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Introduction

Texas ScholarWorks was established to provide open, online access to the products of the University's research and scholarship, to preserve these works for future generations, to promote new models of scholarly communication, and to help deepen community understanding of the value of higher education.

UT Tower and campus image credit: Earl McGehee, CC-BY, https://www.flickr.com/photos/ejmc/7452145850

 

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Recent Submissions

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Fast-charging lithium metal batteries enabled by engineering tetrahydrofuran-based electrolytes
(2024-05) Paul-Orecchio, Austin; Mullins, C. B.; David Mitlin, Hang Ren, Michael Aubrey; Michael Aubrey; Hang Ren
There has been significant interest from academic and industrial sectors to use lithium metal anodes in energy storage devices due to their superior energy density (3860 mAh/g) compared with conventional, graphite-based counterparts. However, the safety and inefficiency concerns arising from dendritic lithium formation prohibit their widespread adoption. This dissertation focuses on preventing dendrites by engineering a tetrahydrofuran-based electrolyte mixture (LiFSI-THFMix) with alloying M-nitrate (M: Ag, Bi, Ga, In, Zn) additives. Through a simple in situ solution, lithium metal anodes can withstand stable lithium metal plating during fast-charging conditions. Notably, Zn-protected cells achieve the lowest overpotential (156 mV) and longest cycle stability (140 cycles) during ultra-fast 10.0 mA cm⁻² Li||Li cycling. Additionally, C/2 Li||LFP full cells demonstrate the highest capacity (134 mAh g⁻¹) and capacity retention (89.2%) after 400 cycles. Their success was attributed to a robust passivation layer (LiF, Li₃N, LiNₓOᵧ) and lithiophilic alloy (LiZn), enhancing Li⁺ diffusion and plating. Overall, this dissertation highlights tetrahydrofuran-based electrolyte mixtures and alloying nitrate additives as promising solutions enabling next-generation lithium metal batteries.
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The discovery and design of rare-earth-free magnets using machine learning
(2024-05) Liao, Timothy; Chelikowsky, James R.; Alex Demkov; Feliciano Giustino; Keji Lai; Gyeong Hwang
In today's rapidly advancing technological landscape, the reliance on powerful magnets spans various sectors, including advanced technology and green energy. These magnets, integral to the functionality of devices like wind turbines, electric cars, and computer hard disks, often feature rare-earth elements such as neodymium or samarium. Given the supply risks associated with rare-earth elements, my dissertation research focuses on discovering strong magnets without them. I leverage efficient first principles calculations and machine learning to accelerate the typically slow trial-and-error method in experiments. This presentation outlines the efforts, culminating in the discovery of a new material, Fe₃CoB₂. Initially, I establish a magnetic materials database encompassing magnetization (i.e., magnetic strength), magnetic anisotropy (i.e., magnetic field resilience), and Curie temperature (i.e., heat resilience). Then, I enhance the functionality of a popular machine learning model to predict both macroscopic and microscopic properties, validated through high-throughput first-principles calculations on Fe-Co-N. Following successful machine learning model testing, I introduce an adaptive machine learning feedback system for efficient materials discovery. This framework streamlines the computational discovery and experimental synthesis of Fe₃CoB₂, reducing the process to mere days. Building on this achievement, I extend the search to Fe-Co-Si compounds, expected to be compatible with a Si substrate. Finally, I evaluate the performance of our top candidate Fe-Co-X (X = N, B, Si, P, and C) structures against common rare-earth and rare-earth-free magnets.
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Rest-frame UV colors for faint galaxies at z ∼ 9 − 16 with the JWST NGDEEP survey
(2024-05) Morales, Alexa M. ; Finkelstein, Steven L.; Bromm, Volker; Casey, Caitlin M.; Berg, Danielle
We present measurements of the rest-frame UV spectral slope, β, for a sample of 36 faint star-forming galaxies at z ∼ 9 − 16 discovered in one of the deepest JWST NIRCam surveys to date, the Next Generation Deep Extragalactic Exploratory Public (NGDEEP) Survey. We use robust photometric measurements for UV-faint galaxies (down to M [subscript UV] ∼ −16), originally published in Leung et al. (2023), and measure values of the UV spectral slope via photometric power-law fitting to both the observed photometry and to stellar population models obtained through spectral energy distribution (SED) fitting with Bagpipes. We obtain a median and 68% confidence interval for β from photometric power-law fitting of β [subscript PL] = −2.7 [superscript +0.5 over subscript −0.5] and from SED-fitting, β [subscript SED] = −2.3 [superscript +0.2 over subscript −0.1] for the full sample. We show that when only 2-3 photometric detections are available, SED-fitting has a lower scatter and reduced biases than photometric power-law fitting. We quantify this bias and find that after correction, the median β [subscript SED,corr] = −2.5 [superscripg +0.2 over subscript −0.2]. We measure physical properties for our galaxies with BAGPIPES and find that our faint (M [subscript UV] = −18.1 [superscript +0.7 over subscript −0.9]) sample is low mass (log[M [subscript ∗]/M [subscript ⊙]] = 7.7 [superscript +0.5 over subscript −0.5]), fairly dust-poor (A [subscript v] = 0.1 [superscript +0.2 over subscript −0.1] mag), and modestly young (log[age] = 7.8 [superscript +0.2 over subscript −0.8] yr) with a median star formation rate of log(SFR) = −0.3 [superscript +0.4 over subscript −0.4]M [subscript ⊙]/yr. We find no strong evidence for ultra-blue UV spectral slopes (β ∼ −3) within our sample, as would be expected for exotically metal-poor (Z/Z [subscript ⊙]< 10⁻³) stellar populations with very high Lyman-continuum escape fractions. Our observations are consistent with model predictions that galaxies of these stellar masses at z ∼ 9 − 16 should have only modestly low metallicities (Z/Z [subscript ⊙]∼ 0.1–0.2).
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An exploratory content analysis of comments and thumbnails of YouTube mukbang videos using computational methods
(2024-05) Kim, Hyun Ji, M.A.; Love, Brad (Ph. D. in media and information studies); Jihye Lee
Mukbang continues to thrive on YouTube, originating as a trend but ultimately becoming ingrained in a cultural phenomenon. Nevertheless, the impact of Mukbang on individuals' eating patterns is a subject of debate. Mukbang videos can have negative consequences, such as weight gain and the development of eating disorders. Therefore, it is crucial to comprehend the viewers' perceptions of these videos. This study is exploratory research that utilizes computational methods to analyze comments and investigate the sentiment and emotion of the viewers. The mention of food cravings and YouTuber names is also being observed to find out if people focus on food or the YouTuber while they watch the video. Additionally, the visual attributes of the video thumbnails are examined to explore the visual characteristics of popular Mukbang videos. The results indicate that the dominant sentiment and emotion expressed by the people were 'positive' and 'happiness'. Additionally, the study reveals that the group that mentions craving or YouTubers showed a distinct sentiment from the group that does not. Visual analysis revealed that common characteristics observed in popular Mukbang videos include the use of warm colors and the inclusion of a person's face in their thumbnails.
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Cu-catalyzed three-component carboamination of vinylcyclopropanes
(2024-05) Skumial, Piotr ; Hull, Kami; Anslyn, Eric V.
This thesis introduces and explores the expanding field of applications for three-membered carbocycles, which has seen a resurgence recently. Traditionally, the utility of these small rings in organic chemistry was largely shown in radical clock experiments for elucidating reaction mechanisms. However, the past decades has seen their use broaden significantly due to advances in transition metal catalysis. Three-membered carbocycles, such as cyclopropenes, methylenecyclopropanes, vinylcyclopropanes, and cyclopropanes, are crucial for constructing complex molecular architectures due to their unique structural and electronic properties. These characteristics facilitate a diverse array of chemical transformations, making them versatile building blocks in synthetic chemistry. This work is devoted to the development of vinylcyclopropane chemistry, with a focus on the copper-catalyzed procedure that enable regioselective ring-opening and 1,5-carboamination difunctionalizations. These methodologies are crucial for the efficient construction of nitrogen-containing organic compounds, which are key in the development of pharmaceuticals, agrochemicals, and functional materials. A broad substrate scope with good functional group tolerance is demonstrated. Additionally, mechanistic insights of the reaction are discussed.