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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42

Multiscale Modeling of Vinyl-Addition Polynorbornenes: The Effect of Stereochemistry

Vinyl-addition polynorbornenes are candidates for designing high-performance polymers due to unique characteristics, which include a high glass transition temperature associated with a rigid backbone. Recent studies have established that the processability and properties of these polymers can be fine-tuned by using targeted substitutions. However, synthesis with different catalysts results in materials with distinct properties, potentially due to the presence of various stereoisomers that are difficult to quantify experimentally. Herein, we develop all-atom models of polynorbornene oligomers based on classical force fields and density functional theory. To establish the relationship between chemical architecture, chain conformations, and melt structure, we perform detailed molecular dynamics simulations with the fine-tuned atomistic force field and propose simpler coarse-grained descriptions to address the high molecular weight limit. All-atom simulations of oligomers suggest high glass transition temperatures in the range of 550–600 K. In the melt state (800 K), meso chains form highly rigid extended coils (C∞≈11) with amorphous structural characteristics similar to the X-ray diffraction data observed in the literature. In contrast, simulations with racemo chains predict highly helical tubular chain conformations that could promote assembly into crystalline structures.

Polymer Science↗

Assessing sensitivities of climate model weighting to multiple methods, variables, and domains in the south-central United States

Given the increasing use of climate projections and multi-model ensemble weighting for a diverse array of applications, this project assesses the sensitivities of climate model weighting strategies and their resulting ensemble means to multiple components, such as the weighting schemes, climate variables, or spatial domains of interest. The purpose of this study is to assess the sensitivities associated with multi-model weighting strategies. The analysis makes use of global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and their statistically downscaled counterparts created with the localized constructed analogs (LOCA) method. This work focuses on historical and projected future mean precipitation and daily high temperatures of the south-central United States. Results suggest that the model weights and the corresponding weighted model means can be sensitive to the weighting strategy that is applied. For instance, when estimating model weights based on Louisiana precipitation, the weighted projections show a wetter and cooler south-central domain in the future compared to other weighting strategies. Alternatively, for example, when estimating model weights based on New Mexico temperature, the weighted projections show a drier and warmer south-central domain in the future. However, when considering the entire south-central domain in estimating the model weights, the weighted future projections show a compromise in the precipitation and temperature estimates. As for uncertainty, our matrix of results provided a more certain picture of future climate compared to the spread in the original model ensemble. If future impact assessments utilize weighting strategies, then our findings suggest that how the specific weighting strategy is used with climate projections may depend on the needs of an impact assessment or adaptation plan.

54 ENVIRONMENTAL SCIENCES↗

Assessing the climate impact of an improved volcanic sulfate aerosol representation in E3SM

Accurately simulating historical surface temperature variations is essential for evaluating climate models, yet many struggle to reproduce the mid-20th-century temperature trends associated with significant volcanic eruptions. This study examines the impact of volcanic sulfate aerosol representation on these biases using the Energy Exascale Earth System Model (E3SM). The standard CMIP6 protocol prescribes volcanic forcing through radiative perturbations, omitting volcanic aerosol–cloud interactions (VACIs). Here, we implement an emission-based approach with an updated volcanic eruption inventory that directly incorporates volcanic sulfur dioxide (SO 2 ) emissions, enabling a more process-based representation of volcanic forcing. This approach leads to improved surface temperature variability and a modest reduction in cold biases between 1940 and 1980 compared to the CMIP6 setup. Additionally, we assess cloud property responses to a more realistic volcanic sulfate aerosol representation, which weakens cloud-induced cooling during periods of lower volcanic activity. However, despite these refinements, a significant temperature cold bias remains, indicating that further improvements in atmospheric chemistry, aerosol microphysics, cloud processes, and model parameterizations are needed to fully resolve this issue in E3SM.

54 ENVIRONMENTAL SCIENCES↗

DOE EM Sponsored Research on Long-Term Dry Storage of Aluminum Clad SNF

This PowerPoint presentation describes and discusses DOE EM and INL lead studies on addressing potential technical issues associated with long-term dry storage of aluminum clad spent nuclear fuel. This same presentation was made to the US Nuclear Waste Technical Review Board in Nov 2019.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Organochlorine pesticides and risk of papillary thyroid cancer in U.S. military personnel: a nested case-control study

Background: The effects of organochlorine pesticide (OCP) exposure on the development of human papillary thyroid cancer (PTC) are not well understood. A nested case-control study was conducted with data from the U.S. Department of Defense Serum Repository (DoDSR) cohort between 2000 and 2013 to assess associations of individual OCPs serum concentrations with PTC risk. Methods: This study included 742 histologically confirmed PTC cases (341 females, 401 males) and 742 individually-matched controls with pre-diagnostic serum samples selected from the DoDSR. Associations between categories of lipid-corrected serum concentrations of seven OCPs and PTC risk were evaluated for classical PTC and follicular PTC using conditional logistic regression, adjusted for body mass index category and military branch to compute odds ratios (OR) and 95% confidence intervals (CIs). Effect modification by sex, birth cohort, and race was examined. Results: There was no evidence of associations between most of the OCPs and PTC, overall or stratified by histological subtype. Overall, there was no evidence of an association between hexachlorobenzene (HCB) and PTC, but stratified by histological subtype HCB was associated with significantly increased risk of classical PTC (third tertile above the limit of detection (LOD) vs. <LOD, OR = 1.61, 95% CI, 1.09, 2.38; p for trend = 0.05) and significantly decreased risk of follicular variant PTC (third tertile above the limit of detection (LOD) vs. <LOD, OR = 0.38, 95% CI, 0.16, 0.91; p for trend = 0.04). Further stratified by sex, risk of classical PTC was higher for females (third tertile above LOD vs. <LOD, OR = 2.23, 95% CI: 1.23, 4.06; p-trend = 0.02) than for males (OR = 1.22, 95%CI: 0.72–2.08; p-trend = 0.56), though the test for interaction by sex was not statistically significant (p-interaction = 0.30). Similarly, β-hexachlorocyclohexane (β-HCCH) was associated with a higher risk for classical PTC for women with concentrations ≥LOD versus <LOD (OR = 1.76, 95% CI: 1.07, 2.89), while the effects were null for men. There were no consistent trends when stratified by race or birth year. Conclusions: The U.S. Environmental Protection Agency has classified HCB and other OCPs we studied here as probable human carcinogens. Our findings of increased risks for classical PTC associated with increased concentrations of HCB and β-HCCH, which were stronger among females, should be replicated in future studies of other populations.

60 APPLIED LIFE SCIENCES↗

Prognostic model and failure mechanisms of steam generators in Sodium-Cooled fast reactors

This paper presents a prognostic model for sodium-cooled fast reactor (SFR) steam generators (SGs). Here, the purpose of the model is to estimate the remaining useful life of SFR SGs and thus to support the decision-making of autonomous control. SFR SGs are of great interest for plant integrity due to their harsh operation environment. They operate at higher temperatures and higher coolant-to-steam pressure differences than those of current light water reactors (LWR). The severity of the SFR SG failure consequences, which include water-sodium contact, is another reason. Understanding its failure mechanisms is important for the development of its prognostic model. Based on our literature review and physics-based analysis, we concluded that creep would be a dominant degradation mode of SFR SGs due to SFR’s high-temperature and high-pressure environment. Thus, creep is the focus of the prognostic model. Various other failure modes were also investigated in this study. The mechanical fatigue due to flow-induced vibration is usually observed in early developmental phases and would not be an important issue during normal operation. The thermal fatigue due to thermal stripping is occasionally observed in other components in SFRs but does not affect SG integrity. Pure water stress corrosive crack, fretting, and so on are commonly observed in LWR SGs but are significantly less important in SFR SGs because of the high temperatures, high pressure differences, and chemical properties of liquid sodium. Based on these investigations, a prognostic model focusing on creep failures was developed. It estimates the failure probability profile by sampling the Larson-Miller parameter (LMP) and temperature and associated uncertainties through Monte Carlo methods. Two case studies were presented. The first one demonstrated the model’s capability to calculate the failure probability for a new specimen within a given time. If the tube is working under temperatures of 500C ± 3 and pressures of 15.2 MPa, which leads to LMP of 20,100 ± 50, the failure probabilities within 50, 70, and 90 years are approximately 0.1 %, 3.2 %, and 17.5 %. The second demonstrated how adjusting the workload can help to protect the integrity of the component. For an old tube reaching 99 % of its lifespan, continuing to run at temperatures of 500C ± 3 and LMP of 20,100 ± 50 leads to a failure probability of about 29.0 % within a year. If the temperature is reduced by 5C, the failure probability can be reduced to 2.5 %, and, if the pressure is also reduced such that the LMP is increased by 100, the failure probability can further be reduced to 0.12 %.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Small Molecule Sorting: A Fluorescence Study of Microemulsions

The application of microemulsions to a wide range of industries relies on their ability to solubilize small molecules with vastly different structures. Herein, we use multiple fluorescence techniques to probe ionic (rhodamine 6g, r6g), polar (coumarin 153, c153), nonpolar (diphenylanthracene, DPA), and amphiphilic (laurdan) small molecules in a nonionic, bicontinuous microemulsion of varying hydration. All fluorophores investigated were found to associate with the surfactant region despite their different structures and properties. The hydration of the surfactant layer was found to increase linearly with water addition, but while this initially increases the fluidity of the surfactant layer, fluorescence anisotropy of c153 and r6g indicates a stiffening of the surfactant at water content >60%. This stiffening of the surfactant layer at higher water content correlates with a morphological change in the microemulsion from a bicontinuous structure to droplets. In contrast, the nonpolar DPA shows a change in partitioning as hydration changes, increasing its association with the oil domain. Altogether, these studies elucidate not only the capability of these microemulsions to host a range of small molecules in the surfactant layer with tunable position but also the ability to probe the driving force of bulk structural changes in these heterogeneous fluids.

25 ENERGY STORAGE↗

The Electron Thermal Conductivity of Pu and Zr Substituted $\mathcal{γ}$-U

Uranium alloys are attractive recycled nuclear fuels because of their high thermal conductivity (𝑘) and fissile density. Limited experimental studies of the 𝑘 of U-Pu-Zr alloys in the range of 15 to 20 wt% Pu and 6 to 15 wt% Zr indicate that increasing the content of either Zr or Pu tends to lower 𝑘. However, which element has the greater effect on 𝑘, and the associated mechanisms, remains unclear. Here, in this study, the electron thermal conductivity (𝑘 𝑒 ) of U-Pu-Zr compositions are calculated using density functional theory. The electronic structure is evaluated to understand the effects of plutonium (Pu) and zirconium (Zr) substitution on the 𝑘 𝑒 of 𝛾-U. Alloys of up to 37.5 at. % Pu and 37.5 at. % Zr are examined. Two methods are applied to calculate 𝑘 𝑒 ; we find that the accuracy of each method depends on the electronic and mass similarities between the solute and solvent atoms. Specifically, when the solute atom is similar in electronic structure and mass, the more accurate method is that which employs the electron relaxation time of 𝛾-U, while if the elements are dissimilar, a mixed method that mixes several parameters associated with JNW_S⁢3033426825100132 from each element in the alloy is best. The introduction of all alloying elements decreases 𝑘 𝑒 ; however, in binary compounds, Pu and Zr have different effects. Pu flattens the electronic bands but compensates for this deleterious effect by increasing electron density near the Fermi level. Zr flattens the electronic bands more severely without adding electron density near the Fermi level. Therefore, Zr decreases 𝑘 𝑒 more than Pu in binary compounds. In ternary compounds, the difference between Pu and Zr is minimal due to the phononic change from the large mass change of Zr substitution, even at 12.5 at. %. Thus, we predict that higher loadings of Pu, and potentially other actinides, can be added to U-Pu-Zr compositions for faster recycling of spent fuel without sacrificing 𝑘. We also note that these 𝑘 𝑒 calculation methods can be applied to non-fuel alloys that require 𝑘 𝑒 predictions, such as cladding, heat exchanger, and structural materials.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hyporheic Exchange Driven by Submerged Rigid Vegetation: A Modeling Study

Flow-vegetation interaction affects fluid flow hydraulics and associated material transport in river corridors. Concomitant changes in pressure within the flow field due to the presence of vegetation may act as a driver for the formation of hyporheic flow across the sediment-water interface. This potentially important process, however, has yet to be studied. In order to investigate vegetation-induced hyporheic exchange, a series of numerical models of interlinked surface-subsurface flow modified by plant stems was conducted. Periodically staggered plant stem arrays on a flat sediment bed were considered within a coupled multiphysics computational fluid dynamics approach. Plants were idealized as rigid cylinders and arranged in different streamwise and spanwise spacing distances. Each vegetation array was then subjected to a broad range of flow Reynolds Numbers (Re). The results showed that hyporheic flow occurs in all conditions with the presence of vegetation. The vegetation-induced hyporheic flux is found to be a function of Re via a power law. The flux increases with interstem space until the space reaches the distance that rigid stems no longer affect the flow structures in the vicinity of each other. Larger intervegetation distances lead to a larger hyporheic zone. A direct comparison with bedforminduced hyporheic flow showed that vegetation can induce higher hyporheic flux through relatively shallower exchange zones. The results of all the simulations were synthesized into predictive models for hyporheic flux, bulk residence time and exchange depth based on drag coefficient, vegetation density, and Reynolds Number.

54 ENVIRONMENTAL SCIENCES↗

Intraspecific variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus

Optimizing crops for synergistic soil carbon (C) sequestration can enhance CO 2 removal in food and bioenergy production systems. Yet, in bioenergy systems, we lack an understanding of how intraspecies variation in plant traits correlates with variation in soil biogeochemistry. This knowledge gap is exacerbated by both the heterogeneity and difficulty of measuring belowground traits. Here, we provide initial observations of C and nutrients in soil and root and stem tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes—established for aboveground biomass-to-biofuels research. Our goal was to explore the value of such field sites for evaluating genotype-specific effects on soil C, which ultimately informs the potential for optimizing bioenergy systems for both aboveground productivity and belowground C storage. To do this, we investigated variation in chemical traits at the scale of individual trees and genotypes and we explored correlations among stem, root, and soil samples. We observed substantial variation in soil chemical properties at the scale of individual trees and specific genotypes. While correlations among elements were observed both within and among sample types (soil, stem, root), above-belowground correlations were generally poor. We did not observe genotype-specific patterns in soil C in the top 10 cm, but we did observe genotype associations with soil acid-base chemistry (soil pH and base cations) and bulk density. Finally, a specific phenotype of interest (high vs low lignin) was unrelated to soil biogeochemistry. Our pilot study supports the usefulness of decade-old, genetically-variable, Populus bioenergy field test plots for understanding plant genotype effects on soil properties. Finally, this study contributes to the advancement of sampling methods and baseline data for Populus systems in the Pacific Northwest, USA. Further species- and region-specific efforts will enhance C predictability across scales in bioenergy systems and, ultimately, accelerate the identification of genotypes that optimize yield and carbon storage.

54 ENVIRONMENTAL SCIENCES↗

Machine learning and shallow groundwater chemistry to identify geothermal prospects in the Great Basin, USA

This study discovers various geothermal prospects in the Great Basin, USA based on shallow groundwater chemical (geochemical) data. The geochemical data are expected to include hidden (latent) information that is a proxy for geothermal prospectivity. We processed the sparse geochemical data in the Great Basin at 14,341 locations including 18 attributes. Next, a non-negative matrix factorization with customized k-means clustering is applied to the geochemical data matrix that automatically finds three hidden geothermal signatures representing modestly, moderately, and highly confident geothermal prospects. The algorithm also evaluated the probability of occurrence of these types of resources through the studied region. There is a consistency between regional geothermal prospectivity as estimated by our ML methodology and the traditional play fairway analysis conducted over a portion of the study area. We also identify the dominant data attributes associated with each signature. Finally, our ML analyses allow us to reconstruct attributes from sparse into continuous over the study domain. The predicted continuous attributes can be used for future detailed geothermal explorations in the Great Basin.

15 GEOTHERMAL ENERGY↗

G protein nucleolar 3 promotes Non-Hodgkin lymphoma progression by activating the Wnt/β-catenin signaling pathway

G protein nucleolar 3 (GNL3), which acts as an oncoprotein in various carcinomas, is associated with tumor progression; however, little is known regarding GNL3 function in non-Hodgkin lymphoma (NHL). In this study, we first used in silico analysis to determine associations between GNL3 and diffuse large B-cell lymphoma (DLBCL). We then examined the effect of GNL3 on NHL progression, including cell proliferation, apoptosis, and cell cycle progression, and determined its underlying molecular mechanism using in vitro lymphoma cell lines and in vivo mouse xenograft models. We found that GNL3 mRNA levels were markedly higher in DLBCL tissues than in normal tissues, with these higher levels associated with poor prognosis. Additionally, GNL3 overexpression promoted NHL cell proliferation and cell cycle progression and reduced apoptosis in vitro, and enhanced tumorigenesis in an in vivo xenograft model. Moreover, we found that GNL3 upregulated the levels of Wnt/β-catenin signaling pathway-related factors and downstream target genes, whereas the opposite result was observed in GNL3-silenced cells. Furthermore, a rescue experiment using a Wnt/β-catenin inhibitor (XAV939) confirmed that GNL3 promotes NHL progression by activating the Wnt/β-catenin signaling pathway. These findings demonstrated that GNL3 functions as an oncogenic driver in NHL via the Wnt/β-catenin pathway.

60 APPLIED LIFE SCIENCES↗

A Bayesian nonparametric analysis for zero-inflated multivariate count data with application to microbiome study

High-throughput sequencing technology has enabled researchers to profile microbial communities from a variety of environments, but analysis of multivariate taxon count data remains challenging. Here, we develop a Bayesian nonparametric (BNP) regression model with zero inflation to analyse multivariate count data from microbiome studies. A BNP approach flexibly models microbial associations with covariates, such as environmental factors and clinical characteristics. The model produces estimates for probability distributions which relate microbial diversity and differential abundance to covariates, and facilitates community comparisons beyond those provided by simple statistical tests. We compare the model to simpler models and popular alternatives in simulation studies, showing, in addition to these additional community-level insights, it yields superior parameter estimates and model fit in various settings. The model's utility is demonstrated by applying it to a chronic wound microbiome data set and a Human Microbiome Project data set, where it is used to compare microbial communities present in different environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multipoint Observations of Dispersive Scale Alfvénic Field‐Line Resonances Associated With Substorm Auroral Beads

We present a case study of the field-aligned current (FAC) systems that transpire within the high-altitude auroral acceleration region of an “auroral bead” initiated double oval substorm observed on 23 February 2001 by the Cluster fleet. Conjunctive Cluster measurements and auroral images from IMAGE reveal that auroral bead current system formation and evolution is a multi-scale, injection-mediated process. The FACs at large scales vary on substorm evolution time scales (~minutes) in response to the injection and evolution of hotter denser magnetospheric plasma. Embedded within the large-scale FACs are intense short-scale (≲ few 10s of km) currents comprising dispersive scale Alfvén wave (DAW) fluctuations. The DAWs are a complex mixture of ingoing and reflected components that regularly interfere to form a broad spectrum of kinetic (dispersive) scale Alfvénic field-line resonances (KFLRs). The Alfvénic currents appear as a nested series of upward and downward FAC densities with amplitudes reaching a few 100 nA/m 2 . Energized field-aligned or counterstreaming electrons near keV energies and below are observed with parallel skews that vary in concert with variations in the DAW current sense. Positive correlations between DAW electric field energy densities and the energies of energized H + , He + , and O + outflow are observed, indicative of ion energization within the DAW fields. Due to their L-shell location (L~5.8–7.0) and associations with injections, the KFLRs are interpreted as the high-altitude auroral zone analog of KFLRs observed in the equatorial inner magnetosphere.

79 ASTRONOMY AND ASTROPHYSICS↗

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system. Methods: We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ) and ground-level ozone (O 3 ), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ longterm exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage. Results: Among the 151105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM 2.5 (1.70 µg/m 3 ), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO 2 . We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O 3 for hospital admission, ICU admission and death, respectively.

60 APPLIED LIFE SCIENCES↗

YAP1 Dysfunction Promotes Molecular Properties Linked to Breast Cancer Susceptibility

YAP1 is a cotranscription factor that promotes malignant and stem cell properties in cancer. We previously found that YAP1 dysregulation is associated with aging in human mammary epithelia. With increased age, YAP1 expression changes in luminal epithelial cells, the prospective breast cancer cell of origin. Because age is a significant risk factor for breast cancer, we tested whether YAP1 dysregulation acted early in cancer progression by conferring cellular states associated with increased cancer susceptibility. In this study, we find that with increased age and genetic risk for developing cancer, human breast tissues showed significantly increased YAP1 expression, and cultured primary human mammary epithelial cells (HMEC) showed significantly increased expression of both YAP1 and its transcriptional targets. Increased YAP1 expression in cultured HMEC induced gene expression changes associated with increased cancer susceptibility, such as genes associated with stem cell states, increased telomerase activity, breast cancer progression, and increased age and genetic breast cancer risk. Furthermore, overexpression of YAP1 in post-stasis HMEC—finite lifespan cells that have bypassed a retinoblastoma-mediated senescence barrier—promoted properties related to increased growth potential. We found that YAP1 dysregulation in finite epithelial cells allows for access to gene programs and functions that are typically thought to be restricted to stem cells. We hypothesize that YAP1 acts early in breast cancer progression, long before the development of a tumor, to impose cancer-susceptible molecular states.

YAP1↗

Willingness to Receive mHealth Services Among Patients with Diabetes on Chronic Follow-up in Public Hospitals in Eastern Ethiopia: Multicenter Mixed-Method Study

Background: Management of diabetes requires a long-term care strategy, including support for adherence to a healthy lifestyle and treatment. Exploring the willingness of patients with diabetes to receive mHealth services is essential for designing efficient and effective services. This study aimedto determine willingness to receive mHealth services and associated factors, as well as explore the barriers to receive mHealth services among patients with diabetes. Methods: A multicenter mixed-method study was employed from September 1 to November 30, 2022. For the quantitative part, a total of 365 patients with diabetes receiving chronic follow-up at three public hospitals were enrolled. Data were gathered using structured questionnaires administered by interviewers, entered into Epi-data version 4.6, and analyzed using Stata version 17. A binary and multivariable logistic regression model was computed to identify the associated factors. For qualitative, eight key informants and seven in-depth interviews were conducted. After verbatim transcription and translation, the data were thematically analyzed using ATLAS.ti V. 7.5. Results: Overall, 77.3% had access to a mobile phone, and 74.5% of them were willing to receive mHealth services. Higher odds of willingness to receive mHealth services were reported among patients with an age below 35 years [AOR = 4.11 (1.15– 14.71)], attended formal education [AOR = 2.63 (1.19– 5.77)], without comorbidity [AOR = 3.6 (1.54– 8.41)], < 1-hour travel to reach a health facility [AOR = 3.57 (1.03– 12.36)], answered unknown calls [AOR = 2.3 (1.04– 5.13)], and were satisfied with health-care provider service [AOR = 2.44 (1.04– 5.72)]. In the qualitative part, infrastructure, health facilities, socioeconomic factors, and patients’ behavioral factors were major identified barriers to receiving mHealth services. Conclusion: In this study, the willingness to receive mHealth services for those who have access to mobile phones increased. Additionally, the study highlighted common barriers to receiving mHealth services.

60 APPLIED LIFE SCIENCES↗

Noise Optimization for MKIDs with Different Design Geometries and Material Selections

The separation and optimization of noise components is critical to microwave-kinetic inductance detector (MKID) development. We analyze the effect of several changes to the lumped-element inductor and interdigitated capacitor geometry on the noise performance of a series of MKIDs intended for millimeter-wavelength experiments. We extract the contributions from two-level system noise in the dielectric layer, the generation-recombination noise intrinsic to the superconducting thin-film, and system white noise from each detector noise power spectrum and characterize how these noise components depend on detector geometry, material, and measurement conditions such as driving power and temperature. We observe a reduction in the amplitude of two-level system noise with both an elevated sample temperature and an increased gap between the fingers within the interdigitated capacitors for both aluminum and niobium detectors. We also verify the expected reduction of the generation-recombination noise and associated quasiparticle lifetime with reduced inductor volume. This study also iterates over different materials, including aluminum, niobium, and aluminum manganese, and compares the results with an underlying physical model.

generation-recombination noise↗