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At least 55 records · Page 3

Real-Time Quantitative Analysis of H2, He, O2, and Ar by Quadrupole Ion Trap Mass Spectrometry

The use of a quadrupole ion trap mass spectrometer for quantitative analysis of hydrogen and helium as well as other permanent gases is demonstrated. The customized instrument utilizes the mass selective instability mode of mass analysis as with commercial instruments; however, this instrument operates at a greater RF trapping frequency and without a buffer gas. With these differences, a useable mass range from 2 to over 50 Da is achieved, as required by NASA for monitoring the Space Shuttle during a launch countdown. The performance of the ion trap is evaluated using part-per-million concentrations of hydrogen, helium, oxygen and argon mixed into a nitrogen gas stream. Relative accuracy and precision when quantitating the four analytes were better than the NASA-required minimum of 10% error and 5% deviation, respectively. Limits of detection were below the NASA requirement of 25-ppm hydrogen and 100-ppm helium; those for oxygen and argon were slightly higher than the requirement. The instrument provided adequate performance at fast data recording rates, demonstrating the utility of an ion trap mass spectrometer as a real-time quantitative monitoring device for permanent gas analysis.

Ottens, Andrew K.

A Quantitative Study of Oxygen as a Metabolic Regulator

An acute reduction in oxygen (O2) delivery to a tissue is generally associated with a decrease in phosphocreatine, increases in ADP, NADH/NAD, and inorganic phosphate, increased rates of glycolysis and lactate production, and reduced rates of pyruvate and fatty acid oxidation. However, given the complexity of the human bioenergetic system and its components, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). Of special interest is the determination of mechanisms relating tissue oxygenation to observed metabolic responses at the tissue, organ, and whole body levels and the quantification of how changes in tissue O2 availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study, we extend a previously developed mathematical model of human bioenergetics to provide a physicochemical framework that permits quantitative understanding of O2 as a metabolic regulator. Specifically, the enhancement permits studying the effects of variations in tissue oxygenation and in parameters controlling the rate of cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The whole body is described as a bioenergetic system consisting of metabolically distinct tissue/organ subsystems that exchange materials with the blood. In order to study the dynamic response of each subsystem to stimuli, we solve the ordinary differential equations describing the temporal evolution of metabolite levels, given the initial concentrations. The solver used in the present study is the packaged code LSODE, as implemented in the NASA Lewis kinetics and sensitivity analysis code, LSENS. A major advantage of LSENS is the efficient procedures supporting systematic sensitivity analysis, which provides the basic methods for studying parameter sensitivities (i.e., changes in model behavior due to parameter variation). Sensitivity analysis establishes relationships between model predictions and problem parameters (i.e., initial concentrations, rate coefficients, etc). It helps determine the effects of uncertainties or changes in these input parameters on the predictions, which ultimately are compared with experimental observations in order to validate the model. Sensitivity analysis can identify parameters that must be determined accurately because of their large effect on the model predictions and parameters that need not be known with great precision because they have little or no effect on the solution. This capability may prove to be important in optimizing the design of experiments, thereby reducing the use of animals. This approach can be applied to study the metabolic effects of reduced oxygen delivery to cardiac muscle due to local myocardial ischemia and the effects of acute hypoxia on brain metabolism. Other important applications of sensitivity analysis include identification of quantitatively relevant pathways and biochemical species within an overall mechanism, when examining the effects of a genetic anomaly or pathological state on energetic system components and whole system behavior.

Radhakrishnan, Krishnan

Quantitative molecular characterization of bovine vitreous and lens with non-invasive dynamic light scattering

The non-invasive technique of dynamic light scattering (DLS) was used to quantitatively characterize vitreous and lens structure on a molecular level by measuring the sizes of the predominant particles and mapping the three-dimensional topographic distribution of these structural macromolecules in three spatial dimensions. The results of DLS measurements in five fresh adult bovine eyes were compared to DLS measurements in model solutions of hyaluronan (HA) and collagen (Coll). In the bovine eyes DLS measurements were obtained from excised samples of gel and liquid vitreous and compared to the model solutions. Measurements in whole vitreous were obtained at multiple points posterior to the lens to generate a three-dimensional 'map' of molecular structure. The macromolecule distribution in bovine lens was similarly characterized.In each bovine vitreous (Bo Vit) specimen, DLS predominantly detected two distinct particles, which differed in diffusion properties and hence size. Comparisons with model vitreous solutions demonstrated that these most likely corresponded to the Coll and HA components of vitreous. Three-dimensional mapping of Bo Vit found heterogeneity throughout the vitreous body, with different particle size distributions for Coll and HA at different loci. In contrast, the three-dimensional distribution of lens macromolecules was more homogeneous. Thus, the non-invasive DLS technique can quantitate the average sizes of vitreous and lens macromolecules and map their three-dimensional distribution. This method to assess quantitatively the macromolecular structure of vitreous and lens should be useful for clinical as well as experimental applications in health and disease. Copyright 2001 Academic Press.

Models, Molecular

The value of assessing pulmonary venous flow velocity for predicting severity of mitral regurgitation: A quantitative assessment integrating left ventricular function

Although alteration in pulmonary venous flow has been reported to relate to mitral regurgitant severity, it is also known to vary with left ventricular (LV) systolic and diastolic dysfunction. There are few data relating pulmonary venous flow to quantitative indexes of mitral regurgitation (MR). The object of this study was to assess quantitatively the accuracy of pulmonary venous flow for predicting MR severity by using transesophageal echocardiographic measurement in patients with variable LV dysfunction. This study consisted of 73 patients undergoing heart surgery with mild to severe MR. Regurgitant orifice area (ROA), regurgitant stroke volume (RSV), and regurgitant fraction (RF) were obtained by quantitative transesophageal echocardiography and proximal isovelocity surface area. Both left and right upper pulmonary venous flow velocities were recorded and their patterns classified by the ratio of systolic to diastolic velocity: normal (>/=1), blunted (<1), and systolic reversal (<0). Twenty-three percent of patients had discordant patterns between the left and right veins. When the most abnormal patterns either in the left or right vein were used for analysis, the ratio of peak systolic to diastolic flow velocity was negatively correlated with ROA (r = -0.74, P <.001), RSV (r = -0.70, P <.001), and RF (r = -0.66, P <.001) calculated by the Doppler thermodilution method; values were r = -0.70, r = -0.67, and r = -0.57, respectively (all P <.001), for indexes calculated by the proximal isovelocity surface area method. The sensitivity, specificity, and predictive values of the reversed pulmonary venous flow pattern for detecting a large ROA (>0.3 cm(2)) were 69%, 98%, and 97%, respectively. The sensitivity, specificity, and predictive values of the normal pulmonary venous flow pattern for detecting a small ROA (<0.3 cm(2)) were 60%, 96%, and 94%, respectively. However, the blunted pattern had low sensitivity (22%), specificity (61%), and predictive values (30%) for detecting ROA of greater than 0.3 cm(2) with significant overlap with the reversed and normal patterns. Among patients with the blunted pattern, the correlation between the systolic to diastolic velocity ratio was worse in those with LV dysfunction (ejection fraction <50%, r = 0.23, P >.05) than in those with normal LV function (r = -0.57, P <.05). Stepwise linear regression analysis showed that the peak systolic to diastolic velocity ratio was independently correlated with RF (P <.001) and effective stroke volume (P <.01), with a multiple correlation coefficient of 0.71 (P <.001). In conclusion, reversed pulmonary venous flow in systole is a highly specific and reliable marker of moderately severe or severe MR with an ROA greater than 0.3 cm(2), whereas the normal pattern accurately predicts mild to moderate MR. Blunted pulmonary venous flow can be seen in all grades of MR with low predictive value for severity of MR, especially in the presence of LV dysfunction. The blunted pulmonary venous flow pattern must therefore be interpreted cautiously in clinical practice as a marker for severity of MR.

Non-NASA Center

Assessment of metabolic bone diseases by quantitative computed tomography

Advances in the radiologic sciences have permitted the development of numerous noninvasive techniques for measuring the mineral content of bone, with varying degrees of precision, accuracy, and sensitivity. The techniques of standard radiography, radiogrammetry, photodensitometry, Compton scattering, neutron activation analysis, single and dual photon absorptiometry, and quantitative computed tomography (QCT) are described and reviewed in depth. Results from previous cross-sectional and longitudinal QCT investigations are given. They then describe a current investigation in which they studied 269 subjects, including 173 normal women, 34 patients with hyperparathyroidism, 24 patients with steroid-induced osteoporosis, and 38 men with idiopathic osteoporosis. Spinal quantitative computed tomography, radiogrammetry, and single photon absorptiometry were performed, and a spinal fracture index was calculated on all patients. The authors found a disproportionate loss of spinal trabecular mineral compared to appendicular mineral in the men with idiopathic osteoporosis and the patients with steroid-induced osteoporosis. They observed roughly equivalent mineral loss in both the appendicular and axial regions in the hyperparathyroid patients. The appendicular cortical measurements correlated moderately well with each other but less well with spinal trabecular QCT. The spinal fracture index correlated well with QCT and less well with the appendicular measurements. Knowledge of appendicular cortical mineral status is important in its own right but is not a valid predictor of axial trabecular mineral status, which may be disproportionately decreased in certain diseases. Quantitative CT provides a reliable means of assessing the latter region of the skeleton, correlates well with the spinal fracture index (a semiquantitative measurement of end-organ failure), and offers the clinician a sensitive means of following the effects of therapy.

Minerals/analysis

A Quantitative Approach to Assessing System Evolvability

When selecting a system from multiple candidates, the customer seeks the one that best meets his or her needs. Recently the desire for evolvable systems has become more important and engineers are striving to develop systems that accommodate this need. In response to this search for evolvability, we present a historical perspective on evolvability, propose a refined definition of evolvability, and develop a quantitative method for measuring this property. We address this quantitative methodology from both a theoretical and practical perspective. This quantitative model is then applied to the problem of evolving a lunar mission to a Mars mission as a case study.

Christian, John A., III

Applying Qualitative Hazard Analysis to Support Quantitative Safety Analysis for Proposed Reduced Wake Separation Conops

This paper describes a scenario-driven hazard analysis process to identify, eliminate, and control safety-related risks. Within this process, we develop selective criteria to determine the applicability of applying engineering modeling to hypothesized hazard scenarios. This provides a basis for evaluating and prioritizing the scenarios as candidates for further quantitative analysis. We have applied this methodology to proposed concepts of operations for reduced wake separation for closely spaced parallel runways. For arrivals, the process identified 43 core hazard scenarios. Of these, we classified 12 as appropriate for further quantitative modeling, 24 that should be mitigated through controls, recommendations, and / or procedures (that is, scenarios not appropriate for quantitative modeling), and 7 that have the lowest priority for further analysis.

Shortle, John F.

Assessment and Mission Planning Capability For Quantitative Aerothermodynamic Flight Measurements Using Remote Imaging

High resolution calibrated infrared imagery of vehicles during hypervelocity atmospheric entry or sustained hypersonic cruise has the potential to provide flight data on the distribution of surface temperature and the state of the airflow over the vehicle. In the early 1980 s NASA sought to obtain high spatial resolution infrared imagery of the Shuttle during entry. Despite mission execution with a technically rigorous pre-planning capability, the single airborne optical system for this attempt was considered developmental and the scientific return was marginal. In 2005 the Space Shuttle Program again sponsored an effort to obtain imagery of the Orbiter. Imaging requirements were targeted towards Shuttle ascent; companion requirements for entry did not exist. The engineering community was allowed to define observation goals and incrementally demonstrate key elements of a quantitative spatially resolved measurement capability over a series of flights. These imaging opportunities were extremely beneficial and clearly demonstrated capability to capture infrared imagery with mature and operational assets of the US Navy and the Missile Defense Agency. While successful, the usefulness of the imagery was, from an engineering perspective, limited. These limitations were mainly associated with uncertainties regarding operational aspects of data acquisition. These uncertainties, in turn, came about because of limited pre-flight mission planning capability, a poor understanding of several factors including the infrared signature of the Shuttle, optical hardware limitations, atmospheric effects and detector response characteristics. Operational details of sensor configuration such as detector integration time and tracking system algorithms were carried out ad hoc (best practices) which led to low probability of target acquisition and detector saturation. Leveraging from the qualified success during Return-to-Flight, the NASA Engineering and Safety Center sponsored an assessment study focused on increasing the probability of returning spatially resolved scientific/engineering thermal imagery. This paper provides an overview of the assessment task and the systematic approach designed to establish confidence in the ability of existing assets to reliably acquire, track and return global quantitative surface temperatures of the Shuttle during entry. A discussion of capability demonstration in support of a potential Shuttle boundary layer transition flight test is presented. Successful demonstration of a quantitative, spatially resolved, global temperature measurement on the proposed Shuttle boundary layer transition flight test could lead to potential future applications with hypersonic flight test programs within the USAF and DARPA along with flight test opportunities supporting NASA s project Constellation.

Horvath, Thomas

Satellite Contributions to the Quantitative Characterization of Biomass Burning for Climate Modeling

Characterization of biomass burning from space has been the subject of an extensive body of literature published over the last few decades. Given the importance of this topic, we review how satellite observations contribute toward improving the representation of biomass burning quantitatively in climate and air-quality modeling and assessment. Satellite observations related to biomass burning may be classified into five broad categories: (i) active fire location and energy release, (ii) burned areas and burn severity, (iii) smoke plume physical disposition, (iv) aerosol distribution and particle properties, and (v) trace gas concentrations. Each of these categories involves multiple parameters used in characterizing specific aspects of the biomass-burning phenomenon. Some of the parameters are merely qualitative, whereas others are quantitative, although all are essential for improving the scientific understanding of the overall distribution (both spatial and temporal) and impacts of biomass burning. Some of the qualitative satellite datasets, such as fire locations, aerosol index, and gas estimates have fairly long-term records. They date back as far as the 1970s, following the launches of the DMSP, Landsat, NOAA, and Nimbus series of earth observation satellites. Although there were additional satellite launches in the 1980s and 1990s, space-based retrieval of quantitative biomass burning data products began in earnest following the launch of Terra in December 1999. Starting in 2000, fire radiative power, aerosol optical thickness and particle properties over land, smoke plume injection height and profile, and essential trace gas concentrations at improved resolutions became available. The 2000s also saw a large list of other new satellite launches, including Aqua, Aura, Envisat, Parasol, and CALIPSO, carrying a host of sophisticated instruments providing high quality measurements of parameters related to biomass burning and other phenomena. These improved data products have enabled significant progress in the study of biomass burning from space. However, appreciable uncertainty remains in many of the measurements that still needs to be addressed. Nevertheless, climate and other atmospheric models are

Ichoku, Charles

Application of Fault Management Theory to the Quantitative Selection of a Launch Vehicle Abort Trigger Suite

The theory of System Health Management (SHM) and of its operational subset Fault Management (FM) states that FM is implemented as a "meta" control loop, known as an FM Control Loop (FMCL). The FMCL detects that all or part of a system is now failed, or in the future will fail (that is, cannot be controlled within acceptable limits to achieve its objectives), and takes a control action (a response) to return the system to a controllable state. In terms of control theory, the effectiveness of each FMCL is estimated based on its ability to correctly estimate the system state, and on the speed of its response to the current or impending failure effects. This paper describes how this theory has been successfully applied on the National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program to quantitatively estimate the effectiveness of proposed abort triggers so as to select the most effective suite to protect the astronauts from catastrophic failure of the SLS. The premise behind this process is to be able to quantitatively provide the value versus risk trade‐off for any given abort trigger, allowing decision makers to make more informed decisions. All current and planned crewed launch vehicles have some form of vehicle health management system integrated with an emergency launch abort system to ensure crew safety. While the design can vary, the underlying principle is the same: detect imminent catastrophic vehicle failure, initiate launch abort, and extract the crew to safety. Abort triggers are the detection mechanisms that identify that a catastrophic launch vehicle failure is occurring or is imminent and cause the initiation of a notification to the crew vehicle that the escape system must be activated. While ensuring that the abort triggers provide this function, designers must also ensure that the abort triggers do not signal that a catastrophic failure is imminent when in fact the launch vehicle can successfully achieve orbit. That is, the abort triggers must have low false negative rates to be sure that real crew‐threatening failures are detected, and also low false positive rates to ensure that the crew does not abort from non‐crew‐threatening launch vehicle behaviors. The analysis process described in this paper is a compilation of over six years of lessons learned and refinements from experiences developing abort triggers for NASA's Constellation Program (Ares I Project) and the SLS Program, as well as the simultaneous development of SHM/FM theory. The paper will describe the abort analysis concepts and process, developed in conjunction with SLS Safety and Mission Assurance (S&MA) to define a common set of mission phase, failure scenario, and Loss of Mission Environment (LOME) combinations upon which the SLS Loss of Mission (LOM) Probabilistic Risk Assessment (PRA) models are built. This abort analysis also requires strong coordination with the Multi‐Purpose Crew Vehicle (MPCV) and SLS Structures and Environments (STE) to formulate a series of abortability tables that encapsulate explosion dynamics over the ascent mission phase. The design and assessment of abort conditions and triggers to estimate their Loss of Crew (LOC) Benefits also requires in‐depth integration with other groups, including Avionics, Guidance, Navigation and Control(GN&C), the Crew Office, Mission Operations, and Ground Systems. The outputs of this analysis are a critical input to SLS S&MA's LOC PRA models. The process described here may well be the first full quantitative application of SHM/FM theory to the selection of a sensor suite for any aerospace system.

Lo, Yunnhon

Quantitative Technology Assessment in Space Mission Analysis

New technologies will need to be developed to create feasible concepts for NASA's ambitious missions of the future, but quantitative assessments of the impacts that technologies have on systems or architectures are sporadic and often inadequate. The Space Mission Analysis Branch at NASA's Langley Research Center is developing a quantitative technology assessment framework to address this issue with a vision of being able to understand the mission and system architecture impacts of technology development activities. A phased approach is being pursued to answer technology needs assessment and technology forecasting questions. First, the integration of subject matter experts, data collection, and data analysis techniques ensures that the framework is accessible and analyzable. Second, systems analysis determines the impact of key technologies from the first phase on systems, architectures, and campaigns. The goal of a quantitative technology assessment framework is to accelerate technology assessments, to improve the accuracy of those assessments, and to provide deeper insights into the impact of new technologies. Keywords: technology assessment, data analysis, systems analysis.

Arney, Dale C.

Quantitative x-ray scattering of free molecules

Advances in x-ray free electron lasers have made ultrafast scattering a powerful method for investigating molecular reaction kinetics and dynamics. Accurate measurement of the ground-state, static scattering signals of the reacting molecules is pivotal for these pump-probe x-ray scattering experiments as they are the cornerstone for interpreting the observed structural dynamics. Here, this article presents a data calibration procedure, designed for gas-phase x-ray scattering experiments conducted at the Linac Coherent Light Source x-ray Free-Electron Laser at SLAC National Accelerator Laboratory, that makes it possible to derive a quantitative dependence of the scattering signal on the scattering vector. A self-calibration algorithm that optimizes the detector position without reference to a computed pattern is introduced. Angle-of-scattering corrections that account for several small experimental non-idealities are reported. Their implementation leads to near quantitative agreement with theoretical scattering patterns calculated with ab-initio methods as illustrated for two x-ray photon energies and several molecular test systems.

74 ATOMIC AND MOLECULAR PHYSICS

Computational Methods for Modeling Electrospray Microdroplet Chemistry for Improved Quantitative Mass Spectrometry

This project aimed at enhancing the quantitative analysis capabilities of electrospray ionization mass spectrometry (ESI-MS) by developing advanced computational methods. The primary focus was to integrate continuum and molecular dynamics simulations to study the behavior of microdroplets in the ESI process, from formation to evaporation. Through this research, we sought to bridge significant length and time scales to provide a comprehensive understanding of how analyte concentrations evolve from bulk solutions into gas-phase ions. This understanding is crucial for addressing challenges such as ionization efficiency, solvent effects, and ion suppression, which currently limit the accuracy of quantitative ESI-MS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Quantitative Diagnosis of Continuous-Valued, Stead-State Systems

Quantitative diagnosis involves numerically estimating the values of unobservable parameters that best explain the observed parameter values. We consider quantitative diagnosis for continuous, lumped- parameter, steady-state physical systems because such models are easy to construct and the diagnosis problem is considerably simpler than that for corresponding dynamic models. To further tackle the difficulties of numerically inverting a simulation model to compute a diagnosis, we propose to decompose a physical system model in terms of feedback loops. This decomposition reduces the dimension of the problem and consequently decreases the diagnosis search space. We illustrate this approach on a model of thermal control system studied in earlier research.

Quantitative Diagnosis

Development Status of the WetLab-2 Project: New Tools for On-orbit Real-time Quantitative Gene Expression.

The primary objective of NASA Ames Research Centers WetLab-2 Project is to place on the ISS a research platform to facilitate gene expression analysis via quantitative real-time PCR (qRT-PCR) of biological specimens grown or cultured on orbit. The WetLab-2 equipment will be capable of processing multiple sample types ranging from microbial cultures to animal tissues dissected on-orbit. In addition to the logistical benefits of in-situ sample processing and analysis, conducting qRT-PCR on-orbit eliminates the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms. The system can also validate terrestrial analyses of samples returned from ISS by providing quantitative on-orbit gene expression benchmarking prior to sample return. The ability to get on orbit data will provide investigators with the opportunity to adjust experimental parameters for subsequent trials based on the real-time data analysis without need for sample return and re-flight. Finally, WetLab-2 can be used for analysis of air, surface, water, and clinical samples to monitor environmental contaminants and crew health. The verification flight of the instrument is scheduled to launch on SpaceX-5 in Aug. 2014.Progress to date: The WetLab-2 project completed a thorough study of commercially available qRT-PCR systems and performed a downselect based on both scientific and engineering requirements. The selected instrument, the Cepheid SmartCycler, has advantages including modular design (16 independent PCR modules), low power consumption, and rapid ramp times. The SmartCycler has multiplex capabilities, assaying up to four genes of interest in each of the 16 modules. The WetLab-2 team is currently working with Cepheid to modify the unit for housing within an EXPRESS rack locker on the ISS. This will enable the downlink of data to the ground and provide uplink capabilities for programming, commanding, monitoring, and instrument maintenance. The project is currently designing a module that will lyse the cells and extract RNA of sufficient quality for use in qRT-PCR reactions while using a housekeeping gene to normalize RNA concentration and integrity. Current testing focuses on two promising commercial products and chemistries that allow for RNA extraction with minimal complexity and crew time.

quantitative PCR

Quantitative Identification of Dopant Occupation in Li‐Rich Cathodes

Elemental doping is widely used to improve the performance of cathode materials in lithium‐ion batteries. However, macroscopic/statistical investigation on how doping sites are distributed in the material lattice, despite being a key prerequisite for understanding and manipulating the doping effect, has not been effectively established. Herein, to solve this predicament, a universal strategy is proposed to quantitatively identify the locations of Al and Mg dopants in lithium‐rich layered oxides (LLOs). Solid evidence confirms that Al prefers to occupy the transition metal (TM) layer, while Mg evenly occupies both TM and Li layers. As a result, Mg significantly reduces the thickness of LiO 2 slabs at room temperature, which will increase the energy barrier of oxygen activation and enhance the structure stability of LLOs. The suppressed oxygen activity in Mg‐doped LLO can be kinetically unlocked at 55 °C. The different characteristics of Al and Mg enlighten an Al/Mg co‐doping strategy to optimize LLOs, which significantly improves the cycle performance while lifting the capacity. In conclusion, these insights from the quantitative identification of doping sites shed light on the manipulation of doping effects toward better cathodes.

25 ENERGY STORAGE

A Machine Learning Approach to Quantitative Analysis of Enamel Microstructure from Scanning Electron Microscopy Images

Dental enamel, the outermost tissue of mammalian teeth, must withstand a lifetime of wear and cyclic contact. To meet this demand, enamel possesses a combination of high hardness and resistance to fracture, properties that are typically mutually exclusive. The impressive damage tolerance has been attributed largely to decussation of the enamel rods, the principal unit of its microstructure. As such, enamel is inspiring the design of next‐generation structural materials. However, quantitative descriptions of the decussated enamel rod microstructure remain limited due to challenges encountered in applying computed tomography and in acquiring quality images appropriate for traditional digital processing methods. Here, a machine learning segmentation method is applied to images of the enamel obtained using scanning electron microscopy to support quantitative analysis of the microstructure. A pretrained convolutional neural network is used to expand the input training image dataset to allow the training of a random forest classifier, which ultimately segments the image with a very small training set ( n = 3 images). A validation of this segmentation method is presented, in addition to its application to calculate relevant microstructural parameters for images of tooth enamel from selected mammalian species. The methodology applied here is equally applicable to other hard tissues.

36 MATERIALS SCIENCE

Fabrication of porous transport electrodes: Development of quantitative approach for quality control

This work focuses on porous transport electrodes (PTEs), which integrate the anodic catalyst with the adjacent Ti porous transport layer (PTL). Challenges in catalyst deposition on PTLs, particularly at low loadings, motivated this study to evaluate various fabrication methods and characterization approaches. This work investigated Pt-treated PTLs coated with Ir-based catalysts using several common methods, including airbrush coating, rod coating, ultrasonic spray coating, electrodeposition, and sputter deposition, with catalyst loadings ranging from 2.9 to 0.1 mg/cm 2 , providing the opportunity for comparisons across a large set of samples produced by different methods. Two widely accessible characterization techniques: X-ray computed tomography (XCT) and scanning electron microscopy energy dispersive X-ray spectroscopy (SEM-EDS) were explored. Initial evaluation of selected samples with XCT provided qualitative insights into catalyst distribution, however comprehensive quantitative analysis was limited. SEM-EDS enabled detailed information on the catalyst distribution both qualitatively and quantitatively using two metrics. Atomic and surface area % ratios of Pt:Ir and Ti:Ir revealed trends in catalyst loading and losses into the PTL pores, as well as evaluating the homogeneity of catalyst coatings. The analysis demonstrated that ultrasonic spray coating, electrodeposition, and sputter coating produced the most homogeneous coatings, with minimal catalyst losses observed for electrodeposition and sputter coating. By adapting common techniques with novel, standardized methodologies, this work establishes a universally applicable framework for cross-study comparison of PTEs. The SEM-EDS approach provides a practical, accessible tool for PTE characterization and contributes a reference dataset supporting both research development and rapid quality control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH