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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Radiation Stability of Mixed Tin-Lead Halide Perovskites: Implications for Space Applications

Mixed organic-inorganic halide perovskite solar cells (PSCs) have received considerable attention in recent years for their impressive solar to electrical power efficiency gains and potentially lower material and processing costs for optoelectronic applications. In addition to terrestrial applications, PSCs are of interest to the space power markets for their low cost, low weight, adaptability to flexible architectures, and tolerance to high energy particle irradiation (mainly protons and electrons). Here we investigate the properties of mixed formamidinium-methylammonium tin-lead iodide (FASn)0.6(MAPb)0.4I3 perovskites which lower the lead content as well as the bandgap, making them attractive for the low bandgap absorber material in tandem PSCs. Through current density-voltage (JV) characterization at lower temperatures, majority carrier transport is hindered and a barrier to photogenerated carrier extraction is evident. This is attributed to the thermally induced change of the bandgap of the absorber layer relative to the energy selective contacts in the device. We find that although the architecture used here hinders the performance at temperatures below 225 K, the tolerance to high energy (3.7 MeV) protons is impressive, considerably out-performing commercially available thin-film CIGS. These results suggest further improvements to structural and interface stability as well as lightweight encapsulation could lead to all perovskite flexible tandem arrays deployed for power generation on missions to low Earth orbit, the moon, Mars, and beyond.

perovskite solar cells↗
DOE OSTI2021

Analysis of power conversion technology options for a self-powered furnace

A self-powered furnace is defined as one that imports no electricity: a power cycle integrated into the furnace generates all the electrical power needed, and the heat rejected by the power cycle contributes to space heating. This paper presents criteria for selection of suitable power generation technology for such a furnace. A weighting system was presented to assign weight to each criterion based on its importance to the success of a self-powered furnace implementation. Power generation candidates were reviewed and scored based on the selection criteria. The top five candidates were analyzed to quantitatively compare the additional heat exchange requirements they impose on a baseline furnace. Air-cooled internal combustion engines and microturbine generators had negligible impact on the heat exchange requirement compared to a baseline furnace. Liquid-cooled internal combustion engines increased the heat exchange requirement by a factor of 1.5. Thermoelectric generators and thermophotovoltaic increased the heat exchange requirement by a factor of roughly 2.5. Organic Rankine cycle increased the heat exchange requirement by a factor of 5.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A Cybersecurity Event Simulation Tool and Platform

Digital Instrumentation and Control Systems (ICSs) have replaced analog control systems in nuclear power plants raising cybersecurity concerns. To study and understand the cybersecurity risks of nuclear power plants both high fidelity models of the plant physics and controllers must be created, and a framework to test and evaluate cyber security events must be established. A testing and evaluation framework of cybersecurity events consists of a method of interfering with control systems, a simulation of the plant network, and a network packet capture and recording tool. Sandia National Labs (SNL) in collaboration with the University of New Mexico’s Institute for Space and Nuclear Power Studies (UNM-ISNPS) is developing such a cybersecurity testing framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Validation of theory-based models for the control of plasma currents in W7-X divertor plasmas

A theory-based model for the control of plasma currents for steady-state operation in W7-X is proposed and intended for model-based plasma control. The conceptual outline implies the strength of physics-based models: it offer approaches applicable to future conditions of fusion devices or next-step machines. The application at extrapolated settings is related to the validity range of the theory model. Therefore, the predictive power of theory-based control models could be larger than for data-driven approaches and limitations can be predicted from the validity range for the prediction of bootstrap currents in W7-X. The model predicts the L/R response when density or heating power is changed. The model is based on neoclassical bootstrap current calculations and validated for different discharge conditions. While the model was found to be broadly applicable for conducted electron-cyclotron-heated discharges in W7-X, limits were found for cases when the polarization of the electron cyclotron heating was changed from X2 to O2-heating. The validity assessment attempts to quantify the potential of the derived model for model-based control in the operational space (density, heating power) of W7-X.

neoclassical modelling↗
DOE OSTI2026

Resilience of High-Efficiency CdSeTe:As and CdSeTe:Cu Solar Cells to Proton Irradiation

Power generation in space is currently dominated by expensive III-V multi-junction photovoltaic (PV) devices and cheap crystalline silicon (c-Si) PV devices. Both of these technologies degrade rapidly in proton-radiation-rich space environments, such as the Van Allen belt. The present study of cadmium selenide telluride- (CdSeTe-) based PV devices exposed to 150-to-1500 keV proton irradiation with fluences up to 9 x 1013 cm-2 reveal a more radiation-hard alternative to III-V and c-Si PV technologies. We report on measurement and analysis of current density vs voltage (JV), external quantum efficiency (EQE), external radiative efficiency, and capacitance vs voltage (CV) characteristics. JV characteristics of As-doped CdSeTe devices show 80% remaining power conversion efficiency (PCE) relative to unexposed controls when exposed to 650 keV protons at a fluence of 1012 cm-2. Under these same irradiation conditions, Cu-doped CdSeTe devices demonstrate an even better 95% PCE retention compared with unirradiated control devices. Evidence of radiation-induced absorber p-type doping compensation is observed in the glass-side EQE at 0 V and CV characteristics of most of the irradiated CdSeTe:As devices, but clear compensation is evident only for the most heavily irradiated CdSeTe:Cu devices. Elevated blue-green photocurrent in the film-side 0 V EQE suggests a buried junction in the most heavily irradiated CdSeTe:As devices. Although CdSeTe:Cu devices are the more resilient of the CdSeTe structures, both CdSeTe-based technologies are radiation-hard when compared to c-Si and III-V multi-junction PV.

14 SOLAR ENERGY↗
DOE OSTI2021

Modeling of Am-241 as an alternative fuel source in a radioisotope thermoelectric generator

Radioisotope thermoelectric generators (RTGs) have been utilized in the USA to power satellites and space exploration equipment for over half a century. In our preceding paper, Dustin and Borrelli (2021), we assessed the performance of 241 Am as an alternative to 238 Pu by modeling the specific decay-heat and gamma spectra of several potential radioisotopes in SCALE-ORIGEN, and comparing these with 238 Pu An analysis of heat output, heat stability, safety, availability and required mass showed that of the isotopes reviewed, 241 Am had the greatest potential for replacing 238 Pu, with additional design considerations. In our current work, we have assessed radiation transport for two configurations of an 241 Am powered Multi-Mission Radioisotope Thermoelectric Generator (MMRTG), due to the potential health effects for operators, fabricators, and others with the potential to be exposed to neutrons and lower energy gamma rays. We have modeled the use of americium as a fuel source replacement for plutonium in current MMRTG designs. The assessment has been performed using MCNP6, in terms of neutron and gamma emissions that might interfere with sensitive equipment and power system production. The radiation transport behavior in terms of dose rate of the 241 Am fueled models is compared with that of a 238 Pu fueled model. Finally, additional work was performed to validate modeling simplifications with regards to thermocouple material configurations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Stochastic machine learning via sigma profiles to build a digital chemical space

This work establishes a different paradigm on digital molecular spaces and their efficient navigation by exploiting sigma profiles. To do so, the remarkable capability of Gaussian processes (GPs), a type of stochastic machine learning model, to correlate and predict physicochemical properties from sigma profiles is demonstrated, outperforming state-of-the-art neural networks previously published. The amount of chemical information encoded in sigma profiles eases the learning burden of machine learning models, permitting the training of GPs on small datasets which, due to their negligible computational cost and ease of implementation, are ideal models to be combined with optimization tools such as gradient search or Bayesian optimization (BO). Gradient search is used to efficiently navigate the sigma profile digital space, quickly converging to local extrema of target physicochemical properties. While this requires the availability of pretrained GP models on existing datasets, such limitations are eliminated with the implementation of BO, which can find global extrema with a limited number of iterations. A remarkable example of this is that of BO toward boiling temperature optimization. Holding no knowledge of chemistry except for the sigma profile and boiling temperature of carbon monoxide (the worst possible initial guess), BO finds the global maximum of the available boiling temperature dataset (over 1,000 molecules encompassing more than 40 families of organic and inorganic compounds) in just 15 iterations (i.e., 15 property measurements), cementing sigma profiles as a powerful digital chemical space for molecular optimization and discovery, particularly when little to no experimental data is initially available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Renormalon cancellation and linear power correction to threshold-like asymptotics of space-like parton correlators

Abstract In this paper, we show that the common hard kernel of double-log-type or threshold-type factorization for certain space-like parton correlators that arise in the context of lattice parton distributions, theheavy-light Sudakov hard kernel, has linear infrared (IR) renormalon. We explicitly demonstrate how this IR renormalon correlates with ultraviolet (UV) renormalons of next-to-leading power operators in two explicit examples: threshold asymptotics of space-like quark-bilinear coefficient functions and transverse momentum dependent (TMD) factorization of quasi wave function amplitude. Theoretically, the pattern of renormalon cancellation complies with general expectations to marginal asymptotics in the UV limit. Practically, this linear renormalon explains the slow convergence of imaginary parts observed in lattice extraction of the Collins-Soper kernel and signals the relevance of next-to-leading power contributions. Fully factorized, fully controlled threshold asymptotic expansion for space-like quark-bilinear coefficient functions in coordinate and moment space has also been proposed.

Physics↗
DOE OSTI2021

Cooling and Timing Tests of the ATLAS Fast TracKer VME Boards

The Fast TracKer (FTK) is an ATLAS trigger upgrade built for full-event, low-latency, high-rate tracking. The FTK core, made of 9U VME boards, performs the most demanding computational task. The associative memory board (AMB) serial link processor and the auxiliary card (AUX), plugged on the front and back sides of the same VME slot, constitute the processing unit (PU), which finds tracks using hits from eight layers of the inner detector. The PU works in pipeline with the second stage board (SSB), which finds 12-layer tracks by adding extra hits to the identified tracks. In the designed configuration, 16 PUs and four SSBs are installed in a VME crate. The high power consumption of the AMB, AUX, and SSB (respectively, of about 250, 70, and 160 W per board) required the development of a custom cooling system. Even though the expected power consumption for each VME crate of the FTK system is high compared with a common VME setup, the 8 FTK core crates will use ≈60 kW, which is just a fraction of the power and the space needed for a CPU farm performing the same task. We report on the integration of 32 PUs and eight SSBs inside the FTK system, on the infrastructures needed to run and cool them, and on the tests performed to verify the system processing rate and the temperature stability at a safe value.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗
DOE OSTI2021

Theory and application of the vector pair correlation function for real-space crystallographic analysis of order/disorder correlations from STEM images

Deviations of local structure and chemistry from the average crystalline unit cell are increasingly recognized to have a significant influence on the properties of many technologically important materials. Here, we present the vector pair correlation function (vPCF) as a new real-space crystallographic analysis method, which can be applied to atomic-resolution scanning transmission electron microscopy (STEM) images to quantify and analyze structural order/disorder correlations. Our STEM-based vPCFs have several advantages over radial PCFs and/or 3D pair distribution functions from x-ray total scattering: vPCFs explicitly retain crystallographic orientation information, are spatially resolved, can be applied directly on a sublattice basis, and are suitable for any material that can be imaged with STEM. To show the utility of our approach, we measure partial vPCFs in Ba 5 SmSn 3 Nb 7 O 30 (BSSN), a tetragonal tungsten bronze (TTB) structured complex oxide. Many TTBs are known to be classical or relaxor ferroelectrics, and these properties have been correlated with the presence of superlattice ordering. BSSN, specifically, exhibits relaxor behavior and an incommensurate structural modulation. From the vPCF data, we observe that, of the cation sites, only the Ba (A2) sublattice is structurally modulated. We then infer the local modulation vector and reveal a marked anisotropy in its correlation length. Finally, short-range correlated polar displacements on the B2 cation sites are observed. This work introduces the vPCF as a powerful real-space crystallography technique, which enables direct, robust quantification of short-to-long range order on a sublattice-specific basis and is applicable to a wide range of complex material types.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Results of the KRUSTY Warm Critical Experiments

The Kilowatt Reactor Using Stirling TechnologY (KRUSTY) was a prototypic nuclear-powered test of a 5-kW(thermal) Kilopower space reactor. This paper presents results from the KRUSTY warm critical experiments, which were completed prior to the final system test. The first set of criticals comprised cold or zero-power criticals; i.e., the core was not heated by fission power. These were followed by three warm criticals, where fission power heated the core to 200°C, 300°C, and 450°C, respectively. These criticals provided the data, confidence, and regulatory framework that were needed to proceed with the KRUSTY nuclear system test. The criticals also provided valuable data for the benchmarking of codes applicable to all nuclear systems. Finally, a comparison of KRUSTY results to pretest predictions is provided, and overall, the models matched the experimental results very closely.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Neutronics Analysis of Cold Critical KRUSTY Experiments using MCNP and Serpent

Kilowatt Reactor Using Stirling Technology (KRUSTY) is a prototype designed as a proof of concept for NASA’s Kilo power program, which was funded in order to create a small reactor for various space applications such as providing power for a colony on Mars or the moon and eventually as a possible option for powering rockets on deep space missions. KRUSTY was tested at the National Criticality Experiments Research Center (NCERC) located at the Nevada National Security Site (NNSS) from November 2017, through March 2018. The experimental campaign was conducted in four phases: com ponent critical experiments, cold critical experiments, warm critical runs, and high temperature demonstration. The component critical and cold critical experiments were used to determine the worth of the beryllium oxide (BeO) reflector rings and the boron carbide (B4C) control rod disks under different conditions. These conditions were altered by the addition and subtraction of other components in the assembly. The component critical phase was performed at atmospheric pressure and had four solid support rods spanning the center core; whereas the cold critical phase had the center core placed in a vacuum chamber and eight sodium-filled heat pipes spanning the center core region. This summary discusses the static neutronic analysis completed on the cold critical phase of the campaign using MCNP ® and Serpent. These two codes were used to assess any potential differences or biases in the simulation results. Understanding these potential biases is a key step toward the final goal of being able to fully analyze the transient experiments performed during phases 3 and 4 of the campaign.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Characterization of fluidized bed chemical vapor deposition ZrC coatings on PyC/YSZ kernels deposited under differing conditions

In this study, coated fuel particle architectures with ZrC coatings are candidate fuels for advanced power reactors and space nuclear propulsion (SNP) concepts. Owing to its relevance to SNP, the composition, microstructure, and mechanical properties of eight ZrC coatings prepared by fluidized bed chemical vapor deposition were evaluated. Evaluation by SEM and EBSD showed that all grains were columnar. Across the various examined samples, minor axis diameters varied between 0.3 and 1.1 μm, and major axis diameters varied between 0.4 and 2.3 μm. Major and minor diameters increased with thickness particularly at higher deposition temperatures in which the major grain axis (from an ellipse fit to the grain shape) increased by 2.5 μm over the entire coating. Coatings with higher reactive gas flows and Zr/C concentrations closer to 1 were observed to contain nanocrystalline graphite deposits. Reactive gas flow doubling led to increases in coating thickness from around 10–15 μm to around 22–27 μm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Quantum Accurate Prediction of Plutonium–Plutonium Dihydride Phase Equilibrium Using a Lattice Gas Model

Plutonium-based materials are vital for use as nuclear fuels and as portable power sources for space vehicles. However, elucidating their sensitivity to hydriding corrosion represents an extreme challenge because of the toxicity of Pu as well as their anomalous magnetic properties. In this work, we develop a lattice gas model of plutonium–plutonium dihydride (Pu–PuH 2 ) phase equilibrium that retains the accuracy of density functional theory, while yielding many orders of magnitude improvement in computational efficiency. Using Monte Carlo and free-energy sampling algorithms, we compute a number of Pu–PuH 2 equilibrium properties that are difficult to probe experimentally, including equilibrium pressures and phase compositions and the PuH 2 heat of formation. In conclusion, our method will have particular impact on these types of materials studies, where there is a strong need for computationally efficient approaches to bridge time and length scale gaps between quantum calculations and experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Beyond the two-point correlation: Constraining primordial non-Gaussianity with density-perturbation moments

Constraining primordial non-Gaussianity (PNG) on the large-scale cosmic structure (LSS) is an important step in understanding properties of the early Universe, specifically in distinguishing between different inflationary models. Measuring PNG relies on evaluating the scale-dependent correlations in the density field. New summary statistics beyond the two- and three-point correlation functions in configuration space and their Fourier-space counterparts, the power- and bispectrum may provide increased sensitivity. We introduce a new method for extracting the PNG signal imprinted on the LSS by using the first three Gaussian moments of the normalized correlation in density perturbations, evaluated on varying distance scales. We aim to assess this method’s sensitivity to local PNG, parameterized by f NL . We performed spherical convolutions on a range of scales on dark-matter-halo simulations to measure the scale-dependent correlations in the density field. From these, we computed the first three moments and compared them to a model expectation vector, parameterized to the second power in f NL . Our method provides about 21% improvement in sensitivity to f NL with respect to using the two-point correlation function alone. Notably, we find that the second moment alone carries nearly as much constraining power as the mean, highlighting the potential of higher order statistics. Given its simplicity and efficiency, this framework is well suited for application to current and upcoming large-scale surveys such as the Dark Energy Spectroscopic Instrument (DESI).

early universe↗
DOE OSTI2023

Autonomous sputter synthesis of thin film nitrides with composition controlled by Bayesian optimization of optical plasma emission

Autonomous experimentation has emerged as an efficient approach to accelerate the pace of material discovery. Although instruments for autonomous synthesis have become popular in molecular and polymer science, solution processing of hybrid materials, and nanoparticles, examples of autonomous tools for physical vapor deposition are scarce yet important for the semiconductor industry. Here, we report the design and implementation of an autonomous workflow for sputter deposition of thin films with controlled composition, leveraging a highly automated sputtering reactor custom-controlled by Python, optical emission spectroscopy (OES), and a Bayesian optimization algorithm. We modeled film composition, measured by x-ray fluorescence, as a linear function of plasma emission lines monitored during co-sputtering from elemental Zn and Ti targets in an N 2 and Ar atmosphere. A Bayesian control algorithm, informed by OES, navigates the space of sputtering power to fabricate films with user-defined compositions by minimizing the absolute error between desired and measured optical emission signals. We validated our approach by autonomously fabricating Zn x Ti 1-x N y films that deviate from the targeted cation composition by a relative ±3.5%, even for 15 nm thin films, demonstrating that the proposed approach can reliably synthesize thin films with a specific composition and minimal human interference. Moreover, the proposed method can be extended to more difficult synthesis experiments where plasma intensity lines depend non-linearly on pressure, or the elemental sticking coefficients strongly depend on the substrate temperature.

36 MATERIALS SCIENCE↗