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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 379 records · Page 21

Twisted bilayer graphene as topological heavy fermion: II. Analytical approximations of the model parameters

The recently-introduced topological heavy fermion (THF) model [1] of twisted bilayer graphene (TBG) aims to reconcile the quantum-dot-like electronic structure of the latter observed by scanning tunneling microscopy, with its electron delocalization seen in transport measurements. The THF model achieves this by coupling localized (heavy) fermions with anomalous conduction electrons. Originally, the parameters of the THF model were obtained numerically from the Bistritzer–Macdonald (BM) model of TBG [1]. In this work, we derive analytical expressions for the THF model parameters as a function of the twist angle, the ratio between the tunneling amplitudes at the AA and AB regions (w 0 /w 1 ), and the screening length of the interaction potential. By numerically computing the THF model parameters across an extensive experimentally-relevant parameter space, we show that the resulting approximations are remarkably good, i.e., within the 30% relative error for almost the entire parameter space. At the single-particle level, the THF model accurately captures the energy spectrum of the BM model over a large phase space of angles and tunneling amplitude ratios. When interactions are included, we also show that the THF description of TBG is good around the magic angle for realistic values of the tunneling amplitude ratios (0.6 ≤ w 0 /w 1 ≤ 1.0), for which the hybridization between the localized and conduction fermions γ is smaller than the onsite repulsion of the heavy fermions U 1 (i.e., |γ| < U 1 ).

Approximation methods↗

Cryo-EM sample preparation for high-resolution structure studies

High-resolution structures of biomolecules can be obtained using single-particle cryo-electron microscopy (SPA cryo-EM), and the rapidly growing number of structures solved by this method is encouraging more researchers to utilize this technique. As with other structural biology methods, sample preparation for an SPA cryo-EM data collection requires some expertise and an understanding of the strengths and limitations of the technique in order to make sensible decisions in the sample-preparation process. Here, in this article, common strategies and pitfalls are described and practical advice is given to increase the chances of success when starting an SPA cryo-EM project.

36 MATERIALS SCIENCE↗

A control oriented comprehensive degradation model for battery energy storage system life prediction

In order to ensure that stationary battery energy storage systems (BESSs) provide reliable energy buffering, both for power quality and economic purposes, the degradation must be considered. Cell degradation involves various side reactions and is highly dependent on its operating conditions. To accurately track cell degradation and predict its impact on battery behavior, a comprehensive physics-based degradation model based on an electrolyte phase-enhanced single particle (SP) model is developed. Key degradation physics, namely solid electrolyte interphase (SEI) layer formation and growth, Li plating on the graphite anode, and Mn dissolution on cathode of nickel-cobalt-manganese oxide (NMC622) are considered. The model is validated against experimental capacity data. The results reveal that the deposition rate of both SEI layer and Li metal increase as the charge voltage increases. At the cathode side, the solvent oxidation rate determines the Mn dissolution rate. As a result, the volume fraction of NMC622 in the cathode continually decreases at a gradually increasing rate.

25 ENERGY STORAGE↗

Structure of the Human BK Ion Channel in Lipid Environment

Voltage-gated and ligand-modulated ion channels play critical roles in excitable cells. To understand the interplay among voltage sensing, ligand binding, and channel opening, the structures of ion channels in various functional states and in lipid membrane environments need to be determined. Here, the random spherically constrained (RSC) single-particle cryo-EM method was employed to study human large conductance voltage- and calcium-activated potassium (hBK or hSlo1) channels reconstituted into liposomes. The hBK structure was determined at 3.5 Å resolution in the absence of Ca 2+ . Instead of the common fourfold symmetry observed in ligand-modulated ion channels, a twofold symmetry was observed in hBK in liposomes. Compared with the structure of isolated hSlo1 Ca 2+ sensing gating rings, two opposing subunits in hBK unfurled, resulting in a wider opening towards the transmembrane region of hBK. In the pore gate domain, two opposing subunits also moved downwards relative to the two other subunits.

59 BASIC BIOLOGICAL SCIENCES↗

Resolving Nonequilibrium Shape Variations among Millions of Gold Nanoparticles

Nanoparticles, exhibiting functionally relevant structural heterogeneity, are at the forefront of cutting-edge research. Now, high-throughput single-particle imaging (SPI) with X-ray free-electron lasers (XFELs) creates opportunities for recovering the shape distributions of millions of particles that exhibit functionally relevant structural heterogeneity. To realize this potential, three challenges have to be overcome: (1) simultaneous parametrization of structural variability in real and reciprocal spaces; (2) efficiently inferring the latent parameters of each SPI measurement; (3) scaling up comparisons between 10 5 structural models and 10 6 XFEL-SPI measurements. Here, we describe how we overcame these three challenges to resolve the nonequilibrium shape distributions within millions of gold nanoparticles imaged at the European XFEL. These shape distributions allowed us to quantify the degree of asymmetry in these particles, discover a relatively stable “shape envelope” among nanoparticles, discern finite-size effects related to shape-controlling surfactants, and extrapolate nanoparticles’ shapes to their idealized thermodynamic limit. Ultimately, these demonstrations show that XFEL SPI can help transform nanoparticle shape characterization from anecdotally interesting to statistically meaningful.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhanced beam-beam modeling to include longitudinal variation during weak-strong simulation

Beam-beam interactions pose substantial challenges in the design and operation of circular colliders, significantly affecting their performance. In particular, the weak-strong simulation approach is pivotal for investigating single-particle dynamics during the collider design phase. This paper evaluates the limitations of existing models in weak-strong simulations, noting that while they accurately account for energy changes due to slingshot effects, they fail to incorporate longitudinal coordinate changes ( z variation). To address this gap, we introduce two novel transformations that enhance Hirata’s original framework by including both z variation and slingshot effect-induced energy changes. Through rigorous mathematical analysis and extensive weak-strong simulation studies, we validate the efficacy of these enhancements in achieving a more precise simulation of beam-beam interactions. Our results reveal that although z variation constitutes a higher-order effect and does not substantially affect the emittance growth rate within the specific design parameters of the Electron-Ion Collider, the refined model offers improved accuracy, particularly in scenarios involving the interaction between beam-beam effects and other random diffusion processes, as well as in simulations incorporating realistic lattice models. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

ExaFEL: extreme-scale real-time data processing for X-ray free electron laser science

ExaFEL is an HPC-capable X-ray Free Electron Laser (XFEL) data analysis software suite for both Serial Femtosecond Crystallography (SFX) and Single Particle Imaging (SPI) developed in collaboration with the Linac Coherent Lightsource (LCLS), Lawrence Berkeley National Laboratory (LBNL) and Los Alamos National Laboratory. ExaFEL supports real-time data analysis via a cross-facility workflow spanning LCLS and HPC centers such as NERSC and OLCF. Our work therefore constitutes initial path-finding for the US Department of Energy's (DOE) Integrated Research Infrastructure (IRI) program. We present the ExaFEL team's 7 years of experience in developing real-time XFEL data analysis software for the DOE's exascale supercomputers. We present our experiences and lessons learned with the Perlmutter and Frontier supercomputers. Furthermore we outline essential data center services (and the implications for institutional policy) required for real-time data analysis. Finally we summarize our software and performance engineering approaches and our experiences with NERSC's Perlmutter and OLCF's Frontier systems. This work is intended to be a practical blueprint for similar efforts in integrating exascale compute resources into other cross-facility workflows.

59 BASIC BIOLOGICAL SCIENCES↗

Southern California Megacity CO2, CH4, and CO Flux Estimates Using Ground- and Space-Based Remote Sensing and a Lagrangian Model

We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the So-CAB to be 104±26 Tg CO2 yr(exp -1) for the study period of July 2013–August 2016. We obtain a slightly higher estimate of 120±30 Tg CO2 yr(exp -1) using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360±90 Gg CH4 y(exp -1)) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342–440 Gg CH4 yr(exp -1)). CO emissions are estimated at 487±122 Gg CO yr(exp -1), much lower than previous top-down estimates (1440 Gg CO yr(exp -1)). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25%, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.

Total Carbon Column Observing Network (TCCON)↗

Community recommendations on cryoEM data archiving and validation

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry

NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum (Sorghum bicolor), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.

09 BIOMASS FUELS↗

Impact of particle arrays on phase separation composition patterns

We examine the symmetry-breaking effect of fixed constellations of particles on the surface-directed spinodal decomposition of binary blends in the presence of particles whose surfaces have a preferential affinity for one of the components. Our phase-field simulations indicate that the phase separation morphology in the presence of particle arrays can be tuned to have a continuous, droplet, lamellar, or hybrid morphology depending on the interparticle spacing, blend composition, and time. In particular, when the interparticle spacing is large compared to the spinodal wavelength, a transient target pattern composed of alternate rings of preferred and non-preferred phases emerges at early times, tending to adopt the symmetry of the particle configuration. We reveal that such target patterns stabilize for certain characteristic length, time, and composition scales characteristic of the pure phase-separating mixture. To illustrate the general range of phenomena exhibited by mixture-particle systems, we simulate the effects of single-particle, multi-particle, and cluster–particle systems having multiple geometrical configurations of the particle characteristic of pattern substrates on phase separation. Our simulations show that tailoring the particle configuration, or substrate pattern configuration, a relative fluid-particle composition should allow the desirable control of the phase separation morphology as in block copolymer materials, but where the scales accessible to this approach of organizing phase-separated fluids usually are significantly larger. Limited experiments confirm the trends observed in our simulations, which should provide some guidance in engineering patterned blend and other mixtures of technological interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chaotic Dynamics Driven by Particle-Core Interactions

High-intensity beams in modern linacs are frequently encircled by diffuse halos, which drive sustained particle losses and result in gradual degradation of accelerating structures. In large part, the growth of halos is facilitated by internal space-charge forces within the beams, and detailed characterization of this process constitutes an active area of ongoing research. A partial understanding of dynamics that ensue within space-charge dominated beams is presented by the particle-core interaction paradigm – a mathematical model wherein single particle dynamics, subject to the collective potential of the core, are treated as a proxy for the broader behavior of the beam. In this work, we investigate the conditions for the onset of large-scale chaos within the framework of this model, and demonstrate that the propensity towards stochastic evolution is strongly dependent upon the charge distribution of the beam. In particular, we show that while particle motion within a uniformly charged beam is dominantly regular, rapid deterministic chaos readily arises within space-charge dominated Gaussian beams. Importantly, we find that for sufficiently high values of the beam’s space charge and beam pulsation amplitude, enhanced chaotic mixing between the core and the halo can lead to an enhanced radial diffusion of charged particles. We explain our results from analytic grounds by demonstrating that chaotic motion is driven by the intersection of two principal resonances of the system, and derive the relevant overlap conditions. Additionally, our analysis illuminates a close connection between the mathematical formulation of the particle-core interaction model and the Andoyer family of integrable Hamiltonians

43 PARTICLE ACCELERATORS↗

Data for Influence of Particle Size on NIR Spectroscopic Characterization of Sorghum Biomass for the Biofuel Industry

NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum ( Sorghum bicolor ), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.

Biomass Analytics↗

Scaling and Single Event Effects (SEE) Sensitivity

This paper begins by discussing the potential for scaling down transistors and other components to fit more of them on chips in order to increasing computer processing speed. It also addresses technical challenges to further scaling. Components have been scaled down enough to allow single particles to have an effect, known as a Single Event Effect (SEE). This paper explores the relationship between scaling and the following SEEs: Single Event Upsets (SEU) on DRAMs and SRAMs, Latch-up, Snap-back, Single Event Burnout (SEB), Single Event Gate Rupture (SEGR), and Ion-induced soft breakdown (SBD).

Oldham, Timothy R.↗

On Characterizing Particle Shape

It is well known that particle shape affects flow characteristics of granular materials, as well as a variety of other solids processing issues such as compaction, rheology, filtration and other two-phase flow problems. The impact of shape crosses many diverse and commercially important applications, including pharmaceuticals, civil engineering, metallurgy, health, and food processing. Two applications studied here include the dry solids flow of lunar simulants (e.g. JSC-1, NU-LHT-2M, OB-1), and the flow properties of wet concrete, including final compressive strength. A multi-dimensional generalized, engineering method to quantitatively characterize particle shapes has been developed, applicable to both single particle orientation and multi-particle assemblies. The two-dimension, three dimension inversion problem is also treated, and the application of these methods to DEM model particles will be discussed. In the case of lunar simulants, flow properties of six lunar simulants have been measured, and the impact of particle shape on flowability - as characterized by the shape method developed here -- is discussed, especially in the context of three simulants of similar size range. In the context of concrete processing, concrete construction is a major contributor to greenhouse gas production, of which the major contributor is cement binding loading. Any optimization in concrete rheology and packing that can reduce cement loading and improve strength loading can also reduce currently required construction safety factors. The characterization approach here is also demonstrated for the impact of rock aggregate shape on concrete slump rheology and dry compressive strength.

Ennis, Bryan J.↗

Derivation of Physical and Optical Properties of Midlatitude Cirrus Ice Crystals for a Size-Resolved Cloud Microphysics Model

Single-crystal images collected in mid-latitude cirrus are analyzed to provide internally consistent ice physical and optical properties for a size-resolved cloud microphysics model, including single-particle mass, projected area, fall speed, capacitance, single-scattering albedo, and asymmetry parameter. Using measurements gathered during two flights through a widespread synoptic cirrus shield, bullet rosettes are found to be the dominant identifiable habit among ice crystals with maximum dimension (Dmax) greater than 100μm. Properties are therefore first derived for bullet rosettes based on measurements of arm lengths and widths, then for aggregates of bullet rosettes and for unclassified (irregular) crystals. Derived bullet rosette masses are substantially greater than reported in existing literature, whereas measured projected areas are similar or lesser, resulting in factors of 1.5-2 greater fall speeds, and, in the limit of large Dmax, near-infrared single-scattering albedo and asymmetry parameter (g) greater by approx. 0.2 and 0.05, respectively. A model that includes commonly imaged side plane growth on bullet rosettes exhibits relatively little difference in microphysical and optical properties aside from approx. 0:05 increase in mid-visible g primarily attributable to plate aspect ratio. In parcel simulations, ice size distribution, and g are sensitive to assumed ice properties.

asymmetry↗

GEN3D Experimental and Numerical Development of GEN3 Durability Models

Understanding of the high temperature durability of particles and the materials that contain them is critical to next generation of concentrating solar power (CSP) technology. Here we studied the durability of particles and their containment materials under extreme UV cycling, thermal cycling, and in low-speed high temperature mechanical wear situations. The optical stability of seven candidate particles has been determined following exposure to the high temperature conditions present in a generation 3 particle-based CSP technology. Particle solar weighted absorptance and emittance measured periodically during 10,000 high solar irradiance exposure cycles and up to 400 hours of isothermal aging has been documented. The particle aging due to repeated exposure to concentrated solar flux represented the 30-year lifetime of a power plant. Models were fit to the absorptivity and emissivity data following the isothermal aging provides the projected optical degradation of the particles as a function of temperature. Mechanical wear was studied through the use of custom developed wear testing facilities for measuring high temperature impact wear, abrasion wear, and particle attrition. Additionally, a novel technique for measuring the high temperature mechanical properties of single particles was developed. Through these tests it was observed that high nickel alloys generally showed lower wear than comparable iron based steels, particularly at elevated temperatures of 800°C. Mechanical wear at these temperatures is a highly complex phenomenon combining both mechanical wear and oxidation. Additionally, the containment materials wear rates are influenced by the particles (both hardness and roundness), making the wear mechanisms complex. The initial wear test conducted in the abrasion test rig revealed a substantial amount of oxide materials in the particle bed after testing (in relative to later tests), and substantially more wear, likely indicating a need for concern in startup operation of particle facilities to not incur high wear from the presence of oxides. Particle attrition experiments have only been conducted for a single material but increase size distribution, reduction in circularity, and particle diameter is observed. Efforts to develop predictive models was limited due to a testing campaign that prioritized testing materials for particle pathway developers over building a comprehensive design of experiments. The results discussed in this report inform future CSP developers and researchers further de risking the technology and assisting in its future development. ParticleBased CSP development provides a path to dispatchable solar power generation with storage at a price competitive in the current energy market. Lowering the cost of CSP technology provides a carbon free power generation solution that can assist in the transition from fossil fuels to renewable sources of electricity.

14 SOLAR ENERGY↗

Single Event Rates for Devices Sensitive to Particle Energy

Single event rates (SER) can include contributions from low-energy particles such that the linear energy transfer (LET) is not constant. Previous work found that the environmental description that is most relevant to the low-energy contribution to the rate is a "stopping rate per unit volume" even when the physical mechanisms for a single-event effect do not require an ion to stop in some device region. Stopping rate tables are presented for four heavy-ion environments that are commonly used to assess device suitability for space applications. A conservative rate estimate utilizing limited test data is derived, and the example of SEGR rate in a power MOSFET is presented.

conservative rate↗