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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Microbial maintenance energy quantified and modeled with microcalorimetry

Refining the energetic costs of cellular maintenance is essential for predicting microbial growth and survival in the environment. In this work, we evaluate a simple batch culture method to quantify energy partitioning between growth and maintenance using microcalorimetry and thermodynamic modeling. The constants derived from the batch culture system were comparable to those that have been reported from meta-analyses of data derived from chemostat studies. The model accurately predicted temperature-dependent biomass yield and the upper temperature limit of growth for Desulfovibrio alaskensis G20, suggesting the method may have broad application. An Arrhenius temperature dependence for the specific energy consumption rate, inferred from substrate consumption and heat evolution, was observed over the entire viable temperature range. By combining this relationship for specific energy consumption rates and observed specific growth rates, the model describes an increase in nongrowth associated maintenance at higher temperatures and the corresponding decrease in energy available for growth. This analytical and thermodynamic formulation suggests that simply monitoring heat evolution in batch culture could be a useful complement to the recognized limitations of estimating maintenance using extrapolation to zero growth in chemostats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Predicting Sintering Window of Binder Jet Additively Manufactured Parts Using a Coupled Data Analytics and CALPHAD Approach

Batch-to-batch variation in powder compositions for binder jet additive manufacturing (BJAM) can significantly deter defining an “ideal” sintering window for a given alloy. One way to overcome the problem is by running sintering experiments at various temperatures for each batch of the powder. However, such an approach increases the time required to achieve large-scale production of parts. The predictive capabilities of computational thermodynamic tools like CALPHAD can be leveraged to overcome the challenge, especially for binder jet additive manufacturing, since the process occurs under near-equilibrium conditions. However, calculating the sintering window using CALPHAD can be computationally expensive, considering many possible feedstock compositions within “specification”. Here, we generate high throughput CALPHAD data for nickel-based superalloys to develop machine learning models to predict the sintering window rapidly. The predictive capability of the models has been validated using published results on BJAM of Inconel 718 and 625. Further, validated models are lightweight and can be deployed in an industrial setting to get sintering window in an accelerated manner.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High solids loading biorefinery for the production of cellulosic sugars from bioenergy sorghum

A novel process applying high solids loading in chemical-free pretreatment and enzymatic hydrolysis was developed to produce sugars from bioenergy sorghum. Hydrothermal pretreatment with 50% solids loading was performed in a pilot scale continuous reactor followed by disc refining. Sugars were extracted from the enzymatic hydrolysis at 10% to 50% solids content using fed-batch operations. Here, three surfactants (Tween 80, PEG 4000, and PEG 6000) were evaluated to increase sugar yields. Hydrolysis using 2% PEG 4000 had the highest sugar yields. Glucose concentrations of 105, 130, and 147 g/L were obtained from the reaction at 30%, 40%, and 50% solids content, respectively. The maximum sugar concentration of the hydrolysate, including glucose and xylose, obtained was 232 g/L. Additionally, the glucose recovery (73.14%) was increased compared to that of the batch reaction (52.74%) by using two- stage enzymatic hydrolysis combined with fed-batch operation at 50% w/v solids content.

09 BIOMASS FUELS↗
DOE OSTI2024

The simultaneous removal of technetium and iodine from Hanford tank waste

The simultaneous removal of radionuclides technetium-99 and iodine-129 from an actual decontaminated Hanford tank waste sample (a mixture of decontaminated waste from tanks 241-AP-105 and 241-AP-107) was demonstrated for the first time in this work. A series of commercially available ion exchange resins were evaluated in batch contact tests in the tank waste, and all showed removal of both Tc and I. The highest Tc removal was observed for Purolite A530e while the highest iodine removal was observed for ResinTech SIR-110-MP. Batch tests in simulated tank waste with these two resins showed that the SIR-110-HP-MP had consistently higher K d for both pertechnetate and iodide and much higher K d than previous works on Tc removal from Hanford waste. As such, the SIR-110-MP was evaluated in a dual -column (lead/lag) test processing 5.2L of the tank waste mixture showing 60% breakthrough of Tc on the lead column and no significant breakthrough on the lag after 625 bed volumes (BV, 6 mL size) while significant iodine breakthrough (>50%) occurred after 28 BV. The limited iodine uptake was attributed to the column conditions generating mass transfer limitations. A fraction of the Tc and I was not captured by the resin (<10%) in either the batch tests or column tests. The iodine fraction was identified to be an iodide, likely organo-iodide. The fraction of the Tc was identified as a non-pertechnetate species, which is the first time non-pertechnetate has been identified in AP-105 and AP-107 tanks, although the exact species is still unknown.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Active learning for SNAP interatomic potentials via Bayesian predictive uncertainty

Bayesian inference with a simple Gaussian error model is used to efficiently compute prediction variances for energies, forces, and stresses in the linear SNAP interatomic potential. Here, the prediction variance is shown to have a strong correlation with the absolute error over approximately 24 orders of magnitude. Using this prediction variance, an active learning algorithm is constructed to iteratively train a potential by selecting the structures with the most uncertain properties from a pool of candidate structures. The relative importance of the energy, force, and stress errors in the objective function is shown to have a strong impact upon the trajectory of their respective net error metrics when running the active learning algorithm. Batched training of different batch sizes is also tested against singular structure updates, and it is found that batches can be used to significantly reduce the number of retraining steps required with only minor impact on the active learning trajectory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Effective kinetics driven by dynamic concentration gradients under coupled transport and reaction

Biogeochemical reaction kinetics are generally established from batch reactors where concentrations are uniform. In natural systems, many biogeochemical processes are characterized by spatially and temporally variable concentration gradients that often occur at scales which are not resolved by field measurements or biogeochemical and reactive transport models. Yet, it is not clear how these sub-scale chemical gradients affect reaction kinetics compared to batch kinetics. Here we investigate this question by studying the paradigmatic case of localized pulses of solute reacting with a solid or a dissolved species in excess. Additionally, we consider non-linear biogeochemical reactions, representative of mineral dissolution, adsorption and redox reactions, which we quantify using simplified power-law kinetics. The combined effect of diffusion and reaction leads to effective kinetics that differ quantitatively and qualitatively from the batch kinetics. Depending on the nonlinearity (reaction order) of the local kinetics, these effects lead to either enhancement or decrease of the overall reaction rate, and result in a rich variety of reaction dynamics. We derive analytical results for the effective kinetics, which are validated by comparison to direct numerical simulations for a broad range of Damköhler numbers and reaction order. Our findings provide new insights into the interpretation of imperfectly mixed lab experiments, the effective kinetics of field systems characterized by intermittent reactant release and the integration of sub-scale concentration gradients in reactive transport models.

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

Optimization of key energy and performance metrics for drug product manufacturing

During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors, this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. Here, the results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The effect of varying powder feedstock chemistry and printing atmosphere on the microstructure of additively manufactured nickel-based ODS alloys: Role on stabilization of cellular structures vs. oxide dispersion formation

Nickel-based alloys have a wide variety of structural applications due to their high corrosion resistance and mechanical strength which depend on solid solution strengthening, or the formation of oxides and/or intermetallic precipitation for their properties. In this study, the microstructure of six Ni–Cr–Y–Ti–Al powder batches designed for the production of oxide dispersion strengthened nickel were compared. These batches varied in chemistry and atomization technique used which included Gas Atomization Reactive Synthesis (GARS). The batches of powder were then consolidated via Additive Manufacturing (AM) Powder Bed Fusion using Laser Beam (PBF-LB) and characterized via transmission electron microscopy to elucidate the influence of powder feedstock (i.e. synthesis methodology and chemistry) on the PBF-LB microstructure. The study investigates (i) how the amount of yttrium and titanium additions in the powder feedstock and the addition of oxygen during the processing (through GARS) affect the microstructure of the powder itself and the AM printed microstructure, and (ii) how the control of oxygen addition in the printing atmosphere during the PBF-LB printing process itself is another important parameter for achieving the formation of the wanted oxide dispersion versus the stabilization of the cellular structure (often observed in AM processed alloys). Microstructural characterization of both powder particles and additively manufactured nickel alloys in this study provide important insights into the movement of yttrium within the material upon solidification, particularly along cell boundaries, and how yttrium behaves depending on alloy chemistry. When a threshold of yttrium content is reached within the system, yttrium consistently reacts to form an intermetallic along cell boundaries instead of forming oxide nanoparticles.

36 MATERIALS SCIENCE↗
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↗
DOE OSTI2024

Influence of porous aluminosilicate grain size materials in experimental and modelling Cs + adsorption kinetics and wastewater column process

This paper focuses on the influence of the grain size of a geopolymer based adsorbent on its Cs + adsorption performances both in batch and fixed-bed process. The geopolymer phase was used as a binder to support NaY zeolite particle in a 20 wt% charged porous composite with 160 m 2 .g –1 of porous surface area. These samples were shaped with three grain sizes (50 /100/500 µm) to remove 80–90 mg/g of Cs + in batch and column operations. After their microstructural and porous characterizations, their efficiency and adsorption characteristics were investigated through adsorption isotherms and kinetic in the two processes. While the grain size has no influence on the maximal extraction capacity of the adsorbent, it strongly affects the sorption kinetic. By coupling experimental data and a modelling approach, the complex sorption mechanism was highlighted, suggesting a new insight of the contaminant sorption kinetic. Then, comparison of batch and column adsorption experiments illustrates the detailed explanation of various process parameters for column study. The results show challenges for fixed-bed column utilization by the choice of the appropriate grain size as a compromise between the material sorption kinetic and hydrodynamic considerations. Furthermore, this is of high importance to more accurately optimize the design of column adsorption to assess the transport of Cs+ in multi-porous tailored grain size materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Initial tests of large format sensors for the ATLAS ITk strip tracker

For the construction of the Inner Tracker (ITk) as part of the phase-II upgrade programme of the ATLAS detector for the High-Luminosity (HL) LHC, batches of Long Strip (LS) and Short Strip (SS) n + -in-p type micro-strip sensors have been produced by Hamamatsu Photonics and Infineon. The full size sensors measure approximately 98 × 98 mm 2 and are designed and engineered for tolerance against the 9.7 × 10 14 1 MeV n eq /cm 2 fluence expected at the HL-LHC, including a safety factor of 1.5. Each sensor has 2 or 4 columns of 1280 individual channels arranged at 75.5 μ m horizontal pitch. To ensure the sensors comply with their specifications, a Quality Control (QC) procedure has been implemented, comprising measurements on every individual sensor as well as on a sample basis. Every sensor is subjected to an initial visual inspection, after which the full surface of the sensor is captured with very high resolution by an automated camera setup. Non-contact metrology is performed to obtain the sensor surface profile. Electrical measurements establishing the reverse bias leakage current and depletion voltage are then conducted automatically. Sample sensors from every batch are subjected to 40 h of leakage stability checks in controlled atmosphere, and tests on every channel measuring leakage current, coupling capacitance and bias resistance are done. The recorded results are uploaded to a production database following data quality checks. In this paper, QC test validation data and the compiled results for the first batches of production grade sensors are presented. The QC protocol was validated, and the first production sensors were confirmed to be within specification. The results are compared to those from the previous generation of prototype sensors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Chemometrics and visible diffuse reflectance spectroscopy to classify plutonium dioxide

Diffuse reflectance (DR) spectra in the Vis-NIR (∼380–1050 nm) region were acquired for a series of PuO 2 samples with a spot size of about 10 × 10 μm. Two batches of six PuO 2 samples, synthesized approximately 7.5 months apart, were prepared using both Pu(III) and Pu(IV) oxalate precursors at three distinct calcination temperatures (450, 650, and 950 °C). This yielded a total of 12 PuO 2 samples and 433 DR spectra. The DR spectrum of PuO 2 contained numerous peaks in the visible region, and characteristic features were identified with respect to calcination temperature and chemistry. A distinct peak multiplet near 615 nm was observed for samples prepared at low calcination temperatures, and a peak near 660 nm was observed for higher calcination temperatures. A multivariate classification strategy based on principal component analysis (PCA) was developed to distinguish PuO 2 calcination temperatures of 450, 650, and 950 °C with 100 % accuracy. Classification results also indicate the potential to distinguish chemical processing history (i.e., Pu(III) or Pu(IV)) based on the spectra with 72 % accuracy based on k-nearest neighbors applied to the PCA scores. Partial least squares discriminant analysis was used to identify variation among batches with 88 % accuracy and found that peaks near 669, 681, 811, and 970 nm were the most useful for predicting the batch identity. Here, this work demonstrates how micro-diffuse reflectance spectroscopy and chemometrics can be used to classify PuO 2 processing history based on Vis-NIR spectral features. Combining the chemometric approach with mapping sequences could provide a rapid, nondestructive approach to classify Pu oxide materials for environmental, forensics, and nonproliferation applications.

Actinide↗
DOE OSTI2023

Sequence Design of Random Heteropolymers as Protein Mimics

Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent developments in reversible-deactivation radical polymerization allowed simulated polymer sequences based on the well-established Mayo–Lewis equation to more accurately reflect ground-truth sequences that are experimentally synthesized. This led to opportunities to perform bioinformatics-inspired analysis on simulated sequences to guide the design, synthesis, and interpretation of RHPs. We compared batches on the order of 10000 simulated RHP sequences that vary by synthetically controllable and measurable RHP characteristics such as chemical heterogeneity and average degree of polymerization. Our analysis spans across 3 levels: segments along a single chain, sequences within a batch, and batch-averaged statistics. We discuss simulator fidelity and highlight the importance of robust segment definition. Examples are presented that demonstrate the use of simulated sequence analysis for in-silico iterative design to mimic protein hydrophobic/hydrophilic segment distributions in RHPs and compare RHP and protein sequence segments to explain experimental results of RHPs that mimic protein function. To facilitate the community use of this workflow, the simulator and analysis modules have been made available through an open source toolkit, the RHPapp.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Simple but tricky: Investigations of terephthalic acid purity obtained from mixed PET waste

In this study, we report for the first time, the basic depolymerization of mixed waste-polyethylene terephthalate (PET) by hydrolysis and subsequent terephthalic acid monomer recovery at high purity using benign reaction conditions. Several conditions were tested for depolymerization such as PET chips size, concentration of aqueous sodium hydroxide (20 or 30%), organic co-solvent (ethylene glycol or ethanol), temperature at which the reaction was run and duration of the heating. More importantly, several batches of PET were utilized as starting materials including a commercial PET, chopped PET obtained from clean bottles whose caps and labels were removed and the purity of the product from each condition was evaluated via nuclear magnetic resonance (1HNMR and 13CNMR), differential scanning calorimetry (DSC) and powder Xray diffraction (XRD). Unsurprisingly, the conversion of PET is dependent on the particle size varying from 100% conversion for fine powder to 73% conversion for (300 µm, mesh 6 – 20 or mesh 14-20). Ethanol appears to be more efficient as a co-solvent than ethylene glycol, with higher PET depolymerization conversions (94% versus 75-80%), shorter reaction times (2h versus 6h) and lower temperatures (80 °C versus 110 °C). The terephthalic acid (TPA) recovered appeared to have only subtle differences among the batches, most notably a pink color when the reaction was run in ethanol/base. The DSC of the compounds produced in ethylene glycol water appear to display a melting point (280-288 °C) while the samples prepared in ethanol as well as a commercial sample did not. Overall, the purity of the various TPA batches is comparable, and similar to commercial TPA, demonstrating the utility of the method to depolymerize realistic waste streams. The method is simple, demonstrated on multigram scale (15-30g) and allows for the complete removal of waste other than PET unaffected by alkaline conditions.

Cosimbescu, Lelia↗
DOE OSTI2023

Optimization of nutrient utilization efficiency and productivity for algal cultures under light and dark cycles using genome-scale model process control

Abstract Algal cultivations are strongly influenced by light and dark cycles. In this study, genome-scale metabolic models were applied to optimize nutrient supply during alternating light and dark cycles of Chlorella vulgaris . This approach lowered the glucose requirement by 75% and nitrate requirement by 23%, respectively, while maintaining high final biomass densities that were more than 80% of glucose-fed heterotrophic culture. Furthermore, by strictly controlling glucose feeding during the alternating cycles based on model-input, yields of biomass, lutein, and fatty acids per gram of glucose were more than threefold higher with cycling compared to heterotrophic cultivation. Next, the model was incorporated into open-loop and closed-loop control systems and compared with traditional fed-batch systems. Closed-loop systems which incorporated a feed-optimizing algorithm increased biomass yield on glucose more than twofold compared to standard fed-batch cultures for cycling cultures. Finally, the performance was compared to conventional proportional-integral-derivative (PID) controllers. Both simulation and experimental results exhibited superior performance for genome-scale model process control (GMPC) compared to traditional PID systems, reducing the overall measured value and setpoint error by 80% over 8 h. Overall, this approach provides researchers with the capability to enhance nutrient utilization and productivity of cell factories systematically by combining genome-scale models and controllers into an integrated platform with superior performance to conventional fed-batch and PID methodologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Production of renewable alcohols from maple wood using supercritical methanol hydrodeoxygenation in a semi-continuous flowthrough reactor

Biomass conversion to alcohols using supercritical methanol depolymerization and hydrodeoxygenation (SCM-DHO) with CuMgAl mixed metal oxide is a promising process for biofuel production. Here, we demonstrate how maple wood can be converted at high weight loadings and product concentrations in a batch and a semi-continuous reactor to a mixture of C 2 –C 10 linear and cyclic alcohols. Maple wood was solubilized semi-continuously in supercritical methanol and then converted to a mixture of C 2 –C 9 alcohols and aromatics over a packed bed of CuMgAlO x catalyst. Up to 95 wt% of maple wood can be solubilized in the methanol by using four temperature holds at 190, 230, 300, and 330 °C. Lignin was solubilized at 190 and 230 °C to a mixture of monomers, dimers, and trimers while hemicellulose and cellulose solubilized at 300 and 330 °C to a mixture of oligomeric sugars and liquefaction products. The hemicellulose, cellulose, and lignin were converted to C 2 –C 10 alcohol fuel precursors over a packed bed of CuMgAlO x catalyst with 70–80% carbon yield of the entire maple wood. The methanol reforming activity of the catalyst decreased by 25% over four beds of biomass, which corresponds to 5 turnovers for the catalyst, but was regenerable after calcination and reduction. In batch reactions, maple wood was converted at 10 wt% in methanol with 93% carbon yield to liquid products. The product concentration can be increased to 20 wt% by partially replacing the methanol with liquid products. The yield of alcohols in the semi-continuous reactor was approximately 30% lower than in batch reactions likely due to degradation of lignin and cellulose during solubilization. These results show that solubilization of whole biomass can be separated from catalytic conversion of the intermediates while still achieving a high yield of products. However, close contact of the catalyst and the biomass during solubilization is critical to achieve the highest yields and concentration of products.

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↗