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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Experimental evidence for the two-path description of neutron spin echo

Here, we describe an experiment that strongly supports a two-path interferometric model in which the spin-up and spin-down components of each neutron propagate coherently along spatially separated parallel paths in a typical neutron spin-echo small-angle scattering (SESANS) experiment. Specifically, we show that the usual semi-classical, single-path treatment of Larmor precession of a polarized neutron in an external magnetic field predicts a damping as a function of the spin-echo length of the SESANS signal obtained with a periodic phase grating when the transverse width of the neutron wave packet is finite. However, no such damping is observed experimentally, implying either that the Larmor model is incorrect or that the transverse extent of the wave packet is very large. In contrast, we demonstrate theoretically that a quantum-mechanical interferometric model in which the two mode-entangled (i.e., intraparticle entangled) spin states of a single neutron are separated in space when they interact with the grating accurately predicts the measured SESANS signal, which is independent of the wave packet width.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Implementation of a self-consistent slab model of bilayer structure in the SasView suite

Slab models are simple and useful structural descriptions which have long been used to describe lyotropic lamellar phases, such as lipid bilayers. Typically, slab models assume a midline symmetry and break a bilayer structure into three pieces, a central solvent-free core and two symmetric outer layers composed of the soluble portion of the amphiphile and associated solvent. This breakdown matches reasonably well to the distribution of neutron scattering length density and therefore is a convenient and common approach for the treatment of small-angle scattering data. Here, an implementation of this model within the SasView software suite is reported. The implementation is intended to provide physical consistency through the area per amphiphile molecule and number of solvent molecules included within the solvent-exposed outer layer. The proper use of this model requires knowledge of (or good estimates for) the amphiphile and solvent molecule volume and atomic composition, ultimately providing a self-consistent data treatment with only two free parameters: the lateral area per amphiphile molecule and the number of solvent molecules included in the outer region per amphiphile molecule. Here, the use of this code is demonstrated in the fitting of standard lipid bilayer data sets, obtaining structural parameters consistent with prior literature and illustrating the typical and ideal cases of fitting for neutron scattering data obtained using single or multiple contrast conditions. While demonstrated here for lipid bilayers, this model is intended for general application to block copolymers, surfactants, and other lyotropic lamellar phase structures for which a slab model is able to reasonably estimate the neutron scattering length density/electron-density profile of inner and outer layers of the lamellae.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Scale filtering analysis of kinetic reconnection and its associated turbulence

Previously, using an incompressible von Kármán–Howarth formalism, the behavior of cross-scale energy transfer in magnetic reconnection and turbulence was found to be essentially identical to each other, independent of an external magnetic (guide) field, in the inertial and energy-containing ranges [Adhikari et al., Phys. Plasmas 30, 082904 (2023)]. However, this description did not account for the energy transfer in the dissipation range for kinetic plasmas. In this Letter, we adopt a scale-filtering approach to investigate this previously unaccounted-for energy transfer channel in reconnection. Using kinetic particle-in-cell simulations of antiparallel and component reconnection, we show that the pressure–strain interaction becomes important at scales smaller than the ion inertial length, where the nonlinear energy transfer term drops off. Also, the presence of a guide field makes a significant difference in the morphology of the scale-filtered energy transfer. These results are consistent with kinetic turbulence simulations, suggesting that the pressure strain interaction is the dominant energy transfer channel between electron scales and ion scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Optimal binning of correlated measurements

Experimental measurements are commonly represented on a discrete grid, requiring a balance between granularity and statistical noise. Two strategies have traditionally been used to improve such representations: selecting an appropriate bin width to control discretization error and applying kernel-based smoothing to suppress fluctuations. Despite their shared goal, these approaches have largely developed independently, without a unified statistical description of how discretization and correlation jointly determine measurement precision. Here, we extend the discussion of optimal interval averaging to a correlation-aware setting by Gaussian process regression, which explicitly accounts for correlations among neighboring bins. Starting from first principles, we derive the mean-squared error of discretized measurements and obtain closed-form asymptotic expressions for the optimal bin width and correlation length. When recast in reduced variables, the theory reveals distinct universal scaling laws governing the error in the correlation-free and correlation-controlled regimes. Characterized by intrinsically smooth intensity profiles and counting-based statistics, neutron scattering measurements are well suited for demonstrating the enhanced error contraction enabled by inter-bin correlations. We show that such improvement is achievable over the experimentally accessible Q-range and across multiple instruments and material systems. These results show that explicitly accounting for correlations systematically reshapes the limits of precision in discretized, noise-limited measurements. More broadly, the framework provides a transferable statistical foundation for optimizing data representation, inference, and experimental design across the physical and data sciences.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
DOE OSTI2022

Visualizing Electric and Magnetic Field Coupling in Au-Nanorod Trimer Structures via Stimulated Electron Energy Gain and Cathodoluminescence Spectroscopy: Implications for Meta-Atom Imaging

In this work, trimer meta-atoms composed of three gold rods in an equilateral triangular geometry were fabricated, and their near-field plasmonic responses were characterized via electron energy loss (EEL), cathodoluminescence (CL), and stimulated electron energy loss/gain (sEEL/sEEG) spectroscopy. The trimer structure hybridizes into a low-energy mode with all three rods coupling in-phase, which produces a circulating current and thus a magnetic field. The next highest-energy mode consists of two rods coupling out-of-phase and produces a net electric dipole. We investigate the near fields of hybridized magnetic and electric modes via EEL and CL and correlate their spectral characteristics and intensity maps. Then, by changing the length of the trimer rods, we tune the magnetic and electric modes to our laser energy and characterize the excited state via sEEL/sEEG spectroscopy. Exploration of the tilt dependence, relative to the optical source, of the two modes reveals that the electric mode sEEG intensity increases more than the expected sin 2 (θ) dependence of the optical electric field coupling (see the Supporting Information for a detailed description). After correcting for the tail of the close-proximity electric mode, we demonstrate sEEG via coupling of the magnetic component of the optical field to the magnetic meta-atoms, which has the expected cos 2 (θ) tilt dependence. This realization opens the possibility to explore the nanoscale excited-state near-field imaging of other magnetic meta-atom structures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The cell morphological diversity of Saccharomycotina yeasts

The ~1 200 known species in subphylum Saccharomycotina are a highly diverse clade of unicellular fungi. During its lifecycle, a typical yeast exhibits multiple cell types with various morphologies; these morphologies vary across Saccharomycotina species. Here, we synthesize the evolutionary dimensions of variation in cellular morphology of yeasts across the subphylum, focusing on variation in cell shape, cell size, type of budding, and filament production. Examination of 332 representative species across the subphylum revealed that the most common budding cell shapes are ovoid, spherical, and ellipsoidal, and that their average length and width is 5.6 µm and 3.6 µm, respectively. 58.4% of yeast species examined can produce filamentous cells, and 87.3% of species reproduce asexually by multilateral budding, which does not require utilization of cell polarity for mitosis. Interestingly, ~1.8% of species examined have not been observed to produce budding cells, but rather only produce filaments of septate hyphae and/or pseudohyphae. 76.9% of yeast species examined have sexual cycle descriptions, with most producing one to four ascospores that are most commonly hat-shaped (37.4%). Systematic description of yeast cellular morphological diversity and reconstruction of its evolution promises to enrich our understanding of the evolutionary cell biology of this major fungal lineage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multilevel atomic structural model for interstratified opal materials

The structure of opal has long fascinated scientists. It occurs in a number of structural states, ranging from amorphous to exhibiting features of stacking disorder. Opal-CT, where C and T signify cristobalite- and tridymite-like interstratification, represents an important link in the length scales between amorphous and crystalline states. However, details about local atomic (dis)order and arrangements extending to long-range stacking faults in opal polymorphs remain incompletely understood. Here, a multilevel modeling approach is reported that considers stacking states in correlation with the abundance of C and T segments as a high-level structural parameter (i.e. not each atom). Optimization accounting for inter-tetrahedral bond lengths and angles and the regularity of the silicate tetrahedra is included as lower levels of structural parameters. Together, a set of parameters with both coarse-grained and atomistic features for different levels of structural details is refined. Structural disorder at the ~10–100 Å distance scale is evaluated using experimental pair distribution function and diffraction datasets, comparing peak intensities, widths and asymmetry. Here this work presents a complete multilevel structural description of natural opal-CT and explains many of the unusual features observed in X-ray powder diffraction patterns. This modeling approach can be adopted generally for analyzing layered materials and their assembly into 3D structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Transcritical diffuse-interface hydrodynamics of propellants in high-pressure combustors of chemical propulsion systems

Rocket engines and high-power new generations of gas-turbine jet engines and diesel engines oftentimes involve the injection of one or more reactants at subcritical temperatures into combustor environments at high pressures, and more particularly at pressures higher than those corresponding to the critical points of the individual components of the mixture, which typically range from 13 to 50 bars for most propellants. This class of trajectories in the thermodynamic space has been traditionally referred to as transcritical. However, the fundamental understanding of fuel atomization, vaporization, mixing, and combustion processes at such high pressures remains elusive. In particular, whereas fuel sprays are relatively well characterized at normal pressures, analyses of dispersion of fuel in high-pressure combustors are hindered by the limited experimental diagnostics and theoretical formulations available. The description of the thermodynamics of hydrocarbon-fueled mixtures employed in chemical propulsion systems is complex and involves mixing-induced phenomena, including an elevation of the critical point whereby the coexistence region of the mixture extends up to pressures much larger than the critical pressures of the individual components. As a result, interfaces subject to surface-tension forces may persist in multicomponent systems despite the high pressures, and may give rise to unexpected spray-like atomization dynamics that are otherwise absent in monocomponent systems above their critical point. In this article, the current understanding of this phenomenon is reviewed within the context of propulsion systems fueled by heavy hydrocarbons. Emphasis is made on analytical descriptions at mesoscopic scales of interest for computational fluid dynamics. In particular, a set of modifications of the constitutive laws in the Navier–Stokes equations for multicomponent flows, supplemented with a high-pressure equation of state and appropriate redefinitions of the thermodynamic potentials, are introduced in this work based on an extended version of the diffuse-interface theory of van der Waals. The resulting formulation involves revisited forms of the stress tensor and transport fluxes of heat and species, and enables a description of the mesoscopic volumetric effects induced by transcritical interfaces consistently with the thermodynamic phase diagram of the mixture at high pressures. Additionally, applications of the theory are illustrated in canonical problems, including dodecane/nitrogen transcritical interfaces in non-isothermal systems. The results indicate that a transcritical interface is formed between the propellant streams that persists downstream of the injection orifice over distances of the same order as the characteristic thermal-entrance length of the fuel stream. The transcritical interface vanishes at an edge that gives rise to a fully supercritical mixing layer.

02 PETROLEUM↗
DOE OSTI2020

Amphiphile Organization in Organic Solutions: An Alternative Explanation for Small-Angle X-ray Scattering Features in Malonamide/Alkane Mixtures

In this work, the role of different intermolecular interactions in the aggregation of amphiphiles in an organic solvent is studied for systems of relevance to liquid-liquid extraction (LLE), a chemical process used to selectively recover metals from complex mixtures. Of specific interest is the role, or lack thereof, of hydrogen bonding, which is often assumed to be a main driver of the organic phase structural organization that has been linked to separation efficacy. Toward that end, a series of malonamide extractants in n-dodecane have been studied in the absence of any extracted aqueous solutes, including water. The series of extractants includes N,N'-dimethyl-N,N'-dibutyltetradecylmalonamide (DMDBTDMA), two of its homologs, and N,N'-dimethyl-N,N'-dioctylhexylethoxymalonamide (DMDOHEMA). This simplified model LLE system enables systematic investigation of the role of dipole-dipole and alkyl tail steric interactions in amphiphile aggregation. Small-angle X-ray scattering (SAXS) profiles computed from molecular dynamics trajectories are in good agreement with experimental SAXS data. Molecular dynamics simulations show that malonamide aggregation results from dipole-driven self-association and lacks characteristic aggregate sizes. Mid-q correlation peaks in the SAXS profiles emerge at high concentration for each malonamide. In those densely packed solutions, the correlation peaks are observed to result from alkyl tail-induced spacing between electron-rich polar head groups, with peak positions determined by the different alkyl tail lengths present in the malonamide molecule. This explanation of the SAXS correlation peaks contrasts with the prevailing literature, which attributes mesoscale features observed in small-angle scattering to the formation of microemulsions. Instead, this work finds that these features are present in the absence of water or any reverse micellar organization of the malonamides. As such, molecular-scale malonamide self-association and packing, rather than microemulsion-based colloidal-scale descriptions, is a more appropriate framework for these LLE systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Correlation between backbone and pyridine dynamics in poly(2-vinyl pyridine)/silica polymer nanocomposites

Polymer segmental dynamics in polymer nanocomposites (PNCs) can be significantly perturbed from bulk and underly macroscopic material properties such as mechanical enhancements and improved small molecule transport, but fundamental studies are necessary to further understand this concept. To elucidate a mechanistic description of this perturbation and isolate different molecular motions, we present quasi-elastic neutron scattering (QENS) measurements on PNCs with attractive interactions comprised of colloidal silica nanoparticles (NPs) uniformly dispersed in poly(2-vinyl pyridine) (P2VP) with and without backbone deuteration. Measurements of fully-protonated P2VP probe the dynamics of both the polymer backbone and pyridine pendant group, whereas measurements of backbone deuterated P2VP isolate the dynamics of only the pyridine ring. On the small length scales (~1 nm) and fast time scales (~1 ns) captured by QENS, we show that the backbone and pyridine ring dynamics are highly coupled at high temperature and both are slowed by about 35% relative to neat polymer in 25 vol% PNCs. This observation implies that the backbone and pendant interfacial dynamics are perturbed similarly in PNCs, which further develops our fundamental understanding of microscopic properties in PNCs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scale-Dependent Bedform Migration and Deformation in the Physical and Spectral Domains

Multi-scale bathymetries observed in laboratory channels and natural rivers have posed several challenges to the description of bedform geometry and kinematics. To better quantify scale-dependent migration velocity, high resolution spatio-temporal bed evolution data are analyzed using three independent methods: (i) a bedform tracking method that identifies individual bedforms in longitudinal bed elevation profiles, (ii) a cross-correlation based, image matching technique in consecutive bathymetry scans similar to Particle Image Velocimetry, and (iii) two-dimensional frequency-wavenumber spectra marking a dispersion relation between bedform period and length, allowing estimation of Fourier-based, scale-dependent migration velocities. The comparative studies show that the spectral and bedform tracking methods present small differences in the migration velocity of medium-large bedforms. However, significant deviations occur in the small bedforms, mostly due to bedform sheltering or amplified exposure to the flow, which also contribute to their enhanced scale-dependent deformation. The analysis also shows that some form of scale separation is needed to extract the large and slowly migrating bedforms as they are masked by secondary features when several bedform orders coexist. Bathymetric Image Velocimetry reasonably estimates the averaged migration velocity and exhibits potential to study relations between spanwise bed surface velocity and local bedform kinematics.

58 GEOSCIENCES↗
DOE OSTI2022

SynBio QC-Library QC (LibQC) v2.0.0

This software is a pipeline used to identify the distribution of user-specified sequences in oligo pools that have been sequenced on the MiSeq platform for quality control purposes. The software counts instances of user-specified sequences (inserts or spacers) identified in sequencing data, returning the distribution of sequences in each pool and the length distribution of all the sequences. Among other types similar types of projects, this can be used to assess the quality of a guideRNA library once it has been inserted into the vector of choice to ensure that there is an even distribution of all the individual protospacers in the pool. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up.

Simirenko, Lisa↗
DOE OSTI2023

Influences of cloud vertical overlapping on the calculated cloud albedo and their validation with satellite observations

Cloud albedo is expected to influence cloud radiative forcing in addition to cloud fraction, and inadequate description of the cloud overlapping effects on the cloud fraction may influence the simulated cloud fraction, and thus the relative cloud radiative forcing (RCRF) and cloud albedo. In this study, we first present a new formula by extending that presented previously in Liu et al. (2011) to consider multilayer clouds directly in the relationship between cloud albedo, cloud fraction and RCRF, and then quantitatively evaluate the effects of different cloud vertical overlapping structures, represented by the decorrelation length scales (L cf ), on the simulated cloud albedos. We use the BCC_AGCM2.0_CUACE/Aero model with simultaneous validation by observations from the Clouds and the Earth's Radiation Energy System (CERES) satellite. When L cf < 4 km (i.e., the cloud overlap is closer to the random overlap), the simulated cloud albedos are generally in good agreement with the satellite-based albedos for December– February and June–August; when L cf ≥ 4 km (i.e., the cloud vertical overlap is closer to the maximum overlap), the difference between simulated and observed cloud albedos became larger, due mainly to significant differences in cloud fractions and RCRF. Further quantitative analysis shows that the relative Euclidean distance, which represents the degree of overall model–observation disagreement, increases with the L cf for all three variables (cloud albedo, cloud fraction and RCRF), indicating the importance of cloud vertical overlapping in determining the accuracy of the calculated cloud albedo for multilayer clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Uniqueness of relaxation times determined by dielectric spectroscopy

Dielectric spectroscopy is extremely powerful to study molecular dynamics, because of the very broad frequency range. Often multiple processes superimpose resulting in spectra that expand over several orders of magnitude, with some of the contributions partially hidden. For illustration, we selected two examples, (i) normal mode of high molar mass polymers partially hidden by conductivity and polarization and (ii) contour length fluctuations partially hidden by reptation using the well-studied polyisoprene melts as example. The intuitive approach to describe experimental spectra and to extract relaxation times is the addition of two or more model functions. Here, we use the empirical Havriliak-Negami function to illustrate the ambiguity of the extracted relaxation time, despite an excellent agreement of the fit with experimental data. We show that there are an infinite number of solutions for which a perfect description of experimental data can be achieved. However, a simple mathematical relationship indicates uniqueness of the pairs of the relaxation strength and relaxation time. Sacrificing the absolute value of the relaxation time enables to find the temperature dependence of the parameters with a high accuracy. For the specific cases studied here, the time temperature superposition (TTS) is very useful to confirm the principle. However, the derivation is not based on a specific temperature dependence, hence, independent from the TTS. We compare new and traditional approaches and find the same trend for the temperature dependence. The important advantage of the new technology is the knowledge of the accuracy of the relaxation times. Relaxation times determined from data for which the peak is clearly visible are the same within the experimental accuracy for traditional and new technology. However, for data where a dominant process hides the peak, substantial deviations can be observed. Finally, we conclude that the new approach is particularly helpful for cases in which relaxation times need to be determined without having access to the associated peak position.

36 MATERIALS SCIENCE↗
DOE OSTI2023

FUN-BioCROP model with litter decomposition parameters derived from the LIDET dataset

This repository contains the code and data necessary to run the FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms, and Protection) model with litter decomposition parameters derived from a modified Monte Carlo simulation that used the Long-term Intersite Decomposition Experiment Team dataset. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of Files: FUNBioCROP_LIDET Study.Rmd R code with FUN-BioCROP model that can be run with 10 different sets of parameters for litter decomposition (Baseline, LIDET, or eight other best parameter sets identified in the modified Monte Carlo simulation. CORPSE Functions_Bioenergy_V2.R Code with CORPSE model functions, called by FUNBioCROP_LIDET Study.Rmd Model Input Data: bulk.csv, bulk_till.csv, rhizo.csv, rhizo_till.csv, litter.csv Initial C and N (kg C or N/m2) pool values for each soil compartment, final values from spin up. All five files have the same columns: (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 Model Input Data: FluxTower_AvgSoilT.csv: Average daily soil temperature (oC) at 10 cm depth at University of Illinois Urbana-Champaign (UIUC) Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: FluxTower_AvgSoilVWC.csv: Average daily soil volumetric water content (VWC) at 10 cm depth at UIUC Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: input_CCS_LIDET Study.csv: This file has daily data to run FUN-BioCROP (Column - Description - Units): yr - calendar year - year doy - day of year (1 to 365) (no leap year) - day anpp - aboveground NPP (DayCent) - kg C/m2/day bnpp - belowground NPP (DayCent) - kg C/m2/day aglivc - live aboveground biomass carbon (DayCent) - kg C/m2 bglivcj - live juvenile fine root biomass carbon (DayCent) - kg C/m2 bglivcm - live mature fine root biomass carbon (DayCent) - kg C/m2 aglivn - live aboveground biomass nitrogen (DayCent) - kg N/m2 bglivnj - live juvenile fine root biomass nitrogen (DayCent) - kg N/m2 bglivnm - live mature fine root biomass nitrogen (DayCent) - kg N/m2 nyr - simulation year - year cult - indicates a cultivation event (0 or 1) crop - indicates a new crop (0 or 1) fert - indicates a fertilizer event (0 or 1) frst - indicates the first day of the growing season (0 or 1) harv - indicates a harvest event (0 or 1) last - indicates the end of the growing season (0 or 1) croptype - crop type (0=none; 1=alfalfa; 2=corn; 3=grass clover pasture; 4=soybean; 5=wheat) cropsrl - crop specific root length - mm/g root cultrhizmix - fraction of rhizosphere mixed with bulk soil during cultivation (0.0-1.0) - fraction cultlitmix - fraction of litter mixed with bulk soil during cultivation (0.0-1.0) - fraction harvremov - fraction of above ground biomass removed during harvest (0.0-1.0) - fraction fertamt - fertilization amount - g N/m2 lifehist - plant life history (0 = annual, 1 = perennial) froot_turnover_c - amount of C in fine root turnover - kg C/m2 froot_turnover_n - amount of N in fine root turnover - kg N/m2 agrd_turnover_c - amount of C in aboveground biomass turnover - kg C/m2 agrd_turnover_n - amount of N in aboveground biomass turnover - kg N/m2 leaf_litter_fastfrac - Fast decomposing fraction of leaf litter (0.0-1.0) - fraction root_litter_fastfrac - Fast decomposing fraction of root litter (0.0-1.0) - fraction root_diameter - root diameter - mm root_length - root length - mm root/m2 rhizo_frac - fraction of total soil volume that is rhizosphere (0.0 - 1.0) - fraction date - date in format YYYY-MM-DD Instructions: Save the model code ("FUN-BioCROP_LIDET Study.Rmd") and accompanything files (data streams and CORPSE function code) in the same folder. In model code "Chunk 3: Load CORPSE Data Streams" set the working directory (setwd) to the folder with the files saved in step #1. In "Chunk 5: Define LIDET parameter sets" select the litter decomposition parameter set to be used in the run, and comment out all other sets. If changing any parameter values, edit them in "Chunk 6: Load parameters." Run all chunks up to and including "Chunk 10: Prepare Data for Export." In "Chunk 11: Export Output Data" edit data frames for export and filenames, as necessary. "Chunk 12: Graph Total Soil C" makes a figure of C remaining over the model run period. Description of each model chunk (in file FUN-BioCROP_LIDET Study.Rmd): Chunk 1: Remove all functions, clear memory. Removes all functions from R environment, clears the memory. Chunk 2: Load Packages. Loads packages necessary to run the code. Chunk 3: Load CORPSE Data Streams. Sets the working directory and loads the data files necessary to run CORPSE. Chunk 4: Load CORPSE Functions. Loads the R script with CORPSE functions from the working directory, "CORPSE Functions_Bioenergy_V2.R". Chunk 5: Define LIDET parameter sets. Has ten different parameter sets for litter decomposition tested in this study: Baseline parameters, LIDET parameters, and the other 8 best performing parameter sets identified in the modified Monte Carlo. To run the model, all but one parameter set must be commented out. Chunk 6: Load Parameters. Loads all fixed parameters to run the model. Data frame with definitions of parameters is in the CORPSE function script "CORPSE Functions_Bioenergy_V2.R" Chunk 7: Prepare Data Streams. Takes data streams loaded in Chunk 3 and puts them in the format necessary to run the model. The model is coded to run at least two sites at a time, so if only one site is being run it must be run in duplicate. Individual data tables of daily values are created in this chunk from the input data file. Chunk 8: Set Initial Conditions. Creates data tables of soil C and N pools for each soil compartment (rhizo_till, rhizo, bulk_till, bulk, litter) and loads initial values into the data tables. Creates lists for each soil compartment to hold model output. Chunk 9: Load FUN Data and Set Up Matrices. Uses DayCent data to calculate FUN input data: root and leaf N demand, total N demand, plant CN, leaf N available for retranslocation, and litter production. Creates matrices for FUN model outputs. Chunk 10: Run Model. Runs the model. Chunk 11: Prepare Data for Export. Combines data from each day saved as lists into data frames for each soil compartment. Adds values from all soil compartments together to calculate total soil values, creates separate data frames for each soil C and N pool (e.g., protected slow C) for the total soil value. Adds different C and N pools together to calculate total soil C and N for all layers. Creates data frame of ratio of protected to unprotected SOC. Organizes FUN data for export. Chunk 12: Export Results. Exports CSV files of model results to the working directory. Chunk 13: Graph Total Soil C. Makes figure of C remaining over time. Related Links: Original FUN-BioCROP model: https://github.com/BrzostekEcologyLab/FUN-BioCROP LIDET dataset: https://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023

Juice, Stephanie↗
DOE OSTI2023

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↗
DOE OSTI2024

An idealized model for the crystal structure of intermetallic compounds isostructural with Mg 3 Cr 2 Al 18

Mg 3 Cr 2 Al 18 (abbreviated in this report as MCA) is the parent phase for a large class of intermetallic compounds that belong to the cubic crystal space group, $Fd\overline{3}m$. The purpose of this paper is to introduce an ideal, unrelaxed crystal structure for compounds isostructural with MCA. There are five distinct atomic sublattices in MCA compounds, which can be denoted, $A, B, C, D,$ and $E$. With this, a general description for MCA structures can be written as $A^{8a}_{1}B^{16c}_{2}C^{16d}_{2}D^{48f}_{6}E^{96g}_{12}$, where the superscripts represent the Wyckoff special equipoints associated with the various sublattices in MCA, and the subscripts indicate the contributions of each sublattice to the stoichiometry of one formula unit in an any given MCA structured compound. Sublattices D and E are where deviations from ideality occur in real, MCA-like compounds. This paper examines MCA bond lengths, nearest-neighbour polyhedral arrangements, 3-D sublattice crystal structures, 2-D atom tessellation patterns, and crystal chemical effects associated with atomic relaxations on the $D$ and $E$ sublattices. The ideal MCA crystal structure developed in this report provides an appropriate initial structure for use as input to crystal structure refinements of diffraction data for MCA-like phases being examined experimentally, or as input for computational, atomistic simulations of the structures of such compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A scoping study of far-SOL main-wall protection limiters for steady-state operation of compact pilot plant tokamaks

We present a novel method for handling steady-state heat fluxes incident on the main wall of pilot plant-scale magnetic fusion devices, based on the utilization of protection limiters in the far scrape-off layer (SOL). This method helps avoid large plasma-wall gaps, without excessively compromising blanket performance. We present an optimization algorithm for determining the appropriate size and scale of these protection limiters given (1) probability distributions of SOL plasma parameters and (2) assumed risk tolerance. As part of this optimization, we have developed an analytic description of parallel heat fluxes across limiter shadows, and an objective cost function (the ‘Far-SOL Marginal Cost’) to quantify the impact that different main-wall thermal management design choices have on reactor capital cost. Applying the model to a midscale fusion pilot plant concept shows that making use of far-SOL protection limiters can reduce capital costs on the order of $500 M, relative to naively increasing the plasma-wall gap. Our analysis demonstrates that the far-SOL power decay length is the highest-leverage plasma assumption for thermal loading of the first wall, and the primary cost driver for main wall thermal management. The relative cost efficiency of protection limiters increases as assumptions on the far-SOL heat flux become more pessimistic. The concepts described in this paper motivate the further development of far-SOL protection limiters as part of larger efforts to design economical core-edge-wall compatible solutions for a fusion pilot plant.

Design under uncertainty↗