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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Rational Design of Nanoplasmonic Array Geometries for Biosensing

Background: Molecular diagnostics provide early and accurate diagnosis, which is essential for the prevention and treatment of infectious as well as chronic diseases. These tests are designed to detect disease-specific bioanalytes such as nucleic acid (DNA or RNA) or protein (antigens, antibodies) biomarkers. In the context of infectious disease diagnosis, nucleic acid-based detection methods are known to provide more specific and sensitive results. Here, the presence of a unique sequence belonging to the pathogenic genomic material is targeted to identify species, organism, genera and/or antimicrobial resistant gene markers. The majority of the common nucleic acid based diagnostic techniques require amplification (polymerase chain reaction, isothermal amplification etc.) of the pathogenic genetic material prior to detection impacting diagnostic speed, complexity, and cost thereby limiting ease of use. Thus, the development of simplified nucleic acid-based diagnostics that can be even used in resource-poor settings may hugely benefit patients across the globe. Nanopath is a molecular diagnostics company utilizing a solid-state nanosensor to enable sequence-specific detection of target nucleic acids without the need of amplification. These nanostructures enable ultra-sensitive biomarker detection using geometric, feature-dependent properties highly dependent on the local dielectric environment, allowing them to be sensitive to low concentration binding events. This paper describes an application of this approach to provide highly relevant clinical information within a single doctor’s office visit. Intro: The Nanopath team is in collaboration with NASA (National Aeronautics and Space Administration) and NIST (National Institute of Standards and Technology) to push the bounds of the fundamental physics associated with their biosensing platform. The ability of metals to support electromagnetic surface waves gives rise to surface plasmons when optically illuminated. This property, and its strong sensitivity to changes in the local refractive index, allows for the use of metal nanoparticles as ultra-sensitive transducers. In prior work by members of this team, ensembles of randomly oriented nanoparticles (i.e., colloidal nanorods dispersed on chip) were employed for sequence-specific nucleic acid sensing (1-3). While these particle sensors have the advantage of rapid fabrication, they suffer from low sensitivity and quality factor due to the random particle dispersity. In contrast, in this study we employ ordered array nanoparticle ensembles which can be used to improve sensor sensitivity and figure-of-merit. Study Methods Overview: In this talk, we detail the results of sensing experiments and computational simulations to outline a rational design of the structure of these plasmonic nanoparticle arrays for biomolecular sensing. Through simulation and experiment, we iteratively tailor nanostructure dimension to provide high quality signal and large resonance shifts upon modeled nucleic acid binding. In particular, full-wave electromagnetic simulations were conducted using Lumerical photonic simulation software in which periodic boundary conditions were applied in the x- and y- dimensions for each of the nanoplasmonic sensor geometries. To simulate the resonance response to changes in the bulk solution in contact with the sensor surface, the refractive index of the surrounding media was changed appropriately. Nucleic acid hybridization events were modeled using either using spherical structures approximating the relevant radius of genomic material as estimated by polymer models, or as conformal layers with the known refractive indices for nucleic acids. On the basis of initial simulations, nanosensors were fabricated using traditional electron-beam lithography protocols at NIST. To evaluate consensus between simulations and experiments, bulk sensing experiments were carried out in which the resonance peaks were obtained by submerging the sensors in refractive index standards. Key nanosensor characteristics including resonance peak locations, resonance peak shifts as a function of refractive index, and figure of merit (FOM) of extinction curves were examined between the experimental and simulation results prior to proceeding with simulations on additional geometries and more complex solution conditions, and further device fabrication. This iterative process is repeated toward a rational design of nanoplasmonic array geometries for biosensing optimizing response for targeted disease detection. In summary, this study puts forth a methodology for rational design and characterization of regularly spaced nanoparticle arrays for optics-based biosensing. The results of this study will allow for more informed design of nanostructure geometries towards sequence-specific nucleic acid detection. These improved designs have the potential to improve clinical sensitivity and limit-of-detection across disease indication.

sensor↗
NASA NTRS1971

A Fluorescent Source NDIR Carbon Monoxide Analyzer

This paper describes a new technique for measuring trace quantities of carbon monoxide by the nondispersive infrared (NDIR) methods. The technique uses the property of infrared fluorescence in a gas to generate a specific source of radiation which is an exact match of the absorption spectrum of the fundamental band of carbon monoxide. This results in an instrument with high sensitivity and specificity for CO. A novel method of referencing using an isotopic species of CO confers great stability on the instrument.

Link, W. T.↗
NASA NTRS2015

On-Orbit, Immuno-Based, Label-Free White Blood Cell Counting System with Microelectromechanical Sensor Technology (OILWBCS-MEMS)

Aurora Flight Sciences, in partnership with Draper Laboratory, has developed a miniaturized system to count white blood cells in microgravity environments. The system uses MEMS technology to simultaneously count total white blood cells, the five white blood cell differential subgroups, and various lymphocyte subtypes. The OILWBCS-MEMS detection technology works by immobilizing an array of white blood cell-specific antibodies on small, gold-coated membranes. When blood flows across the membranes, specific cells' surface protein antigens bind to their corresponding antibodies. This binding can be measured and correlated to cell counts. In Phase I, the partners demonstrated surface chemistry sensitivity and specificity for total white blood cells and two lymphocyte subtypes. In Phase II, a functional prototype demonstrated end-to-end operation. This rugged, miniaturized device requires minimal blood sample preparation and will be useful for both space flight and terrestrial applications.

Edmonds, Jessica↗
NASA NTRS1991

Regulated bioluminescence as a tool for bioremediation process monitoring and control of bacterial cultures

An effective on-line monitoring technique for toxic waste bioremediation using bioluminescent microorganisms has shown great potential for the description and optimization of biological processes. The lux genes of the bacterium Vibrio fischeri are used by this species to produce visible light. The lux genes can be genetically fused to the control region of a catabolic gene, with the result that bioluminescence is produced whenever the catabolic gene is induced. Thus the detection of light from a sample indicates that genetic expression from a specific gene is occurring. This technique was used to monitor biodegradation of specific contaminants from waste sites. For these studies, fusions between the lux genes and the operons for naphthalene and toluene/xylene degradation were constructed. Strains carrying one of these fusions respond sensitively and specifically to target substrates. Bioluminescence from these cultures can be rapidly measured in a nondestructive and noninvasive manner. The potential for this technique in this and other biological systems is discussed.

Burlage, Robert S.↗
NASA NTRSDate not supplied

Crowd Sourcing Medical Data Collection Using Medical Students

OBJECTIVE We undertook an upgrade of the Evidence Library database of NASA HRP’s Integrated Medical Model, assessing 120 medical conditions which integrate with a novel probabilistic risk assessment (IMPACT) tool of medical risk and resource utilization for long duration exploration human spaceflight. This data collection process included a selection of these conditions crowd sourced over one year via three 4-week medical student electives at the University of Colorado School of Medicine (IDPT 8059 Space Medicine: Human Spaceflight Factors & Medical Risk Assessment). Students undertook a rapid systematic review of each medical condition, under close preceptors with backgrounds in clinical medicine, library science, epidemiology, biostatistics, and evidence-based medicine. As part of the elective, students also received instruction in core space medicine concepts, evidence based medicine and problem based learning sessions as a flight surgeon supporting a simulated Mars mission. METHODS The list of 120 medical conditions includes both common, terrestrial illness/injury (epistaxis, diverticulitis) as well as spaceflight-specific ones (space adaptation conditions, EVA-related injuries). A rapid systematic review process was developed that would allow students to find the data for determining disease incidence/prevalence, return to definitive care (often a surrogate such as hospitalization rates), loss of crew life, and treatment duration. Each data point required a tailored, specialized search process using different databases and corresponding specialized search filters. Databases were selected on their ability to provide high quality literature in an efficient manner and prioritized by their ability to provide graded evidence via a set rubrics specific to human spaceflight. Students were responsible for performing all literature searches and identifying the highest quality available evidence for each data point. Completed student data sheets underwent initial review by faculty preceptors followed by a secondary editing review by the ExMC Clinical Science Team. RESULTS Over the course of three electives, approximately 105 medical conditions were researched by students using spreadsheets with pre-crafted search strategies. Overall, this process was successful in allowing students to perform the preponderance of work to update incidence, treatment duration, return to definitive care, and loss of crew life data points. Students were successful in running searches, identifying the necessary data points within the literature, and determining the types of terrestrial data that most aligns with the astronaut population for successful completion of their tasks. Limitations included variable student experience with search methodologies [PubMed], differing values of evidence grading [best practice evidence based medicine vs. relevant to spaceflight], and students’ unfamiliarity with spaceflight specific conditions. CONCLUSION Finding the relevant literature for medical conditions in spaceflight within terrestrial databases in a systematic method is time consuming and not intuitive. However, the stepwise process that balanced sensitivity with specificity allowed for students to be highly successful in a short amount of time. Additionally, as the process was refined over the course of three electives, preceptors were better able to anticipate where students were likely to encounter barriers, which allowed the course to be adjusted to account for certain data points needing more time for completion. This replicable process may be an efficient way to accomplish rapid systematic reviews for a large volume of data in a short amount of time.

J Lemery↗
NASA NTRS1995

PCR Based Microbial Monitor for Analysis of Recycled Water Aboard the ISSA: Issues and Prospects

The monitoring of spacecraft life support systems for the presence of health threatening microorganisms is paramount for crew well being and successful completion of missions. Development of technology to monitor spacecraft recycled water based on detection and identification of the genetic material of contaminating microorganisms and viruses would be a substantial improvement over current NASA plans to monitor recycled water samples that call for the use of conventional microbiology techniques which are slow, insensitive, and labor intensive. The union of the molecular biology techniques of DNA probe hybridization and polymerase chain reaction (PCR) offers a powerful method for the detection, identification, and quantification of microorganisms and viruses. This technology is theoretically capable of assaying samples in as little as two hours with specificity and sensitivity unmatched by any other method. A major advance in probe-hybridization/PCR has come about in a technology called TaqMan(TM), which was invented by Perkin Elmer. Instrumentation using TaqMan concepts is evolving towards devices that could meet NASA's needs of size, low power use, and simplicity of operation. The chemistry and molecular biology needed to utilize these probe-hybridization/PCR instruments must evolve in parallel with the hardware. The following issues of chemistry and biology must be addressed in developing a monitor: Early in the development of a PCR-based microbial monitor it will be necessary to decide how many and which organisms does the system need the capacity to detect. We propose a set of 17 different tests that would detect groups of bacteria and fungus, as well as specific eukaryotic parasites and viruses; In order to use the great sensitivity of PCR it will be necessary to concentrate water samples using filtration. If a lower limit of detection of 1 microorganism per 100 ml is required then the microbes in a 100 ml sample must be concentrated into a volume that can be added to a PCR assay; There are not likely to be contaminants in ISSA recycled water that would inhibit PCR resulting in false-negative results; The TaqMan PCR product detection system is the most promising method for developing a rapid, highly automated gene-based microbial monitoring system. The method is inherently quantitative. NASA and other government agencies have invested in other technologies that, although potentially could lead to revolutionary advances, are not likely to mature in the next 5 years into working systems; PCR-based methods cannot distinguish between DNA or RNA of a viable microorganism and that of a non-viable organism. This may or may not be an important issue with reclaimed water on the ISSA. The recycling system probably damages the capacity of the genetic material of any bacteria or viruses killed during processing to serve as a template in a PCR desinged to amplify a large segment of DNA (less than 650 base pairs). If necessary, vital dye staining could be used in addition to PCR, to enumerate the viable cells in a water sample; The quality control methods have been developed to insure that PCR's are working properly, and that reactions are not contaminated with PCR carryover products which could lead to the generation of false-positive results; and The sequences of the small rRNA subunit gene for a large number of microorganisms are known, and they consititue the best database for rational development of the oligonucleotide reagents that give PCR its great specificity. From those gene sequences, sets of oligonucleotide primers for PCR and Taqman detection that could be used in a NASA microbial monitor were constructed using computer based methods. In addition to space utilization, a microbial monitior will have tremendous terrestrial applications. Analysis of patient samples for microbial pathogens, testing industrial effluent for biofouling bacteria, and detection biological warfare agents on the battlefield are but a few of the diverse potential uses for this technology. Once fully developed, gene-based microbial monitors will become the fundamental tool in every lab that tests for microbial contaminants, and serve as a powerful weapon in mankind's war with the germ world.

Cassell, Gail H.↗
NASA NTRS2019

Predicting Cancer Risk from Ionizing Radiation

The ability to predict cancer risk associated with exposure to low doses of high-LET ionizing radiation (IR) remains a challenge. Epidemiological methods lack the sensitivity and power to provide detailed risk estimates for cancer and ignore individual variance in IR sensitivity. We have hypothesized that DNA repair capacity can be used as a marker to evaluate and differentiate individual radiation sensitivity. More specifically, this work is based on the concept that the combined time-dose dependence of radiation-induced foci (RIF) of p53-binding protein 1 (53BP1) following low-LET exposure contains sufficient information to infer sensitivity to any other LET. Our hypothesis was tested in 15 different mouse strains as well as in primary human immune cells. We first approached individual ionizing radiation sensitivity in a mouse model by culturing primary skin fibroblasts extracted from 76 mice of 15 different genetic backgrounds and exposing them to HZE particles and X-rays. This work is one of the most extensive studies on the kinetics and possible genetic underpinnings of radiation-induced DNA damage and repair. Our results is in agreement with a DNA repair model we previously postulated, where nearby DNA double strand breaks (DSB) in the nucleus are brought together for more efficient repair, leading to RIF clustering. Such mechanism was evidenced by a specific dose and LET dependence of RIF numbers. Briefly, RIF quantification after low-LET X-ray exposure showed an asymptotic saturation for doses between 1 Gy and 4 Gy 4 hours post-irradiation across all 15 strains. The clustering of DSB across all strains also led to more RIF/Gy for lower LET (X-ray and 350 MeV/n Ar) than for higher LET (600 MeV/n Fe) 4 hours post-exposure. Considering the fact that the number of DSB/Gy should be independent of LET, our data suggest there are more DSB in individual RIF as the LET increases. RIF numbers for 24 and 48 hours post-exposure led to the inverse trend, with more remaining RIF/Gy for higher LET (by 600 MeV/n Fe). This result suggests cells have more difficulty resolving RIF from higher LET as they the number DSB/RIF increases. Note that for most conditions, the variance of RIF/Gy was small within individual animals of the same strain and large between strains, suggesting a strong genetics component. Furthermore, we present our preliminary data from an ongoing study on human genetic associations with IR sensitivity. To address the human variability in responses to HZE particle irradiation in a maximally comprehensive manner, we are in the process of collecting and isolating primary blood mononuclear cells from 768 healthy subjects of European descent, 18-75 years of age, 50/50 male/female distribution. We have analyzed 53BP1+ RIF formation as well as oxidative stress and cell death in primary cells from 192 subjects in response to the same HZE particles as used in mice: 600 MeV/n Fe, 350 MeV/n Ar and 350 MeV/n Si, 1.1 and 3 particles/100m2, 4 and 24 hours after irradiation. We will next complete the quantification of HZE particle-induced DNA and cellular damage in the remaining subjects and compare it to their responses to low-LET irradiation. Finally, we will perform GWAS analysis to identify human genomic associations with IR sensitivity and potential targets for biomarker development.

High-LET radiation↗
NASA NTRS2005

Development of Ultra-High Sensivity Silicon Carbide Detectors

A variety of silicon carbide (SiC) detectors have been developed to study the sensitivity of SiC ultraviolet (UV) detectors, including Schottky photodiodes, p-i-n photodiodes, avalanche photodiodes (APDs), and single photon-counting APDs. Due to the very wide bandgap and thus extremely low leakage current, Sic photo-detectors showed excellent sensitivity. The specific detectivity, D*, of SiC photodiodes are orders of magnitude higher than that of their competitors, such as Si photodiodes, and comparable to the D* of photomultiplier tubes (PMTs). To pursue the ultimate detection sensitivity, SiC APDs and single photon-counting avalanche diodes (SPADs) have also been fabricated. By operating the SiC APDs at a linear mode gain over 10(exp 6), SPADs in UV have been demonstrated. SiC UV detectors have great potential for use in solar blind UV detection and biosensing. Moreover, SiC detectors have excellent radiation hardness and high temperature tolerance which makes them ideal for extreme environment applications such as in space or on the surface of the Moon or Mars.

Yan, Feng↗
NASA NTRS2019

DNA Damage Response to Low and High-LET in a Large Cohort of Mice and Humans and Latest Advancement in NASA Space Omics

This presentation will first focus on a thorough evaluation of the DNA damage response to both low and high-LET in a cohort of 76 mice primary skin fibroblast derived from 15 different strains or in human blood mononuclear cells derived from 550 healthy donors. In both the human and mice work, we have hypothesized that DNA repair capacity can be used as a marker to evaluate and differentiate individual radiation sensitivity. More specifically, this work is based on the concept that the combined time-dose dependence of radiation-induced foci (RIF) of p53-binding protein 1 (53BP1) following low-LET exposure contains sufficient information to infer sensitivity to any other LET. This work is one of the most extensive studies on the kinetics and possible genetic underpinnings of radiation-induced DNA damage and repair. Results on humans are still preliminary as we are still in the process of collecting and isolating primary blood mononuclear cells from 500 to 800 healthy subjects of European descent, 18-75 years of age, 50/50 male/female distribution. We have analyzed 53BP1+ RIF formation as well as oxidative stress and cell death in primary cells from 192 subjects in response to the same HZE particles as used in mice: 600 MeV/n Fe, 350 MeV/n Ar and 350 MeV/n Si, 1.1 and 3 particles/100m2, 4 and 24 hours after irradiation. The second part of the talk will focus on describing GeneLab: The NASA Systems Biology Platform for Space Omics Repository, Analysis and Visualization. NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). Started as a repository designed to archive precious omics from space experiments, GeneLab has expanded its scope to maximize the intelligibility of the raw data (e.g. RNAseq, microarray, WGBS, metagenome), particularly for users with limited bioinformatics knowledge. As such GeneLab is now providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome), to help users explore important questions: Which genes or proteins are expressed differently in space for various living organisms? What are the consequences arising from these changes? What specifics DNA mutations or epigenetic changes happen in space? What species or genetic features lead to better adaption to such a unique environment? In this presentation, we will report on the current and future objectives for GeneLab, and review recent published studies relating molecular changes observed in various animal models and tissue with microgravity, radiation, circadian rhythm, hydration and carbon dioxide conditions.

DNA repair kinetics↗
NASA NTRS2019

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗
NASA NTRS2007

Microscopic Observation of Self-Propagation of Calcifying Nanoparticles (Nanobacteria)

Biologists typically define living organisms as carbon and water-based cellular forms with :self-replication" as the fundamental trait of the life process. However, this standard dictionary definition of life does not help scientists to categorize self-replicators like viruses, prions, proteons and artificial life. CNP also named nanobacteria were discovered in early 1990s as about 100 nanometer-sized bacteria-like particles with unique apatite mineral-shells around them, and found to be associated with pathological-calcification related diseases. Although CNP have been isolated and cultured from mammalian blood and diseased calcified tissues, and their biomineralizing properties well established, their biological nature and self-replicating capability have always been severely challenged. The terms "self-replication", "self-assembly" or "self-propagation" have been widely used for all systems including nanomachines, crystals, computer viruses and memes. In a simple taxonomy, all biological and non-biological "self replicators", have been classified into "living" or "nonliving" based on the properties of the systems and the amount of support they require to self-replicate. To enhance our understanding about self-replicating nature of CNP, we have investigated their growth in specific culture conditions using conventional inverted light microscope and BioStation IM, Nikon s latest time-lapse imaging system. Their morphological structure was examined using scanning (SEM) and transmission (TEM) electron microscopy. This present study, in conjunction with previous findings of metabolic activity, antibiotic sensitivity, antibody specificity, morphological aspects and infectivity, all concomitantly validate CNP as living self-replicators.

Mathew, Grace↗
NASA NTRS1984

Quantitative non-destructive evaluation of composite materials based on ultrasonic wave propagation

The size, shape, and orientation of damage correlates well between the polar backscatter technique and the deply technique. There is good quantitative correlation between the areas of damage indicated by the two techniques. These results suggest that the polar backscatter technique is sensitive to specific orientations of damage. The polar backscatter technique provides a good qualitative image of the size and shape of the largest zone of damage in each of the principal orientations. A quantitative estimate of the extent of these largest damage zones is obtained from the polar backscatter technique. The selective sensitivity of polar backscatter provides a useful tool for further studies of the mechanisms of impact damage in graphite fiber reinforced composite laminates.

Miller, J. G.↗
DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2024

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Surface-Enhanced Raman Spectroscopy (SERS) for Venus Atmospheric Characterization and Trace Organics Identification

The chemical composition of Venus’ clouds has attracted considerable attention since the first atmospheric probes entered the planet in the early 1980s. We know from these early studies that cloud aerosols consist of micron and submicron droplets of sulfuric acid (~85%) and water (~15%), but outstanding questions still exist regarding their trace chemical composition, especially the identity of the unknown UV absorber(s) and the possible presence of organic material (Spacek & Benner, 2021). Veritas and DaVinci will launch at the end of the decade to advance our understanding of Venus’ surface and atmosphere, however these missions are not designed to sample and analyze cloud aerosols at trace levels. Raman spectroscopy is an ideal candidate for characterizing aerosols and has a track record in studies of Earth’s atmosphere. Raman provides broad chemical screening of organic and inorganic molecules within seconds, and Raman instrumentation can be miniaturized to meet the stringent size, weight, and power (SWaP) constraints of an atmospheric probe while retaining sensitivity and specificity that allow spectral fingerprinting of compounds and functional groups. Raman alone is insufficient to characterize trace constituents however, as limits of detection are typically in the 10s to 100s of ppm at best for planetary Raman spectrometers. Surface-Enhanced Raman Spectroscopy (SERS), a method that utilizes nanoscale materials interacting with a sample to enhance weak Raman signals by orders of magnitude when probed by a laser, has the potential to drastically improve the sensitivity of a Raman instrument while adding little-to-no SWaP nor complexity to a scientific payload. We aim to de-risk SERS technology for rapid infusion in future planetary science missions by developing custom SERS substrates tailored towards Venus atmospheric exploration. We have developed SERS substrates consisting of nanotextured silver films and tested them on potential Venus-relevant organic compounds, with preliminary results indicating sub-ppm sensitivity. Additionally, we have planned tests to investigate durability, longevity, and other key characteristics that impact SERS substrate performance to prepare SERS technology for flight.

Venus↗
NASA NTRS1987

An enzyme immunoassay for rat growth hormone - Applications to the study of growth hormone variants

A sensitive and specific competitive enzyme immunoassay for rat growth hormone (GH) is described and its use in the detection of GH variants is demonstrated. In the present assay, soluble GH and GH adsorbed to a solid-phase support compete for monkey anti-GH antibody binding sites. The immobilized antibody-GH complex is detected and quantified using goat antimonkey immunoglobin G covalently conjugated to horseradish peroxidase. It is noted that the assay can be performed in 27 hours and that sensitivities in the range of 0.19 to 25 ng can be obtained in the region of 10 to 90 percent binding.

Farrington, Marianne A.↗
NASA NTRS2007

Determination of Scopolamine in Human Saliva Using Solid Phase Extraction and LC/MS/MS

Purpose: Scopolamine is the preferred treatment for motion sickness during space flight because of its quick onset of action, short half-life and favorable side-effect profile. The dose administered depends on the mode of administration and usually ranges between 0.1 and 0.8 mg. Such small doses make it difficult to detect concentrations of scopolamine in biological fluids by using conventional HPLC methods. To measure scopolamine in saliva and thereby to evaluate the pharmacokinetics of scopolamine, we developed an LC/MS/MS method using off-line solid phase extraction. Method: Samples (0.5mL) were loaded onto Waters Oasis HLB co-polymer cartridges (10 mg, 1 mL) and eluted with 0.5 mL methanol without evaporation and reconstitution. HPLC separation of the eluted sample was performed using an Agilent Zorbax SB-CN column (50 x 2.1 mm) at a flow rate of 0.2 mL/min for 4 minutes. The mobile phase for separation was 90:10 (v/v) methanol: ammonium acetate (2 mM) in water, pH 5.0 +/- 0.1. Concentrations of scopolamine were determined using a Micromass Quattro Micro(TM) mass spectrometer with electrospray ionization (ESI). ESI mass spectra were acquired in positive ion mode with multiple reaction monitoring for the determination of scopolamine m/z = 304.2 yields 138.1 and internal standard (IS) hyoscyamine m/z = 290.2 yields 124.1. Results: The method is rapid, reproducible, specific and has the following parameters: scopolamine and the IS are eluted at 1.7 and 3.2 min respectively. The linear range is 50-5000 pg/mL for scopolamine in saliva with correlation coefficients > 0.99 with a CV < 0.5 %. The intra-day and inter-day CVs are < 15 % for quality control samples with concentrations of 75, 300, 750 and 3000 pg/mL of scopolamine in human saliva. Conclusion: Solid phase extraction allows more rapid sample preparation and greater precision than liquid extraction. Furthermore, we increased the sensitivity and specificity by adjusting the LC mobile phase and using an MS/MS detector.

Wang, Zuwei↗
NASA NTRSDate not supplied

Developmental Hardware Testing Results and Forward Plans for the Spacecraft Water Impurity Monitor (SWIM) Organic Water Module (OWM)

We present testing results for developmental hardware of the Spacecraft Water Impurity Monitor (SWIM) Organic Water Module (OWM). SWIM-OWM will monitor spacecraft potable water and system water for trace organic contaminants. The system will detect and identify the specific organic chemical that makes up a given total organic carbon reading. We have built a first development unit (1DU) for SWIM-OWM, which directly injects aqueous water samples and detects chemicals with both a thermal conductivity detector and mass spectrometer sensor. The gas chromatography mass spectrometer (GCMS) system that comprises SWIM-OWM draws on the success of ISS-proven mass spectrometer hardware, and the demonstration of GCMS detection of trace organic contaminants in ISS cabin air. SWIM-OWM benefits from the excellent sensitivity and specificity afforded by GCMS. We have demonstrated detection of a set of chemicals relevant to both crew health and performance as well as system monitoring; these target chemicals range from light, volatile organics such as acetone and ethanol, to heavier, very non-volatile compounds such as dimethyl sulfone and o-phthalaldehyde. Direct aqueous injection was chosen for the general applicability of the technique to clean water sampling and to preclude sample pre-processing, which facilitates an on-line implementation of the SWIM-OWM when deployed in a spacecraft or habitation module. A specific advantage of direct aqueous injection when coupled with appropriate methods is that both the light, volatile organics and heavier non-volatiles can be detected from a single injection, in a single chromatogram. Results from 1DU testing will be discussed, and forward plans will be outlined for continued maturation of SWIM-OWM with the goal of implementing a technology demonstration for the purposes of maturing the engineering design and operations in an environment relevant to NASA’s future goals of exploring and setting up habitation on the Moon and Mars.

Water Monitoring↗