Accelerated ab initio molecular dynamics: plastic deformation in ceramics

NAISS 2023/6-12


NAISS Medium Storage

Principal Investigator:

Davide Sangiovanni


Linköpings universitet

Start Date:


End Date:


Primary Classification:

10304: Condensed Matter Physics




Machine-learning interatomic potentials (CMD) and density-functional ab initio molecular dynamics (AIMD) are used to investigate the mechanical properties and phase stability of novel high-entropy ceramics and superlattice structures up to temperatures (>1000 K) or relevance for practical uses. The project is a theoretical-experimental collaboration between LiU, TUWien (Austria), Comenius University (Slovakia) and University of California San Diego and includes a large part of activities of FunMat II consortium. The theoretical investigations are based on methods developed by the PI. Financial support: VR Etablering Grant Nº VR-2021-04426, VINN Excellence Center Functional Nanoscale Materials FunMat-2 prolonged to 2027 (Grant 2022-03071), Olle Engkvist Foundation, Austrian Academy of Sciences, ‎ÖAW, via the DOC fellowship, KUWI grant from TU Wien, Hertha Firnberg Programme. During 2021-present, we published 14 papers +4 in review. SNIC resources are acknowledged in all publications. 1. A Kakanakova, ... DG Sangiovanni, et al. MOCVD of AlN on epitaxial graphene at extreme temperatures CrystEngComm 23, 385 (2021) 2. M Mikula, ... DG Sangiovanni Thermally induced structural evolution and age-hardening of polycrystalline V1–xMoxN (x≈0.4) thin films Surface and Coatings Technology 405, 126723 (2021) 3. D.G. Sangiovanni, et al. Temperature-dependent elastic properties of binary and multicomponent high-entropy refractory carbides Materials & Design 204 (2021) 109634 4. M. Zarshenas, ..., D.G. Sangiovanni, K. Sarakinos, Room-temperature diffusion of metal clusters on graphene Physical Chemistry Chemical Physics 23, 13087 (2021) 5. D.G. Sangiovanni, ..., K.S. Vecchio Enhancing plasticity in high-entropy refractory ceramics via tailoring valence electron concentration Materials & Design 209, 109932 (2021) 6. H. Levämäki,..., D.G. Sangiovanni, et al., Predicting elastic properties of hard-coating alloys using ab-initio and machine learning methods, NPJ Computational Materials 8, 17 (2022) 7. N. Koutná, ..., D.G. Sangiovanni, Atomistic mechanisms underlying plasticity and crack growth in ceramics: a case study of AlN/TiN, Acta Materialia 229, 117809 (2022) 8. O Dippo, D.G. Sangiovanni et al., Color and pseudogap tunability in multicomponent carbonitrides, Materials & Design 217, 110600 (2022) 9. J Buchinger, N Koutna, et al, Heavy-element-alloying for toughness enhancement of hard nitrides on the example Ti-W-N, Acta Materialia 231, 117897 (2022) 10. Z Gao, ..., N Koutná, et al., Ab initio supported development of TiN/MoN thin films with improved hardness and toughness, Acta Materialia 231, 117871 (2022) 11. T Fiantok, ... N Koutná, et al., Structure evolution and mechanical properties of ternary ZrAlB2 sputtered thin films, Journal of Vacuum Science & Technology A 40, 033414 (2022) 12. J. Salamania, D.G. Sangiovanni, et al., Elucidating dislocation core structures in titanium nitride through high-resolution imaging and atomistic simulations, Materials & Design 224 (2022) 111327 13. DG Sangiovanni, et al. Discovering atomistic pathways for supply of metal atoms from methyl-based precursors to graphene surface, Physical Chemistry Chemical Physics 25 (2023) 829 14. H. Levämäki, … D.G. Sangiovanni, et al. HADB: A materials-property database for hard-coating alloys, Thin Solid Films 766 (2023) 139627