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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Methods to Evaluate Subcolumn Profiles Based on Two-Point Diagnostics

In atmospheric models, stochastic generation of subgrid-scale profiles or “subcolumns” has been used for a variety of purposes. Such subcolumns can be generated from subgrid probability density functions (PDFs) at different vertical levels, when such PDFs are available. To do so, the generator needs to decide how strongly points should be correlated in the vertical, that is, how much the values should be overlapped. This is sometimes called “PDF overlap.” To assess vertical correlation in a simplified, observable setting, here the vertical correlation of vertical velocity in subcloud layers is examined. Doppler lidar is used to evaluate the vertical profiles of vertical velocity produced by a large-eddy simulation (LES) model and the Subgrid Importance Latin Hypercube Sampler (SILHS) subcolumn generator. In order to diagnose unrealistic features in subcolumn profiles, various statistical diagnostics are examined here, including the bivariate PDF of vertical velocity at two separated points (i.e., altitudes), the two-point velocity correlation, the integral correlation length, the PDF of two-point velocity differences, and the skewness and kurtosis of two-point velocity differences. The profiles produced by LES match lidar well, except that they are too smooth at small scales. The profiles produced by SILHS exhibit sharp jumps from updraft to downdraft that are not observed in the lidar data. To reduce the generation of these unrealistically sharp jumps, the SILHS sampling method is revised. The diagnostics confirm that the revised sampling method reduces the overprediction of sharp jumps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

In engineering and aerospace applications, it is vital to operational success to have insight into the expected performance and health of physical systems. The field of prognostics and health management provides quantitative methods for monitoring, predicting, and managing system health. Prognostics algorithms can be employed to assess the current state of a system, propagate the system throughout time, and predict potential anomalies or failures that may occur. While they can provide accurate prediction results, effective prognostics algorithms can be challenging to use in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for future remaining useful life predictions. In this work, we implement new algorithmic approaches for prediction, quantitatively compare them via a battery degradation use-case, and provide recommendations of potential improvements to a prognostics framework. One approach to prediction is through sampling, whereby the current state of a physical system is sampled many times and each sample is propagated forward until failure is reached, resulting in a distribution of failure values. To improve the efficiency of this process, we implemented five new algorithmic approaches to prediction, including three distinct sampling methods (standard Monte Carlo, Quasi-Monte Carlo, and Latin Hypercube Sampling), a variable time step algorithm, and a variable sample size algorithm. To compare the algorithms, we employ a variety of metrics designed specifically to analyze both computational efficiency and model accuracy. Our metrics include accuracy to compare the average predicted value to ground truth, mean absolute deviation to illustrate dispersion, specific percentile error to describe accuracy within a user-defined risk tolerance, and code run-time. To quantitatively analyze our results, we employ a use-case of degradation of a Lithium-ion battery. We use an electrochemistry-based model to describe the current health state of the battery, and implement our prediction algorithms to propagate forward in time until end-of-discharge (EOD) is reached. Notably, through this work it was found that none of our sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. We find that while the sampling methods are unique, the distributions they generate are similar, ultimately producing final predictions that are nearly identical. In exploring the effect of the time step within the prediction algorithm, we found that prediction accuracy was highly dependent on the time step used, and that implementing a variable time step within a particular prediction may provide an increase in computational efficiency while also maintaining prediction accuracy. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment can result in improved computation speed and maintained prediction accuracy. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency.

prognostics↗
NASA NTRS1974

Evaluation of membrane filter field monitors for microbiological air sampling

Due to area constraints encountered in assembly and testing areas of spacecraft, the membrane filter field monitor (MF) and the National Aeronautics and Space Administration-accepted Reyniers slit air sampler were compared for recovery of airborne microbial contamination. The intramural air in a microbiological laboratory area and a clean room environment used for the assembly and testing of the Apollo spacecraft was studied. A significantly higher number of microorganisms was recovered by the Reyniers sampler. A high degree of consistency between the two sampling methods was shown by a regression analysis, with a correlation coefficient of 0.93. The MF samplers detected 79% of the concentration measured by the Reyniers slit samplers. The types of microorganisms identified from both sampling methods were similar.

Fields, N. D.↗
DOE OSTI2024

Behavioral Ensemble CLM5 Hydrological Parameter Sets

This repository contains hydrological parameter sets derived using the hybrid regionalization method for three distinct streamflow signatures: Streamflow Signatures: Q10: Represents low flow, indicating the nonexceedance probability of 0.1 for daily streamflow. Q90: Represents high flow, with a nonexceedance probability of 0.9 for daily streamflow. Qmean: Indicates the mean annual flow. Parameters for 464 CAMELS Basins: CAMELS_1000_parameters.csv: Contains 1,000 ensemble parameter sets generated using the Latin hypercube sampling method for CLM5, encompassing 15 hydrological parameters. CAMELS_q10_behavioral_parameter_num.csv: Provides the behavioral ensemble parameter sets for the Q10 streamflow signature for each basin. The associated ID number refers to entries in the CAMELS_1000_parameters.csv file. A minimum of 10 ensemble parameter sets are available for each basin. CAMELS_q90_behavioral_parameter_num.csv: Similar to the above file but for the Q90 streamflow signature. CAMELS_qmean_behavioral_parameter_num.csv: Corresponds to the Qmean streamflow signature, similar to the previous files. Parameters for 50,629 1/8° CONUS Land Grid Cells: CONUS_350_parameters.csv: Contains 350 ensemble parameter sets derived using the Latin hypercube sampling method for CLM5's 15 hydrological parameters within 1/8° CONUS land grid cells. CONUS_q10_behavioral_parameter_num.csv: Holds the behavioral ensemble parameter sets for the Q10 streamflow signature, organized for each grid cell. The ID number relates to entries in CONUS_350_parameters.csv. A minimum of 10 ensemble parameter sets are provided for each grid cell. CONUS_q90_behavioral_parameter_num.csv: Similar to the above file but focusing on the Q90 streamflow signature. CONUS_qmean_behavioral_parameter_num.csv: Corresponds to the Qmean streamflow signature, following a similar structure to the previous files.

Yan, Hongxiang↗
DOE OSTI2024

Point-of-use filtration units as drinking water distribution system sentinels

Abstract Municipal drinking water distribution systems (DWDSs) and associated premise plumbing (PP) systems are vulnerable to proliferation of opportunistic pathogens, even when chemical disinfection residuals are present, thus presenting a public health risk. Monitoring the structure of microbial communities of drinking water is challenging because of limited continuous access to faucets, pipes, and storage tanks. We propose a scalable household sampling method, which uses spent activated carbon and reverse osmosis (RO) membrane point-of-use (POU) filters to evaluate mid- to long-term occurrence of microorganisms in PP systems that are relevant to consumer exposure. As a proof of concept, POU filter microbiomes were collected from four different locations and analyzed with 16S rRNA gene amplicon sequencing. The analyses revealed distinct microbial communities, with occasional detection of potential pathogens. The findings highlight the importance of local, and if possible, continuous monitoring within and across distribution systems. The continuous operation of POU filters offers an advantage in capturing species that may be missed by instantaneous sampling methods. We suggest that water utilities, public institutions, and regulatory agencies take advantage of end-of-life POU filters for microbial monitoring. This approach can be easily implemented to ensure drinking water safety, especially from microbes of emerging concerns; e.g., pathogenic Legionella and Mycobacterium species.

42 ENGINEERING↗
DOE OSTI2025

Round Robin Analysis of Uranium Isotopics on Cotton Swipes Measured Using Microextraction-Based Sampling Versus Conventional Bulk Analysis

A comparison of microextraction sampling methods to directly analyze uranium isotopics on cotton swipes was performed concurrently with traditional bulk-processing methods. For the microextraction sampling approach, two different detection platforms were evaluated, a quadrupole-based inductively coupled plasma mass spectrometer (ICP-MS) and the liquid sampling-atmospheric pressure glow discharge (LS-APGD) coupled to an Orbitrap mass spectrometer. Results presented from this innovative sampling approach (i.e., microextraction) are compared with a more traditional approach employed for analysis of cotton-based environmental swipes, namely bulk ashing/digestion, separation, and subsequent analysis by high-precision multi-collector ICP-MS. Overall, the microextraction approach proved to be a reliable and accurate means to determine isotopic ratios of uranium collected on cotton swipes. The ICP-MS-based detection had relative standard deviations of <0.65% for the major isotopic determinations, whereas the LS-APGD-Orbitrap method had relative standard deviations of <3%. The percent relative difference for the 235 U/ 238 U ratios, in comparison to the expected values, was <1% for ICP-MS and <4% for the microplasma-Orbitrap method. Additionally, the microextraction ICP-MS accurately (<2%) and precisely (<5%) determined the minor isotopic compositions (i.e., 234 U/ 238 U and 236 U/ 238 U).

ICP-MS↗
NASA NTRS2006

Multifrequency Ultra-High Resolution Miniature Scanning Microscope Using Microchannel And Solid-State Sensor Technologies And Method For Scanning Samples

A miniature, ultra-high resolution, and color scanning microscope using microchannel and solid-state technology that does not require focus adjustment. One embodiment includes a source of collimated radiant energy for illuminating a sample, a plurality of narrow angle filters comprising a microchannel structure to permit the passage of only unscattered radiant energy through the microchannels with some portion of the radiant energy entering the microchannels from the sample, a solid-state sensor array attached to the microchannel structure, the microchannels being aligned with an element of the solid-state sensor array, that portion of the radiant energy entering the microchannels parallel to the microchannel walls travels to the sensor element generating an electrical signal from which an image is reconstructed by an external device, and a moving element for movement of the microchannel structure relative to the sample. Discloses a method for scanning samples whereby the sensor array elements trace parallel paths that are arbitrarily close to the parallel paths traced by other elements of the array.

Wang, Yu↗
NASA NTRS2006

Cultural Challenges Faced by American Mission Control Personnel Working with International Partners

Operating the International Space Station (ISS) involves an indefinite, continuous series of long-duration international missions, and this requires an unprecedented degree of cooperation across multiple sites, organizations, and nations. Both junior and senior mission control personnel have had to find ways to address the cultural challenges inherent in such work, but neither have had systematic training in how to do so. The goals of this study were to identify and evaluate the major cultural challenges faced by ISS mission control personnel and to highlight the approaches that they have found most effective to surmount these challenges. We pay particular attention to the approaches successfully employed by the senior personnel and the training needs identified by the junior personnel. We also evaluate the extent to which the identified approaches and needs are consistent across the two samples. METHODS: Participants included a sample of 14 senior ISS flight controllers and a contrasting sample of 12 more junior controllers. All participants were mission operations specialists chosen on the basis of having worked extensively with international partners. Data were collected using a semi-structured qualitative interview and content analyzed using an iterative process with multiple coders and consensus meetings to resolve discrepancies. RESULTS: The senior respondents had substantial consensus on several cultural challenges and on key strategies for dealing with them, and they offered a wide range of specific tactics for implementing these strategies. Data from the junior respondents will be presented for the first time at the meeting. DISCUSSION: Although specific to American ISS personnel, our results are consistent with recent management, cultural, and aerospace research on other populations. We aim to use our results to improve training for current and future mission control personnel working in international or multicultural mission operations teams.

Clement, J. L.↗
NASA NTRS2008

An Organic Decontamination Method for Sampling Devices used in Life-detection Studies

Organic decontamination of sampling and storage devices are crucial steps for life-detection, habitability, and ecological investigations of extremophiles living in the most inhospitable niches of Earth, Mars and elsewhere. However, one of the main stumbling blocks for Mars-analogue life-detection studies in terrestrial remote field-sites is the capability to clean instruments and sampling devices to organic levels consistent with null values. Here we present a new seven-step, multi-reagent cleaning and decontamination protocol that was adapted and tested on a glacial ice-coring device and on a rover-guided scoop used for sediment sampling both deployed multiple times during two field seasons of the Arctic Mars Analog Svalbard Expedition AMASE). The effectiveness of the protocols for both devices was tested by (1)in situ metabolic measurements via APT, (2)in situ lipopolysacchride (LPS) quantifications via low-level endotoxin assays, and(3) laboratory-based molecular detection via gas chromatography-mass spectrometry. Our results show that the combination and step-wise application of disinfectants with oxidative and solvation properties for sterilization are effective at removing cellular remnants and other organic traces to levels necessary for molecular organic- and life-detection studies. The validation of this seven-step protocol - specifically for ice sampling - allows us to proceed with confidence in kmskia4 analogue investigations of icy environments. However, results from a rover scoop test showed that this protocol is also suitable for null-level decontamination of sample acquisition devices. Thus, this protocol may be applicable to a variety of sampling devices and analytical instrumentation used for future astrobiology missions to Enceladus, and Europa, as well as for sample-return missions.

Eigenbrode, Jennifer↗
NASA NTRS2022

Wilson Corners Solid Waste Management Unit (SWMU) 001: 2021 Annual Long-Term Monitoring Report, Kennedy Space Center, Florida

This report presents a summary of the long-term monitoring (LTM) activities that occurred in 2021 at Wilson Corners, Solid Waste Management Unit (SWMU) 001, at Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action Program. Adaptive site management is being utilized through ongoing assessment, design, and interim measures (IM). Annual LTM of the groundwater is also being conducted at the site. This approach also meets the requirements of Chapter 62-780, Florida Administrative Code (F.A.C.). The goal of LTM at this site is threefold: to determine groundwater flow characteristics, monitor the downgradient concentration trends, and monitor select locations internal to the groundwater plume. Every 5 years, upgradient and side-gradient monitoring wells are sampled to verify delineation. The last time this was performed was in 2015. The sampling of these wells in 2020 was replaced with the direct push technology (DPT) investigations completed in October 2020 and April 2021. This DPT groundwater data was presented in an Advance Data Package (ADP) in September 2021 and discussed in the Implementation Work Plan (IWP) dated November 2021 for installation of an air sparge (AS) system. Based on results from groundwater sampling activities performed during the previous reporting period, including the 2020 and 2021 DPT groundwater sampling, it was determined that the LTM sampling plan was no longer meeting the goal of LTM because delineation was not verified. The 2021 LTM sampling plan was modified to include the sampling of monitoring wells located around the perimeter of the low concentration plume (LCP); the area with concentrations of contaminants of concern [COCs] greater than Groundwater Cleanup Target Levels [GCTLs]), and sampling of 10 monitoring wells proposed for installation (April 2021 KSC Remediation Team (KSCRT) Meeting, Decision 2104-D32). The modified LTM plan received team consensus at the September 2021 KSCRT Meeting (Decision Number 2109-D03), and sampling of the existing monitoring wells was completed in December 2021. The proposed monitoring wells are planned for installation in late 2022, concurrent with ongoing IM construction activities. December 2021 LTM data was presented at the May 2022 KSCRT Meeting, and activities are summarized in this report. The activities presented in this report include the December 2021 groundwater gauging of 42 monitoring wells and sampling of 44 monitoring wells. During the December 2021 event, the low flow sampling method was used, and samples were analyzed for a select list of volatile organic compounds (VOCs), including 1,1,2-trichloro-1,2,2-trifluoroethane (Freon 113). The following conclusions can be made based on the 2021 LTM results: - In December 2021, groundwater flow for the site was generally to the west at all intervals. This is generally consistent with historical observations at the site, with the exception of a southwest and southeast flow component observed at 34 to 48 feet below land surface (bls). - The vertical extent of VOCs was historically delineated by monitoring wells screened greater than 48 feet bls. The results from the two vertical extent monitoring wells, WILC-MW0078 (screened 65 to 70 feet bls) and WILC-MW0130 (screened 56 to 66 feet bls) that were sampled during the 2021 LTM indicate that groundwater vinyl chloride (VC) concentrations in both wells were greater than the GCTL. The Remediation Team has previously agreed to delay deeper DPT investigations in this area to prevent the creation of additional pathways for vertical migration. - The LCP continues to extend both horizontally, predominantly to the west, and vertically beyond the current monitoring well network, with some retraction observed to the southeast. Evaluation of this data combined with data from the 2020 and 2021 DPT sampling event indicate that the LCP encompasses an estimated 20.7 acres based on an expanded sampling area, as compared to the 2020 LCP footprint of 17.0 acres. - Freon 113 was not detected above GCTLs during the 2021 LTM event. Based on groundwater sampling activities performed in 2021, including April 2021 DPT groundwater sampling, the following recommendations are provided: - Perform the next LTM sampling event, targeted to occur in 2023, concurrently with the IM baseline sampling prior to AS system installation; - Include sampling from nine monitoring wells that are planned to be installed in late 2022, concurrent with upcoming IM construction activities. Installation of one deep vertical well, screened 70 to 80 feet bls, will be delayed to prevent the creation of an additional pathway for vertical migration; - Continue to sample under the modified annual LTM plan as presented in Table 4-1 concurrently with IM baseline sampling; and - Once the AS system install and start-up is complete, select monitoring wells from the LTM program will transition into the performance monitoring plan, and LTM will be temporarily discontinued. Performance monitoring will be performed quarterly, and the monitoring well network will be evaluated following the first performance monitoring sampling event.

long-term monitoring (LTM)↗
NASA NTRS2024

Wilson Corners, Solid Waste Management Unit 001(SWMU 01) 2023 Annual Long-Term Monitoring Report

This report presents a summary of the long-term monitoring (LTM) activities that occurred in 2023 at Wilson Corners, Solid Waste Management Unit 001, at Kennedy Space Center (KSC), Florida. Annual LTM of groundwater is being conducted at the site. Based on results from groundwater sampling activities performed during the 2019 through 2020 LTM reporting period and the 2020 and 2021 DPT groundwater sampling, it was determined that the LTM sampling plan was no longer meeting the goal of LTM because delineation was not verified and the installation of an air sparge (AS) system to treat the area of the High Concentration Plume was recommended. The AS System was installed in late 2022 and early 2023. System start-up activities were initiated in April 2023. Following system startup, several site wells required retrofitting to equip wellheads for withstanding the air pressure released from air sparge wells during system operation. Some site wells also required repair or abandonment, and replacement. Survey of location and top-of-casing of newly installed monitoring wells was combined with scheduled AS system survey activities and was completed in January 2024. The activities presented in this report include the February and April 2023 LTM monitoring well installations; March and April 2023 LTM and performance monitoring well water level gauging and sampling; November 2023 LTM well retrofits and repairs; a summary of December 2023 LTM well abandonments and installations (complete site well abandonment activities will be presented under a separate cover); and January 2024 LTM well survey. During the March and April 2023 sampling events, the low-flow sampling method was used, and samples were analyzed for a select list of volatile organic compounds. In March 2023, groundwater flow for the site was generally to the west was generally consistent with historical observations at the site. The Low Concentration Plume (LCP) continues to extend both horizontally and vertically beyond the terminal depth of the current monitoring well network. Data, inclusive of the 2023 LTM and baseline performance monitoring sampling events, indicate that the LCP encompasses an estimated 19.5 acres, compared to the 2021 LCP footprint, inclusive of the 2020 and 2021 DPT sampling events of 20.7 acres. The vertical extent of VOCs was historically delineated by monitoring wells screened greater than 48 feet below land surface (bls). The results from the three vertical extent monitoring wells screened below 48 feet bls that were sampled during the 2023 LTM indicate that groundwater vinyl chloride concentrations in these three wells are greater than the GCTL. As presented in the 2021 Long-Term Monitoring Report (NASA 2022), the KSCRT agreed to delay deeper investigations in this area to prevent the creation of additional pathways for vertical migration. Based on groundwater sampling activities performed in 2023, recommendations are to perform the next annual LTM sampling event, scheduled for April 2024 and to conduct quarterly performance monitoring of the AS System. The current selection of monitoring wells in the recommended 2024 LTM plan will provide an adequate data set for monitoring groundwater plume behavior; however, the LTM monitoring well network will be evaluated and refined based on 2024 LTM and year one performance monitoring data.

King Linnea↗
DOE OSTI2024

Apparatus and methods for sample analysis with multi-gradient microfluidics

A device for analyzing biological samples comprises first, second, third, and fourth layers. The first layer comprises a sample chamber in which a sample is positioned. The second layer comprises first, second, and third channels. A third, porous layer is positioned between the first layer and the second layer. A fourth layer composed of a substantially liquid-impermeable material is positioned between the second layer and the third layer. The fourth layer includes first and second pass-through channels that are aligned with the first and second channel, respectively. Fluids that flow in the first and second channels pass through the pass-through channels and diffuse into the sample chamber, establishing a chemical concentration gradient therein. A gas in the sample chamber can diffuse through the third and fourth layers and interact with a fluid flowing in the third channel, establishing a gas concentration gradient in the sample chamber.

Kim, Peter Wonhee↗
NASA NTRS1971

Rock sampling

A method for sampling rock and other brittle materials and for controlling resultant particle sizes is described. The method involves cutting grooves in the rock surface to provide a grouping of parallel ridges and subsequently machining the ridges to provide a powder specimen. The machining step may comprise milling, drilling, lathe cutting or the like; but a planing step is advantageous. Control of the particle size distribution is effected primarily by changing the height and width of these ridges. This control exceeds that obtainable by conventional grinding.

Blum, P.↗
NASA NTRS2019

Cleanroom Contamination Identification Method Development

During fabrication, assembly, and testing of spacecraft and flight hardware it is vital to avoid contaminants that can cause degradation and could result in significant failure. Yet, there is no existing contamination monitoring method that provides the identity of airborne particles in a cleanroom facility. Knowing the particle identities, would allow scientists and engineers to determine the source of the contaminants and prevent setbacks before they occur or cause damage. Current cleanliness monitoring methods include airborne particle counters (APCs), fallout filters, and visual inspections. Particle counts from APCs are the primary metric used to define a cleanroom class and hence its level of cleanliness, but do not provide identification nor can they differentiate between large and small sizes of particles. In addition, using fallout filters is not a proactive, timely, or representative approach to cleanroom contamination monitoring because these samples are only retrieved after 30 days and are placed away from spacecraft processing to avoid interference with operations. In contrast, the forced air sampling method can collect a sample within an hour at any location required and provide results in less than a day. This system uses a cassette and filter sample medium to capture airborne particles which are then taken to a scanning electron microscope with energy dispersive spectroscopy (SEM/EDS) to identify and size the captured particles. Development of forced air sampling into an established laboratory capability will allow for fast sampling and routine identification of unknown contamination sources within the cleanroom. The test method development required market research for an air sampling cassette that increases sample collection efficiency and a filter with low enough background contamination to allow differentiation between a blank (control) and the collected sample. It was determined that a conductive black cassette and a polycarbonate filter were the best options. Conductive black cassettes, in comparison to the standard styrene, are manufactured using polypropylene filled with carbon. This makes the cassette conductive and minimizes the tendency of particles to stick to the wall of the cassette due to electrostatic force. In previous trials a mixed cellulose ester (MCE) filter was used to capture the contaminants, however the rougher surface of the filter contributed to entrapment of the particles within the filter structure and made it harder to identify the particles. In comparison, track etched polycarbonate filters have random cylindrical pores and a smooth surface which contributes to uniform sample distribution on the surface of the filter. Future work includes: testing the system using control samples to determine the efficiency and suitability of the medium, performing sample collection in various environments to establish ideal operating parameters and analyzing contaminant particles using SEM/EDS and assistant characterization techniques. Once fully developed, employing the forced air sampling method will help to prevent damage to spacecraft, avoid schedule delays, and allow for mission success.

Hernandez Melendez, Jailyn M.↗
NASA NTRS1986

Convenient mounting method for electrical measurements of thin samples

A method for mounting thin samples for electrical measurements is described. The technique is based on a vacuum chuck concept in which the vacuum chuck simultaneously holds the sample and established electrical contact. The mounting plate is composed of a glass-ceramic insulating material and the surfaces of the plate and vacuum chuck are polished. The operation of the vacuum chuck is examined. The contacts on the sample and mounting plate, which are sputter-deposited through metal masks, are analyzed. The mounting method was utilized for van der Pauw measurements.

Matus, L. G.↗