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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors

Hierarchical models with gamma hyperpriors provide a flexible, sparse-promoting framework to bridge L 1 and L 2 regularizations in Bayesian formulations to inverse problems. Despite the Bayesian motivation for these models, existing methodologies are limited to maximum a posteriori estimation. The potential to perform uncertainty quantification has not yet been realized. This paper introduces a variational iterative alternating scheme for hierarchical inverse problems with gamma hyperpriors. The proposed variational inference approach yields accurate reconstruction, provides meaningful uncertainty quantification, and is easy to implement. In addition, it lends itself naturally to conduct model selection for the choice of hyperparameters. Here, we illustrate the performance of our methodology in several computed examples, including a deconvolution problem and sparse identification of dynamical systems from time series data.

Bayesian shrinkage↗
DOE OSTI2024

Wrought Aluminum-Cerium Alloys by Shear Assisted Processing and Extrusion

Al-Ce alloys have attracted recent interest because of their high thermal stability due to the very low solubility of Ce in the Al matrix. The Al 11 Ce 3 eutectic phase gives excellent strain hardening behavior and moderate high-temperature strength in the as-cast state. However, its strengthening effect is limited by its coarse as-cast structure. Therefore, alternative manufacturing methods such as additive manufacturing or equal channel angular pressing have been applied to refine the Al 11 Ce 3 phase to good effect. However, these techniques are both expensive and time-consuming. Therefore, this study aims to use Shear Assisted Processing and Extrusion (ShAPE), an emerging solid phase processing technique that is more easily scalable than the previously mentioned methods. ShAPE can produce useful cross-sections of an Al-8Ce-4Mg alloy while refining the Al 11 Ce 3 phase to produce a higher strength material. It was found that a low temperature ShAPE process can improve the room temperature yield strength by ~60% compared to a binary Al-4Mg alloy. Additionally, the high-temperature yield strength of the Al-Ce alloys increased by 20%, with a simultaneous 15% improvement in ductility compared to the binary Al-Mg alloy. These results highlight the potential for ShAPE as a processing technique for Al-Ce alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Conceptual Designs of the Structure of Inflatable Blades for Enabling Larger Turbines

Over the last couple of decades, increasingly larger rotor diameters have enabled significant reductions in the levelized cost of energy for wind through higher energy capture and improved capacity factors. But for onshore turbines, this has been met with manufacturing and transportation challenges. To enable larger onshore rotors, an innovative inflatable blade concept is investigated that employs both traditional and onsite manufacturing. The design architecture consists primarily of an inflatable aerodynamic shell attached to a factory-manufactured primary structure. Multiple architectures, cross-sectional topologies, and material combinations for the primary structure are investigated, as well as multiple skin materials. Structural cross-sectional characteristics are compared to a traditional blade, and inflatability and cost evaluations are presented. Results show that a box-beam architecture using only composite materials yields significant mass reduction with mature technologies/processes and modest cost decrease compared to traditional blade construction. This low-TRL study demonstrates the inflatable blade concept's techno-economic potential.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2026

Bimetallic Coinage Metal Complexes of Tetradentate ortho Ter arylene Ligands

The synthesis, structural and photophysical properties of five bimetallic coinage metal complexes of three tetradentate charge-transfer (CT) ligands are presented. The ligand structures incorporate donor/acceptor moieties electronically decoupled by ortho connection to a bridging biphenylene group. The M M distances observed in the crystal structures of the bimetallic complexes are shorter than the sum of the Van der Waals radii of the metal ions, suggesting stabilizing interactions between the d10 metal centers. Additionally, short distances between the bridging biphenylene and metal atoms suggest arylene metal interactions. Bimetallic Cu, Ag, and Au complexes of the ligand incorporating a carbazole donor and pyridyl acceptor (N2R22-) show absorption and emission energies that trend with the ionization potential of each metal, indicating metal character in the excited state. These properties contrast with our previously reported mononuclear Zn complex of N2R22-The structural and photophysical properties of five bimetallic d10 coinage metal complexes were presented. The M M distances observed in the crystal structures of the bimetallic complexes are shorter than the sum of the metals’ Van der Waals radii, suggesting attractive interactions between the d10 metal centers. Additionally, short distances between the bridging biphenylene and metal atoms suggest arylene metal interactions. The absorption and emission spectra of the bimetallic complexes redshift based on the oxidation potential of the metal ion. This suggests involvement of metal based orbitals in the excited state transitions of the bimetallic complexes, which was corroborated by molecular modeling. High photoluminescent quantum yields were observed in solution and in rigid media (up to PL = 0.75), and the excited state lifetimes in solution were found to exceed several microseconds.

Shariaty, Darius Allen [University of Southern Cal↗
DOE OSTI2024

Object-oriented analysis as a foundation for building climate storylines of compounding short-term drought and crop heat stress

Introduction: Crops are vulnerable to precipitation and heat extremes during late spring through summer. Methods: We analyzed for a north-central U.S. region short-term drought and agricultural heat stress during April-May-June-July. We used the 4-km Parameter Elevation Regression on Independent Slopes Model (PRISM) for observations, aggregated to a 25-km grid, and two 25-km Regional Climate Model version 4 (RegCM4) simulns used either GFDL- or MPI-GCM boundary conditions. We chose 1981-2000 as our contemporary time period, and 2041- 2060 as our scenario time period, which used the Representative Concentration Pathway 8.5 emissions scenario. We used object-oriented analysis to identify events of interest in observations and simulations by identifying objects in a space-time domain that meet specified criteria, such as exceeding a heat-stress temperature threshold. The event diagnosis allowed analysis of compound events, occurring when temperature and drought objects overlap. Results: Identified objects yielded events that can undermine agricultural productivity and which are thus relevant to decision makers, making them building blocks for possible climate storylines. The observations and simulations showed similar spatial distributions of event frequencies across the analysis region. However, the simulations attained this distribution by having fewer events that tend to cover larger areas compared to observed events, suggesting that the effective resolution of the simulations was coarser than their 25-km grids. Short-term drought frequency increased and heat-stress frequency decreased in transitioning to the scenario climate. When compounding occurred heat-stress events generally preceded the short-term drought events. The overlapping, compound events tended to be more extreme compared to non-overlapping events of either type. Discussion: The information yielded projected changes in these agriculturally motivated events. One prominent conditional behavior emerging from the work was that a heat-stress event should be a warning to watch for potential drought, as both could compound each other to more intense levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Angular Dependence of Drell-Yan in the SeaQuest Experiment using Deep Neural Network-Based Reconstruction

The SeaQuest and SpinQuest experiments at Fermilab were designed to probe the internal dynamics of protons and neutrons via the angular dependence of muons created by colliding 120 GeV protons into stationary targets. To do this, it is necessary to translate the detector data into coherent information about the particles detected in the experiment. This dissertation describes the development and implementation of QTracker, a neural network-based algorithm designed to reconstruct muons. The application of QTracker to experimental data yields improved reconstruction of muon tracks, allowing for a more precise investigation of the transverse momentum distributions and angular modulations in the Drell-Yan process. This work highlights the potential of neural network-based methods to advance particle tracking and enhance our understanding of nucleon structure.

Conover, Arthur↗
DOE OSTI2026

Engineering Anti-Microbial Peptide Production in Fungi and Bioprocess Development (CRADA 502)

Crop Protection, specifically controlling agricultural diseases and pests, is essential for crop production at every agricultural scale. Biologics hold enormous potential in this equation to decrease use of more toxic pesticides. Currently, the widespread use of biologics in crop protection is severely hampered by the lack of available tools for their mass production. To ensure biologics are regulated under EPA Biopesticide regulations, the following must be true: The biopesticide is a naturally occurring substance or structurally similar and functionally identical to a naturally occurring substance with a history of exposure to humans and the environment demonstrating minimal toxicity. Since this pertains to the marketed product it is also essential that fermentation hosts have a history of exposure and safe use by humans This research focuses on developing a novel platform for the production and delivery of the cghSAMP peptide using the filamentous fungus Aspergillus niger. A. niger is a well-established industrial microorganism, widely recognized for its strong protein secretion capabilities, high-yield production of enzymes, and classification as a generally recognized as safe (GRAS) organism. By genetically modifying A. niger to express the cghSAMP peptide transgene, we aim to leverage the fungus's robust fermentation system to produce a high volume of the antimicrobial agent. This engineered system represents a potential breakthrough in sustainable disease management, offering an environmentally friendly method for localized application or large-scale production of a biopesticide designed to mitigate the effects of citrus greening disease. The main objectives of this project were: 1. Developing a high-yield and cost-efficient bioprocess to produce an AMP in a current ABF host or readily onboarded hosts. 2. Scale up the process in stirred tank reactors and produce at least 100 grams of AMP at 1- 5g/L

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Calibration of the liquid argon ionization response to low energy electronic and nuclear recoils with DarkSide-50

DarkSide-50 has demonstrated the high potential of dual-phase liquid argon time projection chambers in exploring interactions of WIMPs in the GeV=c 2 mass range. The technique, based on the detection of the ionization signal amplified via electroluminescence in the gas phase, allows us to explore recoil energies down to the sub-keV range. We report here on the DarkSide-50 measurement of the ionization yield of electronic recoils down to ~180 eV er , exploiting 37 Ar and 39 Ar decays, and extrapolated to a few ionization electrons with the Thomas-Imel box model. Further, we present a model-dependent determination of the ionization response to nuclear recoils down to ~500 eV nr , the lowest ever achieved in liquid argon, using in situ neutron calibration sources and external datasets from neutron beam experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Techno-Economic Impact of Diesel Fuel, Labor, and Interest Rates on Bulk-Format and Round Bale Logistics Expenses for Switchgrass

Highlights System-wide sensitivity of bulk-format and round bale logistics responded to different degrees of expense inputs. Biomass size-reduction expenses for bulk-format were consistently less than round-bale chopping. Stack/reclaim operations with high-density-capacity equipment for bulk-format were the highest expenses. Clean-sheet design of stacker/reclaimer and self-compacting bulk trailer may significantly reduce expenses. Abstract . Deterministic cost analyses were conducted for a harvest, storage, preprocessing, and supply system providing 371,870 dry Mg (dMg) year-1 of milled switchgrass (SG) to a biorefinery from 21,929 ha of production fields within 72 km of the biorefinery. Varied input costs of diesel fuel, labor, and interest rate were input into a highly detailed cost analysis for bulk-format and baseline round bale logistics. These operational input factors, potentially reflecting an evolving economic climate or paradigm shift, were examined to provide insight into the cost to deliver preprocessed biomass feedstock for centralized commercial-scale conversions. Total annual costs per dry unit of SG were determined for all combinations of diesel fuel prices of $0.53 L-1, $0.92 L-1, and $1.32 L-1; total labor costs of $20.00 h-1, $28.85 h-1, and $40.00 h-1 singly and uniformly applied across all labor inputs; and three representative interest rates of 6%, 8%, and 12%. Increases in total cost most depended on increases in diesel fuel cost, followed by labor rate, and finally interest rate. Increases in fuel costs from $0.53 L-1 to $1.32 L-1 yielded a total cost increase of about $11.56 dMg-1 and $13.36 dMg-1 for bulk-format and round bale logistics, respectively, for all combinations of labor and interest rates. The overall increase in labor rate ($20.00 h-1 to $40.85 h-1) resulted in increased total costs of about $10.32 dMg-1 for bulk-format logistics and $9.94 dMg-1 for round bale logistics for all fuel and interest rates. The overall increase in interest rate (6% to 12%) resulted in increased total costs of about $6.72 dMg-1 for bulk-format logistics and $4.21 dMg-1 for round bale logistics for all fuel and labor rates. Increases in total costs for combined increases in fuel cost, labor rate, and interest rate were $28.60 dMg-1 and $27.48 dMg-1, yielding maximum total costs of $87.87 dMg-1 and $86.53 dMg-1 for bulk-format and round bale logistics, respectively. Costs were determined for existing equipment systems, including novel use of waste compaction and ejector semi-trailers. The highest potential for cost reductions may require clean-sheet equipment designs specifically tailored for SG, such as forage harvesters that direct-cut standing SG, mobilized stacker-reclaimer technology to not inhibit stack-area footprint, self-compacting ejector trailer technology, and bale grinding technology incorporating controlled mass feeding and shear failure elements. Keywords: Bales, Bioenergy, Bulk-format, Densification, Field chop, Logistics, Transportation

Agriculture↗
DOE OSTI2024

The Overlooked Potential of Sulfated Zirconia: Reexamining Solid Superacidity Toward the Controlled Depolymerization of Polyolefins

Closed-loop recycling via an efficient chemical process can help alleviate the global plastic waste crisis. However, conventional depolymerization methods for polyolefins, which compose more than 50% of plastics, demand high temperatures and pressures, employ precious noble metals, and yield complex mixtures of products limited to single-use fuels or oils. Superacidic sulfated zirconia (SZrO) with Hammet Acidity Functions (H 0 ) = -12 (i.e., stronger than 100% H 2 SO 4 ) is an industrially deployed heterogeneous catalyst capable of activating hydrocarbons under mild conditions and is shown to decompose polyolefins at ambient pressure and temperatures near 200 °C. Additionally, confinement of active sites in porous supports is known to radically increase selectivity, coking and sintering resistance, and acid site activity, presenting a possible approach to low-energy polyolefin depolymerization. However, a critical examination of the literature on SZrO led us to a surprising conclusion: despite 40 years of catalytic study, engineering, and industrial use, the surface chemistry of SZrO is poorly understood. Ostensibly spurred by SZrO's impressive catalytic activity, the application-driven study of SZrO has resulted in deleterious ambiguity in requisite synthetic conditions and insufficient characterization of acidity, porosity, and active site structure. Here, this ambiguity has produced significant knowledge gaps surrounding the synthesis, structure, and mechanisms of hydrocarbon activation for optimized SZrO, stunting the potential of this catalyst in olefin cracking and other industrially relevant reactions, such as isomerization, esterification, and alkylation. Toward mitigating these long extant issues, we herein identify and highlight these current shortcomings and knowledge gaps, propose explicit guidelines for characterization of and reporting on characterization of solid acidity, and discuss the potential of pore-confined superacids in the efficient and selective depolymerization of polyolefins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The mechanism for acetate formation in electrochemical CO (2) reduction on Cu: selectivity with potential, pH, and nanostructuring

Nanostructured Cu catalysts have increased the selectivities and geometric activities for high value C–C coupled (C 2 ) products (ethylene, ethanol, and acetate) in the electrochemical CO (2) reduction reaction (CO (2) RR). The selectivity among the high-value C 2 products is also altered, where for instance the yield of acetate increases with alkalinity and is dependent on the catalyst morphology. The reaction mechanisms behind the selectivity towards acetate vs. other C 2 products remain controversial. In this work, we elucidate the reaction mechanism for acetate formation by using ab initio simulations, a coupled kinetic-transport model, and loading dependent experiments. We find that trends in acetate selectivity can be rationalized from variations in electrolyte pH and the local mass transport properties of the catalyst and not from changes in Cu's intrinsic activity. The selectivity mechanism originates from the transport of ketene, a stable (closed shell) intermediate, away from the catalyst surface into solution where it reacts to form acetate. While this type of mechanism has not yet been discussed in the CO (2) RR, variants of it may explain similar selectivity fluctuations observed for other stable intermediates like CO and acetaldehyde. Our proposed mechanism suggests that acetate selectivity increases with increasing pH, decreasing catalyst roughness and significantly varies with the applied potential.

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

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data

Abstract Background The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potential of machine learning models for understanding the connections between soil and biological phenotypes. We investigate an integrative framework performing accurate machine learning-based prediction of plant performance from biological, chemical, and physical properties of the soil via two models: random forest and Bayesian neural network. Results Prediction improves when we add environmental features, such as soil properties and microbial density, along with microbiome data. Different preprocessing strategies show that human decisions significantly impact predictive performance. We show that the naive total sum scaling normalization that is commonly used in microbiome research is one of the optimal strategies to maximize predictive power. Also, we find that accurately defined labels are more important than normalization, taxonomic level, or model characteristics. ML performance is limited when humans can’t classify samples accurately. Lastly, we provide domain scientists via a full model selection decision tree to identify the human choices that optimize model prediction power. Conclusions Our study highlights the importance of incorporating diverse environmental features and careful data preprocessing in enhancing the predictive power of machine learning models for soil and biological phenotype connections. This approach can significantly contribute to advancing agricultural practices and soil health management.

Aghdam, Rosa↗
DOE OSTI2025

Evaluating Short-warning Mitigation via Intentional Robust Disruption of a Hypothetical Impact of Asteroid 2023 NT1

We investigate various short-warning mitigation scenarios via fragmentation for a hypothetical impact of asteroid 2023 NT1, a near-Earth object (NEO) that was discovered on 2023 July 15, two days after its closest approach to Earth on July 13. The asteroid passed by Earth within ∼0.25 lunar distances, with a closest approach of ∼1 × 10 5 km and a velocity of 11.27 km s −1 . Its size remains largely uncertain, with an estimated diameter range of 26–58 m and a most probable estimate of 34 m (JPL Sentry, 2023 September 15; weighted by the NEO size frequency distribution). If 2023 NT1 had collided with Earth, it could have caused significant local damage. Assuming a spherical asteroid with a diameter of 34 m, uniform density of 2.6 g cm −3 , and impact velocity of 15.59 km s −1 , a collision would have yielded an estimated impact energy of ∼1.5 Mt, approximately 3 times the energy of the Chelyabinsk airburst in 2013. We analyze the effectiveness of mitigation via intentional robust disruption for objects similar to 2023 NT1. We utilize Pulverize It (PI), a NASA Innovative Advanced Concepts study of planetary defense via fragmentation, to model potential mitigation scenarios through simulations of hypervelocity asteroid disruption and atmospheric ground effects in the case of a terminal defense mode. Simulations suggest that PI is an effective multimodal approach for planetary defense that can operate in extremely short interdiction modes, in addition to long interdiction timescales with extended warning. Our simulations support the proposition that threats like 2023 NT1 can be effectively mitigated with intercepts of 1 day (or less) prior to impact, yielding minimal to no ground damage.

Asteroids↗
DOE OSTI2026

Connecting ground-state properties of 6 Li to each other and to scattering data

We examine the relationship between the asymptotic normalization coefficient (ANC) of 6 Li and other low-energy observables in the α–deuteron system. Our analysis uses a set of calculations carried out within the ab initio no core shell model with continuum (NCSMC) using a variety of inter-nucleon interactions and basis sizes, and yielding 6 Li deuteron separation energies between 1.3 and 1.8 MeV (Hebborn et al 2022 Phys. Rev. Lett. 129 042503). These NCSMC calculations show that the square of the ANC is strongly correlated with the separation energy over this range. In this work, we investigate the origin of this correlation using the phenomenological R-matrix, a single-channel potential and a perturbative approach. We show that this correlation occurs because the depth of the α–deuteron central potential changes by only a small relative amount as the separation energy varies. We then investigate if the ANC can be accurately extracted from α–deuteron phase shifts in an ideal case in which low-energy data are available and there are no experimental errors. We find that both R-matrix and Coulomb-modified effective-range theory (CM-ERE) yield extracted ANCs close to, although not exactly equal to, the NCSMC value, provided the extrapolation is constrained by the known position of the bound-state pole and at least three terms are included in the fit function. The R-matrix approach converges faster than the CM-ERE as the number of parameters increases and is also more robust against the inclusion of low-energy and high-energy phase shift data. Finally, our study also shows that a naive quantification of uncertainties by comparing different truncations used in both theories is not accurate, and suggests the accuracy of ANCs extracted from phase shift data needs further investigation.

R-matrix↗
DOE OSTI2022

Integrating out beyond tree level and relativistic superfluids

We revisit certain subtleties of renormalization that arise when one derives a low-energy effective action by integrating out the heavy fields of a more complete theory. Usually these subtleties are circumvented by matching some physical observables, such as scattering amplitudes, but a more involved procedure is required if one is interested in deriving the effective theory to all orders in the light fields (but still to fixed order in the derivative expansion). As a concrete example, we study the U(1) Goldstone low-energy effective theory that describes the spontaneously broken phase of a $\phi$ 4 theory for a complex scalar. Working to lowest order in the derivative expansion, but to all orders in the Goldstones, we integrate out the radial mode at one loop and express the low-energy effective action in terms of the renormalized couplings of the UV completion. This yields the one-loop equation of state for the superfluid phase of (complex) $\phi$ 4 . We perform the same analysis for a renormalizable scalar SO(N) theory at finite chemical potential, integrating out the gapped Goldstones as well, and confirm that the effective theory for the gapless Goldstone exhibits no obvious sign of the original SO(N) symmetry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗
DOE OSTI2022

Ferric chloride aided peracetic acid pretreatment for effective utilization of sugarcane bagasse

The synergetic impacts of ferric chloride aided peracetic acid (FPA) pretreatment were investigated to enhance the total biomass utilization through effective cellulose conversion and high-quality lignin production. The sugarcane bagasse pretreatment with 2% peracetic acid (PAA) and 0.1 mol/L ferric chloride (FeCl 3 ) effectively removed 57.3% of lignin and 72.2% of xylan while preserving ~ 97% of cellulose from sugarcane bagasse under mild temperature (90 °C). The FPA pretreated sugarcane bagasse was effectively hydrolyzed with a glucose yield of 313.0 mg/g-biomass, which was 4.5 times higher than the yield of untreated biomass (69.75 mg/g-biomass) and 1.6 and 3.6 times higher than that of individual PAA and FeCl 3 pretreated sugarcane bagasse, respectively. The regenerated lignin (FPA lignin) showed great potential for further valorization by preserving the major interunit linkage (up to 86% of β-O-4) without significant carbohydrate contamination and lignin condensation due to its mild reaction conditions. In this paper, the combination of PAA and FeCl 3 synergistically enhanced the pretreatment efficiency on sugarcane bagasse and resulted in high fermentable sugar and high-quality lignin production.

09 BIOMASS FUELS↗