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DOE OSTI2018

On Stable Wall Boundary Conditions for the Hermite Discretization of the Linearised Boltzmann Equation

We define certain criteria, using the characteristic decomposition of the boundary conditions and energy estimates, which a set of stable boundary conditions for a linear initial boundary value problem, involving a symmetric hyperbolic system, must satisfy. We first use these stability criteria to show the instability of the Maxwell boundary conditions proposed by Grad (Commun Pure Appl Math 2(4):331–407, 1949). We then recognise a special block structure of the moment equations which arises due to the recursion relations and the orthogonality of the Hermite polynomials; the block structure will help us in formulating stable boundary conditions for an arbitrary order Hermite discretization of the Boltzmann equation. The formulation of stable boundary conditions relies upon an Onsager matrix which will be constructed such that the newly proposed boundary conditions stay close to the Maxwell boundary conditions at least in the lower order moments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Analytical Approach for Detection of Ergosterol in Mushrooms Based on Modification Free Electrochemical Sensor in Organic Solvents

Ergosterol (Erg) is the major sterol component in the plasma membranes of fungi. The main goal of this work was to develop rapid, reliable, and cost-effective method toward Erg detection based on application of unmodified boron-doped diamond electrode. Several organic solvents were tested (acetonitrile, dimethyformamide, dimethylsulfoxide, dichloromethane), and it was found that best analytical characteristics were achieved using acetonitrile containing 0.1 M tetrabutylammonium hexa-fluorophosphate as supporting electrolyte. Oval shaped and well-defined oxidation peak was recorded at potential of around 1.17 V versus Ag/Ag+ non-aqueous reference electrode. Under optimized experimental conditions, linear working range from 2 to 200 mu M was estimated, with limit of detection of 0.7 mu M, using square wave voltammetry. Negligible effect of possible interfering compound was observed. Proposed methodology was successfully applied for estimation of Erg content in mushrooms extract with satisfactory results in comparison with spectrophotometric procedure. Obtained results clearly show that developed analytical methodology can be adequate replacement for the, up to date, used methods and open-novel approach for ergosterol detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Observer-based H{sub ∞} control for nonlinear Markovian jump systems with time-delay and input saturation

This paper focus on the problem of observer-based H{sub ∞} control for uncertain nonlinear Markovian jump systems with time-delay and actuator saturation. A delay-dependent sufficient condition is proposed which guarantees that the uncertain nonlinear Markovian jump system with time-delay and input saturation is stochastically stable via Lyapunov theory and linear matrix inequality (LMI) approach. Then, with this condition, the estimation of stability region and the design method of observer-based H{sub ∞} controller are given by solving LMIs and convex optimization problems. Finally, numerical examples are exploited to illustrate the effectiveness of the proposed method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Derivative-based SINDy (DSINDy): Addressing the challenge of discovering governing equations from noisy data

Recent advances in the field of data-driven dynamics allow for the discovery of ODE systems using state measurements. One approach, known as Sparse Identification of Nonlinear Dynamics (SINDy), assumes the dynamics are sparse within a predetermined basis in the states and finds the expansion coefficients through linear regression with sparsity constraints. This approach requires an accurate estimation of the state time derivatives, which is not necessarily possible in the high-noise regime without additional constraints. We present an approach called Derivative-based SINDy (DSINDy) that combines two novel methods to improve ODE recovery at high-noise levels. First, we denoise the state variables by applying a projection operator that leverages the assumed basis for the system dynamics. Second, we use a second order cone program (SOCP) to find the derivative and governing equations simultaneously. We derive theoretical results for the projection-based denoising step, which allow us to estimate the values of hyperparameters used in the SOCP formulation. This underlying theory helps limit the number of required user-specified parameters. Finally, we present results demonstrating that our approach leads to improved system recovery for the Van der Pol oscillator, the Duffing oscillator, the Rössler attractor, and the Lorenz 96 model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Sensitivity of the U.S. economy to oil prices controlling for domestic production and imports

This paper investigates the sensitivity of U.S. economic performance to oil price changes, accounting for changes in the domestic petroleum supply-demand balance over the last decade. Herein, a non-linear (asymmetric) autoregressive distributed lag (NARDL) model is used to estimate the U.S. GDP elasticity with respect to the oil price, controlling for oil production, consumption and imports, and macroeconomic variables. The positive and negative components of the oil price both have statistically significant long-run impacts on the real U.S. GDP. The parameter estimates imply that a 1% positive and permanent oil price shock, all else the same, would have a long-run impact of –0.045% on the U.S. economy (an elasticity of –0.045), but short-run parameters on the positive oil price terms are not significant at the 10% level. The long-run parameter on the negative oil price component term implies an elasticity of –0.034. Thus, controlling for domestic U.S. oil production and oil trade, the long-run oil price elasticity of the U.S. GDP remains within the range of estimates from previous studies. The results also show that domestic oil production and consumption have short-run impacts on the U.S. GDP. The potential extent of interactions among these variables, and implications for the net economic impacts, under an oil price shock are subjects of future research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2014

Cadmium exposure and neuropsychological development in school children in southwestern Spain

This study assessed the association between cadmium exposure and neuropsychological development in children from a region with high industrial and mining activities in southwestern Spain. We conducted a cross-sectional study with 261 children aged 6–9 years between January and March 2012. Cadmium exposure was measured in urine and hair of children, and neuropsychological development was assessed with the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) and with three computerized tests from the Behavioral Assessment and Research System (BARS): Reaction Time Test (RTT), Continuous Performance Test (CPT) and Selective Attention Test (SAT). Multivariate linear regression models, adjusted for potential confounders, were used to estimate the association between neuropsychological development and cadmium exposure measured in urine and hair samples. Geometric means of urine and hair cadmium levels were 0.75 μg/g creatinine and 0.01 μg/g, respectively. We observed that doubling of levels of cadmium in urine was associated with a reduction of two points (95% CI: −3.8 to −0.4) in the Full-Scale intelligence quotient (IQ) in boys. By domains, association was statistically significant for Verbal Comprehension (β=−2.0; p=0.04) and close to the significance level for Perceptual Reasoning (β=−1.8; p=0.06). Among girls, only Verbal Comprehension showed suggestive associations with cadmium exposure (β=−1.7; p=0.06). Cadmium exposure is associated with cognitive delays in boys in our region. Our results provide additional evidence of the neurotoxic effect of low-level postnatal cadmium exposure among children, and support the hypothesis of differences between sexes in the neurotoxic effect of metals on children. - Highlights: • This study associates Cd exposure and neuropsychological development in children. • Cd exposure was associated with cognitive delay in boys, but not in girls. • Intellectual quotient of boys decreased two points for a doubling of urine Cd levels. • Verbal Comprehension and Perceptual Reasoning were the most affected domains in boys. • Results support the sex-related differences in the neurotoxicity of metals in children.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Integrated State Estimation and Contingency Analysis Software Implementation using High Performance Computing Techniques

Power system simulation tools are traditionally developed in sequential mode and codes are optimized for single core computing only. However, the increasing complexity in the power grid models requires more intensive computation. The traditional simulation tools will soon not be able to meet the grid operation requirements. Therefore, power system simulation tools need to evolve accordingly to provide faster and better results for grid operations. This paper presents an integrated state estimation and contingency analysis software implementation using high performance computing techniques. The software is able to solve large size state estimation problems within one second and achieve a near-linear speedup of 9,800 with 10,000 cores for contingency analysis application. The performance evaluation is presented to show its effectiveness.

Chen, Yousu↗

DOE OSTI2026

Active operator learning with predictive uncertainty quantification for partial differential equations

With the increased prevalence of neural operators being used to provide rapid solutions to partial differential equations (PDEs), understanding the accuracy of model predictions and the associated error levels is necessary for deploying reliable surrogate models in scientific applications. Existing uncertainty quantification (UQ) frameworks employ ensembles or Bayesian methods, which can incur substantial computational costs during both training and inference. Here, we propose a lightweight predictive UQ method tailored for Deep operator networks (DeepONets) that also generalizes to other operator networks. Numerical experiments on linear and nonlinear PDEs demonstrate that the framework’s uncertainty estimates are unbiased and provide accurate out-of-distribution uncertainty predictions with a sufficiently large training dataset. Our framework provides fast inference and uncertainty estimates that can efficiently drive outer-loop analyses that would be prohibitively expensive with conventional solvers. We demonstrate how predictive uncertainties can be used in the context of Bayesian optimization and active learning problems to yield improvements in accuracy and data-efficiency for outer-loop optimization procedures. In the active learning setup, we extend the framework to Fourier Neural Operators (FNO) and describe a generalized method for other operator networks. To enable real-time deployment, we introduce an inference strategy based on precomputed trunk outputs and a sparse placement matrix, reducing evaluation time by more than a factor of five. Our method provides a practical route to uncertainty-aware operator learning in time-sensitive settings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Aqueous TiO 2 Nanoparticles React by Proton-Coupled Electron Transfer

Redox reactions of aqueous colloidal TiO 2 4 nm nanoparticles (NPs) have been examined, including both citratecapped and uncapped NPs (c-TiO 2 and uc-TiO 2 ). Photoreduction gave stable blue colloidal c-TiO 2 R NPs with 10–60 electrons per particle. Equilibration of these reduced NPs with soluble redox reagents such as methylviologen (MV 2+ ) provided measurements of the colloid reduction potential as a function of pH. The potentials of c-TiO 2 from pH 2–9 varied linearly with pH, with a slope of –60 ± 5 mV/pH. Estimates of the potential at pH 12 were consistent with extrapolating that line to high pH. The reduction potentials did not correlate with the zeta potentials (ζ) or the surface charge of the NPs across this pH range. Similar reduction potentials were observed for c- and uc-TiO 2 at low pH even though they have quite different ζ potentials. These results show that the common surface-charging explanation of the pH dependence is not tenable in these systems. Oxidation of reduced c-TiO 2 R with the electron-transfer oxidant potassium triiodide (KI 3 ) occurred with a significant drop in pH, showing that protons were released when the electrons were removed from the NPs. Smaller pH drops were observed for the proton-coupled electron transfer (PCET) reagents O 2 (air) and 4-MeO-TEMPO (4-methoxy-2,2,6,6-tetramethylpiperine-1-oxy radical). The difference in the number of protons released with KI 3 vs O 2 and 4-MeO-TEMPO was roughly one proton per electron removed. Thus, the thermodynamically preferred reactivity of these colloidal TiO 2 NPs is PCET over the pH 2–13 range studied. The measured redox potentials refer to the chemical process TiO 2 + H + + e – → TiO 2 ·e – ,H + ; and therefore they do not correspond with an electronic energy such as a conduction band edge or flat band potential. The 1e – /1H + stoichiometry means that the TiO 2 reduction potentials correspond to a TiO 2 –H bond dissociation free energy (BDFE), determined to be 49 ± 2 kcal mol –1 . The PCET description is consistent with the pH dependence of E(TiO 2 /TiO 2 ·e – ,H + ), the release of protons upon oxidation, the lack of correlation with ζ potentials, the similarity of capped and uncapped NPs, and the small change in the potential and BDFE from the first to the last electron/proton pair (H atom) removed. Furthermore, this behavior is suggested to be the norm for redox-active oxide/water interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Nuclear quadrupole moment-induced Cotton-Mouton effect in molecules

Nuclear magneto-optic effects could make important contributions to novel, high-sensitivity, and high-resolution spectroscopic and imaging methods that provide nuclear site-specific structural and dynamic information on molecular and materials systems. Here we present a first-principles electronic structure formulation of nuclear quadrupole moment-induced Cotton-Mouton effect in terms of response theory, as well as ab initio and density-functional theory calculations of this phenomenon for a series of molecular liquids: H{sub 2}O, CH{sub 3}NO{sub 2}, CH{sub 3}CH{sub 2}OH, C{sub 6}H{sub 6}, C{sub 6}H{sub 12} (cyclohexane), HI, XeF{sub 2}, WF{sub 5}Cl, and Pt(C{sub 2}dtp){sub 2}. The roles of basis-set convergence, electron correlation, and relativistic effects are discussed. The estimated order of magnitude of the overall ellipticities induced to linearly polarized light is 10{sup −3}–10{sup −7} rad/(M cm) for fully spin polarized nuclei. The cases with the largest presently obtained ellipticities should be detectable with modern instrumentation in the Voigt magneto-optic setup, particularly for the heavy nuclei.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Stochastic growth logistic model with aftereffect for batch fermentation process

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Gompertzian stochastic model with delay effect to cervical cancer growth

In this paper, a Gompertzian stochastic model with time delay is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of cervical cancer growth. Low values of Mean-Square Error (MSE) of Gompertzian stochastic model with delay effect indicate good fits.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Electric properties and carrier multiplication in breakdown sites in multi-crystalline silicon solar cells

This paper studies the effective electrical size and carrier multiplication of breakdown sites in multi-crystalline silicon solar cells. The local series resistance limits the current of each breakdown site and is thereby linearizing the current-voltage characteristic. This fact allows the estimation of the effective electrical diameters to be as low as 100 nm. Using a laser beam induced current (LBIC) measurement with a high spatial resolution, we find carrier multiplication factors on the order of 30 (Zener-type breakdown) and 100 (avalanche breakdown) as new lower limits. Hence, we prove that also the so-called Zener-type breakdown is followed by avalanche multiplication. We explain that previous measurements of the carrier multiplication using thermography yield results higher than unity, only if the spatial defect density is high enough, and the illumination intensity is lower than what was used for the LBIC method. The individual series resistances of the breakdown sites limit the current through these breakdown sites. Therefore, the measured multiplication factors depend on the applied voltage as well as on the injected photocurrent. Both dependencies are successfully simulated using a series-resistance-limited diode model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Compensating cylindrical Hohlraum mode 4 asymmetry via capsule thickness tailoring and effects on implosions

We report previously, hydrodynamic simulations suggested that precisely tailoring the capsule ablator thickness (shimming) could counterbalance cylindrical Hohlraum Legendre P 4 drive asymmetries at the capsule in laser indirect drive implosions. As a result, the stagnated deuterium–tritium (DT) fuel areal density P 4 asymmetry is reduced, potentially resulting in a nuclear yield increase. Inflight radiographs of various level of shimmed capsules with plastic (CH) ablators showed that shims can indeed control the in-flight capsule shell P 4 asymmetry, with a linear sensitivity to shim amplitude that is close to analytic estimates and simulations. Furthermore, the stagnated DT fuel areal density P 4 asymmetry inferred from downscattered neutron imaging was reduced when the capsule shim was applied, in agreement with simulations matching the inflight shell asymmetry. A nuclear yield improvement via shim was not observed, as predicted, likely due to implosion instabilities and as built capsule shim deviations from an ideal P 4 shape.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Quantification of air leakage paths: a comparison of airflow and acoustic measurements

Today, the fan pressurization method is the most frequently used method to evaluate a building's airtightness. However, the localization and quantification of leaks remain difficult. In this paper, an acoustic method is introduced to estimate the leakage size of single leaks. Acoustic and airflow measurements were conducted and compared in laboratory tests within the same boundary conditions. This work aims to investigate if various leak sizes can be predicted using acoustic measurement methods. The test apparatus consists of two chambers, separated by a test wall. This wall represents a single characteristic air leakage path. Various types of wall structures with different slit geometries, wall thicknesses, and insulation materials were investigated. The acoustic measurements were performed with a sound source placed in one chamber and ultrasonic microphones located in both chambers. These results were compared to measured airflows through the test wall to provide estimates of uncertainty in the acoustic approach, which indicate a linear trend. Finally, these laboratory measurements were compared to the same measurements at a real office building. Finally, although the acoustic measurement uncertainty is still significant (greater than +/- 50%), the acoustic method has the potential to give an order of magnitude of single leak sizes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Calculations of electronic excitation by protons and alpha particles in silicon

This paper presents an ab initio method of calculating the valence electron contribution to the stopping and interaction cross sections of swift ions in matter using linear response calculations of the dielectric function in crystals. We estimate the contribution to the stopping and cross sections by repeated electron capture and stripping of the projectile ion by the medium. We also predict the electronic stopping of protons and alpha particles in silicon and compare to measured values. The predictions generally agree with the data at ion speeds greater than 1 atomic unit. We find that electron capture and stripping is at most a small contribution to the stopping for both ions studied.

electron excitation, silicon, nuclear interactions↗

DOE OSTI2024

Quapprox: A Framework for Benchmarking the Approximability of Variational Quantum Circuit

Most of the existing quantum neural network models, such as variational quantum circuits (VQCs), are limited in their ability to explore the non-linear relationships in input data. This gradually becomes the main obstacle for it to tackle realistic applications, such as natural language processing, medical image processing, and wireless communications. Recently, there have emerged research efforts that enable VQCs to perform non-linear operations. However, it is still unclear on the approximability of a given VQC (i.e., the order of non-linearity that can be handled by a specified design). In response to this issue, we developed an automated tool designed to benchmark the approximation of a given VQC. The proposed tool will generate a set of synthetic datasets with different orders of non-linearity and train the given VQC on these datasets to estimate their approximability. Our experiments benchmark VQCs with different designs, where we know their theoretic approximability. We then show that the proposed tool can precisely estimate the approximability, which is consistent with the theoretic value, indicating that the proposed tool can be used for benchmarking the approximability of a given quantum circuit for learning tasks.

artificial intelligence↗

DOE OSTI2019

Multiscale Modeling of Total Ionizing Dose Effects in Commercial-off-the-Shelf Parts in Bipolar Technologies

A multiscale modeling platform that supports the “virtual” qualification of commercial-off-the-shelf parts is presented. The multiscale approach is divided into two modules. The first module generates information related to the bipolar junction transistor gain degradation that is a function of fabrication process, operational, and environmental inputs. The second uses this information as inputs for radiation-enabled circuit simulations. The prototype platform described in this paper estimates the total ionizing dose and dose rate responses of linear bipolar integrated circuits for different families of components. The simulation and experimental results show good correlation and suggest this platform to be a complementary tool within the radiation-hardness assurance flow. Finally, the platform may reduce some of the costly reliance on testing for all systems.

97 MATHEMATICS AND COMPUTING↗