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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 487 records · Page 27

X-ray Multilayers for Next-Generation Astrophysics Missions

In this work, we proposed to demonstrate the feasibility of high-reflectivity multilayer coatings that will enable next-generation astrophysics missions in the x-ray region (2 – 7 nm wavelengths) where currently high-performance coatings largely do not exist. This paucity is due to multilayer interfacial effects that severely reduce the coating reflectance; our approach was based on understanding these interfacial effects and on tailored process modifications to control and minimize them. The experimental validation of our approach was made difficult by our multilayer deposition tool being down for a large portion of the project. The required repairs used significant amount of funding and time, which forced to reduce the scope of the project. Our experimental study focused on Cr/C multilayers and their optimization using N2 reactive sputtering. We showed that the highest reflectance was achieved when depositing the multilayers with 35% N2, and with a larger Cr thickness ratio than what was initially predicted by simulations. This result consists of a 13% relative increase in reflectivity compared to our previous work. It will benefit upcoming NASA proposals and LLNL’s leadership in this area, as well as topics highly relevant to LLNL/DOE’s priority areas, such as x-ray laser science and semiconductor manufacturing. This work will be further investigated as part of a Laboratory Directed Research and Development (LDRD) Exploratory Research (ER) project starting in Fiscal Year (FY) 2024.

36 MATERIALS SCIENCE↗

Assessment of Carbonated Brine Injection as Low-risk Strategy for Geologic Carbon Storage

The main objective of this early-phase research was to evaluate the techno-economic feasibility and risk associated with combined brine and CO 2 storage in SWD wells using brine dissolution in the North Dakota portion of the Williston Basin. Three simulation studies were conducted to investigate: (1) CO 2 phases at different conditions, (2) wellbore compatibility, and (3) long-term storage fate in reservoir. (1) A simple reservoir model and injection simulations were created using data to represent the BEST (brine extraction and storage test) site, an operational SWD facility located near Watford City, North Dakota. The pressure evolution caused by CO 2 comingled in produced water injectate in a layer cake reservoir was then modeled while tracking aqueous CO 2 throughout the project. The salinity of the injection water, the salinity of the reservoir brine, and the amount of dissolved CO 2 comingled in the injection water were varied. (2) A wellbore corrosion model was performed using the CO 2 concentrations selected based on the reservoir modeling to examine the carbonated produced water impact on wellbore. (3) Reactive transport modeling was conducted with the optimal CO 2 concentration for this injection site to study the rock-fluid interactions and CO 2 fate in the reservoir. Results suggest that CO 2 dissolved in produced water can be injected without appreciably increasing subsurface pressure or leakage risks. Pressure buildup was found to vary with salinity but not with CO 2 mass fraction. Simulation results show that lower CO 2 percent mass fraction leads to a higher amount of CO 2 that can be dissolved at a higher injection salinity. Furthermore, the long-term goal of dissolution trapping in a traditional carbon storage project is accomplished from the start, mitigating risks associated with potential migration of buoyant CO 2 , so long as the reservoir pressure and temperature are used to determine the maximum mass fraction of the dissolved CO 2 .

54 ENVIRONMENTAL SCIENCES↗

An optimized approach and inflation media for obtaining complimentary mass spectrometry-based omics data from human lung tissue

Human disease states are biomolecularly multifaceted and can span across phenotypic states, therefore it is important to understand diseases on all levels, across cell types, and within and across microanatomical tissue compartments. To obtain an accurate and representative view of the molecular landscape within human lungs, this fragile tissue must be inflated and embedded to maintain spatial fidelity of the location of molecules and minimize molecular degradation for molecular imaging experiments. Here, we evaluated agarose inflation and carboxymethyl cellulose embedding media and determined effective tissue preparation protocols for performing bulk and spatial mass spectrometry-based omics measurements. Mass spectrometry imaging methods were optimized to boost the number of annotatable molecules in agarose inflated lung samples. This optimized protocol permitted the observation of unique lipid distributions within several airway regions in the lung tissue block. Laser capture microdissection of these airway regions followed by high-resolution proteomic analysis allowed us to begin linking the lipidome with the proteome in a spatially resolved manner, where we observed proteins with high abundance specifically localized to the airway regions. We also compared our mass spectrometry results to lung tissue samples preserved using two other inflation/embedding media, but we identified several pitfalls with the sample preparation steps using this preservation method. Overall, we demonstrated the versatility of the inflation method, and we can start to reveal how the metabolome, lipidome, and proteome are connected spatially in human lungs and across disease states through a variety of different experiments.

59 BASIC BIOLOGICAL SCIENCES↗

A Guideline to Mitigate Interfacial Degradation Processes in Solid‐State Batteries Caused by Cross Diffusion

Abstract Diffusion of transition metals across the cathode–electrolyte interface is identified as a key challenge for the practical realization of solid‐state batteries. This is related to the formation of highly resistive interphases impeding the charge transport across the materials. Herein, the hypothesis that formation of interphases is associated with the incorporation of Co into the Li 7 La 3 Zr 2 O 12 lattice representing the starting point of a cascade of degradation processes is investigated. It is shown that Co incorporates into the garnet structure preferably four‐fold coordinated as Co 2+ or Co 3+ depending on oxygen fugacity. The solubility limit of Co is determined to be around 0.16 per formula unit, whereby concentrations beyond this limit causes a cubic‐to‐tetragonal phase transition. Moreover, the temperature‐dependent Co diffusion coefficient is determined, for example, D 700 °C = 9.46 × 10 −14 cm 2 s −1 and an activation energy E a = 1.65 eV, suggesting that detrimental cross diffusion will take place at any relevant process condition. Additionally, the optimal protective Al 2 O 3 coating thickness for relevant temperatures is studied, which allows to create a process diagram to mitigate any degradation with a minimum compromise on electrochemical performance. This study provides a tool to optimize processing conditions toward developing high energy density solid‐state batteries.

Chemistry↗

Toward perturbation theory methods on a quantum computer

Perturbation theory, used in a wide range of fields, is a powerful tool for approximate solutions to complex problems, starting from the exact solution of a related, simpler problem. Advances in quantum computing, especially over the past several years, provide opportunities for alternatives to classical methods. Here, we present a general quantum circuit estimating both the energy and eigenstates corrections that is far superior to the classical version when estimating second-order energy corrections. We demonstrate our approach as applied to the two-site extended Hubbard model. In addition to numerical simulations based on qiskit, results on IBM’s quantum hardware are also presented. Our work offers a general approach to studying complex systems with quantum devices, with no training or optimization process needed to obtain the perturbative terms, which can be generalized to other Hamiltonian systems both in chemistry and physics.

97 MATHEMATICS AND COMPUTING↗

Direct current microplasma formation around microstructure arrays

We demonstrate the formation and transition behaviors of a microplasma around microstructure arrays at different gas pressures via two-dimensional particle-in-cell/Monte Carlo collision simulations. It is found that the microdischarge occurs outside the cathode microcavities at the lowest pressure and starts penetrating the microcavities with a curved sheath edge as the pressure increases. At higher pressure, coupled periodic microhollow cathode discharges (MHCDs) are formed inside the microcavities. Further increasing the gas pressure results in the disappearance of the MHCDs, and the dominant discharge shifts outside of the microcavity, locating above the protrusion tips. The effect of the space charge shielding on the discharge and the conditions for MHCD formation are discussed. The macroscopic discharge parameter scalings with the gas pressure and the electron kinetics are also examined. The results are helpful for deeply understanding the microplasma formation with nonplanar electrodes, which inform the scaling, design, and optimization of microplasma array devices across a wide range of pressure regimes in practical applications.

42 ENGINEERING↗

Initial steady-state core simulation capability or thermal and pool-type molten salt reactors, coupling reactor physics, thermal-hydraulics, and evolving chemistry

This report presents the development and validation of an initial steady-state multiphysics capability for molten salt reactors (MSRs) under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in Fiscal Year 2025. The framework integrates neutronics, thermal-hydraulics, species transport, and thermochemistry to capture the coupled dynamics of liquid-fueled systems. Implementation and testing were performed on two representative designs: the Molten Salt Reactor Experiment (MSRE), a thermal-spectrum, channeled-flow reactor, and the Lotus Molten Salt Reactor (L-MSR), a fast-spectrum, pool-type reactor. The modeling suite employs Griffin for reactor physics and depletion, Pronghorn and SAM for thermal-hydraulics, Thermochimica for chemistry, and Saline for thermophysical properties, with benchmarking and validation carried out against historical MSRE data, experimental flow-loop measurements, and reference depletion calculations from Monte Carlo codes. The framework demonstrated the ability to reproduce key reactor behaviors including temperature feedback, reactivity losses, delayed neutron precursor transport, xenon poisoning, and redox potential evolution. The results confirm the feasibility and accuracy of the coupled models in predicting steady-state and selected transient MSR behaviors. This latter ones are used in this report as a proxy indicating that the steady-state models from which the transient starts are accurate. For MSRE, validation showed good agreement with pump start-up and natural circulation tests, while for the L-MSR, benchmarking confirmed hydraulic calibration and consistency of neutronics–thermal coupling. The tools also provided new insights into species transport, noble metal deposition, and salt solidification dynamics. On the Xenon transport front, the code is validated against the steady state Xenon poisoining measurement and showed good agreement with the experimental value. Identified areas for future work include advanced void transport modeling, three-dimensional simulations, improved alloy corrosion models, and tighter integration with high-fidelity Monte Carlo codes. These developments provide a foundation for high-fidelity MSR simulations that can support reactor design optimization, safety assessments, and long-term operational strategies.

42 - ENGINEERING↗

Hierarchical multi-time-scale predictive thermal management and fuel optimization for heavy-duty compression ignition engines

For heavy-duty diesel engines, NO X emissions reduction is strongly constrained by fuel efficiency. This paper presents a hierarchical model predictive controller (H-MPC) for coordinated control of tailpipe NO X emissions and fuel consumption. The H-MPC uses the separation of slow and fast dynamics that exist in the engine and its aftertreatment system. The controller is synthesized with an architecture in which a high-level MPC uses a longer prediction horizon compared to the low-level predictive controller which tracks the high-level controller command and manages the thermal dynamics of the aftertreatment system. Engine load preview enables the high-level controller to estimate the desired catalyst temperature ahead of time and addresses the selective catalytic reduction (SCR) slow thermal dynamics. Calculated by the high-level controller, the intake manifold pressure, and the start of injection (SOI) crank angle is used as reference trajectories in the low-level controller that regulates fast dynamical behaviors such as engine out NO X emissions. Hardware-in-the-loop (HIL) validation of this integrated H-MPC on a rapid prototype controller shows that when the SCR catalyst temperature is above light-off temperature (warmed-up condition), the engine operation is shifted to operate with the best fuel economy since the warmed-up SCR can efficiently reduce the engine-out NO X emissions. Results indicate that up to 0.8% benefit in cycle averaged BSFC along with a 13% reduction in tailpipe NO X compared to a stock engine calibration can be achieved with the coordinated engine and aftertreatment system through H-MPC.

Engineering↗

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗

Constant Overhead Entanglement Distillation via Scrambling

High-fidelity quantum entanglement enables key quantum networking capabilities such as secure communication and distributed quantum computing, but long-distance entanglement distribution is limited by noise and loss. Entanglement distillation protocols address this problem by extracting high-fidelity Bell pairs from multiple noisy ones. The primary objective is minimizing the resource overhead: the number of noisy input pairs needed to distill each high-fidelity output pair. While protocols achieving optimal overhead are known in theory, they often require complex decoding operations that make practical implementation challenging. We circumvent this challenge by introducing protocols that use quantum scrambling—the spreading of quantum information under chaotic dynamics—through random Clifford operations. Based on this scrambling mechanism, our protocol maintains asymptotically constant overhead, independent of the desired output error rate $\bar{𝜖}$ , and can be implemented with shallow quantum circuits of depth 𝑂⁡(poly log log⁡ $\bar{𝜖}$ −1 ) and memory 𝑂⁡(poly log⁡ $\bar{𝜖}$ −1 ). Our protocol remains effective even with noisy quantum gates. By incorporating error correction, our protocol achieves state-of-the-art performance: starting with pairs of 10% initial infidelity, we require only seven noisy inputs per output pair to distill a single Bell pair with infidelity $\bar{𝜖}$ =10 −12 , substantially outperforming existing schemes. We demonstrate the utility of our protocols for quantum repeater networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sensitivity of Riparian Buffer Designs to Climate Change—Nutrient and Sediment Loading to Streams: A Case Study in the Albemarle-Pamlico River Basins (USA) Using HAWQS

Riparian buffer zones (RBZs) provide multiple benefits to watershed ecosystems. We aimed to conduct an extensive sensitivity analysis of the RBZ designs to climate change nutrient and sediment loadings to streams. We designed 135 simulation scenarios starting with the six baselines RBZs (grass, urban, two-zone forest, three-zone forest, wildlife, and naturalized) in three 12-digit Hydrologic Unit Code watersheds within the Albemarle-Pamlico river basin (USA). Using the hydrologic and water quality system (HAWQS), we assessed the sensitivity of the designs to five water quality indicator (WQI) parameters: dissolved oxygen (DO), total phosphorous (TP), total nitrogen (TN), sediment (SD), and biochemical oxygen demand (BD). To understand the climate mitigation potential of RBZs, we identified a subset of future climate change projection models of air temperature and precipitation using EPA’s Locating and Selecting Scenarios Online tool. Analyses revealed optimal RBZ designs for the three watersheds. In terms of watershed ecosystem services sustainability, the optimal Urban RBZ in contemporary climate (1983–2018) reduced SD from 61–96%, TN from 34–55%, TP from 9–48%, and BD from 53–99%, and raised DO from 4–10% with respect to No-RBZ in the three watersheds. The late century’s (2070–2099) extreme mean annual climate changes significantly increased the projected SD and BD; however, the addition of urban RBZs was projected to offset the climate change reducing SD from 28–94% and BD from 69–93% in the watersheds. All other types of RBZs are also projected to fully mitigate the climate change impacts on WQI parameters except three-zone RBZ.

54 ENVIRONMENTAL SCIENCES↗

Potential Supply Chain and Cost Reduction Strategies for Advanced Nuclear Reactors

This milestone represents a level of effort to provide recommendations for a supply chain plan and establish relationships between advanced reactor companies and large companies in the oil & gas and chemical industries. It represents a starting point to develop the plan with options, general equipment lists, and rough associated cost estimates of major equipment and the associated systems needed. This effort will provide an opportunity to leverage the experience that oil & gas and chemicals companies possess in large capital equipment procurement, modularization, acquisition and installation. Potential supply chain solutions will be discussed and preliminary options for worldwide manufacturers will be elucidated. The goal of this effort will be to leverage the years of accumulated experience in the oil & gas and chemical industries in the area of capital equipment acquisition to understand the potential supply chain options and to reduce potential acquisition costs by optimizing the supply chain options for advanced nuclear reactor modularization, manufacturing and acquisition.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Overview on Shielding Analyses for the VENUS Instrument at SNS

VENUS, a world‐class versatile neutron imaging instrument, is under construction and is expected to be completed and ready to start commissioning in 2023. The range of cold to epithermal neutrons at SNS will give users of VENUS access to novel imaging methods, as well as to significantly improved existing methods. The instrument is being built on beam line 10 at Spallation Neutron Source (SNS) First Target Station (FTS) facing a decoupled poisoned hydrogen moderator. Instrument design, which includes optics, Front-End components and instrument enclosure components and shape started over 10 years ago and during this time had significant changes. All changes were supported by neutronics analyses to provide adequate shielding for both Front-End and instrument enclosure.Final optics design will provide the field of view (FOV) at the detector position (where the image is formed) to be as high as 0.20 by 0.20 m. Both the beam, which contains a large fraction of high-energy neutrons, and the desire for a large footprint on the detector are challenges for shielding design and budget, because the driving cost for the instrument is the beam line and enclosure shielding. For cost reason VENUS baseline design is optimized with respect to both the instrument cave footprint and its wall thickness, and Front-End shielding is tailored along the beam. Analyses are performed with the Monte Carlo particle transport code MCNPX version 2.7.0 to make choices on materials, thicknesses and configurations of the shielding. Numerous calculations are performed to meet space and coast constrain and to satisfy instrument physics needs and to comply with radiation protection requirements.

Gallmeier, Franz X.↗

ENSIGN

ENSIGN is a data analytics software package offering a modern unsupervised machine learning solution for scalable discovery in Big Data. The analytics in ENSIGN are based on an advanced mathematical tool called tensor decomposition and they are optimized to run efficiently on a range of computing platforms (from small multicore Desktop platforms to large Supercomputing clusters and novel high-end memory-driven computing platforms such as HPE Superdome Flex). ENSIGN enables the user to extract deep insights from the entirety of massive-scale (100s of Gigabytes or Terabytes scale) multidimensional data. ENSIGN uncovers latent patterns in data without the user having to specify or describe what the patterns are; the user, in the first place, may not even know such patterns existed and that they have to look for such patterns. The insights gained from ENSIGN could be trailheads that can be used as starting points for deeper forensic investigation.

Baskaran, Muthu↗

ENSIGN

ENSIGN is a data analytics software package offering a modern unsupervised machine learning solution for scalable discovery in Big Data. The analytics in ENSIGN are based on an advanced mathematical tool called tensor decomposition and they are optimized to run efficiently on a range of computing platforms (from small multicore Desktop platforms to large Supercomputing clusters and novel high-end memory-driven computing platforms such as HPE Superdome Flex). ENSIGN enables the user to extract deep insights from the entirety of massive-scale (100s of Gigabytes or Terabytes scale) multidimensional data. ENSIGN uncovers latent patterns in data without the user having to specify or describe what the patterns are; the user, in the first place, may not even know such patterns existed and that they have to look for such patterns. The insights gained from ENSIGN could be trailheads that can be used as starting points for deeper forensic investigation.

Baskaran, Muthu↗

Positron beams at Ce+BAF

Positron beams would provide a new and meaningful probe for the experimental program at the Thomas Jefferson National Accelerator Facility (JLab). The JLab Positron Working Group, formed in 2018 and now with over 250 members from 75 institutions, continues to develop an experimental program with high duty-cycle positron beams including but not limited to future hadronic physics and dark matter experiments. Critical requirements involve generating positron beams with a high degree of spin polarization, sufficient intensity and a continuous-wave (CW) bunch train compatible with acceleration to 12 GeV at the Continuous Electron Beam Accelerator Facility (CEBAF). In this presentation we describe a start-to-end layout for positron beams at 12 GeV CEBAF utilizing the Low Energy Research Facility (LERF) at Jefferson Lab to build two new injectors. A GaAs dc high voltage photo-gun first generates >1 mA of polarized electrons which are then accelerated to 80-150 MeV and directed to a high-power spinning W target for polarized bremsstrahlung and positron pair creation. A second injector then collects, bunches and accelerates the positrons to 123 MeV. The positron beams are transported by a new beam line and injected into the CEBAF acceptance for acceleration to the end stations with energies up to 12 GeV. The layout is optimized to provide Users with positron spin polarization >60% and intensity greater than >100 nA, and with higher intensities when polarization is not required.

Benesch, J.↗

A Gate-to-Gate Life Cycle Assessment for the CO 2 -EOR Operations at Farnsworth Unit (FWU)

Greenhouse gas (GHG) emissions related to the Farnsworth Unit’s (FWU) carbon dioxide enhanced oil recovery (CO 2 -EOR) operations were accounted for through a gate-to-gate life cycle assessment (LCA) for a period of about 10 years, since start of injection to 2020, and predictions of 18 additional years of the CO 2 -EOR operation were made. The CO 2 source for the FWU project has been 100% anthropogenically derived from the exhaust of an ethanol plant and a fertilizer plant. A cumulative amount of 5.25 × 106 tonnes of oil has been recovered through the injection of 1.64 × 106 tonnes of purchased CO 2 , of which 92% was stored during the 10-year period. An LCA analysis conducted on the various unit emissions of the FWU process yielded a net negative (positive storage) of 1.31 × 106 tonnes of CO 2 equivalent, representing 79% of purchased CO 2 . An optimized 18-year forecasted analysis estimated 86% storage of the forecasted 3.21 × 106 tonnes of purchased CO 2 with an equivalent 2.90 × 106 tonnes of crude oil produced by 2038. Major contributors to emissions were flaring/venting and energy usage for equipment. Improvements on the energy efficiency of equipment would reduce emissions further but this could be challenging. Improvement of injection capacity and elimination of venting/flaring or fugitive gas are methods more likely to be utilized for reducing net emissions and are the cases used for the optimized scenario in this work. This LCA illustrated the potential for the CO 2 -EOR operations in the FWU to store more CO 2 with minimal emissions.

54 ENVIRONMENTAL SCIENCES↗

Structural and phonon anomalies in the superconducting Bi 2 Sr 2 CaCu 2 O 8+σ with varying doping level at high pressures

Here we examined the effect of the lattice compression on the crystal structure of the Bi 2 Sr 2 CaCu 2 O 8+σ superconductor with nearly optimally doped and overdoped composition using X-ray diffraction technique. Our studies show that at high pressures (up to 30 GPa ) the doping level does not affect the crystal structure of this superconductor. Along with this, structural anomalies in ratio appear at a pressure that corresponds to that at which T c begins to decrease. This fact indicates a close connection between the observed anomalies and superconductivity. We also studied the effect of doping and pressure on the T c (P) and on the Raman active lattice modes of the Bi 2 Sr 2 CaCu 2 O 8+σ superconductors. We find universal suppression of the T c by the pressure starting from the critical pressure P c in the range from 9 to 16 GPa, depending on the doping level of the Bi 2 Sr 2 CaCu 2 O 8+σ samples. Concomitantly, we observe phonon anomalies around 10 to 20 GPa, which indicate possible pressure-induced charge redistribution in BiO layers. These newly detected anomalies may be related to the changes in the electronic structure which compete with the superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗