Structure and atomic dynamics in condensed matter under pressure and Li-ion battery materials

The main goal of this research was to apply first-principles electronic structure calculations to investigate atomic motions in several condensed materials. This thesis consists of five separate but related topics that are classified into two main categories: structure of materials under pressure and Li ion dynamics in lithium battery materials. The atomic structure of liquid gallium was investigated in order to resolve a controversy about an anomalous structural feature observed in the x-ray and neutron scattering patterns. We explored the pressure effect when modifying the liquid structure close to the solid-liquid melting line. The atomic trajectories obtained from first-principles molecular dynamics (FPMD) calculations were examined. The results clarified the local structure of liquid gallium and explained the origin of a peculiar feature observed in the measured static structure factor. We also studied the structure of a recently discovered phase-IV of solid hydrogen over a broad pressure range near room temperature. The results revealed novel structural dynamics of hydrogen under extreme pressure. Unprecedented large amplitude fluxional atomic dynamics were observed. The results helped to elucidate the complex vibrational spectra of this highly-compressed solid. The atomic dynamics of Li ions in cathode, anode, and electrolyte materials - the three main components of a lithium ion battery - were also studied. On LiFePO4, a promising cathode material, we found that in addition to the commonly accepted one-dimensional diffusion along the Li channels in the crystal structure, a second but less obvious multi-step Li migration through the formation of Li-Fe antisites was identified. This discovery confirms the two-dimensional Li diffusion model reported in several Li conductivity measurements and illustrates the importance of the distribution of intrinsic defects in the enhancement of Li transport ability. The possibility of using type-II clathrate Si136 as an anode material was investigated. It was found that lithiated Si-clathrates are intrinsic metals and their crystal structures are very stable. Calculations revealed the charge and discharge voltages are very low and almost independent of the Li concentrations, an ideal property for an anode material. Significantly, migration pathways for Li ions diffusing through the cavities of the clathrate structures were found to be rather complex. Finally, the feasibility of a family of Li3PS4 crystalline and nanoporous cluster phases were studied for application as solid electrolytes. It was found that the ionic conductivity in the nanocluster is much higher than in crystalline phases. It is anticipated that the knowledge gained in the study of battery materials will assist in future design of new materials with improved battery charge and discharge performance

MoS2_2 2D-polymorphs as a Li-/Na-ion batteries: 1T' vs 2H phases

In this study, we compare the performance of two phases of MoS$_2$ monolayers: 1T' and 2H, about their ability to adsorb lithium and sodium ions. Employing the density functional theory and molecular dynamics, we include the ion concentration to analyze the electronic structure, ion kinetics, and battery performance. The pristine 2H-MoS$_2$ monolayer is the ground state. However, the charge transfer effects above a critical ion concentration yields a stability change, where the 1T'-MoS$_2$ monolayer with adsorbed ions becomes more stable than the 2H counterpart. The diffusion of ions onto the 1T' monolayer is anisotropic, being more efficient at ion adsorption than the 2H phase. Finally, we calculate the open circuit voltage and specific capacity, confirming that the 1T'-MoS$_2$ phase has great potential for developing lithium/sodium ion batteries.Comment: 27 pages 7 figure

Surveying the Energy Landscapes of Multistable Elastic Structures

Energy landscapes analysis is a versatile approach to study multistable systems by identifying the network of stable states and reconfiguration pathways. Thus far, it has primarily been used in microscale systems, such as studying chemical reaction rates and to characterise the behaviour of how protein fold. Here, however, we aim to utilise energy landscape techniques to study multistable elastic structures, in particular, complex 3D structures that have been buckled from 2D patterns, which are of interest for applications such as flexible electronics and microelectromechanical systems. To this end we have developed new energy landscape methods and software that are well suited to continuous, macroscale systems with many degrees of freedom. The first is the binary image transition state search method (BITSS), which offers greater efficiency for large scale systems compared to traditional transition state search methods, and it is well suited to complex, non-linear pathways. Next, a new software library is introduced that contains a variety of energy landscape methods and potentials which are parallelised to study large-scale continuous systems. This library can be flexibly used for any chosen application, and has been designed to be easily extensible for new methods and potentials. Furthermore, we exploit energy landscape analysis to tailor the stable states and reconfiguration paths of various reconfigurable buckled mesostructures. We establish stability phase diagrams and identify the corresponding available reconfiguration pathways by varying essential structural parameters. Furthermore, we identify how the introduction of creases affects the multistability of the structures, finding that a small number can increase the number of distinct states, but more creases can lead to a loss of multistability. Taken together, these results and methodology can be used to influence the design of new structures for a variety of different applications

Development of computational methods for electronic structural characterization of strongly correlated materials: from different ab-initio perspectives

The electronic correlations in materials drive a variety of fascinating phenomena from magnetism to metal-to-insulator transitions (MIT), which are due to the coupling between electron spin, charge, ionic displacements, and orbital ordering. Although Density Functional Theory (DFT) successfully describes the electronic structure of weakly interacting material systems, being a static mean-field approach, it fails to predict the properties of Strongly Correlated Materials (SCM) that include transition and rare earth metals where there is a prominent electron localization as in the case of d and f orbitals due to the nature of their spatial confinement. Dynamical Mean Field Theory (DMFT) is a Green’s function based method that has shown success in treating SCM. This dissertation focuses on the development of a user-friendly, open-source Python/Fortran framework, “DMFTwDFT” combining DFT and DMFT to characterize properties of both weakly and strongly correlated materials. The DFT Kohn- Sham orbitals are projected onto Maximally Localized Wannier Functions (MLWF) which essentially maps the Hubbard model to a local impurity model which we solve numerically using quantum Monte Carlo methods to capture both itinerant and localized nature of electrons. Additionally, we provide a library mode for computing the DMFT density matrix which can be linked and internally called from any DFT package allowing developers of other DFT codes to interface with our package and achieve full charge-self-consistency within DFT+DMFT. We then study the stability and diffusion of oxygen vacancies in the correlated material LaNiO3. By treating Ni-d as correlated orbitals along with a Ni-O hybridization manifold, we show that certain configurations undergo a MIT based on the environment of their vacancies. We also compute the transition path energy of a single oxygen vacancy through means of the nudged elastic band (NEB) method. We show that the diffusion energy profile calculated through DFT+U differs from that of DMFT, due to correlation effects that are not quite well captured with static mean-field theories. Additionally, DMFTwDFT was utilized to study strongly correlated alloys and materials useful for neuromorphic computing applications

ZnSnS 3

The rapid growth of the solar energy industry is driving a strong demand for high performance, efficient photoelectric materials. In particular, ferroelectrics composed of earth-abundant elements may be useful in solar cell applications due to their large internal polarization. Unfortunately, wide band gaps prevent many such materials from absorbing light in the visible to mid-infrared range. Here, we address the band gap issue by investigating the effects of substituting sulfur for oxygen in the perovskite structure ZnSnO3. Using evolutionary methods, we identify the stable and metastable structures of ZnSnS3 and compare them to those previously characterized for ZnSnO3. Our results suggest that the most stable structure of ZnSnS3 is the monoclinic structure, followed by the metastable ilmenite and lithium niobate structures. The latter structure is highly polarized, possessing a significantly reduced band gap of 1.28 eV. These desirable characteristics make it a prime candidate for solar cell applications