arXiv subjects

Taylor D. Sparks

Publications and source records attributed to Taylor D. Sparks.

16 recordsLinked to original sources

arXiv2025

Honegumi: An Interface for Accelerating the Adoption of Bayesian Optimization in the Experimental Sciences

Bayesian optimization (BO) has emerged as a powerful tool for guiding experimental design and decision-making in various scientific fields, including materials science, chemistry, and biology. However, despite its growing popularity, the complexity of existing BO libraries and the steep learning curve associated with them can deter researchers who are not well-versed in machine learning or programming. To address this barrier, we introduce Honegumi, a user-friendly, interactive tool designed to simplify the process of creating advanced Bayesian optimization scripts. Honegumi offers a dynamic selection grid that allows users to configure key parameters of their optimization tasks, generating ready-to-use, unit-tested Python scripts tailored to their specific needs. Accompanying the interface is a comprehensive suite of tutorials that provide both conceptual and practical guidance, bridging the gap between theoretical understanding and practical implementation. Built on top of the Ax platform, Honegumi leverages the power of existing state-of-the-art libraries while restructuring the user experience to make advanced BO techniques more accessible to experimental researchers. By lowering the barrier to entry and providing educational resources, Honegumi aims to accelerate the adoption of advanced Bayesian optimization methods across various domains.

cs.LG↗

arXiv2024

A quantized anomalous Hall effect above 4.2 K in stacked topological insulator/magnet bilayers

Quantized anomalous Hall effects (QAHEs) occur in remarkable electronic states which possess not only quantized Hall signals but in some cases regions of dissipationless electron transport. The initial demonstrations of a QAHE in a magnetically-doped topological insulator (TI) required temperatures below 100 mK, and since then a major focus of the field has been to increase the temperature scale. Here, we report quantized Hall signals up to 10 K (in what is known as the parity anomaly state) in TI/magnet bilayers made by mechanical assembly, rather than by conventional deposition techniques. This is a factor of 100 higher temperature than any previous realization of a QAHE in a proximity-coupled TI/magnet heterostructure made by deposition, and approximately twice the previous record for any QAHE system.

cond-mat.mes-hall↗

arXiv2024

Sampling Latent Material-Property Information From LLM-Derived Embedding Representations

Vector embeddings derived from large language models (LLMs) show promise in capturing latent information from the literature. Interestingly, these can be integrated into material embeddings, potentially useful for data-driven predictions of materials properties. We investigate the extent to which LLM-derived vectors capture the desired information and their potential to provide insights into material properties without additional training. Our findings indicate that, although LLMs can be used to generate representations reflecting certain property information, extracting the embeddings requires identifying the optimal contextual clues and appropriate comparators. Despite this restriction, it appears that LLMs still have the potential to be useful in generating meaningful materials-science representations.

cs.CL↗

arXiv2022

Effect of Sintering Conditions on the Microstructure and Electrochemical Properties of 6Scandia 1Ceria co-doped Zirconia (6Sc1CeZr)

The current work studies the effect of sintering conditions on the densification behavior, microstructure, and electrochemical performance of 6 mol% Sc2O3, 1 mol% CeO2 co-doped ZrO2 (6Sc1CeZr) for solid-state electrolyte applications. The specimen's physical properties and electrochemical performance sintered at different temperatures ranging from 1000 °C to 1700 °C for 6 hours are examined through diffraction, microscopy, and Raman and electrochemical impedance spectroscopy. The activation energy and pre-exponential conductivity factor of the oxygen ions are calculated using a linear fit to the Arrhenius-type conductivity equation. We observe that samples sintered at 1500 °C for 6h show a lower c/a axial ratio for the tetragonal phase, highest relative density, and highest total conductivity among all samples investigated. The higher total conductivity is explained by the formation of a higher symmetric tetragonal phase and the simultaneous existence of the cubic and tetragonal phases (with higher symmetry), supported by the presence of the cerium ions partially replaced zirconium ions' sites.

cond-mat.mtrl-sci↗

arXiv2022

Gate-tunable anomalous Hall effect in a 3D topological insulator/2D magnet van der Waals heterostructure

We demonstrate advantages of samples made by mechanical stacking of exfoliated van der Waals materials for controlling the topological surface state of a 3-dimensional topological insulator (TI) via interaction with an adjacent magnet layer. We assemble bilayers with pristine interfaces using exfoliated flakes of the TI BiSbTeSe2 and the magnet Cr2Ge2Te6, thereby avoiding problems caused by interdiffusion that can affect interfaces made by top-down deposition methods. The samples exhibit an anomalous Hall effect (AHE) with abrupt hysteretic switching. For the first time in samples composed of a TI and a separate ferromagnetic layer, we demonstrate that the amplitude of the AHE can be tuned via gate voltage with a strong peak near the Dirac point. This is the signature expected for the AHE due to Berry curvature associated with an exchange gap induced by interaction between the topological surface state and an out-of-plane-oriented magnet.

cond-mat.mes-hall↗

arXiv2022

Synthesis and Electrochemical Study of Multi-Phase, Multi-Species Ion Conductor Sodium beta"-Alumina (BASE) + 20SDC Using a Vapor-Phase Process

The recent emergence of multi-species multi-phase materials provides intriguing opportunities to maximize electrochemical performance in various electrochemical devices. This work summarizes the current understanding of the coupled transport reactions in multi-phase multi-species ionic conductors. We also provide experimental results of the fabrication of multi-phases Na-beta"-alumina+20mol% Scandia Doped Ceria(20SDC) as simultaneous sodium and oxygen ion conductor by a cost-effective vapor phase process demonstrating higher conductivity achieved in a much shorter time than other published results. In this study, two-phase contiguous composites of Al2O3+20SDC are fabricated by conventional ceramic processing and sintering in the air at 1400C 1500C, and 1600C, for 3 hours. The samples are heat-treated while exposed to a sodium oxide vapor source at different time lengths. The conversion mechanism involves coupled transport of sodium ions through newly formed Na-beta"-alumina and oxygen ions through 20SDC. The experimental data are analyzed using diffraction and spectroscopy methods. The samples with finer grains show faster kinetics compared to coarse microstructures due to the presence of more extended triple-phase boundaries (TPB). As a result, the total conductivity of the multi-phase sample compared to that of pure 20SDC is improved by three times, while fabrication time is decreased by 60% compared to Na-beta"-alumina+YSZ.

physics.chem-ph↗

arXiv2022

High-dimensional Bayesian Optimization of Hyperparameters for an Attention-based Network to Predict Materials Property: a Case Study on CrabNet using Ax and SAASBO

Expensive-to-train deep learning models can benefit from an optimization of the hyperparameters that determine the model architecture. We optimize 23 hyperparameters of a materials informatics model, Compositionally-Restricted Attention-Based Network (CrabNet), over 100 adaptive design iterations using two models within the Adaptive Experimentation (Ax) Platform. This includes a recently developed Bayesian optimization (BO) algorithm, sparse axis-aligned subspaces Bayesian optimization (SAASBO), which has shown exciting performance on high-dimensional optimization tasks. Using SAASBO to optimize CrabNet hyperparameters, we demonstrate a new state-of-the-art on the experimental band gap regression task within the materials informatics benchmarking platform, Matbench (~4.5% decrease in mean absolute error (MAE) relative to incumbent). Characteristics of the adaptive design scheme as well as feature importances are described for each of the Ax models. SAASBO has great potential to both improve existing surrogate models, as shown in this work, and in future work, to efficiently discover new, high-performing materials in high-dimensional materials science search spaces.

cond-mat.mtrl-sci↗

arXiv2022

Data-Driven Materials Discovery and Synthesis using Machine Learning Methods

Experimentally [1-38] and computationally [39-50] validated machine learning (ML) articles are sorted based on the size of the training data: 1-100, 101-10000, and 10000+ in a comprehensive set summarizing legacy and recent advances in the field. The review emphasizes the interrelated fields of synthesis, characterization, and prediction. Size range 1-100 consists mostly of Bayesian optimization (BO) articles, whereas 101-10000 consists mostly of support vector machine (SVM) articles. The articles often use combinations of ML, feature selection (FS), adaptive design (AD), high-throughput (HiTp) techniques, and domain knowledge to enhance predictive performance and/or model interpretability. Grouping cross-validation (G-CV) techniques curb overly optimistic extrapolative predictive performance. Smaller datasets relying on AD are typically able to identify new materials with desired properties but do so in a constrained design space. In larger datasets, the low-hanging fruit of materials optimization is typically already discovered, and the models are generally less successful at extrapolating to new materials, especially when the model training data favors a particular type of material. The large increase of ML materials science articles that perform experimental or computational validation on the predicted results demonstrates the interpenetration of materials informatics with the materials science discipline and an accelerating materials discovery for real-world applications.

cond-mat.mtrl-sci↗

arXiv2022

Real-space visualization of short-range antiferromagnetic correlations in a magnetically enhanced thermoelectric

Short-range magnetic correlations can significantly increase the thermopower of magnetic semiconductors, representing a noteworthy development in the decades-long effort to develop high-performance thermoelectric materials. Here, we reveal the nature of the thermopower-enhancing magnetic correlations in the antiferromagnetic semiconductor MnTe. Using magnetic pair distribution function analysis of neutron scattering data, we obtain a detailed, real-space view of robust, nanometer-scale, antiferromagnetic correlations that persist into the paramagnetic phase above the Néel temperature $T_{\mathrm{N}}$ = 307 K. The magnetic correlation length in the paramagnetic state is significantly longer along the crystallographic $c$ axis than within the $ab$ plane, pointing to anisotropic magnetic interactions. Ab initio calculations of the spin-spin correlations using density functional theory in the disordered local moment approach reproduce this result with quantitative accuracy. These findings constitute the first real-space picture of short-range spin correlations in a magnetically enhanced thermoelectric and inform future efforts to optimize thermoelectric performance by magnetic means.

cond-mat.mtrl-sci↗

arXiv2020

Topological Phase Transitions in a Hybridized Three-Dimensional Topological Insulator

As the thickness of a three-dimensional (3D) topological insulator (TI) becomes comparable to the penetration depth of the surface states, quantum tunneling between surfaces turns their gapless Dirac electronic structure into a gapped surface state. Analytical formulation suggests that the hybridization gap scales exponentially with decrease in number of layers while the system oscillates between topologically trivial and non-trivial insulators. This work explores the transport properties of a 3D TI in the inter-surface hybridization regime. By experimentally probing the hybridization gap as a function of BiSbTeSe2 thickness using three different methods, we map the crossover from the 3D to 2D state. In the 2D topological state, we observe a finite longitudinal conductance at ~2e2/h when the Fermi level is aligned within the surface gap, indicating a quantum spin Hall (QSH) state. Additionally, we study the response of trivial and non-trivial hybridization gapped states modulated by external out-of-plane magnetic and electric fields. Our revelations of surface gap-closing and/or reopening features are strongly indicative of topological phase transitions (TPTs) in the hybridization gap regime, realizing magnetic/electric field switching between band insulating and QSH states with immense potential for practical applications.

cond-mat.mes-hall↗

arXiv2020

Landau Levels of Topologically-Protected Surface States Probed by Dual-Gated Quantum Capacitance

Spectroscopy of discrete Landau levels (LLs) in bulk-insulating three-dimensional topological insulators (3D TIs) in perpendicular magnetic field characterizes the Dirac nature of their surface states. Despite a number of studies demonstrating the quantum Hall effect (QHE) of topological surface states, quantitative evaluation of the LL energies, which serve as fundamental electronic quantities for study of the quantum states, is still limited. In this work, we explore the density of states of LLs by measuring quantum capacitance (CQ) in a truly bulk insulating 3D TI via a van der Waals heterostructure configuration. By applying dual gate voltages, we access the individual surface states' LLs and extract their chemical potentials to quantify the LL spacings of each surface. We evaluate the LLs' energies at two distinguished QH states, namely dissipationless (ν= +/-1) and dissipative (ν= 0) states in the 3D TI.

cond-mat.mes-hall↗

arXiv2020

Tunable Coupling between Surface States of a Three-Dimensional Topological Insulator in the Quantum Hall Regime

The paired top and bottom Dirac surface states, each associated with a half-integer quantum Hall (QH) effect, and a resultant integer QH conductance (νe2/h), are hallmarks of a three-dimensional (3D) topological insulator (TI). In a dual-gated system, chemical potentials of the paired surface states are controlled through separate gates. In this work, we establish tunable capacitive coupling between the surface states of a bulk-insulating TI BiSbTeSe2 and study the effect of this coupling on QH plateaus and Landau level (LL) fan diagram via dual-gate control. We observe non-linear QH transitions at low charge density in strongly-coupled surface states, which are related to the charge-density-dependent coupling strength. A splitting of the N= 0 LL at the charge neutrality point for thin devices (but thicker than the 2D limit) indicates inter-surface hybridization possibly beyond single-particle effects. By applying capacitor charging models to the surface states, we explore their chemical potential as a function of charge density and extract the fundamental electronic quantity of LL energy gaps from dual-gated transport and capacitance measurements. These studies are essential for the realization of exotic quantum effects such as topological exciton condensation.

cond-mat.mes-hall↗

arXiv2018

Topological Insulator-Based van der Waals Heterostructures for Effective Control of Massless and Massive Dirac Fermions

Three dimensional (3D) topological insulators (TIs) are an important class of materials with applications in electronics, spintronics and quantum computing. With the recent development of truly bulk insulating 3D TIs, it has become possible to realize surface dominated phenomena in electrical transport measurements e.g. the quantum Hall (QH) effect of massless Dirac fermions in topological surface states (TSS). However, to realize more advanced devices and phenomena, there is a need for a platform to tune the TSS or modify them e.g. gap them by proximity with magnetic insulators, in a clean manner. Here we introduce van der Waals (vdW) heterostructures in the form of topological insulator/insulator/graphite to effectively control chemical potential of the TSS. Two types of gate dielectrics, normal insulator hexagonal boron nitride (hBN) and ferromagnetic insulator Cr2Ge2Te6 (CGT) are utilized to tune charge density of TSS in the quaternary TI BiSbTeSe2. hBN/graphite gating in the QH regime shows improved quantization of TSS by suppression of magnetoconductivity of massless Dirac fermions. CGT/graphite gating of massive Dirac fermions in the QH regime yields half-quantized Hall conductance steps and a measure of the Dirac gap. Our work shows the promise of the vdW platform in creating advanced high-quality TI-based devices.

cond-mat.mes-hall↗

arXiv2018

Enhancement in surface mobility and quantum transport of Bi_(2-x)Sb_(x)Te_(3-y)Se_(y) topological insulator by controlling the crystal growth conditions

Despite numerous studies on three-dimensional topological insulators (3D TIs), the controlled growth of high quality (bulk-insulating and high mobility) TIs remains a challenging subject. This study investigates the role of growth methods on the synthesis of single crystal stoichiometric BiSbTeSe2 (BSTS). Three types of BSTS samples are prepared using three different methods, namely melting growth (MG), Bridgman growth (BG) and two-step melting-Bridgman growth (MBG). Our results show that the crystal quality of the BSTS depend strongly on the growth method. Crystal structure and composition analyses suggest a better homogeneity and highly-ordered crystal structure in BSTS grown by MBG method. This correlates well to sample electrical transport properties, where a substantial improvement in surface mobility is observed in MBG BSTS devices. The enhancement in crystal quality and mobility allow the observation of well-developed quantum Hall effect at low magnetic field.

cond-mat.mtrl-sci↗

arXiv2016

A recommendation engine for suggesting unexpected thermoelectric chemistries

The experimental search for new thermoelectric materials remains largely confined to a limited set of successful chemical and structural families, such as chalcogenides, skutterudites, and Zintl phases. In principle, computational tools such as density functional theory (DFT) offer the possibility of rationally guiding experimental synthesis efforts toward very different chemistries. However, in practice, predicting thermoelectric properties from first principles remains a challenging endeavor, and experimental researchers generally do not directly use computation to drive their own synthesis efforts. To bridge this practical gap between experimental needs and computational tools, we report an open machine learning-based recommendation engine (http://thermoelectrics.citrination.com) for materials researchers that suggests promising new thermoelectric compositions, and evaluates the feasibility of user-designed compounds. We show that this engine can identify interesting chemistries very different from known thermoelectrics. Specifically, we describe the experimental characterization of one example set of compounds derived from our engine, RE12Co5Bi (RE = Gd, Er), which exhibits surprising thermoelectric performance given its unprecedentedly high loading with metallic d and f block elements, and warrants further investigation as a new thermoelectric material platform.

cond-mat.mtrl-sci↗

arXiv2013

Magnetocapacitance as a sensitive probe of magnetostructural changes in NiCr$_2$O$_4$

The spinel NiCr$_2$O$_4$ is characterized using dielectric and high magnetic field measurements. The trends in the magnetodielectric response fall into three clear temperature regimes corresponding to known magnetic and structural transitions. Above 65\,K, weak magnetic field dependence of the dielectric constant is observed with no hysteresis. When 30\,K\,$\leq\,T\,\leq$\,65\,K, a strong dependence of the dielectric constant on the magnetic field is observed and hysteresis develops resulting in so called butterfly loops. Below 30\,K, magnetodielectric hysteresis is enhanced. Magnetodielectric hysteresis mirrors magnetic hysteresis suggesting that spin-spin interactions are the mechanism for the magnetoelectric effect in NiCr$_2$O$_4$. At high fields however, the magnetization continues to increase while the dielectric constant saturates. Magnetodielectric measurements of NiCr$_2$O$_4$ suggest an additional, previously unobserved transition at 20\,K. Subtle changes in magnetism and structure suggest that this 20\,K anomaly corresponds to the completion of ferrimagnetic ordering and the spin driven structural distortion. We demonstrate that magnetocapacitance is a sensitive probe of magnetostructural distortion.

cond-mat.mtrl-sci↗