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At least 667 records · Page 37

Advanced silicon tracking detector developments for the future Electron-Ion Collider

The proposed Electron-Ion Collider (EIC) will operate high-luminosity high-energy electron+proton and electron+nucleus collisions at the collision energies from 20 GeV to 141 GeV to solve several fundamental questions in the high energy and nuclear physics fields. Its instantaneous luminosity can reach 10 33-34 cm -2 s -1 and the bunching crossing rate is around 10 ns. The EIC project has received CD1 approval from the US DOE in 2021 and moves toward the machine design and preparation for construction. To realize various particle measurements with high precision at the future EIC, a low material-budget and high-granularity silicon vertex and tracking detector with fine spatial and momentum resolutions and nearly 4π solid angle coverage is desired. The Monolithic Active Pixel Sensor (MAPS) and AC Coupled Low Gain Avalanche Diode (AC-LGAD) technologies stand out of several advanced technology options for the EIC silicon vertex and tracking detector subsystems. The MAPS technology has advanced features of low material budget, low power consumption, good radiation resistance and fine spatial resolution. The AC-LGAD technology can achieve fast timing resolution. Latest studies and progress of the EIC silicon vertex and tracking detector conceptual design, performance validations in simulation and ongoing MAPS and AC-LGAD R&D will be shown. Furthermore, schedule and plan of the EIC project detector development will be discussed as well.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The ATLAS ITk Strip detector system for the Phase-II LHC upgrade

In the view of the luminosity increase foreseen by the High-Luminosity Large Hadron Collider program at CERN, the ATLAS experiment initiated an R&D program to replace its complete inner detector (ID) system. The new Inner Tracker (ITk) system, anticipated to be installed by 2028, will be a new all-silicon based tracker including Strip and Pixel detector technologies. The new detector is designed to meet the requirements of operating under a harsh environment namely, high radiation levels, increased pile-up and data rates while decrease the material budget and maintain or even improve the performance. The Strip project has advanced in several areas the last years while facing challenges moving from pre-production to production. Here, this manuscript gives an overview of the ITk Strip system and describes the advancements and challenges to date.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

3x3 array module of 8×8×32 mm 3 position-sensitive virtual frisch-grid CdZnTe detectors for imaging and spectroscopy of cosmic gamma-rays

Here, we evaluated the performance of the 3x3 array of 32-mm long position-sensitive virtual Frisch-grid (VFG) CdZnTe (CZT) detectors read out by the IDEAS GDS-100 data acquisition system. The array is a mechanically solid module designed for integration into a large effective area gamma-ray telescope proposed for imaging and spectroscopy of cosmic gamma-rays. The array employs the bar-shaped 8x8x32 mm 3 CZT crystals which recently became available from Redlen Technologies, Inc. and Kromek-eV Group PLC at affordable costs. The waveform sampling IDE3421 application-specific integrated circuit (ASIC), developed by the University of Michigan and IDEAS for CZT pixel detectors, was adapted to capture the signals from the array's VFG detectors. We showed good spectral performance of the Redlen detectors with an energy resolution of <1% FWHM at 662 keV and slightly poorer performance of the Kromek-eV detectors with a resolution of <2% measured at a reduced temperature of 13 °C. By testing the same detectors as single devices using hybrid charge-sensitive preamplifiers, we demonstrated improved energy resolutions at a normal temperature of ~25°C: <1% and 1.3-1.7%, respectively. However, the Kromek-eV detectors did not perform as well as the Redlen ones. We explained this by the space charge formation (polarization) decreasing the electric field and the electron drift times. The polarization was likely caused by the high injections of holes from the anode contacts. The absence of polarization in Redlen detectors suggested that the quality of the contacts might have played a role in this case.

47 OTHER INSTRUMENTATION↗

Characterization of EJ-270 and Ce-doped LiCAF scintillators for the development of high-rate neutron reflectometer detectors

The Second Target Station of the Spallation Neutron Source at Oak Ridge National Laboratory is anticipated to provide a neutron source with ∼20 times increase in peak brightness than the First Target Station. The neutron reflectometers currently in operation at the First Target Station need to be upgraded due to the increased neutron flux. A prototype neutron detector module based upon a pixelated scintillator array readout by silicon photomultipliers is being developed to address the high-rate challenge faced with future neutron reflectometer instruments at the Second Target Station. Two types of scintillator materials were considered for this detector development, i.e., 6 Li-loaded EJ-270 plastic scintillator and Ce-doped LiCAF single crystal. This paper reports the scintillator characterization results, including light yield, pulse shape discrimination performance, capability to detect thermal neutrons in a high γ-ray field, and γ-ray sensitivity. The number of photons produced per neutron capture by EJ-270 and LiCAF:Ce was measured to be 2176 ± 91 and 2651 ± 108, respectively. EJ-270 demonstrated a good capability to discriminate between neutrons and γ-rays by employing the commonly used charge comparison method (figure-of-merit: 1.13 ± 0.01 for an energy cut of 292–426 keVee) and a reasonable performance when using the time-over-threshold techniques; however, no discrimination was observed from LiCAF:Ce regardless of the pulse shape discrimination approaches utilized, making pulse height discrimination necessary for LiCAF:Ce to differentiate between neutrons and γ-rays. Both EJ-270 and LiCAF:Ce exhibited an acceptable capacity to detect thermal neutrons at high exposure rates up to approximately 584 mR/h. Furthermore, the γ-ray sensitivities measured with a 60 Co source at an exposure rate of around 1145 mR/h were determined to be (6.11 ± 0.87) × 10 −6 and (7.64 ± 1.08) × 10 −7 for EJ-270 and LiCAF:Ce, respectively.

EJ-270↗

Performance characterization of 5×5×12 mm 3 virtual Frisch-grid TlBr detectors

Thallium bromide (TlBr) is a promising material for semiconductor gamma-ray detectors due to its high atomic number (Tl = 81, Br = 35), high density (7.56 g/cm 3 ), and relatively low melting point (460 °C). These properties give TlBr several competitive features, including high detection efficiency, good energy resolution, and lower fabrication costs, making it suitable for applications requiring compact, highly sensitive gamma-ray detection systems. Recent developments of TlBr detectors have progressed toward thicker crystals, up to 10–20 mm, configured as pixelated or virtual Frisch-grid (VFG) devices with volumes >1 cm 3 . Despite these advances, challenges remain in practical implementation, including material and fabrication issues that affect energy resolution, device stability, performance, and longevity. These challenges are similar to those faced by HgI 2 and lead-halide perovskite detectors. Here, this study presents results from characterizing over 100 position-sensitive 5×5×12 mm 3 virtual Frisch-grid detectors fabricated by Radiation Monitoring Devices Inc. For a prototype Radioisotope Identification Device (RIID). The work identified factors limiting the performance and longevity of TlBr detectors, including stochastic response variations that limit the energy resolution to 2–3 % (at 662 keV) for most devices, performance degradation associated with defect decoration, and contact delamination. Addressing these issues advances the use of TlBr and similar materials for reliable, high-resolution gamma-ray spectroscopy.

47 OTHER INSTRUMENTATION↗

Design and construction of the CMS Outer Tracker for the phase-2 upgrade

The High-Luminosity LHC (HL-LHC) is expected to deliver an integrated luminosity of 3000–4000 fb −1 over 10 years of operation with the peak instantaneous luminosity reaching about 5–7.5 × 1 0 34 cm −2 s −1 . During Long Shutdown 3, several components of the CMS detector will undergo major improvements, called Phase-2 upgrades, to be able to operate in the challenging environment of the HL-LHC. The current CMS tracker will be replaced. The Phase-2 Outer Tracker (OT) will have increased radiation tolerance, higher granularity, and the capability to handle higher data rates. Moreover, the OT will provide tracking information to the Level-1 trigger for the first time at a hadron collider, allowing trigger rates to be kept at a sustainable level without sacrificing physics potential. For this, the OT will be made of modules with two closely-spaced silicon sensors read out by front-end ASICs that can correlate hits in the two sensors to create short track segments, used in the Level-1 track finder. The modules come in two flavors: strip-strip and pixel-strip, containing different sensor configurations and multiple ASICs. This contribution presents the Phase-2 OT, the finalization of the OT module design, and the quality assurance and control procedures used to ensure that the modules fulfill both the specifications from the assembly steps as well as the proper communication among the ASICs.

Zoi, Irene [Fermilab] (ORCID:0000000257389446)↗

HRPPD photosensors for RICH detectors with a high resolution timing capability

Recently, a new version of DC-coupled High Rate Picosecond Photodetectors (DC-HRPPDs) substantially re-designed for use at the Electron-Ion Collider (EIC) has been developed. A first batch of seven “EIC HRPPDs” was manufactured in early 2024. These HRPPDs are DC-coupled photosensors based on Micro-Channel Plates (MCPs) that have an active area of 104 mm by 104 mm, 32 × 32 direct readout pixel array at a pitch of 3.25 mm, peak quantum efficiency in excess of 30%, exceptionally low dark count rates and timing resolution of 15–20 ps for a single photon detection. As such, these photosensors are very well suited for Ring Imaging CHerenkov (RICH) detectors that can additionally provide high resolution timing capability, especially in a configuration where a detected charged particle passes through the sensor window, which produces a localized flash containing a few dozens of Cherenkov photons in it.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improved light yield and growth of large-volume ultrafast single crystal scintillators Cs 2 ZnCl 4 and Cs 3 ZnCl 5

Due to their reported fast decay times, Cs 2 ZnCl 4 and Cs 3 ZnCl 5 are promising candidates for detection of gamma rays and X-rays in high count rate and fast timing applications. In this work, we show that single crystals with better optical quality than previously demonstrated – and larger in size – can be grown via the vertical Bridgman method. Highly transparent Ø7 mm crystals of undoped Cs 2 ZnCl 4 and Cs 3 ZnCl 5 are grown and measured to have light yields surpassing those previously reported, achieving 1980 ± 100 ph/MeV and 1460 ± 70 ph/MeV at 662 keV – a 55% and 232% improvement, respectively. We observe single-component scintillation decay times for both Cs 2 ZnCl 4 (1.66 ns) and Cs 3 ZnCl 5 (0.82 ns) and radioluminescence emission with maximum intensity at ~290 nm. Scalability of these materials is also evaluated based on growth of Ø22 mm crystals. Minimal cracking is observed, and the fast decay times are maintained at this size. Coincidence time resolution of 3 × 3 × 5 mm 3 and 7 × 7 × 10 mm 3 pixels cut from Ø22 mm Cs 2 ZnCl 4 are measured to be 148 ± 1 ps FWHM and 175 ± 1 ps FWHM, respectively. Here, the improved performance and ability to be fabricated in large sizes now place Cs 2 ZnCl 4 and Cs 3 ZnCl 5 on the map as potential contenders for radiation detection applications where BaF 2 – the most commonly used ultrafast inorganic scintillator – is typically considered.

36 MATERIALS SCIENCE↗

Pseudorapidity distributions of charged hadrons in lead-lead collisions at $\sqrt{S_{NN}}$ = 5.36 TeV

The pseudorapidity (η) distributions of charged hadrons are measured using data collected at the highest ever nucleon-nucleon center-of-mass energy of $\sqrt{S_{NN}}$ = 5.36 TeV for collisions of lead-lead ions. The data were recorded by the CMS experiment at the LHC in 2022 and correspond to an integrated luminosity of 0.30 ± 0.03 μb -1 . Using the CMS silicon pixel detector, the yields of primary charged hadrons produced in the range |η| < 2.6 are reported. The evolution of the midrapidity particle density as a function of collision centrality is also reported. In the 5% most central collisions, the charged-hadron η density in the range |η| < 0.5 is found to be 2032 ± 91(syst), with negligible statistical uncertainty. This result is consistent with an extrapolation from nucleus-nucleus collision data at lower center-of-mass energies. Comparisons are made to various Monte Carlo event generators and to previous measurements of lead-lead and xenon-xenon collisions at similar collision energies. These new data detail the dependence of particle production on the collision energy, initial collision geometry, and the size of the colliding nuclei.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Geothermal Artificial Intelligence for geothermal exploration

Exploration of geothermal resources involves analysis and management of a large number of uncertainties, which makes investment and operations decisions challenging. Remote Sensing (RS), Machine Learning (ML) and Artificial Intelligence (AI) have potential in managing the challenges of geothermal exploration. In this paper, we present a methodology that integrates RS, ML and AI to create an initial assessment of geothermal potential, by resorting to known indicators of geothermal areas namely mineral markers, surface temperature, faults and deformation. We demonstrated the implementation of the method in two sites (Brady and Desert Peak geothermal sites) that are close to each other but have different characteristics (Brady having clear surface manifestations and Desert Peak being a blind site). Here, we processed various satellite images and geospatial data for mineral markers, temperature, faults and deformation and then implemented ML methods to obtain pattern of surface manifestation of geothermal sites. We developed an AI that uses patterns from surface manifestations to predict geothermal potential of each pixel. We tested the Geothermal AI using independent data sets obtaining accuracy of 92-95%; also tested the Geothermal AI trained on one site by executing it for the other site to predict the geothermal / non-geothermal delineation, the Geothermal AI performed quite well in prediction with 72-76% accuracy.

15 GEOTHERMAL ENERGY↗

2-D soil zymography: Accounting for the spatial variation of pH

Soil zymography is commonly used to quantify spatial distribution of hydrolytic enzyme activities on soil and plant root surfaces. It is recommended to adjust pH in zymography substrates and calibration solutions with respect to soil/root pH. However, pH values may vary greatly within a few mm of plant rhizosphere, potentially altering the distribution of pH in zymography membranes. Despite the fact that the effect of pH on the calibration of zymography membranes is generally known, its potential impact on zymography results is unaccounted for in processing zymography images and calculations of enzyme activity. In this study we assessed the effect of pH variations on the persistency of the methylumbelliferone (MUF) calibration. The studied pH values ranged from 4.5 to 7.5. The MUF calibration curves greatly deviated from that at a reference pH of 6.5, with a marked nonlinear increase of deviation with greater membrane brightness. We suggest that the problem can be partially alleviated by reducing the membrane incubation time. However, such deviations suggest the need for a more comprehensive resolution via mapping pH and using pH-specific calibrations to process zymography images. Here, we developed a MATLAB code to implement a pixel-based correction of enzyme activity for pH in processing time-lapse zymography images.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-scale integration of satellite remote sensing improves characterization of dry-season green-up in an Amazon tropical evergreen forest

In tropical forests, leaf phenology-particularly the pronounced dry-season green-up-strongly regulates biogeochemical cycles of carbon and water fluxes. However, uncertainties remain in the understanding of tropical forest leaf phenology at different spatial scales. Phenocams accurately characterize leaf phenology at the crown and ecosystem scales but are limited to a few sites and time spans of a few years. Time-series satellite observations might fill this gap, but the commonly used satellites (e.g. MODIS, Landsat and Sentinel-2) have resolutions too coarse to characterize single crowns. To resolve this observational challenge, we used the PlanetScope constellation with a 3m resolution and near daily nadir-view coverage. We first developed a rigorous method to cross-calibrate PlanetScope surface reflectance using daily BRDF-adjusted MODIS as the reference. We then used linear spectral unmixing of calibrated PlanetScope to obtain dry-season change in the fractional cover of green vegetation (GV) and non-photosynthetic vegetation (NPV) at the PlanetScope pixel level. We used the Central Amazon Tapajos National Forest k67 site, as all necessary data (from field to phenocam and satellite observations) was available. For this proof of concept, we chose a set of 22 dates of PlanetScope measurements in 2018 and 16 in 2019, all from the six drier months of the year to provide the highest possible cloud-free temporal resolution. Our results show that MODIS-calibrated dry-season PlanetScope data (1) accurately assessed seasonal changes in ecosystem-scale and crown-scale spectral reflectance; (2) detected an increase in ecosystem-scale GV fraction (and a decrease in NPV fraction) from June to November of both years, consistent with local phenocam observations with R 2 around 0.8; and (3) monitored large seasonal trend variability in crown-scale NPV fraction. Finally, our results highlight the potential of integrating multi-scale satellite observations to extend fine-scale leaf phenology monitoring beyond the spatial limits of phenocams.

54 ENVIRONMENTAL SCIENCES↗

Multiscale assessment of land surface phenology from harmonized Landsat 8 and Sentinel-2, PlanetScope, and PhenoCam imagery

As the spatial and temporal resolution of remotely sensed imagery has improved over the last four decades, algorithms for monitoring and mapping seasonal changes in surface properties have evolved rapidly. Most recently, the availability of daily PlanetScope imagery has created new opportunities for monitoring the land surface phenology (LSP) of terrestrial ecosystems at high spatial resolution. However, the quality and value of LSP information from PlanetScope imagery have not been systematically examined. In this paper, we evaluate the character and quality of LSP information derived from PlanetScope by comparing time series of vegetation indices and LSP metrics from PlanetScope to corresponding time series and LSP metrics derived from Harmonized Landsat 8 and Sentinel-2 (HLS) imagery and PhenoCams at six sites that span a diverse range of land cover types and climate. Results show that vegetation index time series from all three data sources show high temporal correlation, and LSP metrics derived from HLS, PlanetScope, and PhenoCam show high agreement with negligible bias. Semi-variograms for phenometrics estimated from PlanetScope imagery indicate that the majority of spatial variance captured in PlanetScope phenometrics occurs well below the spatial resolution HLS imagery. At the same time, LSP metrics from HLS are most strongly correlated with the 50–75% quantiles of 3 m LSP metrics from PlanetScope. This indicates that HLS captures the average phenology at sub-pixel scale captured in PlanetScope imagery. Here, our results represent the first comprehensive comparison of LSP metrics estimated from PlanetScope and publicly available moderate spatial resolution imagery, and provide insights regarding: (1) the quality and character of LSP metrics derived from HLS and PlanetScope; and (2) the relative merits and trade-offs associated with the use of each data source for LSP studies.

54 ENVIRONMENTAL SCIENCES↗

A physical method for downscaling land surface temperatures using surface energy balance theory

Fine-resolution land surface temperature (LST) derived from thermal infrared remote sensing images is a good indicator of surface water status and plays an essential role in the exchange of energy and water between land and atmosphere. A physical surface energy balance (SEB)-based LST downscaling method (DTsEB) is developed to downscale coarse remotely sensed thermal infrared LST products with fine-resolution visible and near-infrared data. Here, the DTsEB method is advantageous for its ability to mechanically interrelate surface variables contributing to the spatial variation of LST, to quantitatively weigh the contributions of each related variable within a physical framework, and to efficaciously avoid the subjective selection of scaling factors and the establishment of statistical regression relationships. The applicability of the DTsEB method was tested by downscaling 12 scenes of 990 m Moderate Resolution Imaging Spectroradiometer (MODIS) and aggregated Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST products to 90 m resolution at six overpass times between 2005 and 2015 over three 9.9 km by 9.9 km cropland (mixed by grass, tree, and built-up land) study areas. Three typical LST downscaling methods, namely the widely applied TsHARP, the later developed least median square regression downscaling (LMS) and the geographically weighted regression (GWR), were introduced for intercomparison. The results showed that the DTsEB method could more effectively reconstruct the subpixel spatial variations in LST within the coarse-resolution pixels and achieve a better downscaling accuracy than the TsHARP, LMS and GWR methods. The DTsEB method yielded, on average, root mean square errors (RMSEs) of 2.01 K and 1.42 K when applied to the MODIS datasets and aggregated ASTER datasets, respectively, which were lower than those obtained with the TsHARP method, with average RMSEs of 2.41 K and 1.71 K, the LMS method, with average RMSEs of 2.35 K and 1.63 K, and the GWR method, with average RMSEs of 2.38 K and 1.64 K, respectively. The contributions of the related surface variables to the subpixel spatial variation in the LST varied both spatially and temporally and were different from each other. In summary, the DTsEB method was demonstrated to outperform the TsHARP, LMS, and GWR methods and could be used as a good alternative for downscaling LST products from coarse to fine resolution with high robustness and accuracy.

54 ENVIRONMENTAL SCIENCES↗

Next generation Arctic vegetation maps: Aboveground plant biomass and woody dominance mapped at 30 m resolution across the tundra biome

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m −2 ) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ∼6000 g m −2 (mean ≈ 350 g m −2 ), while predicted values ranged from 0 to ∼4000 g m −2 (mean ≈ 275 g m −2 ), resulting in model validation root-mean-squared-error (RMSE) ≈ 400 g m −2 and R 2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling.

Climate change↗

A comprehensive analysis of the crop effect on the urban-rural differences in land surface phenology

The response of land surface phenology (LSP) to the urban heat island effect (UHI) is a useful biological indicator for understanding how vegetated ecosystems will be affected by future climate warming. However, vegetation cover in rural areas is often dominated by cultivated land, whose phenological timing is considerably influenced by agricultural managements (e.g., timing of sowing and harvesting), leading to biased conclusions derived from the urban-rural LSP differences. To demonstrate this problem, we investigated the crop influence on the phenological response to a warmer environment resulting from the UHI effect. We partitioned cities in the United States into cultivated and non-cultivated categories according to the proportion of crops in rural areas. We then built continuous buffer zones starting from the urban boundary to explore the urban-rural LSP differences considering the UHI effect on them. In this work, the results suggest crop inclusion is likely to lead to >14 days of urban-rural differences at both the start of the season (SOS) and the end of the season (EOS) between cultivated and non-cultivated cities. The temperature sensitivity (ST) of SOS is overestimated by approximately 2.7 days/°C, whereas the EOS is underestimated by 3.6 days/°C. Removing crop-dominated pixels (i.e., above 50 %) can minimize the influence of crop planting/harvesting on LSP and derive reliable results. We, therefore, suggest explicit consideration of crop impacts in future studies of phenological differences between urban and rural areas and the UHI effect on LSP in urban domains, as presented by this comprehensive study.

54 ENVIRONMENTAL SCIENCES↗

Shining light on nanoscale ‘vine-on-stick’ eutectic structures in the Al-Ce-Ni system

Multiphase eutectics often comprise entangled solid phases with nanoscale periodicity, making it difficult to unravel their 3D connectivity using conventional 2D techniques. Among such systems, the three-phase eutectic Al-Al 11 Ce 3 -Al 3 Ni stands out for its ultrafine (∼100 nm) interphase spacing and promising creep resistance, yet its microstructure remains relatively unexplored despite its potential for high-temperature applications. Here, we use scanning hard X-ray microscopy with an unprecedented ∼10 nm pixel size to resolve its 3D morphology. Reconstructions reveal a novel “vine-on-stick” motif, wherein Al 11 Ce 3 wraps around Al 3 Ni pillars. Analysis of phase tortuosities confirms that Al 11 Ce 3 exhibits more convoluted morphologies than Al 3 Ni. No orientation relationship was observed between the two intermetallics, suggesting that growth is controlled by local solute gradients rather than epitaxy. Fragmentation of intermetallics along their longitudinal axis suggests a Rayleigh-type breakup mechanism in solid state. The “vine-on-stick” pattern may generalize to other alloy systems with variable interfacial anisotropies and low mutual solubilities.

36 MATERIALS SCIENCE↗

SNAPRed: Reduction of multidimensional neutron time-of-flight diffraction data

SNAP is a neutron time-of-flight diffractometer at the Spallation Neutron Source operated by Oak Ridge National Laboratory. It generates large arrays of neutron detection events that encode the crystalline atomic structure of materials under study. SNAPRed is an application that makes these datasets accessible to end users by orchestrating the process of data reduction while automatically managing the variable neutron instrumentation configuration. It supports arbitrary grouping and masking of individual detector pixels and includes custom-developed data compression approaches to accommodate the large volumes of data generated by the SNAP instrument.

Diffraction↗