Materials Science & Engineering

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Author: search.filters.author.Bai, Qiang

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    Unsupervised discovery of solid-state lithium ion conductors
    (Springer Nature, 2019-11-20) Zhang, Ying; He, Xingfeng; Chen, Zhiqian; Bai, Qiang; Nolan, Adelaide M.; Roberts, Charles A.; Banerjee, Debasish; Matsunaga, Tomoya; Mo, Yifei; Ling, Chen
    Although machine learning has gained great interest in the discovery of functional materials, the advancement of reliable models is impeded by the scarcity of available materials property data. Here we propose and demonstrate a distinctive approach for materials discovery using unsupervised learning, which does not require labeled data and thus alleviates the data scarcity challenge. Using solid-state Li-ion conductors as a model problem, unsupervised materials discovery utilizes a limited quantity of conductivity data to prioritize a candidate list from a wide range of Li-containing materials for further accurate screening. Our unsupervised learning scheme discovers 16 new fast Li-conductors with conductivities of 10−4–10−1 S cm−1 predicted in ab initio molecular dynamics simulations. These compounds have structures and chemistries distinct to known systems, demonstrating the capability of unsupervised learning for discovering materials over a wide materials space with limited property data.
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    First Principles Computational Design of Solid Ionic Conductors through Ion Substitution
    (2019) Bai, Qiang; Mo, Yifei; Material Science and Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Solid ionic conductors are key components of energy storage and conversion devices. To achieve high efficiency in these energy devices, solid ionic conductors should demonstrate high ionic or electronic conductivity. While pristine materials often suffer from poor conductivity, substituting ions in materials can tailor their electronic and ionic transport to fulfill requirements of transport properties in energy devices. In this dissertation, I applied first-principles computational techniques to elucidate the effect of ion substitution on electronic and ionic transport properties of solid materials. Therefore, three representative materials SrCeO3, La2-x-ySrx+yLiH1-x+yO3-y, and Li6KTaO6 are investigated as model systems to elucidate how ion substitution can affect the transport of electron, anion, and cation, respectively. I studied SrCeO3 as a model material to uncover the effects of B-site dopants on electronic transport. Based on theoretical calculations, I confirmed a polaron mechanism, including polaron formation and hopping, contributed to the electronic conductivity of SrCeO3. I found different dopants exhibit distinct capabilities for localizing electron polarons, and therefore result in different electronic conductivities in doped SrCeO3. The study demonstrated the capabilities of first principles computation to design new materials with desired polaron formation and migration. I studied La2-x-ySrx+yLiH1-x+yO3-y oxyhydrides as a model material to investigate H- diffusion mechanism in a mixed anion system and its relationship with the cation substitution of Sr2+ to La3+. I found the substitution of Sr2+ to La3+ can alter the H- diffusion mechanism from 2D to 3D pathways. Increasing H- vacancies through Sr2+ to La3+ substitution can also expedite the H- conductivity of the oxyhydrides. Based on the new understanding, a number of promising dopants in Sr2LiH3O were predicted to enhance H- transport. Fast Li-ion conductor materials as solid electrolytes are crucial for the development of all-solid-state Li-ion batteries. I systematically studied Li+ diffusion mechanisms in Li6KTaO6 predicted by our computational study. I found that different carrier defects such as Li vacancies or interstitials can induce distinct Li+ transport mechanisms. In addition, I developed a computational workflow to predict a wide range of materials in a prototype structure. By employing the workflow, I computationally predicted a group of Li superionic conductors with good stabilities by substituting the Li6KTaO6 structure.