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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Seawater alkalization via an energy-efficient electrochemical process for CO 2 capture

Electrochemical pH-swing strategies offer a promising avenue for cost-effective and energy-efficient carbon dioxide (CO 2 ) capture, surpassing the traditional thermally activated processes and humidity-sensitive techniques. The concept of elevating seawater’s alkalinity for scalable CO 2 capture without introducing additional chemical as reactant is particularly intriguing due to its minimal environmental impact. However, current commercial plants like chlor-alkali process or water electrolysis demand high thermodynamic voltages of 2.2 V and 1.23 V, respectively, for the production of sodium hydroxide (NaOH) from seawater. These high voltages are attributed to the asymmetric electrochemical reactions, where two completely different reactions take place at the anode and cathode. Here, we developed a symmetric electrochemical system for seawater alkalization based on a highly reversible and identical reaction taking place at the anode and cathode. We utilize hydrogen evolution reaction at the cathode, where the generated hydrogen is looped to the anode for hydrogen oxidation reaction. Theoretical calculations indicate an impressively low energy requirement ranging from 0.07 to 0.53 kWh/kg NaOH for established pH differences of 1.7 to 13.4. Experimentally, we achieved the alkalization with an energy consumption of 0.63 kWh/kg NaOH, which is only 38% of the theoretical energy requirements of the chlor-alkali process (1.64 kWh/kg NaOH). Further tests demonstrated the system’s potential of enduring high current densities (~20 mA/cm 2 ) and operating stability over an extended period (>110 h), showing its potential for future applications. Notably, the CO 2 adsorption tests performed with alkalized seawater exhibited remarkably improved CO 2 capture dictated by the production of hydroxide compared to the pristine seawater.

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

Ion velocity effect governs damage annealing process in defective KTaO 3

Effects of electronic to nuclear energy losses (S e /S n ) ratio on damage evolution in defective KTaO 3 have been investigated by irradiating pre-damaged single crystal KTaO 3 with intermediate energy O ions (6 MeV, 8 MeV and 12 MeV) at 300 K. By exploring these processes in pre-damaged KTaO 3 containing a fractional disorder level of 0.35, the results demonstrate the occurrence of a precursory stage of damage production before the onset of damage annealing process in defective KTaO 3 that decreases with O ion energy. The observed ionization-induced annealing process by ion channeling analysis has been further mirrored by high resolution transmission electron microscopy analysis. In addition, the reduction of disorder level is accompanied by the broadening of the disorder profiles to greater depth with increasing ion fluence, and enhanced migration is observed with decreasing O ion energy. Since S e (~3.0 keV nm –1 ) is nearly constant for all 3 ion energies across the pre-damaged depth, the difference in behavior is due to the so-called 'velocity effect': the lower ion velocity below the Bragg peak yields a confined spread of the electron cascade and hence an increased energy deposition density. Here, the inelastic thermal spike calculation has further confirmed the existence of a velocity effect, not previously reported in KTaO 3 or very scarcely reported in other materials for which the existence of ionization-induced annealing has been reported. In other words, understanding of ionization-induced annealing has been advanced by pointing out that ion velocity effect governs the healing of pre-existing defects, which may have significant implication for the creation of new functionalities in KTaO 3 through atomic-level control of microstructural modifications, but may not be limited to KTaO 3 .

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Structural and functional insights into the interaction between the bacteriophage T4 DNA processing proteins gp32 and Dda

Abstract Bacteriophage T4 is a classic model system for studying the mechanisms of DNA processing. A key protein in T4 DNA processing is the gp32 single-stranded DNA-binding protein. gp32 has two key functions: it binds cooperatively to single-stranded DNA (ssDNA) to protect it from nucleases and remove regions of secondary structure, and it recruits proteins to initiate DNA processes including replication and repair. Dda is a T4 helicase recruited by gp32, and we purified and crystallized a gp32–Dda–ssDNA complex. The low-resolution structure revealed how the C-terminus of gp32 engages Dda. Analytical ultracentrifugation analyses were consistent with the crystal structure. An optimal Dda binding peptide from the gp32 C-terminus was identified using surface plasmon resonance. The crystal structure of the Dda–peptide complex was consistent with the corresponding interaction in the gp32–Dda–ssDNA structure. A Dda-dependent DNA unwinding assay supported the structural conclusions and confirmed that the bound gp32 sequesters the ssDNA generated by Dda. The structure of the gp32–Dda–ssDNA complex, together with the known structure of the gp32 body, reveals the entire ssDNA binding surface of gp32. gp32–Dda–ssDNA complexes in the crystal are connected by the N-terminal region of one gp32 binding to an adjacent gp32, and this provides key insights into this interaction.

Biochemistry & Molecular Biology↗
DOE OSTI2026

String-Breaking Dynamics in Quantum Adiabatic and Diabatic Processes

Confinement prohibits isolation of color charges, e.g., quarks, in nature via a process called string breaking : the separation of two charges results in an increase in the energy of a color flux, visualized as a string, connecting those charges. Eventually, creating additional charges is energetically favored, hence breaking the string. Such a phenomenon can be probed in simpler models, including quantum spin chains, enabling enhanced understanding of string-breaking dynamics. A challenging task is to understand how string breaking occurs as time elapses, in an out-of-equilibrium setting. This work establishes the phenomenology of dynamical string breaking induced by a gradual increase of string tension over time. It, thus, goes beyond instantaneous quench processes and enables tracking the real-time evolution of strings in a more controlled setting. We focus on domain-wall confinement in a family of quantum Ising chains. Our results indicate that, for sufficiently short strings and slow evolution, string breaking can be described by the transition dynamics of a two-state quantum system akin to a Landau-Zener process. For longer strings, a more intricate spatiotemporal pattern emerges: the string breaks by forming a superposition of bubbles (domains of flipped spins of varying sizes), which involve highly excited states. We finally demonstrate that string breaking driven only by quantum fluctuations can be realized in the presence of sufficiently long-ranged interactions. This work holds immediate relevance for studying string breaking in quantum-simulation experiments.

Ising model↗
DOE OSTI2026

Direct cross section measurement of 102 Pd ⁢(𝛾,𝑝) and 102 Pd ⁢(𝛾,𝛼) for the astrophysical 𝑝 process

Background: A handful of neutron-deficient stable nuclei, known as the “p nuclei,” cannot be produced through astrophysical neutron capture processes. Instead, some of these nuclei are proposed to be produced by 𝛾-induced reactions on existing r- and s-process seeds. The specific astrophysical site or sites are not yet identified, however, with uncertainties in the cross sections of these 𝛾-induced reactions playing a role. Databases of reaction rates for astrophysical simulations often rely on theoretical statistical model calculations, such as Hauser-Feshbach, for rates where no experimental information is known. However, reasonable variations in the choice of parametrizations of various nuclear properties can create order-of-magnitude variations in the final predicted cross sections and reaction rates, which are then propagated through the models to the predicted final abundances. Purpose: To better constrain these statistical model calculations and ultimately reduce the uncertainties from the nuclear physics on our understanding of the p nuclei, a measurement of the cross sections of 𝛾-induced reactions on the p-nucleus 102 Pd was undertaken. This work represents the first measurement of its kind, using segmented silicon detectors to measure prompt charged particle emission from 𝛾-induced reactions. Methods: Quasimonoenergetic gamma beams from the High Intensity 𝛾 Source facility bombarded an enriched 102 Pd target. A segmented silicon array was arranged to detect the particles emitted from (𝛾,𝑝) and (𝛾,𝛼) reactions. Results: Reaction cross sections were deduced at multiple 𝛾-beam energies between 10 and 19 MeV, and compared to statistical model calculations using talys-1.96. The 102 Pd ⁢(𝛾,𝑝)⁢ 101 Rh reaction cross section was reasonably well reproduced by a subset of photon strength functions and level densities, though the strength to the ground state of 101 Rh was underestimated at higher incident gamma energies. The 102 Pd ⁢(𝛾,𝛼)⁢ 98 Ru was in general overpredicted by the various alpha-nucleus optical model potentials. Conclusions: While the theoretical cross sections used to model the (𝛾,𝑝) reactions for the p process may be reasonable, a more careful approach is needed in the case of (𝛾,𝛼). Further work to probe gamma-induced reaction cross sections at and near the p nuclei is warranted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Linear Boltzmann transport for jet propagation in the quark-gluon plasma: Inelastic processes and jet modification

A linear Boltzmann transport (LBT) Monte Carlo model has been developed to describe jet propagation and interaction with the quark-gluon plasma (QGP) in relativistic heavy-ion collisions. A complete set of elastic-scattering processes and medium-induced gluon emissions based on the higher-twist formalism are incorporated for both jet shower and medium recoil partons. It has been employed to describe experimental data on large transverse momentum hadron and jet spectra, correlation and jet substructures in high-energy heavy-ion collisions. Here, we document in detail the structure of the model and validation of the Monte Carlo implementations of the physics processes in LBT, in particular, the inelastic process of medium-induced gluon radiation. We carry out a comprehensive examination of the jet-medium interaction as implemented in LBT through energy loss and momentum broadening of a single hard parton, the energy and transverse momentum transfer from leading partons to medium-induced gluons and jet-induced medium excitation, and medium modification of reconstructed jets in a static and uniform medium. With realistic and event-by-event hydrodynamic medium in heavy-ion collisions, we compute and compare with experimental data on the jet cone-size dependence of the single inclusive jet suppression at both the BNL Relativistic Heavy-Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC), the dijet asymmetry at the LHC and γ-jet correlation at RHIC. Effects of medium-induced gluon emissions and jet-induced medium excitation on jet observables are systematically examined. Rescatterings of the radiated gluons and recoil partons with the QGP are found essential to account for the enhancement of soft particle yield toward the edge of the jet cone.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Quantum Thermodynamics of Nonequilibrium Processes in Lattice Gauge Theories

A key objective in nuclear and high-energy physics is to describe nonequilibrium dynamics of matter, e.g., in the early Universe and in particle colliders, starting from the standard model of particle physics. Classical computing methods, via the framework of lattice gauge theory, have experienced limited success in this mission. Quantum simulation of lattice gauge theories holds promise for overcoming computational limitations. Because of local constraints (Gauss’s laws), lattice gauge theories have an intricate Hilbert-space structure. This structure complicates the definition of thermodynamic properties of systems coupled to reservoirs during equilibrium and nonequilibrium processes. We show how to define thermodynamic quantities such as work and heat using strong-coupling thermodynamics, a framework that has recently burgeoned within the field of quantum thermodynamics. Our definitions suit instantaneous quenches, simple nonequilibrium processes undertaken in quantum simulators. To illustrate our framework, we compute the work and heat exchanged during a quench in a Z 2 lattice gauge theory coupled to matter in 1+1 dimensions. Here, the thermodynamic quantities, as functions of the quench parameter, evidence a phase transition. For general thermal states, we derive a simple relation between a quantum many-body system’s entanglement Hamiltonian, measurable with quantum-information-processing tools, and the Hamiltonian of mean force, used to define strong-coupling thermodynamic quantities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Generalized Quantum Signal Processing

Quantum signal processing (QSP) and quantum singular value transformation (QSVT) currently stand as the most efficient techniques for implementing functions of block-encoded matrices, a central task that lies at the heart of most prominent quantum algorithms. However, current QSP approaches face several challenges, such as the restrictions imposed on the family of achievable polynomials and the difficulty of calculating the required phase angles for specific transformations. In this paper, we present a generalized quantum signal processing (GQSP) approach, employing general SU(2) rotations as our signal-processing operators, rather than relying solely on rotations in a single basis. Our approach lifts all practical restrictions on the family of achievable transformations, with the sole remaining condition being that | P | ≤ 1 , a restriction necessary due to the unitary nature of quantum computation. Furthermore, GQSP provides a straightforward recursive formula for determining the rotation angles needed to construct the polynomials in cases where P and Q are known. In cases where only P is known, we provide an efficient optimization algorithm capable of identifying in under a minute of GPU time, a corresponding Q for polynomials of degree on the order of 10 7 . We further illustrate GQSP simplifies QSP-based strategies for Hamiltonian simulation, offer an optimal solution to the ϵ -approximate fractional query problem that requires O ( ( 1 / δ ) + log ( 1 / ϵ ) ) queries to perform where O ( 1 / δ ) is a proved lower bound, and introduces novel approaches for implementing bosonic operators. Moreover, we propose a novel framework for the implementation of normal matrices, demonstrating its applicability through synthesis of diagonal matrices, as well as the development of a new algorithm for convolution through synthesis of circulant matrices using only O ( d log N + log 2 N ) 1 and 2-qubit gates for a filter of lengths d . Published by the American Physical Society 2024

Motlagh, Danial↗
DOE OSTI2026

First plasma processing trial of a quarter-wave resonator cryomodule at the Facility for Rare Isotope Beams

Studies of plasma processing for reduction of field emission in quarter-wave resonator (QWR) cryomodules are underway at the Facility for Rare Isotope Beams (FRIB), where a total of 104 QWRs are presently in operation. Driving the plasma with a higher-order mode allows for less mismatch at the fundamental power coupler and higher plasma density. The first plasma processing trial for FRIB QWRs in a cryomodule was conducted in January 2024. In-bunker cold tests of the cryomodule showed a significant reduction in field emission x-rays after plasma processing.

Glow & corona plasma discharges↗
DOE OSTI2026

pathSQE : an automated workflow for single-crystal inelastic neutron scattering data processing and analysis

Inelastic neutron scattering (INS) experiments utilizing modern time-of-flight spectrometers enable the comprehensive mapping of the energy (E)- and momentum (Q)-resolved dynamical structure factor of single crystals, probing both the lattice and magnetic excitations. Yet, the large size and complexity of four-dimensional INS data are challenging current analysis workflows, often resulting in an underutilization of the measured information. To help address this issue, this paper introduces new software interfaced with the Mantid framework, pathSQE, designed to streamline the processing, analysis and interpretation of 4D single-crystal INS data. By automating key tasks such as 1D/2D slicing, symmetrization, Brillouin zone folding, data visualization, prioritization and filtering, and comparisons with simulations, pathSQE facilitates and accelerates INS data analysis workflows. Here, this paper outlines the features and implementation and provides several illustrations of the use of pathSQE on data collected on single crystals using direct-geometry time-of-flight spectrometers at the Spallation Neutron Source, including Ge, FeSi, MnO and SnS single-crystal measurements on the ARCS, HYSPEC and CNCS neutron spectrometers. Beyond streamlining post-experiment data processing, pathSQE establishes an automated and modular processing pipeline that could support future real-time experiment steering.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Preparing an on-Demand Cloud Processing Workflow for NISAR Ecosystems Science Products

In preparation for the NISAR launch and data collection in 2024, the NISAR Project Science Team is building workflows for each Science Team discipline (Ecosystems, Cryosphere, and Solid Earth). This abstract focuses on the Ecosystem disciplines and the development of on-demand cloud-processing workflows for wetlands inundation, forest biomass, agricultural active crop area, and forest disturbance. The workflow simulates NISAR data using UAVSAR or ALOS-2 Single Look Complex data, which are processed to Level 2 geocoded polarimetric covariance matrix products using InSAR Scientific Computing Environment 3.0 software and to Level 3 science products using the Algorithm Theoretical Basis Documents. In this presentation, we describe these workflows and efforts to improve efficiency and data accessibility by using a cloud processing system. We present preliminary sample products from each Ecosystem discipline: inundation, forest biomass, crop area, and forest disturbance.

Christensen, Alexandra↗
DOE OSTI2024

Mass, enthalpy, and chemical‐derived emission flows in mineral processing

Abstract The production of materials from mineral resources is a significant contributor to anthropogenic CO 2 emissions. This contribution is driven primarily by chemical CO 2 emissions from the conversion of mineral resources and emissions tied to energy demands for material processing. In this work, we synthesize the thermodynamically required enthalpy and chemically derived emissions of mineral processing and consumption in the United States. We quantify mass, enthalpy, and emissions flows for minerals described by the US Geological Survey, with 882 mass flows and 155 chemical reactions analyzed. In total, 503 PJ of enthalpy is thermodynamically required for 398 Mt of chemically converted material consumption in the United States, resulting in 129 Mt of chemically derived CO 2 emissions. Additionally, 249 PJ of fuel resources such as coke are stoichiometrically required for the chemical conversion of minerals. These enthalpy requirements and CO 2 emissions are primarily from high‐mass consumption materials such as cement, carbon steel, fertilizer, and aluminum. Cumulatively, the dataset synthesized in this work provides a complete view of the chemical requirements of mineral processing and can aid in guiding decarbonization or sustainable growth in critical minerals sectors, including construction materials and materials for energy storage or generation.

Kane, Seth↗
DOE OSTI2026

Engineering Microstructure in Dry-Processed Cathodes Via Calendering

Calendering serves as a multifunctional step in dry electrode processing that not only densifies the electrode but also induces polytetrafluoroethylene (PTFE) fibrillation and reorganizes the microstructure. These coupled effects are essential for achieving electrical connectivity and sufficient cohesion, yet they also introduce trade-offs, such as active material particle fracture, pore collapse, and excessive porosity loss, that can hinder ionic transport. This research systematically maps the calendering parameter space for LiNi0.6Mn0.2Co0.2O2 (NMC622) dry cathodes with a target thickness of ∼100 µm and porosity of ∼30% by varying roll gaps, roll temperature, roll speed, and the number of passes. A practical processing window for this formulation and electrode architecture is identified that achieves sufficient PTFE fibrillation and strong interfacial contact while minimizing particle fracture and preserving the porosity required for efficient ionic transport. In particular, gradual-gap calendering with moderate per-pass compression mitigates fracture and pore collapse while still reaching the target thickness with reasonable throughput, and slower roll speeds with modest roll temperatures further reduce mechanical damage. These results provide actionable guidance for scaling NMC622-based thick dry-processed cathodes.

Park, Hyunji↗
DOE OSTI2024

Arroyo Stream Processing Toolset (arroyopy) v0.1.0

Processing event or streaming data presents several technological challenges. A variety of technologies are often used by scientific user facilities. ZMQ is used to stream data and messages in a peer-to-peer fashion. Message brokers like Kafka, Redis Pubsub, EPICS PVA and RabbitMQ are often employed to route and pass messages from instruments to processing workflows. Arroyopy provides an API and structure to flexibly integrate with these tools and incorporate arbitrarily complex processing workflows, letting the hooks to the workflow code be independent of the connection code and hence reusable at a variety of instruments.

Chavez Esparza, Tanny Andrea [Lawrence Berkeley Na↗
DOE OSTI2026

LaPT (Lab Process Tracker) [SWR-26-048]

LaPT (Lab Process Tracker) is a QR/barcode scanning infrastructure for tracking samples and processes. It is a tracking application for lab operations with a graphical user interface. Track processes and sample scans using QR code input, with logs saved to CSV files.

Daxini, Rajiv [National Laboratory of the Rockies ↗
DOE OSTI2024

Approach for energy efficient building design during early phase of design process

Energy consumption in the building sector is about 40% of total energy consumed globally and is trending upwards, along with its contribution to greenhouse gas (GHG) emissions. Given the adverse impacts of GHG emissions, it is crucial to integrate energy efficiency into building designs. The most significant opportunities for enhancing energy performance are present during the initial phases of building design, when there is less impact of other design constraints. Various tools exist for simulating different design options and providing feedback in terms of energy consumption and comfort parameters. These simulation outputs must then be analyzed to derive design solutions. This paper presents an innovative approach that utilizes user input parameters, processes them through cloud computing, and outputs easily understandable strategies for energy-efficient building design. The methodology employs Asynchronous Distributed Task Queues (DTQ) - a more scalable and reliable alternative to conventional speedup techniques-for conducting parametric energy simulations in the cloud. The goal of this approach is to assist design teams in identifying, visualizing, and prioritizing energy-saving design strategies from a range of possible solutions for each project. Furthermore, a tool ‘eDOT’ has been developed utilizing the discussed methodology. Unlike existing tools, eDOT leverages artificial intelligence to dynamically generate and provide design strategies during the early phases of design process. By simplifying the simulation process, eDOT enables design teams to make informed, data-driven decisions without needing to interpret complex simulation outputs. A case study simulated for two locations is provided in this paper to demonstrate the effectiveness of eDOT, further underscoring its practical impact on energy-efficient building design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Data for Microbial-Explicit Processes and Refined Perennial Plant Traits Improve Modeled Ecosystem Carbon Dynamics

Globally, soils hold approximately half of ecosystem carbon and can serve as a source or sink depending on climate, vegetation, management, and disturbance regimes. Understanding how soil carbon dynamics are influenced by these factors is essential to evaluate proposed natural climate solutions and policy regarding net ecosystem carbon balance. Soil microbes play a key role in both carbon fluxes and stabilization. However, biogeochemical models often do not specifically address microbial-explicit processes. Here, we incorporated microbial-explicit processes into the DayCent biogeochemical model to better represent large perennial grasses and mechanisms of soil carbon formation and stabilization. We also take advantage of recent model improvements to better represent perennial grass structural complexity and life-history traits. Specifically, this study focuses on: 1) a plant sub-model that represents perennial phenology and more refined plant chemistry with downstream implications for soil organic matter (SOM) cycling though litter inputs, 2) live and dead soil microbe pools that influence routing of carbon to physically protected and unprotected pools, 3) Michaelis-Menten kinetics rather than first-order kinetics in the soil decomposition calculations, and 4) feedbacks between decomposition and live microbial pools. We evaluated the performance of the plant sub-model and two SOM cycling sub-models, Michaelis-Menten (MM) and first-order (FO), using observations of net ecosystem production, ecosystem respiration, soil respiration, microbial biomass, and soil carbon from long-term bioenergy research plots in the mid-western United States. The MM sub-model represented seasonal dynamics of soil carbon fluxes better than the FO sub-model which consistently overestimated winter soil respiration. While both SOM sub-models were similarly calibrated to total, physically protected, and physically unprotected soil carbon measurements, the models differed in future soil carbon response to disturbance and climate, most notably in the protected pools. Adding microbial-explicit mechanisms of soil processes to ecosystem models will improve model predictions of ecosystem carbon balances but more data and research are necessary to validate disturbance and climate change responses and soil pool allocation.

Field Data↗
DOE OSTI2024

Competitiveness Assessment of Decarbonizing Electricity and Process Heat Supply to a Campus with a Small Nuclear Reactor

This paper analyzes the competitiveness of siting a small nuclear reactor to support decarbonization of sites requiring tens of MW of electricity and/or process heat to support centralized heating and cooling system. This paper focuses on campuses as representative of sites with collections of buildings and research facilities with decarbonization needs represented by buildings heating, and electricity consumption by electrical loads which may include cooling via chilled water (e.g., for air conditioning and to cool down computer clusters). A nuclear reactor can be considered to decarbonize a site’s high-temperature steam generation used mostly for building heating needs, climate control, and hot water, by supplying process heat capabilities, while electricity decarbonization would be achieved mostly by the grid. However, a secondary application can be considered to maximize reactor utilization and avoid ramping down the reactor if the steam demand varies significantly throughout the year. Chilled water generation through steam-driven systems was identified as an attractive secondary option for the site analyzed, due to potential for plant design simplification, while electricity generation could be considered as well to reduce electricity purchases for a wider range of site applications. For a campus with peak 60MW thermal power demand, a small nuclear reactor with similar thermal power rating would almost eliminate CO2 emissions from steam generation and reduce electricity imports for chilled water production. A preliminary techno-economic feasibility study shows that a small nuclear reactor design that is optimized to support process heat can represent an economically feasible option when compared with other decarbonization alternatives.

Stauff, Nicolas E.↗