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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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1,709 records · Page 66

Nitrene generation and transfer for unnatural biosynthesis in living cells

Abstract Synthetic biology has enabled the production of natural and unnatural products from inexpensive sustainable feedstocks. Yet, the scope of available products has been limited largely to compounds accessible from nature’s chemical reactions. Evolved enzymes can catalyse reactions of unnatural substrates or reactions not found in nature but often require the addition of synthetic reagents to purified enzymes or to resting cells containing those enzymes. Here we show that chemical reactions of metabolic intermediates produced intracellularly in living cells can include intermolecular nitrene transfers. The biosynthesis of N -acetoxyanilines, in combination with the generation and transfer of N -aryl nitrene intermediates from them catalysed by a cytochrome P450, generates amino alcohols, diamines, diarylamines and aminoalkyl arenes from simple carbon feedstocks. These products—common substructures of pharmaceuticals and agrochemicals—are challenging to synthesize by standard organic chemistry and were produced from inexpensive, renewable feedstocks. Evolution of the enzymes in this pathway showed that titres can be increased by engineering and that the products can be synthesized with high enantioselectivity.

Donnell, Isaac

Precise Modeling of a Complex Solenoidal Magnetic Field Using a Combination of Analytic Functions and a PINN

We demonstrate an iterative approach to modeling a sparsely measured magnetic field in a large-bore solenoid. This approach uses a hybrid of traditional and machine learning techniques. The traditional technique is a linear least-squares fit using a series solution to Laplace's equation, while the machine learning technique involves the training of a physics-informed neural network (PINN) on the least-squares fit residuals. We use a newly defined activation function "DELTAsnake," a modification to the snake activation function proposed by Ziyin et al. that allows for stronger curvature and non-monotonicity. The combined model approximately obeys Maxwell's equations to a level sufficient for producing high quality physics simulations and analysis. Our approach is applied to a highly realistic calculation of the expected magnetic field in the Mu2e experiment's Detector Solenoid which includes a simple model for the expected statistical measurement uncertainties. Using ten toy measurement simulations, we demonstrate the capabilities of our model in comparison to the least-squares method alone; the least-squares method alone results in a reduced chi-squared statistic of ${2.15 \pm 0.01}$, while our approach improves the reduced chi-square to ${1.034 \pm 0.005}$. Furthermore, for an average toy simulation, we show that the range of the RMS of the three field component residuals reduces from ${0.07-0.37}$ Gauss to ${0.05-0.07}$ Gauss. We find that this novel method is robust against a realistic systematic uncertainty deriving from Hall probe calibration bias and can be used to significantly reduce the number of measurements required to achieve an accurate model.

Kampa, Cole [Caltech] (ORCID:0000000192972920)

Nuclear Structure and Decay Data for A=35 Isobars

Here, this work presents a comprehensive and critical evaluation of experimental nuclear spectroscopic data from reactions and decays for all 11 known nuclides with mass number 35 (Ne, Na, Mg, Al, Si, P, S, Cl, Ar, K, Ca). Recommended values are produced for level energies, spins and parities, half-lives, and radiation properties including energies, branching ratios, and multipolarities of γ rays, as well as characteristics of β radiation decays, based on a rigorous assessment of all available experimental data. Discrepancies among existing results are carefully addressed. This work supersedes earlier full evaluations of A=35 published by 2011Ch48, 1990En08 (also 1998En04 update) and 1978En02.

Sun, Lijie [Michigan State University, East Lansin

Exact block encoding of imaginary time evolution with universal quantum neural networks

We develop a constructive approach to generate quantum neural networks capable of representing the exact thermal states of all many-body qubit Hamiltonians. The Trotter expansion of the imaginary time propagator is implemented through an exact block encoding by means of a unitary, restricted Boltzmann machine architecture. Marginalization over the hidden-layer neurons (auxiliary qubits) creates the nonunitary action on the visible layer. Then, we introduce a unitary deep Boltzmann machine architecture in which the hidden-layer qubits are allowed to couple laterally to other hidden qubits. We prove that this wave-function is closed under the action of the imaginary time propagator and, more generally, can represent the action of a universal set of quantum gate operations. We provide analytic expressions for the coefficients for both architectures, thus enabling exact network representations of thermal states without stochastic optimization of the network parameters. In the limit of large imaginary time, the yields the ground state of the system. The number of qubits grows linearly with the number of interactions and total imaginary time for a fixed interaction order. Both networks can be readily implemented on quantum hardware via midcircuit measurements of auxiliary qubits. If only one auxiliary qubit is measured and reset, the circuit depth scales linearly with imaginary time and number of interactions, while the width is constant. Alternatively, one can employ a number of auxiliary qubits linearly proportional to the number of interactions, and circuit depth grows linearly with imaginary time only. Every midcircuit measurement has a postselection success probability, and the overall success probability is equal to the product of the probabilities of the midcircuit measurements.

97 MATHEMATICS AND COMPUTING

Active Fluids Form System-Spanning Filamentary Networks

Recent experimental realizations of liquid-liquid phase separation of active liquid crystals have offered an insight into the interaction between phase separation, ubiquitous in soft matter and biology, and chaotic active flows. Here, in this Letter, we use continuum theory to examine phase separation of an active liquid crystal and a passive fluid and report two new results. First, we provide an analytical derivation of the activity-induced suppression of the phase boundary of the coexistence region—a result first reported in simulations and experiments. We show that the shift in the critical point is a result of the balance between self-stirring active flows and phase-separating diffusive fluxes. Second, we show that this same balance is responsible for dramatically changing the morphology of the phase separated state, resulting in the emergence of a new mixed active phase consisting of a dynamical filamentous active network that invades the entire system area, trapping droplets of passive material. This structure exists even for very low volume fractions of active material. Our work provides an important step towards the goal of understanding how to use activity as a new handle for sculpting interfaces.

active nematics

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database

Development of large-scale, 3D Printed high temperature ceramic material

Through this collaborative effort, a new 3D printing platform for ceramics called laser-induced slip casting (LIS) was explored and developed for improving the processing and manufacture of silicon carbide (SiC), a high temperature ceramic material. This method prints layers of ceramic slips/slurries with subsequent selective-laser heating to dry each layer to build a 3D structure. The completed and dried part is then sintered. This manufacturing process is inherently lower cost than alternative ceramic printing methods such as binder jet technology or stereolithography when it comes to the feedstock material but is more expensive than robocasting or direct ink writing. However, it has the potential to make more controlled parts with less defects compared to robocasting. The largest cost is the heating source for the printer. With this technique, there is potential to make large ceramic parts in a near-net shape. Further, there is no known commercial manufacturing of 3D printed ceramics that creates a large range of different high-density ceramics at large scale. The goals and outcomes for the development of the new printing technology were: 1) assessing the technology with alumina by characterizing coupons, 2) printing and sintering of silicon carbide (SiC), and 3) characterization and properties testing of materials printed and a scale-up of SiC part(s). Through this collaborative project, it was sought to provide the best solution to achieving highly dense and near-net shaped ceramic parts at large scale and reduced cost. The goal was to produce high density sintered materials for applications in defense, energy generating systems, armor, and wear parts using 3D printing methods. Variables including powder particle sizes, dispersant molecular weights (MWs), binders, printing parameters, and post processing were explored as well as the characterization of the physical properties (add specifics here).

36 MATERIALS SCIENCE

Delamination recycling of multilayer plastic films: Solvent-assisted separation pathways and recovery of solid polyolefins

Multilayer plastic films are excellent packaging materials due to the bound layers of multiple polymers, with each different polymer contributing to the film properties. Desirable properties lead to continuously growing demand for multilayer films. Multilayer plastic films are typically single-use and, as such, their increased production and disposal have led to waste management problems. Multilayer films are not currently recyclable primarily due to the multiple bound polymers. This work advances delamination as a recycling process to separate and sequester valuable polymers from multilayer films, facilitating the incorporation of these polymers into the circular economy. We effect delamination in a physical process that preserves targeted polymers as solid film, hence retaining their embodied energy. This work documents three different pathways of inducing delamination of multilayer films, with appropriate solvents disrupting adhesion between adjacent layers or dissolving a minor component of the film in less than an hour and at temperatures below 90°C, and where all initial polyethylene is maintained in its solid form throughout the process and is recovered at high purity. Solvent-based delamination is exemplified on commercial multilayer films with majority polyethylene (PE), and polyethylene terephthalate (PET) or ethylene vinyl alcohol copolymer (EVOH) or nylon also present. Solvent-based delamination is an energy-efficient and environmentally friendly recycling process that improves upon dissolution-precipitation recycling, since delamination involves very little dissolution and no precipitation, and is superior to pyrolysis which breaks down the polymers, while delamination keeps polymer chains intact. Furthermore, delamination recycling can contribute to the sustainable use of multilayer films as they continue to protect our food and medicine.

Chemical Recycling

Overcoming the Entropy Penalty of Direct Air Capture for Efficient Gigatonne Removal of Carbon Dioxide

Atmospheric carbon poses an existential threat to civilization via global climate change. Hundreds of gigatonnes of carbon dioxide must be removed from earth’s atmosphere in the next three decades, necessitating a low-cost, energy-efficient process to extract low concentrations of carbon dioxide for conversion to a stable material permanently stored for thousands of years. In this work, the challenge of removing gigatonnes of CO 2 is described via the scale of effort and the thermodynamics of collecting and reducing this diffuse chemical, the accumulation of which imparts a substantial entropy penalty on any atmospheric carbon capture process. The methods of CO 2 reduction combined with upstream direct air capture (DAC) including absorption, membrane separation, and adsorption are compared with biomass torrefaction and permanent burial (BTB). A Monte Carlo model assesses the mass, energy, and economics of the full process of biomass torrefaction from biomass collection and transport to stable carbon burial to determine that 95% of scenarios could remove carbon for less than $200 per CO 2 -tonne-equivalent. Torrefied carbon is further discussed for its long-term stability and availability at the scale required to substantially mitigate the threat of climate change.

biomass

Polarized target nuclear magnetic resonance measurements with deep neural networks

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.

Metrology

Development of Novel Combustion Codes for Supercritical CO2 Combustion: Cooperative Research and Development Final Report, CRADA Number CRD-20-17182

The Allam-Fetvedt Cycle, a novel supercritical CO2 (sCO2) power cycle developed by 8 Rivers Capital, LLC, generates low-cost power from fossil fuels while capturing combustion-CO2. This cycle employs high-temperature oxy-combustion using sCO2 as the working fluid, leading to a challenging environment for materials. The most critical component for reliable deployment of this technology is the combustor-turbine interface. In the proposed partnership between NREL and 8 Rivers, we will develop a simulation-based tool to provide key design inputs for defining the materials and geometries required in this critical area.

09 BIOMASS FUELS

Strong Kitaev Interaction in BaCo 2⁢ (AsO 4 ) 2

The inelastic neutron scattering results and their analysis unequivocally point to a dominant Kitaev interaction in the honeycomb-lattice cobaltate BaCo 2 ⁢(AsO 4 ) 2 . Our anisotropic-exchange model closely describes all available neutron scattering data in the material’s field-polarized phase. Furthermore, the density-matrix renormalization group results for our model are in close accord with the unusual double-zigzag magnetic order and the low in-plane saturation field of BaCo 2 ⁢(AsO 4 ) 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Building Operation Model (Morpheus) for Dallas Fort Worth Airport (CRADA CRD-19-16301 Final Report)

The primary objective of this project was to leverage digital twin technology to enhance the design and operation of DFW Airport terminals and their associated energy systems. To achieve this, Morpheus, a building digital twin, was developed to guide improvements in airport operations, specifically targeting reductions in peak power demand and overall energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Atomistic Mechanisms of Stress-Dependent Molten Salt Corrosion in NiCr Alloys

Ni-based structural alloys in molten salt environments often experience simultaneous mechanical loading and corrosive attack, yet the mechanisms governing stress-corrosion interactions remain unclear. Prior studies largely emphasize tensile stress, while the role of compressive stress has received limited attention. Here, reactive molecular dynamics simulations are used to investigate the coupled effects of applied strain and corrosion in Ni 0.75 Cr 0.25 exposed to molten FLiNaK at 800 °C. A Σ5(210) grain boundary model is subjected to tensile (+4%) to compressive (−4%) uniaxial strains, and corrosion behavior is evaluated through fluorine adsorption, charge redistribution, and grain boundary evolution. Tensile strain accelerates intergranular corrosion susceptibility by reducing local atomic packing through elastic dilation and increasing excess free volume at the grain boundary, which enhances atomic mobility and salt infiltration. In contrast, compressive strain can suppress corrosion by promoting the formation of a ridge-like surface layer along the grain boundary, limiting salt access to the underlying alloy. These results provide atomistic insight into how stress states influence grain boundary corrosion in molten salts.

36 - MATERIALS SCIENCE

Robustness of pairwise kinematic Sunyaev–Zel’dovich effect to optical-cluster-selection bias

The pairwise kinematic Sunyaev–Zel’dovich (kSZ) effect measures both the pairwise motion between galaxy groups and clusters and the amount of gas within them, providing a tracer for cosmic growth. To interpret the cosmological information in the kSZ measurements, it is crucial to understand the optical-cluster-selection bias on the kSZ observables. Line-of-sight structures that contribute to both the optical observable (e.g., richness) and the cosmological signal can induce a correlation between these two quantities at a fixed cluster mass. The selection bias arising from this correlation is a key systematic effect for cosmological analyses. For cosmological observables such as cluster abundance and weak lensing, controlling this selection bias may help explain the tension between the DES-Y1 results and the Planck constraints. In order to test for a kSZ effect equivalent of such a bias, we adopted an alternative mock richness based on galaxy counts within cylindrical volumes along the line of sight. We applied the cylindrical count method to hydrodynamical simulations across a wide range of galaxy-selection criteria, assigning richness consistent with DES-Y1 to the mock clusters. When comparing optically selected clusters to mass-selected halos, we find no significant bias on pairwise kSZ signals, pairwise velocities, or optical depth within our uncertainty limits of approximately 16, 10, and 8%, respectively.

79 ASTRONOMY AND ASTROPHYSICS

High performance zinc anode for battery applications

An improved zinc anode for use in a high density rechargeable alkaline battery is disclosed. A process for making the zinc electrode comprises electrolytic loading of the zinc active material from a slightly acidic zinc nitrate solution into a substrate of nickel, copper or silver. The substrate comprises a sintered plaque having very fine pores, a high surface area, and 80-85 percent total initial porosity. The residual porosity after zinc loading is approximately 25-30%. The electrode of the present invention exhibits reduced zinc mobility, shape change and distortion, and demonstrates reduced dendrite buildup cycling of the battery. The disclosed battery is useful for applications requiring high energy density and multiple charge capability.

Casey, John E., Jr.

Qualification Progress and Mission-Enabling Capabilities of the 12-kW Hall-Effect, Advanced Electric Propulsion System (AEPS) Thruster

An update of the 12 kW Advanced Electric Propulsion System (AEPS) qualification and flight thruster status is provided. Three flight thrusters completed acceptance testing in 2025 and have been delivered to NASA. Environmental qualification is complete and preparations are under way for long-duration life-demonstration testing. Programmatic lessons learned associated with risk management, contract oversight, and requirement definition during the fabrication and assembly are discussed. In addition, the extensibility of the AEPS thruster to enable a variety of NASA missions is presented.

Electric Propulsion

Assessment of Molybdate Based Corrosion Inhibitor for use at the Savannah River Tank Farm Cooling Water System

The Savannah River Site (SRS) has relied on 51 underground storage tanks, many dating back to the 1950s, to store radioactive liquid waste generated from nuclear processing and radionuclide production. These tanks use carbon steel cooling coils, cooled by soft, acidic water, to dissipate the decayed heat produced by radioactive waste. For decades, following historical industry practices, chromate has been added to the cooling water (~450 ppm at pH 9-11) to effectively inhibit corrosion, ensuring cooling coil longevity. Inspections of failed coils reveal that chromate-treated surfaces are generally well-preserved.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W