Rishi Bodlos

Voids in face-centered cubic (fcc) metals are commonly assumed to form via the aggregation of vacancies; however, the mechanisms of vacancy clustering and diffusion are not fully understood. In this study, we use computational modeling to provide a detailed insight into the structures and formation energies of primary vacancy clusters, mechanisms and barriers for their migration in bulk copper, and how these properties are affected at simple grain boundaries. The calculations were carried out using embedded atom method (EAM) potentials and density functional theory (DFT) and employed the site-occupation disorder code (SOD), the activation relaxation technique nouveau (ARTn) and the knowledge led master code (KLMC). We investigate stable structures and migration paths and barriers for clusters of up to six vacancies. The migration of vacancy clusters occurs via hops of individual constituent vacancies with di-vacancies having a significantly smaller migration barrier than mono-vacancies and other clusters. This barrier is further reduced when di-vacancies interact with grain boundaries. This interaction leads to the formation of self-interstitial atoms and introduces significant changes into the boundary structure. Tetra-, penta-, and hexa-vacancy clusters exhibit increasingly complex migration paths and higher barriers than smaller clusters. Finally, a direct comparison with the DFT results shows that EAM can accurately describe the vacancy-induced relaxation effects in the Cu bulk and in grain boundaries. Significant discrepancies between the two methods were found in structures with a higher number of low-coordinated atoms, such as penta-vacancies and di-vacancy absortion by grain boundary. These results will be useful for modeling the mechanisms of diffusion of complex defect structures and provide further insights into the structural evolution of metal films under thermal and mechanical stress.

Voids in face-centered cubic (fcc) metals are commonly assumed to form by the aggregation of vacancies; however, the mechanisms of vacancy clustering and diffusion are not fully understood. In this study, we use computational modeling to provide a detailed insight into the structures and formation energies of primary vacancy clusters, mechanisms and barriers for their migration in bulk copper, and how these properties are affected at simple grain boundaries. The calculations were carried out using Embedded Atom Method (EAM) potentials and Density Functional Theory (DFT) and employed the Site-Occupation Disorder code (SOD), the Activation Relaxation Technique nouveau (ARTn) and the Knowledge Led Master Code (KLMC). We investigate stable structures and migration paths and barriers for clusters of up to six vacancies. Migration of vacancy clusters occurs via hops of individual constituent vacancies with di-vacancies having a significantly smaller migration barrier than mono-vacancies and other clusters. This barrier is further reduced when di-vacancies interact with grain boundaries. This interaction leads to the formation of self-interstitial atoms and introduces significant changes into the boundary structure. Tetra-, penta-, and hexa-vacancy clusters exhibit increasingly complex migration paths and higher barriers than smaller clusters. Finally, the direct comparison with the DFT results shows that EAM can accurately describe the vacancy-induced relaxation effects in the Cu bulk and in grain boundaries. Significant discrepancies between the two methods were found in structures with a higher number of low-coordinated atoms, such as penta-vacancies and di-vacancy absortion by grain boundary. These results will be useful for modeling the mechanisms of diffusion of complex defect structures and provide further insights into the structural evolution of metal films under thermal and mechanical stress.

Nanocrystalline alloy thin films offer a variety of attractive properties, such as high hardness, strength and wear resistance. A disadvantage is the large residual stresses that result from their fabrication by deposition, and subsequent susceptibility to defects. Here, we use experimental and modelling methods to understand the impact of minority element concentration on residual stresses that emerge after deposition in a tungsten-titanium film with different titanium concentrations. We perform local residual stress measurements using micro-cantilever samples and employ machine learning for data extraction and stress prediction. The results are correlated with accompanying microstructure and elemental analysis as well as atomistic modelling. We discuss how titanium enrichment significantly affects the stress stored in the nanocrystalline thin film. These findings may be useful for designing stable nanocrystalline thin films.

Cu/W composites are widely used in various industrial fields as they show thermomechanical properties suitable for a wide range of applications. Additionally, in semiconductor products, WTi in contact with Cu acts as a barrier material between Cu and Si/SiO₂. Therefore, the bonding behavior of both Cu/W and Cu/WTi is of great economical interest, also with respect to the effects that impurities could have on the behaviour of the Cu/W(Ti) interface. The segregation behavior of relevant impurities has not been studied in detail before. In this work, we create atomistic models of the Cu/W and Cu/WTi interfaces, compare their energetics to previously known interfaces and study the effect of segregation on the interface cohesion. We find that all investigated segregants, i.e. Ti, Cl, S, Al, H, O, and vacancies weaken the cohesion of the interface.

Nanocrystalline metallic alloy thin films provide a variety of interesting properties. A disadvantage concerns their inherent instability and generation of residual stresses. Here, we present a unique framework incorporating machine learning assisted experimental and modelling methods to perceive the impact of the minority element concentration on the generated residual stresses within a nanocrystalline thin film. As a candidate system we use a W-Ti alloy thin film with different Ti concentrations. We perform machine-learning assisted local residual stress measurements, correlate the results with accompanied microstructure and elemental analysis and apply density functional theory. We inquire why the experimental observed Ti enrichment can be strongly reduced at smaller concentrations and discuss how it significantly effects the stress stored in the nanocrystalline thin film. The presented perception is highly crucial to yield future design guidelines for more stable nanocrystalline thin films.

WTi is used as an adhesive layer in integrated circuit devices. The temperature dependent mechanical properties of WTi are still largely unexplored. In this paper we investigate WTi solid solutions with density functional theory calculations to determine the temperature and concentration dependent behavior of volume and coefficient of thermal expansion. The coefficient of thermal expansion is analyzed in terms of the bulk modulus, heat capacity, and Grüneisen parameter. Furthermore, we gain insight into the bonding of the system via investigation of the electronic structure, phonon density of states, and analysis of the formation energy. Low Ti concentrations lead to strong W-Ti bonding, as manifested in additional high frequency peaks in the phonon density of states. As a consequence, deviations from Vegard's law are found at low Ti concentrations, with a minimum of the lattice constant at about 15 at. % Ti. The CTE as a function of Ti concentration shows a negative trend at low temperatures and Ti concentrations, which is related to a strong decrease of heat capacity. Finally we show that the Debye-Grüneisen model yields results for WTi comparable to the quasiharmonic approach at a fraction of the computational cost.