Global ETD Search

Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

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Showing 1 to 11 of 11 for “"Materials Informatics"”.

  1. Data-driven Materials Informatics for Optoelectronics: From Natural Language Processing to Predictive Modelling of TADF Molecules

    … and application of data-driven approaches to materials informatics for optoelectronics, with a focus on thermally-activated delayed fluorescence (TADF). Chapter 1 provides an introduction to the background and recent progress in data-driven methods in materials sciences and thermally-activated …

    cambridge Repository record for Data-driven Materials Informatics for Optoelectronics: From Natural Language Processing to Predictive Modelling of TADF Molecules (opens in a new tab)

  2. Magnetic and Superconducting Materials Discovery: Employing Data Science, Natural Language Processing and Machine Learning

    This thesis focusses on the application of materials informatics to the study and discovery of inorganic compounds that exhibit magnetism and superconductivity. In particular, the materials discovery process is viewed through the lens of data-mining and natural language processing, by which large …

    cambridge Repository record for Magnetic and Superconducting Materials Discovery: Employing Data Science, Natural Language Processing and Machine Learning (opens in a new tab)

  3. Accelerating Materials Discovery for Optical Applications using Machine Learning, Natural Language Processing and Density Functional Theory

    … thesis presents a novel approach that combines materials informatics and theoretical calculations to accelerate the discovery of materials with desirable optical properties. Unlike traditional experimental research programmes, this work emphasises the significant contributions in terms of …

    cambridge Repository record for Accelerating Materials Discovery for Optical Applications using Machine Learning, Natural Language Processing and Density Functional Theory (opens in a new tab)

  4. A Systematic Framework for Feature Analysis, Selection, and Property Prediction of Chemical Materials Using Machine Learning

    … feature selection workflow within the field of materials informatics. Its utility is demonstrated via the prediction of various material properties across different research domains, including solid-state physics, condensed matter physics, materials science and engineering, as well as …

    cambridge Repository record for A Systematic Framework for Feature Analysis, Selection, and Property Prediction of Chemical Materials Using Machine Learning (opens in a new tab)

  5. Facilitating an Integrated Data-Centric Approach to Optimize Donor-Acceptor Copolymer Based Organic Field Effect Transistors

    … population underscore the need for innovative materials to develop efficient and affordable electronic devices. One such area grappling with this surge in demand is the realm of conjugated polymer (CP)--based electronic materials. These semiconducting polymers have emerged as promising …

    gatech Repository record for Facilitating an Integrated Data-Centric Approach to Optimize Donor-Acceptor Copolymer Based Organic Field Effect Transistors (opens in a new tab)

  6. Data-Driven Characterization of Micro-structural Shape and Topology in Engineering Materials

    … shape and topology in engineering materials, integrating invariant geometric descriptors and statistical dimensionality reduction techniques. Specifically, Hu moments, Principal Eigenvalue Moment (PEM), and Principal Component Analysis (PCA) are applied to a diverse dataset …

    vt Repository record for Data-Driven Characterization of Micro-structural Shape and Topology in Engineering Materials (opens in a new tab)

  7. Development of Multivariate Powder X-ray Diffraction Techniques and Total Scattering Analyses to Enable Informatic Calibration of Solid Dispersion Potential

    … central hypothesis states that a combination of materials properties exists that defines the propensity of an active pharmaceutical ingredient to form a binary amorphous molecular solid dispersion with polyvinylpyrrolidone:vinyl acetate copolymer using a melt-quench procedure. Testing this …

    duquesne Repository record for Development of Multivariate Powder X-ray Diffraction Techniques and Total Scattering Analyses to Enable Informatic Calibration of Solid Dispersion Potential (opens in a new tab)

  8. Accelerating Materials Discovery with Machine Learning

    … data to aid the discovery and development of new materials. We begin by looking at a traditional materials informatics task -- elucidating the structure-function relationships of high-temperature cuprate superconductors. One of the most significant challenges for materials informatics is the …

    cambridge Repository record for Accelerating Materials Discovery with Machine Learning (opens in a new tab)

  9. Optimization of Materials for Magnetic Refrigeration and Thermomagnetic Power Generation

    … has two main parts: one focusing on novel materials for energy harvesting; and another focusing on methods of materials discovery for refrigeration purposes. Thermomagnetic power generation (TMG) is the process by which magnetic flux, which comes from a temperature-driven change of …

    cuny-grad Repository record for Optimization of Materials for Magnetic Refrigeration and Thermomagnetic Power Generation (opens in a new tab)

  10. Data-driven PSP linkages for atomistic datasets

    For a variety of materials, atomic-scale modeling techniques are commonly employed as a means of investigating fundamental properties, including both structural and chemical responses. While force-field based calculations are significantly less computationally expensive than their …

    gatech Repository record for Data-driven PSP linkages for atomistic datasets (opens in a new tab)

  11. Calculation, utilization, and inference of spatial statistics in practical spatio-temporal data

    … scales to the performance characteristics of materials is a core premise of materials science. Spatial correlations in the form of n-point statistics have been shown to be very effective in robustly describing the structural features of a plethora of materials systems, with a high number of …

    gatech Repository record for Calculation, utilization, and inference of spatial statistics in practical spatio-temporal data (opens in a new tab)