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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 271 records · Page 15

Structure and Shape of Surface-Mediated Assembly of Surfactants

Achieving controls on the self-assembly of cationic and block copolymer micelles has significant implications for advancing novel material systems for energy, environmental, and biological applications and for tuning fluid flow behavior in subsurface geologic environments. While it is known that the aggregation of micelles is influenced by the composition of the surrounding fluid, the influence of a solid interface has been less explored. In this study, we probe the organization of cetyltrimethylammonium bromide (CTAB) micelles in the absence and presence of the Pluronic P123 block copolymer and quartz substrate using transmission and grazing-incidence small-angle X-ray scattering measurements and classical molecular dynamics (MD) simulations. In the absence of the quartz interface, CTAB with and without P123 molecules assemble as ellipsoid core–shell micelles. Densification of the core on adding P123 is noted from the decrease in the core radius from 15.9 to 14.6 Å. Here, the presence of a quartz substrate causes the micelles to elongate, which is noted by the emergence of a power-law slope in the low q region (<0.02 Å –1 ). Moreover, in the presence of both P123 and the quartz substrate, the micelle shape changes from ellipsoid core–shell to cylindrical core–shell, and a significantly higher number of aggregates are formed. The higher number of aggregates, and faster aggregation kinetics are linked to the organization of the solvent structures as noted from the MD simulations. These findings demonstrate the effects of adding a block copolymer and including a quartz substrate on the self-assembly of cationic (CTAB) micelles, which can be used to inform the design of functional material systems that harness surfactant chemistries.

42 ENGINEERING↗

Swing Contract-Based Valuation for Distributed Energy Resources in Transactive Energy Systems: A Reinforcement Learning Approach

With the proliferation of distributed energy resources (DERs) and power grids with high fractions of renewable energy, market constructs are evolving to allow DERs to participate in multiple possible markets, at different levels of grid hierarchy. The effective participation of DERs in market environments is aided by swing contract-based pricing mechanisms, whereby DERs have a two-part compensation structure – one for their reservation/commitment and another for performancedriven ex-post payment for their actual mobilization during dispatch. In this paper, we propose a reinforcement learningbased (Q-learning) approach that allows a rational DER agent to select the market it wants to participate in within a composite market environment where individual markets are coordinated by possibly different actors. The proposed Q-learning framework aids DERs in their self-valuation by implicitly maximizing their own payoff through market participation, assuming a swing contract-based compensation structure. We complement our work through simulation-based investigations where factors affecting the DER decision making process, such as parametric uncertainties in market (and grid) environments, are studied.

Naqvi, Syed Ahsan Raza↗

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

A Catalyst-Like System Enables Efficient Perovskite Solar Cells

High-quality perovskite films are essential for achieving high performance of optoelectronic devices; However, solution-processed perovskite films are known to suffer from compositional and structural inhomogeneity due to lack of systematic control over the kinetics during the formation. Here, in this work, the microscopic homogeneity of perovskite films is successfully enhanced by modulating the conversion reaction kinetics using a catalyst-like system generated by a foaming agent. The chemical and structural evolution during this catalytic conversion is revealed by a multimodal synchrotron toolkit with spatial resolutions spanning many length scales. Combining these insights with computational investigations, a cyclic conversion pathway model is developed that yields exceptional perovskite homogeneity due to enhanced conversion, having a power conversion efficiency of 24.51% for photovoltaic devices. This work establishes a systematic link between processing of precursor and homogeneity of the perovskite films.

14 SOLAR ENERGY↗

Toward High Efficiency Water Processed Organic Photovoltaics: Controlling the Nanoparticle Morphology with Surface Energies

Here efficient organic photovoltaic devices fabricated from water-based colloidal dispersions with donor:acceptor composite nanoparticles achieving up to 9.98% power conversion efficiency (PCE) are reported. This high efficiency for water processed organic solar cells is attributed to morphology control by surface energy matching between the donor and the acceptor materials. Indeed, due to a low interfacial energy between donor and the acceptor, no large phase separation occurs during the nanoparticle formation process as well as upon thermal annealing. Indeed, synchrotron-based scanning transmission X-ray microscopy reveals that the internal morphology of composite nanoparticles is intermixed as well as the active layer morphology after thermal treatment. The PCE of this system reaches 85% that of devices prepared from chlorinated solvent. The gap between water-based inks and organic solvent-based inks gets narrower, which is promising for the development of eco-friendly processing and fabrication of organic photovoltaics.

14 SOLAR ENERGY↗

A-Cation-Dependent Structure–Optical Property Relationships of Halide Perovskite Heterostructures with Complex Interfaces

Halide perovskite heterostructures offer promising interfacial interactions for energy conversion, yet challenges in synthesizing structurally well-defined systems limit detailed investigations into structure–property relationships. In this article, we report the synthesis of compositionally controlled 3D/3D and 3D/2D halide perovskite heterostructures using evaporation crystallization-polymer pen lithography (EC-PPL) and a single-particle analysis of their properties. By systematically varying A-site cation combinations and crystal dimensions, we show that heterointerfaces induce local lattice distortions that modulate vibrational dynamics and electron-phonon coupling. These interfacial effects result in significantly extended carrier lifetimes compared to compositionally similar pure phases. Raman spectroscopy, temperature-dependent photoluminescence, and power-dependent emission analysis reveal that localized structural modulations at the interface govern exciton-phonon interactions. These effects are magnified in smaller crystals due to increased interfacial contributions. Our findings highlight the critical role of interface-driven lattice control in tuning the optoelectronic properties of halide perovskites and provide design principles for engineering heterostructures in next-generation optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of a Molten Salt Flow Cell for Combined Absorbance and Laser-Induced Breakdown Spectroscopy for Online Measurements

A novel flow cell allowing for multiple optical spectroscopy measurements on flowing molten salts was designed, and demonstrative calibrations of impurities in aqueous samples were performed. Online compositional measurements of molten salts are of high interest to monitor the state of relevant solar and nuclear systems. Here, the Spectroscopic Configuration for Optical Real-Time Characterization of High-Temperature (SCORCH) fluids cell was designed to meet this need by providing optical access to a high-temperature molten salt sample stream without physical contact between the sample and window materials. Laser-induced breakdown spectroscopy (LIBS) was utilized to quantify Li, Cr, Fe, Ni, Sr, and Pr at concentrations ranging nominally from 0 to 315 mmol L −1 . Laser power, frequency, and plasma position were optimized to mitigate challenges associated with sample splashing. Univariate calibration models were built with R 2 > 0.98, percent root mean square error of cross-validation (%RMSECV) as low as 2.7%, and limits of quantification (LOQs) down to 4.1 mmol L −1 . Simultaneously, absorbance calibrations were developed for the applicable analytes (Cr, Ni, and Pr) using Beer’s law with a pathlength of 4.41 ± 0.10 mm. These models provide excellent quantification performance with R 2 > 0.999, %RMSECV as low as 0.6%, and LODs down to 0.08 mmol L −1 . Although these calibrations were performed for each spectroscopic technique separately, the two methods may be combined in the future through multivariate modeling and sensor fusion to provide more robust models with the benefits of both techniques (e.g., absorbance: oxidation state concentrations, LIBS: elemental concentration). Additionally, optimized spectrometers may be deployed to enhance sensitivity.

absorbance spectroscopy↗

Phase Diagrams of Alloys and Their Hydrides via On-Lattice Graph Neural Networks and Limited Training Data

Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology applications. To alleviate the prohibitive computational expense of high-throughput configurational sampling with density functional theory (DFT), surrogate modeling strategies like cluster expansion are many orders of magnitude more efficient but can be difficult to construct in systems with high compositional complexity. We therefore employ minimal-complexity graph neural network models that accurately predict and can even extrapolate to out-of-train distribution formation energies of DFT-relaxed structures from an ideal (unrelaxed) crystallographic representation. This enables the large-scale sampling necessary for various thermodynamic property predictions that may otherwise be intractable and can be achieved with small training data sets. Two exemplars, optimizing the thermodynamic stability of low-density high-entropy alloys and modulating the plateau pressure of hydrogen in metal alloys, demonstrate the power of this approach, which can be extended to a variety of materials discovery and modeling problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated Fuel Qualification of Fast Modular Reactor Fuel in a Thermal Reactor: Modeling and Simulation Paired with Irradiation Testing

The accelerated fuel qualification (AFQ) methodology is applied by simulating accelerated fuel tests of the General Atomics Electromagnetic Systems’ fuel system for its 44-MW(electric) gas-cooled, fast-spectrum fast modular reactor (FMR). This fuel is comprised of UO 2 pellets in SiGA® cladding, a silicon carbide ceramic matrix composite. Fast reactors, like the FMR, offer many benefits, including high fuel utilization and flexibility, but may require a lengthy material design process if tests are performed using fast neutron irradiation alone. A thermal neutron irradiation can instead be used to rapidly test how well key components of the current material models extend to high burnup. Thermal neutrons produce a different radial power distribution within the pin than fast neutrons. However, the temperature and burnup values for the two neutron types are comparable, and the differences between the simulated fuel responses are relatively small, demonstrating the weak sensitivity of the physics-based fuel model calculations on the neutron type and the irradiation rate. Furthermore, the deformation of the SiGA cladding saturates after about 1 displacement per atom for both neutron spectra. In an accelerated fuel test, the irradiation time required to reach the target fuel burnup can be reduced by a factor of 3 by using a small rodlet with a 45% smaller pellet diameter while maintaining the same linear power. Therefore, the time for data collection up to high burnup can be significantly reduced while maintaining the same temperature profile, which largely determines the material response. Tests of fuel rodlets of standard and compact size will be carried out in the Idaho National Laboratory’s Advanced Test Reactor (ATR), including full size and compact rodlets with varying gap sizes. By applying physics-based mechanistic modeling and simulation in accordance with the AFQ methodology, this type of compact rodlet testing in a thermal test reactor captures the necessary phenomena to test fuel material models up to high burnup and to simulate the expected impact of fast neutron radiation on the fuel in FMR operations. Finally, this approach to testing fast reactor fuels in existing thermal test reactors, paired with advanced physics-based mechanistic modeling and simulation, is expected to be applicable to a range of advanced fuels and will decrease the overall fuel qualification timeframe from decades to years.

Advanced test reactor (ATR)↗

Scalable Distributed Reachability Analysis for Cyber-Physical Networked Microgrids with Communication Latency

Due to the high penetration of power-electronic-interfaced distributed energy resources (DERs), a microgrid's inertia is significantly reduced, making it sensitive to cyberand physical operational changes. When multiple microgrids are interconnected to form networked microgrids for improving system's resilience, the changes of one microgrid can quickly escalate to the overall system. In cyber-physical networked microgrids, the communication latency varies a lot. To efficiently quantify the impact of the communication latency on the dynamics of networked microgrids, a scalable distributed reachability analysis approach is presented in this paper. Reachable sets are calculated for each microgrid and then composited for the overall system dynamics evaluation. Extensive tests in the full paper will demonstrate the influence of communication latency on system dynamics and validate reachable sets can bound a system's all dynamic trajectories subject to latency changes. The test results also offer an insight into designing and managing the communication network for enhancing the system's resilience.

Li, Yan↗

Spin phase diagram of the interacting quantum Hall liquid

Measurement of the ground-state spin polarization of quantum systems offers great potential for the discovery and characterization of correlated electronic states. However, spin polarization measurements have mainly involved optical and NMR techniques that perturb the delicate ground states and, for quantum Hall systems, have provided conflicting results. In this work we present spin-resolved pulsed tunnelling (SRPT) that precisely determines the phase diagram of the ground-state spin polarization as a function of magnetic field and Landau level (LL) filling factor ($ν$) with negligible perturbation to the system. Our phase diagram shows a variety of polarized, unpolarized and topological spin states in the lowest (N = 0) LL, which can largely be described by a weakly interacting composite fermion (CF) model7. However, the phase diagram shows unexpected behaviour in the N = 1 LL. We observe fully polarized $ν$ = 5/2 and 8/3 states but a partially depolarized $ν$ = 7/3 state. This behaviour deviates from the conventional theoretical picture of weakly interacting fractional quasiparticles, but instead suggests unusual electronic correlations and the possibility of new non-Abelian phases. The results establish SRPT as a powerful technique for investigating correlated electron phenomena.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Joining Study for Formed Plate Heat Exchangers (CRADA Final Report)

Plate heat exchangers (PHEs) have been used in numerous industrial applications, such as HVAC systems, power generation, transportation and manufacturing. The performance of plate heat exchangers is frequently undermined by corrosion, fouling, and scaling. These phenomena not only diminish heat transfer efficiency but also lead to increased operational costs, maintenance demands, and reduced equipment lifespan. In this project, the team addressed the widespread challenges of corrosion, fouling, and scaling, and explored alternative material solutions. While commonly used materials like stainless steel and titanium offer notable benefits, they can still experience corrosion under certain operating conditions. The advancement of new materials and surface engineering technologies, such as advanced coating, ceramics, composites materials, and high entropy alloys are promising for can help solve these issues, enable longer lifetime and high performance of plate heat exchangers.

99 GENERAL AND MISCELLANEOUS↗

Joining Study for Formed Plate Heat Exchangers (Final Report)

Plate heat exchangers (PHEs) have been used in numerous industrial applications, such as HVAC systems, power generation, transportation and manufacturing. The performance of plate heat exchangers is frequently undermined by corrosion, fouling, and scaling. These phenomena not only diminish heat transfer efficiency but also lead to increased operational costs, maintenance demands, and reduced equipment lifespan. In this project, the team addressed the widespread challenges of corrosion, fouling, and scaling, and explored alternative material solutions. While commonly used materials like stainless steel and titanium offer notable benefits, they can still experience corrosion under certain operating conditions. The advancement of new materials and surface engineering technologies, such as advanced coating, ceramics, composites materials, and high entropy alloys are promising for can help solve these issues, enable longer lifetime and high performance of plate heat exchangers.

36 MATERIALS SCIENCE↗

Secure and Resilient Operations Using Open-Source Distributed Systems Platform (OpenDSP)

The goal of this project is to identify and address cybersecurity gaps by developing a multi-layer multi-channel cyber-physical defense and survival mechanism for operating distribution networks with high penetration of solar / inverter-based resource (IBR) / distributed energy resource (DER). The proposed security enhancements are built upon the distributed framework and solution architecture for both information technology (IT) and operational technology (OT) systems. The technical solutions consist of two composite functionalities and six layers: proactive defense (vulnerability assessment, communication protection, and attack detection, as layers 1-3), and adaptive self-healing (attack-resilient control, adaptive recovery, and resilient survival, as layers 4-6). These layers, built on and extended from DHS CISA Cyber Framework, establish an integrated and robust cybersecurity framework for operating large-scale distribution networks.

14 SOLAR ENERGY↗

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data. This is revision 1 of the 2024 study (published December 17, 2024 and updated on January 24, 2025) and corrects a modeling error in natural gas composition. See the errata on page 2 for more information.

03 NATURAL GAS↗

A dimensionless number for high-throughput design of multi-principal element alloys in directed energy deposition

The present study demonstrates the development of a dimensionless number to predict the build height in the additive manufacturing technique of directed energy deposition (DED). The build height can also be used to estimate the dendrite arm spacing and, thus, the cooling rate in the fabrication of samples. A baseline sample, 316L stainless steel, was used to fit the build height to the dimensionless number. A range of process parameters, including laser power, laser feed rate, powder flow rate, layer thickness, and hatch spacing, were varied. Based upon dendrite arm spacing, the estimated cooling rate varied between 102 and 104 K/s. Using the fitted relationship for the stainless steel, high-throughput (HT) processing of multi-principal element alloys (MPEAs) was performed. For this study, HT is the ability to fabricate a batch of 25 bulk samples (∼1 cm3) with different compositions within a 5-h period with ±10 at. % accuracy. A range of compositions using in situ alloying of elemental powders in the Fe–Ni–Cr–Mo system were made. The MPEAs' build height followed the same relationship to the dimensionless number as the 316L alloy. The dimensionless number predicts both macro and meso-scale features in HT processing, thus offering a design tool for choosing process parameters in DED additive manufacturing. Also, the ability to control or increase cooling rates can enhance the ability to promote metastability as well as control meso-scale chemical distributions of alloy samples.

Islam, Zahabul (ORCID:0000000169613209)↗

Evaluation of Additively Manufactured Monolithic SiC and SiC Ceramic Matrix Composites for Concentrating Solar Receiver Applications

Supported by an award from the Solar Technology Office, US Department of Energy, GE Aerospace Research in collaboration with Heliogen Holdings Inc, is engaged in the development of ultra-High Operating Temperature SiC-matrix Solar Thermal Air Receiver (HOTSSTAR). We report the results of our study of the effective heat transfer characteristic of several candidate structure motifs, or feature geometries, made of SiC via additive manufacturing in a simulative laboratory test. The SiC structure motifs studied include different permutations of three-dimensional periodic lattices and defined shapes. The solar-thermal simulating laboratory test setup is constructed using a 4kW CO2 laser system with beam shaping optics to apply radiative heating power on one face of 2”-diameter cylindrical feature specimens representing the structure motifs of interest for receiver element design. Using the test setup, simulative test conditions representative of a concentrated solar flux of up to ~2000 suns could be achieved in the lab tests under varying air flow through the test structure. A numerical analysis scheme is developed to extract an effective or compound heat transfer coefficient representative of the test structure under steady-state heat flow conditions.

14 SOLAR ENERGY↗

Crack fault diagnosis of rotating machine in nuclear power plant based on ensemble learning

Crack faults in rotating machines can cause machine shutdown or scrapping, endangering the normal operation and safety of nuclear power plants. Intelligent diagnostic techniques based on machine learning have the potential to diagnose crack faults. However, problems such as scarcity of field fault data and high noise of plant measurements pose challenges to the application of machine learning. Here this study proposes an ensemble learning approach to mitigate the negative impacts of the problems. Ensemble learning is a strategy for combining multiple machine learning models into a composite model. The basic idea of ensemble learning is that even if one model makes a mistake, other models can correct it. Case studies based on bearing and gear system fault experiments show that the proposed ensemble learning models have better diagnostic results than the single model in the presence of noise and small data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗