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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 OSTI2026

A Physical Model Enhanced Data Driven Method for High-Resolution Residential Load Profile Generation

Residential buildings account for significant energy consumption, creating opportunities to offer grid services. As electric utilities seek to implement effective system operation strategies, understanding residential energy consumption patterns becomes essential; However, the time intervals of load profiles measured by utilities' smart meters are typically from 15 minutes to 60 minutes. The low-resolution data make it hard to extract appliance-level load information, which is critical for providing grid services. This paper presents a load profile generator designed to produce synthetic load profiles for residential buildings that emphasizes the importance of accurate representations of realistic energy consumption patterns. The generator takes realistic low-resolution residential load measurements and weather data as inputs, producing 1-minute interval profiles that match the characteristics of the original profiles. Further, this generator can be used to populate load profiles in areas where actual measurements are limited to improve the ability of utilities to analyze their distribution systems. By providing more high-resolution residential building load profiles, this tool supports electric utilities to enhance their residential building load control strategies and improve overall grid stability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Steam Generators: Thermal Hydraulic Measurements and Instrumentation

Steam generators are integral components of both conventional and advanced reactors utilizing steam power cycles, as they influence the power conversion performance. Steam generator designs are highly influenced by the type of reactor coolant used, which mainly governs the different control, monitoring, and safety system actuation requirements. Therefore, the present work reviews the thermal hydraulics instrumentation within steam generators designed for pressurized water reactors (PWRs), high-temperature gas-cooled reactors (HTGRs), sodium fast reactors (SFRs), and molten salt cooled reactors (MSRs). Emphasis is given to measurement techniques that are either unique or particularly important to specific reactor types. Lastly, a discussion is provided on the instrumentation and measured parameters. The work identifies standard parameters of interest and is expected to aid the development of test beds and novel measurements techniques.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Maximizing the Benefits of On-Site Renewable Energy Generation Using On-Site Energy Storage

The commercial and industrial building sectors have a major role to play in a U.S. low-carbon future. Building owners can make a difference by deploying on-site renewable generation and storage technologies, which facilitates future-proofing their buildings as well as more effectively meeting the service requirements of the building. This resource provides an overview of common generation, storage, and load management technologies in behind-the-meter systems, and serves as a primer to demonstrate the impact on net building loads required from the grid for different sizes of renewable generation along with on-site electrical and thermal storage. These discussions can help commercial building owners communicate the value of these systems to project teams and develop innovative behind-the-meter solutions to achieve their energy goals.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2026

Generative AI in Supply Chain Management: Applications, Challenges, and Future Directions

Supply chain management (SCM) is undergoing rapid transformation due to increasing global complexity, demand volatility, and operational disruptions. Generative Artificial Intelligence (GenAI) has emerged as a powerful paradigm capable of synthesizing data, simulating operational scenarios, and enabling adaptive decision-making across supply chain networks. This paper presents a survey of GenAI’s role in SCM, focusing on its applications in predictive analytics, autonomous logistics, and fraud detection. Unlike traditional AI systems that rely primarily on predictive analytics, GenAI models, including large language models, generative adversarial networks, and diffusion-based architectures, enable the creation of synthetic supply chain scenarios and autonomous optimization strategies. This survey provides (1) a taxonomy of GenAI techniques for supply chain applications, (2) a comparative analysis of generative AI approaches with traditional machine learning, reinforcement learning, and blockchain-based methods, and (3) a discussion of key challenges such as data privacy, interpretability, and integration with legacy enterprise systems. Furthermore, we outline open research problems and propose directions for future research toward autonomous, resilient, and sustainable AI-driven supply chains.

15 - GEOTHERMAL ENERGY↗
DOE OSTI2024

Apollo Next Generation Sample Analysis (ANGSA): an Apollo Participating Scientist Program to Prepare the Lunar Sample Community for Artemis

As a first step in preparing for the return of samples from the Moon by the Artemis Program, NASA initiated the Apollo Next Generation Sample Analysis Program (ANGSA). ANGSA was designed to function as a low-cost sample return mission and involved the curation and analysis of samples previously returned by the Apollo 17 mission that remained unopened or stored under unique conditions for 50 years. These samples include the lower portion of a double drive tube previously sealed on the lunar surface, the upper portion of that drive tube that had remained unopened, and a variety of Apollo 17 samples that had remained stored at -27 °C for approximately 50 years. ANGSA constitutes the first preliminary examination phase of a lunar “sample return mission” in over 50 years. It also mimics that same phase of an Artemis surface exploration mission, its design included placing samples within the context of local and regional geology through new orbital observations collected since Apollo and additional new “boots-on-the-ground” observations, data synthesis, and interpretations provided by Apollo 17 astronaut Harrison Schmitt. ANGSA used new curation techniques to prepare, document, and allocate these new lunar samples, developed new tools to open and extract gases from their containers, and applied new analytical instrumentation previously unavailable during the Apollo Program to reveal new information about these samples. Most of the 90 scientists, engineers, and curators involved in this mission were not alive during the Apollo Program, and it had been 30 years since the last Apollo core sample was processed in the Apollo curation facility at NASA JSC. There are many firsts associated with ANGSA that have direct relevance to Artemis. ANGSA is the first to open a core sample previously sealed on the surface of the Moon, the first to extract and analyze lunar gases collected in situ, the first to examine a core that penetrated a lunar landslide deposit, and the first to process pristine Apollo samples in a glovebox at -20 °C. All the ANGSA activities have helped to prepare the Artemis generation for what is to come. The timing of this program, the composition of the team, and the preservation of unopened Apollo samples facilitated this generational handoff from Apollo to Artemis that sets up Artemis and the lunar sample science community for additional successes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Rapid particle generation from an STL file and related issues in the application of material point methods to complex objects

Abstract In this paper, we focus on three issues related to applications of material point methods (MPMs) to objects with complex geometries. They are material point generation, compatibility of material points with a mesh, and sensitivity to mesh orientation. An efficient method of generating material points from a stereolithography (STL) file is introduced. This material point generation method is independent of the mesh used in MPM calculations. The compatibility between the material points and the mesh is then studied. We also show that the original MPM and the dual domain material point (DDMP) method are sensitive to mesh orientation. These issues are related to the calculation of the internal force and are concerns of the MPMs. They become more prominent when MPMs are applied to complex geometries. Our numerical results show that the recently developed local stress difference (LSD) algorithm (Perez et al. in J Comp Phys 498:112681, 2024) can be used to effectively address them.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Improved titanium-44 purification process for establishing a high apparent molar activity titanium-44/scandium-44 generator

44 Sc-radiopharmaceuticals are gaining more interest but still lack availability. The proof of principle of a 44 Ti/ 44 Sc generator, which can produce 44 Sc daily, has been established but with some limitations and drawbacks. Despite recent advances, separation of 44 Ti from massive quantities of scandium target material is still cumbersome. Here, in this work, the improved radiochemical separation of 44 Ti from residual scandium target material was carried out by precipitation of Sc with fluoride ions. Furthermore, two approaches were used to set up a high apparent molar activity small-scale generator. The first method relied on extraction chromatography for fine purification using a DGA resin, followed by loading of the purified 44 Ti onto a ZR resin column. In the second method, 44 Ti was loaded on the ZR resin directly after the precipitation step. This second method was used to set up a generator of 370 kBq and evaluate by radiolabeling. An apparent molar activity of 2 MBq/nmol was obtained for the radiolabeling with DOTA, the most common and suitable chelate for scandium. This result is comparable with previously published data on 44m/44 Sc.

44Sc↗
DOE OSTI2025

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP↗
DOE OSTI2025

Automated model generation and parameter estimation of building energy models using an ontology-based framework

This study presents a methodology for automated model generation and parameter estimation of building energy models using semantic modeling and Bayesian estimation. Semantic modeling techniques are used to represent the system components and their interactions, facilitating the automatic generation of a simulation model from dynamic component models. The proposed approach is applied to a case study of a ventilation system where a simulation model is generated, calibrated, and assessed through different performance metrics. These metrics demonstrate the accuracy and reliability of both model point estimates and probabilistic prediction intervals across all model outputs. Overall, the proposed methodology offers a systematic and automated approach to model development and calibration in building energy systems, with potential applications in building performance analysis, monitoring, and optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Superior electrochemical performance and reduced heat generation in 3D printed vs. 2D tape-casted NMC622 electrodes

This study compares the charge storage mechanisms, thermodynamics behavior, ion transport, and heat generation in NMC622 electrodes fabricated using a novel 3D printing process and the conventional 2D tape casting process. First, potentiometric entropy measurements revealed that the charge storage mechanisms for both types of electrodes consisted of lithium deintercalation in a homogeneous solid solution of NMC622 followed by a transition from a hexagonal (H1) phase to another hexagonal (H2) phase through a monoclinic (M) phase. Both types of electrodes had similar thermodynamics behavior with overlapping entropic potential profiles. Furthermore, operando isothermal calorimetry at high C-rates indicated that the 3D printed electrodes featured larger specific capacity and better rate performance than the 2D tape-casted electrodes. The better performance of 3D printed electrodes was attributed to their larger electrode/electrolyte interfacial surface area and electrical conductivity as well as their faster lithium ion transport. As a result, the instantaneous heat generation rates were smaller in 3D printed electrodes than in 2D tape-casted electrodes, thus resulting in lower overall specific electrical energy and thermal energy dissipation per unit charge stored. Overall, additive manufacturing techniques offer great potential in producing electrodes with superior electrochemical performance and reduced heat generation for fast charging batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Generating synthetic signaling networks for in silico modeling studies

Predictive models of signaling pathways have proven to be difficult to develop. Reasons include the uncertainty in the number of species, the complexity in species’ interactions, and the sparseness and uncertainty in experimental data. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. For example, uncertainty and sparseness of the data often result in overfitted models that have little predictive value beyond recapitulating the experimental data itself. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. However, to determine the effectiveness of any new algorithm, a baseline model is needed to test its performance. To meet this need, we developed a method for generating artificial synthetic networks that are reasonably realistic and thus can be treated as ground truth models. These synthetic models can then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. Here, we describe a simple approach for generating synthetic signaling networks that can be used for this purpose.

42 ENGINEERING↗
DOE OSTI2024

On forced RF generation of CW magnetrons for accelerators

CW magnetrons, initially developed for industrial RF heaters, were suggested to power RF cavities of superconducting accelerators due to their higher efficiency and lower cost than traditionally used klystrons, IOTs or solid-state amplifiers. RF amplifiers driven by a master oscillator serve as coherent RF sources. CW magnetrons are regenerative RF generators with a huge regenerative gain. This causes regenerative instability with a quite large noise when a magnetron operates with the anode voltage above the threshold of self-excitation. Traditionally, an injection locking by a small signal is used for stabilization of magnetrons. In this case CW magnetrons with the injection-locked oscillations generate a high level of noise. This may preclude use of standard CW magnetrons in this operating mode in the Superconducting RF (SRF) accelerators. In this article we described a method developed for forced RF generation of CW magnetrons when the magnetron startup is provided by the injected forcing signal and the regenerative noise is suppressed. The method is most suitable for powering high Q-factor cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information

A Dynamic Bayesian network (DBN) model for solar power generation forecasting in solar plants is proposed in this paper. The key idea is to fuse sensor data, operational indicators, meteorological data, lagged output power information, and model errors for more accurate short-term (e.g., hours) and mid-term (e.g., days to weeks) power generation forecasting. The proposed DBN augments automated data-driven structure learning with expert knowledge encoding using continuous and categorical data given constraints to represent causal relationships within a solar inverter system. Additionally, an error compensation mechanism is proposed to capture temporal fluctuation. The effectiveness of the DBN on solar power generation forecasting was evaluated by rolling window analysis with one-year testing data collected from a local solar plant. The proposed DBN is compared with four state-of-art methods including support-vector regression (SVR), k-nearest neighbors (kNN), artificial neural network (ANN), and long short-term memory (LSTM) models. The result show that the proposed DBN achieves better accuracy in general, and it is not as data-hungry as some neural network-based models. The proposed DBN is also shown to have robust and consistent forecasting power with different forecasting horizons. The accuracy is 92% - 95% from one hour to one week ahead forecasting.

14 SOLAR ENERGY↗
DOE OSTI2025

A theoretical study of the upper bound of surface elevation variance in the Phillips initial stage during wind-wave generation

The resonance mechanism in the initial of wind-wave generation proposed by Phillips is a foundation of wind-wave generation theory, but a precise theoretical quantification of wave energy growth in this initial stage has not been obtained yet after more than six decades of research. In this study, we aim to address this knowledge gap by developing an analytical approach based on a novel complex analysis method to theoretically investigate the temporal evolution of the wave energy in the Phillips initial stage. We quantitatively derive and analyse the growth behaviour of the surface wave energy and obtain an analytical solution for its upper bound. Our result highlights the crucial effects of surface tension. Because the phase velocity of gravity–capillary waves has a minimal value at a critical wavenumber, gravity–capillary waves and gravity waves (which neglect surface tension) exhibit distinct resonance curve properties and wave energy growth behaviours. For gravity waves, the resonance curve extends indefinitely; for gravity–capillary waves, it either forms a finite-length curve or does not exist, depending on the wind speed. The leading-order term of the upper-bound solution of the energy of gravity waves increases linearly over time, while for gravity–capillary waves, the term increases linearly over time under strong wind conditions but remains finite under weak wind conditions. This theoretical study provides an analytical framework for the generation of wind-waves in the Phillips initial stage, which may inspire further theoretical, numerical and experimental research.

58 GEOSCIENCES↗
DOE OSTI2025

Automatic Generation of Chemical Mechanisms for Electrochemical Systems: Solid Electrolyte Interphase Formation in Lithium Batteries

Electrolytes in many lithium ion batteries decompose at the low potentials near the anode. The decomposition products form a layer termed the solid electrolyte interphase (SEI). The composition and growth of the SEI layer significantly affect both the capacity fade and safety of lithium ion batteries. However, SEI formation and growth kinetics are not well understood. In this work, we present an extension of the Reaction Mechanism Generator (RMG) software to automatically generate mechanisms for SEI formation. We extend RMG’s solvation correction framework to account for kinetic solvent effects and demonstrate the accuracy of our technique. We calculate thermochemical parameters for 252 species and rate coefficients for 69 reactions, most with associated solvation corrections. This and additional quantum chemistry data are used to extend RMG’s thermodynamic group additivity and solute parameter estimation schemes to handle lithiated species and add 14 new reaction families to RMG. RMG is additionally extended to simulate electrocatalytic systems. Lastly, we demonstrate RMG on the decomposition of acetonitrile and ethylene carbonate near a battery anode. Furthermore, while this framework does not yet resolve individual ions, as appropriate thermochemistry estimators are not available, and thus, cannot yet resolve more complex electrochemical pathways, RMG is able to generate reasonable pathways for SEI formation that match literature pathways and products. In particular, RMG identifies a new important reaction pathway that is not present in literature.

Chemical reactions↗
DOE OSTI2025

Chemically Generated Liquid Sulfur Droplets at Room and Subzero Temperatures

The liquid phase of sulfur has been observed at room temperature, resulting from the electrochemical oxidation of polysulfides, a process occurring on the electrodes and influenced by the electrode materials. However, such electrode-dependent behavior of liquid sulfur has constrained its use in battery applications, driving research for alternative processes. This paper introduces an approach to generating liquid sulfur at both room and subzero temperatures through chemical reactions independent of the substrate material. We demonstrate that using a redox mediator, polysulfides can be chemically oxidized into liquid sulfur droplets in the electrolyte close to but away from the electrode. This pathway can generate liquid sulfur at room and subzero temperatures of −15 °C, 130 °C below sulfur’s melting temperature (115 °C). The chemically generated liquid sulfur further enriches the lithium–sulfur-electrolyte material systems, potentially creating opportunities for high-energy lithium–sulfur and other metal–sulfur batteries.

liquid sulfur↗
DOE OSTI2024

The interplay of DNA repair context with target sequence predictably biases Cas9-generated mutations

Abstract Repair of double-stranded breaks generated by CRISPR/Cas9 is highly dependent on the flanking DNA sequence. To learn about interactions between DNA repair and target sequence, we measure frequencies of over 236,000 distinct Cas9-generated mutational outcomes at over 2800 synthetic target sequences in 18 DNA repair deficient mouse embryonic stem cells lines. We classify the outcomes in an unbiased way, finding a specialised role forPrkdc(DNA-PKcs protein) andPolmin creating 1 bp insertions matching the nucleotide on the protospacer-adjacent motif side of the break, a variable involvement ofNbnandPolqin the creation of different deletion outcomes, and uni-directional deletions dependent on both end-protection and end-resection. Using our dataset, we build predictive models of the mutagenic outcomes of Cas9 scission that outperform the current standards. This work improves our understanding of DNA repair gene function, and provides avenues for more precise modulation of Cas9-generated mutations.

Science & Technology - Other Topics↗
DOE OSTI2026

Milliwatt-level UV generation using sidewall poled lithium niobate

Integrated coherent sources of ultra-violet (UV) light are essential for a wide range of applications, from ion-based quantum computing and optical clocks to gas sensing and microscopy. Recently, approaches that use frequency upconversion have received considerable attention. Among these, the integrated thin-film lithium niobate (TFLN) photonic platform shows particular promise. However, to date, the high propagation losses and lack of reliable techniques for consistent poling of cm-long waveguides with small poling periods have impeded progress. Here, we present a sidewall poled lithium niobate (SPLN) waveguide approach that overcomes these obstacles and results in a two-orders-of-magnitude increase in generated UV power. We demonstrate SPLN waveguides featuring record-low propagation losses of 2.3 dB/cm, complete domain inversion across the waveguide cross-section, and an optimum 50% duty cycle, resulting in a record-high normalized conversion efficiency of 5050%W$^{−1}$cm$^{−2}$, and 4.2 mW of generated on-chip power at 390 nm wavelength. This advancement makes the TFLN platform a viable option for high-quality on-chip UV generation, benefiting emerging applications.

Franken, C. A.A. [Harvard U.; Twente U., Enschede]↗