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Open Access Publications from the University of California

Scholarly Works (4 results)

  • Article
  • Peer Reviewed
UC Berkeley Previously Published Works (2024)
Three-dimensional lattices are fundamental to solid-state physics. The description of a lattice with an atomic basis constitutes the necessary information to predict solid phase properties and evolution. Here, we present an algorithm for systematically exploring crystallographic phase space. Coupled with ab initio techniques, such as density functional theory, this algorithm offers an approach for exploring and tuning materials behavior, with a broad range of potential applications: particularly martensitic phase transformations and materials stability.
    Cover page: Crystallographic map: A general lattice and basis formalism enabling efficient and discretized exploration of crystallographic phase spaceCreative Commons 'BY' version 4.0 license
    • Thesis
    • Peer Reviewed
    UC Berkeley Electronic Theses and Dissertations (2022)

    Structure-property relationships comprise the foundation of the field of Materials Science. When characterizing the structure of a crystalline solid, traditional approaches have focused on using three generating vectors to define a lattice. These vectors, when combined with offsets defining normalized positions of atoms within each identical unit cell, form the complete specification of a crystal. This intuitive definition forms the current standard for the field of materials science. However, this choice of definition is highly-redundant and obscures relationships between different crystal structures. For instance, there exists an infinite number unit cells and atomic offsets that can define the same crystal structure. Further, it is computationally and mathematically difficult to determine the perturbations necessary to transform one crystal structure into another.

    Here, outlined in this thesis, I propose a new scheme for specifying crystal structure based off the complementary ideas of a lattice-normal-form and a basis-normal-form. Together, these provide a unique fingerprint for each crystal structure that is a function only of physical geometry. Further, I develop a traversal algorithm that connects together every possible crystal structure via a series of neighbors, each of which represents a small perturbation to the original crystal geometry: either via a small strain or a small phonon mode amplitude.

    Building on this framework, I outline a new algorithm for exploring crystallographic phase space to find saddle points, and I re-derive known low-energy transformation pathways in the Zirconium crystal system. Together, this study and this framework show the power of a crystallographic map: a means to systematically explore crystallographic phase space. In this application we use the map to find saddle points; however, it is my hope that this new tool will lead to the elucidation and prediction of many more crystal phenomena.

      • Article
      • Peer Reviewed
      UC Berkeley Previously Published Works (2020)
      Discovering the ideal material for a new application involves determining its numerous properties, such as electronic, mechanical, or thermodynamic, to match those of its desired application. The rise of high-throughput computation has meant that large databases of material properties are now accessible to scientists. However, these databases contain far more information than might appear at first glance, since many relationships exist in the materials science literature to derive, or at least approximate, additional properties. propnet is a new computational framework designed to help scientists to automatically calculate additional information from their datasets. It does this by constructing a network graph of relationships between different materials properties and traversing this graph. Initially, propnet contains a catalog of over 100 property relationships but the hope is for this to expand significantly in the future, and contributions from the community are welcomed.
        Cover page: propnet: A Knowledge Graph for Materials Science
        • Article
        • Peer Reviewed
        LBL Publications (2017)
        Dielectrics are an important class of materials that are ubiquitous in modern electronic applications. Even though their properties are important for the performance of devices, the number of compounds with known dielectric constant is on the order of a few hundred. Here, we use Density Functional Perturbation Theory as a way to screen for the dielectric constant and refractive index of materials in a fast and computationally efficient way. Our results constitute the largest dielectric tensors database to date, containing 1,056 compounds. Details regarding the computational methodology and technical validation are presented along with the format of our publicly available data. In addition, we integrate our dataset with the Materials Project allowing users easy access to material properties. Finally, we explain how our dataset and calculation methodology can be used in the search for novel dielectric compounds.
          Cover page: High-throughput screening of inorganic compounds for the discovery of novel dielectric and optical materials
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