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131 records · Page 8

Qualifying Bulk Metallic Glass Gear Materials for Spacecraft Applications

NASA is evaluating bulk metallic glass (BMG) gears for extreme environment (cryogenic) applications; e.g., Europa Lander. The main purpose of this report is to recommend a quality assurance (QA) protocol for the production of consistent and reliable gear castings. Currently, there are two, separate manufacturers involved; Materion Corporation produces re-melt stock and Visser Precision Cast, Inc. produces BMG castings. Division of the existing alloy specifications document into material supplier-specific documents is proposed. Until a composition-based specification is established, processability- and performance-based methodologies may be an option during manufacturing development. It is recommended that each of the documents has a distinct focus; the processing behavior of crystalline feedstock, and the mechanical behavior of amorphous castings. The report addresses the “gray area” in QA testing between these materials suppliers by outlining an equitable division of responsibilities. The use of a number of dedicated reference dies to produce witness materials for physical and mechanical property evaluation is strongly recommended. Allocation of QA tests between screen testing of gear castings, and formal testing of witness materials, including cryogenic properties, is also proposed. The most effective suite of tests for both physical and mechanical property determination are down-selected from available national and international standards. The contents of this report create a solid basis for selection of QA tests, thereby setting the stage for negotiations between the materials suppliers and the customer.This technical paper:a) provides recommendations to advance materials specifications document JPL D-56223,Rev. A from “draft” to “preliminary” status;b) proposes division of the current document into two supplier-specific documents;c) separates testing methods by “ingots/castings” and “witness materials”;d) classifies test methodology based on “processability” and “performance”;e) assembles candidate ASTM specifications for “screen testing” and “formal testing”;f) identifies standard tests compatible with evaluation of BMG flexspline gears;g) suggests division of responsibilities for processability and performance testing; andh) addresses the QA “gray area” between production of ingots and castings.The report recommends that:a) processability- and performance-based QA methods might be used in lieu ofcompositional specifications during manufacturing development only;b) reference dies be designed for “acceptance” and “qualification” castings;c) witness materials provide physical and mechanical property data;d) formal testing be conducted at ambient and cryogenic temperatures; ande) processing/properties be correlated with compositional variations.

Hales, Stephen J.↗

"Smart" Sensor Module

An assembly that contains a sensor, sensor-signal-conditioning circuitry, a sensor-readout analog-to-digital converter (ADC), data-storage circuitry, and a microprocessor that runs special-purpose software and communicates with one or more external computer(s) has been developed as a prototype of "smart" sensor modules for monitoring the integrity and functionality (the "health") of engineering systems. Although these modules are now being designed specifically for use on rocket-engine test stands, it is anticipated that they could also readily be designed to be incorporated into health-monitoring subsystems of such diverse engineering systems as spacecraft, aircraft, land vehicles, bridges, buildings, power plants, oilrigs, and defense installations. The figure is a simplified block diagram of the "smart" sensor module. The analog sensor readout signal is processed by the ADC, the digital output of which is fed to the microprocessor. By means of a standard RS-232 cable, the microprocessor is connected to a local personal computer (PC), from which software is downloaded into a randomaccess memory in the microprocessor. The local PC is also used to debug the software. Once the software is running, the local PC is disconnected and the module is controlled by, and all output data from the module are collected by, a remote PC via an Ethernet bus. Several smart sensor modules like this one could be connected to the same Ethernet bus and controlled by the single remote PC. The software running in the microprocessor includes driver programs for operation of the sensor, programs that implement self-assessment algorithms, programs that implement protocols for communication with the external computer( s), and programs that implement evolutionary methodologies to enable the module to improve its performance over time. The design of the module and of the health-monitoring system of which it is a part reflects the understanding that the main purpose of a health-monitoring system is to detect damage and, therefore, the health-monitoring system must be able to function effectively in the presence of damage and should be capable of distinguishing between damage to itself and damage to the system being monitored. A major benefit afforded by the self-assessment algorithms is that in the output of the module, the sensor data indicative of the health of the engineering system being monitored are coupled with a confidence factor that quantifies the degree of reliability of the data. Hence, the output includes information on the health of the sensor module itself in addition to information on the health of the engineering system being monitored.

Mahajan, Ajay↗

Elemental profiling and genomewide association studies reveal genomic variants modulating ionomic composition in Populus trichocarpa leaves

Samples were collected from a population of 1,089 black cottonwood genotypes (P. trichocarpa) assembled from native stands to encompass the central portion of the natural range of the species, stretching from 38.8° to 54.3° N Q13 latitude from California, USA, to British Columbia, Canada. Establishment of the common garden, growth conditions, and site maintenance have been described by Muchero et al (2015). In this study, leaf samples for ionomic profiling were collected from 4-year-old trees, during the growing season, in July 2012, from a field located in Clatskanie, Oregon, USA (46°6′11″N 123°12′13″W). The field site was located in a protected alluvial floodplain containing a uniform Wauna-Locoda silt loam soil area characterized by an acidic pH, in Columbia County, Oregon. A subset of 584 out of the 1,089 P. trichocarpa genotypes were represented in this sampling. These genotypes were randomly selected to represent the geographical distribution of the population. A single fully mature (LPI 7-9) leaf on the south side of the tree exposed to full sunlight conditions was removed from the tree within a 6-hour window centering on solar noon and immediately frozen under dry ice before processing. Leaf samples of 584 P. trichocarpa genotypes were finely ground to 40 mm particle size using a mortar and pestle, and ionomic composition was analyzed using ICP-MS. In total, 20 elements were profiled, including aluminum (Al27), arsenic (As75), boron (B11), cadmium (Cd111), calcium (Ca43), cobalt (Co), copper (Cu), iron (Fe57), magnesium (Mg25), manganese (Mn55), molybdenum (Mo), nickel (Ni60), phosphorus (P31), potassium (K39), rubidium (Rb85), selenium (Se82), sodium (Na23), strontium (Sr88), sulfur (S34), and zinc (Zn66), following a protocol established by Ziegler et al. (2013). For each sample, 75mg of powder was digested overnight in 2.5 mL HNO3 containing 20 parts per billion (ppb) indium as an internal standard, following the protocol described in Ziegler et al. (2013). Following a dilution, concentration of the 20 elements was measured using an Elan 6000 DRC-e mass spectrometer (Perkin-Elmer SCIEX) connected to a PFA microflow nebulizer (Elemental Scientific) and Apex HF desolvator (Elemental Scientific). One measurement per sample per genotype was done. For subsequent analyses, the quantifications were converted to total element concentration.

CBI ionomics, GWAS, plasma-mass spectrometry, neut↗

Enumeration and Fluorescence In Situ Hybridization of Microbial Bioburden on Cleanroom Surfaces

Introduction: Microorganisms are everywhere on Earth, even in the cleanest of places. Spacecraft assembly cleanrooms can harbor low levels of living and dead microbial cells (e.g., [1,2]), and cleanroom bioburden can also include organic molecules from industrial sources and in situ biomass. Life detection missions require careful attention to avoid contaminants that can be easily convoluted with analytical targets. We are evaluating epifluorescent microscopy and fluorescence in situ hybridization (FISH) as methods to complement organic contamination detection techniques. Epifluorescent cell counting offers an accurate and cost-effective way to quantify low levels of surface biomass. FISH could allow for the identification of residual organisms, and can be targeted to detect active populations of specific organisms such as bacteria known to resist cleaning procedures. This effort is part of a larger study that is concentrated on characterizing the surface and airborne molecular organic contamination background in Johnson Space Center (JSC) Astromaterials curation laboratories and Goddard Space Flight Center (GSFC) spacecraft assembly rooms, and understanding contaminants in the context of cleaning procedures and residual bioburden. Methods: Samples were collected by swabbing surfaces in ISO 5 and ISO 7 equivalent cleanrooms at JSC. Swabs for FISH were fixed in 4% paraformaldehyde (PFA) for 3 hours and then stored in 1:1 ethanol:PBS, while swabs for cell counting were stored in 4% PFA until analysis to avoid any cell loss during centrifugation that could impact quantification of very low biomass samples. Cell counting was performed with SYBR Gold as in [3], but adapted for very low biomass. FISH was performed as in [4], using DAPI as a counterstain for all DNA-containing cells. Negative controls included wells with no probe applied, to test for natural fluorescence, as well as the nonsense probe NONEUB (reverse complement of EUB338) to evaluate non-specific probe binding. Results and Discussion: Cleanroom surfaces had 102-103 cells cm-2. The extremely low biomass of these samples was challenging for enumeration, and required careful and routine use of “field” and laboratory blanks. FISH was performed with the general archaeal and bacterial probes ARCH915 and EUB338 (EUBMIX, [4]), probe GAMBET ([4]), and PSE227, which targets the genus Pseudomonas [5]). The latter two probes were selected because Pseudomonas spp. and other Gammaproteobacteria have not been isolated from cleanroom surfaces but do appear frequently in rRNA gene libraries from these surfaces. While some active bacteria were identified (Fig. 1c), most cells detectable by DAPI did not have a strong or any fluorescent signal (e.g., Fig. 1d), indicating that the vast majority of cells are dead or inactive. This suggests that cleaning protocols are effective at inactivating microbial contaminants, but that dead or inactive cells can remain on surfaces. Cells were often clumped in a weakly autofluorescent matrix, possibly biofilm material (Fig. 1c,d). We also observed other particulate material that was collected by the swabs, including apparent textile fibers (Fig. 1b). Our results are consistent with other studies that show that the bioburden present in clean rooms includes active, dormant, and dead cells. We will discuss how FISH and epifluorescent cell counting could be applied in planetary protection protocols, including the advantages and disadvantages of FISH and cell counting for routine use, as well as different possible applications for more specialized FISH procedures. References: [1] Moissl-Eichinger et al. (2015) Sci Rep, 5, 9156 [2] Hendrickson et al. (2021) Microbiome, 9, 238 [3] Jones et al. (2017) Appl Environ Microbiol, 83, e00909-17 [4] Jones et al. (2015) Appl Environ Microbiol, 81, 1242-1250. [5] Watt et al. (2006) Environ Microbiol, 8, 871-884

C J Huff↗

Molecular Technique to Reduce PCR Bias for Deeper Understanding of Microbial Diversity

Current planetary protection policies require that spacecraft targeted to sensitive solar system bodies be assembled and readied for launch in controlled cleanroom environments. A better understanding of the distribution and frequency at which high-risk contaminant microbes are encountered on spacecraft surfaces would significantly aid in assessing the threat of forward contamination. However, despite a growing understanding of the diverse microbial populations present in cleanrooms, less abundant microbial populations are probably not adequately taken into account due to technological limitations. This novel approach encompasses a wide spectrum of microbial species and will represent the true picture of spacecraft cleanroom-associated microbial diversity. All of the current microbial diversity assessment techniques are based on an initial PCR amplification step. However, a number of factors are known to bias PCR amplification and jeopardize the true representation of bacterial diversity. PCR amplification of a minor template appears to be suppressed by the amplification of a more abundant template. It is widely acknowledged among environmental molecular microbiologists that genetic biosignatures identified from an environment only represent the most dominant populations. The technological bottleneck overlooks the presence of the less abundant minority population and may underestimate their role in the ecosystem maintenance. DNA intercalating agents such as propidium monoazide (PMA) covalently bind with DNA molecules upon photolysis using visible light, and make it unavailable for DNA polymerase enzyme during polymerase chain reaction (PCR). Environmental DNA samples will be treated with suboptimum PMA concentration, enough to intercalate with 90 99% of the total DNA. The probability of PMA binding with DNA from abundant bacterial species will be much higher than binding with DNA from less abundant species. This will increase the relative DNA concentration of previously "shadowed" less abundant species available for PCR amplification. These PCR products obtained with and without PMA treatment will then be subjected to downstream diversity analyses such as sequencing and DNA microarray. It is expected that PMA-coupled PCR will amplify the "minority population" and help in understanding microbial diversity spectrum of an environmental sample at a much deeper level. This new protocol aims to overcome the major potential biases faced when analyzing microbial 16S rRNA gene diversity. This study will lead to a technological advancement and a commercial product that will aid microbial ecologists in understanding microbial diversity from various environmental niches. Implementation of this technique may lead to discoveries of novel microbes and their functions in sustenance of the ecosystem.

Vaishampayan, Parag A.↗