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At least 145 records · Page 8

Exploring the Production of NOx by Lightning and Its Impact on Tropospheric Ozone

Our quantitative understanding of free tropospheric (FT) chemistry is quite poor. State-of-the-art regional air quality models (e.g., US EPA's CMAQ) perform very poorly in simulating FT chemistry, with Uniform ozone around 70 ppb throughout the FT in summer, while ozonesonde data show much higher levels of ozone and much spatial-temporal structure. Such models completely neglect lightning-NOx (LNOx) emissions (the most significant source of NOx in the FT), and also contain large uncertainties in the specifications of intercontinental transport, stratosphere-troposphere exchange (STE) and PBLFT exchange (PFTE). Global air chemistry models include LNOx, but in very crude fashion, with the frequency and distribution of lightning being based on modeled cloud parameters (hence large uncertainty), lightning energetics being assumed to be constant for all flashes (literature value, while in reality there is at least a two-orders of magnitude variability from flash-to-flash), and the production of NOx in the surrounding heated air, per Joule of heating, being assumed to be constant also (literature value, while in fact it is a non-linear function of the dissipated heat and local air density, p). This situation is commonly blamed on paucity of pertinent observational data, but for the USA, there is now a wealth of surface- and satellite-based data of lightning available to permit much improved observation-based estimation of LNOx emissions. In the FT, such NOx has a long residence time, and also the ozone production efficiency from NOx there is considerably higher than in the PBL. It is, therefore, of critical importance in FT chemistry. This paper will describe the approach and data products of an ongoing NSSTC project aimed at a much-improved quantification of not only LNOx production on the scale of continental USA based on local and regional lightning observations, but also of intercontinental transport, STE and PFTE, all in upgraded simulations of tropospheric transport and chemistry. In our approach for LNOx, (a) we utilize continuous observed lightning information from the NLDN ground network and from satellite imagers (OTD and LIS) to quantify lightning frequency and distribution at the spatial-temporal scales of models such as CMAQ; (b) we develop new methodologies to quantify flash-specific lightning energy dissipation as heat (epsilon) using data from the research-grade lightning measurement facility at NASA-KSC, and to parameterize epsilon based on regional lightning monitoring data (ground- and satellite-based); and, (c) we develop a new parameterization of NOx production as a function of epsilon and rho. Based on such observation-based information, we are working to develop a gridded, episodic LNOx emissions inventory for the USA for use in models like CMAQ. We are also developing approaches for global(MOZART)- regional(CMAQ) chemistry coupling to improve intercontinental transport and STE. Finally, we are developing new methodologies for assimilation of satellite-observed (GOES) clouds into meteorological modeling (MM5), to improve PFTE and to optimize co-location of cloud convection and observed lightning. We will incorporate these improvements in CMAQ simulations over the USA to better understand FT processes and chemistry, and its impact on ground-level ozone.

Gillani, Noor↗

A Novel Framework to Project the Permafrost Fate With Explicit Quantification of Soil Property and Future Climate Uncertainties

This study develops a novel general framework to project the permafrost fate with rigorous uncertainty quantification to assess dominant sources. Borehole temperature records from three sites in the Russian western Arctic are used to constrain the uncertainty of a high‐fidelity freeze‐thaw model. Projections from 9 Global Climate Models (GCM) are stochastically downscaled to generate future trajectories of surface ground heat flux. Under the two emission scenarios SSP2‐4.5 and SSP5‐8.5, the projected average thawing depths by 2100 vary from 0.4 to 14.4 m or 2.1 to 17.7 m, and the increase in the top 10 m average temperature from 2015 to 2100 is 1.2–2.7°C or 1.9–3.0°C. The results show that the freeze‐thaw model uncertainty can sometimes dominate over that of GCM outputs, calling for site‐specific information to improve model accuracy. The framework is applicable for understanding permafrost degradation and related uncertainties at larger scales.

Bayesian downscaling↗

Implementing Recommendations of the Columbia Accident Investigation Board: Development of On-Orbit IR Thermography

One of NASA's Space Shuttle Return-to-Flight (RTF) efforts has been to develop thermography for the on-orbit inspection of the Reinforced Carbon Carbon (RCC) portion of the Orbiter Wing Leading Edge (WLE). This paper addresses the capability of thermography to detect cracks in RCC by using in-plane thermal gradients that naturally occur on-orbit. Crack damage, which can result from launch debris impact, is a detection challenge for other on-orbit sensors under consideration for RTF, such as the Intensified Television Camera and Laser Dynamic Range Imager. We studied various cracks in RCC, both natural and simulated, along with material characteristics, such as emissivity uniformity, in steady-state thermography. Severity of crack, such as those likely and unlikely to cause burn through were tested, both in-air and in-vacuum, and the goal of this procedure was to assure crew and vehicle safety during reentry by identification and quantification of a damage condition while on-orbit. Expected thermal conditions are presented in typical shuttle orbits, and the expected damage signatures for each scenario are presented. Finally, through statistical signal detection, our results show that even at very low in-plane thermal gradients, we are able to detect damage at or below the threshold for fatality in the most critical sections of the WLE, with a confidence exceeding 1 in 10,000 probability of false negative.

Ottens, Brian P.↗

OPAD through 1991 - Status report no. 2

The Optical Plume Anomaly Detection (OPAD) experimental program has attempted to develop a rocket engine health monitor for the detection, and if possible the quantification, of anomalous atomic and molecular species in exhaust plumes. The test program has formulated instrument designs allowing both wide spectral range and high spectral resolution. Attention is presently given to OPAD data collected for the SSME at NASA-Marshall's technology test stand, with a view to spectral emissions at startup and variations in baseline plume emissions due to changes in rated power level.

Powers, W. T.↗

Implementing Recommendations of the Columbia Accident Investigation Board - Development of on-Orbit RCC Thermography

One of NASA s Space Shuttle Return-to-Flight (RTF) efforts has been to develop thermography for the on-orbit inspection of the Reinforced Carbon Carbon (RCC) portion of the Orbiter Wing Leading Edge (WLE). This paper addresses the capability of thermography to detect cracks in RCC by using in-plane thermal gradients that naturally occur on-orbit. Crack damage, which can result from launch debris impact, is a detection challenge for other on-orbit sensors under consideration for RTF, such as the Intensified Television Camera and Laser Dynamic Range Imager. We studied various cracks in RCC, both natural and simulated, along with material characteristics, such as emissivity uniformity, in steady-state thermography. Severity of crack, such as those likely and unlikely to cause burn through were tested, both in-air and in-vacuum, and the goal of this procedure was to assure crew and vehicle safety during re-entry by identification and quantification of a damage condition while on-orbit. Expected thermal conditions are presented in typical shuttle orbits, and the expected damage signatures for each scenario are presented. Finally, through statistical signal detection, our results show that even at very low in-plane thermal gradients, we are able to detect damage at or below the threshold for fatality in the most critical sections of the WLE, with a confidence exceeding 1 in 10,000 probability of false negative.

Ottens, Brian↗

Improved representation of the global dust cycle using observational constraints on dust properties and abundance

Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of 2 relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with a geometric diameter up to 20 µm (PM20) is approximately 5000 Tg yr−1, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded datasets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this dataset is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

Dust cycle↗

Aura OMI Observations of Global SO2 and NO2 Pollution from 2005 to 2013

The Ozone Monitoring Instrument (OMI), a NASA partnership with the Netherlands and Finland, flies on the NASA Aura satellite and uses reflected sunlight to measure the two critical atmospheric trace gases: nitrogen dioxide (NO2) and sulfur dioxide (SO2) characterizing daily air quality. Both gases and the secondary pollutants they produce (particulate matter, PM2.5, and tropospheric ozone) are USEPA designated criteria pollutants, posing serious threats to human health and the environment (e.g., acid rain, plant damage and reduced visibility). Our group at NASA GSFC has developed and maintained OMI standard SO2 and NO2 data products. We have recently released an updated version of the standard NO2 L2 and L3 products (SP v2.1) and continue improving the algorithm. We are currently in the process of releasing next generation pollution SO2 product, based on an innovative Principal Component Analysis (PCA) algorithm, which greatly reduces the noise and biases. These new standard products provide valuable datasets for studying anthropogenic pollution on local to global scales. Here we highlight some of the OMI observed changes in air quality over several regions. Over the US average NO2 and SO2 pollution levels had decreased dramatically as a result of both technological improvements (e.g., catalytic converters on cars) and stricter regulations of emissions. We see continued decline in pollution over Europe. Over China OMI observed an increase of about 60 percent in NO2 pollution between 2005 and 2013, despite a temporal reversal of the growing trend due to both 2008 Olympic Games and the economic recession in 2009. Chinese SO2 pollution seems to have stabilized since peaking in 2007, probably due to government efforts to curb SO2 emissions from the power sector. We have also observed large increases in both SO2 and NO2 pollution particularly in Eastern India where a number of large new coal power plants had been built in recent years. We expect that further improvements in the OMI NO2 and SO2 products will allow more robust quantification of long-term trends in global air quality.

SO2↗

Improved Representation of the Global Dust Cycle Using Observational Constraints on Dust Properties and Abundance

Even though desert dust is the most abundant aerosol by mass in Earth’s atmosphere, atmospheric models 25 struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused byfundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, 30 extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global 35 basis, we find that the emission flux of dust with geometric diameter up to 20 μm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current 40 model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

aerosols, dust↗

Baselining the Indirect Effect by Improving Quantification of Sea Spray and Marine Sources at Ascension Island (Final Report)

Oceans cover two-thirds of the Earth and understanding the interactions of aerosols with clouds in these large marine regions requires quantifying the man-made contributions to the budget of cloud-drop forming particles (known as cloud condensation nuclei, or CCN) relative to the non-manmade “baseline” conditions and understanding the meteorology of boundary layer clouds. Modeling studies have shown substantial uncertainties and sensitivities to natural marine CCN sources, meaning that to reduce uncertainties in indirect effects we must be able to better quantify the CCN budget in ocean regions. While models provide important constraints on these uncertainties, actually reducing uncertainties requires substantial observations in open-ocean and coastal regions in order to establish the baseline on which manmade emissions are added. The tropical South Atlantic Ocean is one of the least-sampled regions of the planet, making the comprehensive measurements of the Department of Energy Atmospheric Radiation Measurement Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign provides the longest record of aerosol size distribution measurements from a differential mobility analyzer in a cloud-influenced marine location in the ARM database, with 17 months of ground-based aerosol size distribution measurements. This project addressed the research topic of Aerosol-Cloud Interactions (ACI) by supporting three publications from the LASIC measurements: 1. The ARM measurements were combined with a new value-added technique that was pioneered by the Russell group for quantifying sea salt. This quantification of sea salt uses supermicron scattering measurements for retrieving reasonable sea spray mass concentrations, providing the best-available, observationally-constrained estimate of the sea spray mode properties when supermicron size distribution measurements are not available. 2. The fitted modes of the distribution were used to investigate the signatures of cloud processing for very clean to very smoky aerosol conditions, revealing not only differences in the particles that activate in clouds but also in the mechanisms that control that droplet formation process. In clean air, the size required to form a cloud droplet is influenced by the number of particles, as well as how quickly particles take up water during growth in cloud. 3. Building on this aerosol characterization, cloud and meteorological conditions were used to evaluate aerosol-related changes in cloud albedo and optical depth. We introduced a new method of decomposing the impact of aerosols on clouds known as the Twomey effect by incorporating retrieved supersaturation from two independent sets of observations to constrain the feedback of aerosol particles on cloud properties. The method quantifies the reduction of the Twomey effect at high aerosol concentrations, which has never been explained quantitatively by observations. In addition, the results provide the first direct validation for the conditions observed in the tropical South Atlantic of a parcel-based approach that is embedded in many climate models. Together these findings illustrate how ARM extended field campaigns in stratocumulus-covered regions can be used to constrain ACI processes with direct observations, providing specific radiative effects without models. By making such process-specific constraints available to improve ACI in global climate models, ARM observations play a key role in supporting model development.

58 GEOSCIENCES↗

Structured light approaches in laser-based plasma diagnostics

There is a growing demand for plasma diagnostics suitable for industrial plasma reactors employed in semiconductor nanofabrication, especially relevant to microelectronics and quantum information systems. Such reactors typically have limited optical access and pose considerable diagnostic challenges, including intense background emission, significant thermal loads, and contamination of optical viewports. In this study, we outline research into structured light techniques (laser beams with tailored spatial, temporal, or phase characteristics) that effectively overcome these issues using laser-induced fluorescence (LIF) as an example. The focus of presented diagnostics is on ion kinetics analysis within an industrial plasma source, although this approach is broadly applicable to other plasma systems and diagnostic contexts. We present a confocal LIF implementation using an axicon-generated Bessel annular beam, achieving spatial resolutions of approximately 5 mm at a focal distance of 300 mm, with potential improvements to about 1 mm. This approach matches conventional orthogonal LIF performance but requires only one optical port. Wavelength-modulation LIF employs nonlinear laser wavelength tuning to measure spectral line derivatives, suppressing background emission and enhancing details of spectral line shape. Additionally, we present new results on applying vortex beams (laser beams carrying orbital angular momentum, OAM) for LIF measurements in an industrial plasma device. These measurements enable simultaneous axial and tangential velocity determination using a single laser beam and have been tested with xenon ion transition. Initial quantification of results was performed. Together, these structured-light approaches provide robust, background-resilient, multi-dimensional diagnostics for complex plasma environments.

Romadanov, Ivan [Princeton Plasma Physics Laborato↗

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗

Data and code for Daily and Multi-Day Extreme Rainfall Analysis Under Future Climates Using Stochastic Storm Transposition and NEX-GDDP-CMIP6 Over CONUS

This data package provides inputs, codes, and outputs for a comprehensive analysis of projected changes in extreme precipitation across 10 regions of the continental United States, using 34 downscaled Earth System Models (ESMs) from the NASA Earth Exchange Global Daily Downscaled Projections, Coupled Model Intercomparison Project Phase 6 (NEX-GDDP-CMIP6) dataset. These models are part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), a coordinated climate modeling framework widely used to assess climate change impacts. The analysis applies a stochastic storm transposition method to quantify changes in extreme rainfall under two Shared Socioeconomic Pathway (SSP) climate scenarios—SSP2-4.5 (moderate emissions) and SSP5-8.5 (high emissions)—compared to historical conditions (1995–2014 vs. 2081–2100). The dataset includes rainfall depth estimates for extreme events with return periods from 2 to 500 years across multiple storm durations (1, 3, and 5 days) for each of the 10 U.S. regions. Weighted ensemble statistics are derived from individual ESM performance against historical precipitation patterns, enabling robust uncertainty quantification through both sign-based and permutation-test-based model agreement assessments. Key analyses address: (1) relative changes in extreme precipitation for each climate scenario, (2) differences between SSP scenarios (SSP5-8.5 vs. SSP2-4.5), (3) contrasts between rare and frequent events, and (4) variations between multi-day and daily storm durations. The workflow produces ensemble statistics—median, 5th, 25th, 75th, and 95th percentiles—along with model agreement metrics that identify regions and event types with robust climate change signals. The dataset includes: processed rainfall depth outputs (netCDF format) from the RainyDay Python package, ESM weights from historical performance evaluation using DayMet observations, ensemble statistics across all storm dimensions, and figures summarizing key findings.

54 ENVIRONMENTAL SCIENCES↗

Quantification of Energy Release in Composite Structures

Energy release rate is usually suggested as a quantifier for assessing structural damage tolerance. Computational prediction of energy release rate is based on composite mechanics with micro-stress level damage assessment, finite element structural analysis and damage progression tracking modules. This report examines several issues associated with energy release rates in composite structures as follows: Chapter I demonstrates computational simulation of an adhesively bonded composite joint and validates the computed energy release rates by comparison with acoustic emission signals in the overall sense. Chapter II investigates the effect of crack plane orientation with respect to fiber direction on the energy release rates. Chapter III quantifies the effects of contiguous constraint plies on the residual stiffness of a 90 deg ply subjected to transverse tensile fractures. Chapter IV compares ICAN and ICAN/JAVA solutions of composites. Chapter V examines the effects of composite structural geometry and boundary conditions on damage progression characteristics.

Minnetyan, Levon↗

Quantification of Energy Release in Composite Structures

Energy release rate is usually suggested as a quantifier for assessing structural damage tolerance. Computational prediction of energy release rate is based on composite mechanics with micro-stress level damage assessment, finite element structural analysis and damage progression tracking modules. This report examines several issues associated with energy release rates in composite structures as follows: Chapter I demonstrates computational simulation of an adhesively bonded composite joint and validates the computed energy release rates by comparison with acoustic emission signals in the overall sense. Chapter II investigates the effect of crack plane orientation with respect to fiber direction on the energy release rates. Chapter III quantifies the effects of contiguous constraint plies on the residual stiffness of a 90 ply subjected to transverse tensile fractures. Chapter IV compares ICAN and ICAN/JAVA solutions of composites. Chapter V examines the effects of composite structural geometry and boundary conditions on damage progression characteristics.

Minnetyan, Levon↗

Characterization of Material Response During Arc-Jet Testing with Optical Methods Status and Perspectives

The characterization of ablation and recession of heat shield materials during arc jet testing is an important step towards understanding the governing processes during these tests and therefore for a successful extrapolation of ground test data to flight. The behavior of ablative heat shield materials in a ground-based arc jet facility is usually monitored through measurement of temperature distributions (across the surface and in-depth), and through measurement of the final surface recession. These measurements are then used to calibrate/validate materials thermal response codes, which have mathematical models with reasonably good fidelity to the physics and chemistry of ablation, and codes thus calibrated are used for predicting material behavior in flight environments. However, these thermal measurements only indirectly characterize the pyrolysis processes within an ablative material pyrolysis is the main effect during ablation. Quantification of pyrolysis chemistry would therefore provide more definitive and useful data for validation of the material response codes. Information of the chemical products of ablation, to various levels of detail, can be obtained using optical methods. Suitable optical methods to measure the shape and composition of these layers (with emphasis on the blowing layer) during arc jet testing are: 1) optical emission spectroscopy (OES) 2) filtered imaging 3) laser induced fluorescence (LIF) and 4) absorption spectroscopy. Several attempts have been made to optically measure the material response of ablative materials during arc-jet testing. Most recently, NH and OH have been identified in the boundary layer of a PICA ablator. These species are suitable candidates for a detection through PLIF which would enable a spatially-resolved characterization of the blowing layer in terms of both its shape and composition. The recent emission spectroscopy data will be presented and future experiments for a qualitative and quantitative characterization of the material response of ablative materials during arc-jet testing will be discussed.

Winter, Michael↗

Harmonizing tau positron emission tomography in Alzheimer's disease: The CenTauR scale and the joint propagation model

Abstract INTRODUCTION Tau‐positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis. METHODS Using head‐to‐head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed “CenTauR” [CTR]). JPM is a statistical model that simultaneously models the relationships between head‐to‐head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale. RESULTS A strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach. DISCUSSION Preliminary findings using the JPM support the development and adoption of a universal scale for tau‐PET quantification. Highlights Tested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed “CenTauRs”. Tested a Centiloid‐like linear regression approach. Using five cohorts with head‐to‐head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.

Neurosciences & Neurology↗

X-Ray Microanalysis and Electron Energy Loss Spectrometry in the Analytical Electron Microscope: Review and Future Directions

This paper reviews and discusses future directions in analytical electron microscopy for microchemical analysis using X-ray and Electron Energy Loss Spectroscopy (EELS). The technique of X-ray microanalysis, using the ratio method and k(sub AB) factors, is outlined. The X-ray absorption correction is the major barrier to the objective of obtaining I% accuracy and precision in analysis. Spatial resolution and Minimum Detectability Limits (MDL) are considered with present limitations of spatial resolution in the 2 to 3 microns range and of MDL in the 0.1 to 0.2 wt. % range when a Field Emission Gun (FEG) system is used. Future directions of X-ray analysis include improvement in X-ray spatial resolution to the I to 2 microns range and MDL as low as 0.01 wt. %. With these improvements the detection of single atoms in the analysis volume will be possible. Other future improvements include the use of clean room techniques for thin specimen preparation, quantification available at the I% accuracy and precision level with light element analysis quantification available at better than the 10% accuracy and precision level, the incorporation of a compact wavelength dispersive spectrometer to improve X-ray spectral resolution, light element analysis and MDL, and instrument improvements including source stability, on-line probe current measurements, stage stability, and computerized stage control. The paper reviews the EELS technique, recognizing that it has been slow to develop and still remains firmly in research laboratories rather than in applications laboratories. Consideration of microanalysis with core-loss edges is given along with a discussion of the limitations such as specimen thickness. Spatial resolution and MDL are considered, recognizing that single atom detection is already possible. Plasmon loss analysis is discussed as well as fine structure analysis. New techniques for energy-loss imaging are also summarized. Future directions in the EELS technique will be the development of new spectrometers and improvements in thin specimen preparation. The microanalysis technique needs to be simplified and software developed so that the EELS technique approaches the relative simplicity of the X-ray technique. Finally, one can expect major improvements in EELS imaging as data storage and processing improvements occur.

Goldstein, J. I.↗