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The Photonics group top level processes regarding development and qualification of space flight hardware for optoelectronic components and optical systems along with our contributions and successes with LIDAR systems, space flight reliability heritage, and our testing capabilities are conveyed with this power point presentation.
Additive manufacturing of powder metallurgy (PM) disk superalloys can produce unique microstructures that differ from those usually encountered in traditional processing as the result of consolidation, forging, and heat treatments. Unusual variations in grain size, major and minor phase precipitate sizes, and defects can occur. The failure modes associated with these unique microstructures are of high interest. The objective of this study was to compare the failure modes for a low solvus, high refractory (LSHR) PM disk superalloy produced by electron-beam-melting additive manufacturing. Specimens were subsequently given different solution heat treatments and a fixed aging heat treatment. Tensile, creep, and fatigue failure modes were screened in tests at elevated temperatures. Failure modes were considered with respect to these unique microstructures.
Twenty novel Mn, Fe, and Cu complexes of ethylene cross-bridged tetraazamacrocycles with potentially copolymerizable allyl and benzyl pendant arms were synthesized and characterized. Multiple X-ray crystal structures demonstrate the cis-folded pseudo-octahedral geometry forced by the rigidifying ethylene cross-bridge and show that two cis coordination cites are available for interaction with substrate and oxidant. The Cu complexes were used to determine kinetic stability under harsh acidic and high-temperature conditions, which revealed that the cyclam-based ligands provide superior stabilization with half-lives of many minutes or even hours in 5 M HCl at 50–90 °C. Cyclic voltammetry studies of the Fe and Mn complexes reveal reversible redox processes indicating stabilization of Fe 2+ /Fe 3+ and Mn 2+ /Mn 3+ /Mn 4+ oxidation states, indicating the likelihood of catalytic oxidation for these complexes. Finally, dye-bleaching experiments with methylene blue, methyl orange, and rhodamine B demonstrate efficient catalytic decolorization and allow selection of the most successful monomeric catalysts for copolymerization to produce future heterogeneous water purification materials.
Human carbonic anhydrase II (hCAII) is a metalloenzyme essential to critical physiological processes in the body. hCA inhibitors are used clinically for the treatment of indications ranging from glaucoma to epilepsy. Targeted protein degraders have emerged as a promising means of inducing the degradation of disease-implicated proteins by using the endogenous quality control mechanisms of a cell. Here, a series of heterobifunctional degrader candidates targeting hCAII were developed from a simple aryl sulfonamide fragment. Degrader candidates were functionalized to produce either cereblon E3 ubiquitin ligase (CRBN) recruiting proteolysis targeting chimeras (PROTACs) or adamantyl-based hydrophobic tags (HyTs). Screens in HEK293 cells identified two PROTAC small-molecule degraders of hCA. Optimization of linker length and composition yielded a degrader with sub-nanomolar potency and sustained depletion of hCAII over prolonged treatments. Mechanistic studies suggest that this optimized degrader depletes hCAII through the same mechanism as previously reported CRBN-recruiting heterobifunctional degraders.
In May 2022, the newest supercomputer to top the TOP 500 list was Frontier at Oak Ridge National Laboratory, demonstrating the capability of computing more than 1.1 quintillion (1018) floating-point calculations every second. Driving this ground-breaking rate of computing is Frontier’s more than 37,000 graphics processing units (GPUs) and 9,408 central processing units (CPUs). In total, Frontier contains more than 60 million parts. At this scale, the smallest margin of error may generate hundreds of hardware errors across the system. These errors are capable of directly hindering world-class science performed on Frontier if not found. In this work, we describe and evaluate two strategies for finding hardware-level faults in Frontier’s 9,408 compute nodes. There are two strategies developed: the first uses the Slurm scheduler to scavenge available compute time to run the node screen, the second builds upon the lessons learned in the first strategy and enforces a weekly screen of each node. Using June 2023 as a case study, we find that the first scheduling strategy consumed more than ten times the resources as the second scheduling strategy, but successfully detected five hardware defects in Frontier. We summarize the lessons learned while developing and running a node screen on the world’s first exascale supercomputer.
Microwave absorbing catalysts have the potential to make thermal reactions such as methane reforming (CH4 + CO2 + H2O → H2 + CO) into carbon negative processes when coupled with decarbonized electricity. Due to microwaves directly heating the catalyst rather than heating the reactor and gases, even high temperature reactions such as dry reforming methane (DRM, CH4 + CO2 → H2 + CO) can be achieved rapidly, efficiently, and on-demand, ideal for coupling with intermittent renewable electricity. However, microwave catalysts present unique design challenges due to the same material needing to both efficiently absorb microwaves in oxidative and reductive reaction conditions and be an efficient and stable catalyst in inherently non-isothermal reactors. We screened from over 28 catalysts in the La0.8Sr0.2(Co-Ni-Mn)O3 perovskite solid-solution family to determine promising microwave reforming catalysts and identify design principles for effective materials. The best performing catalyst candidate was able to produce syngas ratios (H2:CO) from 1-3, and scale up testing showed CO and H2 production efficiencies rivaling conventional carbon intensive steam reforming efficiencies at the liters per minute level of production.
The overarching goal of this project is to understand the phase stability and mechanical behavior of non-stoichiometric multi-principal element alloy (MPEA) materials. In order to identify suitable alloys, we plan to use a combinatorial thin film screening approach, in collaboration with scientists at Lawrence Berkeley National Laboratory who are performing computational work as well as complementary experimental work. Specific tasks within the scope of this project include the fabrication, using thin film deposition from six sputtering targets, of combinatorial samples with multi-dimensional gradients in composition and microstructure. These samples are studied to screen MPEA systems for promising candidate alloys with specific composition(s), based on characterization of composition, structure and mechanical behavior across the thin film. We want to produce single-phase MPEAs with chemical homogeneity in a given thin film region, simple grain structures, and no intermetallic phases present. Gradient films facilitate first-pass screening for desirable characteristics and inform the next stage of work that involves fabrication of bulk MPEA specimens for (tensile) mechanical testing and characterization. To make the bulk alloys, metal (elemental) pieces are melted to form MPEAs, followed by heat treatment to homogenize the composition and microstructure. A subset of alloys is also cast, using vacuum arc melting, to yield larger samples (diameter ~1 cm and length ~5-10 cm) and these allow us to assess viability of scale-up for the alloys in structural applications. Further processing plans include rolling and heat treatment to recrystallize selected bulk MPEAs and grow grains to different extents, in order to investigate size effects in the mechanical behavior of MPEAs. Microspecimen testing will be performed (primarily in tension) to assess the mechanical behavior over a range of temperatures. The deformation microstructure of mechanically tested alloys will be characterized using transmission electron microscopy (TEM) to provide a scientific basis for understanding the structure-property relationships in MPEA mechanical behavior.
Although several observations of material changes on-orbit have been reported, mechanistic understanding has not yet become clear because new sets of non-intuitive processes are occurring on orbit. Reactant kinetic energy, low collision rates and surface/adsorbate interactions must be considered in the analysis of these observations. The specific example of oxide formation of elemental materials is examined in terms of thermodynamics and possible reaction pathways. On the basis of this approach, a rational trend emerges from the orbital behavior of these samples. The role of reactant kinetic energy as opposed to internal energy in chemiluminescent product formation is also presented. Development of a systematic thermochemical approach may be useful in making screening predictions of long-term material behavior on-orbit.
NASA Glenn has invested over $1.5 million in engineering, and infrastructure upgrades to renovate an existing test facility at the NASA Glenn Research Center (GRC), which is now being used as an Alternative Fuels Laboratory. Facility systems have demonstrated reliability and consistency for continuous and safe operations in Fischer-Tropsch (F-T) synthesis and thermal stability testing. This effort is supported by the NASA Fundamental Aeronautics Subsonic Fixed Wing project. The purpose of this test facility is to conduct bench scale F-T catalyst screening experiments. These experiments require the use of a synthesis gas feedstock, which will enable the investigation of F-T reaction kinetics, product yields and hydrocarbon distributions. Currently the facility has the capability of performing three simultaneous reactor screening tests, along with a fourth fixed-bed reactor for catalyst activation studies. Product gas composition and performance data can be continuously obtained with an automated gas sampling system, which directly connects the reactors to a micro-gas chromatograph (micro GC). Liquid and molten product samples are collected intermittently and are analyzed by injecting as a diluted sample into designated gas chromatograph units. The test facility also has the capability of performing thermal stability experiments of alternative aviation fuels with the use of a Hot Liquid Process Simulator (HLPS) (Ref. 1) in accordance to ASTM D 3241 "Thermal Oxidation Stability of Aviation Fuels" (JFTOT method) (Ref. 2). An Ellipsometer will be used to study fuel fouling thicknesses on heated tubes from the HLPS experiments. A detailed overview of the test facility systems and capabilities are described in this paper.
Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.
Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.
More than 40,000 infrared measurements of stellar sources have been obtained since November, 1976 during the ongoing process of compiling an Equatorial Infrared Catalogue. Because of the problem of eliminating spurious sources, which has affected earlier space surveys, an extensive effort is being made to verify the sources by means of (1) repetitive observations by satellite sensors, (2) cross correlation with a large data base developed from ground-based and space surveys at other wavelengths, and (3) investigation of a significant subset of the sources with a ground-based infrared telescope. As sources are verified, they are transferred from a working list to a screened preliminary version of the catalogue. The catalogue comprises the only survey of a significant area of the sky that has been accomplished (or is presently planned) with positional accuracies of a few arc seconds at a wavelength of not less than 2 microns.
Science On a Sphere (SOS) is a large visualization system, developed by the National Oceanic and Atmospheric Administration (NOAH), that uses computers running Redhat Linux and four video projectors to display animated data onto the outside of a sphere. Said another way, SOS is a stationary globe that can show dynamic, animated images in spherical form. Visualization of cylindrical data maps show planets, their atmosphere, oceans, and land, in very realistic form. The SOS system uses 4 video projectors to display images onto the sphere. Each projector is driven by a separate computer, and a fifth computer is used to control the operation of the display computers. Each computer is a relatively powerful PC with a high-end graphics card. The video projectors have native XGA resolution. The projectors are placed at the corners of a 30' x 30' square with a 68" carbon fiber sphere suspended in the center of the square. The equator of the sphere is typically located 86" off the floor. SOS uses common image formats such as JPEG, or TIFF in a very specific, but simple form; the images are plotted on an equatorial cylindrical equidistant projection, or as it is commonly known, a latitude/longitude grid, where the image is twice as wide as it is high (rectangular). 2048x] 024 is the minimum usable spatial resolution without some noticeable pixelation. Labels and text can be applied within the image, or using a timestamp-like feature within the SOS system software. There are two basic modes of operation for SOS: displaying a single image or an animated sequence of frames. The frame or frames can be setup to rotate or tilt, as in a planetary rotation. Sequences of images that animate through time produce a movie visualization, with or without an overlain soundtrack. After the images are processed, SOS will display the images in sequence and play them like a movie across the entire sphere surface. Movies can be of any arbitrary length, limited mainly by disk space and can be animated at frame rates up to 30 frames per second. Transitions, special effects, and other computer graphics techniques can be added to a sequence through the use of off-the-shelf software, like Final Cut Pro. However, one drawback is that the Sphere cannot be used in the same manner as a flat movie screen; images cannot be pushed to a "side", a highlighted area must be viewable to all sides of the room simultaneously, and some transitions do not work as well as others. We discuss these issues and workarounds in our poster.
Lignin is a random heteropolymer that has been extensively studied as a renewable source of aromatic precursors for high-value chemicals, biofuels, and bioplastics. A key challenge in lignin valorization is the structural and compositional heterogeneity of lignin feedstocks. Solvent-based approaches are commonly used to fractionate lignin to reduce this heterogeneity, but solvent selection can be challenging due to variability in lignin composition. In this work, we developed computational methods to predict good and poor organic solvents as a function of lignin composition. We analyzed 28 different linear pentamer structures, 18 from known libraries and 10 hypothetical polymers, and calculated their activity coefficients in 50 different organic solvents by using the conductor-like screening model for realistic solvents. We used these data to train a regression model that enabled the extensive investigation of the impact of solvent and monolignol compositions on predicted lignin solubility. The exhaustive exploration of solubility trends using model predictions revealed sets of solvents, identified using Kamlet–Taft parameters, that are predicted to promote lignin dissolution regardless of lignin composition. We further identified solvents expected to selectively isolate lignin fractions enriched in certain subunits. Furthermore, these results establish heuristic guidelines for solvent selection that can be used to tailor fractionation processes for lignin feedstocks of distinct composition or to design new processes that isolate fractions with higher proportions of selected subunits.
A figure depicts an apparatus that simultaneously records magnified ordinary top-view video images and laser shadowgraph video images of a sessile drop on a flat, horizontal substrate that can be opaque or translucent and is at least partially specularly reflective. The diameter, contact angle, and rate of evaporation of the drop as functions of time can be calculated from the apparent diameters of the drop in sequences of the images acquired at known time intervals, and the shadowgrams that contain flow patterns indicative of thermocapillary convection (if any) within the drop. These time-dependent parameters and flow patterns are important for understanding the physical processes involved in the spreading and evaporation of drops. The apparatus includes a source of white light and a laser (both omitted from the figure), which are used to form the ordinary image and the shadowgram, respectively. Charge-coupled-device (CCD) camera 1 (with zoom) acquires the ordinary video images, while CCD camera 2 acquires the shadowgrams. With respect to the portion of laser light specularly reflected from the substrate, the drop acts as a plano-convex lens, focusing the laser beam to a shadowgram on the projection screen in front of CCD camera 2. The equations for calculating the diameter, contact angle, and rate of evaporation of the drop are readily derived on the basis of Snell s law of refraction and the geometry of the optics.
The DebriSat project analyzes the debris from a hypervelocity impact test conducted on a 56 kg-simulated satellite target in 2014. Its purpose is to generate a comprehensive database of the size, mass, material, shape, and the radar and optical properties of fragments generated from orbital collisions of modern-built spacecraft. Three hundred ninety-one foam catch panels from the DebriSat test have been X-rayed to locate the particles within them for subsequent extraction and assessment. The data from the tens of thousands of extracted particles has heretofore been the focus of the debris assessment. The work presented here connects the X-ray sample location images to reconstruct the 3D distribution of the entire fragment cloud. Although some errors are inherent to the process, this 3D database is valuable for qualitative studies of size and energy distributions. Further, the 3D database can indicate the extent of bending or breaking of the fragments as they decelerated to full capture. By virtue of its full sphere perspective, the 3D database allows graphical insight to the physics of the collision and breakup. This 3D representation has been developed as a “point and click” graphical interface to retrieve the full data set on individual recovered and assessed fragments within the growing database. Overall, this macro-level screening technique has added enormous insight to the experiment in unexpected ways.
The multi-subunit translation initiation factor eIF2B is a control node for protein synthesis. eIF2B activity is canonically modulated through stress-responsive phosphorylation of its substrate eIF2. The eIF2B regulatory subcomplex is evolutionarily related to sugar-metabolizing enzymes, but the biological relevance of this relationship was unknown. To identify natural ligands that might regulate eIF2B, we conduct unbiased binding- and activity-based screens followed by structural studies. We find that sugar phosphates occupy the ancestral catalytic site in the eIF2Bα subunit, promote eIF2B holoenzyme formation and enhance enzymatic activity towards eIF2. A mutant in the eIF2Bα ligand pocket that causes Vanishing White Matter disease fails to engage and is not stimulated by sugar phosphates. These data underscore the importance of allosteric metabolite modulation for proper eIF2B function. We propose that eIF2B evolved to couple nutrient status via sugar phosphate sensing with the rate of protein synthesis, one of the most energetically costly cellular processes.
The transputer parallel processing lab at NASA Lewis Research Center (LeRC) consists of 69 processors (transputers) that can be connected into various networks for use in general purpose concurrent processing applications. The main goal of the lab is to develop concurrent scientific and engineering application programs that will take advantage of the computational speed increases available on a parallel processor over the traditional sequential processor. Current research involves the development of basic programming tools. These tools will help standardize program interfaces to specific hardware by providing a set of common libraries for applications programmers. The thrust of the current effort is in developing a set of tools for graphics rendering/animation. The applications programmer currently has two options for on-screen plotting. One option can be used for static graphics displays and the other can be used for animated motion. The option for static display involves the use of 2-D graphics primitives that can be called from within an application program. These routines perform the standard 2-D geometric graphics operations in real-coordinate space as well as allowing multiple windows on a single screen.