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DOE OSTI2022

Multivariate analysis: An essential for studying complex glasses

Understanding the impact of individual compositional components on the devitrification of complex multicomponent glasses, for example, 10–50+ oxides, typically requires numerous studies to examine each component's impact. Here we apply exploratory data analysis (EDA) to a heterogeneous data set of silicate glasses to determine the cations’ individual and interacting effects on the crystallization of nepheline (nominally NaAlSiO 4 ). Our data consisted of 795 simulated high-level nuclear waste glasses composed of, on average, 50 oxide components. We determine the interactions in the heterogeneous data that cause deviations from the behavior found in simplified composition studies. Using both univariate and bivariate EDA techniques, we demonstrate the importance of including calculated structural glass parameters on nepheline's devitrification, including field strength, cation-to-anion radius ratio, and single-bond strength. Here, we also show that studies with simplified glass compositions may fall short in generating knowledge directly transferrable to complex glass compositions. The method used in this study has the potential to inform experimental design for simplified compositions (~6+ oxides) that can generate knowledge directly transferrable to complex, multivariable compositions. The observations reported here have broad implications for any study attempting to map the physical properties of a complex glass containing numerous cations.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Simultaneous carbon catabolite repression governs sugar and aromatic co-utilization in Pseudomonas putida M2

ABSTRACT Pseudomonas putida have emerged as promising biocatalysts for the conversion of sugars and aromatic compounds obtained from lignocellulosic biomass. Understanding the role of carbon catabolite repression (CCR) in these strains is critical to optimize biomass conversion to fuels and chemicals. The CCR functioning in P. putida M2, a strain capable of consuming both hexose and pentose sugars as well as aromatic compounds, was investigated by cultivation experiments, proteomics, and CRISPRi-based gene repression. Strain M2 co-utilized sugars and aromatic compounds simultaneously; however, during cultivation with glucose and aromatic compounds ( p- coumarate and ferulate) mixture, intermediates (4-hydroxybenzoate and vanillate) accumulated, and substrate consumption was incomplete. In contrast, xylose-aromatic consumption resulted in transient intermediate accumulation and complete aromatic consumption, while xylose was incompletely consumed. Proteomics analysis revealed that glucose exerted stronger repression than xylose on the aromatic catabolic proteins. Key glucose (Eda) and xylose (XylX) catabolic proteins were also identified at lower abundance during cultivation with aromatic compounds implying simultaneous catabolite repression by sugars and aromatic compounds. Reduction of crc expression via CRISPRi led to faster growth and glucose and p -coumarate uptake in the CRISPRi strains compared to the control, while no difference was observed on xylose+ p -coumarate. The increased abundances of Eda and amino acid biosynthesis proteins in the CRISPRi strain further supported these observations. Lastly, small RNAs (sRNAs) sequencing results showed that CrcY and CrcZ homologues levels in M2, previously identified in P. putida strains, were lower under strong CCR (glucose+ p -coumarate) condition compared to when repression was absent ( p -coumarate or glucose only). IMPORTANCE A newly isolated Pseudomonas putida strain, P. putida M2, can utilize both hexose and pentose sugars as well as aromatic compounds making it a promising host for the valorization of lignocellulosic biomass. Pseudomonads have developed a regulatory strategy, carbon catabolite repression, to control the assimilation of carbon sources in the environment. Carbon catabolite repression may impede the simultaneous and complete metabolism of sugars and aromatic compounds present in lignocellulosic biomass and hinder the development of an efficient industrial biocatalyst. This study provides insight into the cellular physiology and proteome during mixed-substrate utilization in P. putida M2. The phenotypic and proteomics results demonstrated simultaneous catabolite repression in the sugar-aromatic mixtures, while the CRISPRi and sRNA sequencing demonstrated the potential role of the crc gene and small RNAs in carbon catabolite repression.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Δ133p53 coordinates ECM-driven morphogenesis and gene expression in 3-dimensional mammary epithelial acini

Growing evidence indicates that p53 has a crucial role in normal tissue development. The role of the canonical p53 (p53α) and its 12± isoforms in development and homeostasis of healthy tissue remains poorly understood. Here we demonstrate that Δ133p53, three short isoforms of p53 isoform, responds specifically to laminin-111 and plays an important regulatory role in formation of mammary organoids in concert with p53α. We demonstrate that down-modulation of Δ133p53 isoforms leads to changes in gene expression of extracellular matrix molecules: fibronectin (FN), EDA+-FN, laminin α5, and laminin α3 in human breast epithelial cells. These changes resulted in increased actin stress fibers and enhanced migratory behavior of cells in 2-dimensional culture. We found that α5β1-integrin coupled with the extracellularly deposited EDA+-FN activates Akt signaling pathway in 3-dimensional (3D) culture when Δ133p53 is dysregulated. Cells that do not express detectable Δ133p53 isoforms or express low levels of these isoforms failed to form polarized structures in 3D. These results uncover that Δ133p53 isoforms coordinate expression and deposition of organ-specific ECM molecules that are critical for maintenance of tissue architecture and function.

Lee, Sun-Young (ORCID:000000034970241X)↗

DOE OSTI2022

Reduced Graphene Oxide Aerogels with Functionalization-Mediated Disordered Stacking for Sodium-Ion Batteries

Surface modified reduced graphene oxide (rGO) aerogels were synthesized using the hydrothermal method. Ethylene diamine (EDA) and α-cyclodextrin (CD) were used to functionalize the surface of the graphene oxide layers. The oxygen reduction and surface modification occurred in-situ during the hydrothermal self-assembly process. The chemical functionality and structure of the resulting ethylene diamine modified (rGO-EDA) and cyclodextrin modified (rGO-CD) aerogels as well as of the pristine unmodified rGO aerogel were studied using XPS, SEM, XRD, and SANS techniques. The overall surface composition showed a significant decrease in the oxygen content for all synthesized aerogels. The surface modified aerogels were characterized by a disordered stacking of the assembled rGO layers. The surface functionalities resulted in a broad distribution of the interlayer spacing and introduced structural heterogeneities. Such disordered structures can enable a better adsorption mechanism of the sodium ions. Coin cells based on the synthesized aerogels and sodium metal were assembled and tested at several charge and discharge rates. The correlation between the surface functionality of the rGO, the induced structural heterogeneities due to the disordered stacking, and the electrochemical performance of sodium-ion batteries were investigated. Operando XRD measurements were carried out during the battery cycling to investigate the adsorption or intercalation nature of the sodiation mechanism.

25 ENERGY STORAGE↗

DOE OSTI2025

Using feature importance as an exploratory data analysis tool on Earth system models

Abstract. Machine learning (ML) models are commonly used to generate predictions, but these models can also support the discovery of new science. Generating accurate predictions necessitates that a model captures the structure of the underlying data. If the structure is properly extracted, ML could be a useful exploratory and evidential tool. In this paper, we present a case study that demonstrates the use of ML for exploratory data analysis (EDA) in the climate space. We apply the ML explainability method of spatiotemporal zeroed feature importance (stZFI) to understand how climate-variable associations evolve over space and time. Our analyses focus on data from ensembles of Earth system models (ESMs) which provide data on different climate states and conditions. We elect to work with ESM ensembles since they allow us to compare feature importance across alternative scenarios not available with observed data. The ensembles also account for natural variability so that we can distinguish between signal and noise due to natural climate variability when computing feature importance. The use of perturbed initial condition ensembles introduces variability mimicking the natural variability in the atmosphere; thus the signals emerging using feature importance (FI) can be evaluated against the natural variability in the climate system. For our analyses, we consider the 1991 volcanic eruption of Mount Pinatubo, which was a large stratospheric aerosol injection. We explore the climate pathway associated with the eruption from aerosols to radiation to temperature at both the near-surface and stratospheric levels. In addition to applying the method to data generated from two different ESMs, we apply stZFI to reanalysis data to compare the associations identified by stZFI. We show how stZFI tracks the importance of aerosol optical depth over time on forecasting temperatures. This case study illustrates usefulness of an ML tool (stZFI) for EDA on a well-studied climate exemplar.

Ries, Daniel (ORCID:0000000250294647)↗

NASA NTRS1997

Environmental Radiation Measurements on MIR Station: Internal Experiment - Program 1

Environmental radiation levels on the Russian space station Mir are being monitored under differing shielding conditions by a series of six area passive dosimeters (APDs) placed at individual locations inside the Core and Kvant 2 modules, and by an External Dosimeter Array (EDA) to be-deployed on the exterior surface of the Kvant 2 module. Each APD and the EDA contains CR-39 plastic nuclear track detectors (PNTDs) for measurement of LET spectra and TLDs for absorbed dose measurements. Two of the missions, NASA-2/Mir-21 and NASA-3/Mir-22 have been completed and the six APDs from each mission returned to Earth from Mir. This report covers progress to date on the analysis of TLDs and PNTDs from these two missions. For NASA-2/Mir-21, average mission absorbed dose rates varied from 271 to 407 micro-Gy/d at the APDS. For NASA-3/Mir-22, average mission absorbed dose rates varied from 265 to 421 micro-Gy/d.

Benton, E. V.↗

NASA NTRS1997

Electronic Design Automation: Integrating the Design and Manufacturing Functions

As the complexity of electronic systems grows, the traditional design practice, a sequential process, is replaced by concurrent design methodologies. A major advantage of concurrent design is that the feedback from software and manufacturing engineers can be easily incorporated into the design. The implementation of concurrent engineering methodologies is greatly facilitated by employing the latest Electronic Design Automation (EDA) tools. These tools offer integrated simulation of the electrical, mechanical, and manufacturing functions and support virtual prototyping, rapid prototyping, and hardware-software co-design. This report presents recommendations for enhancing the electronic design and manufacturing capabilities and procedures at JSC based on a concurrent design methodology that employs EDA tools.

Bachnak, Rafic↗

NASA NTRS1999

National Aeronautics and Space Administration (NASA)/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program, 1998

The continuous increase in complexity of electronic systems is making the design and manufacturing of such systems more challenging than ever before. As a result, designers are finding it impossible to design efficient systems without the use of sophisticated Electronic Design Automation (EDA) tools. These tools offer integrated simulation of the electrical, mechanical, and manufacturing functions and lead to a correct by design methodology. This report identifies the EDA tools that would be needed to design, analyze, simulate, and evaluate electronic systems for spacecraft vehicles. In addition, the report presents recommendations to enhance the current JSC electronic design capabilities. This includes cost information and a discussion as to the impact, both positive and negative, of implementing the recommendations.

Richard B Bannero↗

NASA NTRS1999

Update of the Development of a Low Cost Data Acquisition System for the Space Shuttle Solid Rocket Booster Program

The space shuttle solid rocket boosters (SRBs) experience a severe environment during their brief flight. During the last few years several SRB's have sustained noticeable structural damage. The environmental characteristics (vibration, structure, and thermal) encountered by the SRB's during ascent, descent and water impact are in most cases unknown. A developmental flight instrumentation (DFI) system collected data from the SRBs' first four flights in the early 1980's, and after the first three flights during the shuttle return-to-flight phase after the Challenger accident. However, the DFI data collected are of low fidelity and do not correlate well with cases of observed structural damage. The DFI system was evaluated for reuse, but the cost to fly it was prohibitive. The space shuttle is presently scheduled to fly until 2030. To support the shuttle flight schedule, avionics on the SRB's will be upgraded. The environments on the different sections of the SRB will need to be defined more completely to properly qualify the avionics for multiple flights. The DFI data previously gathered do not provide enough information to properly qualify the avionics. Marshall Space Flight Center's (MSFC) SRB Project Office requested the Science and Engineering (S&E) Directorate to develop a stand-alone data acquisition system that could collect data from any area of the booster. In answer to this requirement, S&E developed the Enhanced Data Acquisition System (EDAS). To minimize development time and cost, the development team used state-of-the-art commercial off the shelf (COTS) equipment. The first two flights of this system occurred on shuttle mission STS-91 in June 1998 and STS-95 in October 1998. Twenty-one measurements were successfully recorded on the STS-91 right hand booster, providing new accelerometer, strain, temperature, and heating rate data to analysts. Twenty-four measurements were successfully recorded on the STS-95 left hand booster, providing data from the booster and the external tank. This paper summarizes the effort to develop, test, qualify and fly the EDAS to meet SRB flight and data collection requirements.

Crawford, Kevin↗

NASA NTRS1999

Using a Commerical off the Shelf Data Acquisition System for the Space Shuttle Solid Rocket Booster Program

Crawford, Kevin↗

NASA NTRS2017

Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

Classification; Climate change; Crop model; Ensemb↗

NASA NTRS2014

Trajectory Prediction Accuracy and Error Sources for Regional Jet Descents: Results of a 2010 Flight Trial at Denver International Airport using SkyWest Revenue Flights - Part II

The Efficient Descent Advisor (EDA) controller automation tool generates trajectory-based speed, path, and altitude-profile advisories to facilitate efficient, continuous descents into congested terminal airspace. While prior field trials have assessed the trajectory prediction accuracy for large jet (i.e., Boeing and Airbus) types, smaller (i.e., regional and business) jet types present unique challenges involving different descent procedures and Flight Management System (FMS) capabilities. This paper quantifies the trajectory prediction accuracy for small jet revenue flight descents based on SkyWest Canadair Regional Jet 200, 700, and 900 aircraft arrivals to Denver in the fall of 2010. Post flight test data analysis and SkyWest pilot interviews uncovered unexpected variation between flight crews due to different interpretations of (1) which fixed flight path angle (FPA) to fly based on the flight trial procedure and (2) how to fly the descent to achieve the target FPA. Pilot reports were used to select a subset of flights where pilots indicated an FPA according to the flight trial procedure to remove the unexpected variation due to (1) to focus on (2). Results for the subset for en-route descents, from prior to top of descent to the meter fix 30 to 130 nmi downstream, indicate that aircraft arrived to the meter fix six seconds early with about a twelve second standard deviation. Large FPA errors up to one degree relative to the EDA flight trial procedure were detected after the flight trial as a characteristic of the unexpected variation. It is recommended that quantitative validation be performed during future flight trials so that experimental procedures can be adjusted if unexpected results are detected.

Field Test Results↗

NASA NTRS2012

Spacecraft-to-Earth Communications for Juno and Mars Science Laboratory Critical Events

Deep Space communications typically utilize closed loop receivers and Binary Phase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK). Critical spacecraft events include orbit insertion and entry, descent, and landing.---Low gain antennas--> low signal -to-noise-ratio.---High dynamics such as parachute deployment or spin --> Doppler shift. During critical events, open loop receivers and Multiple Frequency Shift Keying (MFSK) used. Entry, Descent, Landing (EDL) Data Analysis (EDA) system detects tones in real-time.

radio science↗

DOE OSTI2020

Thermally Activated Adsorption in Metal–Organic Frameworks with a Temperature‐Tunable Diffusion Barrier Layer

Abstract Modification of the external surfaces of metal–organic frameworks offers a new level of control over their adsorption behavior. It was previously shown that capping of MOFs with ethylenediamine (EDA) can effectively retain small gaseous molecules at room temperature. Reported here is a temperature‐induced variation in the capping‐layer gate‐opening mechanism through a combination of in situ infared experiments and ab initio simulations of the capping layer. An atypical acceleration and increase in the loading of weakly adsorbed molecules upon raising the temperature above room temperature is observed. These findings show the discovery of novel temperature‐dependent kinetics that goes beyond standard kinetics and suggest a new avenue for tailoring selective adsorption by thermally tuning the surface barrier.

Tan, Kui↗

DOE OSTI2020

Thermally activated adsorption in metal–organic frameworks with a temperature–tunable diffusion barrier layer

Modification of the external surfaces of metal organic frameworks offers a new level of control over their adsorption behavior. Here, we have previously shown that capping of MOFs with ethylenediamine (EDA) can effectively retain small gaseous molecules at room temperature. Here, we report a temperature–induced variation in the capping–layer gate opening mechanism through a combination of in situ IR experiments and ab initio simulations of the capping layer. We find an atypical acceleration and increase in the loading of weakly adsorbed molecules upon raising the temperature above room temperature. Our findings show the discovery of a novel temperature–dependent kinetics that goes beyond standard kinetics and suggest a new avenue for tailoring selective adsorption by thermally tuning the surface barrier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Assembling Phenothiazine into a Porous Coordination Cage to Improve Its Photocatalytic Efficiency for Organic Transformations

Abstract Photo‐catalysis by small‐molecules is often limited by catalyst degradation and low electron‐transfer efficiency. Herein we report a stable N‐phenyl‐phenothiazine (PTH)‐derived porous coordination cage (PCC) as a highly efficient photocatalyst. By the incorporation of the photocatalytic PTH moiety into a PCC, aggregation‐induced quenching (AIQ) was shown to be reduced. An improvement in catalyst stability was discovered, ascribed to the synergistic effects of the PTH moieties. The catalyst, operating through a photolytic single‐electron transfer, was utilized for photo‐catalyzed dehalogenation and borylation. Evaluation of the catalytic mechanism in the borylation reaction showed that the improved performance results from the more efficient formation of the electron donor‐acceptor (EDA) complex with the cage. This discovery provides a potential strategy to improve the photophysical properties and stabilities of small‐molecule organic photocatalysts via supramolecular chemistry.

Chemistry↗

DOE OSTI2025

Parallel sorting algorithm classification: is manual instrumentation necessary?

Understanding parallel algorithms is crucial for accelerating scientific simulations on complex, distributed memory, high-performance computers. Modern algorithm classification approaches learn semantics directly from source code to differentiate between algorithms, however, accessing source code is not always possible. We can learn about parallel algorithms from observing their performance, as programs running the same algorithms and using the same hardware should exhibit similar performance characteristics. We present an approach to learn algorithm classes from parallel performance data directly in order to classify algorithms without access to the source code. We extend previous work to enable classifying parallel sorting algorithms using automatic instrumentation instead of requiring manual region annotations in the source code. In this work, we design and demonstrate a study for classification of parallel sorting algorithms using parallel performance data collected from automatic instrumentation, and evaluate the performance of our new methodology on classification. We leverage Caliper to collect the performance data, Thicket for our exploratory data analysis (EDA), and PyTorch and Scikit-learn to evaluate the effectiveness of random forests, support vector machines (SVMs), decision trees, neural networks, and logistic regressions on parallel performance data. Additionally, we study noise in parallel performance data, whether the removal of noise and pre-processing of the data is necessary to accurately classify parallel sorting algorithms, and determine the effectiveness of features created from performance data. In conclusion, we demonstrate classification accuracy for these five different models of up to 97.7% across four different parallel algorithm classes.

Algorithm Classification↗

DOE OSTI2022

Research on oxygen solubility in aqueous amine solvents with common additives used for CO 2 chemical absorption

Oxidative degradation in amine based post-combustion carbon capture (PCCC) leads to solvent losses and decreased solvent performance. Oxygen (O 2 ) in the flue gas is dissolved into the aqueous solvent and can reactively degrade the amine component. Advanced aqueous amine solvents are designed to contain additional surfactant and anti-foam additives as well as two types of corrosion inhibitors. These additives contribute to improve the solvent performance while reducing foaming and corrosion of expensive equipment. This work examines the impact of these additives on oxygen solubility (or dissolved oxygen - DO) in various aqueous amines used in PCCC including ethanolamine (MEA), 1-amino-2-propanol (A2P), 2-amino-1-propanol (2A1P), 2-(methylamino)-ethanol (NMEA), 2-(ethylamine)-ethanol (2EAE), diethanolamine (DEA), methyl-diethanolamine (MDEA), dimethylethanolamine (DMEA), piperazine (PZ), 1,2-ethyldiamine (EDA), and 1,6 hexadiamine (HDA). Further, the impact of carbon loading on oxygen solubility with and without these additives was also examined. The surfactant and anti-foam additives had minimal impact on DO for all the solvents investigated. The two anticorrosion additives had opposite effects in the measured DO, 2- mercaptobenzothiazole (MBT) decreased the DO concentration, and sodium metavanadate showed an increase. These results indicate that several of these common additives can be expected to minimally affect DO related oxidative degradation in these advance amine solvents.

60 APPLIED LIFE SCIENCES↗