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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effect of Nanoscale Ce 0.8 Gd 0.2 O 2–δ Infiltrant and Steam Content on Ni–(Y 2 O 3 ) 0.08 (ZrO 2 ) 0.92 Fuel Electrode Degradation during High-Temperature Electrolysis

Studies of Ni–yttria-stabilized zirconia (YSZ) fuel electrode degradation mechanisms in solid oxide electrolysis cells (SOECs) are complicated by the different possible Ni–YSZ microstructures and compositions, and the variations in the H 2 /H 2 O ratio encountered in an electrolysis stack. Here, in this study, we describe a life testing scheme aimed at providing survey results on degradation as a function of the H 2 O–H 2 composition, with life tests carried out at five different steam contents from 90% to 10%. A Ni–YSZ-supported symmetric cell geometry is employed both with and without infiltrated nanoscale gadolinia-doped ceria (GDC). Impedance spectroscopy is utilized to observe changes in electrochemical characteristics during the life test, and a transmission-line-based equivalent circuit is used to model the data. Post-test electrode microstructures were observed. The results suggest that the GDC infiltrant reduces the electrode polarization resistance and provides more stable electrode polarization over a range of conditions.

08 HYDROGEN↗
DOE OSTI2024

Evolution of connectivity architecture in the Drosophila mushroom body

Brain evolution has primarily been studied at the macroscopic level by comparing the relative size of homologous brain centers between species. How neuronal circuits change at the cellular level over evolutionary time remains largely unanswered. Here, using a phylogenetically informed framework, we compare the olfactory circuits of three closely related Drosophila species that differ in their chemical ecology: the generalists Drosophila melanogaster and Drosophila simulans and Drosophila sechellia that specializes on ripe noni fruit. We examine a central part of the olfactory circuit that, to our knowledge, has not been investigated in these species—the connections between projection neurons and the Kenyon cells of the mushroom body—and identify species-specific connectivity patterns. We found that neurons encoding food odors connect more frequently with Kenyon cells, giving rise to species-specific biases in connectivity. These species-specific connectivity differences reflect two distinct neuronal phenotypes: in the number of projection neurons or in the number of presynaptic boutons formed by individual projection neurons. Finally, behavioral analyses suggest that such increased connectivity enhances learning performance in an associative task. Our study shows how fine-grained aspects of connectivity architecture in an associative brain center can change during evolution to reflect the chemical ecology of a species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Quantum solver for single-impurity Anderson models with particle-hole symmetry

Quantum embedding methods, such as dynamical mean-field theory (DMFT), provide a powerful framework for investigating strongly correlated materials. A central computational bottleneck in DMFT is in solving the Anderson impurity model (AIM), whose exact solution is classically intractable for large bath sizes. In this work, we benchmark a quantum-classical hybrid solver tailored for particle-hole symmetric AIMs, using the variational quantum eigensolver to prepare the ground state of the model with shallow quantum circuits. The solver uses shallow quantum ansätze and one set of variational parameters to prepare the ground state and its particle and hole excitations, enabling the construction of the impurity Green’s function through a continued-fraction expansion. We evaluate the performance of this approach across a few bath sizes and interaction strengths under noisy, shot-limited conditions. We compare three optimization routines (COBYLA, Adam, and L-BFGS-B) in terms of convergence and fidelity, assess the benefits of estimating a quantum-computed moment correction to the variational energies, and benchmark the approach by comparing the density of states computed from the impurity Green’s function against that obtained using a classical pipeline. Our results demonstrate the feasibility of Green’s function construction on near-term devices and establish practical benchmarks for quantum impurity solvers embedded within self-consistent DMFT loops.

Karabin, Mariia [ORNL]↗
DOE OSTI2026

Resilience of the surface code to error bursts

Quantum error correction works effectively only if the error rate of gate operations is sufficiently low. However, some rare physical mechanisms can cause a temporary increase in the error rate that affects many qubits; examples include ionizing radiation in superconducting hardware and large deviations in the global control of atomic systems. We refer to such rare transient spikes in the gate error rate as error bursts. In this work, we investigate the resilience of the rotated surface code to generic error bursts. We assume that, after appropriate mitigation strategies, the spike in the error rate lasts for only a single syndrome-extraction cycle; we also assume that the enhanced error rate is uniform across the code block. Under these assumptions, and for a circuit-level depolarizing noise model, we perform Monte Carlo simulations to determine the regime in burst error rate and background error rate for which the memory time becomes arbitrarily long as the code block size grows. Our results indicate that suitable hardware mitigation methods combined with standard decoding methods may suffice to protect against transient error bursts in the rotated surface code.

Quantum error correction↗
DOE OSTI2024

Data-Driven Digital Twin for Reliability Assessment of DC/DC Buck Converter

In commercial applications, the operation of DC/DC converters significantly impacts overall system performance and long-term reliability. This study introduces a data-driven digital twin (DT) approach for estimating critical degradation parameters of DC/DC BUCK converter under steady-state condition. Initially, a circuit-level MATLAB/Simulink digital model (DM C ) is refined against a hardware prototype’s switching model dataset using offline particle swarm optimization. The optimized digital model’s steady-state response is then verified with its average model response while varying the duty and load. Subsequently, degradation profiles are imposed on the inductor, capacitor, MOSFET in the DMC. A large dataset is generated from this model, allowing training, validation, and testing of machine learning (ML) models for component health regression tasks. The proposed method employs random forest ML models, achieving impressive regression results with a squared R value as high as 0.99978 and a root mean square error of 4.2× 10 –6 . The method is further validated on a medium power level DC/DC BUCK prototype with varying load conditions, and includes the analysis of MOSFET’s on-resistance under degradation conditions. This data-driven DT method shows promise for identifying parasitic degradation and ohmic loss parameters, enhancing converter reliability assessments in a non-invasive, generalized, and computationally efficient manner.

14 SOLAR ENERGY↗
DOE OSTI2025

A Two-Stage Quantum Reinforcement Learning Method for Multi-Objective Transmission Switching

Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale increases, finding feasible solutions becomes increasingly challenging due to the problem's nonlinearity and high computational complexity. To address these challenges, this paper proposes a two-stage quantum reinforcement learning method that leverages potential quantum advantages for MO-TS. In the first stage, candidate switching lines are identified using a graph-theoretical approach to reduce the problem's dimensionality. The second stage introduces a quantum-classical reinforcement learning framework, where a learnable measurement-based CNN-ResVQC architecture is developed to effectively reduce the input dimension for quantum processing, mitigate vanishing gradients, and enhance trainability while improving the quantum circuit's flexibility in modeling complex decision policies for MO-TS. Numerical studies on IEEE 14-bus, 57-bus, and 118-bus systems demonstrate that the proposed algorithm achieves superior training stability and faster convergence with approximately 1% of the network parameters required by classical algorithms, highlighting its effectiveness, efficiency, and scalability. Furthermore, the practicality is validated through its stable convergence under three common quantum noise channels.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Parametric Modeling and Economic Analysis of a 2MW th 3-Stream sCO 2 Heat Exchanger

Here, this paper presents the design and cost optimization of a novel 2MW th 3-stream sCO2 plate-fin heat exchanger. This heat exchanger design is unique in that it uses reduced metal oxide particle-to-sCO2 heat exchanger for cost-effective energy storage applications. The design uses low velocity, laminar air as the re-oxidizing reactant to transfer the heat of the re-oxidizing reaction to a sCO2 power loop. The design of the heat exchanger is based on a 2-D, 3-fluid plate/fin heat transfer model. The model parameterizes the size, shape, and number of passages of the heat exchanger to calculate the temperature profile, pressure drop, and fluid velocities of all three fluids. Global heat exchanger parameters such as the effectiveness and total heat transferred to the sCO2 are then calculated for overall performance. Due to the value and increased use of sCO2 heat exchangers in power cycles, a cost model of the system based on the unique high temperature/high pressure operating conditions was created using quotes from reference projects and market analysis. These quoted air-to-sCO2 heat exchangers are then processed using multiple weighting factors pertinent to heat exchanger design, including heat exchanger type, maximum temperature, differential pressures, fluids, duty, and more. These factors are then used in an exponential function in order to generate a parameterized cost curve. The design and cost of the heat exchanger are then optimized using the SMPSO genetic algorithm in Python. The optimization objectives for the system are to maximize the overall system effectiveness, including an air recuperator for preheating, and to minimize unit costs. Additional constraints are added to the system for the sCO2 and air pressure drops, air velocity to reduce particle entrainment, and the length and volume of the heat exchanger.

Cost Model↗
DOE OSTI2022

Carrier Dynamics of Polar, Semipolar, and Nonpolar InGaN/GaN LEDs Measured by Small-Signal Electroluminescence

The carrier dynamics in InGaN/GaN light-emitting diodes (LEDs) are directly tied to their efficiency and maximum modulation speed, which are important metrics for solid-state lighting, displays, and optical communication. In this work, we measure the carrier dynamics of a variety of InGaN/GaN LEDs using small-signal electroluminescence methods [1]. A rate equation approach and associated small-signal circuit are used to model carrier injection, recombination in the active region, recombination in the cladding regions, and carrier escape. The model is fit to the measured optical frequency response (S21) and input impedance (S11) of the LEDs to extract the various carrier lifetimes, the carrier density, and the radiative and non-radiative recombination rates. We specifically study planar nonpolar and semipolar LEDs, which show record-high modulation speeds for III-nitride LEDs and present the modulation characteristics of core-shell nanowire-based LEDs. The planar nonpolar m-plane ($101\bar{0}$) micro-LEDs achieve a record-high -3dB modulation bandwidth for a III-nitride LED of 1.5 GHz [2]. The -3dB response of an electrically injected nanowire-based micro-LED with nonpolar facets is also reported, showing a -3dB bandwidth of 1.2 GHz [3]. The high speed is attributed to the shorter carrier lifetime associated with the nonpolar orientation. We also study the carrier dynamics in semipolar ($20\bar{2}\bar{1}$) LEDs for various temperatures [4]. Finally, we present carrier dynamics measurements on commercial-grade c-plane epitaxy for various active region designs, including a wavelength series and a growth quality series. The wavelength series offers insight into the contributions of the quantum confined Stark effect (QCSE) and InGaN material quality on the green gap [5]. The growth quality series investigates the role of non-radiative centers on the LED performance. Extraction of the carrier dynamics using small-signal electroluminescence offers insight into the factors limiting the efficiency and high-speed performance of III-nitride emitters and can be leveraged to ultimately improve the devices.

LEDs, InGaN, electroluminescence, bandwidth, modul↗
DOE OSTI2023

Carrier Dynamics of Polar, Semipolar, and Nonpolar InGaN/GaN LEDs Measured by Small-Signal Electroluminescence

The carrier dynamics in InGaN/GaN LEDs are directly tied to their efficiency and maximum modulation speed, which are important metrics for solid-state lighting, displays, and optical communication. We measure the carrier dynamics of nonpolar, semipolar, and commercial c-plane InGaN/GaN LEDs using small-signal electroluminescence methods. Rate equations and a small-signal circuit are used to model the carrier dynamics. The model is fit to the optical frequency response and input impedance of the LEDs to extract the carrier lifetimes and the recombination rates. The results offer insight into the underlying causes of efficiency droop and the green gap, and inform device design strategies.

42 ENGINEERING↗
DOE OSTI2022

Improved Understanding of Zircaloy Hydrogen Pickup Mechanisms in BWRs. NSUF Report (Final Report)

Using an instrumented autoclave operating at 288°C and 1100 psi, electrical impedance spectroscopy (EIS) measurements were taken from three neutron irradiated fuel channel samples (Zircaloy-2 and Zircaloy-4). The three high priority fuel channel samples were tested at 288°C using a simulated PWR water with the AC frequency range extending down through 10 -4 Hz, with corresponding DC measurements to validate the resistance measurements. EIS measurements were also taken at room temperature using a simulated PWR water from four neutron irradiated fuel channel samples (Zircaloy-2 and Zircaloy-4). and four water rod samples (Zircaloy-2). EIS measurements were also performed on unirradiated Zircaloy-2 tubes that were previously oxidized in autoclaves at various temperatures for different time durations to obtain oxide layers of different thicknesses. These experiments proved to be more challenging than anticipated because of the small size of the samples, which required development of fixtures to allow valid testing of the materials, some of which are radioactive, under pressure and temperature. Equivalent circuits were used to model the data. Some samples resulted in Nyquist plots where the arcs were too close to each other resulting in the inability to separate the different oxide morphological thicknesses. Microstructural characterization in the form of optical microscopy, scanning electron microscopy and (scanning) transmission electron microscopy was performed to document the microstructural features of the oxidized Zr-2 and Zr-4 samples (oxide and metal/oxide interface) and to interpret the EIS results. At the start of this work, it was assumed that despite the laminar cracks and porosity visible in both optical and SEM, the oxide scale is dense near the metal, effectively preventing the water from contacting the metal directly. While it is generally accepted that the large laminar cracks pores allow the water to percolate into the oxide film, it is unknown just how deep it can go, and how interconnected is the porosity, which will dictate how much the porosity is connected electrically to the water within the oxide scale. The EIS results demonstrated that there is in fact a distribution of oxide thicknesses over the various samples, and within each material condition, that are communicating to the liquid. This is derived from the fact that Nyquist plots have an arc radius whose center point is often below the Z’ axis, implying that instead of a single oxide thickness, these oxides have a distribution of thicknesses. This distribution of thicknesses produces arcs that are not clearly separable in most of the samples.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Enhanced Inductance and Winding Loss Model for Coupled Inductors

An enhanced model for coupled inductors with significant fringing effect is developed in the form of equivalent circuit. The equivalent circuit is derived from a physical model that captures the flux paths through a leakage inductor and two mutual inductors on the primary and secondary side. A mutual winding resistor is added in parallel with the mutual inductor to model the winding loss affected by the fringing flux that penetrates the winding. The equivalent circuit is verified by finite-element simulation (FES) and successfully predicts the open-circuit winding loss and winding loss variation with phase-shift impact.

Xue, Lincoln↗
DOE OSTI2026

Evaluation of a Reduced-Order Model for IBR Fault Response Representation via OEM Blackbox Models: Preprint

Driven by the need to capture the electromagnetic transients of transmission lines, inverter switching behavior, and detailed control systems, electromagnetic transient (EMT) studies have become increasingly important in industry, such as IBR interconnection study and fault study. However, original equipment manufacturer (OEM) inverter models typically include extensive parameters and proprietary settings that are unavailable to protection engineers. This paper introduces a data-driven, reduced-order model (ROM) developed as a PSCAD library component for use in EMT-based fault studies. The ROM replicates key OEM model behaviors without requiring detailed knowledge of control design or parameterization. The accompanying Python automation scripts streamline data generation, parameter fitting, and validation. The ROM's performance is demonstrated through comparison with both IEEE 2800-compliant and non-compliant OEM models in a real-world power system. Relay responses show nearly identical results, while simulation runtime is reduced by an average of 32.8\%, highlighting the ROM's practicality for protection engineers.

14 SOLAR ENERGY↗
DOE OSTI2024

Building spatial symmetries into parameterized quantum circuits for faster training

Practical success of quantum learning models hinges on having a suitable structure for the parameterized quantum circuit. Such structure is defined both by the types of gates employed and by the correlations of their parameters. While much research has been devoted to devising adequate gate-sets, typically respecting some symmetries of the problem, very little is known about how their parameters should be structured. In this work, we show that an ideal parameter structure naturally emerges when carefully considering spatial symmetries (i.e. the symmetries that are permutations of parts of the system under study). Namely, we consider the automorphism group of the problem Hamiltonian, leading us to develop a circuit construction that is equivariant under this symmetry group. The benefits of our novel circuitstructure, called ORB, are numerically probed in several ground-state problems. We find a consistent improvement (in terms of circuit depth, number of parameters required, and gradient magnitudes) compared to literature circuit constructions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Strong Zero Modes in Integrable Quantum Circuits

It is a classic result that certain interacting integrable spin chains host robust edge modes known as strong zero modes (SZMs). In this Letter, we extend this result to the Floquet setting of local quantum circuits, focusing on a prototypical model providing an integrable Trotterization for the evolution of the XXZ Heisenberg spin chain. By exploiting the algebraic structures of integrability, we show that an exact SZM operator can be constructed for these integrable quantum circuits in certain regions of parameter space. Our construction, which recovers a well-known result by Paul Fendley in the continuous-time limit, relies on a set of commuting transfer matrices known from integrability, and allows us to easily prove important properties of the SZM, including normalizabilty. Our approach is different from previous methods and could be of independent interest even in the Hamiltonian setting. Furthermore, our predictions, which are corroborated by numerical simulations of infinite-temperature autocorrelation functions, are potentially interesting for implementations of the XXZ quantum circuit on available quantum platforms.

1-dimensional spin chains↗
DOE OSTI2023

Demonstration of low-density, high-performance operation of sustained spheromaks and favorable scalability toward compact, low-cost fusion power plants (Final Scientific/Technical Report)

This project worked to advance the technical viability of a novel method for efficiently sustaining stable, high-performance spheromak plasma configurations to serve as the basis of compact, low-cost fusion power plants. In particular, our group worked to improve the method of Steady Inductive Helicity Injection (SIHI) with Imposed-Dynamo Current Drive (IDCD) for spheromak plasma sustainment. Prior to this project demonstrations of this plasma sustainment technology have achieved plasma performance consistent with entry milestone 3 of the BETHE FOA. Research and development (R&D) activities for this project were focused on increasing plasma performance toward a level consistent with exit milestone 4. To do this the PI and his group worked to increase the performance of sustained spheromaks produced in an existing experimental prototype (HIT-SIU) while improving confidence in projections to and design of future, higher performance devices through three primary R&D activities: 1) Improved control over the density of plasma in the device throughout a discharge to provide a pathway for demonstration of spheromaks Ohmically heating to the Mercier beta limit via: a. Fueling the device directly with plasma through the installation of pre-ionized source on the injectors b. Optimization of electrical current waveforms in the driver circuits to enable low-density plasma formation with a lower fueling rate 2) Computational demonstration of a validated, realistic injector circuit coupled to a dynamic plasma model capable of use as a design tool for SIHI drivers and associated circuits for new experimental design points on the pathway to commercial reactors. The improvements in plasma performance achieved during research activity 1), and the computational projections performed in research activity 2) increased the technological readiness level (TRL) of this fusion energy concept toward a level sufficient to attract early-stage private investment and/or other forms of follow-on investment to pursue required R&D activities required for the eventual fusion power plants based on this novel technical approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Exploring single-cell biosynthetic noise and dynamics for enhanced betaxanthin production in Escherichia coli

Cell-to-cell variability often limits the efficiency of microbial bioproduction, yet how individual cells fluctuate over time and how these fluctuations shape population-level output remain unclear. To address this issue, we tracked a heterologous betaxanthin pathway in Escherichia coli using microfluidics-assisted time-lapse microscopy, allowing simultaneous measurement of fluctuations in betaxanthin, its biosynthetic enzyme DOD and growth across generations. Here we show that over 50% of high betaxanthin producers become medium or low producers after two divisions. Betaxanthin variation primarily originates from DOD noise, with a smaller contribution from growth rate fluctuations. We further develop a stochastic model to explore various control circuits and find that pathway enzyme or metabolite-based growth selection strategies are most effective in enhancing production. We experimentally validate the model by coupling enzyme expression to nutrient availability, which enriches high producers and boosts titer by 4.4-fold. Our results highlight key sources of metabolic heterogeneity and provide a framework for designing robust microbial processes.

Bacterial systems biology↗
DOE OSTI2022

Fixed Depth Hamiltonian Simulation via Cartan Decomposition

Simulating quantum dynamics on classical computers is challenging for large systems due to the significant memory requirements. Simulation on quantum computers is a promising alternative, but fully optimizing quantum circuits to minimize limited quantum resources remains an open problem. In this study, we tackle this problem by presenting a constructive algorithm, based on Cartan decomposition of the Lie algebra generated by the Hamiltonian, which generates quantum circuits with time-independent depth. We highlight our algorithm for special classes of models, including Anderson localization in one-dimensional transverse field $\mathrm{XY}$ model, where $\mathscr{O}$(n 2 )-gate circuits naturally emerge. Compared to product formulas with significantly larger gate counts, our algorithm drastically improves simulation precision. In addition to providing exact circuits for a broad set of spin and fermionic models, our algorithm provides broad analytic and numerical insight into optimal Hamiltonian simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗