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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Methylated Poly(ethylene)imine Modified Capacitive Micromachined Ultrasonic Transducer for Measurements of CO2 and SO2 in Their Mixtures

A gravimetric gas detection device based on surface functionalized Capacitive Micromachined Ultrasound Transducers (CMUTs) was designed, fabricated and tested for detection of carbon dioxide (CO2) and sulfur dioxide (SO2) mixtures in nitrogen. The created measurement setup of continuous data collection, integrated with an in-situ Fourier Transform Infrared (FT-IR) spectroscopy, allows for better understanding of the mechanisms and molecular interactions with the sensing layer (methylated poly(ethylene)imine) and its need of surface functionalization for multiple gas detection. During experimentation with CO2 gases, weak molecular interactions were observed in spectroscopy data. Linear sensor response to frequency shift was observed with CO2 concentrations ranging from 0.16 vol % to 1 vol %. Moreover, the Raman and FT-IR spectroscopy data showed much stronger SO2 and the polymer interactions, molecules were bound by stronger forces and irreversibly changed the polymer film properties. However, the sensor change in resonance frequency in the tested region of 1 vol % to 5 vol % SO2 showed a linear response. This effect changed not only the device resonance frequency but also affected the magnitude of electroacoustic impedance which was used for differentiating the gas mixture of CO2, SO2, in dry N2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Ensembles of novelty detection classifiers for structural health monitoring using guided waves

Guided wave structural health monitoring uses sparse sensor networks embedded in sophisticated structures for defect detection and characterization. The biggest challenge of those sensor networks is developing robust techniques for reliable damage detection under changing environmental and operating conditions. To address this challenge, we develop a novelty classifier for damage detection based on one class support vector machines. We identify appropriate features for damage detection and introduce a feature aggregation method which quadratically increases the number of available training observations.We adopt a two-level voting scheme by using an ensemble of classifiers and predictions. Each classifier is trained on a different segment of the guided wave signal, and each classifier makes an ensemble of predictions based on a single observation. Using this approach, the classifier can be trained using a small number of baseline signals. We study the performance using monte-carlo simulations of an analytical model and data from impact damage experiments on a glass fiber composite plate.We also demonstrate the classifier performance using two types of baseline signals: fixed and rolling baseline training set. The former requires prior knowledge of baseline signals from all environmental and operating conditions, while the latter does not and leverages the fact that environmental and operating conditions vary slowly over time and can be modeled as a Gaussian process.

Dib, Gerges (ORCID:0000000255004047)↗
NASA NTRS1999

Measuring the Chemical Potential of the Martian Regolith to Generate and Sustain Life

A critical component for identifying chemical biosignatures is the ability to assess in-situ the potential of an aqueous geochemical environment to generate and sustain life. On Mars or other solar bodies, in-situ chemical characterization could provide evidence as to whether the chemical composition of the regolith or evaporites in suspected ancient water bodies have been biologically influenced or possess the chemical parameters within which life may have existed, or may still exist. A variety of analytical techniques have been proposed for use in detecting and identify signatures of past or present life. These techniques fall into two groups; visual observation with instruments such as cameras or optical/atomic-force microscopes; or elemental chemical analysis with such instruments as X-ray fluorescence (XRF) and diffraction (XRD), a-proton backscatter (APX), y-ray, Mossbauer, Raman, IR, UV/VIS spectroscopies, gas chromatography (GC), or mass spectrometry (MS). Direct observation of an identifiable lifeform by the first set of instruments in a single sample is highly unlikely, especially for extinct organisms or on the surface. The later instruments can provide vital data as to the elemental mineralogy and geological history of the planet, but are highly inadequate for understanding the chemistry of the planet in terms of indigenous life or interactions with human explorers. Techniques such as XRD, XRF, and APX, provide elemental composition at high limits of detection. Some of this data can be extrapolated or interpolated to provide chemical parameters such as oxidation state or composition. Gas chromatography (GC) without standards and non-specific detectors, has little chance of identifying a mixture of unknown components. Combined with GC or by itself, mass spectrometry (MS) can provide identification of compounds, but in both cases the sample must be appropriately prepared for accurate and reliable analysis. Life as we know it, and probably identify it as such, requires an aqueous environment. Deciphering die chemical speciation of this aqueous environment is the key to recognizing therein the biosignatures of any extinct or present life forms. Identifying the soluble (ionic and nonionic) components by reacting a currently dormant environment can provide a "picture" of the thermodynamics and chemical components of a possibly bioactive environment. The only devices which can provide such information are electrochemical sensors based on the potentiometric ion selective electrodes (ISEs) and on dynamic techniques such as cyclic voltammetry (CV) and stripping voltammetry (SV). Such an array of devices can provide not only the chemical composition of a water-soluble Martian soil sample, but also several other vital chemical parameters such as pH, conductivity, redox potential, and dissolved gases. To address these issues we have been investigating the possible use of an electrochemically-based ion sensor array as a new integrated approach to quantitative analytical and chemometric electrochemical measurements. The sensor array will consist of specific and semispecific ion selective and amperometric transducers, which can simultaneously and continuously identify and semiquantitatively determine over 50 organic and inorganic analytes in water-based environments. Several individual sensors, based on the same principle, have been flight-tested and have been installed as part of the MECA instrumentation on the Mars 2001 Lander for in-situ analyses. However, the microfabrication, integration and multiplexing of such a large number of these sensors on a single substrate have not been previously attempted.

Kounaves, S. P.↗
DOE OSTI2012

Real sample temperature: a critical issue in the experiments of nuclear resonant vibrational spectroscopy on biological samples

There are several practical and intertangled issues which make the experiments of nuclear resonant vibrational spectroscopy (NRVS) on biological samples difficult to perform. The sample temperature is one of the most important issues. In NRVS the real sample temperatures can be very different from the readings on the temperature sensors. In this study the following have been performed: (i) citing and analyzing various existing NRVS data to assess the real sample temperatures during the NRVS measurements and to understand their trends with the samples’ loading conditions; (ii) designing several NRVS measurements with (Et 4 N)[FeCl 4 ] to verify these trends; and (iii) proposing a new sampleloading procedure to achieve significantly lower real sample temperatures and to balance among the intertangled experimental issues in biological NRVS measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

Secondary ion mass spectrometry (SIMS) analysis of hypervelocity microparticle impact sites on LDEF surfaces

Two dimensional elemental ion maps have been recorded for hundreds of microparticle impact sites and contamination features on LDEF surfaces. Since the majority of the analyzed surfaces were metal-oxide-silicon (MOS) impact detectors from the Interplanetary Dust Experiment, a series of 'standard' and 'blank' analyses of these surfaces are included. Hypervelocity impacts of forsterite olivine microparticles on activated flight sensors served as standards while stylus and pulsed laser simulated 'impacts' served as analytical blanks. Results showed that despite serious contamination issues, impactor residues can be identified in greater than 1/3 of the impact sites. While aluminum oxide particles could not be detected on aluminum surfaces, they were detected on germanium surfaces from row 12. Remnants of manmade debris impactors consisting of paint chips and bits of metal were identified on surfaces from LDEF Rows 3 (west or trailing side), 6 (south), 9 (ram or leading side), 12 (north) and the space end. Higher than expected ratios of manmade microparticle impacts to total microparticle impacts were found on the space end and the trailing side. These results were consistent with time-tagged and time-segregated microparticle impact data from the IDE and other LDEF experiments. A myriad of contamination interferences were identified and their effects on impactor debris identification mitigated during the course of this study. These interferences include pre-, post and inflight deposited surface contaminants as well as indigenous heterogeneous material contaminants. Non-flight contaminations traced to human origins, including spittle and skin oils, contributed significant levels of alkali-rich carbonaceous interferences. A ubiquitous layer of in-flight deposited silicaceous contamination varied in thickness with location on LDEF, even on a micro scale. In-flight deposited (low velocity) contaminants include urine droplets and bits of metal film from eroded thermal blankets.

Simon, C. G.↗
NASA NTRS2002

Role of Satellite Rainfall Information in Improving Understanding of the Dynamical Link Between the Tropics and Extratropics Prospects of Improved Forecasts of Weather and Short-Term Climate Variability on Sub-Seasonal Time Scales

The tropics and extratropics are two dynamically distinct regimes. The coupling between these two regimes often defies simple analytical treatment. Progress in understanding of the dynamical interaction between the tropics and extratropics relies on better observational descriptions to guide theoretical development. However, global analyses currently contain significant errors in primary hydrological variables such as precipitation, evaporation, moisture, and clouds, especially in the tropics. Tropical analyses have been shown to be sensitive to parameterized precipitation processes, which are less than perfect, leading to order-one discrepancies between estimates produced by different data assimilation systems. One strategy for improvement is to assimilate rainfall observations to constrain the analysis and reduce uncertainties in variables physically linked to precipitation. At the Data Assimilation Office at the NASA Goddard Space Flight Center, we have been exploring the use of tropical rain rates derived from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments in global data assimilation. Results show that assimilating these data improves not only rainfall and moisture fields but also related climate parameters such as clouds and radiation, as well as the large-scale circulation and short-range forecasts. These studies suggest that assimilation of microwave rainfall observations from space has the potential to significantly improve the quality of 4-D assimilated datasets for climate investigations (Hou et al. 2001). In the next few years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007. Continued improvements in assimilation methodology, rainfall error estimates, and model parameterizations are needed to ensure that we derive maximum benefits from these observations.

Hou, Arthur Y.↗
DOE OSTI2022

Nondestructive Damage Detection of Concrete With Alkali-Silica Reactions Using Coda Wave and Anomaly Detection

An anomaly detection model for early damage detection for concrete structures undergoing alkali-silica reaction (ASR) is presented. It is difficult to detect ASR initiation and early damage without a reference expansion measurement. Coda waves, or the multiply scattered portion of ultrasonic waves, have been found to be indicative of small changes in complex material such as concrete. The relationship between concrete damage and relative velocity change and decorrelation of coda waves has been studied, but a generalized model which detects when damage occurs in a concrete structure is still lacking. The presented method uses features extracted from coda waves to detect early damage in concrete structures. The model uses unsupervised learning and only requires data from undamaged structures for training. During the training process, the reconstruction error of the training data is minimized. When the data collected from damaged concrete structures is used as an input of the model, it returns high reconstruction errors that indicate the occurrence of damage in the structures. The performance of the model is validated using experimental studies and has been shown to generalize across two different ASR specimens.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

On the Sensitivity of Piezoceramics and Piezopolymers in Structural Integrity Monitoring of Large Trusses

An analytical assessment has been made of the reliability of using integrated microactuators and sensors in the form of piezoceramics and piezopolymers as joint integrity monitors in trussed systems. The concept is first implemented for a simple structure which consists of two truss members with a 45 deg lift angle joined at the apex. A piezoceramic patch (or piezopolymer film) bonded on the surface of one of the members at a location near the joint is used as a collocated actuator/sensor. The overall structural dynamic response under an excitation was modeled by finite element method. Different degrees of nodal constraints at the joints representing various degrees of joint integrity are employed. The resulting dynamic response showed distinct responses for varying joint stiffnesses. Parallel experimental work on a truss model using a multichannel data acquisition system and a digital signal analyzer confirms the results from analysis. We further studied the sensitivity of the micro-sensors to the behavior of joints of large arch truss structure. Results obtained for large trusses with many degrees of freedom indicate optimum locations of sensors for which the dynamic response signatures are distinct and distinguishable for relatively small changes in joint integrity and/or structural geometry. Computations based on finite element modeling show that locating the single actuator/sensor at the joint corresponding to the first loss of static stability appear optimal. Hence, static stability analysis of complex trusses can give us a good indication of the optimum placement of sensors for maximum response. This observation is important if few distributed sensors and actuators are available for placement in constructed facilities made from large trusses with many degrees of freedom. As an extension of this work a dynamic response signature identification technique to monitor in-service degradation of joints is under development for application to the monitoring of the integrity of adhesive joints in composite structures.

Abatan, A. O.↗
NASA NTRS2001

Spectral Data Assimilation for Merging Satellite Ocean Color Imagery

The Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project was initiated 'to develop a methodology and operational capability to combine data products from various ocean color missions in a manner that ensures the best possible global coverage and best exploits the complementary missions of the sensors'. While the merging of data from multiple sources has already been implemented for sea surface temperature (SST), altimetry or clouds, this is a new topic in ocean color science. Merging ocean color data has obvious advantage in terms of spatial and temporal coverage of the global ocean but data merging should also result in new, more diverse and improved data products with lower uncertainties. The merging of ocean color satellite data is generally considered at the level of the global gridded products, i.e., NASA Level-3 and, more specifically, for the merging of chlorophyll a concentration data, [Ch1]. This approach limits computational issues and deals with a unique, simple quantity, [Ch1]. However, ocean color data merging can also be conducted at the level of water-leaving radiances, LwN(lamda), using either empirical or semi-analytical algorithms. Although more challenging, this latter approach is potentially extremely powerful as it can achieve good consistency in the final data products and can take advantage of both the specificities and differences of each source of data. The demonstration of the feasibility of such approach is the main objective of our SIMBIOS work. Here, we use a semi-analytical algorithm to merge Rrs (or, equivalently LwN) data from different sources to estimate [Ch1]. The model also allows for the retrieval of other quantities such as the combined absorption of colored detrital particulate and dissolved organic matter at 443 nm, a(sub cdm)(443) and the particulate backscattering, b(sub bp)(443).

Siegel, David A.↗
NASA NTRS1998

A New Approach to Overcoming Spatial Aliasing in Structural Damage Detection

Aircraft, reusable launch vehicles,unmanned aircraft, and other advanced structures are being built using lightweight composite materials/metals with design safety factors as low as 1.25. These advanced structures operate in uncertain and severe environments and are susceptible to damage such as delamination, fiber/matrix damage, hydrothermal strain in composite materials, and fatigue and cracking in metals. To ensure human safety and load-bearing integrity these structures must be inspected to detect and locate often invisible damage and faults before they become catastrophic. Conventional methods of non-destructive evaluation sometimes miss significant damage and are time consuming and expensive to perform. In contrast, vibrometry or vibration signature techniques are a global method of structural integrity monitoring that potentially can efficiently detect damage on large structures, including damage that is away from sensor locations, and in the interior of structures. However, a barrier problem in damage detection using vibration measurements is the need to measure the vibration response at a large number of points on the structure. Typically, model reduction or expansion procedures such as Guyan reduction or dynamic expansion are attempted to overcome the problem of insufficient measurements or spatial aliasing. These approaches depend on using information from the healthy model, and thus put error into the reduction used to represent the damaged structure. In this paper, a Frequency Response Function technique is used to detect damage to a fixed-free beam. The technique uses measured frequency response functions from the healthy structure as reference data, and then monitors vibration measurements during the life of the structure to detect damage. In an analytical simulation using a finite-element model of a beam, damage was located using only sparse measurements because the technique uses both rotation and translation measurements from the damaged structure.

Schulz, Mark J.↗
NASA NTRS1989

Low level remote sensing: Orographic winds

The orographic flow data set was obtained from a flight program to measure the influence of orographic features on turbulence momentum, heat, and moisture fluxes. The NASA B-57 aircraft instrumented with probes for measuring the three fluctuating wind speed components, temperature, and humidity was the primary measuring vehicle. Ancillary measurements were made with several ground-based sensors. These include the NOAA radar wind profilers, the Boulder wind network, the PROFS mesoscale surface network, the Boulder Atmospheric Observatory 300 m tower, special rawinsonde observations, and the NOAA/WPL Doppler lidar. The major objective of the flight program was to provide planetary boundary layer parameter information for new and current general circulation computer models. A numerical code, WINDER, based on a discrete element technique was run to numerically model the water tunnel simulated flow. Comparison of the analytical model with the experimental results is very good. Physical fluid dynamic principles embedded in the computational model and visual and hot wire anemometer measurements from the simulation are being rationalized to develop a physical understanding of the vortex flow. The results will be interpreted as they pertain to full scale atmospheric flows.

Frost, Walter↗
NASA NTRSDate not supplied

Characterization of NU-LHT-4M Lunar Regolith Simulant Using Different Raman Configurations

As much as possible, structures to help sustain a long-term human presence on the moon will be constructed via in-situ resource utilization (ISRU) from lunar regolith. Various processes have been proposed to make lunar regolith-based construction materials, but one complication is that the lunar regolith is relatively complex in terms of composition and can vary quite significantly from one site to another. Some of these methods to make lunar regolith-based construction materials are quite sensitive to the composition and so in-situ methods for evaluating the composition of the lunar regolith could be critical. Various analytical instrumentation has been proposed for in-situ characterization of the composition of regolith on planetary bodies. Raman spectroscopy has been suggested and has some advantages over other in-situ techniques, such as potential for relatively high spatial resolution, direct determination of the mineralogy (while other methods may only infer the mineralogy), nondestructive analysis, relatively simple instrument configurations, and minimal sample preparation/handling. For example, Raman instrumentation has already been deployed in rover-based missions to Mars. Previously, we developed the Standoff Ultracompact Micro-Raman Sensor (SUCR), which is a portable Raman spectroscopy instrument capable to be integrated into a rover or onto a lander. Here, we present work on Raman spectroscopy measurements of NU-LHT-4M lunar simulant using three different Raman instruments with different configurations for collecting Raman data with the goal to explore the effect of these different configurations on the results, especially for use in a lunar environment.

Raman Spectroscopy↗
DOE OSTI2022

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2017

Unsteady Aerodynamic Force Sensing from Strain Data

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm.

aerodynamic load sensing↗
DOE OSTI2026

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗
DOE OSTI2019

Distributed Acoustic Sensing of Strain at Earth Tide Frequencies

The solid Earth strains in response to the gravitational pull from the Moon, Sun, and other planetary bodies. Measuring the flexure of geologic material in response to these Earth tides provides information about the geomechanical properties of rock and sediment. Such measurements are particularly useful for understanding dilation of faults and fractures in competent rock. A new approach to measuring earth tides using fiber optic distributed acoustic sensing (DAS) is presented here. DAS was originally designed to record acoustic vibration through the measurement of dynamic strain on a fiber optic cable. Here, laboratory experiments demonstrate that oscillating strain can be measured with DAS in the microHertz frequency range, corresponding to half-day (M2) lunar tidal cycles. Although the magnitude of strain measured in the laboratory is larger than what would be expected due to earth tides, a clear signal at half-day period was extracted from the data. With the increased signal-to-noise expected from quiet field applications and improvements to DAS using engineered fiber, earth tides could potentially be measured in deep boreholes with DAS. Because of the distributed nature of the sensor (0.25 m measurement interval over kilometres), fractures could be simultaneously located and evaluated. Such measurements would provide valuable information regarding the placement and stiffness of open fractures in bedrock. Characterization of bedrock fractures is an important goal for multiple subsurface operations such as petroleum extraction, geothermal energy recovery, and geologic carbon sequestration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Real time monitoring of the chemistry of hydroxylamine nitrate and iron as surrogates for nuclear materials processing

The separation of actinides in aqueous solution often involves changes in redox chemistry achieved by reagents such as hydroxylamine nitrate (HAN). As a result, in situ monitoring of the chemistry of HAN in contact with plutonium and neptunium in concentrated nitric acid at 35°C is important for the efficacy of Pu-238 extraction. A spectroscopic method of following the chemistry of HAN in contact with iron (as a simulant for plutonium) was developed, using a quantum cascade laser-attenuated total reflectance (QCL-ATR) system. The mid-infrared (3.67–12.5 μm) was chosen for its ability to distinguish the molecular vibrations of analytes and exclude the background absorption of the concentrated HNO 3 matrix. The concentrations of chemical species found in the reaction were drawn from the collected QCL power data using Beer’s law after a baseline correction. These data were qualitatively compared to a kinetic rate model based on a simplified reaction mechanism. The QCL-ATR method can help assess the areas of stability of HAN, nitrate/nitrite interactions, and assist process control of actinide separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties

Connecting a material's surface chemistry with its electrocatalytic performance is one of the major questions in analytical electrochemistry. This is especially important in many sensor applications where analytes from complex media need to be measured. Unfortunately, today this connection is still largely missing except perhaps for the most simple ideal model systems. Here we present an approach that can be used to obtain insights about this missing connection and apply it to the case of carbon nanomaterials. In this paper we show that by combining advanced computational techniques augmented by machine learning methods with x-ray absorption spectroscopy (XAS) and electrochemical measurements, it is possible to obtain a deeper understanding of the correlation between local surface chemistry and electrochemical performance. As a test case we show how by computationally assessing the growth of amorphous carbon (a-C) thin films at the atomic level, we can create computational structural motifs that may in turn be used to deconvolute the XAS data from the real samples resulting in local chemical information. Then, by carrying out electrochemical measurements on the same samples from which x-ray spectra were measured and that were further characterized computationally, it is possible to gain insight into the interplay between the local surface chemistry and electrochemical performance. To demonstrate this methodology, we proceed as follows: after assessing the basic electrochemical properties of a-C films, we investigate the effect of short HNO 3 treatment on the sensitivity of these electrodes towards an inner sphere redox probe dopamine to gain knowledge about the influence of altered surface chemistry to observed electrochemical performance. Overall, these results pave the way towards a more general assessment of electrocatalysis in different systems and provide the first steps towards data driven tailoring of electrode surfaces to gain optimal performance in a given application.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗