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DOE OSTI2022

SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability

Advanced reactors often involve complicated thermal-fluid (T-F) phenomena. Modeling such phenomena with the traditional one-dimensional (1-D) system code is a challenging task. The System Analysis Module (SAM), a modern nuclear system code, has developed a coarse mesh multi-dimensional (multi-D) flow model to capture the spatial effect of T-F phenomena in advanced reactors. As a coarse mesh solver, constitutive relations are required for SAM's multi-D model for unresolved fine-scale physics, such as turbulence. Here this work presents a novel approach that integrates neural networks as data-driven closure for SAM's multi-D flow model. The data-driven closure is trained with fine-resolution data to ensure its accuracy while maintaining a coarse mesh setup to ensure its efficiency and consistency with SAM. We demonstrate the applicability of this SAM-ML capability in an open volume thermal stratification problem, where a neural network model serves as the eddy viscosity closure. A customized interface between the neural network and SAM is developed to ensure flexible and efficient data exchange. The SAM-ML results demonstrate superior performance compared to SAM's built-in zero-equation eddy viscosity closure. The case study shows that although the generalization capability of the data-driven closure still needs to be improved for different transient case or different geometric setup, SAM -ML demonstrates good potential for challenging simulation problems with improved accuracy and computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Improved high-precision mass measurements of mid-shell neon isotopes

New mass values measured with the TITAN MR-TOF-MS are reported for the short-lived isotopes 24-26 Ne, produced at TRIUMF's ISAC facility using a uranium carbide target and cold FEBIAD ion source. A least-squares adjustment within the framework of the Atomic Mass Evaluation was performed and the improved precision of the new mass values is highlighted. The improved mass accuracy in this N = 14mid-shell region can also point to the refinement in values of the charge radii. By reducing the mass uncertainty of isotopes, their contribution of the mass shift uncertainty in laser spectroscopy can be negated. The work is part of developments for reaching the N = 20 Island of Inversion, where high molecular contamination hinders mass measurements of the neon isotopes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Improved light yield and growth of large-volume ultrafast single crystal scintillators Cs 2 ZnCl 4 and Cs 3 ZnCl 5

Due to their reported fast decay times, Cs 2 ZnCl 4 and Cs 3 ZnCl 5 are promising candidates for detection of gamma rays and X-rays in high count rate and fast timing applications. In this work, we show that single crystals with better optical quality than previously demonstrated – and larger in size – can be grown via the vertical Bridgman method. Highly transparent Ø7 mm crystals of undoped Cs 2 ZnCl 4 and Cs 3 ZnCl 5 are grown and measured to have light yields surpassing those previously reported, achieving 1980 ± 100 ph/MeV and 1460 ± 70 ph/MeV at 662 keV – a 55% and 232% improvement, respectively. We observe single-component scintillation decay times for both Cs 2 ZnCl 4 (1.66 ns) and Cs 3 ZnCl 5 (0.82 ns) and radioluminescence emission with maximum intensity at ~290 nm. Scalability of these materials is also evaluated based on growth of Ø22 mm crystals. Minimal cracking is observed, and the fast decay times are maintained at this size. Coincidence time resolution of 3 × 3 × 5 mm 3 and 7 × 7 × 10 mm 3 pixels cut from Ø22 mm Cs 2 ZnCl 4 are measured to be 148 ± 1 ps FWHM and 175 ± 1 ps FWHM, respectively. Here, the improved performance and ability to be fabricated in large sizes now place Cs 2 ZnCl 4 and Cs 3 ZnCl 5 on the map as potential contenders for radiation detection applications where BaF 2 – the most commonly used ultrafast inorganic scintillator – is typically considered.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Metabolic flux modeling of Gluconobacter oxydans enables improved production of bioleaching organic acids

Bioleaching with organic acids is an option for recovery of rare earth elements (REE) and or other valuable metals from consumer or industrial wastes. Biohydrometallurgy can play an economically and environmentally sustainable role in REE recycling, particularly if agriculture or food wastes are used as the carbon substrates for production of the bioleaching agents. A challenge for organic acid based REE bioleaching is the incomplete conversion of the carbon substrate to an optimal organic acid mixture with high REE extraction capability. To help meet this challenge a metabolic flux model was developed for Gluconobacter oxydans to identify options for improving sugar conversion to chelating organic acids. Here, model predictions were consistent with laboratory data for the microbial consumption of glucose and production of gluconic acid and suggested that providing growth conditions with relatively high carbon to nitrogen molar ratios could result in production of lower pH biolixiviant and thus improve REE bioleaching yields.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

An improved detailed chemical kinetic model for C3-C4 linear and iso-alcohols and their blends with gasoline at engine-relevant conditions

Propanol and butanol isomers have received significant research attention as promising fuel additives or neat biofuels. Robust chemical kinetic models are needed that can provide accurate and efficient predictions of combustion performance across a wide range of engine relevant conditions. Herein, this study seeks to improve the understanding of ignition and combustion behavior of pure C3-C4 linear and iso-alcohols, and their blends with gasoline at engine-relevant conditions. In this work, a kinetic model with improved thermochemistry and reaction kinetics was developed based on recent theoretical calculations of H-atom abstraction and peroxy radical reaction rates. Kinetic model validations are reported, and the current model reproduces the ignition delay times of the C3 and C4 alcohols well. Variations in reactivity over a wide range of temperatures and other operating conditions are also well predicted by the current model. Recent ignition delay time measurements from a rapid compression machine of neat iso-propanol and iso-butanol [Cheng et al., Proc. Combust Inst. (2020)] and blends with a research grade gasoline [Goldsborough et al., Proc. Combust Inst. (2020)] at elevated pressure (20–40 bar) and intermediate temperatures (780–950 K) were used to demonstrate the accuracy of the current kinetic model at conditions relevant to boosted spark-ignition engines. The effects of alcohol blending with gasoline on the autoignition behavior are discussed. The current model captures the suppression of reactivity in the low-temperature and negative-temperature-coefficient (NTC) region when either isopropanol and isobutanol are added to a research grade gasoline. Sensitivity and reaction flux analysis were performed to provide insights into the relevant fuel chemistry of the C3-C4 alcohols.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

OC6 phase I: Improvements to the OpenFAST predictions of nonlinear, low-frequency responses of a floating offshore wind turbine platform

We report in the OC5 and OC6 projects, the authors observed a persistent underprediction of the nonlinear, low-frequency responses of an offshore wind semisubmersible with many mid-fidelity engineering models, including the OpenFAST tool developed by the National Renewable Energy Laboratory. Both the low-frequency wave excitation in surge and pitch and the resulting resonance motions were severely underpredicted. In response, we developed several modifications to the OpenFAST model from the OC5/6 projects to improve the predictions of the low-frequency wave loads and responses. All modifications are in the modeling of the viscous drag forces. Efforts were made to provide physical justifications to the changes and to limit the number of additional parameters requiring tuning, so that the modified model can be applied to other floating wind systems. With the proposed modifications, the predictions of the low-frequency surge and pitch wave loads on a fixed floater and the resonance responses of a floating structure are both significantly improved with a single set of model coefficients, which leads to good agreement with the measurements from the OC6 wave-basin experimental campaign.

17 WIND ENERGY↗

DOE OSTI2021

Synthesis strategies toward improved ordering of [MnO 6 ] octahedra in tunnel structured 2 × 3 and 2 × 4 MnO 2

Improved homogeneity of tunnel size in Na-stabilized 2 × 3 and 2 × 4 MnO 2 structures was achieved by identifying and controlling critical synthesis parameters. 2 × 3 and 2 × 4 MnO 2 tunnel manganese oxide nanowires were obtained by hydrothermal treatment of Na-birnessite, a layered manganese oxide that undergoes a layer-to-tunnel transition under high pressure and temperature. Herein, the improved ordering of [MnO 6 ] octahedra is revealed via a combined analysis of X-ray diffraction patterns and scanning transmission electron microscopy images. Furthermore, we show that crystallinity of the Na-birnessite precursor and the chemical composition of the system during hydrothermal treatment are crucial for achieving the targeted size of the structural tunnels with adequate uniformity.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Effects of potassium treatment on SnO 2 electron transport layers for improvements of perovskite solar cells

SnO 2 has been studied intensively as an electron transport layer (ETL) for highly efficient metal halide perovskite solar cells. However, SnO 2 ETL frequently exhibits defect-related issues associated with the bulk SnO 2 and the perovskite/SnO 2 interface, and to passivate the defect states potassium ion has been used. In order to investigate the passivation effect of potassium ion, we carried out KCl treatment on the solution-processed SnO 2 ETL. It was found that KCl-treatment shifted up conduction band maximum and Fermi energy of SnO 2 , and reduced the band gap of perovskite absorber by K + diffusion, which resulted in a better conduction band alignment at perovskite/SnO 2 . Admittance spectroscopy revealed that diffused K + ions can passivate defects of the perovskite absorber layer. With the improvement of band alignment and defect passivation via the KCl treatment, the J-V hysteresis was almost eliminated and power conversion efficiency was much enhanced with improved open-circuit voltage and fill factor.

14 SOLAR ENERGY↗

DOE OSTI2022

Improvement of aerosol optical depth data for localized solar resource assessment

Solar irradiance, especially for direct normal irradiance (DNI), is sensitive to the atmospheric aerosols, which can strongly extinguish DNI over areas with elevated aerosol loadings. The National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL), uses AOD from MERRA-2 reanalysis and is further downscaled from 0.5° to 2-km based on elevation. However, the elevation-based downscaling may not accurately represent AOD, especially over the areas with large AOD gradients. This study examined whether the 1-km MODIS MAIAC satellite-retrieved AOD product can better represent the AOD distribution and be used to improve solar irradiance assessment. We focused on areas with relatively high AOD over North America (California, and New York City, US, and Mexico City in Mexico, in particular). The evaluation of MAIAC AOD and MERRA-2 AOD against ground-truth AERONET AOD shows that MAIAC AOD exhibits smaller RMSE by about 0.05 and higher correlation coefficient by 0.1-0.6 than MERRA-2 AOD. In addition, MERRA-2 AOD shows larger negative bias. The simulated DNI using MAIAC AOD (DNIMAIAC) and using MERRA-2 AOD (DNINSRDB) were evaluated with DNI observations. The results show the performance of DNIMAIAC is better than that of DNINSRDB with smaller RMSE by 0.5-1.5%, smaller positive mean bias by 0.8-3.1% and comparable correlation for the 3 sites analyzed. Overall, 1-km MAIAC AOD shows higher accuracy than 2-km elevation-based MERRA-2 AOD, leading to better performance of the simulated DNI using MAIAC AOD. Therefore, 1-km MAIAC AOD can be used to improve the accuracy of solar resource assessment.

14 SOLAR ENERGY↗

DOE OSTI2024

Use of physics to improve solar forecast: Part III, impacts of different cloud types

Cloud-type impacts present a great challenge to solar forecasting due to diverse and complex cloud-radiation interactions. This third part of our paper sequence seeks to address this challenge by quantifying the forecast accuracies under eight cloud types: cumulus (Cu), stratified clouds (St), altocumulus (Ac), altostratus (As), cirrostratus/anvil (Cr), cirrus (Ci), congestus (Co), deep convective clouds (Dc) across four physics-informed persistence models reported in Part I. To generalize the cloud impacts, the eight cloud types are further grouped into three cloud categories based on their common features: weak convective clouds, stratiform clouds, and strong convective clouds. Here, the decade-long (2001 ~ 2014) collocated measurements of irradiances and cloud types at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program South Great Plain (SGP) Central Facility site are used for model evaluation. Results reveal a clear performance hierarchy for global horizontal irradiance (GHI) and direct normal irradiance (DNI): best for weak convective clouds and cirrus, intermediate for stratiform clouds, and worst for strong convective clouds. Performance for diffuse horizontal irradiance (DHI) is less influenced by cloud types. Cloud albedo dominates all three irradiances for Dc, while both cloud albedo and cloud fraction are influential for other cloud types. A 12 %~33 % improvement in accuracy at 6-hour lead time compared to the benchmark smart model confirms the effectiveness of incorporating physics into the models for various cloud types; further improvements are expected by directly integrating cloud type information into forecasting models by modifying the physical formulation of cloud-radiation interaction, and/or using more advanced machine learning models.

14 SOLAR ENERGY↗

DOE OSTI2024

Metal DiSulfide thin films synthesized by pulsed ion beam ablation: Self-assembled structures with improved mechanical properties in humid conditions

Thin films composed of transition metal dichalcogenides such as molybdenum disulfide (MoS 2 ) or tungsten disulfide (WS 2 ) are well known for their solid lubricating behavior in dry environments such as space, but deteriorate rapidly in environments where oxygen is present. There have been many attempts over recent decades to improve MoS 2 lubricating performance in humid environments by addition of metals such as titanium to the film. The additions have come in the form of co-sputtering with the MoS 2 , or formation of nano multilayer coatings. We have previously reported on the synthesis of MoS 2 films by high-power ion beam ablation [Prasad et al, Matls. Lett. 65 (2010) 4–6]. The resulting films are observed to contain spheres of pure Mo of 10–100 nm size evenly dispersed throughout the ~1 μm-thick film, a form of self-assembly not before seen in films produced by sputtering or by pulsed laser deposition (PLD). The remaining Mosingle bondS matrix was observed to crystalize in situ under frictional contact into MoS 2 with the basal planes orienting themselves in the direction of sliding underneath the wear surface. The present study concerns metal additions in the form of alternating layers with MoS 2 deposited in between from an ablation target. The addition of Ti resulted in the extension of good tribological performance to humid air conditions, but the path to good performance appears to be relatively narrow. The same distributed Mo spheres were present in the new film, and similar self-assembled morphologies when V was substituted for the Ti, and when multilayers were formed of WS 2 with Zr additions. Furthermore, it appears that addition of Ti resulted in improvements in mechanical film strength that contributed to the wear ability in humid conditions.

Intense ion beams↗

DOE OSTI2025

How volatile isoprenoids improve plant thermotolerance

Volatile isoprenoids mainly include isoprene and monoterpenes, which improve the thermotolerance of the emitting plant by lowering reactive oxygen species (ROS) levels, preserving chloroplast membrane ultrastructure, maintaining photosynthesis and primary metabolism, inducing heat shock proteins, and preserving growth and development. Recent data showed that isoprenoids can act as signaling molecules to improve plant thermotolerance by altering related gene expression through Ca 2+ -mediated signaling pathways. Here, to promote further understanding of isoprenoid-mediated thermotolerance mechanisms, we review current understanding of isoprenoid-induced plant thermotolerance, along with new findings describing the corresponding underlying mechanisms and putative signaling pathways. This information is beneficial for the potential utilization of isoprenoids for enhancing crop tolerance to global warming either by enhancing the emission of isoprenoids or by using isoprenoid-inspired anti-high temperature agents.

Ca2+ signal↗

DOE OSTI2023

A Denoising Autoencoder for Improved Kikuchi Pattern Quality and Indexing in Electron Backscatter Diffraction

The rapid collection and indexing of electron diffraction patterns as produced via electron backscatter diffraction (EBSD) has enabled crystallographic orientation and structural determination, as well as additional property-determining strain and dislocation density information with increasing speed, resolution, and efficiency. Pattern indexing quality is reliant on the noise of the collected electron diffraction patterns, which is often convoluted by sample preparation and data collection parameters. EBSD acquisition is sensitive to many factors and thus can result in low confidence index (CI), poor image quality (IQ), and improper minimization of fit, which can result in noisy datasets and misrepresent the microstructure. In an attempt to enable both higher speed EBSD data collection and enable greater orientation fit accuracy with noisy datasets, an image denoising autoencoder was implemented to improve pattern quality. Here, we show that EBSD data processed through the autoencoder results in a higher CI, IQ, and a more accurate degree of fit. In addition, using denoised datasets in HR-EBSD cross correlative strain analysis can result in reduced phantom strain from erroneous calculations due to the increased indexing accuracy and improved correspondence between collected and simulated patterns.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Improving the short-wave infrared response of strained GeSn/Ge multiple quantum wells by rapid thermal annealing

In this work, the evolution of structural, optical and optoelectronic properties of coherently strained Ge 0.883 Sn 0.117 /Ge multiple quantum wells (MQWs) grown by molecular beam epitaxy under rapid thermal annealing (RTA) is systematically investigated. The MQW structure remains fully-strained state with RTA at 400 °C or below and disrupts at higher annealing temperatures due to Sn segregation and interdiffusion of Ge and Sn atoms. The GeSn well layers exhibit the strongest absorption in 2.0–2.4 μm after annealing at 400 °C and become transparent above 1.8 μm after RTA at 600 °C or beyond due to serve Sn segregation. Owing to improved crystal quality after RTA at 400 °C, the dark current of the fabricated metal-semiconductor-metal photodetector is effectively lowered by more than two times. Additionally, the responsivities at 1.55 and 2.0 μm are improved by 4.15 and 3.78 folds, respectively, compared to those of the as-grown sample. Here, the results can be an insightful guidance for the development of high-performance short-wave infrared photonic devices based on Sn-containing group-IV low-dimensional structures.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Improved valorization of sewage sludge in the circular economy by anaerobic digestion: Impact of an innovative pretreatment technology

Anaerobic digestion (AD) of sewage sludge shows low carbon conversion efficiency (CCE) due to the poor biodegradability of sewage sludge. Here, the lack of digestibility is specifically linked to the waste-activated sludge (WAS) making up the majority of sewage sludge along with a smaller portion of primary sludge, depending on the wastewater treatment plant configuration. In this study, we examine the Advanced Wet Oxidation & Steam Explosion process (AWOEx) for improving the CCE of digested sewage sludge (DSS) by thermophilic AD. The effect of the pretreatment temperature in the range between 160 and 185 °C at a fixed residence time of 20 min with and without oxygen added at a dosage of 5 % of the organics present was tested. Methane yield improved by 97.92 % to 183.91 ± 4.93 mL/g vS over the untreated DSS (control), whose methane yield was 92.92 ± 9.07 mL/g vS We have demonstrated for the first time that 84 % of the organics in sewage sludge can successfully be transformed into biogas following AWOEx pretreatment, which can contribute significantly to the circular economy instead of greenhouse gas emissions from landfilling.

09 BIOMASS FUELS↗

DOE OSTI2023

Improving knife milling performance for biomass preprocessing by using advanced blade materials

Mechanical preprocessing of biomass, including size reduction, is a crucial step in converting biomass into biofuel. However, feedstock inevitably contains abrasive intrinsic and extrinsic inorganics that may cause excessive tool wear in preprocessing. Here, this work demonstrates that performance of a knife mill can be significantly improved by applying a more wear-resistant blade material. A series of full-scale knife mill tests were performed for size reduction of forest residue using blades of tungsten carbide (WC–Co), iron-borided tool steel, and diamond-like carbon (DLC) coated tool steel. Blade material loss was quantified in correlation to the amount of feedstock processed and wear mechanisms were investigated via worn surface characterization. While the thin DLC coating was removed quickly, the WC-Co and iron-borided blades improved the tool life by 8X and 3X compared with the M2 tool steel blades (baseline), respectively. The in-situ throughput and power consumption measurements provided additional insights. The WC-Co and iron-borided blades had ~3X higher throughput than the baseline blades by the end of the test with lower normalized power consumption. The experimental results were then used as input for a techno-economic analysis, which suggested that the more wear resistant blades could cut the knife milling cost by $2–3 per ton of biomass processed with downtime reduced by 65–85%.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Disruption of adenosine 2A receptor improves the anti-tumor function of anti-mesothelin CAR T cells both in vitro and in vivo

Chimeric antigen receptor (CAR) T cells have been successfully used for the treatment of hematological malignancies including acute and chronic lymphoblastic leukemia. However, results of CAR T cell projects in solid tumors have been less impressive to date, partly because of immunosuppressive tumor microenvironment (TME). It is widely known that high adenosine production is an important factor causing tumor-induced immunosuppression in TME, and adenosine mediates the suppression of anti-tumor T cell responses via binding and signaling through adenosine 2a receptor (A2aR). Previous studies have shown that adenosine generated by cancer cells significantly inhibits T cell anti-tumor activity through binding and then activating adenosine 2A receptors (A2aRs) of T cells. Based on the previous work, in our study, we evaluated whether A2aR disruption by shRNA could enhance the anti-tumor function of anti-mesothelin (MSLN) CAR T cells both in vitro and in vivo. For this goal above, we used MSLN-positive human ovarian serous carcinoma cells (SKOV3) and human colon cancer cells (HCT116) as target cancer cells while MSLN-negative human ovarian cancer cells (ES2) as non-target cancer cells. We observed that targeting cell-intrinsic A2aR through shRNA overexpression caused significant A2aR disruption in CAR T cells and profoundly increased CAR T cell efficacy in both CAR T cell cytokine production and cytotoxicity towards MSLN-positive cancer cells in vitro. More importantly, in SKOV3 xenograft mouse models, anti-MSLN CAR-T cells significantly reduced the tumor burden compared with non-transduced T cells, and the anti-tumor activity of A2aR-disrupted anti-MSLN CAR-T cells was stronger than that of wild-type anti-MSLN CAR-T cells. Altogether, our study showed enhanced anti-tumor efficacy caused by shRNA-mediated A2aR disruption in anti-MSLN CAR T cells both in vitro and in vivo, which proved that shRNA-mediated modification of gene expression might be an excellent strategy for improving CAR T cell function in immunosuppressive tumor microenvironment (TME) and could potentially improve the outcome of treatment in clinical trials.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Two-stage dynamic deregulation of metabolism improves process robustness & scalability in engineered E. coli.

Here, we report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗