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At least 1,225 records · Page 68

47 Tuc in Rubin Data Preview 1. Exploring Early LSST Data and Science Potential

We present analyses of the early data from Rubin Observatory’s Data Preview 1 (DP1) for the field of the globular cluster 47 Tuc. The DP1 data set for 47 Tuc includes four nights of observations from the Rubin Commissioning Camera (LSSTComCam), covering multiple bands (ugriy). We address challenges of crowding in the inner region of the cluster and toward the SMC in DP1, and demonstrate improved star–galaxy separation by fitting fifth-degree polynomials to the stellar loci in color–color diagrams and applying multidimensional sigma clipping. We compile a catalog of 3576 probable 47 Tuc member stars selected via a combination of isochrone, Gaia proper-motion, and color–color space matched filtering. We explore the sources of photometric scatter in the 47 Tuc color–color sequence, evaluating contributions from various potential sources, including differential extinction within the cluster. Finally, of the 72 well-characterized variables in the field, we recover three known variable stars, including two RR Lyrae and one eclipsing binary, in the coadd-based object catalog, and identify 62 in the difference image-based object catalog. Although the DP1 lightcurves have sparse temporal sampling, they appear to follow the patterns of densely sampled literature lightcurves well. Despite some data limitations for crowded-field stellar analysis, DP1 demonstrates the promising scientific potential for future LSST data releases.

Choi, Yumi [NSF National Optical-Infrared Astronom↗

Science Observations of Deep Space One

During the Deep Space One (DS1) primary mission, the spacecraft will fly by asteroid 1992 KD and possibly comet Borrelly. There are two technologies being validated on DS1 that will provide science observations of these targets, the Miniature Integrated Camera Spectrometer (MICAS) and the Plasma Experiment for Planetary Exploration (PEPE). MICAS encompasses a camera, an ultraviolet imaging spectrometer and an infrared imaging spectrometer. PEPE combines an ion and electron analyzer designed to determine the three-dimensional distribution of plasma over its field of view. MICAS includes two visible wavelength imaging channels, an ultraviolet imaging spectrometer, and an infrared imaging spectrometer all of which share a single 10-cm diameter telescope. Two types of visible wavelength detectors, both operating between about 500 and 1000 nm are used: a CCD with 13-microrad pixels and an 18-microrad-per-pixel, metal-on-silicon active pixel sensor (APS). Unlike the CCD the APS includes the timing and control electronics on the chip along with the detector. The UV spectrometer spans 80 to 185 nm with 0.64-nm spectral resolution and 316-microrad pixels. The IR spectrometer covers the range from 1200 to 2400 nm with 6.6-nm resolution and 54-microrad pixels PEPE includes a very low-power, low-mass micro-calorimeter to help understand plasma-surface interactions and a plasma analyzer to identify de individual molecules and atoms in the immediate vicinity of the spacecraft that have been eroded off the surface of asteroid 1992 KD. It employs common apertures with separate electrostatic energy analyzers. It measures electron and ion energies spanning a range of 3 eV to 30 keV, with a resolution of five percent. and measures ion mass from one to 135 atomic mass units with 5 percent resolution. It electrostatically sweeps its field of view both in elevation and azimuth. Both MICAS and PEPE represent a new direction for the evolution of science instruments for interplanetary spacecraft. These two instruments incorporate a large fraction of the capability of five instruments that had typically flown on NASA's deep space missions The Deep Space One science team acknowledges the support of Philip Varghese, David H. Lehman, Leslie Livesay, and Marc Rayman for providing invaluable assistance in making the science observations possible.

Nelson, Robert M.↗

Diversity and Inclusion in Spacecraft Science Teams: What Do We Know and What Can We Do About It?

Introduction: Not only does the planetary science community lack diversity [1-3], the subset of the community that participates on spacecraft science team is even less diverse than the community as a whole [1, 4]. Results of 2020 Workforce Survey: Previous studies of the diversity of members of spacecraft science teams made incorrect assumptions about the nature of the data before collecting the data. Those analyses assumed a binary gender and ignored the existence of planetary scientists who are neither men nor women [4-6]. We present here results where demographic data was collected without assumptions; each individual surveyed supplied their own answers to demographic questions. The April 2020 survey of Planetary Scientists, which was conducted by the Statistical Research Center of the American Institute of Physics (AIP) and funded by the American Astronomical Society (AAS)’s Division of Planetary Science (DPS) asked participants their gender with 4 possible responses: Woman, Man, Another identify (please specify if you wish), and Prefer not to answer. 32% of respondents chose Woman, 67% chose Man and 1% chose Another gender identity [1]. The survey also asked demographic questions on race, ethnicity, LGBTQ+ identity, and disability. For a full list of questions, see https://dps.aas.org/sites/dps.aas.org/files/reports/2020/survey2020_questionnaire.pdf. In addition to demographic questions, the 2020 Workforce survey asked how many times respondents had been involved in Mission proposals as a Principal Investigator (PI) and, separately, as a Co-Investigator (CoI) [1]. Answers to questions about mission involvement were correlated with answers to demographic questions and the results show that members of historically underrepresented groups (non-white scientists, women, members of the LGBTQ+ community, and disabled scientists) were less likely to be involved in spacecraft mission proposals than were members of historically overrepresented groups [1]. The figures below show the correlated responses for four different axes of underrepresentation [1]. Note that while the figure on gender shows only Women and Men (due to the small percentage of folks answering “Another gender”), non-binary respondents are included in the LGBTQ+ community figure. Conclusion: Being part of a spacecraft science team is a goal for many planetary scientists. With it comes brand new data, more stable funding, and a sense of awe and exploration. It can lead to a cascade of opportunities from conference and public presentations, to membership in subsequent mission teams, and prestige in the community [4]. As a result, participation in spacecraft teams can be used a measure of success within the field. From the survey results, we see that members of historically excluded groups, even after they have overcome barriers to participating in the field, are still experiencing barriers to success within the field itself. Why?: The diminishing percentage of members of underrepresented groups as a career progresses has been referred to as a “leaky pipeline”. However, this fails to adequately capture the experiences of the members of these underrepresented groups as it implies a passive process. In order to capture the active processes (bias, discrimination, harassment, and other exclusionary behaviors) that contribute to low retention in the workforce, the term “Hostile Obstacle Course” is more useful [7,8]. It is these processes that need to be addressed in order to retain valued members of our community. Moving Forward: In order to broaden participation in planetary science, particularly mission science teams, we need to address conditions that create hostile workplace climates. What can mission teams and other groups do to address these conditions? First, each group/team needs to evaluate their own members to determine what specific barriers exist in their own interactions. One tool to accomplish this would be an anonymous survey designed to understand how team members feel about working within the group. Working with professionals who know how to create and analyze such surveys (often called “climate surveys” when applied to University students, for example) would ensure that the survey meets its goals and does not make assumptions that counter the meaningfulness of the results. Such professionals in EDIA (Equity, Diversity, Inclusion, and Accessibility) and workplace culture can make suggestions for policy changes that would eliminate hostile workplace conditions. Policy changes that are often suggested include instituting professional EDIA training for the team and/or for team leadership, instituting and following a code of conduct [9], including more interactive group activities in group meetings, etc. Training and information on EDIA is available for all members of the planetary science community. The first place to look would be in your University or Institution’s EDIA or human resources offices. Bystander Intervention is often offered as part of other meetings [10]. A newer offering is a Workshop on EDIA for Leaders in Planetary Science led by Julie Rathbun (first author of this abstract) and JA Grier (https://edialps.psi.edu/). This 3-day workshop gives participants the tools they need to enact positive change in their personal and professional spheres. The first workshop was help in November 2022 and another workshop will take place in the late spring 2023 with exact dates to be announced soon.

J. A. Rathbun↗

Effects of residual oxygen on superconducting niobium films

The integration of niobium (Nb) into emerging superconducting circuits can enhance their performance and function. However, growth of high purity Nb can be challenging due to its high reactivity with oxygen. Here, in this study, we examine the role of residual oxygen inside the growth chamber in transforming the structural, chemical, and superconducting properties of Nb films. We demonstrate that an increase in unintentional oxygen impurities lowers the superconducting critical temperature of Nb. This evolution coincides with the reduction of Nb crystal domains, which are separated by highly disordered oxygen-rich regions. Moreover, chemical analysis reveals the formation of niobium monoxide within the film during growth. These findings provide a comprehensive picture of how residual oxygen in the growth chamber can affect the properties of the Nb films. This study contributes to the materials science and engineering knowledge of superconducting Nb growth.

36 MATERIALS SCIENCE↗

Functionalized Mesoporous Carbon and Silica for Effective Recovery of Rare Earth Elements from Magnet Scrap

The dependence on international supplies of rare earth elements (REEs) have prompted the US to explore alternative sources and sustainable technologies for domestic REE production. One potential source is the secondary electronic and industrial wastes at the Department of Defense (DoD) complexes and across the US. These hazardous wastes require high costs for the maintenance and remediation, while their high-REE contents offer unique opportunities for REE recovery. However, current hydrometallurgical technologies for REE extraction are energy intensive and costly, with low REE recovery rate and the generation of toxic wastes. Thus, it is beneficial to develop environmentally friendly technologies for REE extraction and processing from the secondary wastes. This project aims to develop novel functionalized mesoporous carbon fiber (MCF) and silica for effective recovery of REEs from end-of-life NdFeB magnet scrap.

36 MATERIALS SCIENCE↗

Thermocapillary and Diffusocapillary Migration of a Fluid Drop

The migration of bubbles, or drops, plays an important role in many engineering science and space manufacturing problems. In material science processes as in the manufacturing of glasses, etc., gas bubbles can be formed from the by-products of chemical reactions or gas trapped in the interstices of the raw material. In the low-g environment of space, forces other than gravitational must be utilized as a bubble separation technique. It is well-known that gradients in interfacial tension on the bubbles' surface can promote droplet motion in the direction of decreasing interfacial tension and hence provide such a separation mechanism. Thus, the role of thermocapillary and diffusocapillary migration of a bubble, or drop, can be of paramount interest in materials processing in space.

Sani, R. L.↗

Data catalog series for space science and applications flight missions. Volume 6: Master index volume

The main purpose of the data catalog series is to provide descriptive references to data generated by space science flight missions. The data sets described include all of the actual holdings of the Space Science Data Center (NSSDC), all data sets for which direct contact information is available, and some data collections held and serviced by foreign investigators, NASA, and other U.S. government agencies. This volume contains the Master Index. The following spacecraft are included: Mariner, Pioneer, Pioneer Venus, Venera, Viking, Voyager, and Helios. Separate indexes to the planetary and interplanetary missions are also provided.

Horowitz, Richard↗

Artificial Neural Network (ANN) Surface Longwave and Shortwave Fluxes Trained on CERES Observations

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of the radiative fluxes and clouds systems. CERES climate quality data products typically take several months of calibration and validation before release to the public. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed to provide key data for the applied sciences and educational users within a week of observation. FLASHFlux achieves this by using simplified calibration, an operational meteorological product from Global Modeling and Assimilation Office (GMAO), and its own surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Terra and NOAA-20 observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1o x 1o gridded data that combines Terra and NOAA-20 observations. Currently, FLASHFlux uses the Langley Parameterized Shortwave Algorithm (LPSA) and Langley Parameterized Longwave Algorithm (LPLA) to derive its surface fluxes (Kratz et al., 2010; Gupta et al, 2001). A new Machine Learning (ML) based approach using Artificial Neural Networks to derive Surface Longwave (LW) & Shortwave (SW) fluxes based on training data from the CERES Clouds Radiative Swath (CRS) product is being investigated to replace LPSA and LPLA in the SSF surface flux products. One of the biggest hurdles in training ML model is model fitting. To overcome the problem of overfitting we use feature engineering that helps in finding the important feature and remove features that are irrelevant to the model. In our training we employed the Leave-One-Feature-Out Importance (LOFO) to evaluate the significance of each feature in our training. We intercompare ANN fluxes against surface fluxes produced from the Fu-Liou model in CRS and the LPSA/LPLA in FLASHFlux SSF. Furthermore, we validated ANN derived fluxes to the Baseline Surface Radiation Network (BSRN).

P C Sawaengphokhai↗

The MODIS RSB calibration and look-up-table delivery process for Collection 6 and 6.1

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board the Aqua and Terra space-craft have provided valuable science data for the last 18 and 20 years, respectively. Each instrument is equipped with 36 spectral bands, 20 of which are reflective solar bands (RSBs). These bands cover a wavelength range of 0.4 – 2.2μm and are calibrated on-orbit using several on-board calibrators (OBCs), such as a solar diffuser (SD)and a solar diffuser stability monitor (SDSM), along with regularly-scheduled lunar observations through the space view (SV) port. The gain (1/m1) and response-verses-scan angle (RVS) are updated on a near-monthly basis and act as the primary look-up-tables (LUTs) for the RSB calibration. A set of separate uncertainty LUTs for each of the RSBs are also delivered regularly and incorporated into the Level 1B (L1B) product to generate a pixel-level Uncertainty Index (UI). In addition to the gain, RVS and uncertainty, there are several other LUTs associated with the reflective bands that are either updated less frequently or remain static. The accuracy of both the forward-predicted and historical RSB LUTs, which are derived by the MODIS Characterization Sup-port Team (MCST), is important in maintaining the quality and accuracy of the L1B and science products.To ensure a timely and accurate LUT update, MCST has established a comprehensive set of procedures. This paper provides an overview of the calibration process, along with the current LUT delivery process for the RSB sin Collection 6 (C6) and Collection 6.1 (C6.1). Improvements to be implemented in future collections are also discussed.

MODIS↗

Review of NASA activities in materials sciences in space

In the year since the 18th Plenary Meeting of COSPAR, NASA has conducted eight materials processing experiments on the Apollo-Soyuz mission and 17 on two rocket flights. In addition, these three missions have implemented one Soviet and three German experiments. The Apollo-Soyuz results have confirmed and extended the findings of the Skylab experiments on solidification and crystal growth effects and have also established capabilities for separating living cells by electrophoresis and returning them still living to earth. The rocket missions provide repetitive flight opportunities much as the Space Shuttle will do, and they are being used to develop research approaches in which investigators will undertake projects calling for multiple space experiments rather than proposing experiments individually. During the year, NASA has also completed definition work on the major payload facilities planned for its initial materials processing experiment program on the Space Shuttle and Spacelab missions of 1980-81.

Bredt, J. H.↗

Biospecimen Retrieval from NASA's Rodent Research-1: Maximizing Science Return from Flight Missions

Rodent Research (RR)-1 was conducted to validate flight hardware, operations, and science capabilities that were developed to support long duration missions on the International Space Station. After 37 days in microgravity twenty mice were euthanized and frozen on orbit. Upon return to Earth the carcasses were dissected and yielded 32 different types of tissues from each mouse and over 3200 tissue aliquots. Many tissues were distributed to the Space Life and Physical Sciences (SLPS) Biospecimen Sharing Program (BSP) Principal Investigators (PIs) through the Ames Life Science Data Archive (ALSDA). A second round of dissections was performed to collect additional tissues from the remaining carcasses thawed for a second time for additional BSP PIs. Tissues retrieved included vaginal walls, aorta, pelvis, brown adipose tissue, tail, spine and forearms. Although the analyses are still in progress, some of the PIs have reported that the quality of the tissues was acceptable for their study. In a separate experiment we tested the RNA quality of the tissues that were dissected from frozen carcasses that were subjected to euthanasia, freezing, first and second thaw dissections. Timelines simulated the on-orbit RR-1 procedures to assess the quality of the tissues retrieved from the second thaw dissections. We analyzed the RIN values of select tissues including kidney, brain, white adipose tissue (WAT) and brown adipose tissue (BAT). Overall the RIN values from the second thaw were lower compared to those from the first by about a half unit; however, the tissues yielded RNA that are acceptable quality for some quantitative gene expression assays. Interestingly, RIN values of brain tissues were 8.4+/-0.6 and 7.9+/-0.7 from first and second round dissections, respectively (n5). Kidney and WAT yielded RIN values less than 8 but they can still be used for qPCR. BAT yielded higher quality RNA (8.2+/-0.5) than WAT (5.2+/-20.9), possibly due to the high fat content. Together, these data show that select tissues can be utilized for gene expression studies even if they are retrieved from carcasses that were subjected to at least two freezing and thawing processes; this further expands science return from valuable and infrequent rodent experiments in space.

rodents↗

Biospecimen Retrieval from NASA's Rodent Research-1: Maximizing Science Return from Flight Missions

Rodent Research (RR)-1 was conducted to validate flight hardware, operations, and science capabilities that were developed to support long duration missions on the International Space Station. After 37 days in microgravity twenty mice were euthanized and frozen on orbit. Upon return to Earth the carcasses were dissected and yielded 32 different types of tissues from each mouse and over 3200 tissue aliquots. Many tissues were distributed to the Space Life and Physical Sciences (SLPS) Biospecimen Sharing Program (BSP) Principal Investigators (PIs) through the Ames Life Science Data Archive (ALSDA). A second round of dissections was performed to collect additional tissues from the remaining carcasses thawed for a second time for additional BSP PIs. Tissues retrieved included vaginal walls, aorta, pelvis, brown adipose tissue, tail, spine and forearms. Although the analyses are still in progress, some of the PIs have reported that the quality of the tissues was acceptable for their study. In a separate experiment we tested the RNA quality of the tissues that were dissected from frozen carcasses that were subjected to euthanasia, freezing, first and second thaw dissections. Timelines simulated the on-orbit RR-1 procedures to assess the quality of the tissues retrieved from the second thaw dissections. We analyzed the RIN values of select tissues including kidney, brain, white adipose tissue (WAT) and brown adipose tissue (BAT). Overall the RIN values from the second thaw were lower compared to those from the first by about a half unit; however, the tissues yielded RNA that are acceptable quality for some quantitative gene expression assays. Interestingly, RIN values of brain tissues were 8.4+/-0.6 and 7.9+/-0.7 from first and second round dissections, respectively (n=5). Kidney and WAT yielded RIN values less than 8 but they can still be used for qPCR. BAT yielded higher quality RNA (8.2+/-0.5) than WAT (5.22+/-0.9), possibly due to the high fat content. Together, these data show that select tissues can be utilized for gene expression studies even if they are retrieved from carcasses that were subjected to at least two freezing and thawing processes; this further expands science return from valuable and infrequent rodent experiments in space.

rodent↗

Numerical analysis of Microgravity Bubble Separation in Open Channels with ISS Bemchmarks

Spacecraft fluid systems often require specific considerations to operate in a manner similar to those on Earth. For instance, an open wedge shaped channel can serve as a pathway for passively separating bubbles from a liquid in a two phase flow, analogous to buoyancy effects on Earth. As the bubbles merge within the channel, they become increasingly confined in the wedge, driving them upwards and outwards toward the free surface due to capillary forces. These same forces ensure coalescence and allow the bubbles to escape through the free surface. However, in low gravity environments, a challenge arises when bubbles are not sufficiently large. Under such conditions, the bubbles tend to follow trajectories near their inscribed elevations, never fully leaving the liquid. Such unseparated bubbles can lead to downstream pump failure, cavitation, flow instabilities, dryout, and other adverse effects aboard spacecraft. Understanding and exploiting the underlying mechanisms behind this behavior is crucial for enhancing the reliability of passive capillary fluids management in space applications, including cryogenic and storable fuels transport, thermal fluids circulation, water recycling for life support, plant watering systems, and more. The joint German Aerospace Center (DLR) and NASA Capillary Channel Flow (CCF) experiment conducted on the International Space Station has provided an extensive publicly available database documenting such phenomena (https://science.nasa.gov/physical sciences informatics psi). Leveraging this resource, we aim to establish benchmarks for our numerical investigation of zero gravity bubbly two phase flow in open wedge channels. Specifically, we seek to quantitatively understand the mechanisms governing ‘inscribed’ bubble motion, considering the apparent interplay of two competing forces: Saffman lift (causing upward/outward motion) and the Magnus effect (causing downward/inward motion). Our cross cutting findings directly inform the development of robust passive phase separation methods within spacecraft plumbing systems.

bubble↗

A Flexible, Redox-Active, Aqueous Electrolyte-Based Asymmetric Supercapacitor with High Energy Density Based on Keratin-Derived Renewable Carbon

This work exploits the advantage of asymmetric configuration over symmetric supercapacitor in designing high energy density flexible devices from two active electrode materials–keratin-based renewable-resource hierarchically porous carbon and hydrous ruthenium oxide (RuO 2 ). Here, the asymmetric device exhibits significantly high capacitance. Conventional estimation of energy storage parameters, however, cannot be applied for devices with a Faradaic energy storage contribution via redox charge transfer mechanism. Therefore, this work applies a precise measurement of pseudocapacitance contribution at various scan rates to correct the device data that reveals effective capacitance of 120 F g –1 with the energy density of 37 W h kg –1 at 776 W kg –1 . It also retains excellent rate capability, >74% at high current density 25 A g –1 . The charge storage activity and device stability can be further enhanced by introducing redox-active electrolytes that improve specific capacitance, but the rate capabilities deteriorate at high current densities. Further, the principle of asymmetric electrode design is applied to fabricate a bending-tolerant, flexible device by depositing active electrode material on wire-shaped current collector followed by coupling those separated with polyvinyl alcohol gel containing redox electrolyte; it yields 36.8 mF cm –1 specific capacitance at a 0.2 mA cm –1 current density.

36 MATERIALS SCIENCE↗

Crystallographic orientation-dependent strain hardening in a precipitation-strengthened Al-Cu alloy

While the strengthening of Al-Cu alloys due to precipitation has been extensively studied, the effect of crystallographic orientation of the matrix and precipitates, as well as precipitate morphology, on the strain hardening behavior is not well understood. In this paper, we investigate this effect with in situ neutron diffraction during deformation of an Al-Cu alloy (206) after multiple aging treatments. Precipitate-dislocation interactions were found to change from precipitate shearing for microstructures predominantly containing GPI and θ" precipitates to Orowan looping for microstructures with primarily θ' and θ precipitates. Notably, significant anisotropy in strain hardening behavior was observed when θ' precipitates were present, which was attributed to crystallographic orientation dependent load transfer from the Al matrix to the θ' precipitates. The anisotropic load transfer is hypothesized to be caused by the extent of rotation of high aspect-ratio θ' precipitates, owing to dislocations looping around them during plastic deformation of the matrix. Predictions from an analytical model describing the anisotropic magnitude of load transfer from precipitate rotation agree well with experimental results, successfully validating the precipitate rotation hypothesis and explaining the anisotropic strain hardening behavior. This model allows for the prediction of stresses separately in the precipitate and matrix phases as a function of crystallographic orientation, only given the bulk mechanical properties.

36 MATERIALS SCIENCE↗

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Three dimensional cluster analysis for atom probe tomography using Ripley’s K-function and machine learning

The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley’s K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K (r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K (r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. Here we find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K (r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.

36 MATERIALS SCIENCE↗