TY - CONF A1 - Ertural, Christina A1 - Deringer, V. L. A1 - George, Janine T1 - Automation of machine learning driven interatomic potential generation for predicting vibrational properties N2 - Investigating the phononic properties is beneficial for predicting low thermal conductivity thermoelectric materials.1–3 Employing density functional theory4 takes many calculation steps and consumes a lot of computational resources.5,6 Using machine learning driven interatomic potentials (MLIP, e.g., Gaussian approximation potential,8 GAP) opens up a faster route to phonons7 but in most cases, the potentials are specifically tailored for a certain compound. In this work, we automate the generation of such MLIPs in a Python code-based workflow, based on the automation tools atomate29 and pymatgen10 which combines the automatic DFT computations with the automated fitting of GAPs. Automation enables easier testing, benchmarking and validation.11 We aim to provide the workflow-generated potentials for storage in databases. T2 - 16th International conference on materials chemistry (MC16) CY - Dublin, Ireland DA - 03.07.2023 KW - Interatomic potentials KW - Machine learning KW - Phonons KW - Thermoelectrics PY - 2023 AN - OPUS4-57932 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ertural, Christina A1 - Deringer, V. A1 - George, Janine T1 - Automation of machine learning driven interatomic potential generation for predicting vibrational properties N2 - Knowing phonon properties is beneficial for predicting low thermal conductivity thermoelectric materials. Employing DFT consumes lots of computational resources. Using ML-driven interatomic potentials (MLIP, e.g., GAP) opens up a faster route, but most potentials are specifically tailored to a certain compound. We aim to generalize the MLIP generation in a Python code-based workflow, combining automatic DFT runs with automated GAP fits. Automation enables easier tests, benchmarks, and validation. T2 - SALSA Make and Measure Conference: Interfaces CY - Berlin, Germany DA - 13.09.2023 KW - Interatomic potentials KW - Machine learning KW - Phonons KW - Thermoelectrics KW - Automated workflows PY - 2023 AN - OPUS4-58374 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hildebrandt, R A1 - Seifert, M A1 - George, J A1 - Blaurock, S A1 - Botti, S A1 - Krautscheid, H A1 - Grundmann, M A1 - Sturm, C T1 - Determination of acoustic phonon anharmonicities via second-order Raman scattering in CuI N2 - We demonstrate the determination of anharmonic acoustic phonon properties via second-order Raman scattering exemplarily on copper iodide single crystals. The origin of multi-phonon features from the second-order Raman spectra was assigned by the support of the calculated 2-phonon density of states. In this way, the temperature dependence of acoustic phonons was determined down to 10 K. To determine independently the harmonic contributions of respective acoustic phonons, density functional theory in quasi-harmonic approximation was used. Finally, the anharmonic contributions were determined. The results are in agreement with earlier publications and extend CuI’s determined acoustic phonon properties to lower temperatures with higher accuracy. This approach demonstrates that it is possible to characterize the acoustic anharmonicities via Raman scattering down to zero-temperature renormalization constants of at least 0.1 cm−1. KW - Thermoelectrics KW - Thermal transport KW - Phonon interactions KW - Density functional theory KW - Phonons PY - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-593164 SN - 1367-2630 VL - 25 IS - 12 SP - 1 EP - 12 PB - IOP Publishing AN - OPUS4-59316 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -