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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Nanoscale Mechanical Behavior of Nuclear Materials

One of the primary performance objectives targeted for improved performance of nuclear fuels is fracture toughness. New materials or composite fuel architectures that offer greater resistance to cracking under the extreme environments encountered during nuclear reactor service would provide significant improvements to steady state (e.g. heat transfer, fuel redistribution) and transient (e.g. radionuclide release at elevated temperatures) conditions. Options currently under investigation include 'nontraditional' nuclear fuels designated around high uranium density. These include uranium silicides, uranium borides, and composite fuel materials constructed of these and uranium nitride or uranium dioxide. The increase uranium density compared with uranium dioxide (UO{sub 2}) has made them interesting to a new generation of nuclear fuels research driven by the renewed push for accident-tolerant light water reactor (LWR) fuels. Measurement of the thermophysical and thermodynamic properties of these constituent materials has progressed in recent years, but evaluation of mechanical properties at relevant temperatures is necessary to support further evaluations. While thermophysical properties such as thermal conductivity, heat capacity, and thermal expansion are generally the primary properties of interest, mechanical properties will play an important role in governing the deformation and fracture of the fuel during both normal operation and potential transients. It is therefore necessary to develop techniques capable of measuring these properties to predict the response of a candidate fuel form to anticipated thermal gradients. Nanoindentation techniques provide a demonstrated alternative to traditional mechanical test methods. Much work has also been carried out over the past few years to obtain stress-strain curves using a spherical nanoindentation approach. The techniques are expected to be useful for measurement of the mechanical properties of local structure of various materials. Nanomechanical test techniques have particular value in the area of nuclear materials, where numerous factors motivate limiting the sample volume to the extent possible. However, few attempts at application of nanoindentation to evaluate the mechanical properties of the nuclear fuels and cladding materials are reported in the literature. The effect of a limited set of variables (e.g. porosity, temperature dependence) on the mechanical properties of UO{sub 2} has been explored using early nanomechanical testing techniques. However, nanomechanical evaluation has not been extended to other nuclear fuels. In this work, we demonstrate the effectiveness of using instrumented spherical nanoindentation test techniques to capture the mechanical response of regions within individual grains in ion-irradiated W and Zr over a range of ion-irradiation conditions. As well as the nanomechanical response of U-Si and UO{sub 2} fuel materials Nanoindentation results obtained at room temperature will be used to express nano- and bulk- mechanical properties as a function of material stoichiometry. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2012

MISR Observations of Etna Volcanic Plumes

In the last twelve years, Mt. Etna, located in eastern Sicily, has produced a great number of explosive eruptions. Volcanic plumes have risen to several km above sea level and created problems for aviation and the communities living near the volcano. A reduction of hazards may be accomplished using remote sensing techniques to evaluate important features of volcanic plumes. Since 2000, the Multiangle Imaging SpectroRadiometer (MISR) on board NASA s Terra spacecraft has been extensively used to study aerosol dispersal and to extract the three-dimensional structure of plumes coming from anthropogenic or natural sources, including volcanoes. In the present work, MISR data from several explosive events occurring at Etna are analyzed using a program named MINX (MISR INteractive eXplorer). MINX uses stereo matching techniques to evaluate the height of the volcanic aerosol with a precision of a few hundred meters, and extracts aerosol properties from the MISR Standard products. We analyzed twenty volcanic plumes produced during the 2000, 2001, 2002-03, 2006 and 2008 Etna eruptions, finding that volcanic aerosol dispersal and column height obtained by this analysis is in good agreement with ground-based observations. MISR aerosol type retrievals: (1) clearly distinguish volcanic plumes that are sulphate and/or water vapor dominated from ash-dominated ones; (2) detect even low concentrations of volcanic ash in the atmosphere; (3) demonstrate that sulphate and/or water vapor dominated plumes consist of smaller-sized particles compared to ash plumes. This work highlights the potential of MISR to detect important volcanic plume characteristics that can be used to constrain the eruption source parameters in volcanic ash dispersion models. Further, the possibility of discriminating sulphate and/or water vapor dominated plumes from ash-dominated ones is important to better understand the atmospheric impact of these plumes.

Scollo, S.↗
NASA NTRS2003

Flightweight Carbon Nanotube Magnet Technology

Virtually all plasma-based systems for advanced airborne/spaceborne propulsion and power depend upon the future availability of flightweight magnet technology. Unfortunately, current technology for resistive and superconducting magnets yields system weights that tend to counteract the performance advantages normally associated with advanced plasma-based concepts. The ongoing nanotechnology revolution and the continuing development of carbon nanotubes (CNT), however, may ultimately relieve this limitation in the near future. Projections based on recent research indicate that CNTs may achieve current densities at least three orders of magnitude larger than known superconductors and mechanical strength two orders of magnitude larger than steel. In fact, some published work suggests that CNTs are superconductors. Such attributes imply a dramatic increase in magnet performance-to-weight ratio and offer real hope for the construction of true flightweight magnets. This Technical Publication reviews the technology status of CNTs with respect to potential magnet applications and discusses potential techniques for using CNT wires and ropes as a winding material and as an integral component of the containment structure. The technology shortfalls are identified and a research and technology strategy is described that addresses the following major issues: (1) Investigation and verification of mechanical and electrical properties, (2) development of tools for manipulation and fabrication on the nanoscale, (3) continuum/molecular dynamics analysis of nanotube behavior when exposed to practical bending and twisting loads, and (4) exploration of innovative magnet fabrication techniques that exploit the natural attributes of CNTs.

Chapman, J. N.↗
DOE OSTI2018

Diamond anvil cell behavior up to 4 Mbar

The diamond anvil cell (DAC) is considered one of the dominant devices to generate ultrahigh static pressure. The development of the DAC technique has enabled researchers to explore rich high-pressure science in the multimegabar pressure range. Here, we investigated the behavior of the DAC up to 400 GPa, which is the accepted pressure limit of a conventional DAC. By using a submicrometer synchrotron X-ray beam, double cuppings of the beveled diamond anvils were observed experimentally. Furthermore, details of pressure loading, distribution, gasket-thickness variation, and diamond anvil deformation were studied to understand the generation of ultrahigh pressures, which may improve the conventional DAC techniques.

47 OTHER INSTRUMENTATION↗
NASA NTRS2004

Design Space Issues for Intrinsic Evolvable Hardware

This paper discusses the problem of increased programming time for intrinsic evolvable hardware (EM) as the complexity of the circuit grows. As the circuit becomes more complex, then more components will be required and a longer programming string, L, is required. We develop equations for the size of the population, n, and the number of generations required for the population to converge, based on L. Our analytical results show that even though the design search space grows as 2L (assuming a binary programming string), the number of circuit evaluations, n*ngen, only grows as O(Lg3), or slightly less than O(L). This makes evolvable techniques a good tool for exploring large design spaces. The major hurdle for intrinsic EHW is evaluation time for each possible circuit. The evaluation time involves downloading the bit string to the device, updating the device configuration, measuring the output and then transferring the output data to the control processor. Each of these steps must be done for each member of the population. The processing time of the computer becomes negligible since the selection/crossover/mutation steps are only done once per generation. Evaluation time presently limits intrinsic evolvable hardware techniques to designing only small or medium-sized circuits. To evolve large or complicated circuits, several researchers have proposed using hierarchical design or reuse techniques where submodules are combined together to form complex circuits. However, these practical approaches limit the search space of available designs and preclude utilizing parasitic coupling or other effects within the programmable device. The practical approaches also raise the issue of why intrinsic EHW techniques do not easily apply to large design spaces, since the analytical results show only an O(L) complexity growth.

Hereford, James↗
DOE OSTI2020

Reviews and syntheses: Ironing out wrinkles in the soil phosphorus cycling paradigm

Soil phosphorus (P) management remains a critical challenge for agriculture worldwide, and yet we are still unable to predict soil P dynamics as confidently as that of carbon (C) or nitrogen (N). This is due to both the complexity of inorganic P (P i ) and organic P (P o ) cycling and the methodological constraints that have limited our ability to trace P dynamics in the soil–plant system. In this review, we describe the challenges for building parsimonious, accurate, and useful biogeochemical models that represent P dynamics and explore the potential of new techniques to usher P biogeochemistry research and modeling forward. We conclude that research efforts should focus on the following: (1) updating the McGill and Cole (1981) model of P o mineralization by clarifying the role and prevalence of biochemical and biological P o mineralization, which we suggest are not mutually exclusive and may co-occur along a continuum of P o substrate stoichiometry; (2) further understanding the dynamics of phytate, a six C compound that can regulate the poorly understood stoichiometry of soil P; (3) exploring the effects of C and P o saturation on P sorption and P o mineralization; and (4) resolving discrepancies between hypotheses about P cycling and the methods used to test these hypotheses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Fast inference of deep neural networks in FPGAs for particle physics

Here, recent results at the Large Hadron Collider (LHC) have pointed to enhanced physics capabilities through the improvement of the real-time event processing techniques. Machine learning methods are ubiquitous and have proven to be very powerful in LHC physics, and particle physics as a whole. However, exploration of the use of such techniques in low-latency, low-power FPGA (Field Programmable Gate Array) hardware has only just begun. FPGA-based trigger and data acquisition systems have extremely low, sub-microsecond latency requirements that are unique to particle physics. We present a case study for neural network inference in FPGAs focusing on a classifier for jet substructure which would enable, among many other physics scenarios, searches for new dark sector particles and novel measurements of the Higgs boson. While we focus on a specific example, the lessons are far-reaching. A companion compiler package for this work is developed based on High-Level Synthesis (HLS) called hls4ml to build machine learning models in FPGAs. The use of HLS increases accessibility across a broad user community and allows for a drastic decrease in firmware development time. We map out FPGA resource usage and latency versus neural network hyperparameters to identify the problems in particle physics that would benefit from performing neural network inference with FPGAs. For our example jet substructure model, we fit well within the available resources of modern FPGAs with a latency on the scale of 100 ns.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Investigating Low Loss Substrates for Improved Qubit Coherence Times

Superconducting qubits are sensitive to dielectric losses from substrates, making the identification, optimization, and preparation of low-loss materials essential for enhancing qubit coherence times. In this work, we utilize Nb superconducting radio-frequency (SRF) cavities as a high-precision measurement tool to study the dielectric loss tangent of substrates with parts-per-billion sensitivity. This technique enables temperature- and field-resolved measurements, providing deep insights into the behavior of candidate materials such as sapphire and silicon. We explore the impact of substrate preparation techniques, examining how surface treatments and cleaning protocols influence dielectric loss. These studies highlight both the microscopic origins of loss in these substrates and the critical role of preparation methods, helping to identify key materials and processes that minimize dielectric loss, crucial for improving qubit performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

SU-F-T-273: Using a Diode Array to Explore the Weakness of TPS DoseCalculation Algorithm for VMAT and Sliding Window Techniques

Purpose: To identify the weakness of dose calculation algorithm in a treatment planning system for volumetric modulated arc therapy (VMAT) and sliding window (SW) techniques using a two-dimensional diode array. Methods: The VMAT quality assurance(QA) was implemented with a diode array using multiple partial arcs that divided from a VMAT plan; each partial arc has the same segments and the original monitor units. Arc angles were less than ± 30°. Multiple arcs delivered through consecutive and repetitive gantry operating clockwise and counterclockwise. The source-toaxis distance setup with the effective depths of 10 and 20 cm were used for a diode array. To figure out dose errors caused in delivery of VMAT fields, the numerous fields having the same segments with the VMAT field irradiated using different delivery techniques of static and step-and-shoot. The dose distributions of the SW technique were evaluated by creating split fields having fine moving steps of multi-leaf collimator leaves. Calculated doses using the adaptive convolution algorithm were analyzed with measured ones with distance-to-agreement and dose difference of 3 mm and 3%.. Results: While the beam delivery through static and step-and-shoot techniques showed the passing rate of 97 ± 2%, partial arc delivery of the VMAT fields brought out passing rate of 85%. However, when leaf motion was restricted less than 4.6 mm/°, passing rate was improved up to 95 ± 2%. Similar passing rate were obtained for both 10 and 20 cm effective depth setup. The calculated doses using the SW technique showed the dose difference over 7% at the final arrival point of moving leaves. Conclusion: Error components in dynamic delivery of modulated beams were distinguished by using the suggested QA method. This partial arc method can be used for routine VMAT QA. Improved SW calculation algorithm is required to provide accurate estimated doses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Detection and Attribution of Regional Climate Change with a Focus on the Precursors of Droughts (Final LDRD Report)

For centuries, droughts have affected human and environmental systems. Understanding the primary causes of droughts has become even more crucial in the context of global warming, with drier conditions predicted to intensify in already arid regions. The problem of identifying human-induced climate change is typically addressed using so-called climate change "detection and attribution” (D&A) techniques, which is a statistical “signal in noise” problem (Hegerl et al., 2007). To date, however, these techniques have seen little application in drought research. Here, we propose to explore whether a novel D&A-derived technique could be applied in this context. A number of mechanisms have been identified as potential drivers of recent droughts. These include specific and persistent spatial patterns in sea surface temperature (SST) anomalies similar to those under La-Nina conditions, and related changes in atmospheric circulation. The ultimate goal of this research will be to determine whether there is an emerging human signal in the frequency and spatial structure of the drought precursors in response to global warming, and how the relative weight of human versus natural contributions to drought evolves over time. Here the progress made to address these questions is discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Multi-Physics Surrogate Modeling with Dimensionality Reduction

This summary provides a new algorithm to construct surrogate models for multi-physics, nonlinear, high dimensional models which typically suffer from the curse of dimensionality. To deal with the high computational cost and difficult error estimation, we employ recent advances in reduced order modeling (ROM) techniques to do an error-preserving reduction for the number of influential model parameters, followed by a conventional surrogate construction process. To implement ROM for a multiphysics model, a range finding algorithm (RFA) is used to identify a linear transformation in which the number of influential parameters can be minimized and the errors resulting from the non-influential parameters can be upper-bounded. The proposed algorithm is applied to the MAMMOTH coupled code system developed at the Idaho National Laboratory. In particular, we investigate the reducibility of Rattlesnake and BISON codes and their multi-physics coupling. The most important result of this work is that the reduction obtained with coupled physics is more significant than that with individual physics models. This summary explores the application of ROM techniques on multi-physics coupling codes system. Concise methodology is provided and selected numerical results are provided to show that coupling system provides additional reduction at interfaces. Future work could be invested to determine the optimum surrogate model format. (authors)

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

Preliminary Assessment of Artificial Gravity Impacts to Deep-Space Vehicle Design

Even after more than thirty years of scientific investigation, serious concerns regarding human physiological effects of long-duration microgravity exposure remain. These include loss of bone mineral density, skeletal muscle atrophy, and orthostatic hypertension, among others. In particular, "Safe Passage: Astronaut Care for Exploration Missions," states "loss of bone density, which apparently occurs at a rate of 1% per month in microgravity, is relatively manageable on the short-duration missions of the space shuttle, but it becomes problematic on the ISS [International Space Station]. ...If this loss is not mitigated, interplanetary missions will be impossible." While extensive investigations into potential countermeasures are planned on the ISS, the delay in attaining full crew complement and onboard facilities, and the potential for extending crews tours of duty threaten the timely (< 20 years!) accumulation of sufficient data for countermeasures formulation. Indeed, there is no guarantee that even with the data, a practical or sufficiently robust set of countermeasures will be forthcoming. Providing an artificial gravity (AG) environment by crew centrifugation aboard deep-space human exploration vehicles, long a staple technique of science fiction, has received surprisingly limited engineering assessment. This is most likely due to a number of factors: the lack of definitive design requirements, especially acceptable artificial gravity levels and rotation rates, the perception of high vehicle mass and performance penalties, the incompatibility of resulting vehicle configurations with space propulsion options (i.e., aerocapture), the perception of complications associated with de-spun components such as antennae and photovoltaic arrays, and the expectation of effective crew micro-gravity countermeasures. These perception and concerns may have been overstated, or may be acceptable alternatives to countermeasures of limited efficacy. This study was undertaken as an initial step to try to understand the implications of and potential solutions to incorporating artificial gravity in the design of human deep-space exploration vehicles. Of prime interest will be the mass penalties incurred by incorporating AG, along with any mission performance degradation.

Joosten, B. Kent↗
DOE OSTI2025

A Fundamentally New Coupled Approach to Contact Mechanics via the Dirichlet‐Neumann Schwarz Alternating Method

Contact phenomena are crucial for understanding the behavior of mechanical systems. However, existing computational approaches for simulating mechanical contact often face numerical challenges, such as inaccurate physical predictions, energy conservation errors, and unwanted oscillations. Here, we introduce an alternative technique for simulating dynamic contact based on the non‐overlapping Schwarz alternating method, originally developed for domain decomposition. In multibody contact scenarios, this method treats each body as a separate, non‐overlapping domain and prevents interpenetration using an alternating Dirichlet–Neumann iterative process. This approach has a strong theoretical foundation, eliminates the need for contact constraints, and offers flexibility, making it ideal for multiscale and multiphysics applications. We conducted a numerical comparison between the Schwarz method and traditional methods, such as the Lagrange multiplier and penalty methods, focusing on a benchmark impact problem. Our results indicate that the Schwarz alternating method outperforms traditional methods in several key areas: it provides more accurate predictions for various measurable quantities and demonstrates exceptional energy conservation capabilities. To address unwanted oscillations in contact velocities and forces, we explored various algorithms and stabilization techniques, ultimately opting for the naïve‐stabilized Newmark scheme for its simplicity and effectiveness. Additionally, we validated the efficiency of the Schwarz method in a three‐dimensional impact problem, highlighting its inherent capacity to accommodate different mesh topologies, time‐integration schemes, and time steps for each interacting body.

Schwarz alternating method↗
NASA NTRS1986

The Extreme Ultraviolet Explorer - Optics fabrication and performance

The fabrication methods, testing and evaluation techniques, and performance results are presented for the mirrors for the Extreme Ultraviolet Explorer (EUVE). The finest mirror produced to date has a measured half energy width of 8 arcsec at optical wavelengths. With a polished nickel surface, the telescope throughput was 35 percent at 44 A and 60 percent at 256 A. The surface roughness is 20 A rms.

Green, J.↗
DOE OSTI2024

Continuously tunable uniaxial strain control of van der Waals heterostructure devices

Uniaxial strain has been widely used as a powerful tool for investigating and controlling the properties of quantum materials. However, existing strain techniques have so far mostly been limited to use with bulk crystals. Although recent progress has been made in extending the application of strain to two-dimensional van der Waals (vdW) heterostructures, these techniques have been limited to optical characterization and extremely simple electrical device geometries. Here, we report a piezoelectric-based in situ uniaxial strain technique enabling simultaneous electrical transport and optical spectroscopy characterization of dual-gated vdW heterostructure devices. Critically, our technique remains compatible with vdW heterostructure devices of arbitrary complexity fabricated on conventional silicon/silicon dioxide wafer substrates. We demonstrate a large and continuously tunable strain of up to –0.15% at millikelvin temperatures, with larger strain values also likely achievable. We quantify the strain transmission from the silicon wafer to the vdW heterostructure, and further demonstrate the ability of strain to modify the electronic properties of twisted bilayer graphene. Our technique provides a highly versatile new method for exploring the effect of uniaxial strain on both the electrical and optical properties of vdW heterostructures and can be easily extended to include additional characterization techniques.

Electrical properties and parameters↗
NASA NTRS1994

Understanding software faults and their role in software reliability modeling

This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the regression equation. Since most of the existing metrics have common elements and are linear combinations of these common elements, it seems reasonable to investigate the structure of the underlying common factors or components that make up the raw metrics. The technique we have chosen to use to explore this structure is a procedure called principal components analysis. Principal components analysis is a decomposition technique that may be used to detect and analyze collinearity in software metrics. When confronted with a large number of metrics measuring a single construct, it may be desirable to represent the set by some smaller number of variables that convey all, or most, of the information in the original set. Principal components are linear transformations of a set of random variables that summarize the information contained in the variables. The transformations are chosen so that the first component accounts for the maximal amount of variation of the measures of any possible linear transform; the second component accounts for the maximal amount of residual variation; and so on. The principal components are constructed so that they represent transformed scores on dimensions that are orthogonal. Through the use of principal components analysis, it is possible to have a set of highly related software attributes mapped into a small number of uncorrelated attribute domains. This definitively solves the problem of multi-collinearity in subsequent regression analysis. There are many software metrics in the literature, but principal component analysis reveals that there are few distinct sources of variation, i.e. dimensions, in this set of metrics. It would appear perfectly reasonable to characterize the measurable attributes of a program with a simple function of a small number of orthogonal metrics each of which represents a distinct software attribute domain.

Munson, John C.↗
NASA NTRS2001

A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter

Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems. We are exploring the use of one of these techniques, which utilizes multi-signal modeling and the TEAMS-RT real-time diagnostic engine, on the UH-60 Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) flight research aircraft. We focus on the engine and transmission systems, and acquire sensor data across the 1553 bus as well as by direct analog-to-digital conversion from sensors to the QHuMS (Qualtech health and usage monitoring system) computer. The QHuMS computer uses commercially available components and is rack-mounted in the RASCAL facility. A multi-signal model of the transmission and engine subsystems enables studies of system testability and analysis of the degree of fault isolation available with various instrumentation suites. The model and examples of these analyses will be described and the data architectures enumerated. Flight tests of this system will validate the data architecture and provide real-time flight profiles to be further analyzed in the laboratory.

Patterson-Hine, Ann↗
DOE OSTI2015

Coupling of Independent Electrochemical Reactions and Fluorescence at Closed Bipolar Interdigitated Electrode Arrays

Electrochemical reactions occurring at the opposite ends of bipolar electrodes (BPEs) are necessarily coupled, enabling electron transfer events at one end to be read out optically, for example, by coupling to fluorogenic reactions at the other end. In order to explore the potential of this technique for studying multiple redox events, arrays of parallel BPE interdigitated electrode arrays (IDEAs) were fabricated and integrated with separate analytical and reporter microfluidic channels, respectively, in a closed BPE configuration. The apparatus was initially evaluated employing Fe(CN) 6 3/4- in the analytical channel coupled to weakly emissive resazurin and strongly emissive resorufin as the fluorogenic redox reporter pair. We then used the device to investigate a proton-coupled electron transfer reaction, hydroquinone (QH 2 ) oxidation, in structures with an integrated pH modulation electrode (PME). A pH-sensitive dye, fluorescein, was co-introduced into the analytical channel to monitor PME modulation of solution pH, and its coupling to QH 2 oxidation, thereby permitting changes in solution pH, and consequently QH 2 oxidation rate, to be monitored directly in the analytical channel and compared to the fluorescence in the reporter channel. Additionally, diffusion of OH - generated at the PME produced a spatial pH profile that was visualized via fluorescein emission, and, because the oxidation of QH 2 at each BPE is strongly dependent on the local pH, via the coupled fluorogenic reaction at the opposite pole of the corresponding BPE digit in the reporter channel. Thus, BPE IDEAs support the coupling of independent redox reactions and the use of fluorescence imaging to explore a diverse set of spatially varying electrochemical phenomena realized in a variety of electrochemical geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗