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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Let’s Stick Together: Interplay of Moisture, Particle Size, and Anatomical Fraction in the Flowability of Corn Stover Crumbles

Handling of agricultural waste biomass feedstocks (such as corn stover) is a persistent challenge in the production of biofuels and chemicals at integrated biorefineries. Inconsistent flowability and high feedstock variability creates equipment downtime and processing challenges. This work investigates the influence of anatomical fractionation and moisture content on the bulk solids handling behavior of corn stover crumbles. A combination of rotational shear testing, tribological measurements, and surface and sorption characterization techniques (inverse gas chromatography (IGC), dynamic vapor sorption (DVS), and electron microscopy) were used to evaluate the contributions of particle composition, size, and surface properties to flow behavior. Shear and frictional testing revealed that moisture content has the greatest effect on flowability, significantly increasing unconfined yield strength (ƒ c ) and reducing the flow function coefficient (F F C), regardless of anatomical fraction. While differences in surface energy were observed between fractions, particularly in polar contributions (γ AB ), these did not correspond to meaningful differences in flow behavior. Coarser 6 mm particles exhibited poorer flow performance than 4 mm crumbles, likely due to broader particle size distributions and increased particle interlocking. Taken together, these results suggest that anatomical fractionation provides minimal benefit from a bulk handling perspective. Moisture content and particle size heterogeneity dominate handling behavior, reinforcing the utility of unfractionated corn stover in processing environments. These insights can inform the design of more efficient and reliable feedstock processing systems for agricultural biomass in integrated biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2024

Startup Physics Testing of Advanced Reactors

This report documents the startup physics testing from initial fuel loading through ascension to full power for past advanced reactor startup physics testing programs. The review includes an assessment of what nuclear physics data was measured, why this data was measured, how was the measurement made, and the agreement with predictive reactor performance calculations of that time. The purpose of this review is to establish historical precedence for test inclusion for future advanced reactors planned for demonstration at the National Reactor Innovation Center (NRIC). The historical review includes reactor designs considered to be significantly different from current light-water reactor designs, or use simplified, inherent, passive, or other innovative means to accomplish their safety functions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Phase Transformation and Lattice Parameter Changes of Non-trivalent Rare Earth-Doped YSZ as a Function of Temperature

To examine the effect of doping/co-doping on high-temperature phase compositions of YSZ, stand-alone YSZ and CeO{sub 2} and Nb{sub 2}O{sub 5} co-doped YSZ samples were prepared using mechanical alloy and high-temperature sintering. XRD analysis was performed on these samples from room temperature to 1100 °C. The results show that the structure for the co-doped samples tends to be thermally stable when the test temperature is higher than a critical value. Monoclinic phase was dominant in Nb{sub 2}O{sub 5} co-doped YSZ at temperatures lower than 600 °C, while for the YSZ and CeO{sub 2} co-doped YSZ, cubic/tetragonal phase was dominant in the whole test temperature range. The lattice parameters for all the samples increase with increasing test temperature generally. The lattice parameters for the two non-trivalent rare earth oxides co-doped YSZ show that the lattice parameter a for the cubic phase of the Ce{sup 4+} co-doped YSZ is consistently greater than that of 7YSZ which is related to the presence of larger radius of Ce{sup 4+} in the matrix. The lattice parameters a, b, c for the monoclinic phase of Ce{sup 4+} co-doped YSZ are much closer to each other than that of the Nb{sup 5+} co-doped YSZ, indicating the former has better tendency to form cubic/tetragonal phase, which is desired for vast engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Gas-Phase Synthesis of a New Functional Hybrid Material on the Basis of Multiwalled Carbon Nanotubes Decorated with Faceted Aluminum Nanocrystals

The deposition of polyhedral aluminum nanocrystals onto the surface of multiwalled carbon nanotubes (MWCNTs) via metalorganic chemical vapor deposition with the use of triisobutylaluminum as the precursor has been performed for the first time. The new hybrid nanomaterial (Al/MWCNTs) has been characterized by X-ray phase analysis, scanning electron microscopy, and high-resolution transmission electron microscopy. The obtained Al/MWCNTs hybrid materials were tested as the filler for the creation of threedimensional composites on the basis of an AMg2 alloy via powder metallurgy. It has been shown that the use of Al/MWCNTs as the filler increases the hardness of the composites by 18% in comparison with the initial MWCNTs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Correlated Trajectory Uncertainty for Adaptive Sequential Decision Making

One of the great challenges with decision making tasks on real world systems is the fact that data is sparse and acquiring additional data is expensive. In these cases, it is often crucial to make a model of the environment to assist in making decisions. At the same time, limited data means that learned models are erroneous, making it just as important to equip the model with good predictive uncertainties. In the context of learning sequential decision making policies, these uncertainties can prove useful for informing which data to collect for the greatest improvement in policy performance \citep{mehta2021experimental, mehta2022exploration} or informing the policy about unsure regions of state and action space to avoid during test time \citep{yu2020mopo}. Additionally, assuming that realistic samples of the environment can be drawn, an adaptable policy can be trained that attempts to make optimal decisions for any given possible instance of the environment \citep{ghosh2022offline, chen2021offline}. In this work, we examine the so-called ``probabilistic neural network'' (PNN) model that is ubiquitous in model-based reinforcement learning (MBRL) works. We argue that while PNN models may have good marginal uncertainties, they form a distribution of non-smooth transition functions. Not only are these samples unrealistic and may hamper adaptability, but we also assert that this leads to poor uncertainty estimates when predicting multiple step trajectory estimates. To address this issue, we propose a simple sampling method that can be implemented on top of pre-existing models.We evaluate our sampling technique on a number of environments, including a realistic nuclear fusion task, and find that, not only do smooth transition function samples produce more calibrated uncertainties, but they also lead to better downstream performance for an adaptive policy.

Offline Reinforcement Learning↗
DOE OSTI2015

Impact Of Sodium Oxalate, Sodium Aluminosilicate, and Gibbsite/Boehmite on ARP Filter Performance

The Savannah River Site (SRS) is currently treating radioactive liquid waste with the Actinide Removal Process (ARP) and the Modular Caustic Side Solvent Extraction Unit (MCU). Recently, the low filter flux through the ARP of approximately 5 gallons per minute has limited the rate at which radioactive liquid waste can be treated. Salt Batch 6 had a lower processing rate and required frequent filter cleaning. Savannah River Remediation (SRR) has a desire to understand the causes of the low filter flux and to increase ARP/MCU throughput. SRR requested SRNL to conduct bench-scale filter tests to evaluate whether sodium oxalate, sodium aluminosilicate, or aluminum solids (i.e., gibbsite and boehmite) could be the cause of excessive fouling of the crossflow or secondary filter at ARP. The authors conducted the tests by preparing slurries containing 6.6 M sodium Salt Batch 6 supernate, 2.5 g MST/L slurry, and varying concentrations of sodium oxalate, sodium aluminosilicate, and aluminum solids, processing the slurry through a bench-scale filter unit that contains a crossflow primary filter and a dead-end secondary filter, and measuring filter flux and transmembrane pressure as a function of time. Among the conclusions drwn from this work are the following: (1) All of the tests showed some evidence of fouling the secondary filter. This fouling could be from fine particles passing through the crossflow filter. (2) The sodium oxalate-containing feeds behaved differently from the sodium aluminosilicate- and gibbsite/boehmite-containing feeds.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Comparison of multigrid algorithms for high‐order continuous finite element discretizations

Summary We present a comparison of different multigrid approaches for the solution of systems arising from high‐order continuous finite element discretizations of elliptic partial differential equations on complex geometries. We consider the pointwise Jacobi, the Chebyshev‐accelerated Jacobi, and the symmetric successive over‐relaxation smoothers, as well as elementwise block Jacobi smoothing. Three approaches for the multigrid hierarchy are compared: (1) high‐order h ‐multigrid, which uses high‐order interpolation and restriction between geometrically coarsened meshes; (2) p ‐multigrid, in which the polynomial order is reduced while the mesh remains unchanged, and the interpolation and restriction incorporate the different‐order basis functions; and (3) a first‐order approximation multigrid preconditioner constructed using the nodes of the high‐order discretization. This latter approach is often combined with algebraic multigrid for the low‐order operator and is attractive for high‐order discretizations on unstructured meshes, where geometric coarsening is difficult. Based on a simple performance model, we compare the computational cost of the different approaches. Using scalar test problems in two and three dimensions with constant and varying coefficients, we compare the performance of the different multigrid approaches for polynomial orders up to 16. Overall, both h ‐multigrid and p ‐multigrid work well; the first‐order approximation is less efficient. For constant coefficients, all smoothers work well. For variable coefficients, Chebyshev and symmetric successive over‐relaxation smoothing outperform Jacobi smoothing. While all of the tested methods converge in a mesh‐independent number of iterations, none of them behaves completely independent of the polynomial order. When multigrid is used as a preconditioner in a Krylov method, the iteration number decreases significantly compared with using multigrid as a solver. Copyright © 2015 John Wiley & Sons, Ltd.

Sundar, Hari↗
DOE OSTI2023

Impact of Pendent Ammonium Groups on Solubility and Cycling Charge Carrier Performance in Nonaqueous Redox Flow Batteries

The synthesis, characterization, electrochemical performance, and theoretical modeling of two base-metal charge carrier complexes incorporating a pendent quaternary ammonium group, [Ni(bppn-Me3)][BF4], 3′, and [Fe(PyTRENMe)][OTf]3, 4’, are described. Both complexes were produced in high yield and fully characterized using NMR, IR, and UV–vis spectroscopies as well as elemental analysis and single-crystal X-ray crystallography. The solubility of 3′ in acetonitrile showed a 283% improvement over its neutral precursor, whereas the solubility of complex 4’ was effectively unchanged. Cyclic voltammetry indicates an ∼0.1 V positive shift for all waves, with some changes in reversibility depending on the wave. Bulk electrochemical cycling demonstrates that both 3′ and 4’ can utilize the second more negative wave to a degree, whereas 4’ ceases to have a reversible positive wave. Flow cell testing of 3′ and 4’ with Fc as the posolyte reveals little improvement to the cycling performance of 3′ compared with its parent complex, whereas 4’ exhibits reductions in capacity decay when cycling either negative wave. Postcycling CVs indicate that crossover is the likely source of capacity loss in complexes 3, 3′, and 4’ because there is little change in the CV trace. Density functional theory calculations indicate that the ammonium group lowers the HOMO energy in 3′ and 4’, which may impart stability to cycling negative waves while making positive waves less accessible. The incorporation of a positively charged species can improve solubility, stored electron density, and capacity decay depending on the complex, features critical to high energy density redox flow battery performance.

25 ENERGY STORAGE↗
DOE OSTI2017

Investigation of a Quantum Monte Carlo Protocol To Achieve High Accuracy and High-Throughput Materials Formation Energies

High-throughput calculations based on density functional theory (DFT) methods have been widely implemented in the scientific community. However, depending on both the properties of interest as well as particular chemical/structural phase space, accuracy even for correct trends remains a key challenge for DFT. In this work, we evaluate the use of quantum Monte Carlo (QMC) to calculate material formation energies in a high-throughput environment. We test the performance of automated QMC calculations on 21 compounds with high quality reference data from the Committee on Data for Science and Technology (CODATA) thermodynamic database. We compare our approach to different DFT methods as well as different pseudopotentials, showing that errors in QMC calculations can be progressively improved especially when correct pseudopotentials are used. We determine a set of accurate pseudopotentials in QMC via a systematic investigation of multiple available pseudopotential libraries. We show that using this simple automated recipe, QMC calculations can outperform DFT calculations over a wide set of materials. Out of 21 compounds tested, chemical accuracy has been obtained in formation energies of 11 structures using our QMC recipe, compared to none using DFT calculations.

Chemistry↗
DOE OSTI2020

A critical examination of compound stability predictions from machine-learned formation energies

Machine learning has emerged as a novel tool for the efficient prediction of material properties, and claims have been made that machine-learned models for the formation energy of compounds can approach the accuracy of Density Functional Theory (DFT). The models tested in this work include five recently published compositional models, a baseline model using stoichiometry alone, and a structural model. By testing seven machine learning models for formation energy on stability predictions using the Materials Project database of DFT calculations for 85,014 unique chemical compositions, we show that while formation energies can indeed be predicted well, all compositional models perform poorly on predicting the stability of compounds, making them considerably less useful than DFT for the discovery and design of new solids. Most critically, in sparse chemical spaces where few stoichiometries have stable compounds, only the structural model is capable of efficiently detecting which materials are stable. The nonincremental improvement of structural models compared with compositional models is noteworthy and encourages the use of structural models for materials discovery, with the constraint that for any new composition, the ground-state structure is not known a priori. This work demonstrates that accurate predictions of formation energy do not imply accurate predictions of stability, emphasizing the importance of assessing model performance on stability predictions, for which we provide a set of publicly available tests.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Cobalt oxide-coated N- and B-doped graphene hollow spheres as bifunctional electrocatalysts for oxygen reduction and oxygen evolution reactions

Here, a simple and scalable method has been developed for the synthesis of Co 3 O 4 -coated N- and B-doped graphene hollow spheres (Co 3 O 4 /NBGHSs). These Co 3 O 4 /NBGHSs are highly active for both oxygen reduction and evolution reactions and can exhibit higher electrocatalytic activities and better durability than commercial Pt/C and RuO 2 /C, respectively, demonstrating them to be efficient bi-functional electrocatalysts. In-depth analysis shows that the coupling between Co 3 O 4 and NBGHSs, strong interaction with adsorbed O 2 , high electric conductivity, and the specific hollow structure play important roles in imparting the higher electrocatalytic activities to the Co 3 O 4 /NBGHSs. When tested as cathode catalysts for Zn–air batteries, the Co 3 O 4 /NBGHSs exhibit better performance and higher stability than the Pt/C catalyst and other catalysts reported previously. Lastly, this strongly suggests that the Co 3 O 4 /NBGHSs could be used as efficient electrocatalysts for metal–air batteries with great potential to replace precious metal/carbon based materials.

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

CONTROLLED END GAS AUTO IGNITION WITH EXHAUST GAS RECIRCULATION ON A STOICHIOMETRIC, SPARK IGNITED, NATURAL GAS ENGINE

The goal of this study is to address fundamental limitations to achieving diesel-like efficiencies in heavy duty on-highway natural gas (NG) engines. Engine knock and misfire are barriers to pathways leading to higher efficiency engines. This study explores enabling technologies for development of high efficiency stoichiometric, spark ignited, natural gas engines. These include design strategies for fast and stable combustion and higher dilution tolerance. Additionally, advanced control methodologies are implemented to maintain stable operation between knock and misfire limits. To implement controlled end- gas autoignition (C-EGAI) strategies a Combustion Intensity Metric (CIM) is used for ignition control with the use of a Woodward large engine control module (LECM). Tests were conducted using a single cylinder, variable compression ratio, cooperative fuel research (CFR) engine with baseline conditions of 900 RPM, engine load of 800 kPa indicated mean effective pressure (IMEP), and stoichiometric air/fuel ratio. Exhaust gas recirculation (EGR) tests were performed using a custom EGR system that simulates a high pressure EGR loop and can provide a range of EGR rates from 0 to 40%. The experimental measurements included the variance of EGR rate, compression ratio, engine speed, IMEP, and CIM. These five variables were optimized through a Modified Box- Benken design Surface Response Method (RSM), with brake efficiency as the merit function. A positive linear correlation between CIM and f-EGAI was identified. Consequently, CIM was used as the feedback control parameter for C-EGAI. As such, implementation of C-EGAI effectively allowed for the utilization of high EGR rates and CRs, controlling combustion between a narrower gap between knock and lean limits. The change from fixed to parametric ignition timing with CIM targeted select values of f-EGAI with an average coefficient of variance (COV) of peak pressure of 5.4. The RSM efficiency optimization concluded with operational conditions of 1080 RPM, 1150 kPa IMEP, 10.55:1 compression ratio, and 17.8% EGR rate with a brake efficiency of 21.3%. At this optimized point of peak performance, a f-EGAI for C-EGAI was observed at 34.1% heat release due to auto ignition, a knock onset crank angle value of 10.3° aTDC and ignition timing of - 24.7° aTDC. This work has demonstrated that combustion at a fixed f-EGAI can be maintained through advanced ignition control of CIM without experiencing heavy knocking events.

Cooperative Fuel Research Engine, Auto Ignition, E↗
DOE OSTI2017

High Performance Building Mockup in FLEXLAB

Genentech has ambitious energy and indoor environmental quality performance goals for Building 35 (B35) being constructed by Webcor at the South San Francisco campus. Genentech and Webcor contracted with the Lawrence Berkeley National Laboratory (LBNL) to test building systems including lighting, lighting controls, shade fabric, and automated shading controls in LBNL’s new FLEXLAB facility. The goal of the testing is to ensure that the systems installed in the new office building will function in a way that reduces energy consumption and provides a comfortable work environment for employees.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Real Time and Forecasted DLR: Use Cases

This document contains two use cases for the utilization of dynamic line ratings in operational practices. These use cases were developed in support of the Transmission Optimization and Grid Enhancing Technology (TOGETS) task force aimed at facilitating the deployment of dynamic line rating and power flow technologies across the United States. The project included a demonstration of the technology on the Idaho National Laboratory system. The procurement documents, tests scripts, and field-validated results from multiple vendors will be published to improve industry’s familiarity with the products. Because of the urgency in performing this work and INL’s unique test setup, the Task Force identified a need for additional public information on the information exchanges required for operationalizing DLR (i.e. integrating DLR’s within actual system operations). As such, this use case document and an accompanying interoperability profile have been developed with input from the Task Force and various vendors whose systems would ultimately support the functionality described. The use case and interoperability profile support two distinct functionalities with different purposes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

On the Feasibility of Tailoring Copper–Nickel Functionally Graded Materials Fabricated through Laser Metal Deposition

In this study, pulse-width modulation of laser power was identified as a feasible means for varying the chemical gradient in copper–nickel-graded materials. Graded material deposits of 70 wt. %. copper-30 wt. %. nickel on 100 wt. %. nickel and vice versa were deposited and characterized. The 70/30 copper–nickel weight ratio in the feedstock powder was achieved through blending elemental copper and 96 wt. %. Ni–Delero-22 alloy. At the dissimilar material interface over the course of four layers, the duty cycle of power was ramped down from a high value to optimized deposition conditions. This change was theorized to influence the remelting and deposition height, and by extension, vary the chemistry gradient. X-ray Energy Dispersive Spectroscopy (EDS) analysis showed significant differences in the span and nature of chemistry gradient with varying duty cycles. These observations were also supported by the variation in microhardness values across the interface. The influence of different chemistry gradients on the tensile performance was observed through mini-tensile testing, coupled with Digital Image Correlation (DIC). The strain fields from the DIC analysis showed variations in strain for different chemistry gradients. The strength measurements from these specimens were also different for different chemistry gradients. The site of failure was observed to always occur within the copper-rich region.

36 MATERIALS SCIENCE↗
DOE OSTI2026

First evaluation of the tracking performance of the ARCADIA Fully Depleted MAPS with 120 GeV proton beam

This work presents test beam characterization of the ARCADIA Main Demonstrator 3, a 200 $μ$m thick Fully Depleted MAPS developed using a custom LFoundry 110 nm CIS process on a high-resistivity substrate. Measurements using a 120 GeV proton beam demonstrate a detection efficiency exceeding 99% and a spatial resolution down to 3.8 $μ$m. The study evaluates cluster size, spatial resolution, and efficiency as a function of the threshold, front-end currents, and backside bias voltage.

Rignanese, M. [Padua U.; INFN, Padua]↗
DOE OSTI2016

Concept of an upright wearable positron emission tomography imager in humans

Abstract Background Positron Emission Tomography ( PET ) is traditionally used to image patients in restrictive positions, with few devices allowing for upright, brain‐dedicated imaging. Our team has explored the concept of wearable PET imagers which could provide functional brain imaging of freely moving subjects. To test feasibility and determine future considerations for development, we built a rudimentary proof‐of‐concept prototype (Helmet_ PET ) and conducted tests in phantoms and four human volunteers. Methods Twelve Silicon Photomultiplier‐based detectors were assembled in a ring with exterior weight support and an interior mechanism that could be adjustably fitted to the head. We conducted brain phantom tests as well as scanned four patients scheduled for diagnostic F 18‐ FDG PET / CT imaging. For human subjects the imager was angled such that field of view included basal ganglia and visual cortex to test for typical resting‐state pattern. Imaging in two subjects was performed ~4 hr after PET / CT imaging to simulate lower injected F 18‐ FDG dose by taking advantage of the natural radioactive decay of the tracer (F 18 half‐life of 110 min), with an estimated imaging dosage of 25% of the standard. Results We found that imaging with a simple lightweight ring of detectors was feasible using a fraction of the standard radioligand dose. Activity levels in the human participants were quantitatively similar to standard PET in a set of anatomical ROI s. Typical resting‐state brain pattern activation was demonstrated even in a 1 min scan of active head rotation. Conclusion To our knowledge, this is the first demonstration of imaging a human subject with a novel wearable PET imager that moves with robust head movements. We discuss potential research and clinical applications that will drive the design of a fully functional device. Designs will need to consider trade‐offs between a low weight device with high mobility and a heavier device with greater sensitivity and larger field of view.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Adiabatic-connection fluctuation-dissipation DFT for the structural properties of solids—The renormalized ALDA and electron gas kernels

We present calculations of the correlation energies of crystalline solids and isolated systems within the adiabatic-connection fluctuation-dissipation formulation of density-functional theory. We perform a quantitative comparison of a set of model exchange-correlation kernels originally derived for the homogeneous electron gas (HEG), including the recently introduced renormalized adiabatic local-density approximation (rALDA) and also kernels which (a) satisfy known exact limits of the HEG, (b) carry a frequency dependence, or (c) display a 1/k{sup 2} divergence for small wavevectors. After generalizing the kernels to inhomogeneous systems through a reciprocal-space averaging procedure, we calculate the lattice constants and bulk moduli of a test set of 10 solids consisting of tetrahedrally bonded semiconductors (C, Si, SiC), ionic compounds (MgO, LiCl, LiF), and metals (Al, Na, Cu, Pd). We also consider the atomization energy of the H{sub 2} molecule. We compare the results calculated with different kernels to those obtained from the random-phase approximation (RPA) and to experimental measurements. We demonstrate that the model kernels correct the RPA’s tendency to overestimate the magnitude of the correlation energy whilst maintaining a high-accuracy description of structural properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗