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At least 1,657 records · Page 92

Stimulus-response incompatibility activates cortex proximate to three eye fields

We used functional magnetic resonance imaging (fMRI) to investigate cortical activation during the performance of three oculomotor tasks that impose increasing levels of cognitive demand. (1) In a visually guided saccade (VGS) task, subjects made saccades to flashed targets. (2) In a compatible task, subjects made leftward and rightward saccades in response to foveal presentation of the uppercase words "LEFT" or "RIGHT." (3) In a mixed task, subjects made rightward saccades in response to the lowercase word "left" and leftward saccades in response to the lowercase word "right" on incompatible trials (60%). The remaining 40% of trials required compatible responses to uppercase words. The VGS and compatible tasks, when compared to fixation, activated the three cortical eye fields: the supplementary eye field (SEF), the frontal eye field (FEF), and the parietal eye field (PEF). The mixed task, when compared to the compatible task, activated three additional cortical regions proximate to the three eye fields: (1) rostral to the SEF in medial frontal cortex; (2) rostral to the FEF in dorsolateral prefrontal cortex (DLPFC); (3) rostral and lateral to the PEF in posterior parietal cortex. These areas may contribute to the suppression of prepotent responses and in holding novel visuomotor associations in working memory. Copyright 2001 Academic Press.

NASA Discipline Neuroscience↗

Automated Wildfire Detection Through Artificial Neural Networks

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.

Miller, Jerry↗

NASA Langley Research Center Systems Analysis & Concepts Directorate Participation in the Exploration Systems Architecture Study

The NASA Langley Research Center (LaRC) Systems Analysis & Concepts Directorate (SACD) began studying human exploration missions beyond low Earth orbit (LEO) in the year 1999. This included participation in NASA s Decadal Planning Team (DPT), the NASA Exploration Team (NExT), Space Architect studies and Revolutionary Aerospace Systems Concepts (RASC) architecture studies that were used in formulating the new Vision for Space Exploration. In May of 2005, NASA initiated the Exploration Systems Architecture Study (ESAS). The primary outputs of the ESAS activity were concepts and functional requirements for the Crewed Exploration Vehicle (CEV), its supporting launch vehicle infrastructure and identification of supporting technology requirements and investments. An exploration systems analysis capability has evolved to support these functions in the past and continues to evolve to support anticipated future needs. SACD had significant roles in supporting the ESAS study team. SACD personnel performed the liaison function between the ESAS team and the Shuttle/Station Configuration Options Team (S/SCOT), an agency-wide team charged with using the Space Shuttle to complete the International Space Station (ISS) by the end of Fiscal Year (FY) 2010. The most significant of the identified issues involved the ability of the Space Shuttle system to achieve the desired number of flights in the proposed time frame. SACD with support from the Kennedy Space Center performed analysis showing that, without significant investments in improving the shuttle processing flow, that there was almost no possibility of completing the 28-flight sequence by the end of 2010. SACD performed numerous Lunar Surface Access Module (LSAM) trades to define top level element requirements and establish architecture propellant needs. Configuration trades were conducted to determine the impact of varying degrees of segmentation of the living capabilities of the combined descent stage, ascent stage, and other elements. The technology assessment process was developed and implemented by SACD as the ESAS architecture was refined. SACD implemented a rigorous and objective process which included (a) establishing architectural functional needs, (b) collection, synthesis and mapping of technology data, and (c) performing an objective decision analysis resulting in technology development investment recommendations. The investment recommendation provided budget, schedule, and center/program allocations to develop required technologies for the exploration architecture, as well as the identification of other investment opportunities to maximize performance and flexibility while minimizing cost and risk. A summary of the trades performed and methods utilized by SACD for the Exploration Systems Mission Directorate (ESAS) activity is presented along with how SACD is currently supporting the implementation of the Vision for Space Exploration.

Keyes, Jennifer↗

Operation and Performance of the Mars Exploration Rover Imaging System on the Martian Surface

This slide presentation details the Mars Exploration Rover (MER) imaging system. Over 144,000 images have been gathered from all Mars Missions, with 83.5% of them being gathered by MER. Each Rover has 9 cameras (Navcam, front and rear Hazcam, Pancam, Microscopic Image, Descent Camera, Engineering Camera, Science Camera) and produces 1024 x 1024 (1 Megapixel) images in the same format. All onboard image processing code is implemented in flight software and includes extensive processing capabilities such as autoexposure, flat field correction, image orientation, thumbnail generation, subframing, and image compression. Ground image processing is done at the Jet Propulsion Laboratory's Multimission Image Processing Laboratory using Video Image Communication and Retrieval (VICAR) while stereo processing (left/right pairs) is provided for raw image, radiometric correction; solar energy maps,triangulation (Cartesian 3-spaces) and slope maps.

imaging↗

Processing of 3-Dimensional Flash Lidar Terrain Images Generated From an Airborne Platform

Data from the first Flight Test of the NASA Langley Flash Lidar system have been processed. Results of the analyses are presented and discussed. A digital elevation map of the test site is derived from the data, and is compared with the actual topography. The set of algorithms employed, starting from the initial data sorting, and continuing through to the final digital map classification is described. The accuracy, precision, and the spatial and angular resolution of the method are discussed.

Bulyshev, Alexander↗

Advances in Spectral-Spatial Classification of Hyperspectral Images

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Fauvel, Mathieu↗

Chemistry of Venus’ Recent Basalts as Clues to its Ancient Past

Perhaps the most important question about Venus is whether it ever had a hydrosphere: liquid water, oceans, and thus an environment suitable for life as we know it. The D/H of Venus’ atmosphere suggests extensive water loss, and climate models may be consistent with global oceans. Rocks dating from that epoch may be preserved in Venus’ tesserae (and especially Ishtar Terra) – inferred to of felsic or silicic rock, which would suggest abundant water. However, the exact elemental compositions of tesserae (silicic or not) will be difficult to retrieve and most of Venus’ surface is basalt flows and volcanic constructs, inferred to be much younger than the oceanic epoch. Remotely sensed data are (and will be) ambiguous about the specific rock types that make up tesserae, and lander spacecraft are almost certain (in the near term) to avoid the rough and precipitous topography of the tesserae and touch down instead on flat, safe basaltic plains or volcanic rises. ‘Recent’ basalts at Venus’ surface could preserve chemical tracers of an ancient aqueous past, if their source regions (material that was re-melted) had been affected by water. This scenario occurs on Earth in Island Arc Basalts (IAB), where their compositions are thought to reflect aqueous alteration of parental midocean ridge basalts (MORB) and incorporation of oceanic sediments. Ancient Venus might have supported plate tectonic and thus have had IAB equivalents; absent plate tectonics, basalt affected by aqueous alteration could have been cycled into its mantle by burial under thick sections of later basalt. Our purpose is to suggest specific chemical clues in current basalts that would permit recognition of those with a history of aqueous interactions from those that did not. We compare Earth’s Ocean Island Basalts (OIB) that involved little water with IAB that show chemical effects ascribable to water. It is not clear that Venus’ basalts can be mapped into terrestrial tectonic settings; however, it seems reasonable that aqueous geochemical processes could have (had) similar effects on both planets.

A H Treiman↗

The Science Case for Spacecraft Exploration of the Uranian Satellites: Candidate Ocean Worlds in an Ice Giant System

The 27 satellites of Uranus are enigmatic, with dark surfaces coated by material that could be rich in organics. Voyager 2 imaged the southern hemispheres of Uranus’s five largest “classical” moons—Miranda, Ariel, Umbriel, Titania, and Oberon, as well as the largest ring moon, Puck—but their northern hemispheres were largely unobservable at the time of the flyby and were not imaged. Additionally, no spatially resolved data sets exist for the other 21 known moons, and their surface properties are essentially unknown. Because Voyager 2 was not equipped with a near-infrared mapping spectrometer, our knowledge of the Uranian moons’ surface compositions, and the processes that modify them, is limited to disk-integrated data sets collected by ground- and space-based telescopes. Nevertheless, images collected by the Imaging Science System on Voyager 2 and reflectance spectra collected by telescope facilities indicate that the five classical moons are candidate ocean worlds that might currently have, or had, liquid subsurface layers beneath their icy surfaces. To determine whether these moons are ocean worlds, and to investigate Uranus’s ring moons and irregular satellites, close-up observations and measurements made by instruments on board a Uranus orbiter are needed.

Richard J. Cartwright↗

Harmonic analysis of discrete tracers of large-scale structure

It is commonplace in cosmology to analyze fields projected onto the celestial sphere, and in particular density fields that are defined by a set of points e.g. galaxies. When performing an harmonic-space analysis of such data (e.g. an angular power spectrum) using a pixelized map one has to deal with aliasing of small-scale power and pixel window functions. We compare and contrast the approaches to this problem taken in the cosmic microwave background and large-scale structure communities, and advocate for a direct approach that avoids pixelization. We describe a method for performing a pseudo-spectrum analysis of a galaxy data set and show that it can be implemented efficiently using well-known algorithms for special functions that are suited to acceleration by graphics processing units (GPUs). The method returns the same spectra as the more traditional map-based approach if in the latter the number of pixels is taken to be sufficiently large and the mask is well sampled. The method is readily generalizable to cross-spectra and higher-order functions. It also provides a convenient route for distributing the information in a galaxy catalog directly in harmonic space, as a complement to releasing the configuration-space positions and weights, and a route to spectral apodization. Finally, we make public a code enabling the application of our method to existing and upcoming datasets.

79 ASTRONOMY AND ASTROPHYSICS↗

Bioindicator “fingerprints” of methane-emitting thermokarst features in Alaskan soils

Permafrost thaw increases the bioavailability of ancient organic matter, facilitating microbial metabolism of volatile organic compounds (VOCs), carbon dioxide, and methane (CH 4 ). The formation of thermokarst (thaw) lakes in icy, organic-rich Yedoma permafrost leads to high CH 4 emissions, and subsurface microbes that have the potential to be biogeochemical drivers of organic carbon turnover in these systems. However, to better characterize and quantify rates of permafrost changes, methods that further clarify the relationship between subsurface biogeochemical processes and microbial dynamics are needed. In this study, we investigated four sites (two well-drained thermokarst mounds, a drained thermokarst lake, and the terrestrial margin of a recently formed thermokarst lake) to determine whether biogenic VOCs (1) can be effectively collected during winter, and (2) whether winter sampling provides more biologically significant VOCs correlated with subsurface microbial metabolic potential. During the cold season (March 2023), we drilled boreholes at the four sites and collected cores to simultaneously characterize microbial populations and captured VOCs. VOC analysis of these sites revealed “fingerprints” that were distinct and unique to each site. Total VOCs from the boreholes included > 400 unique VOC features, including > 40 potentially biogenic VOCs related to microbial metabolism. Subsurface microbial community composition was distinct across sites; for example, methanogenic archaea were far more abundant at the thermokarst site characterized by high annual CH 4 emissions. The results obtained from this method strongly suggest that ∼10% of VOCs are potentially biogenic, and that biogenic VOCs can be mapped to subsurface microbial metabolisms. By better revealing the relationship between subsurface biogeochemical processes and microbial dynamics, this work advances our ability to monitor and predict subsurface carbon turnover in Arctic soils.

anaerobic degradation↗

Development of a Multi-physics Capability for Predicting Residual Stress in a GTS Reservoir.

This report documents completion of a Level 2 Milestone on the development of a multi-physics capability to predict the evolving material state through the manufacturing process of a Gas Transfer Systems (GTS) reservoir. We present details on new developments and capability improvements that address the following completion criteria: (i) validation of a microstructure evolution model, including recrystallization and strain aging, (ii) demonstration of the capability to remesh, map and transfer material state (internal state variables) and residual stress from forging to machining to welding processes, and (iii) formal V&V characterization and quantification of uncertainties of material parameters and manufacturing process parameters on residual stress.

36 MATERIALS SCIENCE↗

Windblown Features on Venus and Geological Mapping

The objectives of this study were to: 1) develop a global data base of aeolian features by searching Magellan coverage for possible time-variable wind streaks, 2) analyze the data base to characterize aeolian features and processes on Venus, 3) apply the analysis to assessments of wind patterns near the surface and for comparisons with atmospheric circulation models, 4) analyze shuttle radar data acquired for aeolian features on Earth to determine their radar characteristics, and 5) conduct geological mapping of two quadrangles. Wind, or aeolian, features are observed on Venus and aeolian processes play a role in modifying its surface. Analysis of features resulting from aeolian processes provides insight into characteristics of both the atmosphere and the surface. Wind related features identified on Venus include erosional landforms (yardangs), depositional dune fields, and features resulting from the interaction of the atmosphere and crater ejecta at the time of impact. The most abundant aeolian features are various wind streaks. Their discovery on Venus afforded the opportunity to learn about the interaction of the atmosphere and surface, both for the identification of sediments and in mapping near-surface winds.

Greeley, Ronald↗

Implementing Scientific Simulation Codes Highly Tailored for Vector Architectures Using Custom Configurable Computing Machines

The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.

Rutishauser, David↗

ExMC Work Prioritization Process

Last year, NASA's Human Research Program (HRP) introduced the concept of a "Path to Risk Reduction" (PRR), which will provide a roadmap that shows how the work being done within each HRP element can be mapped to reducing or closing exploration risks. Efforts are currently underway within the Exploration Medical Capability (ExMC) Element to develop a structured, repeatable process for prioritizing work utilizing decision analysis techniques and risk estimation tools. The goal of this effort is to ensure that the work done within the element maximizes risk reduction for future exploration missions in a quantifiable way and better aligns with the intent and content of the Path to Risk Reduction. The Integrated Medical Model (IMM) will be used to identify those conditions that are major contributors of medical risk for a given design reference mission. For each of these conditions, potential prevention, screening, diagnosis, and treatment methods will be identified. ExMC will then aim to prioritize its potential investments in these mitigation methods based upon their potential for risk reduction and other factors such as vehicle performance impacts, near term schedule needs, duplication with external efforts, and cost. This presentation will describe the process developed to perform this prioritization and inform investment discussions in future element planning efforts. It will also provide an overview of the required input information, types of process participants, figures of merit, and the expected outputs of the process.

Simon, Matthew↗

Automated thematic mapping and change detection of ERTS-A images

The author has identified the following significant results. In the first part of the investigation, spatial and spectral features were developed which were employed to automatically recognize terrain features through a clustering algorithm. In this part of the investigation, the size of the cell which is the number of digital picture elements used for computing the spatial and spectral features was varied. It was determined that the accuracy of terrain recognition decreases slowly as the cell size is reduced and coincides with increased cluster diffuseness. It was also proven that a cell size of 17 x 17 pixels when used with the clustering algorithm results in high recognition rates for major terrain classes. ERTS-1 data from five diverse geographic regions of the United States were processed through the clustering algorithm with 17 x 17 pixel cells. Simple land use maps were produced and the average terrain recognition accuracy was 82 percent.

Gramenopoulos, N.↗

Snow Distribution Patterns Revisited: A Physics-Based and Machine Learning Hybrid Approach to Snow Distribution Mapping in the Sub-Arctic

Snowpack distribution in Arctic and alpine landscapes often occurs in repeating, year-to-year patterns due to local topographic, weather, and vegetation characteristics. Previous studies have suggested that with years of observational data, these snow distribution patterns can be statistically integrated into a snow process modeling workflow. Recent advances in snow hydrology and machine learning (ML) have increased our ability to predict snowpack distribution using in-situ observations, remote sensing data sets, and simple landscape characteristics that can be easily obtained for most environments. Here, we propose a hybrid approach to couple a ML snow distribution pattern (MLSDP) map with a physics-based, snow process model. We trained a random forest ML algorithm on tens of thousands of snow survey observations from a subarctic study area on the Seward Peninsula, Alaska, collected during peak snow water equivalent (SWE). We validated hybrid model outputs using in-situ snow depth and SWE observations, as well as a light detection and ranging data set and a distributed temperature profiling sensor data set. When the hybrid results were compared with the physics-based method, the hybrid method more accurately depicted the spatial patterns of the snowpack, areas of drifting snow, and years when no in-situ observations were used in the random forest ML training data set. The hybrid method also showed improvements in root mean squared error at 61% of locations where time-series estimations of snow depth were observed. These results can be applied to any physics-based model to improve the snow distribution patterning to reflect observed conditions in high latitude and high elevation cold region environments.

54 ENVIRONMENTAL SCIENCES↗

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

Making Thin Sections from National Treasures: A Little Moon Rock Goes a Long Way

NASA’s Johnson Space Center curates the Apollo sample collection through their facilities in Houston, TX. It is a dual-purpose facility, intended both to store and preserve the precious samples, as well as to make them available for ongoing scientific study and public examination. The facilities consist of multiple vaults and lab spaces, including the Apollo Thin Section Lab. Although it is a part of the Curation facilities, this lab is intended to process specific lunar rock and dust samples into what are called “thin sections”. A thin section is a microscope slide with a very thin, highly polished slice of rock material mounted on it. These are used not only for microscope viewing, but also for a range of other sophisticated scientific instruments to map and measure fine details of the rock’s physical and chemical composition and structure. The process of making a thin section requires great care and patience and is an art in itself; each one is unique, and each sample can behave very differently while going through the same basic procedures. In general, it begins by taking a small chip of rock from a much larger sample. The rock fragment is placed within a small mold and liquid epoxy is poured over it and allowed to harden, producing what is called a “potted butt” (Figure 1). This is to stabilize the rock so that it won’t fragment or crumble during polishing, and to fill any cracks or voids within the rock. Once hardened, the epoxy on the bottom is carefully ground away to expose the rock surface within, which is then polished to a 1-micron finish. A thin new layer of fresh epoxy is then applied to the polished surface and used to mount it to a silica slide. Once the mounting epoxy has hardened, the potted butt is cut off less than one millimeter above the slide using a low-speed circular saw. This thin layer of sample material attached to the slide undergoes further grinding and polishing, typically bringing the sample thickness down to about 35 microns – roughly one third of the thickness of a human hair. The remaining potted butt is saved for future scientific investigations and can be re-polished and used again until all the rock material within it is used up. A single thin section can be reused countless times by numerous different researchers. In addition, thin sections are often exquisitely beautiful (Figure 2) and in some cases, lunar thin sections are used as public display samples, such as at the Smithsonian Air and Space Museum in Washington, DC. The production of thin sections allows an immense variety of research to be conducted on a tiny amount of rock or mineral material, allowing the bulk of the Apollo collection to stay pristine and unaltered, and thus, remain available for next generation of lunar scientists to further our insight into the Moon’s geological diversity, and to bring valuable new insights to our understanding of the origin of the Earth-Moon system.

J J Kent↗