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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.

Materials Science↗
DOE OSTI2022

High-Energy X-ray Diffraction Microscopy for Nuclear Forensics FY2022 Project Report

Morphological information on nuclear material has been identified using visible light and scanning electron microscopy. These identify qualitative differences in particle morphology. Three-dimensional imaging of materials through alternating scanning electron microscopy imaging and focused ion beam milling has also been used. Unfortunately, these techniques are time- and labor-intensive, with significant sample preparation required and lengthy analysis times. Further, the resulting 3D images are qualitative, require manual identification, and do not capture statistically-representative populations. High energy X-ray 3D imaging using a direct-beam or diffracted-beam (High-Energy Diffraction Microscopy) have been developed at the Advanced Photon Source and can produce quantitative information on grains (phase, location, etc.) and pores (size distribution, sphericity) in a material. These techniques require only minutes to characterize a sample volume and are non-destructive, thus suitable for a wide range of existing samples and for confirmatory analyses to be carried out using conventional microscopy techniques. In this first year of the project, all uranium oxide samples were synthesized and characterized using conventional analyses by the analytical chemistry laboratory. Conventional analysis methods included powder x-ray diffraction, scanning electron microscopy, impurity analysis via inductively coupled plasma mass spectrometry, and infrared spectroscopy. Impurity analysis shows a drop in boron content from UO 3 to the lowest U 3 O 8 calcination temperature, but otherwise no appreciable difference in any sample. Analysis of diffraction data shows a flip of peaks from UO 3 dominated for the 600 °C calcined sample to U 3 O 8 dominated at 700 °C and 800 °C. Analysis of scanning electron microscopy images shows that with increased calcination temperature the size distribution of particles seems to increase and broaden. Both of these last findings are in line with previously published data, though this work used significantly fewer particles to simply show similar trends instead of getting truly quantitative particle analysis. Infrared analysis similarly shows ingrowth of U 3 O 8 as calcination temperature is increased, along with depression of peaks associated with UO 3 and water. Samples were prepared for analysis at the Advanced Photon Source at beamline 1-ID. It is anticipated that analysis will occur in November of 2022. AI/ML techniques to de-noise data coming out of 1-ID during the analyses was also developed during this time using previously gathered data. Preliminary results using a self-supervision technique called Noise2Selfshow good de-noising of data. Once the uranium oxide samples are analyzed, real data will be used to test the de-noising and other AI/ML techniques that may be developed in the second year of the project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2000

Quantifying Void Ratio in Granular Materials Using Voronoi Tessellation

Voronoi technique was used to calculate the local void ratio distribution of granular materials. It was implemented in an application-oriented image processing and analysis algorithm capable of extracting object edges, separating adjacent particles, obtaining the centroid of each particle, generating Voronoi polygons, and calculating the local void ratio. Details of the algorithm capabilities and features are presented. Verification calculations included performing manual digitization of synthetic images using Oda's method and Voronoi polygon system. The developed algorithm yielded very accurate measurements of the local void ratio distribution. Voronoi tessellation has the advantage, compared to Oda's method, of offering a well-defined polygon generation criterion that can be implemented in an algorithm to automatically calculate local void ratio of particulate materials.

Alshibli, Khalid A.↗
DOE OSTI2026

Dual particle imaging using time-of-flight neutron classification

Fast-neutron imaging technology is well-suited for passive nuclear material monitoring, secondary inspection of flagged cargo, and wide-area search for lost neutron sources. However, imaging systems that use pulse shape discrimination for event classification require complex pulse waveform analysis. In this work, we evaluate time-of-flight (TOF) based particle classification as an alternative solution for fast-neutron imaging by classifying all events with a TOF above a maximum threshold as neutrons. We measured a Cf-252 source next to Cs-137 using a 12-bar organic-glass scintillator array. By varying the TOF thresholds for neutron identification, we demonstrate a clear trade-off between event yield and backprojection image fidelity, with stricter thresholds improving precision at the cost of statistics, TOF thresholded data generated an image that predicted the neutron source direction with 20% reduced mean central angle prediction error compared to a traditional pulse shape discrimination (PSD) method with comparable event count. Time-of-flight particle classification shows promise as an alternative to pulse shape discrimination systems for fast neutron imaging systems looking to minimize costs and size of electronics with comparable imaging quality. The sources used demonstrate that the method is effective in classifying measured neutrons in a measurement environment with 150 μCi Cs-137 and 1.6 × 10 6 n/s Cf-252 sources positioned at distances of 66 cm and 81 cm from the detector. Additionally, the method classifies low-energy neutron events that pulse shape discrimination removes, so a combination of both methods would result in a higher overall neutron event efficiency.

Heriot, William [Univ. of Michigan, Ann Arbor, MI ↗
NASA NTRS1999

Soil Analysis Micro-Mission Concepts Derived from the MSP 2001 Mars Environmental Compatibility Assessment (MECA)

The Mars Environmental Compatibility Assessment (MECA) will evaluate the Martian environment for soil and dust-related hazards to human exploration as part of the Mars Surveyor Program 2001 Lander. The integrated MECA payload contains a wet-chemistry laboratory, a microscopy station, an electrometer to characterize the electrostatic environment, and arrays of material patches to study abrasion and adhesion. Heritage will be all-important for low cost micro-missions, and adaptations of instruments developed for the Pathfinder, '98 and '01 Landers should be strong contenders for '03 flights. This talk has three objectives: (1) Familiarize the audience with MECA instrument capabilities; (2) present concepts for stand-alone and/or mobile versions of MECA instruments; and (3) broaden the context of the MECA instruments from human exploration to a comprehensive scientific survey of Mars. Due to time limitations, emphasis will be on the chemistry and microscopy experiments. Ion-selective electrodes and related sensors in MECA's wet-chemistry laboratory will evaluate total dissolved solids, redox potential, pH, and the concentration of many soluble ions and gases in wet Martian soil. These electrodes can detect potentially dangerous heavy-metal ions, emitted pathogenic gases, and the soil's corrosive potential, and experiments will include cyclic voltammetry and anodic stripping. For experiments beyond 2001, enhancements could allow multiple use of the cells (for mobile experiments) and reagent addition (for quantitative mineralogical and exobiological analysis). MECA's microscopy station combines optical and atomic-force microscopy (AFM) in an actively focused, controlled illumination environment to image particles from millimeters to nanometers in size. Careful selection of substrates allows controlled experiments in adhesion, abrasion, hardness, aggregation, magnetic and other properties. Special tools allow primitive manipulation (brushing and scraping) of samples. Soil particle properties including size, shape, color, hardness, adhesive potential (electrostatic and magnetic), will be determined using an array of sample receptacles and collection substrates. The simple, rugged atomic-force microscope will image in the submicron size range and has the capability of performing a particle-by-particle analysis of the dust and soil. Future implementations might enhance the optical microscopy with spectroscopy, or incorporate advanced AFM techniques for thermogravimetric and chemical analysis.

Hecht, M. H.↗
NASA NTRS2018

Fragment Size Distribution for Ice Particle Impacts on a Glass Plate

This work presents the results of an experimental study of ice particle impacts on a flat glass plate. The experiment was conducted at the Ballistics Impact Laboratory of NASA Glenn Research Center. The main objective of the experiment was to gain understanding about the modifications needed to the experimental configuration for a future parametric study at a larger range of values for particle diameters and other parameters. This was achieved by studying the effect of the velocity of an impacting ice particle on the post-impact fragment size and distribution for a reduced range of impacting particle diameters. Pre-impact particle diameter and velocity data were captured with a high-speed side camera. Post-impact fragment data were captured in a single frame with a 29-megapixel camera located above and normal to the target. Repeat runs were conducted for ice particles with diameters ranging from 1.7 to 2.9 millimeters, impacting at velocities between 39 and 98 meters per second. The fragment areas were measured, and the corresponding equivalent diameters and histogram distributions were calculated. Analysis of the data showed that the average equivalent diameter for the fragments in a run was an order of magnitude smaller than the diameter of the impacting ice particle. The histograms for equivalent diameter distribution were nonnormal with long tails, with most of the fragments having equivalent diameters concentrated toward the minimum value of the fragment size that could be resolved. Factors affecting the accuracy of the data during the digital imaging analysis were identified. Needed modifications to the setup to handle small size ice particles and other testing conditions were also identified.

engine icing↗
DOE OSTI2024

On the measurement of shape: With applications to lunar regolith

With the renewed commitment from NASA and other commercial entities for a presence on the Moon, the importance of understanding the characteristics of lunar regolith and how to utilize it have become the target of increasing scrutiny. Much of what is known about lunar regolith was collected during and immediately after the Apollo program, however, analytical techniques and instrumentation have advanced in leaps and bounds in the subsequent decades. Specifically, dynamic image analysis systems have advanced to the point that millions of particles can have morphological characteristics automatically determined in relatively short time frames. Particle morphological data was collected on several lunar samples and a pair of widely used regolith simulants to ascertain the accuracy of these simulants and to explore statistical analysis methods of these large datasets. It is found that these morphology datasets can vary widely depending on the particle size of the particles, and simple averaging of the data skews the results heavily towards the numerically abundant size ranges, the fines. Different reporting methods are suggested to ameliorate these problems. When applied to the lunar regolith, the particles are noted to be less morphologically complex than initially suspected. Compared to the lunar material, the simulants are found to contain some more morphological variability and angular grains. Such difference is likely due to the wildly different comminution processes that these different powder systems are subjected to.

2D shape↗
NASA NTRS1988

Application of optical correlation techniques to particle imaging

Pulsed laser sheet velocimetry yields noninstrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usuallay MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the particle image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.

Wernet, Mark P.↗
DOE OSTI2024

AGR-2 TRISO Layer Thickness Imaging Archive

As a part of fuel quality control characterization, optical microscopy images of particle cross sections near midplane were acquired at Oak Ridge National Laboratory (ORNL). These particles were produced by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program’s AGR-2 irradiation campaign. These images may be of use for the development of image processing algorithms with the benchmark values measured at ORNL. This report provides those benchmark values, along with the raw images and data generated by the ORNL particle layer thickness analysis process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1988

Application of optical correlation techniques to particle imaging velocimetry

Pulsed laser sheet velocimetry yields nonintrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usually MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the partical image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.

Wernet, Mark P.↗
NASA NTRS1984

Structural characterizaiton and gas reactions of small metal particles by high-resolution, in-situ TEM and TED

The existing in-situ transmission electron microscopy (TEM) facility was improved by adding a separately pumped mini-specimen chamber. The chamber contains wire-evaporation sources for three metals and a specimen heater for moderate substrate temperatures. A sample introduction device was constructed, installed, and tested, facilitating rapid introduction of a specimen into the mini-chamber while maintaining the background pressure in that chamber in the 10(-9) millibar range. Small particles and clusters of Pd, grown by deposition from the vapor phase in an in-situ TEM facility on amorphous and crystalline support films of alumina and on ultra-thin carbon films, were analyzed by conventional high-resolution TEM and image analysis in terms of detectability, number density, and size distribution. The smallest particles that could be detected and counted contained no more than 6 atoms; size determinations could be made for particles 1 nm in diameter. The influence of various oxygen plasma treatments, annealing treatments, and of increasing the substrate temperature during deposition was investigated. The TEM technique was employed to demonstrate that under otherwise identica l conditions the lattice parameter of Pd particles in the 1 to 2 nm size range and supported in random orientation on ex-situ prepared mica films is expanded by some 3% when compared to 5 nm size particles. It is believed that this expansion is neither a small-particle diffraction effect nor due to pseudomorphism, but that it is due to a annealing-induced transformation of the small as-deposited particles with predominantly composite crystal structures into larger particles with true f.c.c. structure and thus inherently smaller lattice parameter.

Source record↗
DOE OSTI2021

edxia: Microstructure characterisation from quantified SEM-EDS hypermaps

The characterisation of cement paste microstructure is an important step towards understanding durability mechanisms in cementitious materials. Scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS) is a widely used technique to analyse the microstructure at the micron-scale. However, it is challenging, notably because the characteristic size of many phases is found on a scale smaller than the EDS interaction volume. This work presents a new image analysis framework to identify phases and quantify the microstructure of cementitious materials from SEM-EDS hypermaps. By leveraging domain knowledge, representative points are attributed to phases and mixtures of phases based on ratio plots. Then, quantitative analysis of the microstructure can be carried out (chemical composition, particle size distributions, volume fractions, …). We demonstrate the abilities of the framework, and we present possible applications and extensions of the method. The framework is available as both a graphical interface and a Python code.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Mutagenic effects of a single and an exact number of alpha particles in mammalian cells

One of the main uncertainties in risk estimation for environmental radon exposure using lung cancer data from underground miners is the extrapolation from high- to low-dose exposure where multiple traversal is extremely rare. The biological effects of a single alpha particle are currently unknown. Using the recently available microbeam source at the Radiological Research Accelerator Facility at Columbia University, we examined the frequencies and molecular spectrum of S1- mutants induced in human-hamster hybrid (A(L)) cells by either a single or an exact number of alpha particles. Exponentially growing cells were stained briefly with a nontoxic concentration of Hoechst dye for image analysis, and the location of individual cells was computer-monitored. The nucleus of each cell was irradiated with either 1,2,4, or 8 alpha particles at a linear energy transfer of 90 keV/microm consistent with the energy spectrum of domestic radon exposure. Although single-particle traversal was only slightly cytotoxic to A(L) cells (survival fraction approximately 0.82), it was highly mutagenic, and the induced mutant fraction averaged 110 mutants per 10(5) survivors. In addition, both toxicity and mutant induction were dose-dependent. Multiplex PCR analysis of mutant DNA showed that the proportion of mutants with multilocus deletions increased with the number of particle traversals. These data provide direct evidence that a single a particle traversing a nucleus will have a high probability of resulting in a mutation and highlight the need for radiation protection at low doses.

NASA Discipline Radiation Health↗
NASA NTRS1975

Evaluation of ERTS MSS digital data for monitoring water in the lower Chesapeake Bay area

Water samples collected during the ERTS overpasses of the lower Chesapeake Bay area have been analyzed for chlorophyll, particles, and sediment. Five ERTS images were sufficiently cloud free that a correlation analysis of radiance values from the MSS bands with the water parameters could be performed. A low correlation was established for chlorophyll, except during algal blooms, when band 6 was responsive. There was a fair to good correlation with particles for combinations of band 5, particularly bands (5 minus 6). Sediment correlations were excellent for band 5 or combinations of band 5 with bands 4 and 6. It was evident that such factors as the atmosphere, tide, and different water masses were tending to confuse the data.

Bowker, D. E.↗
NASA NTRS2018

Results of the Aerosol Sampling Experiment on the International Space Station

The indoor air quality of the International Space Station (ISS), in terms of particulate matter, has been assessed through a sampling experiment that collected airborne debris for return to Earth. The Aerosol Sampling Experiment took place on ISS in December 2016 and January 2017, with sample return in February 2017. For redundancy, two different aerosol samplers collected particles in two size ranges spanning from 10 nm to hundreds of micrometers. Multiple analysis techniques have been used to characterize the particles, such as reflective light microscopy, manual scanning electron microscopy (SEM) analysis (secondary and backscattered imaging) with energy dispersive spectroscopy (EDS) x-ray analysis, computer controlled scanning electron microscopy (CCSEM) and Raman spectroscopy. Sampling took place in five locations on ISS, with the greatest deposition of particles in Node 3, followed by Node 1, the US Lab and Node 2. The PMM had very few airborne particles, as expected, owing to the lack of human presence. A large proportion of the sampled material consisted of fibers from clothing. Many particles had complex morphologies or contained multiple metals in a carbonaceous matrix. Metal particles were analyzed for each sampling location in terms of both weight and number percent, with 27 heavy metals detected. Fiberglass and TiO2 particles were present in every location. Quantitative analysis results are presented, and where possible, particle emission sources are identified with the intention to fuel discussions on mitigation.

Meyer, Marit E.↗
DOE OSTI2024

Voltage and temperature effects on low cobalt lithium-ion battery cathode degradation

Degradation of low cobalt lithium-ion cathodes was tested using a full factorial combination of upper cut-off voltage (4.0 V and 4.3 V vs. Li/Li + ) and operating temperature (25 °C and 60 °C). Half-cell batteries were analyzed with electrochemical and microstructural characterization methods. Electrochemical performance was assessed with galvanostatic cycling, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) supported by distribution of relaxation times (DRT) analysis. Electrode microstructure was characterized with scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray absorption near edge structure (XANES) imaging. Higher cut-off voltage cycling shows presence of NiO x formation, a low diffusivity rock-salt phase, in both CV and XRD data. XRD patterns confirmed that the rock-salt phase was beginning to form at the low cut-off voltage at high temperature, but in much lower intensity than at the high cut-off voltage. Higher temperature accelerates degradation processes at both voltages. Degradation factors at high temperature include NiO x formation, cathode material dissolution, and electrolyte decomposition. SEM analysis suggests that supporting phases may isolate and disconnect active material particles reducing capacity retention and battery life cycle. DRT analysis and XANES imaging show that both high temperature samples revealed a NiO x phase based on an increased diffusive impedance and a visible shift in the XANES spectra. The low cut-off voltage, high temperature sample showed a split peak and shift to lower energies indicating early formation of the NiO x phase. The diffusive impedance, which hinders intercalation and deintercalation, is driven by the formation of the NiO x phase. While primarily driven by cut-off voltage, elevated temperature also contributes to this degradation mechanism.

electrochemical impedance spectroscopy↗
NASA NTRS2000

Convective Melting of Particles in Flow Under Microgravity Conditions

Study of melting of dispersed or packed solid particles in a fluid under gravity and microgravity conditions provides benchmark information for many engineering applications such as material processing, environmental assessment and protection and space fire protection. During such processes, packed or dispersed solid particles are interacting with fluid flow at above-melting temperatures. By unmasking the buoyancy effects in coupled flow, phase change and heat transport phenomena, a better understanding of melting rate in non-thermal equilibrium, convective conditions can be studied. A series of flight experiments were conducted onboard the NASA KC-135 Microgravity Research Airplane. The Particle Melting in Plow (PMF) module was designed to allow flow through the initially packed ice particles at controlled temperature and velocity. To achieve this, a close-loop flow system was designed. Video images were taken to record the visualization of the melting process, from which a time variation of packed particle thickness distribution at different times can be obtained by the image analysis method. The fluid temperature distribution within the melting zone is measured by thermocouples. An infrared camera was mounted from the top of the test section to record the ice-water thermal images at a given location. The results from thermal images yield local temperature variation between melting solid and liquid and local Stephan number. Typical results for a number of cases are presented. The mathematical model, describing mass, energy, and momentum balance equations for the liquid and solid phases, is presented. It is found that melting rate is influenced mainly by the ratio of Reynolds number (based on the initial particle diameter) to the Froud number, and Stephan number. At the absence of gravity, Froud number approaches zero, Reynolds number and Stephan number become dominant factors governing the melting rate. The numerically determined results are compared with the experimental ones. It is found that the discrepancy between the predicted and measured melting rate is largely due to the inaccuracy in the constitutive equations for effective thermal physical properties, such as effective thermal conductivity and diffusivity, and transport properties, such as particle interaction coefficient, and local heat transfer coefficient of particles.

Stewart, C.↗