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At least 271 records · Page 15

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DOE OSTI2022

Exponential Escape Rate of Filamentary Incubation in Mott Spiking Neurons

Mott materials such as vanadium oxides, when subject to a strong applied voltage, present an inhomogeneous insulator-to-metal transition with formation of metallic filaments within the insulating bulk. This property is enabling the development of compact and power-efficient neuromorphic devices known as Mott neurons. However, the nature of the transition has not been fully understood yet, as it may be attributed to different effects, including Joule self-heating and hot-carrier injection. Moreover, the experimental determination of the threshold voltage needed to induce the transition has proven to be challenging, as the transition becomes increasingly unpredictable when the threshold is approached. The physical understanding of these issues would not only deepen our understanding of Mott insulators, but would also be an important step toward the realization of neuromorphic devices based on such materials. In this work we use numerical simulations based on the Mott resistor network model to study the nature of the filament incubation and formation process. Here, we show that both electronic and thermal effects, in the form of current density focusing and Joule self-heating, respectively, contribute to the filamentary incubation and growth. Remarkably, we find that the percolation of the metallic filaments near the threshold is intrinsically stochastic, qualitatively similar to the familiar Arrhenius activated behavior and to the stochastic firing of biological neurons. More precisely, we characterize the filament percolation as a Poisson point process, which has the same probability distribution as mathematical models of neuronal firing with an exponential escape rate. Finally, we support the numerical simulation results by performing experiments in VO 2 that are in agreement with the exponential escape rate behavior. Thus, we establish a functionality of Mott insulators that opens a path toward implementing neuromorphic hardware with quantum materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Atomic dynamics of metallic glass melts La 50 Ni 15 Al 35 and Ce 70 Cu 19 Al 11 studied by quasielastic neutron scattering

By employing quasielastic neutron scattering, we studied the atomic-scale relaxation dynamics and transport mechanism of La 50 Ni 15 Al 35 and Ce 70 Cu 19 Al 11 metallic glass melts in the temperature range of > 200K above their liquidus temperatures. The results show that both liquids exhibit stretched exponential relaxation and Arrhenius-type temperature dependence of the effective diffusion coefficient. The La 50 Ni 15 Al 35 melt exhibits an activation energy of 0.545 ± 0.008 eV and a stretching exponent ~0.77 to 0.86 in the studied temperature range; no change of activation energy, as suggested in previous reports, associated with liquid-liquid phase transition was observed. In contrast, the Ce 70 Cu 19 Al 11 melt exhibits larger diffusivity with a much smaller activation energy of 0.201±0.003eV and a smaller stretching exponent ~0.51 to 0.60, suggestive of more heterogeneous dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Slow spin dynamics and quantum tunneling of magnetization in the dipolar antiferromagnet DyScO 3

Here, we present a comprehensive study of static and dynamic magnetic properties in the Ising-like dipolar antiferromagnet (AFM) DyScO 3 by means of DC and AC magnetization measurements supported by classical Monte Carlo calculations. Our AC-susceptibility data show that the magnetic dynamics exhibit a clear crossover from an Arrhenius-like regime to quantum tunneling of magnetization (QTM) at T*=10K. Below T N =3.2K, DyScO 3 orders in an antiferromagnetic GxAy-type magnetic structure and the magnetization dynamics slow down to the minute timescale. The low-temperature magnetization curves exhibit complex hysteretic behavior, which depends strongly on the magnetic field sweep rate. We demonstrate that the low-field anomalies on the magnetization curve are related to the metamagnetic transition, while the hysteresis at higher fields is induced by a strong magnetocaloric effect. Our theoretical calculations, which take into account dipolar interaction between Dy 3+ moments, reproduce essential features of the magnetic behavior of DyScO 3 . We demonstrate that DyScO 3 represents a rare example of an inorganic compound, which exhibits QTM at a single-ion level and magnetic order due to classical dipolar interaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Statistically averaged molecular dynamics simulations of hydrogen diffusion in magnesium and magnesium hydrides

Magnesium has a different crystal structure from its dihydride with hydrogenation leading to a phase transition from the hexagonal closely packed Mg into a tetragonal α-MgH 2 rutile type structure. Such materials exhibit complex hydrogen uptake and release kinetics because hydrogen diffusivities significantly change when the crystal structure changes. To provide a foundational understanding of (de)hydrogenation kinetics that is applicable to all stages of the reaction, we performed statistically averaged molecular dynamics simulations to derive hydrogen diffusivities as a function of temperature and hydrogen content for both magnesium and magnesium hydride. Furthermore, our studies confirm that hydrogen diffusivities in magnesium hydride are much lower than in magnesium, in agreement with experimental data. Additionally, we observe that in either magnesium or magnesium hydride, higher hydrogen compositions result in reduced diffusivities. The latter was not revealed by prior experiments, which were conducted at fixed hydrogen composition. Finally, we discover a non-Arrhenius behavior in magnesium hydride. The physical origin of this behavior is also discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Electronic structure and small-hole polarons in YTiO 3

As a prototypical Mott insulator with ferromagnetic ordering, YTiO 3 (YTO) is of great interest in the study of strong electron correlation effects and orbital ordering. Here we report the first molecular beam epitaxy (MBE) growth of YTO films, combined with theoretical and experimental characterizations of the electronic structure and charge transport properties. The obstacles of YTO MBE growth are discussed and potential routes to overcome them are proposed. DC transport and Seebeck measurements on thin films and bulk single crystals identify p-type Arrhenius transport behavior with an activation energy of ~0.17 eV in thin films, consistent with the energy barrier for small hole polaron migration from hybrid density functional theory calculations. Hard x-ray photoelectron spectroscopy measurements show the lower Hubbard band at 1.1 eV below the Fermi level, whereas a Mott-Hubbard band gap of ~1.5 eV is determined from photoluminescence measurements. These findings provide critical insight into the electronic band structure of YTO and related materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Energy-relaxation pathways in finite-sized artificial square-ice structures

The energy-relaxation pathway in artificial spin ice structures refers to the series of individual moment reorientations the system undergoes as it relaxes from an initial state to a final low-energy state. The probability of the artificial spin ice structure reaching a ground state depends on the energy of the intermediate states as approximated by an Arrhenius-type relation. In this work, we report that by modifying the geometry of artificial square-ice structures, we can influence the probability of observing the ground state in different configurations. Furthermore, our findings are supported by dipolar energy calculations for various energy-relaxation pathways and the corresponding experimental data obtained by magnetic force microscopy.

Analog computation↗

DOE OSTI2022

Hanford low-activity waste glass composition-temperature-melt viscosity relationships

This study developed a model for predicting viscosity of alkali-alumino-borosilicate glass melts as functions of composition and temperature. The model is based on a total of 3935 viscosity-temperature data from 574 glasses with viscosity values ranging from 2.53 to 7260 Poise (P) in the temperature range of 900–1260°C. Several different model forms were surveyed, including those based on Arrhenius, Vogel-Fulcher-Tammann, Avramov-Milchev, and Mauro-Yue-Ellison-Gupta-Allen. For each of these models, combinations of the temperature-independent parameters were fitted to composition. It was found that generally fitting more than one temperature-independent parameter as functions of composition resulted in overfitting. The Avramov-Milchev-based model was found to best represent the Hanford low-activity waste glass melt viscosity data based on model fit and validation statistics. A 21-term partial quadratic mixture model was recommended for use. This model predicts melt viscosity with a root-mean square error of .1736 ln(P), which is similar to the error in viscosity measurements from replicate glass analyses of .1383 ln(P). Viscosity was found to be most increased by SiO 2 > Al 2 O 3 > ZrO 2 > SnO 2 and most decreased by Li 2 O > Na 2 O > B 2 O 3 > CaO > K 2 O > MgO, at temperatures from 900 to 1260°C.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Observed volatilization behavior of silicon carbide in flowing hydrogen above 2000 K

In this work, the intrinsic compatibility of silicon carbide (SiC) and hydrogen (H 2 ) at high temperatures (2000-2473 K) and pressure near one atmosphere was evaluated through a combination of thermodynamic calculations and hot hydrogen exposure testing. Thermodynamic calculations predict the decomposition of SiC in a hydrogen environment to form free silicon (Si) and free carbon (C). Free Si is predicted to vaporize from the surface as a volatile species, while free C may interact with H 2 to form the hydrocarbons CH 4 (T < 2100 K) or C 2 H 2 (T > 2100 K). Coupons of high purity chemical vapor deposition (CVD) β-SiC were exposed to slowly flowing hydrogen at temperatures ranging between 2000 and 2473 K. SiC experienced active attack as the result of H 2 exposure, exhibiting linear weight loss kinetics and an Arrhenius dependence of weight loss on exposure temperature. The linear volatilization constant was experimentally evaluated to correspond with an activation energy of 370 ± 18 kJ/mol. Due to the dependence of observed corrosion rates on gas velocity, corrosion of SiC in flowing H 2 was determined to be governed by external mass transfer of volatile Si species through the boundary layer. Experimentally derived mass losses were in good agreement with mass losses predicted by a boundary layer limited gas diffusion model.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Evaluating steam oxidation kinetics of environmental barrier coatings

Environmental barrier coatings (EBCs) are a commercially proven means of protecting SiC-based materials in gas turbine environments. However, there are little specific data in the literature on the impact of coatings like Yb 2 Si 2 O 7 on preventing accelerated SiO 2 growth in the presence of H 2 O. Quantification of reduced rates are necessary for evaluating and comparing EBC effectiveness and incorporation of silica growth rates into future EBC lifetime models. In this study, baseline kinetics of silica formation on bare Si and chemically vapor deposited (CVD) SiC in the 1250–1425 °C range were obtained via 100 h isothermal exposures in dry air and steam environments utilizing a SiC reaction tube to mitigate specimen volatility. An Arrhenius plot of the resulting rates was constructed, representing baseline minimum and maximum rates for Si and SiC oxidation at ambient pressure. Various EBC systems on CVD SiC substrates including air plasma sprayed (APS) EBCs with and without a Si bond coating and with surface roughening to enhance Yb 2 Si 2 O 7 adhesion were subjected to 1-h furnace cycle testing in air with 90vol%H 2 O at 1250–1350°C for up to 500 cycles. After exposure, silica formation rates were measured and compared to the baseline rates to assess EBC effectiveness, where EBC effectiveness is gauged as the propensity to reduce underlying rates of silica formation. With a Si bond coating, a ~180 µm Yb 2 Si 2 O 7 (YbDS) top coating reduced rates over the entire 1250°-1350°C range. Without a Si bond coating, ~60 µm (YbDS) coatings deposited directly onto CVD SiC exhibited poor adhesion, and had to be deposited onto substrates with enhanced roughness at 1350°C. Finally, while exhibiting good adhesion at 1350°C, overall the single layer YbDS coating exhibited a decreasing effectiveness from 1250° to 1350°C.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Final-stage densification kinetics of direct current–sinteredZrB2

Final-stage sintering was analyzed for nominally phase pure zirconium diboride synthesized by borothermal reduction of high-purity ZrO2. Analysis was conducted on ZrB2 ceramics with relative densities greater than 90% using the Nabarro–Herring stress–directed vacancy diffusion model. Temperatures of 1900°C or above and an applied uniaxial pressure of 50 MPa were required to fully densify ZrB2 ceramics by direct current sintering. Ram travel data were collected and used to determine the relative density of the specimens during sintering. Specimens sintered between 1900 and 2100°C achieved relative densities greater than 97%, whereas specimens sintered below 1900°C failed to reach the final stage of sintering. The average grain size ranged from 1.0 to 14.7 μm. The activation energy was calculated from the slope of an Arrhenius plot that used the Kalish equation. The activation energy was 162 ± 34 kJ/mol, which is consistent with the activation energy for dislocation movement in ZrB2. The diffusion coefficients for dislocation motion that controls densification were 5.1 × 10−6 cm2/s at 1900°C and 5.1 × 10−5 cm2/s at 2100°C, as calculated from activation energy and average grain sizes. This study provides evidence that the dominant mechanism for final-stage sintering of ZrB2 ceramics is dislocation motion.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Embedded Error Bayesian Calibration of Thermal Decomposition of Organic Materials

Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to tradiational materials they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chemical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis. This process requires the calibration of many model parameters to closely match experimental data. Previous efforts in this field have largely been limited to finding a single best-fit set of parameters even though the experimental data may be very noisy. Furthermore the chemical kinetics models are often simplified representations of the true de- composition process. The simplification induces model-form errors that the fitting process cannot capture. In this work we propose a methodology for calibrating decomposition models to thermogravimetric analysis data that accounts for uncertainty in the model-form and experimental data simultaneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and thermogravimetric analysis data. Uncertainty bounds capture devia- tions of the model from the data. The calibrated parameter distributions are also presented. In conclusion, the distributions may be used in forward propagation of uncertainty in models that leverage this material.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Accelerated aging of all-inorganic, interface-stabilized perovskite solar cells

To understand degradation routes and improve the stability of perovskite solar cells (PSCs), accelerated aging tests are needed. Here, we use elevated temperatures (up to 110°C) to quantify the accelerated degradation of encapsulated CsPbI 3 PSCs under constant illumination. Incorporating a two-dimensional (2D) Cs 2 PbI 2 Cl 2 capping layer between the perovskite active layer and hole-transport layer stabilizes the interface while increasing power conversion efficiency of the all-inorganic PSCs from 14.9 to 17.4%. Devices with this 2D capping layer did not degrade at 35°C and required >2100 hours at 110°C under constant illumination to degrade by 20% of their initial efficiency. Degradation acceleration factors based on the observed Arrhenius temperature dependence predict intrinsic lifetimes of 51,000 ± 7000 hours (>5 years) operating continuously at 35°C.

Science & Technology - Other Topics↗

DOE OSTI2025

A large-scale screening campaign of putative carbohydrate-active enzymes reveals a novel xylanase from anaerobic gut fungi

The genomes of anaerobic gut fungi (AGF) encode a diverse array of carbohydrate-active enzymes (CAZymes), yet exceedingly few of these enzymes have been experimentally validated or expressed in heterologous systems. Here, we developed a predictive bioinformatic pipeline to annotate novel putative CAZymes from anaerobic fungi and validate their activity through large-scale heterologous expression in Escherichia coli. A total of 173 fungal proteins from Piromyces finnis associated with biomass degradation were synthesized and expressed in E. coli, and 9.8% were soluble with expression levels exceeding 5% of the total proteome using high-throughput proteomic screening. Among these 17 heterologously expressed proteins, analysis with AlphaFold and FoldSeek predicted 13 multi-functional proteins containing catalytic domains fused with repetitive fungal dockerins, and half of the substrate predictions were experimentally validated. One promising enzyme, celsome_012, exhibited robust and specific activity against beechwood xylan at 37°C and pH 6.4, with titers that were also fivefold higher than those of other recombinant proteins screened here. Both Michaelis-Menten kinetics and the linearized Lineweaver-Burk equation yielded consistent values for K m , and its activation energy was estimated at 51.9 kJ/mol based on the Arrhenius model. This work supports the industrial translation of anaerobic fungal CAZymes due to their robust lignocellulolytic activity and provides a framework for prioritizing AGF proteins for efficient E. coli heterologous expression.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Demystifying the Diffuse Vibrational Spectrum of Aqueous Protons Through Cold Cluster Spectroscopy

The ease with which the pH is routinely determined for aqueous solutions masks the fact that the cationic product of Arrhenius acid dissolution, the hydrated proton, or H + (aq), is a remarkably complex species. Here, we review how results obtained over the past 30 years in the study of H + ·(H 2 O) n cluster ions isolated in the gas phase shed light on the chemical nature of H + (aq). This effort has also revealed molecular-level aspects of the Grotthuss relay mechanism for positive-charge translocation in water. Recently developed methods involving cryogenic cooling in radiofrequency ion traps and the application of two-color, infrared–infrared (IR–IR) double-resonance spectroscopy have established a clear picture of how local hydrogen-bond topology drives the diverse spectral signatures of the excess proton. This information now enables a new generation of cluster studies designed to unravel the microscopic mechanics underlying the ultrafast relaxation dynamics displayed by H + (aq).

Chemistry↗

DOE OSTI2021

Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning

Various modeling techniques are used to predict the capacity fade of Li-ion batteries. Algebraic reduced-order models, which are inherently interpretable and computationally fast, are ideal for use in battery controllers, technoeconomic models, and multi-objective optimizations. For Li-ion batteries with graphite anodes, solid-electrolyte-interphase (SEI) growth on the graphite surface dominates fade. This fade is often modeled using physically informed equations, such as square-root of time for predicting solvent-diffusion limited SEI growth, and Arrhenius and Tafel-like equations predicting the temperature and state-of-charge rate dependencies. In some cases, completely empirical relationships are proposed. However, statistical validation is rarely conducted to evaluate model optimality, and only a handful of possible models are usually investigated. This article demonstrates a novel procedure for automatically identifying reduced-order degradation models from millions of algorithmically generated equations via bi-level optimization and symbolic regression. Identified models are statistically validated using cross-validation, sensitivity analysis, and uncertainty quantification via bootstrapping. On a LiFePO 4 /Graphite cell calendar aging data set, automatically identified models utilizing square-root, power law, stretched exponential, and sigmoidal functions result in greater accuracy and lower uncertainty than models identified by human experts, and demonstrate that previously known physical relationships can be empirically "rediscovered" using machine learning.

25 ENERGY STORAGE↗

DOE OSTI2023

A New Analytical Expression for Estimating the Adiabatic Temperature Rise in Lithium-Ion Batteries During High-Power Pulses

A coupled, thermal-electrochemical model is used to explain why the Joule heating assumption (i.e., I 2 R) does not provide a good representation of the temperature rise during high power pulses in lithium-ion batteries, even in cases where the reversible heat generation can be neglected. The poor agreement occurs because the internal resistance changes during the pulse due to the opposing effects of mass transport in the electrolyte, which raises the resistance, and heat generation (temperature rise), which lowers the resistance. These insights are used to propose a new analytical expression for predicting the temperature rise during adiabatic pulses with limited experimental and physical data. The expression accounts for thermal effects using a Taylor series expansion of an Arrhenius-type equation. It accounts for transport effects using an approximate solution to the one-dimensional diffusion equation. The new expression is shown to accurately estimate the simulated, adiabatic temperature rise across a range of loadings (1 to 4 mAh cm -2 ) and C-rates (1C to 10C) for cells containing LiNi 0.5 Mn 0.3 Co 0.2 O 2 positive electrodes and graphite negative electrodes. In conclusion, it is also shown to accurately estimate the experimental, adiabatic temperature rise measured for cells with LiFePO 4 positive electrodes and mesocarbon negative electrodes with minimal changes to the fitted parameters.

25 ENERGY STORAGE↗

DOE OSTI2024

Leveraging Temperature-Dependent (Electro)Chemical Kinetics for High-Throughput Flow Battery Characterization

The library of redox-active organics that are potential candidates for electrochemical energy storage in flow batteries is exceedingly vast, necessitating high-throughput characterization of molecular lifetimes. Demonstrated extremely stable chemistries require accurate yet rapid cell cycling tests, a demand often frustrated by time-denominated capacity fade mechanisms. We have developed a high-throughput setup for elevated temperature cycling of redox flow batteries, providing a new dimension in characterization parameter space to explore. We utilize it to evaluate capacity fade rates of aqueous redox-active organic molecules, as functions of temperature. We demonstrate Arrhenius-like behavior in the temporal capacity fade rates of multiple flow battery electrolytes, permitting extrapolation to lower operating temperatures. Collectively, these results highlight the importance of accelerated decomposition protocols to expedite the screening process of candidate molecules for long lifetime flow batteries.

25 ENERGY STORAGE↗

DOE OSTI2025

Electrochemical Characterization of Dissolved Oxides in Molten FLiNaK

Molten fluoride salts have long been the subject of investigation given their application in a variety of industrial processes. Oxides are a common exogeneous impurity within these systems, and can lead to many operational and regulatory concerns. In recent studies, the electro-oxidation of dissolved metallic oxides has been attributed to a single step oxygen evolution reaction despite voltametric evidence suggesting otherwise. Here, we first use square wave voltammetry to confirm that the oxidation of dissolved oxides in fluorides proceeds via a two-electron transfer reaction and then demonstrate that the presence of a peroxide-mediated redox reaction better explains the electrochemical data. Numerical simulations were then used to support the determination of improved diffusion coefficients to enable electroanalytical measurements of the oxide concentration across at a variety of temperatures. A linear Arrhenius relationship was observed when the experimental data was corrected for ohmic resistance effects. Concentration measurements using the corrected square wave voltammetry data demonstrated high accuracy across a large range of concentrations, while the uncorrected data showed plateauing and high errors. In total, this work serves to rectify previously misconstrued electrochemical data of oxides in molten salts and demonstrate how accurate, in situ concentration measurements can be achieved in real-world systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗