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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 451 records · Page 25

Combustion characteristics of diisopropoxymethane, a low-reactivity oxymethylene ether

Oxymethylene ethers (OMEs) have been studied for use as low-sooting diesel fuel additives or substitutes; very little literature discusses OMEs as spark-ignition (SI) fuels due to their typically high cetane numbers. In this work, a lower-reactivity, branched OME, diisopropoxymethane (DIPM), is evaluated to determine its effectiveness as a spark-ignition fuel, as it is the lowest-reactivity OME (as determined by Indicated Cetane Number) thus far evaluated in the literature. DIPM is synthesized in-house via acetalization from isopropanol (iPrOH) and trioxane using standard OME production practices. DIPM was then tested in a rapid compression machine (RCM) for autoignition and spark ignition characteristics, and in a modified CFR engine to determine effective octane numbers. In the RCM, an autoignition temperature sweep was performed at stoichiometric conditions from 1000/T = 1.7 - 1.0, at 5:1 inert ratio (comparable to approximately 25% EGR), where it was found that DIPM has ignition delay times 5–10x faster than isooctane and displays NTC ignition behavior. Blends with iPrOH indicate that reactivity can be matched with isooctane with low blend ratios of iPrOH in DIPM. Flame speeds were tested with a laser spark for ignition in the RCM, where the flame speed of DIPM and isooctane is determined to be comparable at engine relevant conditions. In the CFR engine, effective RON and MON based on pressure trace frequency domain measurements were determined for DIPM and a 15 vol% iPrOH in DIPM blend. Neat DIPM has (R+M)/2 = 59 and a negative sensitivity of S = -18, consistent with its NTC behavior and higher reactivity. Furthermore the DIPM/iPrOH blend has positive sensitivity and a pump-gasoline range (R+M)/2 = 89.3. DIPM on its own is unlikely to be an effective SI fuel, however, when blended with iPrOH as an ON booster, it may be a promising SI candidate fuel.

09 BIOMASS FUELS↗

Implosion simulations and optimum times of radiographic Images in OMEGA high-density-carbon cylinder experiments

The Los Alamos Ignition Threshold team is planning direct-drive cylinder implosion experiments (CylDRT24B) at the OMEGA laser, scheduled for Thursday 23 May 2024, to investigate the effect of granular microstructure in high density carbon (HDC) shells. Granular microstructure is believed to play a crucial role in seeding perturbations, reducing compression, and enhancing mix in the implosion of HDC shells at the National Ignition Facility (NIF). But the ICF community lacks a detailed understanding of how grains induce these effects, owing partly to the practical difficulty of numerically simulating the behavior of tiny nanometer-scale granular structures in laboratory-scale experiments. Our planned experiments are aimed at acquiring data to help constrain simulations and calibrate reduced models.

36 MATERIALS SCIENCE↗

Renormalization of states and quasiparticles in many-body downfolding

We explore the principles of many-body Hamiltonian complexity reduction via downfolding on an effective low-dimensional representation. We show that the renormalization factor provides a unique measure of the quality of the compression as it directly represents the projection between the approximate stationary state of the many-body Hamiltonian and the full many-body wavefunction. Hence, the renormalization factor is a measure of fidelity between the effective (reduced-rank) description and the full many-body treatment for arbitrary (i.e., ground and excited) states. When the entire problem is mapped on a system of interacting quasiparticles [Romanova et al., npj Comput. Mater. 9, 126 (2023)], the effective Hamiltonians can faithfully reproduce the physics only when a clear energy scale separation exists between the subsystems and their environment. We also demonstrate that it is necessary to include quasiparticle renormalization at distinct energy scales, capturing the distinct interaction between subsystems and their surrounding environments. Numerical results from simple, exactly solvable models highlight the limitations and strengths of this approach, particularly for ground and low-lying excited states. This work lays the groundwork for applying dynamical downfolding techniques to problems concerned with (quantum) interfaces.

Green-functions technique↗

Cu- and Zn-doped alkali activated mortar – Properties and durability in (bio)chemically aggressive wastewater environments

Metakaolin-based alkali activated mortars (AAM) - with and without CuSO{sub 4}·5H{sub 2}O and ZnO addition (mass ratio M{sup n+}/solid binder 0.08% to 1.7%) - were casted and exposed within an extensive long-term field campaign over the period of 20 months to a sewer basin, strongly affected by biogenic acid corrosion. (Un-)exposed AAM were tested regarding their physicochemical and microstructural properties, bioreceptivity and overall durability. Metal addition led to a retarding effect during alkali-activation reaction, as well as to an increase in open porosity of up to 3.0% and corresponding lower compressive strength of up to 10.9%. Reduced microbial colonization and diversity were observed on AAM with Cu, while Zn addition led to increased biodiversity. We propose that the observed higher durability of Cu-doped AAM is due to antibacterial effects and associated reduction of biogenic acid production, superseding overall negative effects of metal-dosage on physical material properties. Observed lower durability of Zn-doped AAM was related to combined negative physicochemical and microbial effects.

36 MATERIALS SCIENCE↗

Monodomain Liquid‐Crystal Elastomer Lattices for Broad Strain‐Rate Mechanical Damping

Designing structures that effectively dissipate energy across a broad range of mechanical loading rates, including those from compression, shock, and vibration, poses a significant engineering challenge. In this study, liquid‐crystal elastomers (LCEs), which possess anisotropic properties due to the alignment of their polymer backbone, are explored. As a result, LCEs exhibit a soft elastic response under mechanical loading, making them ideal for energy dissipation. Advances in additive manufacturing (AM) enable simple fabrication of foamlike dissipative structures with complex lattice geometries. Herein, direct ink write 3D printing, an extrusion AM method, is used to fabricate aligned, monodomain LCE lattice structures for broad strain‐rate mechanical damping. In this work, it is shown that these structures can dissipate strain energy in quasi‐static environments, comparable to traditional elastomeric lattices, and provide improved damping under high strain‐rate drop testing due to LCE soft elasticity. Additionally, under dynamic mechanical vibration, monodomain LCE lattices enhance damping at structural natural frequencies and provide high‐frequency attenuation. Finally, in these findings, a promising method is presented for fabricating mechanical damping devices that effectively dissipate energy across a broad range of loading rates.

3D printings↗

Quantum mixed state compiling

The task of learning a quantum circuit to prepare a given mixed state is a fundamental quantum subroutine. We present a variational quantum algorithm (VQA) to learn mixed states which is suitable for near-term hardware. Our algorithm represents a generalization of previous VQAs that aimed at learning preparation circuits for pure states. We consider two different ansätze for compiling the target state; the first is based on learning a purification of the state and the second on representing it as a convex combination of pure states. In both cases, the resources required to store and manipulate the compiled state grow with the rank of the approximation. Thus, by learning a lower rank approximation of the target state, our algorithm provides a means of compressing a state for more efficient processing. As a byproduct of our algorithm, one effectively learns the principal components of the target state, and hence our algorithm further provides a new method for principal component analysis. We investigate the efficacy of our algorithm through extensive numerical implementations, showing that typical random states and thermal states of many body systems may be learnt this way. Additionally, we demonstrate on quantum hardware how our algorithm can be used to study hardware noise-induced states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Design and modeling of indirectly driven magnetized implosions on the NIF

The use of magnetic fields to improve the performance of hohlraum-driven implosions on the National Ignition Facility (NIF) is discussed. The focus is on magnetically insulated inertial confinement fusion, where the primary field effect is to reduce electron-thermal and alpha-particle loss from the compressed hotspot (magnetic pressure is of secondary importance). We summarize the requirements to achieve this state. The design of recent NIF magnetized hohlraum experiments is presented. These are close to earlier shots in the three-shock, high-adiabat (BigFoot) campaign, subject to the constraints that magnetized NIF targets must be fielded at room-temperature, and use ≲1 MJ of laser energy to avoid the risk of optics damage from stimulated Brillouin scattering. We present results from the original magnetized hohlraum platform, as well as a later variant that gives a higher hotspot temperature. In both platforms, imposed fields (at the capsule center) of up to 28 T increase the fusion yield and hotspot temperature. Integrated radiation-magneto-hydrodynamic modeling with the Lasnex code of these shots is shown, where laser power multipliers and a saturation clamp on cross-beam energy transfer are developed to match the time of peak capsule emission and the P2 Legendre moment of the hotspot x-ray image. The resulting fusion yield and ion temperature agree decently with the measured relative effects of the field, although the absolute simulated yields are higher than the data by 2.0−2.7×. The tuned parameters and yield discrepancy are comparable for experiments with and without an imposed field, indicating the model adequately captures the field effects. Self-generated and imposed fields are added sequentially to simulations of one BigFoot NIF shot to understand how they alter target dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Desalination metamodels and a framework for cross-comparative performance simulations

There is an opportunity to save energy and reduce operational expenses when choosing a suitable desalination method aided by computational modeling. Existing models are not conducive to generalized comparisons between different desalination methods. Therefore, the work in this study developed metamodels for six desalination methods, grouped them into thermal and molecular transport families, and validated their predictive performance within 9% difference from published data. This validated framework allowed comparisons of desalination methods at their prescribed ranges of operational conditions that they were designed for. These conditions specify feed salinity ranges of 1.6 to 2.4 g/kg for Capacitive Deionization and Reverse Osmosis (RO), 2.8 to 4.2 g/kg for Electrodialysis, 28 to 42 g/kg for Thermovapor Compression and Humidification-Dehumidification, and 37 to 55 g/kg for Multi-Effect Distillation (MED). Despite different operational conditions, all models exhibit non-linear, positive correlation between energy consumption and system size in response to feed salinity and production rate. The framework is also employed in a cross-comparative analysis between MED and RO whose results suggest that energy intensity for MED is an order of magnitude greater than RO for the same operational conditions, but actual operational costs are comparable. Overall, the framework is ready for deployment in case studies of actual desalination plants.

42 ENGINEERING↗

A physics informed model for the prediction of surface energies and the shape of metal particles

Surface energies of metal-based systems are important for determining the Wulff-constructed shapes of metal nanoparticles and understanding the stability. We have developed a physics informed method to predict the total energy of metal-based systems across a wide range of configurations. Our method has been tested against density functional theory (DFT) calculations for late transition metals. This method enables on-the-fly surface energy predictions based on the fundamental of materials property and allows for the Wulff construction of metal particles for a random number of elemental atoms and without the need for DFT calculations. By making a division between atoms in the different layers of the model system, we can improve the accuracy of the model, suggesting a dissimilarity between the electronic structure due to an alternating compression and expansion of atomic layers. We find that our model accurately and effectively provides valuable insights into the distribution and stability of nanoparticles.

Mandal, Shyama Charan (ORCID:0000000245882874)↗

Electronic structure and magnetism of pristine, defected, and strained $\mathrm{Ti_2N}$ $\mathrm{MX}$ene

Here, from first principles electronic structure calculations, we unravel the evolution of structural, electronic, and magnetic properties of pristine, defected, and strained titanium nitride MXene with different functional groups (-F, -O, -H, and -OH). The formation and cohesive energies reveal their chemical stability. The dynamical stability of Ti 2 N mono-layer is also confirmed by phonon calculations. The MAX phase and defect free functionalized MXenes are metallic except for oxygen terminated (Ti 2 NO 2 ) one which is 100% spin polarized half-metallic ferromagnet. The spin–orbit coupling significantly influences the bare MXene (Ti 2 N) to exhibit Dirac topology and band inversion near the high symmetry directions. The strain effect sways the Fermi level thereby shifting it towards lower energy state under compression and towards higher energy state under tensile strain in Ti 2 NH 2 . The Ti 2 NO 2 exhibits exotic electronic structure not only in pristine but also in strained and defected structures. Its half-metallic nature changes to semi-metallic under 1% compression and it is completely destroyed under 2% compression. In single vacancy defect, its band structure remarkably transforms from half-metallic to semi-conducting with large band gap in 12.5% Ti, weakly semi-conducting in 5.5% Ti, and semi-metallic in 12.5% O. The 25% N defect changes its half-metallic characteristic to metallic. Further, the 12.5% Co substitution preserves its half-metallic character, whereas Mn substitution allows it to convert half-metallic characteristic into weak semi-metallic characteristic preserving ferromagnetism. However, Cr substitution converts half-metallic ferromagnetic state to half-metallic anti-ferromagnetic state. The understanding made here on collective structural stability, and electronic band structure, and magnetic phenomena in novel 2D Ti 2 N derived MXenes open up their possibility in designing them for synthesis.

36 MATERIALS SCIENCE↗

Crystal plasticity modeling for the strengthening effect of multilayered copper–graphene nanocomposites

The paper explores plastic deformation mechanisms in metal–graphene nanocomposites, illustrating their material strengthening effects through a crystal plasticity finite element (CPFE) model. This model is compared with published experimental results, which have previously shown that the two-dimensional shape of graphene effectively controls dislocation motion and significantly enhances the strength of metals. Simulated nanopillar compression tests, using a physics-based CP model that incorporates surface nucleation and single-arm source dislocation mechanisms, help us understand dislocation motions at submicron length scales. The crystal plasticity models are applied to nanolayered composites with copper grain layers and monolayer graphene, featuring repeat layer spacings of 200 nm, 125 nm, and 70 nm, respectively. This study quantifies the accumulation of dislocations at the graphene interfaces, contributing to the ultra-high strength of copper–graphene composites. Furthermore, a Hall–Petch-like correlation is established between yield strength and the number of embedded graphene layers.

36 MATERIALS SCIENCE↗

Reviving the rock-salt phases in Ni-rich layered cathodes by mechano-electrochemistry in all-solid-state batteries

The rock-salt phase (RSP) formed on the surface of Ni-rich layered cathodes in liquid-electrolyte lithium-ion batteries is conceived to be electrochemically "dead". Here we show massive RSP forms in the interior of LiNi x Mn y Co (1–x-y) O 2 (NMC) crystals in sulfide based all solid state batteries (ASSBs), but the RSP remains electrochemically active even after long cycles. The RSP and the layered structure constitute a two-phase mixture, a material architecture that is distinctly different from the RSP in liquid electrolytes. The tensioned layered phase affords an effective percolation channel into which lithium is squeezed out of the RSPs by compressive stress, rendering the RSPs electrochemically active. Consequently, the ASSBs with predominant RSP in the NMC cathode deliver remarkable long cycle life of 4000 cycles at high areal capacity of 4.3 mAh/cm 2 . Our study unveils distinct mechano-electrochemistry of RSPs in ASSBs that can be harnessed to enable high energy density and durable ASSBs.

25 ENERGY STORAGE↗

Calibrating a finite-strain phase-field model of fracture for bonded granular materials with uncertainty quantification

To study the mechanical behavior of mock high explosives, an experimental and simulation program was developed to calibrate, with quantified uncertainty, a material model of the bonded granular material Idoxuridine and nitroplasticized Estane-5703. This paper reports on the efficacy of such a framework as a generalizable methodology for calibrating material models against experimental data with uncertainty quantification. Additionally, this paper studies the effect of two manufacturing temperatures and three initial granular configurations on the unconfined compressive behavior of the resulting bonded granular materials. In each of these cases, the same calibration framework was used; in that, hundreds of high-fidelity direct numerical simulations using a new, graphics processing unit-enabled, high-performance finite element method software, Ratel, were run to calibrate a finite-strain phase-field fracture model against experimental data. It was found that manufacturing temperature influenced the elastic response of the mock high explosives, with higher temperatures yielding a stiffer response. By contrast, it was found that the initial configuration of the grains had a negligible impact on the overall behavior of the mock high explosives though it remains possible that local damage accumulation within the specimens could be altered by the initial configurations. Overall, the calibration framework was successful at creating well-calibrated models, showing its usefulness as an engineering and scientific tool.

36 MATERIALS SCIENCE↗

Hydrogen storage in liquid hydrogen carriers: recent activities and new trends

Abstract Efficient storage of hydrogen is one of the biggest challenges towards a potential hydrogen economy. Hydrogen storage in liquid carriers is an attractive alternative to compression or liquefaction at low temperatures. Liquid carriers can be stored cost-effectively and transportation and distribution can be integrated into existing infrastructures. The development of efficient liquid carriers is part of the work of the International Energy Agency Task 40: Hydrogen-Based Energy Storage. Here, we report the state-of-the-art for ammonia and closed CO 2 -cycle methanol-based storage options as well for liquid organic hydrogen carriers.

08 HYDROGEN↗

Visualization Quality Assessment

Understanding how inaccuracies in visualizations affect users’ perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on “natural images” rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies. The goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images.

Grosset, Andre↗

Characterization of textile-grade carbon fiber polypropylene composites

In this work, we consider low-cost carbon fiber produced with a textile-grade precursor. The objective of the study is to investigate textile-grade carbon-fiber-reinforced-polypropylene composites (TCF-PP) from compounded pellets for mechanical and thermal characterization. Four sets of pellets with 1%, 5%, 10%, and 15% reinforcement were manufactured using textile-grade carbon fiber (TCF) and polypropylene (PP) by twin-screw compounding. The addition of TCFs through gravimetric feeder directly in the extruder resulted in lower fiber content; however, side feeder has shown good potential. The pellets were further processed in extrusion compression molding to manufacture plaques. An increase in fiber loading has a negligible effect on fiber attrition as fiber length distribution variation between 1% and 15% reinforced pellets was very small. The addition of TCFs in PP showed a significant improvement in mechanical properties. The tensile strength and modulus of the composite were 26% and 161%, respectively, improved by the addition of 10 wt% TCF. Similar results were observed in the flexure test. However, the impact properties were reduced by 25.54% by the addition of 15% TCF.

36 MATERIALS SCIENCE↗