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At least 217 records · Page 12

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↗

Reducing Zinc Redistribution and Extending Cycle Life Via Electrochemical Synthesis of Zinc/Zinc Oxide Anodes in Rechargeable Alkaline Batteries

Redistribution of zinc over the electrode surface, also known as shape change, is a major problem and a cause of failure in alkaline zinc anode batteries. To mitigate this phenomenon, we propose a scalable approach based on an in situ formed, highly porous electrochemically synthesized ZnO matrix with uniformly electrodeposited zinc particles. This results in ∼70% improvement in cycle life performance at a rate of 10 mA cm −2 compared to control Zn anodes, which have not gone through the formation process. A quantitative electrolyte analysis revealed under-saturated zincate ion concentration in the electrochemically synthesized ZnO/Zn cells indicating reduced zincate movement. Post mortem analysis of the anodes indicated higher retention of both Zn and ZnO on the electrochemically synthesized ZnO anodes signifying reduced redistribution of active material. Image analysis of the cycled anodes revealed a narrower Zn particle size distribution (62−79 μ m) in contrast to a wider particle size distribution of 51–96 μ m observed in the control anodes. The formation approach results in electrochemically synthesized ZnO/Zn anodes providing a stable ZnO matrix in which Zn particles retain their localized distribution on cycling better than control electrodes conventionally made by pasting zinc particles together with a binder.

Kolhekar, Snehal (ORCID:0000000210321153)↗

Motion of near-neutrally buoyant tracers in vortical flows

An analysis of the motion of particles of arbitrary density and size in solid body and potential vortex flows is presented. The study provides a basis for precise, quantitative reduction of tracer-particle visualization of such flows in water tunnels.

Charwat, A. F.↗

Infrared imaging of the coma of Comet Wilson

The brightness of the nuclear condensation noted in March 13-15, 1987 thermal IR images of Comet Wilson did not vary, in contrast to Comet Halley's behavior; a dynamical analysis of the dust coma/tail structure establishes that the particle size distribution in this comet, while different from that of Comet Giacobini-Zinner, is nevertheless more similar to that in Comet Halley. The nonisotropic character of the dust ejection is taken to be evidence for prograde rotation of the nucleus, and it is speculated that Comet Wilson is too young to have developed a dust mantle; this would account for the lack of short time scale variability.

Campins, Humberto↗

Integrated fiber optic probe for dynamic light scattering

An integrated fiber optic probe, comprising a monomode optical fiber fusion spliced to a short length of a graded-index multimode fiber, is fabricated for use as a coherent receiver in dynamic light scattering. The multimode fiber is cleaved to provide a gradient-index fiber lens with a focal length of 125 microns and an f-number close to unity. An integrated fiber receiver is used to measure the intensity-intensity autocorrelation data from a 0.05 percent by weight concentration of an aqueous suspension of polystyrene latex spheres. Analysis of 100 independent data sets indicates that the particle size can be recovered with an accuracy of +/- 1 percent.

Dhadwal, Harbans S.↗

Stardust Curation at Johnson Space Center: Photo Documentation and Sample Processing of Submicron Dust Samples from Comet Wild 2 for Meteoritics Science Community

Dust particles released from comet 81P/Wild-2 were captured in silica aerogel on-board the STARDUST spacecraft and successfully returned to the Earth on January 15, 2006. STARDUST recovered thousands of particles ranging in size from 1 to 100 micrometers. The analysis of these samples is complicated by the small total mass collected ( < 1mg), its entrainment in the aerogel collection medium, and the fact that the cometary dust is comprised of submicrometer minerals and carbonaceous material. During the six month Preliminary Examination period, 75 tracks were extracted from the aerogel cells , but only 25 cometary residues were comprehensively studied by an international consortium of 180 scientists who investigated their mineralogy/petrology, organic/inorganic chemistry, optical properties and isotopic compositions. These detailed studies were made possible by sophisticated sample preparation methods developed for the STARDUST mission and by recent major advances in the sensitivity and spatial resolution of analytical instruments.

Nakamura-Messenger, K.↗

Evaluation and Windspeed Dependence of MODIS Aerosol Retrievals Over Open Ocean

The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the MODIS aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing MODIS Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that MODIS is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and Aqua, respectively. Angstrom Exponent comparisons show a high correlation between MODIS retrievals and shipboard measurements (R= 0.85 Terra, 0.83 Aqua), although the MODIS aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and Aqua ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that Aqua agreement with AERONET is marginally better. However we cannot claim based on the current study that the better Aqua comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and Aqua retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process.

Kleidman, Richard G.↗

Analytical multiple scattering correction to the Mie theory: Application to the analysis of the lidar signal

The contribution of the multiple scattering to the lidar signal is dependent on the optical depth tau. Therefore, the radar analysis, based on the assumption that the multiple scattering can be neglected is limited to cases characterized by low values of the optical depth (tau less than or equal to 0.1) and hence it exclude scattering from most clouds. Moreover, all inversion methods relating lidar signal to number densities and particle size must be modified since the multiple scattering affects the direct analysis. The essential requests of a realistic model for lidar measurements which include the multiple scattering and which can be applied to practical situations follow. (1) Requested are not only a correction term or a rough approximation describing results of a certain experiment, but a general theory of multiple scattering tying together the relevant physical parameter we seek to measure. (2) An analytical generalization of the lidar equation which can be applied in the case of a realistic aerosol is requested. A pure analytical formulation is important in order to avoid the convergency and stability problems which, in the case of numerical approach, are due to the large number of events that have to be taken into account in the presence of large depth and/or a strong experimental noise.

Flesia, C.↗

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↗

Particle size and velocity measurement by laser anemometry

The use of a forward scattering Laser Anemometer system for the measurement of particle diameters larger than the fringe spacing is investigated. A systematic calibration experiment demonstrates a direct relationship between signal amplitude and particle diameter for transparent particles between 30 microns and 240 microns in diameter. A light scattering analysis confirms these measurements and indicates how the range of particles which can be measured using the peak (mean) signal depends on the optical arrangement and particle properties. On the basis of this work a real time Laser Anemometer signal processor is modified so that the peak of the mean of each signal can be measured. A method of correcting data for the effect of particles which do not go through the center of the measurement volume is derived. Good agreement is found between particle size distributions measured in sprays by using the Laser Anemometer and size distributions measured by collecting the particles on a slide and using an image analysis computer.

Yule, A. J.↗

Impact of particle size and particle-flow-wall coupling on pressurized oxy-combustion in the down-fired burner

Concerns over climate change have led to numerous efforts in developing low-carbon energy technologies. Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Designing an effective burner plays a vital role in developing new coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the burner of a pressurized oxy-combustor is close or even higher than the maximum limit that commercial CFD codes (e.g., ANSYS FLUENT) can handle. At this high particle volume fraction, the interactions among particles, fluid flow, and wall need to be re-evaluated. The present computational work is the first step of a systematic analysis of the particle influence, like releasing method, releasing locating, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In a POC process, pulverized coal is burned under elevated pressure and O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing ANSYS FLUENT, using Reynolds-averaged Navier-Stokes (RANS) modeling. It is revealed that for this pilot-scale, pressurized burner, velocity profiles of the near-wall region in this POC facility exhibit some discrepancy against the near-wall turbulent flow velocity profile. In order to investigate the particle influence in the near-wall region, particle releasing location will be investigated. Numerical simulation results exhibit the coupling effect of turbulence flow and particles in this case. The particle size also demonstrates a great effect on particle trajectory, then further has an impact on flame stability and temperature.

Li, Lei↗

Cloud microphysics - Analysis of the clouds of Earth, Venus, Mars, and Jupiter

The probable microphysics of a cloud is deduced by a described method which requires information on cloud particle mean size, composition, number density, and atmospheric structure, but does not require any additional information. The analysis is applied to the sulfuric acid clouds of Venus, the water ice and dust clouds of Mars, and the ammonia-water and ammonia ice clouds of Jupiter. The Venus cloud layer is found to have some resemblance to smog and haze layers on earth. The water ice clouds on Mars resemble tenuous nonprecipitating cirrus clouds on earth. Precipitation, vertical distribution of gases, and vertical transport of heat in the clouds on Jupiter are considered.

Rossow, W. B.↗

Properties of different LLM-105 preparations

LLM-105 (2,6-diamino-3,5-dinitropyrazine-1-oxide) has been prepared at several different size quantities (~10–70 Kg) and not subjected to further purification, such as recrystallization. Chemical and physical properties were compared—small-scale safety testing (impact, friction, ESD), thermal (chemical reactivity, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), one-dimensional time-to-explosion (ODTX)), morphological (particle-size distribution (PSD), scanning electron microscopy (SEM), powder x-ray diffraction (PXRD), skeletal density). Each preparation had similar properties to the other preparations except for PSD and PXRD. For PSD, all preparations exhibited a mono-modal distribution with a variation in median values from ~ 40 μm to over 80 μm. All PXRD values indicated the same morphology with minor variations in crystal orientations. Possible polymorphism was also observed in a few cases. SEM images and PXRD indicate all preparations to be diamond-type and X-type crystals with some twinning. Impact, friction, and ESD and thermal sensitivities values are consistent with these type of crystal habits as seen in vast literature studies.

Explosive characterization↗

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↗

Field intercomparison of ice nucleation measurements: the Fifth International Workshop on Ice Nucleation Phase 3 (FIN-03)

Abstract. The third phase of the Fifth International Ice Nucleation Workshop (FIN-03) was conducted at the Storm Peak Laboratory in Steamboat Springs, Colorado, in September 2015 to facilitate the intercomparison of instruments measuring ice-nucleating particles (INPs) in the field. Instruments included two online and four offline measurement systems for INPs, which are a subset of those utilized in the laboratory study that comprised the second phase of FIN (FIN-02). The composition of the total aerosols was characterized using the Particle Analysis by Laser Mass Spectrometry (PALMS) and Wideband Integrated Bioaerosol Sensor (WIBS) instruments, and aerosol size distributions were measured by a laser aerosol spectrometer (LAS). The dominant total particle compositions present during FIN-03 were composed of sulfates, organic compounds, and nitrates, as well as particles derived from biomass burning. Mineral-dust-containing particles were ubiquitous throughout and represented 67 % of supermicron particles. Total WIBS fluorescing particle concentrations for particles with diameters of > 0.5 µm were 0.04 ± 0.02 cm−3 (0.1 cm−3 highest; 0.02 cm−3 lowest), typical of the warm season in this region and representing ≈ 9 % of all particles in this size range as a campaign average. The primary focus of FIN-03 was the measurement of INP concentrations via immersion freezing at temperatures > −33 °C. Additionally, some measurements were made in the deposition nucleation regime at these same temperatures, representing one of the first efforts to include both mechanisms within a field campaign. INP concentrations via immersion freezing agreed within factors ranging from nearly 1 to 5 times on average between matched (time and temperature) measurements, and disagreements only rarely exceeded 1 order of magnitude for sampling times coordinated to within 3 h. Comparisons were restricted to temperatures lower than −15 °C due to the limits of detection related to sample volumes and very low INP concentrations. Outliers of up to 2 orders of magnitude occurred between −25 and −18 °C; a better agreement was seen at higher and lower temperatures. Although the 5–10 factor agreement of INP measurements found in FIN-03 aligned with the results of the FIN-02 laboratory comparison phase, giving confidence in progress of this measurement field, this level of agreement still equates to temperature uncertainties of 3.5 to 5 °C that may not be sufficient for numerical cloud modeling applications that utilize INP information. INP activity in the immersion-freezing mode was generally found to be an order of magnitude or more, making it more efficient than in the deposition regime at 95 %–99 % water relative humidity, although this limited data set should be augmented in future efforts. To contextualize the study results, an assessment was made of the composition of INPs during the late-summer to early-fall period of this study inferred through comparison to existing ice nucleation parameterizations and through measurement of the influence of thermal and organic carbon digestion treatments on immersion-freezing ice nucleation activity. Consistent with other studies in continental regions, biological INPs dominated at temperatures of > −20 °C and sometimes colder, while arable dust-like or other organic-influenced INPs were inferred to dominate below −20 °C.

54 ENVIRONMENTAL SCIENCES↗

Automated Particle Analysis of Hanford Tank Wastes 241-AN-106, 241-AN-101, and 241-AW-105

This effort is involved in developing particle size and density distribution (PSDD) for the major phases within Hanford tank waste sludge. The object of this work has been to use automated particle analysis (APA) methods on the Scanning Electron Microscope (SEM) to provide PSDDs. The PSDD can be used to quantify the proportion of gibbsite particles likely to settle quickly and enable blending of wastes that may be prone to pipeline plugging such as the uranium phase, clarkeite with other wastes. The Hanford tank waste solids were analyzed with SEM combined with x-ray Energy Dispersive Spectroscopy (EDS) using APA. This method can allow thousands of individual particles to be characterized and so may provide a more representative view of the samples and information PSDDs. We characterized several as-received sludge samples and developed PSDD with APA. Sample preparation methods were found to impact the collected results, as it was more difficult to collect representative samples of the larger particles. Much of the material was also dried and cemented together that further impacted results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Gas Dynamics, Characterization, and Calibration of Fast Flow Flight Cascade Impactor Quartz Crystal Microbalances (QCM) for Aerosol Measurements

During recent high altitude flights, we have tested the aerosol section of the fast flow flight cascade impactor quartz crystal microbalance (QCM) on loan to Howard University from NASA. The aerosol mass collected during these flights was disappointingly small. Increasing the flow through the QCM did not correct the problem. It was clear that the instrument was not being operated under proper conditions for aerosol collect ion primarily because the gas dynamics is not well understood. A laboratory study was therefore undertaken using two different fast flow QCM's in an attempt to establish the gas flow characteristics of the aerosol sections and its effect on particle collection, Some tests were made at low temperatures but most of the work reported here was carried out at room temperature. The QCM is a cascade type impactor originally designed by May (1945) and later modified by Anderson (1966) and Mercer et al (1970) for chemical gas analysis. The QCM has been used extensively for collecting and sizing stratospheric aerosol particles. In this paper all flow rates are given or corrected and referred to in terms of air at STP. All of the flow meters were kept at STP. Although there have been several calibration and evaluation studies of moderate flow cascade impactors of less than or equal to 1 L/rein., there is little experimental information on the gas flow characteristics for fast flow rates greater than 1 L/rein.

Grant, J.R.↗

Impacts of the Conductive Networks on Solid‐State Battery Operation

The micromorphology of composite cathodes is known to play a vital role in determining all-solid-state battery (ASSB) performance. However, much of our current understanding is derived from empirical observations, lacking a deeper mechanistic foundation. The “rocking chair” concept of battery chemistry requires maintaining charge neutrality, emphasizing the necessity of examining electrode micromorphology from the perspective of conductive networks. This study systematically investigates the microscopic electrochemical impacts of conductive network micromorphology by varying the Li + -to-e − channel ratio in cathodes comprising LiNbO 3 -coated LiNi 0.8 Co 0.1 Mn 0.1 O 2 , Li 6 PS 5 Cl, and carbon fibers. Utilizing multiscale synchrotron-based spectro-microscopy, we unravel that unbalanced Li + and e − conducting channels intensify charge polarization within active cathode particles and accelerate their degradation. A further model system with X-ray nano-tomography resolved e − and Li + channels indicates that spatially uniform and well-paired Li + and e − conducting channels are highly desirable as they could promote more uniform lithiation/delithiation, mitigating microscopic electrochemical polarization. Electrode-scale X-ray holotomography analysis reveals that the impact of conductive networks is particle-size-dependent, with smaller cathode particles being more significantly affected. These findings provide mechanistic insights into the interplay between conductive networks and all-solid-state battery operation, laying the groundwork for rational design and optimization of cathode architectures in future solid-state battery technologies.

36 MATERIALS SCIENCE↗