Search NASA⌕ Search

SEARCH · Search NASA

Results for “Cell differentiation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

CSAPR2 Optimized Convective Cell Tracking Data during TRACER

One of the challenges in analyzing convective cell properties is to observe the quick evolution of individual convective cells. While the operational radar data provide a volumetric data set to analyze radar observables of convective precipitation clouds, previous studies also suggested the quick evolution of cell life cycle that might not be captured by conventional radar volume scan strategies that take ~5-7 minutes. Aiming at enhancing our understanding of the links between convective cloud kinematic and microphysical processes as well as life cycles, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER; Jensen et al. 2019) was conducted at Houston, Texas, in 2022. The TRACER campaign deployed the 2nd generation C-band Scanning ARM Precipitation Radar (CSAPR2), which performed frequent updates of range height indicator (RHI) and sector plan position indicator (PPI) scans to track individual convective cells every < 2 minutes, guided by a new cell tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. We provide the processed CSAPR2 cell tracking data in CfRadial format collected during the TRACER field campaign from June to September 2022. The data files include processed radar variables: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification. Figure 1 provides an example of a 3D image of CSAPR2 reflectivity from the lowest PPI scan and an RHI scan after data processing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impaired neuron differentiation in GBA-associated Parkinson’s disease is linked to cell cycle defects in organoids

The mechanisms underlying Parkinson’s disease (PD) etiology are only partially understood despite intensive research conducted in the field. Recent evidence suggests that early neurodevelopmental defects might play a role in cellular susceptibility to neurodegeneration. To study the early developmental contribution of GBA mutations in PD we used patient-derived iPSCs carrying a heterozygous N370S mutation in the GBA gene. Patient-specific midbrain organoids displayed GBA-PD relevant phenotypes such as reduction of GCase activity, autophagy impairment, and mitochondrial dysfunction. Genome-scale metabolic (GEM) modeling predicted changes in lipid metabolism which were validated with lipidomics analysis, showing significant differences in the lipidome of GBA-PD. In addition, patient-specific midbrain organoids exhibited a decrease in the number and complexity of dopaminergic neurons. This was accompanied by an increase in the neural progenitor population showing signs of oxidative stress-induced damage and premature cellular senescence. These results provide insights into how GBA mutations may lead to neurodevelopmental defects thereby predisposing to PD pathology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

CSAPR2 cell-tracking data collected during TRACER

One of the challenges of analyzing convective cell properties is quick evolution of the individual convective cells. While the operational radar data provide great a data set to analyze the evolution of radar observables of convective precipitation clouds statistically, previous studies also suggested that, because of the quick evolution of cell life cycle, conventional radar volume scan strategies taking ~5-7 minutes might not capture the detailed evolution. The TRACER campaign deployed CSAPR2, which performed frequent update of RHI and sector PPI scans to track convective cells every < 2 minutes guided by a new cell-tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. The submitted data files are CSAPR2 data in CfRadial format collected during the TRACER field campaign from June to September 2020. The data files include processed radar variables including: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Long noncoding RNA MEG3 expressed in human dental pulp regulates LPS-Induced inflammation and odontogenic differentiation in pulpitis

Highlights: • LncRNA MEG3, upregulated in inflamed dental pulp, is involved in the inflammation and regeneration in pulpitis. • The expression of lncRNA MEG3 was semiquantitatively detected in the pulp tissue by the innovative RNAscope® technique. • MEG3 downregulation can inhibit inflammatory cytokines secretion and also promote the odontogenic differentiation of hDPCs. • LncRNA MEG3 can be a potential therapeutic target in the inflammation and regeneration of dentin-pulp complex in pulpitis. Pulpitis refers to inflammation of the inner pulp by invading microbes, and tissue repair occurs due to odontogenic differentiation of human dental pulp cells (hDPCs) with multidifferentiation potential. Long noncoding RNAs (lncRNAs) can modulate numerous pathological and biological processes; however, the role of lncRNAs in the inflammation and regeneration of the dentin-pulp complex in pulpitis is unclear. Here, we performed high-throughput sequencing to identify differentially expressed lncRNAs between human normal and inflamed pulp and concluded that lncMEG3 (lncRNA maternally expressed gene 3, MEG3) was signicantly upregulated in both inflamed pulp and LPS-treated hDPCs. MEG3 expression in the pulp tissue was detected using the RNAscope® technique. RNA pulldown assays identified the MEG3-interacting proteins and the potential mechanisms. With MEG3 knockdown, we investigated the role of MEG3 in the secretion of inflammatory cytokines in LPS-treated hDPCs and odontogenic differentiation of hDPCs. MEG3 downregulation inhibited the secretion of TNF-α, IL-1β and IL-6 in LPS-treated hDPCs, and the p38/MAPK signaling pathway may be related to this effect. MEG3 knockdown promoted odontogenic differentiation of hDPCs by regulating the Wnt/β-catenin signaling pathway. Our study suggested that MEG3 has a negative effect on inflammation and regeneration of the dentin-pulp complex in pulpitis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts’ opinion on the development and application of multi-omic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular and functional aberrations within the lesion and within individual cells. Additionally, single-cell proteomic data will be essential for the establishment of new tools that with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included: • The best way/s to analyze single-cells from fresh and preserved tissue • Detection and analysis of secreted molecules and from single cells, especially from a tissue slice • Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment • Multi-omic integration of data to support and inform proteomic measurements • Subcellular organelles – identifying abnormal structure, function, distribution and location within individual premalignant and malignant cells • How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post translational modifications (PTM) • The depth of coverage measured concurrently using single-cell techniques • Quantitation - absolute or semiquantitative? • Single methodology or multiplexed combinations? • Application of analytical methods for identification of biologically significant subsets • Data visualization of N-dimensional datasets • How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME) • Associations between intrinsic cellular processes and extrinsic stimuli • How to predict cellular responses to stress inducing stimuli • Identification of new markers for prediction of progression from precursor, benign and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells • Identification of new targets for immunoprevention or immunotherapy – identification of neoantigens and surfactome of individual cells within a lesion

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cell‐type‐specific transcriptomics uncovers spatial regulatory networks in bioenergy sorghum stems

SUMMARY Bioenergy sorghum is a low‐input, drought‐resilient, deep‐rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum's 4–5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about cell‐type gene expression and regulation in stems was available to enable engineering. To obtain this information, laser capture microdissection was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell‐type‐specific and cell‐preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell‐type‐specific gene regulatory networks (GRNs) revealed that unique transcription factor families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell‐specific transcriptome data was combined with known secondary cell wall (SCW) networks to identify the GRNs that differentially activate SCW formation in vascular sclerenchyma and epidermal cells. The spatial transcriptomic dataset provides a valuable source of information about the function of different sorghum cell types and GRNs that will enable the engineering of bioenergy sorghum stems, and an interactive web application developed during this project will allow easy access and exploration of the data ( https://mc‐lab.shinyapps.io/lcm‐dataset/ ).

09 BIOMASS FUELS↗
DOE OSTI2022

Methodology of the Extraction of Multi-Differential Cross Sections of Charged-Current $\nu_\mu$-Argon Interactions in MicroBooNE Using Wire-Cell $\nu_\mu$CC Selection

Neutrino physics experiments rely on accurate nuclear-interaction models that are in part guided by experimental observations. Multi-differential cross section measurements are particularly valuable for exploring the underlying physics described in these models, making them a significant step forward in the field. This note presents methodology in preparation to unfold neutrino flux-averaged double and triple-differential cross sections of the inclusive muon neutrino charged-current interaction on Argon. This work builds upon the existing framework and methodology presented in recent energy dependent cross section measurements at MicroBooNE using the Wire-Cell tomographic event reconstruction. The signal definition, choice of binning, and handling of estimated detector uncertainties are discussed, and the MicroBooNE simulation model is validated over the multi-dimensional phase space of muon momentum, muon polar angle, and visible hadronic energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Comparative performance and technoeconomic analyses of two microalgae harvesting systems evaluated at a commercially relevant scale

Using a commercially scalable system designed for processing thousands of liters a day, here we evaluated the factors that affected the performance, energy consumption and capital/operating costs of both flocculation-based and filtration-based algal harvesting systems over a 16 month period. Coagulation efficiency was the primary driver of harvest efficiency in the flocculation-based method, while cell lysis was important for the filtration-based method. Culture (algae) age differentially influenced harvest efficiency through changes in cell fragility and stickiness. The average energy consumption of the flocculation-based method was 0.389 kWh/m 3 , while that for the filtration-based method was 4.343 kWh/m 3 . The average harvesting cost of the filtration-based method was 5.35 $\$$/m 3 , while for flocculation-based method it was 4.52 $\$$/m 3 . The concentration factor of filtration-based and flocculation-based method were 770–1086 and 407–448, respectively. For both harvesting methods, labor costs dominated and ranged from 55.84%–67.94% of total cost. Further system automation is a potential method to lower the harvesting cost. The filtration-based harvesting method could produce a better quality of algal biomass with higher concentration factors and less ash content, but needed more energy input, as compared with a flocculation-based method. This study highlights the importance of algal culture status to successful harvesting, and it also provides insight into developing more efficient harvesting technology with lower energy and capital cost.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Construction of extracellular matrix-based 3D hydrogel and its effects on cardiomyocytes

Highlights: • SOD and Triton X-100 could efficiently decellularize cells to get cardiac ECM. • Main proteins of cECM were fibronectin, collagen, elastin, fibrillin, laminin, etc. • 75% cECM-containing 3D hydrogel promoted cell proliferation and anti-apoptosis. • cECM3DH facilitated the differentiation of ESCs into CMs. • APcECM3DH was more conducive to NCM and ESC-derived CM maturation. Some discoveries resulted from 2-dimensional (2D) cultured cardiac cells have been disqualified in animal testing and later clinical trials. Extracellular matrix (ECM) plays a vital role in cardiac homeostasis, cardiac ECM (cECM)-based 3D cell cultures can mimics the physiological and pathological conditions in vivo closely, it is hopeful of addressing this challenge. Construction of cECM-based 3-dimensional (3D) hydrogel (cECM3DH) and its effects on cell behaviors were studied here. The results indicated that cellular compartments could be efficiently removed from heart tissue via sodium dodecyl sulfonate (SDS)- and Triton X-100-mediated decellularization, remaining the natural fibrous network structure and major proteins. 3D hydrogel consisted of 1 × 10{sup 7} cells/mL cells and 75% cECM could promote the proliferation and anti-apoptosis ability of human embryonic kidney (HEK)-293T cells. 0.25% trypsin or 0.20% collagenase was suitable to retrieve these cells from 3D hydrogel for further researches. Compared with 2D culture system, cECM3DH could significantly increase the proportion of GATA 4{sup +} cardiomyocytes (CMs) derived from heart tissue of neonatal mouse or induced differentiation of embryonic stem cells (ESCs) (P < 0.05) The expression levels of mature genes including cTnT, JCN, CaV1.2, MYL2, CASQ2, NCX1, and Cx43 of these CMs in adult pig cECM-based 3D hydrogel (APcECM3DH) were significantly higher than that in 2D culture system and in newborn piglet cECM-based 3D hydrogel (NPcECM3DH), respectively (P < 0.05). Therefore, cECM3DH supports the generation of primary CMs and ESC-derived CMs, APcECM3DH was more conducive to promoting CM maturation, which contributes to building 3D model for pathogenesis exploration, drug screening, and regenerative medicine of heart diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Sorted-cell proteomics reveals an AT1-associated epithelial cornification phenotype and suggests endothelial redox imbalance in human bronchopulmonary dysplasia

Bronchopulmonary dysplasia (BPD) is a neonatal lung disease characterized by inflammation and scarring leading to long-term tissue damage. Previous whole tissue proteomics identified BPD-specific proteome changes and cell type shifts. Little is known about the proteome-level changes within specific cell populations in disease. Here, we sorted epithelial (EPI) and endothelial (ENDO) cell populations based on their differential surface markers from normal and BPD human lungs. Using a low-input compatible sample preparation method (MicroPOT), proteins were extracted and digested into peptides and subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteome analysis. Of the 4,970 proteins detected, 293 were modulated in abundance or detection in the EPI population and 422 were modulated in ENDO cells. Modulation of proteins associated with actin-cytoskeletal function, such as SCEL, LMO7, and TBA1B was observed in the BPD EPIs. Using confocal imaging and analysis, we validated the presence of aberrant multilayer-like structures comprising SCEL and LMO7, known to be associated with epidermal cornification, in the human BPD lung. This is the first report of the accumulation of cornification-associated proteins in BPD. Their localization in the alveolar parenchyma, primarily associated with alveolar type 1 (AT1) cells, suggests a role in the BPD postinjury response. In the ENDOs, redox balance and mitochondrial function pathways were modulated. Alternative mRNA splicing and cell proliferative functions were elevated in both populations, suggesting potential dysregulation of cell progenitor fate. This study characterized the proteome of epithelial and endothelial cells from the BPD lung for the first time, identifying population-specific changes in BPD pathogenesis.

BPD↗
DOE OSTI2021

Kindlin-3 mutation in mesenchymal stem cells results in enhanced chondrogenesis

Identifying patient mutations driving skeletal development disorders has driven our understanding of bone development. Integrin adhesion deficiency disease is caused by a Kindlin-3 (fermitin family member 3) mutation, and its inactivation results in bleeding disorders and osteopenia. In this study, we uncover a role for Kindlin-3 in the differentiation of bone marrow mesenchymal stem cells (BMSCs) down the chondrogenic lineage. Kindlin-3 expression increased with chondrogenic differentiation, similar to RUNX2. BMSCs isolated from a Kindlin-3 deficient patient expressed chondrocyte markers, including SOX9, under basal conditions, which were further enhanced with chondrogenic differentiation. Rescue of integrin activation by a constitutively activated β{sub 3} integrin construct increased adhesion to multiple extracellular matrices and reduced SOX9 expression to basal levels. Growth plates from mice expressing a mutated Kindlin-3 with the integrin binding site ablated demonstrated alterations in chondrocyte maturation similar to that seen with the human Kindlin-3 deficient BMSCs. These findings suggest that Kindlin-3 expression mirrors RUNX2 during chondrogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Ghrelin Modulates Differential Expression of Genes Relevant to Immune Activities and Antimicrobial Peptides in Primary Head Kidney Cells of Rainbow Trout ( Oncorhynchus mykiss )

Ghrelin is a peptide hormone/cytokine that regulates metabolic processes and plays essential roles in the immune system. To evaluate the immunomodulatory actions of ghrelin isoforms in rainbow trout (RT), an in vitro model was utilized with primary cells isolated from fish head kidney (HKD). These RT-HKD cells were treated with synthetic rainbow trout ghrelin and its truncated isoform, desVRQ-ghrelin, over time (0, 2, 4, and 24 h). Reverse transcriptase-coupled qPCR was used to measure the differential expression patterns of genes relevant to various immune processes and genes of antimicrobial peptides. Ghrelin isoform treatments resulted in functional perturbations that displayed overlapping and divergent patterns of gene expression. The differing actions between the two ghrelin isoforms on various assessed genes, and at differing time points, suggested that the two analogs may activate unique pathways, thereby eliciting distinct responses in fish immunity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Mitigation of rapid capacity decay in silicon-LiNi 0.6 Mn 0.2 Co 0.2 O 2 full batteries

Silicon (Si)-based materials have been considered as the most promising anode materials for high-energy-density lithium-ion batteries because of their higher storage capacity and similar operating voltage, as compared to the commercial graphite (Gr) anode. But the use of Si anodes including silicon-graphite (Si-Gr) blended anodes often leads to rapid capacity decay in Si-Gr/LiNixMnyCo z O 2 (x+y+z=1) full cells, which has been attributed to surface instability of the Si component. In addition to stabilizing the surface, this work investigates the potential of the Si-Gr blended anodes in a full-cell configuration and its impact on the capacity contribution from active components. Using dQ/dV plots of the full cells, a powerful but simple-to-implement differential potential approach is developed to decouple the capacity contribution and degradation from the graphite and silicon components. Data collected from three-electrode cells confirm the results from the differential potential approach, which suggests a voltage slippage to a higher voltage at the blended anode side. Additionally, the voltage slippage causes a reduced utilization of the Gr component and exacerbates side reactions between the Si-Gr anode and carbonate electrolytes. Furthermore, based on these failure mechanisms, we adopted a mitigation strategy to tune the open circuit voltage of the prelithiated anode while stabilizing the surface. As a result, the full cells with the modified Si-Gr anodes (mass loading, 2.5 mAh/cm 2 ) offer a highly reversible full-cell energy density of 390 Wh/kg (based on the mass of both anode and cathode materials in a full cell) with a cycling CE of 99.9% over 200 cycles.

25 ENERGY STORAGE↗
DOE OSTI2021

Mixing Cell Model: A One-Dimensional Numerical Model for Assessment of Water Flow and Contaminant Transport in the Unsaturated Zone

This report describes the Mixing Cell Model code, a one dimensional model for water flow and solute transport in the unsaturated zone under steady state or transient flow conditions. The model is based on the principles and assumptions underlying mixing-cell model formulations. The unsaturated zone is discretized into a series of independent mixing cells. Each cell may have unique hydrologic, lithologic, and sorptive properties. Ordinary differential equations describe the material (water and solute) balance within each cell. Water-flow equations are derived from the continuity equation, assuming that unit gradient conditions exist at all times in each cell. Pressure gradients are considered implicitly through model discretization. Unsaturated hydraulic conductivity and moisture contents are determined by the material specific moisture-characteristic curves. Solute-transport processes include explicit treatment of advective processes, first order chain decay, and linear sorption reactions. Dispersion is addressed through implicit and explicit dispersion. Implicit dispersion is an inherent feature of all mixing-cell models and originates from the formulation of the problem in terms of mass balance around fully mixed volume elements. Expressions are provided that relate implicit dispersion to the physical dispersion of the system. Two FORTRAN codes were developed to solve the water flow and solute-transport equations: (1) the Mixing Cell Model for Flow (MCMF) solves transient water-flow problems and (2) the Mixing Cell Model for Transport (MCMT) solves the solute-transport problem. The transient water-flow problem is typically solved first by estimating the water flux through each cell in the model domain as a function of time using the MCMF code. These data are stored in either ASCII or binary files that are later read by the solute transport code (MCMT). Code output includes solute pore water concentrations, water and solute inventories in each cell and at each specified output time, and water and solute fluxes through each cell and specified output time. Computer run times for coupled transient water flow and solute transport were typically several seconds on a 2 GHz Intel Pentium IV desktop computer. The model was benchmarked against analytical solutions and finite element approximations to the partial differential equations (PDE) describing unsaturated flow and transport. Differences between the maximum solute flux estimated by the mixing cell model and the PDE models were typically less than two percent. This revision includes an option for a fixed concentration lower boundary condition for diffusive fluxes for versions 020321 and later.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Differential roles of kinetic on- and off-rates in T-cell receptor signal integration revealed with a modified Fab’-DNA ligand

Antibody-derived T-cell receptor (TCR) agonists are commonly used to activate T cells. While antibodies can trigger TCRs regardless of clonotype, they bypass native T cell signal integration mechanisms that rely on monovalent, membrane-associated, and relatively weakly binding ligand in the context of cellular adhesion. Commonly used antibodies and their derivatives bind much more strongly than native peptide major histocompatibility complex (pMHC) ligands bind their cognate TCRs. Because ligand dwell time is a critical parameter that tightly correlates with physiological function of the TCR signaling system, there is a general need, both in research and therapeutics, for universal TCR ligands with controlled kinetic binding parameters. To this end, we have introduced point mutations into recombinantly expressed α-TCRβ H57 Fab to modulate the dwell time of monovalent Fab binding to TCR. When tethered to a supported lipid bilayer via DNA complementation, these monovalent Fab’-DNA ligands activate T cells with potencies well-correlated with their TCR binding dwell time. Single-molecule tracking studies in live T cells reveal that individual binding events between Fab'-DNA ligands and TCRs elicit local signaling responses closely resembling native pMHC. The unique combination of high on- and off-rates of the H57 R97L mutant enables direct observations of cooperative interplay between ligand binding and TCR-proximal condensation of the linker for activation of T cells, which is not readily visualized with pMHC. This work provides insights into how T cells integrate kinetic information from TCR ligands and introduces a method to develop affinity panels for polyclonal T cells, such as cells from a human patient.

Science & Technology - Other Topics↗
DOE OSTI2022

Radiation-Hardened GaN HEMT and Cell Design, Modeling, and Fabrication for Nuclear Instrumentation Applications

Recent advances in nuclear power generation technologies show great promise for efficient, safe generation of carbon-free power in the near future. Consequently, many new generation reactor designs are being pursued by government and industry groups, including both fission- and fusion-based technologies. Radiation- and temperature-tolerant sensor technology continues to advance, yet development of the electronics/instrumentation technologies suitable for these environments have fallen behind. Industry has adequately addressed harsh environment electronics needs for low earth orbit satellites, but the much more extreme conditions associated with electronics placed near or in a reactor core remain unaddressed. This project investigates the use of gallium nitride (GaN) circuit technology to address the unique needs for sensor interface electronics and communications in reactor environments. This report provides a summary of the first year’s project activities related to developing and optimizing devices and circuits for this GaN high electronic mobility transistor (HEMT) process. Activities reported include multiple analog and digital circuit designs simulated using custom Verilog-A models generated from measured GaN devices fabricated in the target process. Digital circuit designs included fundamental logic circuits such as an inverter, NAND, NOR, AND and OR gates, as well as a 5-stage ring oscillator. Each design was simulated using an open-source SPICE simulator, and an integrated circuit layout was produced of each design for use in future fabrication. Analog circuit designs focused on the fundamental building blocks to be used to construct sensor interface and communications circuits. These included current mirrors, matched differential pairs, and a Gilbert cell mixer design, each with an associated integrated circuit layout. Layout tools used for these designs included two open-source packages—KLayout and Magic—which were customized for specific use with the OSU GaN process layers. Design rules and preliminary device extraction capabilities were built for the Magic tool to enable device extraction and subsequent netlist generation for SPICE simulation. Finally, future research directions for year two are summarized. When the year-two directions are implemented, the project will be in position to advance the state of the art in electronics for near- or in-reactor sensor interfacing and communications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Novel data analysis method for obtaining better performance from a complex 3D-printed collimator

Additively manufactured scattered beam collimators are increasingly being employed to boost the sample to cell peak signal ratio in high pressure neutron diffraction studies because of manufacturing versatility and performance improvements. We study how the measured diffraction pattern is affected by the presence of a collimator downstream of the sample, and develop a novel protocol that provides more effective background rejection. This protocol takes into account critical performance-determinants that were identified in this study, namely: (i) effectively identifying the collimator pattern on the detector; (ii) understanding the dependence of this pattern on sample and cell composition; and (iii) accurately identifying and differentiating the different regions of the pattern on the detector based on the dependency of the cell or sample and finally (iv) resolving the intensities at regions of the detector where neutrons scattered from the sample are preferentially represented, in order to boost the sample to cell peak signal ratio. Application of this novel analysis protocol is shown to increase the collimator performance over the traditional method.

3D printing↗
DOE OSTI2020

Data-driven selection of stiff chemistry ODE solver in operator-splitting schemes

Most computational fluid dynamics simulations of practical combustion applications employ operator-splitting schemes, where chemistry and transport are separated and integrated with distinct numerical methods. The changes in composition due to chemistry are evaluated by solving ordinary differential equations (ODE) in each cell of the computational domain, which typically dominates the computational cost when detailed chemistry is considered. In this work, a data-driven approach for the selection of chemistry ODE solvers in operator-splitting schemes is presented. Neural networks are used to predict the ODE solvers CPU times and errors for a given thermochemical state. This allows the selection of an optimal ODE solver on a cell-by-cell, timestep-by-timestep basis. The models are trained using a wide set of thermochemical states generated through partially-stirred reactors and flames simulations. The methodology is validated by quantifying the prediction errors, the classification accuracy, and the computational speedup. The model predicts the optimal ODE solver for 70 to 95% of the validation cases and decreases the computional cost by a factor of 3 or more. The generalizability of the methodology to different chemical mechanisms and different fuels is assessed and it is shown that the model’s performance is only slightly degraded and its applicability is significantly enhanced if the inputs to the neural networks are restricted to a small set of thermochemical state variables present in most chemical mechanisms. In conclusion, the models are used in an homogeneous reactor case and a multi-dimensional CFD simulation of a diesel spray at high pressure where a speedup of more than 3 is achieved.

42 ENGINEERING↗