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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Thermal energy storage in concrete utilizing a thermosiphon heat exchanger

The performance of a lab-scale concrete thermal energy storage (TES) module with a 2-kWh thermal capacity is evaluated at temperatures up to 400 °C. The TES module uses conventional normal weight concrete with thermal and mechanical properties that are tailored for use as a solid thermal energy storage media. A thermosiphon heat exchanger is used to provide rapid heat transfer into the concrete module, which is reinforced with a steel pipe outer shell. The charging and discharging cycles are examined to assess the thermal performance of the concrete and thermosiphon. Based on the results of testing, the thermosiphon is able to repeatably charge the concrete module from 300 to 400 °C over a 4-h period. After 2250 total hours of charge and discharge cycles, there was no observed delamination between the concrete and the thermosiphon or the steel jacket reinforcement. Non-destructive measurements of the concrete indicated no significant degradation of the solid storage media. The experimental results are then used to validate a numerical model of the concrete TES module for parametric study. Finally, varying insulation conditions were analyzed using this model to determine practical configurations for regular operation of the proposed concrete TES module.

25 ENERGY STORAGE↗
DOE OSTI2026

Air-Stable Room-Temperature Quasi-2D Tin Iodide Perovskite Microlasers

Quasi-2D tin iodide perovskites (TIPs) are promising lead-free alternatives for optoelectronic applications, but achieving stable lasing remains challenging due to their limited environmental stability. Here, we report air-stable, room-temperature lasing from quasi-2D TIP microcrystals as small as 4 μm. Incorporation of the organic spacer 5IPA3 significantly enhanced the stability of these materials compared with previously reported TIPs. Lasing was observed from both dielectric (n = 4) and plasmonic (n = 3 and n = 4) TIP microlasers. Under picosecond pumping, lasing was sustained for over 108 pump pulses in ambient conditions. These results represent a significant step toward practical photonic applications of tin-based perovskites.

crystals↗
DOE OSTI2023

Recreating the California New Year's Flood Event of 1997 in a Regionally Refined Earth System Model

Abstract The 1997 New Year's flood event was the most costly in California's history. This compound extreme event was driven by a category 5 atmospheric river that led to widespread snowmelt. Extreme precipitation, snowmelt, and saturated soils produced heavy runoff causing widespread inundation in the Sacramento Valley. This study recreates the 1997 flood using the Regionally Refined Mesh capabilities of the Energy Exascale Earth System Model (RRM‐E3SM) under prescribed ocean conditions. Understanding the processes causing extreme events informs practical efforts to anticipate and prepare for such events in the future, and also provides a rich context to evaluate model skill in representing extremes. Three California‐focused RRM grids, with horizontal resolution refinement of 14 km down to 3.5 km, and six forecast lead times, 28 December 1996 at 00Z through 30 December 1996 at 12Z, are assessed for their ability to recreate the 1997 flood. Planetary to synoptic scale atmospheric circulations and integrated vapor transport are weakly influenced by horizontal resolution refinement over California. Topography and mesoscale circulations, such as the Sierra barrier jet, are better represented at finer horizontal resolutions resulting in better estimates of storm total precipitation and storm duration snowpack changes. Traditional time‐series and causal analysis frameworks are used to examine runoff sensitivities state‐wide and above major reservoirs. These frameworks show that horizontal resolution plays a more prominent role in shaping reservoir inflows, namely the magnitude and time‐series shape, than forecast lead time, 2‐to‐4 days prior to the 1997 flood onset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Demonstration of machine-learning-enhanced Bayesian quantum state estimation

Machine learning (ML) has found broad applicability in quantum information science in topics as diverse as experimental design, state classification, and even studies on quantum foundations. Here, we experimentally realize an approach for defining custom prior distributions that are automatically tuned using ML for Bayesian quantum state estimation methods that generally better conform to the physical properties of the underlying system than standard fixed prior distributions. Previously, researchers have looked to Bayesian quantum state tomography for advantages like uncertainty quantification, the return of reliable estimates under any measurement condition, and minimal mean-squared error. However, practical challenges related to long computation times and conceptual issues concerning how to incorporate prior knowledge most suitably can overshadow these benefits. Using both simulated and experimental measurement results, we demonstrate that ML-defined prior distributions reduce net convergence times and provide a natural way to incorporate both implicit and explicit information directly into the prior distribution. These results constitute a promising path toward practical implementations of Bayesian quantum state tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Theory of the Little-Parks effect in spin-triplet superconductors

The celebrated Little-Parks effect in mesoscopic superconducting rings has recently gained great attention due to its potential to probe half-quantum vortices in spin-triplet superconductors. However, despite the large number of works reporting anomalous Little-Parks measurements attributed to unconventional superconductivity, the general signatures of spin-triplet pairing in the Little-Parks effect have been less systematically investigated. Here we use Ginzburg-Landau theory to study the Little-Parks effect in a spin-triplet superconducting ring that supports half-quantum vortices; we calculate the field-induced Little-Parks oscillations of both the critical temperature itself and the residual resistance resulting from thermal vortex tunneling below the critical temperature. Here we observe two separate critical temperatures with a single-spin superconducting state in between and find that due to the existence of half-quantum vortices, each minimum in the upper critical temperature splits into two minima for the lower critical temperature. From a rigorous calculation of the residual resistance, we confirm that these two minima in the lower critical temperature translate into two maxima in the residual resistance below and establish the general conditions under which the two maxima can be practically resolved. In particular, we identify a fundamental trade-off between sharpening each maximum and keeping the overall magnitude of the resistance large. Our results will guide experimental efforts in designing mesoscopic ring geometries for probing half-quantum vortices in spin-triplet candidate materials on the device scale.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Application of C ( t )-Integral Solutions in Extending ASME BPVC Section XI Division 2 Code Case N-934 for Transient Creep Crack Growth

Creep crack growth is a phenomenon which arises in damaged metallic structures under combined primary and secondary loads in the creep regime. The High Temperature Flaw Evaluation Code Committee of the American Society of Mechanical Engineers Boiler and Pressure Vessel Code (BPVC) is evaluating methods in extending Code Case N-934 to capture transient creep crack growth. Here, this paper provides context and basic examples on the selected approach to transient creep crack growth methods based on the C(t)-integral. The basis for selected C(t)-integral solution as analytical method is established, including an overview of its derivation. Practical assessments of a crack growing under creep conditions in a realistic component are conducted to illustrate the analytical approach. Additional considerations in the application of the analytical methods and limitations are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Equity-Centered Engagement Through Climate Resilience Policy in Massachusetts

Resilience efforts tend to reinforce injustices. Communities who experience disproportionate climate impacts are often excluded from resilience planning, and those plans do not typically address root causes of social vulnerability. More transformational approaches to resilience would shift decision-making power into communities and affect how people survive and thrive in a climate changing world. The Massachusetts Municipal Vulnerability Preparedness (MVP) 2.0 program is an attempt to change the status quo in resilience planning by bringing new voices into decision-making power, recognizing their labor, addressing root causes of vulnerability, and investing in social infrastructure. It aims to build capacity for equity-focused community engagement within teams of municipal staff and community liaisons, and ultimately build community cohesion. My mixed methods research investigates implementation of this state grant program in several Massachusetts towns. I am using document review, participant observation, and interviews to understand the MVP 2.0 process as written, how different municipalities navigate it, and how individuals make sense of their experiences in it. I seek to understand how those experiences explain relationships between engagement approaches, mediating factors, and process outcomes. I am interested in the conditions that allow for community empowerment and how a model like MVP 2.0 can shift conditions that hold systems in place. In a practical sense, my empirical results will help municipalities reflect on their work during MVP 2.0 and plan for future community engagement. They may be informative for designing future iterations of the MVP program and for other municipalities, offices of community engagement, and practitioners. The findings will also contribute to the participation, resilience, and climate justice literatures, by adding perspectives on equity-centered resilience and community engagement approaches in smaller towns and rural settings.

Callaham, Shannon↗
DOE OSTI2022

The Future of Energy Efficiency for U.S. Buildings - Drivers and Market Scenarios

This paper identifies likely drivers of building efficiency over the next ten years and expectations for how efficiency markets may evolve over this period. To prepare these predictions, we conducted an extensive literature review, interviewed 22 experts, reviewed legislation and executive orders in 12 states, and implemented a detailed questionnaire completed by 41 efficiency practitioners. The two most important drivers revealed by our research are (1) public policies and regulations, particularly those associated with climate change mitigation and adaptation and (2) the cost of energy relative to the cost of delivering efficiency. Other important drivers are technology changes, economic conditions, social priorities, and industry (including utility) business practices for increasing the uptake of efficiency in buildings. Our research indicates that efficiency markets will increasingly focus on supporting building decarbonization and enabling demand flexibility through the use of controls in grid-interactive efficient buildings and communities. Efficiency improvements for specific technologies (e.g., heat pumps, controls, and windows) and technological advances not specific to energy technologies (e.g., interoperability, artificial intelligence, and universal internet access) will improve the efficacy of efficiency measures and actions. Marketing of efficient products and services will increasingly focus on grid services, decarbonization, non-energy benefits for consumers, and integration with other distributed energy resources (DERs). We anticipate increased investment in disadvantaged and historically underserved communities, recognizing the social, health, and safety benefits of efficient energy usage and remediating historical biases. Lastly, we predict that while state and local government actions will vary, jurisdictions will increase their efficiency goals overall.

Schiller, Steven R↗
DOE OSTI2024

The Hard Life of Floatovoltaics: Modeling Wind-Driven Oscillations of Floating Solar Panels

Modern, thin photovoltaic (PV) panels for solar power are susceptible to high stress loads in windy conditions. Manufacturers are eager to determine optimal installation practices to reduce these loads, including in the relatively new practice of installing PV on floating structures located on artificial and natural lakes. As part of our effort to develop simulation capabilities for stress on such floating PV systems, we here present our combined model-simulation approach, which simulates the dynamic wind loading and uses modeled elements to capture both the hydrodynamic and mooring-line forces. We discuss the forces important for our model and the challenges inherent in our simulation. Of particular interest is our model of the hysteresis response displayed by the attached mooring lines, which are engineered to damp motion and oscillation of the floating panel system. We validate our approach against the benchmark problem of vortex-induced vibration of a cylinder, which is driven by the same dynamic forces present in floating PV panels.

floating↗
DOE OSTI2026

Adaptive spectra-to-exposure conversion using ridge regularized polynomial response models

Real-time gamma spectra-to-exposure conversion in aerial and ground monitoring commonly relies on calibration-derived, detector- or system-specific conversion coefficients that are assumed to generalize across operational environments. In practice, deployment specific differences in spectral composition and transport conditions can introduce systematic bias relative to reference instruments, motivating methods that adapt coefficients using minimal field supervision while explicitly limiting overfitting. In this work, we present a conservative coefficient adaptation framework that updates a baseline polynomial energy-weighting function using ridge-regularized regression, with leave-one-out cross-validation (LOOCV) used to select the regularization strength. The findings support ridge-constrained minimal-supervision adaptation as a practical mechanism to suppress site-specific bias without destabilizing a calibration-derived baseline.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Ionic‐Liquid Free and Flexible Transistors Made of 2D Material Inks

The development of thin-film transistors (TFTs) using 2D materials is crucial for enabling scalable, low-cost, and flexible electronics. Currently, 2D TFTs with the highest performance have been achieved by using ionic-liquid gating (ILG), a technique suited for proof-of-concept studies. However, ILG suffers from slow switching speeds, temperature sensitivity, poor long-term stability, and integration challenges, making it unsuitable for practical use. Moreover, typical fabrication methods for 2D TFTs involve harsh conditions such as strong acids or high temperatures (>300 °C), limiting integration with flexible substrates. This work provides the first demonstration of an ILG-free, all-2D-material TFT fabricated onto a flexible substrate. Water-based graphene and hexagonal boron nitride (h-BN) inks are printed to deposit the electrodes and dielectric layers, respectively. The MoS 2 channel is produced via supramolecular interfacial self-assembly, yielding uniform, monolayer-rich films transferable to rigid and flexible substrates. The resulting TFTs operate below 3 V, exhibit negligible leakage current, and achieve field-effect mobilities up to 0.46 cm 2 V −1 s −1 (rising to 2.47 cm 2 V −1 s −1 with silver electrodes) measured under ambient conditions, while maintaining excellent mechanical flexibility. This work establishes a low-cost and scalable solution-processable platform for flexible electronics based on 2D materials that match requirements for practical applications.

2D materials↗
DOE OSTI2021

Natively Periodic Fast Multipole Method: Approximating the Optimal Green’s Function

The fast multipole method (FMM) obeys periodic boundary conditions "natively" if it uses a periodic Green's function for computing the multipole expansion in the interaction zone of each FMM oct-tree node. One can define the "optimal" Green's function for such a method that results in the numerical solution that converges to the equivalent particle-mesh (PM) solution in the limit of sufficiently high order of multipoles. A discrete functional equation for the optimal Green's function can be derived, but is not practically useful as methods for its solution are not known. Instead, this paper presents an approximation for the optimal Green's function that is accurate to better than 10 -3 in ${L}_{\mathrm{MAX}}$ norm and 10 -4 in L 2 norm for practically useful multipole counts. Such an approximately optimal Green's function offers a practical way for implementing the FMM with periodic boundary conditions natively, without the need to compute lattice sums or to rely on hybrid FMM-PM approaches.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Factors Impacting Nuclear Energy Share in U.S. Energy Markets

The purpose of this report is to collate information and findings from recent studies conducted by national and international bodies/institutes to identify approaches for maintaining/enhancing the role of nuclear energy in the current and future energy mix of the United States. This report shows how nuclear generation grew quickly to provide 20% of U.S. electricity, sustaining that level for three decades without the benefit of new construction, but is now projected to decline going forward. Nuclear construction costs in the U.S. spiraled out of control, ending construction for two decades and the recent resumption of construction has continued the pattern of schedule delays and cost overruns. However, nuclear operations exhibited strong learning, achieving and sustaining the highest capacity factor of any electricity generation technology and license extensions and uprates have sustained nuclear market share. The share of nuclear energy in the U.S. electricity market is projected to decline by ~1/3rd over the next 30 years The report provides an overview of how the markets work in theory and in practice. It indicates how market deregulation and clean energy policies have created conditions where nuclear plants are being retired for economic rather than technical reasons. The report also shows how many of the markets do not in practice have free competition but instead have outcomes that are being determined more and more by policy instead of market forces. While electricity costs from existing nuclear plants are low, electricity from new builds is projected to be too expensive to be competitive head-to-head with natural gas, even for nth-of-a-kind costs. Wind and solar energy have enjoyed an extended period of sustained subsidy. This protected environment has resulted in a sustained reduction in plant level costs to the point that some of these Variable Renewable Energy (VRE) technologies are becoming competitive even if their direct subsidies are removed. But plant level costs underestimate total VRE costs which include a number of system-level externalities. The incremental system value of additional VRE capacity was shown to decline as market share increases, with solar value declining more quickly than wind. The report closes with examination of a possible future for nuclear generation as part of deep decarbonization of the electricity sector. This approach avoids direct competition with natural gas. The two options for achieving 100% decarbonization are to use only renewables or to use all zero emissions technologies, and the report shows the second approach is much less expensive than the first.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Temperature-dependent dynamic fouling on superhydrophobic and slippery nonwetting copper surfaces

Bioinspired, superhydrophobic and slippery liquid infused surfaces that offer nonwetting characteristics have been explored in recent years for fouling mitigation. However, most of the studies are in the context of biofouling or under static immersion at ambient temperature conditions that are not reflective of the dynamic flow environment in practice. This article presents, for the first time, a systematic study of dynamic fouling of superhydrophobic (SHS) and slippery lubricant-infused surfaces (LIS) over a range of flow and temperature conditions. In this work, copper metallic surfaces were textured via electrodeposition or etching and further functionalized to achieve SHS and, additionally, infiltrated with a lubricant to fabricate LIS. The nonwetting surfaces were studied for their fouling behavior in a rotating Couette flow of a supersaturated calcium sulfate solution at different rotational speed and temperature. Fouling mineral mass accumulation on the different surfaces was measured as a function of time over a period of days using inductively coupled plasma mass spectroscopy and the fouled surfaces were investigated using scanning electron microscopy. Both SHS and LIS showed superior anti-scaling performance at all ranges of variables. An analytical Hill-Langmuir model is presented, for the first time, to describe the time evolution of scaling within 20% accuracy over the range of parameters studied. The study is the first to juxtapose two surface texturing methods, electrodeposition and etching, and two nonwetting surface types, SHS and LIS, subject to a common suite of experiments to elucidate fundamental understanding of mineral fouling on nonwetting surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Adversarial sampling of unknown and high-dimensional conditional distributions

Many engineering problems require the prediction of realization-to-realization variability or a refined description of modeled quantities. In that case, it is necessary to sample elements from unknown high-dimensional spaces with possibly millions of degrees of freedom. While there exist methods able to sample elements from probability density functions (PDF) with known shapes, several approximations need to be made when the distribution is unknown. In this paper the sampling method, as well as the inference of the underlying distribution, are both handled with a data-driven method known as generative adversarial networks (GAN), which trains two competing neural networks to produce a network that can effectively generate samples from the training set distribution. In practice, it is often necessary to draw samples from conditional distributions. When the conditional variables are continuous, only one (if any) data point corresponding to a particular value of a conditioning variable may be available, which is not sufficient to estimate the conditional distribution. This work handles this problem using an a priori estimation of the conditional moments of a PDF. Herein, two approaches, stochastic estimation, and an external neural network are compared for computing these moments; however, any preferred method can be used. The algorithm is demonstrated in the case of the deconvolution of a filtered turbulent flow field. It is shown that all the versions of the proposed algorithm effectively sample the target conditional distribution with minimal impact on the quality of the samples compared to state-of-the-art methods. Additionally, the procedure can be used as a metric for the diversity of samples generated by a conditional GAN (cGAN) conditioned with continuous variables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

The force explosion condition is consistent with spherically symmetric CCSN explosions

ABSTRACT One of the major challenges in core-collapse supernova (CCSN) theory is to predict which stars explode and which collapse to black holes. The analytic force explosion condition (FEC) shows promise in predicting which stars explode in that the FEC is consistent with CCSN simulations that use the light-bulb approximation for neutrino heating and cooling. In this follow-up manuscript, we take the next step and show that the FEC is consistent with the explosion condition when using actual neutrino transport in gr1d simulations. Since most 1D simulations do not explode, to facilitate this test, we enhance the heating efficiency within the gain region. To compare the analytic FEC and radiation-hydrodynamic simulations, this manuscript also presents a practical translation of the physical parameters. For example: we replace the neutrino power deposited in the gain region, Lντg, with the net neutrino heating in the gain region; rather than assuming that $\dot{M}$ is the same everywhere, we calculate $\dot{M}$ within the gain region; and we use the neutrino opacity at the gain radius. With small, yet practical modifications, we show that the FEC predicts the explosion conditions in spherically symmetric CCSN simulations that use neutrino transport.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance

Computationally predicting the performance of catalysts under reaction conditions is a challenging task due to the complexity of catalytic surfaces and their evolution in situ, different reaction paths, and the presence of solid-liquid interfaces in the case of electrochemistry. We demonstrate here how relatively simple machine learning models can be found that enable prediction of experimentally observed onset potentials. Inputs to our model are comprised of data from the oxygen reduction reaction on non-precious transition-metal antimony oxide nanoparticulate catalysts with a combination of experimental conditions and computationally affordable bulk atomic and electronic structural descriptors from density functional theory simulations. From human-interpretable genetic programming models, we identify key experimental descriptors and key supplemental bulk electronic and atomic structural descriptors that govern trends in onset potentials for these oxides and deduce how these descriptors should be tuned to increase onset potentials. Here, we finally validate these machine learning predictions by experimentally confirming that scandium as a dopant in nickel antimony oxide leads to a desired onset potential increase. Macroscopic experimental factors are found to be crucially important descriptors to be considered for models of catalytic performance, highlighting the important role machine learning can play here even in the presence of small datasets.

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

Unlocking the Path to Decarbonized Building Thermal Systems: Strategies for Designers and Contractors: Preprint

The design and construction community plays a pivotal role in facilitating the transition to decarbonized thermal systems that maintain human comfort while reducing building emissions. Through the U.S. Department of Energy Better Buildings initiative's Design and Construction Allies, a cohort of leading architecture, engineering, and construction firms have identified top ranked barriers that designers and contractors face when implementing solutions for building owners. These barriers to decarbonizing thermal - especially heating - systems include equipment availability; electrical capacity constraints; space allocations; complex system configurations; and lack of experience in designing, installing, and maintaining heat pumps. These impediments significantly amplify the risk and financial burden associated with the adoption of decarbonized solutions. The barriers also decrease the likelihood that designers, contractors, and owners will adopt decarbonization strategies without clear plans and guidance on how to implement these solutions, mitigate risk, and overcome the identified barriers. The National Renewable Energy Laboratory, the Design and Construction Allies, and the American Society of Heating, Refrigerating, and Air-Conditioning Engineers have developed "how to" thermal decarbonization guidance based on best practices. The subjects covered range from the role of energy efficiency in facilitating decarbonized heating solutions to strategies for decarbonizing new and existing heating, ventilating, and air-conditioning systems. The focus is on overcoming barriers so that energy-efficient, electrified buildings - both new and retrofit - become the industry standard. This paper outlines 1) the method used to collect and organize this guidance, 2) industry barriers to decarbonization, and 3) decarbonization techniques that have broad market applicability.

building heating↗