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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Reexamining the relation between the binding energy of finite nuclei and the equation of state of infinite nuclear matter

The energy density is calculated in coordinate space for 12 C, 40 Ca, 48 Ca, and 208 Pb using a dispersive optical model constrained by all relevant data including the corresponding energy of the ground state. The energy density of 8 Be is also calculated using the Green’s function Monte-Carlo method employing the Argonne/Urbana two and three-body interactions. The nuclear interior minimally contributes to the total binding energy due to the 4πr 2 phase space factor. Thus, the volume contribution to the energy in the interior is not well constrained. The dispersive-optical-model energy densities are in good agreement with ab initio self-consistent Green’s function calculations of infinite nuclear matter restricted to treat only short-range and tensor correlations. These results call into question the degree to which the equation of state for nuclear matter is constrained by the empirical mass formula. In particular, the results in this work indicate that saturated nuclear matter does not require the canonical value of 16 MeV binding per particle but only about 13-14 MeV when the interior of 208 Pb is considered.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Diversifying the Materials and Technologies for the Future of Energy Storage

It is increasingly important to meet the growing global energy demand driven by factors such as population growth, electrification, and the rapid development of emerging economies, while minimizing the environmental harm caused by carbon dioxide emissions. Although fossil fuels remain an abundant and inexpensive energy source, there is a global consensus on the critical importance of addressing climate change and an increasing urgency to reduce carbon dioxide emissions without hindering economic growth. This challenge is particularly daunting due to the significant transformations required in electricity generation systems, transportation, and industrial processes. A significant portion of our energy still comes from burning fossil fuels, which poses harmful effects on the environment. Transitioning to renewable energy sources like solar and wind is essential, as these sources provide a low-carbon pathway for power generation and have become increasingly cost-competitive with fossil fuels. However, they face the inherent challenge of intermittency. Thus, energy storage systems (ESS) are essential not only to address this issue but also to accommodate the increasing adoption of electric vehicles (EVs). Lithium-ion batteries (LIBs) are still the predominant ESS used for these applications; however, they suffer from issues related to scarce and harmful resources, safety, and socio-economic impacts. This underscores the need for alternative energy storage systems beyond LIBs. Here, in this review, we discuss the diversification, repurposing, and recycling of ESS to meet the projected energy demand while minimizing environmental harm.

batteries↗
DOE OSTI2021

Modeling in High Temperature Corrosion: A Review and Outlook

Realizing higher operating temperatures to increase efficiency of future applications for energy conversion and storage while minimizing cost is a challenge for development of high-temperature materials. Simultaneous optimization of mechanical properties and corrosion resistance continues to be a difficult task but is essential due to the need to significantly accelerate the transition between technology readiness levels in the future. Furthermore, oxidation-induced degradation will be a critical life-limiting mechanism at increased operating temperatures. Suitable high-temperature materials cannot be solely identified by time-consuming experiments and reliable computational methods incorporating the relevant physics of processes must be considered to complement the experimental efforts. In the present work, a review of the methods employed to model oxidation-induced material degradation described in literature will be discussed. Furthermore, their capability to predict lifetime and aid in material selection will be evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Grid-responsive hydrogen production: Capital utilization and current density vs. efficiency in variable electricity markets

To achieve low-cost hydrogen production from water electrolyzers, grid tied electrolysis may need to operate dynamically to minimize the cost of supplying energy to the electrolyzer stack and produce hydrogen during low-cost hours and turn off/down during high-cost hours. Operating systems in this way can decrease capital utilization (capacity factor) and electricity costs. This strategy would shift the dominant cost drivers away from electricity (and thus efficiency) to the capital costs of the system, due to the underutilized capital when operating at low-capacity factors. Increasing the operational current density of the system could, in effect, reduce the capital cost of the system while producing hydrogen at a lower efficiency on a per unit energy basis. In the variable electricity cost profiles analyzed in this paper, increasing the current density for liquid alkaline from 0.5 A/cm2 to 1.5 Ac/m2 and proton exchange membrane electrolyzers from 2 A/cm2 to 4 A/cm2 resulted in substantial reductions in the levelized cost of hydrogen. Additionally, as capacity factors and electricity costs decrease, the optimal operating current density of the electrolyzer systems analyzed increases. These findings suggest R&D efforts should focus on increasing the operational current densities, reducing the turn down ratios, and understanding the durability implications of those strategies on low-temperature liquid alkaline and proton exchange membrane electrolyzers.

08 HYDROGEN↗
DOE OSTI2023

Impact of organic solutes on capillary phenomena in water-CO2-quartz systems

Hypothesis: The migration of supercritical CO2 (scCO2) injected into underground reservoirs as part of carbon capture and storage is influenced by organic contamination affecting mineral wettability. Molecular dynamics (MD) simulations of relevant systems that incorporate representative organic solutes allow detailed investigation of changes in fundamental interfacial and capillary properties. Experiments: We use MD simulations to explore the effects of four organic solutes (quinoline, decanoic acid, coronene, sorgoleone) on the wettability of quartz by water in the presence of scCO2. We examine the impacts of polar, alkyl, and aromatic moieties as well as fluid flow velocity at elevated temperatures and pressures. Findings: Organic molecules accumulate at the water-CO2 interface, where they distribute according to their size and functional groups. Certain organics penetrate the adsorbed water film at the quartz-CO2 interface, revealing two modes of hydrogen bonding between polar organic functional group, water, and quartz surface –OH groups. Interfacial energies and contact angles are minimally impacted by organic adsorption at the water-CO2 interface, possibly due to simultaneous CO2 desorption. Non- equilibrium MD simulations reveal that flow-induced redistribution of organic compounds modulates the radii of curvature of the advancing and receding water-CO2 interfaces. Our results indicate that organic adsorption on water surfaces is likely ubiquitous during multi-phase flow in soils and sedimen- tary rocks, with implications for the mobilization and transport of organic compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modular Integrated System for Carbon-Neutral Methanol Synthesis Using Direct Air Capture and Carbon-Free Hydrogen Production

This study investigates the development and economic analysis of a modular integrated system for carbon-neutral methanol synthesis, leveraging direct air capture (DAC) and solid oxide electrolysis cells (SOEC) for carbon dioxide and hydrogen production, respectively. The proposed system integrates a novel building-based DAC process, functionalized solid sorbents, and low-energy SOEC technology, aiming to minimize operational and capital costs. A comparison between the base case system (1,000 t methanol/year) and a scaled-up model (14,758 t methanol/year) reveals significant improvements in efficiency and economic feasibility. The scaled-up system achieves a levelized cost of methanol (LCOM) of $740/t, a 7.5% reduction compared to that of conventional DAC-based systems, while utilizing existing building HVAC infrastructure for air handling. Detailed sensitivity analyses were conducted, evaluating the effects of plant capacity and air flow rate on the LCOM, demonstrating the scalability of the building-based DAC system. The cradle-to-gate life cycle analysis shows that the proposed process using renewable-sourced electricity achieves a 38% reduction in greenhouse gas (GHG) emission compared to reported values of green methanol production technologies that use a conventional DAC and a conventional methanol synthesis catalyst. When fossil-sourced electricity is used in the proposed process, it leads to about a 37.5% reduction in GHG emission in comparison to reported values for conventional methanol production technologies using steam methane reforming technology and fossil-sourced electricity.

alcohols↗
DOE OSTI2024

Beyond Single-Reference Fixed-Node Approximation in Ab Initio Diffusion Monte Carlo Using Antisymmetrized Geminal Power Applied to Systems with Hundreds of Electrons

Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in Fermionic systems, the projection needs to be carried out while imposing antisymmetric constraints, which is a nondeterministic polynomial hard problem. In practice, therefore, the application of DMC on electronic structure problems is made by employing the fixed-node (FN) approximation, consisting of performing DMC with the constraint of having a fixed, predefined nodal surface. How do we get the nodal surface? The typical approach, applied in systems having up to hundreds or even thousands of electrons, is to obtain the nodal surface from a preliminary mean-field approach (typically, a density functional theory calculation) used to obtain a single Slater determinant. This is known as single reference. In this paper, we propose a new approach, applicable to systems as large as the C 60 fullerene, which improves the nodes by going beyond the single reference. In practice, we employ an implicitly multireference ansatz (antisymmetrized geminal power wave function constraint with molecular orbitals), initialized on the preliminary mean-field approach, which is relaxed by optimizing a few parameters of the wave function determining the nodal surface by minimizing the FN-DMC energy. We highlight the improvements of the proposed approach over the standard single-reference method on several examples and, where feasible, the computational gain over the standard multireference ansatz, which makes the methods applicable to large systems. We also show that physical properties relying on relative energies, such as binding energies, are affordable and reliable within the proposed scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Rapid Electron Transfer Self-Exchange in Conformationally Dynamic Copper Coordination Complexes

Here we report the electron transfer (ET) self-exchange rate constants (k 11 ) for a pair of Cu II/I complexes utilizing dpa R (dpa = dipicolylaniline, R = OMe, SMe) ligands assessed by NMR line-broadening experiments. These ligands afford copper complexes that are conformationally dynamic in one oxidation state. With R = OMe, the Cu I complex is dynamic, while with R= SMe, the Cu II complex is dynamic. Both complexes exhibit unexpectedly large k 11 of 2.48(6) x 10 5 and 2.21(9) × 10 6 M –1 s –1 for [CuCl(dpa OMe )] +/0 and [CuCl(dpa SMe )] +/0 , respectively. Among the fastest reported for molecular copper coordination complexes to date, that of [CuCl(dpa SMe )] +/0 exceeds all others by an order of magnitude and compares only to those observed in type 1 blue copper proteins. The dynamicity of these complexes establish pre-steady-state con-formational equilibria that minimize the inner sphere reorganization energies to 0.71 and 0.62 eV for R = OMe and SMe, respectively. In contrast to the emphasis on rigidity in the formulation of entatic states applied to blue copper proteins, the success of these two systems highlight the relevance of conformational dynamicity in mediating rapid ET.

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

Direct extraction of lithium from ores by electrochemical leaching

With the rapid increase in lithium consumption for electric vehicle applications, its price soared during the past decade. To secure a reliable and cost-effective supply chain, it is critical to unlock alternative lithium extraction resources beyond conventional brine. In this study, we develop an electrochemical method to directly leach lithium from α-phase spodumene. We find the H 2 O 2 promoter can significantly reduce the leaching potential by facilitating the electron transfer and changing the reaction path. Upon leaching, β-phase spodumene shows a typical phase transformation to HAlSi 2 O 6 , while leached α-phase remains its original crystal phase with a lattice shrinkage. To demonstrate the scale-up potential of electrochemical leaching, we design a catalyst-modified high-throughput current collector for high loading of suspended spodumene, achieving a leaching current of 18 mA and a leaching efficiency of 92.2%. Electrochemical leaching will revolutionize traditional leaching and recycling processes by minimizing the environmental footprint and energy consumption.

25 ENERGY STORAGE↗
DOE OSTI2025

Customizable wave tailoring nonlinear materials enabled by bilevel inverse design

Abstract Passive wave transformation via nonlinearity is ubiquitous in settings from acoustics to optics and electromagnetics. It is well known that different nonlinearities yield different effects on propagating signals, which raises the question of “what precise nonlinearity is the best for a given wave tailoring application?” In this work, considering a one-dimensional spring-mass chain connected by polynomial springs (a variant of the Fermi-Pasta-Ulam-Tsingou system), we introduce a bilevel inverse design method which couples the shape optimization of structures for tailored constitutive responses with reduced-order nonlinear dynamical inverse design. We apply it to two qualitatively distinct problems—minimization of peak transmitted kinetic energy from impact, and pulse shape transformation—demonstrating our method’s breadth of applicability. For the impact problem, we obtain two fundamental insights. First, small differences in nonlinearity can drastically change the dynamic response of the system, from severely under- to outperforming a comparative linear system. Second, the oft-used strategy of impact mitigation via “energy locking” bistability can be significantly outperformed by our optimal nonlinearity. We validate this case with impact experiments and find excellent agreement. This study establishes a framework for broader passive nonlinear mechanical wave tailoring material design, with applications to computing, signal processing, shock mitigation, and autonomous materials.

Science & Technology - Other Topics↗
DOE OSTI2024

Wind Turbine Design Optimization for Hydrogen Production

To help meet the need for inexpensive green fuels, we are working on wind turbine design optimization specifically for hydrogen production. We have thus far achieved a 1.53% decrease in LCOH as compared to a turbine optimized for LCOE using the same code, design variables, and models. We accomplished this by optimizing some components of the wind turbine tower, rotor, and drivetrain design with hydrogen production and costs in the design loop.

hydrogen↗
DOE OSTI2020

K-means-driven Gaussian Process data collection for angle-resolved photoemission spectroscopy

Abstract We propose the combination of k-means clustering with Gaussian Process (GP) regression in the analysis and exploration of 4D angle-resolved photoemission spectroscopy (ARPES) data. Using cluster labels as the driving metric on which the GP is trained, this method allows us to reconstruct the experimental phase diagram from as low as 12% of the original dataset size. In addition to the phase diagram, the GP is able to reconstruct spectra in energy-momentum space from this minimal set of data points. These findings suggest that this methodology can be used to improve the efficiency of ARPES data collection strategies for unknown samples. The practical feasibility of implementing this technology at a synchrotron beamline and the overall efficiency implications of this method are discussed with a view on enabling the collection of more samples or rapid identification of regions of interest.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Dynamical piezomagnetic effect in time-reversal-invariant Weyl semimetals with axionic charge density waves

Charge density waves (CDWs) in Weyl semimetals (WSMs) have been shown to induce an exotic axionic insulating phase in which the sliding mode (phason) of the CDW acts as a dynamical axion field, giving rise to a large positive magnetoconductance. In this work, we predict that dynamical strain can induce a bulk orbital magnetization in time-reversal (TR)-invariant WSMs that are gapped by a CDW. Here, we term this effect the “dynamical piezomagnetic effect” (DPME). Unlike in J. Gooth et al., the DPME introduced in this work occurs in a bulk-constant (i.e., static and spatially homogeneous in the bulk) CDW, and does not rely on fluctuations, such as a phason. By studying the low-energy effective theory and a minimal tight-binding (TB) model, we find that the DPME originates from an effective valley axion field that couples the electromagnetic gauge field with a strain-induced pseudogauge field. In particular, whereas the piezoelectric effects studied in previous works are characterized by 2D Berry curvature, the DPME represents the first example of a fundamentally 3D strain effect originating from the Chern-Simons 3-form. We further find that the DPME has a discontinuous change at a critical value of the phase of the CDW order parameter. We demonstrate that, when there is a jump in the DPME, the surface of the system undergoes a topological quantum phase transition (TQPT), while the bulk remains gapped. Hence, the DPME provides a bulk signature of the boundary TQPT in a TR-invariant Weyl CDW.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Superconducting diode effect in quasi-one-dimensional systems

The recent observations of the superconducting diode effect pose the challenge to fully understand the necessary ingredients for nonreciprocal phenomena in superconductors. In this theoretical work, we focus on the nonreciprocity of the critical current in a quasi-one-dimensional superconductor. We define the critical current as the value of the supercurrent at which the quasiparticle excitation gap closes (depairing). Once the critical current is exceeded, the quasiparticles can exchange energy with the superconducting condensate, giving rise to dissipation. Our minimal model can be microscopically derived as a low-energy limit of a Rashba spin-orbit coupled superconductor in a Zeeman field. Within the proposed model, we explore the nature of the nonreciprocal effects of the critical current both analytically and numerically. Further, our results quantify how system parameters such as spin-orbit coupling and quantum confinement affect the strength of the superconducting diode effect. Our theory provides a complementary description to Ginzburg-Landau theories of the effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector

A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz-boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used in high energy physics analyses. It uses minimally processed detector data as input and directly outputs particle properties of interest. The new technique is demonstrated for the reconstruction of the invariant mass of particles decaying in the CMS detector. The decay of a hypothetical scalar particle A into two photons, A → γ γ , is chosen as a benchmark decay. Lorentz boosts γ L = 60 – 600 are considered, ranging from regimes where both photons are resolved to those where the photons are closely merged as one object. A training method using domain continuation is introduced, enabling the invariant mass reconstruction of unresolved photon pairs in a novel way. The new technique is validated using π 0 → γ γ decays in LHC collision data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

EASY-SHIFT v Alpha

The software is a generic, price- and load-responsive control algorithm integrating heat pumps with thermal energy storage. The algorithm leverages simple models of the system and easily accessible data to schedule operation of heat pumps and thermal energy storage in ways that minimize the cost of operating the heating/cooling system. This tool is specifically designed to be easy to interact with, and something that industry partners are able to adopt. There are two current state of the art approaches. Industry tends to develop very simple algorithms, with predetermined schedules that are not capable of changing operation in response to changes in operating environment. For example, a control designed to avoid high-price electricity from 5-8 PM will not be able to adapt if the high-price period changes to 4-9 PM. Academia commonly develops algorithms called Model predictive control (MPC). MPC requires extensive data and highly trained staff to develop a specific type of simulation model of the building, connect the building to optimization algorithms, and leverage powerful computers. Industry, with limited time/finance budgets for any project, is resistant to adopting MPC due to the associated high complexity and cost.

Grant, Peter [Lawrence Berkeley National Laborator↗
DOE OSTI2021

Discrete modeling of a transformer with ALEGRA

We report progress on a task to model transformers in ALEGRA using the “Transient Magnetics” option. We specifically evaluate limits of the approach resolving individual coil wires. There are practical limits to the number of turns in a coil that can be numerically modeled, but calculated inductance can be scaled to the correct number of turns in a simple way. Our testing essentially confirmed this “turns scaling” hypothesis. We developed a conceptual transformer design, representative of practical designs of interest, and that focused our analysis. That design includes three coils wrapped around a rectangular ferromagnetic core. The secondary and tertiary coils have multiple layers. The tertiary has three layers of 13 turns each; the secondary has five layers of 44 turns; the primary has one layer of 20 turns. We validated the turns scaling of inductance for simple (one-layer) coils in air (no core) by comparison to available independent calculations for simple rectangular coils. These comparisons quantified the errors versus reduced number of turns modeled. For more than 3 turns, the errors are <5%. The magnetic field solver failed to converge (within 5000 iterations) for >10 turns. Including the core introduced some complications. It was necessary to capture the core surfaces in thin grid sheaths to minimize errors in computed magnetic energy. We do not yet have quantitative benchmarks with which to compare, but calculated results are qualitatively reasonable.

42 ENGINEERING↗