Publications of Christian Carbogno

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Carbogno, C.:

Fiebig, F.: Assessing Electronic Transport in Solid Materials via the Fluctuation-Dissipation Theorem. Technische Universität Berlin

Zhu, X.: Ab Initio Green-Kubo Calculations for Strongly Anharmonic Solids: A comparative Benchmark of Lattice Thermal Conductivities. Technische Universität Darmstadt

Ahmetcik, E.: Machine Learning of the Stability of Octet Binaries. Technische Universität Berlin

Kokott, S., F. Merz, Y. Yao, C. Carbogno, M. Rossi, V. Havu, M. Rampp, M. Scheffler and V. Blum: Efficient All-electron Hybrid Density Functionals for Atomistic Simulations Beyond 10,000 Atoms., in press.

Lu, S., L.M. Ghiringhelli, C. Carbogno, J. Wang and M. Scheffler: On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials., in press.

Speckhard, D., C. Carbogno, L.M. Ghiringhelli, S. Lubeck, M. Scheffler and C. Draxl: Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models., in press.

Acosta, C.M., R. Ouyang, A. Fazzio, M. Scheffler, L.M. Ghiringhelli and C. Carbogno: Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing., in press.

Ghiringhelli, L.M., C. Carbogno, S.V. Levchenko, F.R. Mohamed, G. Huhs, M. Lüders, M. Oliveira and M. Scheffler: Towards a Common Format for Computational Materials Science Data. (131), 1–16 (2016).

Ghiringhelli, L.M., C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C.T. Koch, M. Kühbach, A.N. Ladines, P. Lambrix, M.-O. Himmer, S.V. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G.-M. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll and M. Scheffler: Shared Metadata for Data-Centric Materials Science. Scientific Data 10, 626 (2023).