O. T. Hofmann,
Charge Transfer into Organic Thin Films: A Deeper Insight through Machine‐Learning‐Assisted Structure Search.
Advanced Science. 2020, 7(15):2000992.
https://doi.org/10.1002/advs.202000992

E. Wruss, L. Hörmann, O. T. Hofmann
Impact of surface defects on the charge transfer at inorganic/organic interfaces.
The Journal of Physical Chemistry C. 2019, 1;123(12):7118-24.
https://doi.org/10.1021/acs.jpcc.8b11403

L. Hörmann, A. Jeindl, A. T. Egger, M. Scherbela, O. T. Hofmann
SAMPLE: Surface structure search enabled by coarse graining and statistical learning.
Computer physics communications. 2019, 1;244:143-55.
https://doi.org/10.1016/j.cpc.2019.06.010
M. Scherbela, L. Hörmann, A. Jeindl, V. Obersteiner, O. T. Hofmann
Charting the energy landscape of metal/organic interfaces via machine learning.
Physical Review Materials. 2018, 17;2(4):043803.
https://doi.org/10.1103/PhysRevMaterials.2.043803

V. Obersteiner, M. Scherbela, L. Hörmann, D. Wegner, O. T. Hofmann
Structure prediction for surface-induced phases of organic monolayers: overcoming the combinatorial bottleneck.
Nano letters. 2017. 12;17(7):4453-60.
https://doi.org/10.1021/acs.nanolett.7b01637