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DOE OSTI2018

Stochastic Design Optimization of Microstructural Features Using Linear Programming for Robust Design

Microstructure design can have a substantial effect on the performance of critical components in numerous aerospace applications. However, the stochastic nature of metallic microstructures leads to deviations in material properties from the design point and alters the performance of these critical components. In this paper, a novel stochastic linear programming (LP) methodology is developed for microstructure design accounting for uncertainties in desired properties. The metallic microstructure is represented using a finite element discretized form of the orientation distribution function (ODF). The inverse LP problem solves the mean values and covariance matrix of the ODFs to maximize the mean values of a property, given the statistical constraints on other properties. The highlight is an analytical uncertainty quantification model via a Gaussian distribution to model propagation of microstructural uncertainties to the properties. Examples illustrate maximization of the yield strength and magnetostriction of a galfenol alloy when constrained by uncertainties in a set of stiffness constants.

42 ENGINEERING↗

DOE OSTI2025

Hardware-in-Loop Modules for Testing Automated Ventilator Controllers

Automated ventilator controllers have the potential to simplify oxygen and carbon dioxide management for trauma. In the pre-hospital or military medicine environment, trauma care can be required for prolonged periods by personnel with limited ventilator management training. As such, there is a need for closed-loop control systems that can adapt ventilator management to a complex, ever-changing medical environment. Here, we present a novel hardware-in-loop test platform for the independent troubleshooting and evaluation of oxygen and carbon dioxide automated ventilator management capabilities. The oxygen management system provides an analogue blood oxygen signal that is responsive to the fraction of inspired oxygen and the peak inspiratory pressure ventilator settings. A tested oxygenation controller successfully reached the target oxygen saturation within 5 min. The carbon dioxide removal system integrates with commercial ventilator technology and mimics carbon dioxide generation, lung compliance, and airway resistance while providing an end-tidal carbon dioxide level that is responsive to changes in the tidal volume and respiratory rate settings. A test mechanical ventilator controller was able to regulate EtCO2 regardless of the starting value within 10 min. This highlights the system’s functionality and provides proof-of-concept demonstrations for how the hardware-in-loop test platforms can be used for evaluating closed-loop controller technologies.

Berard, David (ORCID:0000000322863846)↗

DOE OSTI2021

A Comprehensive Analysis of NGC 2158 in the Gaia Era: Photometric Parameters, Apex, and Orbit

We present an investigation of NGC 2158 using Gaia DR2 data. We identified 800 most likely cluster members with membership probability higher than 90%. The mean proper motions of this object are determined as (μ {sub x} = −0.203 ± 0.003, μ {sub y} = −1.99 ± 0.004) mas yr{sup −1}. The limiting radius, log(age), and distance of the cluster are obtained as 23.5 arcmin, 9.38 ± 0.04 Gyr, and 4.69 ± 0.22 kpc, respectively. The overall mass function slope (0.93 ± 0.14) is flatter than the Salpeter value (1.35) within the mass range of 1.17–1.44 M {sub ⊙}. This cluster also shows the mass-segregation effect and our study demonstrates that NGC 2158 is a dynamically relaxed open cluster. Using the apex diagram (AD), the apex coordinates of the cluster are obtained in different ways and are examined using the (μ {sub U},μ {sub T}) diagram. The best value of the apex coordinates is determined as A = 8724 ± 160, D = −3661 ± 530. We also determined the orbit of the cluster and found that NGC 2158 moves almost in the solar antapex direction. The resulting spatial velocity of NGC 2158 is 51 km s{sup −1}. A significant oscillation along the Z-coordinate up to 529 pc is detected. Various scenarios regarding the origin of this cluster are also discussed.

42 ENGINEERING↗

DOE OSTI2025

CCN Measurements at Urban Site during CoURAGE

Cloud condensation nuclei (CCN) measurements were collected during CoURAGE from March - June 2025 at the BSEC urban atmospheric chemistry supersite (39.32057 N, 76.6246 W). CCN number concentrations (# cm-3) were obtained at a frequency of 1 second using a cloud condensation nuclei counter (CCN-100, Droplet Measurement Technologies). The CCN counter was operated in stepping mode, measuring CCN over a range of supersaturations from 0.2 to 1.0%. The settings of the instrument were set such that the supersaturation increased in increments of 0.2% up to the maximum supersaturation, and then decreased in increments of 0.2% down to the minimum supersaturation in a repeating cycle. The supersaturation of the instrument was calibrated weekly using ammonium sulfate. The weekly calibrated supersaturation values have been applied to the data. Data during transitions between supersaturation values were removed and replaced with a value of -999. Transitions are defined as the first 210 seconds after a new supersaturation value to ensure the instrument has stabilized following a change in supersaturation. Data were also flagged with a value of -999 if there were concerns with the function of the instrument, specifically the presence of alarm codes, fogging of the optical particle counter (1st stage monitor > 0.4 V), or a sheath to sample flow ratio outside the expected range (< 9 or > 11).

CCN number density↗

DOE OSTI2023

Logging Crew Attributes by Region in the Southeast USA

Urbanization, shrinking markets, and reduced forestry investment may affect harvesting efficiency in regions of the US South. To monitor these conditions, logging businesses have been tracked by surveys conducted by universities and trade associations. This project used a sampling approach coordinated with FIA utilization studies to sample logging crews based on a harvesting location. The approach was used to develop relationships among firm attributes and site attributes in six southeastern states (AL, GA, FL, NC, SC, and VA) from 2011 to 2018. The data included harvest attributes (location, harvest size and stand type) and logging firm attributes (production, crew labor, crew number, the number of machines by type, and machine age). For crew capital value, an equation was developed for this study using machine number and average machine age. The data from logging crews on 419 harvests were analyzed by region, harvest size, and stand type. Mean values for crew labor ranged from 3.1 to 7.1 workers. The average capital value per crew ranged from $\$220,000$ to $\$524,000$ per crew in the Coastal Plain with a narrower range in the Piedmont. In the Coastal Plain, higher productivity was detected for larger harvests and pine versus hardwood and mixed stands; however, in the Piedmont those trends were less obvious. Ratio of feller-bunchers, skidders and loaders were mostly 1:1:1 or 1:2:1 with 41% and 24% of samples, respectively. There were notable trends among Coastal Plain loggers regarding capital value and productivity with evidence supported by a production function. The differences in Piedmont (e.g., ownership size, market access, terrain, population density, etc.) may combine to limit daily production and labor productivity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Apparatus, system and method for highlighting activity-induced change in multi-pass synthetic aperture radar imagery

Described herein are various technologies relating to constructing a differenced change product (DCP) image. A plurality of synthetic aperture radar (SAR) images of a scene are generated based upon radar signals directed towards and reflected off of the scene, and a plurality of coherence change detection (CCD) images of the scene are generated based upon the SAR images. The CCD images are registered with one another, and their pixel values re-scaled according to a monotonic mapping function. The DCP image is generated based upon a computed pixel-wise difference between a pair of the re-scaled CCD images. The DCP image identifies locations in the scene where human activity-induced change is likely to have occurred between a pair of SAR passes of the scene.

42 ENGINEERING↗

DOE OSTI2025

Data release for A search for extremely-high-energy neutrinos and first constraints on the ultra-high-energy cosmic-ray proton fraction with IceCube

<h1 id="summary">Summary</h1> <p>Title: Data Release for A search for extremely-high-energy neutrinos and first constraints on the ultra-high-energy cosmic-ray proton fraction with IceCube</p> <p>The IceCube observatory analyzed 12.6 years of data in search of extremely-high-energy (EHE) neutrinos above 5 PeV. The resultant limit of the search (Fig 1), and the effective area of the event selection (Fig 7), are provided in this data release.</p> <h1 id="contents">Contents</h1> <ul> <li><p>README file: this file</p> </li> <li><p><code>differential_limit_and_sensitivity.csv</code>: a comma separated value file, giving the observed experimental differential limit, and sensitivity, of the search as a function of neutrino energy. This is the content of Fig 1 in the paper. The first column is the neutrino energy in GeV. The second column is the limit in units of GeV/cm2/s/sr. The third column is the sensitivity in units of GeV/cm2/s/sr.</p> </li> <li><p><code>effective_area.csv</code>: a comma separated value file, giving the effective area of the search as a function of energy. This is the content of Fig 7 in the paper. The first column is the neutrino energy in GeV. The second column is the total effective area of the search, summed across neutrino flavors, and averaged across neutrinos and antineutrinos, in meters-squared. The third column is the effective area of the search for the average of electron neutrino and electron antineutrinos in units of meters-squared. The fourth column is the same as the third, but for muon-flavor neutrinos. The fifth column is the same as the third and fourth, but for tau-flavor neutrinos.</p> </li> <li><p><code>demo.py</code>: a short python script to demonstrate how to read the files. Run like <code>python demo.py</code>. A standard base python installation is sufficient, as the only dependencies are numpy and matplotlib.</p> </li> </ul> <h1 id="contacts">Contacts</h1> <p>For any questions about this data release, please write to analysis@icecube.wisc.edu</p>

Astronomy and Astrophysics↗

DOE OSTI2021

Toward sustainable production of value‐added bioenergy and industrial oils in oilseed and biomass feedstocks

Abstract Plant fatty acids are used for food, feed, fuel, and industrial materials. Structurally and chemically diverse fatty acids, referred to as unusual or specialized fatty acids, are found in the seed oils of diverse plant species. Many unusual fatty acids have potential use as alternative and renewable sources of biofuels and bio‐based industrial feedstocks due to their variant structures' physical or functional properties. Oils enriched in these fatty acids can increase the value of oilseed crops and provide co‐products that can be readily extracted from lignocellulosic materials in biomass crops. Here, we describe recent progress in strategies for enhancement of oil production and quality in oilseed crops and the extension of this knowledge for metabolic engineering of biomass crops. Successful implementation of these strategies, in part, through the use of emerging synthetic biology tools, will provide added product value for the economic sustainability of biomass crops as bioenergy feedstocks.

Park, Kiyoul↗

DOE OSTI2019

Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model

We evaluated global soil organic carbon (SOC) stocks and turnover time predictions from a global land model (ELMv1-ECA) integrated in an Earth System Model (E3SM) by comparing them with observed soil bulk and Δ 14 C values around the world. We analyzed observed and simulated SOC stocks and Δ 14 C values using machine learning methods at the Earth System Model grid cell scale (~200 km). In grid cells with sufficient observations, the model provided reasonable estimates of soil carbon stocks across soil depth and Δ 14 C values near the surface but underestimated Δ 14 C at depth. Among many explanatory variables, soil albedo index, soil order, plant function type, air temperature, and SOC content were major factors affecting predicted SOC Δ 14 C values. The influences of soil albedo index, soil order, and air temperature were primarily important in the shallow subsurface (≤30 cm). We also performed sensitivity studies using different vertical root distributions and decomposition turnover times and compared to observed SOC stock and Δ 14 C profiles. The analyses support the role of vegetation in affecting soil carbon turnover, particularly in deep soil, possibly through supplying fresh carbon and degrading physical-chemical protection of SOC via root activities. Allowing for grid cell-specific rooting and decomposition rates substantially reduced discrepancies between observed and predicted Δ 14 C values and SOC content. Furthermore, our results highlight the need for more explicit representation of roots, microbes, and soil physical protection in land models.

58 GEOSCIENCES↗

DOE OSTI2026

Rethinking the soil core microbiome

The concept of a core microbiome emerged from host-associated research to describe microbial members or functions conserved across clearly defined spatial, temporal, and biological boundaries. In soil- and plant-associated microbiome research, however, the term has increasingly shifted toward analytically defined subsets selected using study-specific thresholds or criteria. Synthesizing recent literature and cross-site analyses of bioenergy crop field soils, we show that the original biological meaning of the core microbiome has been blurred by dataset-specific analytical criteria. Taxa designated as ‘core’ were highly sensitive to methodological choices and often reflected explanatory value rather than conserved biological membership. Moreover, many studies that identify taxonomic ‘core’ members interpret their significance in functional terms, suggesting that functional conservation may be the biological interest. Taxonomic conservation may not be the most biologically meaningful target in highly heterogeneous soil and rhizosphere systems, where functional conservation may persist despite taxonomic turnover. Accordingly, ‘core microbiome’ should be reserved for microbial components explicitly demonstrated to be conserved across defined spatial, temporal, and environmental dimensions and linked to conserved ecological functions, while taxa selected for explanatory value are better described as ‘explanatory subsets of taxa’. Greater terminological precision will improve cross-study comparability and strengthen ecological inference in plant–soil microbiome research.

bioenergy crops↗

DOE OSTI2023

Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii , Arabidopsis thaliana , and Setaria viridis

Abstract The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome‐wide protein‐coding gene annotation. A substantial fraction of protein‐coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high‐value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Ultrafast nonlinear absorption of Haldane model quantum dots

We study theoretically the nonlinear absorbance of Haldane model quantum dots (QDs) placed in the field of an ultrashort and strong optical pulse. The absorbance strongly depends on the frequency of the pulse. When the frequency of the pulse is much less than the QD bandgap, the absorbance shows strong dependence on the pulse amplitude and, as a function of an internal phase of the Haldane model, the absorbance has maxima at intermediate values of the phase. When the frequency of the pulse becomes closer to, but still less than, the bandgap, the absorbance has a weak dependence on the pulse amplitude and, as a function of the internal phase, it has a maximum at the phase of 900 when the QD bandgap also has the smallest value. Furthermore, nonlinear electron dynamics in such QD systems changes from almost reversible one at small pulse frequencies to highly irreversible dynamics at large frequencies of the pulse.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Synthesis of End-Functionalized Poly(norbornenes) and Poly(ethylidene norbornenes) Using a Pd(II) Catalyst in Combination with Chain Transfer Agents

Synthesis of end-functionalized poly(norbornene)s (PNBs) and poly(ethylidenenorbornene)s (PENBs) were prepared using the palladium catalyst t Bu 3 PPdMeCl/NaBAr f in combination with chain transfer agents (CTAs) 4-penten-1-ol and 10-undecenal. These CTAs produce polymers end-capped with -OH and -CHO groups, respectively, in high yields with M n values in the range of 6K to 17K, depending on the molar ratio of the CTA: monomer. End-functionalized PNBs and PENBs with precisely controlled Mn values and very narrow molecular weight distributions were accessed by using 4-penten-1-ol and 10-undecenal as chain-terminating agents following living polymerizations in which monomer is completely consumed. The utility of the aldehyde-functionalized polymers is illustrated via coupling to a dye molecule and by synthesis of ambiphilic diblock copolymers, PNB-b-PEG and PENB-b-PEG.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Harnessing Uncertainty through Functional Data Analysis in Gas Breakthrough Data

Detecting subsurface explosions from radionuclide gas migration through rock fractures is an effective way to identify nuclear activity. Los Alamos National Laboratory (LANL) has developed simulation methods, based on data from the 1962 Hardhat underground nuclear test, to predict gas breakthrough times at the surface. However, these methods rely on an imperfect understanding of the relationship between rock damage and fracture permeability. Our clinic project studies methods for predicting breakthrough curves that characterize total mass produced as a function of time, as well as quantifying the uncertainty associated with these predictions. The model that is currently employed to relate damage to permeability uses an empirically motivated power-law expression, with a range of parameter values that are compatible with the experimental Hardhat data. We develop emulators, built from functional data analysis techniques and trained on simulation data, that rapidly predict the gas breakthrough curve given a damage field and given the parameter values of the power-law equation. Using Bayesian regression, we address the problem of uncertainty quantification in our emulators. Finally, in order to test the robustness of the model, we further validate it on a damage field representing different physical conditions.

58 GEOSCIENCES↗

DOE OSTI2019

Biomarker Mapping on Skin Tape Strips Using MALDI Mass Spectrometry Imaging

Keratinocyte organization and biochemistry are important in forming the skin’s protective barrier. Intrinsic and extrinsic factors can affect skin barrier function at the cellular and molecular levels. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometric imaging, a technique which combines both molecular aspects and histological details, has proven to be a valuable method in various disciplines including pharmacology, dermatology and cosmetology. It typically requires ex vivo samples, prepared following frozen tissue sectioning. This paper demonstrates the feasibility of performing MALDI analysis on tape strips collected non-invasively on skin. The aim is to obtain molecular imaging of corneocytes on tapes towards novel biological insights. Tapes were collected from two skin sites (volar forearm and cheek) of human volunteers. Ten molecules relating to skin barrier function were detected with a single mode of acquisition at high spatial resolution with a 7 T MALDI-Fourier transform ion cyclotron resonance (FTICR) instrument. The method sensitivity was adequate to create molecular maps which could be overlaid on transmission microscopy images of the same area of the tape. Analysis of the molecular distributions from tapes at the two skin sites was consistent with the known skin properties of the two sites, confirming the validity of the observations. Hierarchical clustering analysis was used to differentiate corneocyte populations based on their molecular profiles. Furthermore, morphological analysis provided a new way of considering statistical populations of corneocytes on the same tape, rather than measuring a single averaged value, providing additional useful information relating to their structure-function relationship. .

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Exploring the strong-coupling region of SU( N ) Seiberg-Witten theory

We consider the Seiberg-Witten solution of pure N = 2 gauge theory in four dimensions, with gauge group SU(N). A simple exact series expansion for the dependence of the 2(N – 1) Seiberg-Witten periods a I (u), a DI (u) on the N – 1 Coulomb-branch moduli un is obtained around the Z 2N -symmetric point of the Coulomb branch, where all u n vanish. This generalizes earlier results for N = 2 in terms of hypergeometric functions, and for N = 3 in terms of Appell functions. Using these and other analytical results, combined with numerical computations, we explore the global structure of the Kähler potential K = 1/2Σ I Im(a¯ I a DI ), which is single valued on the Coulomb branch. Evidence is presented that K is a convex function, with a unique minimum at the Z 2N -symmetric point. Finally, we explore candidate walls of marginal stability in the vicinity of this point, and their relation to the surface of vanishing Kähler potential.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Melting down a tetraquark: DD() interactions and T c c ( 3875 ) + in a hot environment

We discuss the modification of the properties of the tetraquark-like and its heavy quark spin partner, immersed in a hot bath of pions. We consider these exotic states as purely isoscalar DD* and D*D* S-wave bound states, respectively. Finite temperature effects are incorporated through the D and D* state-of-the-art thermal spectral functions calculated in [G. Montana et al., Phys. Rev. D, 102 (2020) 096020], using the imaginary-time formalism. We find important modifications of the DD* and D*D* scattering amplitudes already for MeV, and show that the hot-bath lineshapes of these tetraquark-like states strongly depend on their Weinberg molecular content. We find that the thermal and spectral functions change more rapidly with temperature for high molecular probabilities P0. For large values of P0, the widths significantly increase with temperature, leading to the melting of these exotic states for temperatures larger than 80 MeV. For small molecular components, the changes in the spectral functions of these states due to temperature become significantly less important. All these results show that any future experimental determination of the D(*)D* scattering amplitudes at finite temperature will provide valuable insights into the molecular content of the and exotics.

Montesinos, V. (ORCID:0000000261862777)↗

DOE OSTI2024

Learning energy-based representations of quantum many-body states

Efficient representation of quantum many-body states on classical computers is a problem of practical importance. An ideal representation of a quantum state combines a succinct characterization informed by the structure and symmetries of the system along with the ability to predict the physical observables of interest. Several machine-learning approaches have been recently used to construct such classical representations, which enable predictions of observables and account for physical symmetries. However, the structure of a quantum state typically gets lost unless a specialized is employed based on prior knowledge of the system. Moreover, most such approaches give no information about what states are easier to learn in comparison with others. Here, we propose a generative energy-based representation of quantum many-body states derived from Gibbs distributions used for modeling the thermal states of classical spin systems. Based on the prior information on a family of quantum states, the energy function can be specified by a small number of parameters using an explicit low-degree polynomial or a generic parametric family such as neural nets and can naturally include the known symmetries of the system. Our results show that such a representation can be efficiently learned from data using exact algorithms in a form that enables the prediction of expectation values of physical observables. Importantly, the structure of the learned energy function provides a natural explanation for the difficulty of learning an energy-based representation of a given class of quantum states when measured in a certain basis. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗