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Continued search for organics on Mars will require the development of simplified procedures for handling and processing of soil or rock core samples prior to analysis by onboard instrumentation.
Radiation Assessment DuRing Exposure And long-Duration Spaceflight (RADREADS) demonstrates space-compatible point-of-care technology for quantitative biological monitoring of blood miRNA biomarkers in response to long-term low dose radiation exposure. This individualized monitoring approach will inform targeted treatment strategies to maximize medical resource utilization by accounting for individual susceptibility to radiation-related illnesses. As human spaceflight progresses beyond Earth’s magnetic shielding, radiation exposure poses a significant risk to astronaut health and safety. Extended operation in this environment comes with an increased risk of radiation exposure, leading to higher risks of radiation sickness, cancer, central nervous system effects, and degenerative diseases. While conventional physical dosimetry techniques capture radiation dose, individualistic susceptibility to radiation damage is varied. Multiple characteristics, including age, body weight, sex, genetics, and immune status, have been found to influence radiosensitivity (Liu et al. 2011, and Bouffler 2016). This differential response necessitates individualized monitoring and targeted treatment strategies to maximize medical resource utilization; however, a practical diagnostic platform for quantifying long-term, low dose radiation-induced tissue damage does not currently exist. MicroRNAs (miRNAs) are a class of small, non-coding RNAs that regulate gene expression by mediating the degradation of messenger RNA. The levels of particular miRNAs are influenced by biological processes such as inflammation and serve as biomarkers for a variety of conditions including cancer (Singh et al. 2017). MicroRNAs are found in various bodily fluids and are amenable to collection via liquid biopsies, providing a minimally invasive and easily quantifiable readout for a variety of radiosensitive reporters. A preliminary signature of 15 spaceflight sensitive miRNA has been identified in rodent and human studies, including miR-21-5p, miR-24-3p, miR-92a-3p, miR-17-5p, miR-16a-3p, miR-34a-3p, and miR-223-3p. These targets generally increased expression with radiation dose and linear energy transfer, though variation between individuals is not yet described. Current gaps in the field include a lack of understanding of longitudinal biological responses to long-term, low dose radiation exposure and the absence of space-compatible point-of-care technology for quantitative biological monitoring. In this body of work, we aim to develop an automated bleed-to-read system to process whole blood for the detection of miRNA biomarkers in order to monitor individualistic responses to radiation exposure. This will be achieved via separating serum (or plasma) from whole blood, followed by extraction, amplification, and quantification of the miRNA using a RT-qPCR reaction. Previously, the WetLab-2 hardware enabled execution of a RT-qPCR reaction aboard ISS; however, it is a manual system that requires crew manipulation and bulky components (Parra et al. 2017). To address these issues, automated fluid handling hardware was developed for each stage of sample preparation. Extraction of total RNA is achieved by sequentially pumping reagents through an off-the-shelf nucleic acid binding column (miRNeasy Serum/Plasma Advanced Kit, Qiagen). This approach eliminates several manual pipetting and centrifuging steps and limits the use of toxic chemicals commonly found in other sample processing techniques. The resulting elution will then be automatically dispensed for RT-qPCR analysis using a compact rotary qPCR (Mic qPCR Cycler, Bio Molecular Systems) that will improve spaceflight compatibility by removing bubbles from the detection region, another challenge highlighted by WetLab-2 (Parra et al. 2017). Efforts are also being made to simplify the RT-qPCR reaction to a 1-step air-dryable mix to improve long-term reagent stability at room temperature and reduce system complexity. By automating the RT-qPCR processes via microfluidic manipulation, RADREADS will reduce crewmember hands-on time and enable the personalized detection of radiation-induced tissue damage during long duration missions. Minimally invasive, longitudinal monitoring of individual’s response to radiation exposure will inform how the physiological system responds to long-term low dose space radiation and enables development of targeted countermeasures by the medical team. Ultimately, this portable technology will require minimal technical expertise and can also be used to monitor miRNA biomarkers associated with other diseases.
The Center for Isotope Cosmochemistry and Geochronology (CICG) at the NASA Johnson Space Center, led by Justin Simon, applies novel elemental and isotopic analytical techniques to understand solar system formation, from processes occurring during the earliest Solar Nebula, to the evolution of planetary bodies during planet formation and differentiation. CICG consists of an integrated suite of labs including dedicated spaces for specialized handling and preparation of meteorites and planetary return samples, metal-free clean chemistry, and mass spectrometry. In addition to a Thermo-Scientific Triton thermal ionization mass spectrometer (TIMS) for high precision isotopic analyses in processed samples, CICG houses two additional mass spectrometry instruments with added laser ablation capabilities for high spatial resolution in-situ measurements: (1) a Thermo-Scientific Element-XR inductively coupled mass spectrometer (ICP-MS) with a Teledyne Photon Machines Analyte Excite+ laser ablation system, and (2) a Nu Sapphire 1700 multi-collector ICP-MS, a large geometry instrument with a multi-pole collision cell for interference removal, with an Applied Spectra J200 tandem laser induced breakdown spectroscopy (LIBS) femto-second laser ablation system. We detail the analytical capabilities of CICG in the context of current and future research projects related to the studies of protoplanetary disk evolution via early-formed Solar System solids, volatile abundances and distribution within the inner solar system, and geochemical and temporal investigations related to planet formation and differentiation. We also highlight opportunities through the relationship with the Center of the Advancement of Space Safety and Mission Assurance Research (CASSMAR) at the University of Texas at El Paso. CICG is open to collaborations and participates in the NASA Facility for Astromaterials Research (NFAR) program, which accepts research proposals for access to the unique facility capabilities.
Light stable isotope work requires the handling of gasses such a way that does not alter isotopic composition. To do this, there are a large number of analytical and experimental procedures which involve the use of a vacuum line, numerous “egg timers” and a human hand on a valve. Unfortunately, the human hand is inconsistent and inadvertent small, and commonly large, differences in timing can have a measurable effect on outcomes. We have constructed a computer controlled high-vacuum line to be used as an expandable platform for future experimental and analytical procedures. The vacuum line consists of an electropolished 316 stainless steel system of cryogenic u-traps partitioned by pneumatic valves. The code to operate the line has been developed using the LabView platform and will allow for automated timing, consistent valve opening speed and unattended operation of long analytical procedures. The aim of this project is to address a need in the light stable isotope laboratory for a general-purpose vacuum line for handling and manipulation of gasses. When combined with existing instrumentation it allows for a significant expansion of current analytical capabilities. The system allows for better handling of standards, gas conversion techniques and gas sample collection for interlaboratory comparisons. The basic structure of the line, automation hardware and software were chosen and designed to provide a base for future expansion of the system to incorporate new automated analytical techniques as laboratory instrumentation and analytical needs expand.
The overview of this presentation is: (1) Introduction to nonproliferation efforts; (2) Scope of activities at Los Alamos National Laboratory; (3) Facilities for radioanalytical work at LANL; (4) Radiochemical characterization capabilities; and (5) Bulk chemical and materials analysis capabilities. Some conclusions are: (1) Analytical chemistry measurements on plutonium and uranium matrices are critical to numerous defense and non-defense programs including safeguards accountancy verification measurements; (2) Los Alamos National Laboratory operates capable actinide analytical chemistry and material science laboratories suitable for nuclear material forensic characterization; (3) Actinide analytical chemistry uses numerous means to validate and independently verify that measurement data quality objectives are met; and (4) Numerous LANL nuclear facilities support the nuclear material handling, preparation, and analysis capabilities necessary to evaluate samples containing nearly any mass of an actinide (attogram to kilogram levels).
Many engineering problems require the prediction of realization-to-realization variability or a refined description of modeled quantities. In that case, it is necessary to sample elements from unknown high-dimensional spaces with possibly millions of degrees of freedom. While there exist methods able to sample elements from probability density functions (PDF) with known shapes, several approximations need to be made when the distribution is unknown. In this paper the sampling method, as well as the inference of the underlying distribution, are both handled with a data-driven method known as generative adversarial networks (GAN), which trains two competing neural networks to produce a network that can effectively generate samples from the training set distribution. In practice, it is often necessary to draw samples from conditional distributions. When the conditional variables are continuous, only one (if any) data point corresponding to a particular value of a conditioning variable may be available, which is not sufficient to estimate the conditional distribution. This work handles this problem using an a priori estimation of the conditional moments of a PDF. Herein, two approaches, stochastic estimation, and an external neural network are compared for computing these moments; however, any preferred method can be used. The algorithm is demonstrated in the case of the deconvolution of a filtered turbulent flow field. It is shown that all the versions of the proposed algorithm effectively sample the target conditional distribution with minimal impact on the quality of the samples compared to state-of-the-art methods. Additionally, the procedure can be used as a metric for the diversity of samples generated by a conditional GAN (cGAN) conditioned with continuous variables.
A Hydrazine Vapor Area Monitor (HVAM) system is currently being field tested as a detector for the presence of hydrazine in ambient air. The MDA/Polymetron Hydrazine Analyzer has been incorporated within the HVAM system as the core detector. This analyzer is a three-electrode liquid analyzer typically used in boiler feed water applications. The HVAM system incorporates a dual-phase sample collection/transport method which simultaneously pulls ambient air samples containing hydrazine and a very dilute sulfuric acid solution (0.0001 M) down a length of 1/4 inch outside diameter (OD) tubing from a remote site to the analyzer. The hydrazine-laden dilute acid stream is separated from the air and the pH is adjusted by addition of a dilute caustic solution to a pH greater than 10.2 prior to analysis. Both the dilute acid and caustic used by the HVAM are continuously generated during system operation on an "as needed" basis by mixing a metered amount of concentrated acid/base with dilution water. All of the waste water generated by the analyzer is purified for reuse by Barnstead ion-exchange cartridges so that the entire system minimizes the generation of waste materials. The pumping of all liquid streams and mixing of the caustic solution and dilution water with the incoming sample are done by a single pump motor fitted with the appropriate mix of peristaltic pump heads. The signal to noise (S/N) ratio of the analyzer has been enhanced by adding a stirrer in the MDA liquid cell to provide mixing normally generated by the high liquid flow rate designed by the manufacturer. An onboard microprocessor continuously monitors liquid levels, sample vacuum, and liquid leak sensors, as well as handles communications and other system functions (such as shut down should system malfunctions or errors occur). The overall system response of the HVAM can be automatically checked at regular intervals by measuring the analyzer response to a metered amount of calibration standard injected into the dilute acid stream. The HVAM system provides two measurement ranges (threshold limit value (TLV): 10 to 1000 parts per billion (ppb)/LEAK: 100 ppb to 10 parts per million (ppm)). The LEAK range is created by dilution of the sulfuric acid/hydrazine liquid sample with pure water. This dual range capability permits the analyzer to quantify ambient air samples whose hydrazine concentrations range from 10 ppb to as high as 10 ppm. The laboratory and field prototypes have demonstrated total system response times on the order of 10 to 12 minutes for samples ranging from 10 to 900 ppb in the lLV mode and is greater than 2 minutes for samples ranging from 100 to 1300 ppb in the LEAK mode. Service intervals of over 3 months have been demonstrated for continuous 24 hour/day, 7 day/week usage. The HVAM is made up of a purged cabinet that contains power supplies, RS422 signal transmission capabilities, a UPS, an on-site warning system, and a Line Replaceable Unit (LRU). The LRU includes all of the liquid flow system, the analyzer, the control/data system microprocessor and assorted flow and liquid-level sensors. The LRU is mounted on a track slide system so it can be serviced inplace or totally removed and quickly exchanged with another calibrated unit, thus minimizing analyzer downtime. Once an LRU is removed from an analyzer enclosure, it can be brought to a laboratory facility for complete calibration and periodic maintenance.
Safe and efficient cleanups are a priority for decontamination and decommissioning of nuclear facilities. The contaminations of byproducts and wastes in such nuclear facilities pose a serious problems while decommissioning, to both the operators and public. Sensing these contaminations and cleaning them is an essential part of the safety procedures. The contaminations might range from low-energy to high-energy byproducts. Sensing these byproducts would require contact based or non-contact based sensing, based on its energy levels. Byproducts such as americium, are low-energy which makes it difficult to sense and sample without contact. Therefore, the workers need to physically swab the surfaces to collect the samples of these contaminations. These tasks pose a great danger for the safety of the human workers which includes the risk to reach greater heights, exposure to the radiation and sampling the entire building. A robotic solution is much more desirable in these cases, where the worker can safely handle the contaminations from a safe area. Use of robotic technologies inside these hazardous environments ensures the safety and enhances the performance. The more suitable robotic solution for reaching great heights and covering large areas of nuclear facilities, are aerial vehicles. Multi-rotor unmanned aerial vehicle (UAV) are chosen for their ability to hover at a position and also fly around in confined spaces. Quadrotors are a common choice of multi-rotor UAVs both research and industry because of its ease to fly and commercial availability. For the applications during the cleanups we need the UAV to not only hover and fly in confined spaces, but also interact with the physical world. Despite of quadrotor's advantages, they are not a best suit as they can't interact with the physical world. The tasks involving physical interactions would require the UAV to apply arbitrary forces and torques in all six degrees of freedom (DOF). As quadrotors are under-actuated and non-holonomic in motion, they cannot exert all the required forces. At Collaborative Robotics Lab, Purdue University, we developed a novel multi-rotor UAV solution, Dexterous Hexrotor, which can exert arbitrary forces and torques in all six DOF, independently and instantaneously. This enables the UAV platform to quickly respond to the external disturbances and precisely hold its position during the mission. The Dexterous Hexrotor serves as a robotic tool for the workers to perform sensing and sampling during the cleanups. Workers can operate Dexterous Hexrotor manually and/or semi-autonomously with human intervention. Manual control requires the worker to fly the Dexterous Hexrotor using a remote control. So the workers should possess knowledge on flying the UAV and to perform physical interaction. A semiautonomous Dexterous Hexrotor requires human input to some extent and requires very less knowledge of flying. The autonomy is designed to operate in flight mode and sampling mode. In flight mode, Dexterous Hexrotor takes off from a 'safe' area, reaches the desired altitude, and fly autonomously towards a sampling point. This sampling point is the target position specified on the 2D reference map. This mode also includes navigation towards the sampling point, avoiding the obstacles in the constrained environment. After reaching a stopping point, Dexterous Hexrotor waits for the human input for a target location to swab and collect samples. The Dexterous Hexrotor is now in sampling mode and waits for the human input. The human operator selects the swabbing location through the live streaming video from onboard camera. Through visual servoing, aided by the map, the UAV will move closer towards the target position. It then transitions to the impact control scheme to perform physical interaction with the wall and collects samples. Once the sample is collected, it autonomously returns back to the takeoff position in 'safe' area for the analysis by mass spectrometry. In this paper, we majorly focus on the physical interaction strategy and the required components which enables the autonomy. Decommissioning of nuclear facilities requires decontamination inside the entire buildings. Decontamination of nuclear facilities involves sensing and sampling the huge buildings, long shafts, etc. Sampling the entire facility is not possible due to the limitation in Dexterous Hexrotor's flight time. But this can be achieved by using a swarm of Dexterous Hexrotors to cover larger areas. The onboard robotic arm can be designed based on the applications such as cleaning, applying sealants, etc. The modularity of the design allows us to switch components as per the requirements of the task. These kind of robotic solutions functioning as tools for the workers, aims to make the work environment safer and playful. (authors)
Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and interkingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.
Abstract In operando powder diffraction remains one of the most powerful tools for non‐destructive investigation of battery electrode materials. While in operando X‐ray, especially synchrotron radiation, powder diffraction is by now a routine experimental technique, in operando neutron powder diffraction is still less established. We present a new electrochemical cell for in operando neutron powder diffraction, which is, first and foremost, easy to use, but can also cycle electrode materials under electrochemical conditions close to those achieved using standard laboratory cells. The cell has been designed in multiple sizes, and high‐quality electrochemical and neutron powder diffraction data is presented for sample sizes as low as 48 mg total active material. The cell handles lithium‐ion and sodium‐ion materials equally well, with no difference in how the cell is prepared and assembled. The cell is intended to be used as sample environment at powder diffractometers at the neutron facilities MLZ, ORNL and ACNS.
Method and system for causing a powder sample in a sample holder to undergo at least one of three motions (vibration, rotation and translation) at a selected motion frequency in order to present several views of an individual grain of the sample. One or more measurements of diffraction, fluorescence, spectroscopic interaction, transmission, absorption and/or reflection can be made on the sample, using light in a selected wavelength region.
We report the design, development, and testing of the Sample Processor for Life on Icy Worlds (SPLIce) system, a microfluidic sample processor to enable autonomous detection of signatures of life and measurements of habitability parameters in Ocean Worlds. This monolithic fluid processing-and-handling system (Figure 1; mass 0.5 kg) retrieves a 50-L-volume sample and prepares it to supply a suite of detection instruments, each with unique preparation needs. SPLIce has potential applications in orbiter missions that sample ocean plumes, such as found in Saturns icy moon Enceladus, or landed missions on the surface of icy satellites, such as Jupiters moon Europa. Answering the question Are we alone in the universe? is captivating and exceptionally challenging. Even general criteria that define life very broadly include a significant role for water [1,2]. Searches for extinct or extant life therefore prioritize locations of abundant water whether in ancient (Mars), or present (Europa and Enceladus) times. Only two previous planetary missions had onboard fluid processing: the Viking Biology Experiments [3] and Phoenixs Wet Chemistry Laboratory (WCL) [4]. SPLIce differs crucially from those systems, including its capability to process and distribute L-volume samples and the integration autonomous control of a wide range of fluidic functions, including: 1) retrieval of fluid samples from an evacuated sample chamber; 2) onboard multi-year storage of dehydrated reagents; 3) integrated pressure, pH, and conductivity measurement; 4) filtration and retention of insoluble particles for microscopy; 5) dilution or vacuum-driven concentration of samples to accommodate instrument working ranges; 6) removal of gas bubbles from sample aliquots; 7) unidirectional flow (check valves); 8) active flow-path selection (solenoid-actuated valves); 9) metered pumping in 100 nL volume increments. The SPLIce manifold, made of three thermally fused layers of precision-machined cyclo-olefin polymer, supports all fluidic components (Figure 1) and integrated microchannels (125 x 250 m). Fluid is pumped by a stepper-motor-driven pump (Lee Co.). The functionality of the integrated MEMS pressure sensor (Honeywell) and passive check valves (Figure 2) were tested in conjunction with our newly designed integral bubble traps (Figure 3) and hydrophobic membrane-based concentrator (Figure 4). The concentrator (initially tested as a standalone component) demonstrated 5-fold vacuum-evaporative concentration. Polyethylene fused bead beds (PEFBBs; 50 porosity) store drylyophilized buffers, calibrants, and fluorescent dyes, and also promote mixing of sample with calibrant, dye, or H2O. Software-controlled automated tests demonstrated successful 1) fluid delivery to each component 2) valve and pump synchronization 3) sample aliquot delivery to instrument interface ports, and 4) rehydration of vacuum-dried fluorescent dye. In Figure 5, fluorescein on PEFBBs was rehydrated for 15 min using a pump-delivered water aliquot; it is displaced as H2O enters the bottom of the channel and pushes the dye into a check valve. Ultimately, SPLIce will fluorescently label amino acids in the sample for microchip-based electrophoretic (MCE) chiral separation and detection to seek and quantify key organic bio-signatures [5]; it will also deliver sample to a microfluidic version of WCL (mWCL) to measure soluble ions and redox-active species.
Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and inter-kingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.
Mars Organic Molecule Analyzer - Mass Spectrometer (MOMA-MS) is an instrument in the MOMA instrument suite for the European Space Agency (ESA) ExoMars 2020 Rover. The rover is Planetary Protection Mission Category IVb, the first IVb mission since the Viking missions in the 1970s. Within the sample path of the MOMA instrument suite, the hardware surfaces of the must be sanitized to a level of less than 0.03 spore/m sq. To meet this requirement, the MS sample path was subjected to Dry Heat Microbial Reduction (DHMR) to decrease the number of viable spores by 4 orders of magnitude from a measured 88 spores/m sq to 0.009 spores/m sq. Before DHMR, the hardware is handled using standard cleanroom practices. After DHMR, planetary protection filters protect the sample path for most of integration, but when sample path exposure is required, aseptic operations are instituted and exposure times are kept to an absolute minimum. The surface area of exposure is also taken into account to determine safe exposure times. Before work begins, the ISO class 5 aseptic workspace is cleaned and tested for surface and airborne bioburden, and all tools that will contact or be used near sample path surfaces are sterilized. During the exposure activity, sterile garments are worn, sterile gloves are changed as often as necessary, and the environment is monitored with active and passive fallout for bioburden and real time airborne particle counts. Sterile tools are handled by a two person team so that the operator touches only the tool and not the exterior surfaces of the sterilization pouch, and a sterile operating field is established as a safe place to organize tools or parts during the aseptic operations. In cases where aseptic operations are not feasible, localized DHMR is used after exposure. Any breach in the planetary protection cleanliness can necessitate repeating instrument level DHMR, which not only has significant cost and schedule implications, it also become a risk to hardware that is not rated for repeated long exposures to high temperatures.
Technological requirements of a planetary return sample mission were studied. The state-of-the-art for problems unique to this class of missions was assessed and technological gaps were identified. The problem areas where significant advancement of the state-of-the-art is required are: life support for the exobiota during the return trip and within the Planetary Receiving Laboratory (PRL); biohazard assessment and control technology; and quarantine qualified handling and experimentation methods and equipment for studying the returned sample in the PRL. Concepts for solving these problems are discussed.
This data set contains atmospheric ice nucleating particle (INP) measurements, using Colorado State University’s (CSU) Ice Spectrometer (IS), of filter collections taken at the U.S. DOE ARM AMF2 site onboard the R/V Polarstern P-deck during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign. Samples were collected from October 27, 2019 to September 24, 2020. A filter sampler was mounted approximately 15 m above ground level on a railing in proximity to (and approximately 3 m below) the Aerosol Observation System (AOS) inlet. Single-use filter units open to the atmosphere were pre-cleaned and pre-loaded with 47-mm diameter Nuclepore polycarbonate (0.2 µm pore-diameter) filters. Filters were typically drawn for a three-day period, with an average volume of air filtered of 87,000 standard liters. Total volumes were calculated through recorded daily flow rates using a mass flow meter (TSI). After collection, filters were stored and transported frozen until analysis using CSU’s IS instrument (McCluskey et al., 2018). Aerosol particles were first re-suspended in 8 mL of 0.1 µm-filtered deionized (DI) water. Aliquots of each suspension, and corresponding 11-fold dilutions, were dispensed into polymerase chain reaction (PCR) trays and placed into the aluminum blocks of the IS. Samples were cooled at approximately 0.33 °C min -1 and freezing detected optically with corresponding temperatures recorded. Cumulative INP concentrations were determined through calculating the number of INPs per mL of suspension (Vali, 1971) and converting to concentration per standard L of air by accounting for the proportion of liquid used and volume of air collected. All samples were corrected for the number of INPs on the average of four field blanks (cleaned, handled, transported, and analyzed in the same way without air flow). Two-tailed, 95% confidence intervals for binomial sampling are provided (Agresti and Coull, 1998). Select samples were also heat treated (95 °C for 20 min) to denature and deactivate biological INPs present and digested in 10% H 2 O 2 at 95 °C under UV-B for 20 min to remove any organic carbon INPs. Agresti, A, and BA Coull. 1998. "Approximate is better than “exact” for interval estimation of binomial proportions." American Statistics 52: 119–126. https://doi.org/10.2307/2685469 McCluskey, CS, J Ovadnevaite, M Rinaldi, J Atkinson, F Belosi, D Ceburnis, … and PJ DeMott. 2018. "Marine and Terrestrial Organic Ice-Nucleating Particles in Pristine Marine to Continentally Influenced Northeast Atlantic Air Masses." Journal of Geophysical Research: Atmospheres 123 (11): 6196–6212, https://doi.org/10.1029/2017JD028033 Vali, G. 1971. "Quantitative Evaluation of Experimental Results and the Heterogeneous Freezing Nucleation of Supercooled Liquids." Journal of the Atmospheric Sciences 28: 402-209. https://doi.org/10.1175/1520-0469(1971)028<0402:QEOERA>2.0.CO;2
As NASA continues to perform research on the ISS and move towards the Moon and Mars, it is important for astronauts to have a technology capable of determining the composition of solid, liquid, and gas samples. Currently, samples are transported back to Earth for analysis, which may impact results due to the time delay of samples waiting to be returned to Earth as well as potential sample contamination from re-entry, change in environment, and various personnel handling. Therefore, researchers at the Applied Chemistry Lab at KSC have developed a proof-of-concept “Plasma-Based Elemental Analyzer,” which has the capability of testing solid, liquid, and gas samples for identification. Currently, the analysis is only qualitative, with quantitative identification left for future work. This technology is similar to ICP-OES, but differs in instrument size and sample preparation. Both technologies use plasma to ionize samples for light emission. The plasma elemental analyzer aims to be portable and lightweight, require only electrical power, and analyze solid, liquid, and gas samples. It does not use acid digestion or a nebulizer, requires less power than ICP-OES, and is able to operate with minimal to no usage of argon gas. Furthermore, the plasma elemental analyzer operates within low power constraints, which makes it feasible for usage on future missions with higher power constraints. The technology was tested at atmospheric pressure using mostly room air as the carrier gas for plasma production in the proof-of-concept study. The results showed the peak signals of the elements with an associated arbitrary signal intensity that allowed for qualitative identification. Solid samples that were tested included inedible biomass from the Golden Heirloom Cherry Tomato plant and Lunar Highlands Simulants (LHS-1). The liquid samples included elements of interest for the space crop production community. This work showed that a system smaller than the traditional ICP-OES equipment is able to be designed and implemented in future use cases, although it requires further development.
The Experiment AO 138-6 was located on the trailing edge of the Long Duration Exposure Facility as part of the French Cooperative Payload (FRECOPA) Experiment. It was purely passive in nature: material specimens 2 x 2 cm, independently mounted in sample-holders, with their surface in the same reference plane, were exposed to space. Thirty samples were set in a vacuum-tight canister which was opened in space a few days after LDEF deployment and closed while still in orbit ten months later; twenty-four samples were directly exposed to space for the total flight duration (preflight handling, shuttle bay environment, separation from shuttle, shuttle environment, LEO environment, docking, descent, transfer to KSC). Materials included paints (conductive or nonconductive), SSM's, polymeric films, surface coatings, composite materials, and metals. After sample retrieving, inspection and measurements were carried out in atmospheric laboratory conditions on each sample: observation with binocular lenses and scanning electron microscopy, spectral relectance and transmittance using an integrating sphere in the wavelength range 280-2300 nm, emissivity by the means of a Gier & Dunkle portable reflectometer, electron spectroscopy for chemical analysis-x-ray photoelectron spectroscopy (ESCA-XPS), and Rutherford backscattering spectroscopy (RBS) measurements on some selected samples. The results obtained from flight were compared to laboratory data obtained in UV-irradiation tests when these data were available. As a general statement a good spectral concordance is observed for all samples not in the canister so long as air recoveries are taken into account. For one material, the degradation is more important for the sample in the canister than for those of the same material mounted at the surface of the tray; for most samples in the canister the degradation is slightly higher than the one which can be predicted from laboratory standard irradiations. Contamination problems having been ruled out, the higher temperature experience by the samples on the inside of canister probably explains these phenomena.