TY - CONF A1 - Ertural, Christina A1 - George, Janine T1 - Vibe Check via Machine Learning: Testing the Prototype N2 - Vibrational properties play a key role in determining the stability and thermal conductivity behaviour of materials. The quasi- harmonic approximation gives insight into the phononic properties of a compound, but in the established way, i.e. density functional theory based methods, it takes many calculation steps and consumes a lot of resources to arrive at the desired results. Machine learning (ML) trained interatomic potentials (e.g. Gaussian approximation potential, GAP) pose an alternative to the traditional computation way of phonons. We develop a Python code based workflow which combines automation tools like atomate2 with ML to ease providing interactomic potentials for (quantum chemical) computations and databases. T2 - #RSCPoster Twitter conference 2023 CY - Online meeting DA - 28.02.2023 KW - Interatomic potentials KW - Machine learning KW - Phonons KW - Workflow PY - 2023 UR - https://twitter.com/cer5814012/status/1630547004462858240 AN - OPUS4-57059 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 - Bustamante, Joana A1 - Naik, Aakash Ashok A1 - Ertural, Christina A1 - Ueltzen, Katharina A1 - George, Janine T1 - Thermodynamic and Thermoelectric Properties of the Canfieldite, (Ag8SnS6 ), in the Quasi-Harmonic Approximation N2 - Argyrodite-type materials have lately sparked a lot of research interest due to their thermoelectric properties.One promising candidate is canfieldite (Ag8SnS6), which has a Pna21 orthorhombic crystal structure at room temperature (RT). Recently, a new low-temperature (LT) phase transition of canfieldite at 120K has been found. Here, we investigate structural, vibrational and thermodynamic properties of Ag8SnS6 at room- and low-temperature employing density functional theory (DFT) and lattice dynamics computations. Thermal properties calculations were based on the quasi-harmonic approximation (QHA) as implemented in phonopy. We achieve good agreement with experiments. Thermal properties such as the constant-pressure heat capacity (Cp) and thermal conductivity are very close to experimental measurements. Furthermore, we compared RT and LT Ag8SnS6 Grüneisen parameters with argyrodites analogues, Ag8XS6 (X = Sn, Si, Ge), to arrive at an improved T2 - 16th International conference on materials chemistry (MC16) CY - Dublin, Ireland DA - 03.07.2023 KW - Thermoelectric materials KW - DFT KW - QHA KW - Grüneisen parameter PY - 2023 AN - OPUS4-57887 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Naik, Aakash Ashok A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Phillip A1 - George, Janine T1 - A Quantum-Chemical Bonding Database for Solid-State Materials N2 - Understanding the chemistry and nature of individual chemical bonds is essential for materials design. Bonding analysis via the LOBSTER software package has provided valuable insights into the properties of materials for thermoelectric and catalysis applications. Thus, the data generated from bonding analysis becomes an invaluable asset that could be utilized as features in large-scale data analysis and machine learning of material properties. However, no systematic studies exist that conducted high-throughput materials simulations to curate and validate bonding data obtained from LOBSTER. Here we present an approach to constructing such a large database consisting of quantum-chemical bonding information. T2 - 16th International conference on materials chemistry (MC16) CY - Dublin, Ireland DA - 03.07.2023 KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 AN - OPUS4-57889 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bustamante, Joana A1 - Naik, Aakash Ashok A1 - Ueltzen, Katharina A1 - Ertural, Christina A1 - George, Janine T1 - Thermodynamic and Thermoelectric Properties of the Canfieldite, (Ag8SnS6 ), in the Quasi-Harmonic Approximation N2 - Argyrodite-type materials have lately sparked a lot of research interest due to their thermoelectric properties. One promising candidate is canfieldite (Ag8SnS6), which has a Pna21 orthorhombic crystal structure at room temperature (RT). Recently, Slade group found a new low-temperature (LT) phase transition of canfieldite at 120K. Therefore, we investigate structural, vibrational and thermodynamic properties of Ag8SnS6 at room- and low-temperature employing density-functional theory (DFT) and lattice dynamics computations. Thermal properties calculations were based on the quasi-harmonic approximation (QHA) as implemented in phonopy. We achieve good agreement with experiments. Lattice parameters were overestimated by 2%, and thermal properties such as the constant-pressure heat capacity Cp are very close to experimental measurements. Our simulations also reveal a possible new phase transition at around 312 K. Furthermore, we compared RT and LT Ag8SnS6 Grüneisen parameters with some argyrodites analogues, Ag8TS6 (T = Si, Ge, Ti and Sn), finding a relationship between the anharmonicity and low thermal conductivity. T2 - TDEP Summer School 2023 (TDEP2023: Finite-temperature and anharmonic response properties of solids in theory and practice) CY - Linköping, Sweden DA - 20.08.2023 KW - Thermoelectric materials KW - DFT KW - QHA KW - Grüneisen parameter PY - 2023 AN - OPUS4-58147 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -