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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Chromium and Vanadium Incorporation in Sulfate-Containing Sodium Aluminoborosilicate Glass

In the composition space for Hanford low-activity nuclear waste glass, the waste loading of some formulations is limited by poor incorporation of sulfate. In particular, certain elements identified in previous studies tend to raise or lower sulfate solubility in borosilicate glass. The aim of the current study is to understand how vanadium and chromium each affect a sulfate-containing sodium aluminoborosilicate glass structure. Glass transition temperature, mass density, visible absorption, and Raman scattering were measured to investigate changes in the glass structure. Both Cr6+ (CrO42-) and Cr3+ were found in the chromium-containing glasses while vanadium primarily existed in the 5+ oxidation state in the vanadium-containing glasses. Electron probe microanalysis determined elemental compositions to assess retention of components. Increasing Cr2O3 caused saturation of Cr concentration within the glass and formation of crystalline eskolaite (Cr2O3). On the other hand, all the targeted V was incorporated into the glass. A fraction of batched S was not incorporated in any glass, presumably due to volatilization during melting. Apparently, the details of incorporation of Cr, and to an extent V, are different depending on whether sulfur is added as in this study or in oversaturated conditions as described in the literature, where Cr partitions to a sulfate-containing salt phase.

Borosilicate glass, Waste Glass, vanadium chemistr↗
DOE OSTI2022

Measurement Acceptance Region (MAR) Assessment Results Based On Sludge Batch 10 Projections from December 2021, February 2022 and August 2022

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26F, Alternate Feed Stock-2 and Sodium Reactor Experiment material from H-Canyon. Frit 473 (8B 2 O 3 -8Li 2 O-5Na 2 O-79SiO 2 , in weight percent) was recommended for sludge-only (SO) and coupled processing with the Salt Waste Processing Facility (SWPF) based on previous assessments of SB10 projections with the DWPF Product Composition Control System (PCCS) glass property models and their associated Measurement Acceptance Region (MAR) constraints. Due to the lower processing rate of Sludge Batch 9 (SB9), the heel in Tank 40 is anticipated to be greater than 40 inches at the projected start of SB10 processing to meet the upcoming Accelerated Basin Deinventory addition dates in Tank 51 for Sludge Batch 11. In December 2021 and February 2022, Savannah River Remediation System Planning provided updated SB10 Tank 40 blend projections based on heels of 74 inches, 84 inches, 94 inches and 103.4 inches. Savannah River Mission Completion (SRMC) subsequently pursued Wash Cycle Y to further reduce the total sulfur in the sludge batch and increase processing flexibility at DWPF. In August 2022, SRMC System Planning provided an updated SB10 Tank 40 blend projection with a 76 inch-heel representing Decant Y2 and 60 kilogallons of bearing water inleakage that is anticipated during the Tank 51 to Tank 40 transfer. The objectives of this task were to: • Determine the impact on the operating windows for SO and coupled processing • Determine whether any composition gaps exist between the already completed SB10 variability study and the reprojected SB10 glass composition region • Compare the SB10 reprojected glass composition region to the DWPF PCCS model development and validation ranges to ensure that compositional gaps do not exist between the data sets. This report documents the results of these evaluations. Calculation-based frit assessments were performed using the DWPF PCCS glass property models and their associated MAR constraints. Evaluated parameters for coupled processing included the following transfer volumes per Sludge Receipt and Adjustment Tank batch: 5700 gallons of Tank 40 sludge, 2400-4500 gallons of the SWPF monosodium titanate (MST) and sludge solids stream, and 15,000 gallons of strip effluent. Based on these MAR assessment results, Frit 473 remains viable for SB10 processing. A target waste loading (WL) of 36% is possible for SO operation and single strike (0.4 g/L MST) coupled processing up to 600 mg/L of SB9 insoluble sludge solids at a nominal transfer volume of ~2800 gallons. Increasing the single strike transfer volume to 4500 gallons may reduce the maximum WL below 40%. Operating windows are 12 percentage points for SO processing and 14-16 percentage points for coupled processing. Frit 625 allows for a target WL of 36% and is acceptable for use during the SB9 to SB10 transition to deplete remaining inventory as needed. Operating windows are 8 percentage points for SO processing and 12-14 percentage points for coupled processing. Predictive PCCS evaluations performed at DWPF will provide insight into batch-specific acceptability at desired WLs for compositions having expected oxide ratios during processing versus the extreme vertices (corner points) evaluated in this study. The reprojected SB10 glass composition region generally overlaps the previously evaluated SB10 variability study composition region. Thus, the minor composition shift of these updated SB10 projections indicates that no additional glasses are necessary to demonstrate acceptability relative to the chemical durability of the Environmental Assessment benchmark glass and predictability using the current PCCS models for durability. Based on a comparison of the PCCS model development and validation data to the reprojected SB10 glass composition region, the viscosity and liquidus temperature models will reliably predict SB10 compositions. No additional glasses are necessary to demonstrate predictability of these models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

A chemical-recovery-free ammonium sulfite-based alkali pretreatment of corn stover for low-cost sugar production via fertilizer use of waste liquor

The production of cellulosic sugars is a pivotal strategy for advancing biomass bioconversion. This study evaluated the pretreatment of corn stover using ammonium sulfite and potassium hydroxide to develop comprehensive data on sugar, lignin, chemicals, and overall mass recovery profiles in a batch reactor at 80 °C. The results indicated significant improvements in delignification, deacetylation, enzymatic digestibility, and overall sugar yield. Specifically, pretreating corn stover with a solution of 40 wt% potassium hydroxide and 15 wt% ammonium sulfite at 80 °C for 2 h achieved 78.9 % lignin removal and 82.1 % acetyl removal, resulting in a total sugar yield exceeding 87.5 % with an enzyme loading of 12.5 mg protein/g-glucan plus xylan. The pretreated spent liquor, containing ammonium, potassium, sulfur, biomass-derived organics, and inorganics, demonstrated substantial potential as a fertilizer. The techno-economic analysis projected a minimum sugar selling price of $0.285 per pound, supporting the ongoing development and implementation of chemical-recovery-free pretreatment technology.

09 BIOMASS FUELS↗
DOE OSTI2020

The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism

Here, we present scalable hybrid-parallel algorithms for training large-scale 3D convolutional neural networks. Deep learning-based emerging scientific workflows often require model training with large, high-dimensional samples, which can make training much more costly and even infeasible due to excessive memory usage. We solve these challenges by extensively applying hybrid parallelism throughout the end-to-end training pipeline, including both computations and I/O. Our hybrid-parallel algorithm extends the standard data parallelism with spatial parallelism, which partitions a single sample in the spatial domain, realizing strong scaling beyond the mini-batch dimension with a larger aggregated memory capacity. We evaluate our proposed training algorithms with two challenging 3D CNNs, CosmoFlow and 3D U-Net. Our comprehensive performance studies show that good weak and strong scaling can be achieved for both networks using up to 2K GPUs. More importantly, we enable training of CosmoFlow with much larger samples than previously possible, realizing an order-of-magnitude improvement in prediction accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

PDQ Users Manual Version 1 for PDQ Code Version 1.12

PDQ is a tool for the management of the input and execution of batch jobs for simulation codes that use a text based input system. It accomplishes this goal by operating at two levels. First, it takes input file templates (commonly known at LANL as input deck templates) and creates multiple instantiations by performing substitutions of data from table files into symbols (variables) found in the template. Second, it provides commands to submit the created files to the SLURM batch system for execution. These two activities taken together produce a whole that is greater than the sum of its parts and provides an elegant way of executing studies across multiple similar simulations while minimizing the risk of typographical errors in the input files.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Tradeoffs and Variability of Mechanical Properties in Cold Worked 21-9-6 Stainless Steel Bars

Sub-standard yield stress in a batch of 21-9-6 stainless steel (Nitronic 40) bars was observed while other batches passed requirements. This material requires enhanced property uniformity due to its application in critical components and therefore has tighter restrictions on alloying elements. Using tensile testing, this study investigates the distribution of yield and ductility across bar geometry for three lots of material and is corroborated alongside Vickers microhardness profiles.

Estrada, Micah Garnet Watson↗
DOE OSTI2021

Specialty chemicals production case study: Economic analysis of modular chemical process intensification versus conventional stick‐built approaches

Abstract The beneficial synergies of chemical process intensification and plant modularization present a unique step‐wise advancement opportunity for many chemical manufacturers, but economic case studies are needed to raise awareness of such opportunities. The primary objective of this case study is to better understand the business case economics of a specialty chemical plant using modular chemical process intensification (MCPI), by comparing it with that of a conventional stick‐built (CSB) plant that produces the same product at the same production capacity. When comparing MCPI against CSB approaches for a plant project strategy decision, analysts should thoroughly understand and model the differences and similarities in scope bases. The MCPI approach for this case study benefitted from dramatic reductions in capital expenditures (CAPEX). A sizeable reduction in plant spatial volume likely explains some of these reductions. Sizeable operational expenditure (OPEX) reductions with the MCPI plant appear to be associated with the reduced operator staffing required from converting a labor‐intensive batch process into an automated, continuous flow process. Traditional project investment economic measures strongly favored the MCPI case for the design, construction, and operation of the specialty chemical plant. The net present value for the MCPI case was nearly twice that for the CSB case over a ten‐year period, and the payback period for the CSB case was nearly five times longer than that of the MCPI case. The opinion‐based perspective of the study participant identified significant contributors to superior MCPI economic performance for this case study. With the two conditions of low MCPI CAPEX and high product profit margin, economic analysis indicates that incorporation of a backup MCPI train, for operational redundancy when downtime occurs, is a very beneficial strategy.

O'Connor, James T.↗
DOE OSTI2020

Dispersible Colloid Facilitated Release of Organic Carbon From Two Contrasting Riparian Sediments

In aqueous systems, including groundwater, nano-colloids (1–100 nm diameter) and small colloids (<450 nm diameter) provide a vast store of surfaces to which organic carbon (OC) can sorb, precluding its normal bioavailability. Because nanomaterials are ubiquitous and abundant throughout Earth systems, it is reasonable that they would play a significant role in biogeochemical cycles. As such, mineral nano-colloids (MNC) and small colloids, formed through mineral weathering and precipitation processes, are both an unaccounted-for reservoir and unquantified vector for transport of OC and nutrients and contaminants within watersheds. Water extractions and leaching experiments were conducted under (1) aerobic (ambient) and (2) anaerobic (environmental chamber) conditions for each of two contrasting riparian sediments from (1) Columbia River, Washington and (2) Tims Branch, South Carolina. Water dispersible colloid-adsorbed OC was as high as 48% of OC for Tims Branch anaerobic batch water extraction and as low as 0% for Columbia River aerobic batch water extractions. Anaerobic leaching from column experiments yielded higher colloid and OC release rates. Transmission electron microscopy with electron dispersive spectroscopy mapping revealed organic carbon associated with aggregations of nano-particulate silicate minerals and Mossbauer identified nano-particulate goethite. This exploratory study demonstrates that mineral facilitated release of OC in riparian sediments is both significant and variable between locations.

Rod, Kenton A.↗
DOE OSTI2025

Evaluation of the absolute single-photon detection efficiency of HRPPD

Pixelated High Rate Picosecond Photon Detectors (HRPPDs) by Incom Inc. are promising photosensors for use in Ring Imaging CHerenkov (RICH) detectors, where a high gain, sub-mm position resolution and sub-100ps timing resolution are required in a single photon mode. Quantum Efficiency (QE) has been measured for the first batch of EIC HRPPDs both by Incom and EIC research groups at Jefferson Lab and Brookhaven Lab, with peak values at ∼365 nm typically exceeding 30%. Furthermore, in this study, we present a first direct measurement of Photon Detection Efficiency being equal to (17.1 ± 0.1 [stat] ± 0.3 [sys])% at 398.6 nm, for a pixel near the center of HRPPD, in a photoelectron pulse counting mode using a picosecond diode laser. HRPPD QE at the same spot and at the same wavelength was evaluated to be (24.4 ± 0.1 [stat] ± 0.3 [sys])%, leading to a Collection Efficiency estimate of (70.3 ± 1.6)%, which is consistent with the expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Efficient Parameterization of Density Functional Tight-Binding for 5 f -Elements: A Th–O Case Study

Density functional tight binding (DFTB) models for f-element species are challenging to parametrize owing to the large number of adjustable parameters. The explicit optimization of the terms entering the semiempirical DFTB Hamiltonian related to f orbitals is crucial to generating a reliable parametrization for f-block elements, because they play import roles in bonding interactions. However, since the number of parameters grows quadratically with the number of orbitals, the computational cost for parameter optimization is much more expensive for the f-elements than for the main group elements. In this work we present a set of efficient approaches for mitigating the hurdle imposed by the large size of the parameter space. A novel group-by-orbital correction functions for two-center bond integrals was developed. With this approach the number of parameters is reduced, and it grows linearly with the number of elements, maintaining the accuracy and the number of parameters, in the case of f elements, by more than 40%. The parameter optimization step was accelerated by means of the mini-batch BFGS method. This method allows parameter optimizations with much larger training sets than other single batch methods. A stochastic optimizer was employed that helped overcome shallow local minima in the objective function. The proposed algorithm was used to parametrize the DFTB Hamiltonian for the Th–O system, which was subsequently applied to the study of ThO 2 nanoparticles. The training set consisted of 6322 unique structures, which is barely feasible with conventional optimization methods. The optimized parameter set, LANL-ThO, displays good agreement with DFT-calculated properties such as energies, forces, and structures for both clusters and bulk ThO 2 . Benefiting from the fewer number of parameters and lower computational costs for objective function evaluations, this new approach shows its potential applications in DFTB parametrization for elements with high angular momentum, which present a challenge to conventional methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Upcycling plastic waste into polyhydroxyalkanoates with high carbon conversion via CO 2 plasma-enabled deconstruction

Plastic deconstruction into fermentable intermediates is a key step for microbial bio-upcycling into value-added products. In this study, CO 2 plasma deconstruction was used as an electrified route to convert polyethylene into oxygenated intermediates and liquid (OIL). The resulting OIL was rich in fatty acids, fatty alcohols, and hydrocarbons, making it a suitable feedstock for medium-chain-length polyhydroxyalkanoate (mcl-PHA) production by Pseudomonas putida NRRL B-14688 and Pseudomonas resinovorans NRRL B-2649. Compared with batch fermentation and monocultures, fed-batch co-cultivation markedly improved biomass formation and PHA accumulation, likely due to complementary substrate utilization, particularly hydrocarbon conversion by P. resinovorans. Using virgin polyethylene-derived OIL (Vir-OIL), the co-culture achieved 40.11% mcl-PHA content and about 18% PHA yield based on total OIL fed. More importantly, OIL produced from post-consumer single-use plastic films (PCR-OIL) was directly fermented and well supported the cell growth and PHA accumulation, achieving 38.11% PHA content and about 14.7% PHA yield. Based on emulsified OIL fractions, PHA yields for Vir-OIL and PCR-OIL were comparable (∼28%). PHA granules were extracted from PCR-OIL-grown cells with high recovery (88.25%) and purity (94.8%). Five monomers were identified in the polymer, including 3-hydroxyhexanoate (3HHx), 3-hydroxyoctanoate (3HO), 3-hydroxydecanoate (3HD), 3-hydroxydodecanoate (3HDD), and 3-hydroxytetradecanoate (3HTD), with 3HO (44.28%) and 3HD (40.60%) as the dominant units. The polymer exhibited moderate molecular weight and narrow dispersity (M n = 65.4 kDa, M w = 92.1 kDa, Đ = 1.40) and low crystallinity (T m ≈ 76.6 °C, X c ≈ 15.5%). These characteristics indicate elastomer-like behavior, making the material suitable for flexible applications such as films, coatings, adhesives, and blend modifiers. Overall, this study establishes a CO 2 plasma-assisted route for generating fermentable polyethylene-derived intermediates and demonstrates that fed-batch co-culture fermentation can effectively funnel plastic-derived carbon into mcl-PHA.

42 ENGINEERING↗
DOE OSTI2024

Hydrothermal solubility of Dy hydroxide as a function of pH and stability of Dy hydroxyl aqueous complexes from 25 to 250 °C

The rare earth elements (REE) have important applications in green energy technologies. The formation of mineral deposits in geologic systems commonly involves hydrothermal fluids which can mobilize the REE. However, the REE speciation is not well known as a function of pH. The thermodynamic properties of REE hydroxyl complexes used in geochemical models are based on the Helgeson-Kirkham-Flowers (HKF) equation of state parameters which were derived by extrapolation of low temperature experimental and estimated data. In this study, Dy hydroxide solubility experiments are combined with available literature data to improve these models from 25 to 250 °C and optimize the thermodynamic properties of Dy 3+ and Dy hydroxyl complexes using GEMSFITS. Batch-type solubility experiments were conducted from 150 to 250 °C and at saturated water vapor pressure in perchloric acid solutions with initial pH values of 2 to 5 in 0.5 pH unit increments. The measured solubility of Dy hydroxide is retrograde with temperature and decreases with pH. The logarithm of total dissolved Dy molality ranges from –2.3 to –5.3 at 150 °C (pH 4.7–5.5), from –2.4 to –5.6 at 200 °C (pH 3.9–5.1), and from –3.7 to –6.9 at 250 °C (pH of 3.4 and 5.0). The optimized standard partial molal Gibbs energies of formation (Δ f G° T ) derived for Dy 3+ and DyOH 2+ display a close to linear relationship with temperature, fitting with previous optimizations based on DyPO 4 solubility data in the literature. A comparison of the optimized ΔfG°T values for aqueous Dy species with predictions from available HKF parameters indicates significant differences ranging from +11 to –26 kJ/mol between 25 and 250 °C. The experimental fits are used to derive the Dy hydroxide solubility products (K s0 ) and formation constants for the hydrolysis of Dy (β n with n = 1 to 3; Dy 3+ + nOH – = DyOH n 3-n ) as a function of temperature. The optimization method presented yields accurate thermodynamic properties for the Dy 3+ aqua ions and the DyOH 2+ species at the acidic to mildly acidic pH studied whereas more experimental work is needed at near-neutral and alkaline conditions to better constrain the other hydroxyl complexes. Furthermore, the optimized thermodynamic data have a significant impact on geochemical modeling of the mobility and solubility of REE minerals in acidic hydrothermal fluids.

58 GEOSCIENCES↗
DOE OSTI2021

CsPbI 3 Nanocrystals Go with the Flow: From Formation Mechanism to Continuous Nanomanufacturing

Despite the groundbreaking advancements in the synthesis of inorganic lead halide perovskite (LHP) nanocrystals (NCs), stimulated from their intriguing size-, composition-, and morphology-dependent optical and optoelectronic properties, their formation mechanism through the hot-injection (HI) synthetic route is not well-understood. Here in this work, for the first time, in-flow HI synthesis of cesium lead iodide (CsPbI 3 ) NCs is introduced and a comprehensive understanding of the interdependent competing reaction parameters controlling the NC morphology (nanocube vs nanoplatelet) and properties is provided. Utilizing the developed flow synthesis strategy, a change in the CsPbI 3 NC formation mechanism at temperatures higher than 150 °C, resulting in different CsPbI 3 morphologies is revealed. Through comparison of the flow- versus flask-based synthesis, deficiencies of batch reactors in reproducible and scalable synthesis of CsPbI 3 NCs with fast formation kinetics are demonstrated. The developed modular flow chemistry route provides a new frontier for high-temperature studies of solution-processed LHP NCs and enables their consistent and reliable continuous nanomanufacturing for next-generation energy technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Preliminary IHLW Formulation Algorithm Description

This report documents the initial algorithm that could be used by the Waste Treatment and Immobilization Plant (WTP) in batching high-level waste (HLW) and glass-forming chemicals (GFCs) in the HLW melter feed preparation vessel (MFPV) (HFP-VSL-00001 and -00005). Not all Hanford tank waste can be accommodated by the models developed for this report and significant expansion of the model boundaries could be achievable to reduce the WTP mission life and total canister production count. The immobilized HLW (IHLW) must meet a series of constraints to be acceptable for disposal in the Monitored Geologic Repository, which are contained in the Specification 1 of the Contract (DOE 2000), the Waste Acceptance Product Specifications (WAPS, DOE 1996), and the Waste Acceptance System Requirements Document (WASRD, DOE 2007). The IHLW Waste Form Compliance Plan (WCP, 24590-HLW-PL-RT-07-0001, Rev 3) specifies that the formulation algorithm will be developed and used to comply with the constraints associated with glass composition and properties. This report is not an engineering calculation, does not provide design input, and is not an engineering study. Algorithm inputs include the chemical analyses of the blended HLW in the HLW blend vessel (HBV) (HLP-VSL-00028, the volume and composition of the MFPV heel, the volume and composition of the MFPV after waste addition, the volume and composition of MFPV batch after GFC addition, the compositions of individual GFCs, and the mass of glass in each canister. In addition to these inputs, uncertainties in the HLW composition and processing parameters are included in the algorithm. Using the above inputs, the algorithm calculates the following outputs: 1) the volume of HLW to be transferred from the HBV to the MFPV, 2) the mass of each GFC for addition to the MFPV, 3) the composition of the glass that will be produced along with uncertainties, and 4) the predicted properties, with associated uncertainties, of the resulting IHLW. The algorithm uses the property-composition models to calculate properties with associated uncertainties and compares them with various constraints to ensure that a processable feed is formulated and a compliant IHLW is produced. The GFC additions are determined using an optimization approach to provide high confidence that the HLW glass will meet all product quality requirements and key processing constraints. For most HLW batches there are many possible glass compositions that meet all constraints. In these cases, the glass composition is optimized for a series of target component concentrations and target property values. The algorithm also incorporates process measurement and product quality uncertainties, based on the work of Piepel et al. (2005). Estimates of the various process and measurement uncertainties that affect glass compositions and predicted glass properties have been previously reported (Piepel et al. 2005, 2006) and the impacts of these estimated uncertainties on the IHLW composition envelope that meets product quality and processing-related properties with sufficient confidence were evaluated. The details of work performed to date to develop this initial GFC addition and batching algorithm are summarized in Sections 4 and 5. An example data set is used to illustrate the calculations of the algorithm summarized in Section 6. Finally, in Section 7, there is a statement of the required work to achieve a final operational IHLW formulation control algorithm. This report is not an engineering calculation, does not provide design input, and is not an engineering study.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Microbial potentiometric sensor technology for real-time detecting and monitoring of toxic metals in aquatic matrices

Considering that toxic metals can affect metabolic processes in microorganisms adversely, it can be hypothesized that these metals in water matrices would induce a decrease in metabolic activity of the biofilm microorganisms populating the surface of a sensing electrode, which could be registered as a change in the open-circuit potential (OCP) generated by the biofilm microorganisms. The goal of this study was to test this hypothesis and demonstrate the underlying principle that microbial potentiometric sensor (MPS) technology could be used for long-term and real-time monitoring and detection of rapid changes in metal concentrations in realistic aquatic environments. To address the goal, four objective were addressed: (1) a batch reactor with three graphite-based MPS electrodes was fabricated; (2) a set of single-ion solutions and one multiple ion solution were prepared reflecting realistic concentrations of metals found in electroplating wastewaters; (3) the responses of the MPS to the simultaneous presence of multiple toxic metal ions in a single solution were measured; and (4) the changes of the MPS signals to the presence of individual metal ion solutions were examined. While the hypothesis was validated, the study also revealed that the MPS was sufficiently sensitive to not only detect, but also quantify, toxic metal ion concentrations in aqueous solutions. The coefficients of determination, which were R 2 > 0.995, and responsiveness of <1 μmol/L for some toxic metal cations, strongly support the performance of MPS technology in the echelons of expensive analytical tools capable detecting and measuring trace elements.The magnitude of the MPS response was toxic metal specific. When the molar concertation normalizes the inhibition portion of the signal area, the assessed sensitivity order was: Se>Cd>Pb>Ag>Ni> Zn. The study provides valuable information for enforcement agents, environmental professionals, and wastewater treatment operators, so toxic metal pollution and its detrimental impacts can be prevented and mitigated.

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

PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein–protein interaction network

Abstract Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover new synergistic drug combinations due to the combinatorial explosion. Deep learning technology holds immense promise for better prediction of in vitro synergistic drug combinations for certain cell lines. In methods applying such technology, omics data are widely adopted to construct cell line features. However, biological network data are rarely considered yet, which is worthy of in-depth study. In this study, we propose a novel deep learning method, termed PRODeepSyn, for predicting anticancer synergistic drug combinations. By leveraging the Graph Convolutional Network, PRODeepSyn integrates the protein–protein interaction (PPI) network with omics data to construct low-dimensional dense embeddings for cell lines. PRODeepSyn then builds a deep neural network with the Batch Normalization mechanism to predict synergy scores using the cell line embeddings and drug features. PRODeepSyn achieves the lowest root mean square error of 15.08 and the highest Pearson correlation coefficient of 0.75, outperforming two deep learning methods and four machine learning methods. On the classification task, PRODeepSyn achieves an area under the receiver operator characteristics curve of 0.90, an area under the precision–recall curve of 0.63 and a Cohen’s Kappa of 0.53. In the ablation study, we find that using the multi-omics data and the integrated PPI network’s information both can improve the prediction results. Additionally, the case study demonstrates the consistency between PRODeepSyn and previous studies.

Wang, Xiaowen↗
DOE OSTI2020

An acidic polysaccharide (AGC3) isolated from North American ginseng ( Panax quinquefolius ) suspension culture as a potential immunomodulatory nutraceutical

Polysaccharides isolated from Panax quinquefolius roots are widely used as nutraceuticals due to their immunomodulatory properties. Despite their popularity, several challenges exist in isolating ginseng root polysaccharides such as batch-to-batch structural inconsistencies and bacterial endotoxin contamination. A plant tissue culture-based platform offers a potential solution to isolate natural polysaccharide fractions with consistent chemical characteristics and reduced endotoxin content. In this study, an acidic polysaccharide fraction (AGC3) with immunomodulatory properties was isolated from Panax quinquefolius suspension cultures. The heterogeneous fraction (molecular weight: 4.81 and 32.14 kDa), purified by anion exchange chromatography, was predominantly composed of galactose (>60%) along with the presence of rhamnose, arabinose, glucose, glucuronic acid and galacturonic acid. The major glycosidic linkages were found to be t-Galp (47.7%), 4-Galp (15.6%), 2,4-Rhap (8.1%), 6-Galp (8.1%) and 4-GalAp (6.8%). Structural analyses indicated the presence of a pectic rhamnogalacturonan I polysaccharide in AGC3. AGC3 significantly (p < 0.05) stimulated RAW 264.7 murine macrophage cells and primary murine splenocytes by enhancing the production of several immunomodulatory mediators such as IL-6, TNF-α, GM-CSF and MCP-1. The results also indicated the putative roles of NF-κB (p65/RelA) and MAPK (p38) signaling pathways in the immunostimulatory response. Additionally, AGC3 induced murine splenocyte proliferation, another major indicator of immunostimulation. Overall, AGC3 has the potential to be used as an immunostimulatory nutraceutical.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Air oxidation of yttrium hydride as a high temperature moderator for thermal neutron spectrum fission reactors

Yttrium hydride (YH x ) is an attractive moderator material for thermal neutron spectrum fission reactors requiring a small reactor core volume and has been selected as the neutron moderator for the Transformational Challenge Reactor (TCR), an advanced gas-cooled microreactor. Before YH x can be used in this application, it is important to understand the material response to off-normal conditions. In the present study, 550–650 °C isothermal dry air oxidation was performed to simulate a depressurized loss of force circulation (DLOFC) event. The oxidation was performed using thermogravimetric analysis (TGA) on bulk crack-free YHx coupons. Oxidation studies were also performed on Y coupons to elucidate the impact of H on oxidation. Both the chemistry and distribution of processing impurities were found to strongly affect oxidization behavior on a batch-to-batch basis. Regardless of batch, YHx oxidized at a significantly lower rate than Y at all temperatures, and the lower rate was directly correlated with increased hydride content. Metallic Y exhibited complex exponential kinetics, whereas YH x also exhibited complex kinetics but gained considerably less mass. According to literature reports on protonic and native-ion conductivities of Y 2 O 3 and mass spectrometry analysis of gaseous reaction products formed during the oxidation of YH x , a mechanism for the reduced oxidation rate of yttrium hydride is suggested.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗