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macroMS: Image-Guided Analysis of Random Objects by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Mass spectrometry imaging is well-suited to characterizing sample surfaces for their chemical content in a spatially resolved manner. However, when the surface contains small objects with significant empty spaces between them, more efficient approaches to sample acquisition are possible. Image-guided mass spectrometry (MS) enables high-throughput analysis of a diverse range of sample types, such as microbial colonies, liquid microdroplets, and others, by recognizing and analyzing selected location targets in an image. Here, we describe an imaging protocol and macroMS, an online software suite that can be used to enhance MS measurements of macroscopic samples that are imaged by a camera or a flatbed scanner. Furthermore, the web-based tool enables users to find and filter targets from the optical images, correct optical distortion issues for improved spatial location of selected targets, input the custom geometry files into an MS device to acquire spectra at the selected locations, and finally, perform limited data analysis and use visualization tools to aid locating samples containing compounds of interest. Using the macroMS suite, an enzyme mutant library of Saccharomyces cerevisiae and nL droplet arrays of Escherichia coli and Pseudomonas fluorescens have been assayed at a rate of ~2 s/sample.

47 OTHER INSTRUMENTATION↗

Methodology for physics-informed generation of synthetic neutron time-of-flight measurement data

Accurate neutron cross section data are a vital input to the simulation of nuclear systems for a wide range of applications from energy production to national security. The evaluation of experimental data is a key step in producing accurate cross sections. There is a widely recognized lack of reproducibility in the evaluation process due to its artisanal nature and therefore there is a call for improvement within the nuclear data community. This can be realized by automating/standardizing viable parts of the process, namely, parameter estimation by fitting theoretical models to experimental data. This automation effort could greatly benefit from a synthetic data resource. This work leverages problem-specific physics, Monte Carlo sampling, and a general methodology for data synthesis to generate unlimited, labelled experimental cross-section data that is statistically indistinguishable to the observed data. Heuristic and, where applicable, rigorous statistical comparisons to observed data support this claim. The demonstration is based on/limited to transmission measurements at Rensselaer Polytechnic Institute (RPI) and energy-differential cross sections in the resolved resonance region (RRR). An open-source software is published alongside this article that executes the complete methodology to produce high-utility synthetic datasets. The goal of this work is to provide an approach and corresponding tool that will allow the evaluation community to begin exploring more data-driven, ML-based solutions to long-standing challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SimELIT: A Novel GUI-Based Comprehensive Ion Trajectory Simulation Software for Mass Spectrometry

Ion trajectory simulation in mass spectrometry systems from injection to detection is technically challenging but very important for better understanding the ion dynamics in instrument development. Here, in this work, we present SimELIT (Simulator of Eulerian and Lagrangian Ion Trajectories), a novel ion trajectory simulation platform. SimELIT is built upon a suite of multiphysics solvers compiled into OpenFOAM (an open-source numerical solver library particularly used for computational mechanics), with a simple web-based graphical user interface (GUI) allowing users to define the details of OpenFOAM cases and run simulations. SimELIT is a modular program and can provide extensions of physics (e.g., gas flows, electrodynamic fields) and thus enable ion trajectory simulations from the ion source to detector. The current version (SimELIT) provides two numerical solvers for ion trajectory simulations–(1) a Lagrangian particle tracker in vacuum and (2) a Eulerian ion density solver in background gas in the presence of electric fields. Here, we describe the architecture of SimELIT, including its use of Docker and the React Framework, and demonstrate the computation of ion trajectories of multiple m/z values in a static/linear voltage drop in vacuum (across a 1 m long flight tube). Further, the drift motion of ions under 1 Torr pressure conditions in a static background (N 2 ) gas through a 20 V/cm static electric field is shown. The results produced from SimELIT were compared with SIMION and theoretical estimates. In addition, we report the computation of ion trajectories in electrodynamic fields within a planar FAIMS device operating at atmospheric pressure.

97 MATHEMATICS AND COMPUTING↗

An Open Source Perovskite Solar Cell Curve Tracer

When developing systems for perovskite solar cells (PSCs), it is important to have a testing platform that closely resembles your deployed systems. While developing a 1 U CubeSat, the Big Red Sat-1 at the University of Nebraska-Lincoln, we found a lack of passive curve tracing instrumentation, which we needed for our mission. To that end, we developed a benchtop passive curve tracer that leverages the Ossila Solar Simulator as an AM1.5 light source. This device utilizes a ladder of switched resistors and a precision voltage and current measurement to achieve the curve tracing. It also integrates a common-anode multiplexer to switch through multipixel PSCs. Finally, the solar cell holder is separate from the main measurement system, so various substrates sizes and pixel counts can be supported. This system is tested using various PSCs. It has been open sourced to enable reuse in future systems that may benefit from the lower power consumption and flight heritage.

14 SOLAR ENERGY↗

Coupling of high-resolution mass spectrometer and photosynthesis system for comprehensive leaf volatile metabolite profiling

Background Leaf-level biogenic volatile organic compounds (BVOCs) emissions represent a major source of organic gases in the atmosphere, influencing both climate and air quality. These emissions are strongly driven by environmental perturbations, which affect individual plant- to ecosystem-level processes. Uncovering all the BVOCs and understanding how their emissions respond to altered environmental conditions provide critical insights into vegetation-driven changes in atmospheric chemistry. We developed a tandem instrumentation setup that integrates a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) with parts-per-trillion detection limits and a photosynthetic infrared gas exchange system for the untargeted survey of all the BVOCs. This novel system enables simultaneous, real-time monitoring of BVOC emissions and photosynthetic parameters at the leaf level, offering new opportunities to disentangle the physiological and environmental drivers of VOC release. Furthermore, we established the VOC Analysis and Processing Optimization Resource (VAPOR), an open-access software tool designed for rapid data post-processing and the analysis of the variability of hundreds of BVOCs. We assessed the performance of the tandem system under varying background conditions, using standard gas mixtures and a range of environmental factors. Results Blank emissions were substantially lower for major BVOCs (e.g., isoprene) compared to those observed in plant emissions. Despite this, the observation of background-level VOCs highlights the importance of routinely acquiring and accounting for blank measurements in analyses using the coupled instrumentation. Introduction of known VOC concentrations to the system demonstrated a linear response across different compounds with varying molecular compositions, indicating minimal gas loss regardless of chemical moieties within the coupled instrumentation. We applied the optimized system to investigate the physiological mechanisms driving BVOC emissions across different genotypes of poplar and pennycress. The high mass resolution capabilities of the PTR-ToF-MS, coupled with comprehensive VAPOR-driven data analysis, enabled the identification of several important BVOCs, including methanol and methanethiol; these BVOCs displayed substantial variation across pennycress genotypes and showed concentrations ~ 100–350% higher than the blank. Moreover, isoprene emissions varied significantly among poplar genotypes grown in different potting media. Conclusions Tandem instrumentation offers a powerful tool for profiling volatile molecular markers and elucidating their genetic and environmental underpinnings. This approach enhances our ability to predict BVOC emissions in response to genotype by environmental interactions and contributes to a deeper understanding of vegetation responses to environmental changes.

Biogenic volatile organic compounds↗

A VXS [VITA41] Trigger Processor for the 12GEV Experimental Programs at Jefferson Lab

The VXS_Trigger_Processor [VTP] was developed and commissioned for CLAS12 in the fall of 2016. This board is a VITA41 switch card and it collects data from a variety of front-end TDC and Flash ADC modules. The VTP has since been used in several experiments at Jefferson Lab serving as the L1 trigger module for a variety of detector types, such as stacked calorimeters, strip calorimeters, time-of-flight, Cerenkov, hodoscopes, drift chambers, and silicon strips. Trigger algorithms implemented include cluster finding (1D, 2D), drift chamber segment and road finding, geometry matching between various detectors, particle counting, and general global trigger bit processing. The VTP is also capable of reading out each front-end crate with up to 40Gbps Ethernet which is an enormous increase compared to the currently used 200MB/s VME bus. Recent progress has been made to show that a firmware and software upgrade can enable existing Jefferson Lab front-end crates to operate in a streaming DAQ mode. In February 2020, tests will be performed on a full calorimeter and matched hodoscope which are components of the CLAS12 Forward Tagger detector system with beam in Hall B. This paper details the hardware performance, triggered, and streaming applications that have been implemented using the VTP for several experiments at Jefferson Lab.

ABBOTT, David↗

CROCUS Air Quality Dataset from the University of Illinois Chicago (UIC), July 2024

This dataset was collected by the measurement system in the Atmosphere, Climate, and Ecosystems (ACE) Lab at the University of Illinois Chicago (UIC) from July 12 to July 31, 2024, as part of the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory.To enhance understanding of urban air quality dynamics in Chicago, and as part of the CROCUS 2024 Urban Canyon Intensive Observation Period (IOP), several instruments were set up to provide continuous measurements of air quality parameters in Chicago during July 2024. These measurements cover both aerosols and gas-phase species. It focuses on particle size distribution (2.5–478 nm) measured by two Scanning Mobility Particle Sizers (SMPS) at a 4-min resolution, total particle number concentrations at a 1-s resolution, and chemical composition from a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (AMS) at a 1-min resolution. Key gas-phase species, including NO, NO₂, SO₂, and O₃, are measured at a 1-min resolution, along with high-resolution NO and dimethyl sulfide (DMS) data from a Chemical Ionization Mass Spectrometer (CIMS). Volatile organic compound (VOC) data for toluene, isoprene, and benzene are provided by a GC-PID with a time resolution of 25 minutes.The data are formatted as NetCDF (.nc) files, making them easily accessible using common software such as MATLAB, R, and Python. Each parameter is stored in an individual dataset, which includes detailed instrument information in the header, as well as the corresponding sample start time and concentration/distribution data for each sample.

54 ENVIRONMENTAL SCIENCES↗

Novel principal component analysis tool based on python for analysis of complex spectra of time-of-flight secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis tool, which can simultaneously provide elemental, isotopic, and molecular information with part per million (ppm) sensitivity. However, each spectrum may be composed of hundreds of ion signals, which makes the spectra data complex. Principal component analysis (PCA) is a multivariate analysis technique that has been widely used to figure out the variances among samples in ToF-SIMS spectra data analysis and is showing great success in the explanation of complex ToF-SIMS spectra. So far, several software tools have been developed for PCA of ToF-SIMS spectra; however, none of them are freely available. Such a situation leads to some difficulties in extending applications of PCA to various research fields. More importantly, it has long been challenging for common researchers to understand PCA plots and extract chemical differences among samples. In this work, we developed a new and flexible software tool (named “advanced spectra pca toolbox”) based on python for PCA of complex ToF-SIMS spectra along with an easy-to-read manual. It can generate data analysis reports automatically to explain chemical differences among samples, allowing less experienced researchers to easily understand tricky PCA results. Moreover, it is expandable and compatible with artificial intelligence/machine learning functions. Pure goethite and different lignin adsorbed goethite samples were used as a model system to demonstrate our new software tool, proving that our software tool can be readily used in complex spectra data processing. Our new software tool is open-source, convenient, flexible, and expandable. We expect this open-source tool will benefit the ToF-SIMS community.

47 OTHER INSTRUMENTATION↗

OpenCSP v.1.0

SAND2024-08987O OpenCSP analyzes and improves the performance of optical mirrors that reflect sunlight and concentrate it onto a receiver. The algorithms in this library analyze the flow of light from an original source—such as the sun—reflecting off one or more mirrors, and onto a receiver, optical screen, or camera. OpenCSP also analyzes optical systems using other techniques, such as shape or slope comparison. The software calculates aggregate properties of the optical system, such as its efficiency, manufacturing error, pointing control error, expected performance, and other useful parameters. OpenCSP also includes high-level tools, such as Open SOFAST, a program that obtains high-resolution measurement of CSP mirrors, full heliostats, and other CSP collectors. OpenCSP supports producing meaningful output data to help CSP designers and field operators improve the performance of their systems. OpenCSP also includes classes and functions that support these calculations, including input utilities, analysis output libraries, geometric constraint analysis for drone flight planning, and more. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Brost, Randolph↗

Implementation of a High-Mach Integral Boundary Layer Method for Arbitrary Streamlined Body Geometry

The Momentum-Energy Integral Technique (MEIT) is an integral boundary layer method for the high-Mach flow regime used to approximate heat transfer and viscous force quantities of interest along streamlines of an inviscid flow solution on the surface of a flight vehicle. This method allows rapid mid-fidelity estimation of these quantities which would otherwise require a much more expensive viscous flow solution to produce. Integral boundary layer methods like MEIT have been around for decades, though usually only formulated for simple geometries such as 2-dimensional wing shapes or axi-symmetric nose shapes. The implementation discussed herein has been generalized to apply to any 3-dimensional streamlined body geometry through correct treatment of the curvilinear axes (streamline attached) momentum and energy entrainment terms, and handling of arbitrary stagnation region geometry. This implementation is provided as a software package for the Python environment, along with readers for common inviscid flow solution providers such as NASA’s CART3D flow solver.

97 MATHEMATICS AND COMPUTING↗

Cloud Droplet Measurement System for the ARM Tethered Balloon System (TBS) Field Campaign Report

The Mesa Photonics' cloud droplet measurement system (CDMS) performs in situ measurement of droplet size distribution and droplet number density in clouds. These characteristics are important cloud microphysical properties that are critical input parameters for atmospheric models and are also useful for proper calibration and validation of performance of other atmospheric measurement instrumentation. This small campaign was the first project (out of two) that involved integration of the CDMS into the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s tethered balloon system (TBS) and its initial testing at the ARM Southern Great Plains (SGP) atmospheric observatory. The follow-up campaign (AFC07016) involved testing of the CDMS under relevant conditions at the third ARM Mobile Facility (AMF3) at Oliktok Point, Alaska and making in situ measurements in clouds. The goal of this small field campaign was to deploy the CDMS on the ARM TBS, demonstrate its integrity and compatibility with the TBS, and test the wireless telecommunication system in preparation for subsequent in-cloud measurements at ARM’s North Slope of Alaska (NSA) observatory at Utqiagvik (formerly Barrow). The specific technical objectives included: (1) Integration of the Mesa Photonics' CDMS into the ARM TBS, (2) testing of the wireless telecommunication system of the CDMS, (3) evaluating the data acquisition software and image processing algorithms especially under high-background-illumination conditions, and (4) testing the ruggedness of the instrument's optical alignment and other performance characteristics. All objectives have been successfully met. The mounting hardware was designed and built mostly at Sandia National Laboratories (SNL), which allowed reliable mounting of the CDMS on the TBS and co-locating the CDMS with other instruments. The field tests were performed by the principal investigator (PI) in collaboration with the TBS operational crew led by D. Dexheimer. The field testing demonstrated good compatibility of the CDMS with the TBS. During the TBS flights, the crew did not experience any operational issues with the CDMS. The instrument demonstrated reliable operational characteristics, including sufficient battery life and good thermal management. The wireless telecommunication system has been successfully tested at TBS flight altitudes of up to 1000 m. During all flights, the CDMS raw data were wirelessly transmitted to the ground station and processed in real time. The ruggedness of the instrument's optical alignment was evaluated by performing calibration of the CDMS (using Mesa Photonics' fixed-size monodisperse droplet generator) before and after the campaign. The calibration was stable within the instrument's measurement precision. In summary, the campaign demonstrated good compatibility of the Mesa Photonics' CDMS with the ARM TBS. The flight tests confirmed the mechanical integrity of the CDMS and stability of its optical layout, as well as reliability of the wireless telecommunication system. Successful completion of this campaign provided a solid basis for the next campaign (AFC07016, November 2020), that involved testing of the CDMS during in-cloud TBS flights at AMF3 at Oliktok Point.

54 ENVIRONMENTAL SCIENCES↗

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗

CHESS 2025: Location data for field observations and sampling

This dataset represents geolocation data associated with field observations and sampling from the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Location data were collected using Trimble DA2 Global Navigation Satellite System (GNSS) receivers with Trimble Catalyst 2 centimeter (cm) positioning service and the Environmental Systems Research Institute (Esri) Field Maps mobile app. Files in this data package include meadow site polygons, shrub site polygons, tree site polygons and stem point locations, and Leaf Area Index (LAI) plot polygons (.geojson). The geojson files can be opened with open-source GIS software (e.g, QGIS). A csv file is also provided with point coordinates for all locations. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

Ultra High Performance Liquid Chromatography with Quadrupole Time-of-Flight Mass Spectrometry and Fisher Ratio Analysis for Discovery-Based Analysis

The ability to discover minute differences between samples or sample classes for ultrahigh performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) can be a challenging endeavor especially when these differences are not known a priori. Indeed a typical UHPLC-QTOF analysis time of ~15 minutes can generate over 4 gigabytes of information for a single sample. Implementation of chemometrics such as Fisher ratio (F-ratio) analysis will allow the analyst to quickly and precise probe the chemical differences between different samples or sample classes. F-ratio analysis can be used to find sample or sample class distinguishing compounds reducing the 5 gigabytes of information into a simple, yet informative hit list. Moreover through combinatorial rearrangement, it is possible to determine a F-ratio threshold to separate the real and non-real hits. The F-ratio software presented herein is a semi-automated algorithm that processes the raw, exported .csv files from the SCIEX 500R QTOF in as little as 30 seconds. While further research is needed to modify and perfect the software to deal with high resolution mass spectra precise to 0.0001 Daltons, the current software, precise to 0.1 Da, is able to find significant chemical differences despite some of them being at extremely low concentrations nearing the limit of detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stereo-vision thermal imaging system for tracking flying animals in wind farm areas (CRADA #763) Abstract

CRADA 763: abstract ThermalTracker-3D (TT3D) is a stereo vision thermal imaging system that provides 3D flight information on detected birds, bats, and other flying targets. The system was initially developed for use in the siting and monitoring of offshore wind projects to establish pre-construction and operation collision risk data but can be applied to terrestrial wind energy projects as well as national security monitoring. This technology will reduce monitoring cost, decrease processing time, and provide more accurate data for wind energy developers/operators and regulatory agencies. While the current technology is at a high level of readiness, Technology Readiness Level (TRL) 7, there remain several barriers to commercialization, particularly around ease-of-use, that result in a low Adoption Readiness Level (ARL). The proposed work will advance commercialization readiness by streamlining calibration methods for built systems. This work will:1. 1. develop a software package for factory and dynamic calibration processes 2. test that package with existing prototype TT3D systems, and 3. conduct outreach with industry end-users.

ThermalTracker↗

POWTEX visits POWGEN

The high-intensity time-of-flight (TOF) neutron diffractometer POWTEX for powder and texture analysis is currently being built prior to operation in the eastern guide hall of the research reactor FRM II at Garching close to Munich, Germany. Because of the world-wide 3 He crisis in 2009, the authors promptly initiated the development of 3 He-free detector alternatives that are tailor-made for the requirements of large-area diffractometers. Herein is reported the 2017 enterprise to operate one mounting unit of the final POWTEX detector on the neutron powder diffractometer POWGEN at the Spallation Neutron Source located at Oak Ridge National Laboratory, USA. As a result, presented here are the first angular- and wavelength-dependent data from the POWTEX detector, unfortunately damaged by a 50 g shock but still operating, as well as the efforts made both to characterize the transport damage and to successfully recalibrate the voxel positions in order to yield nonetheless reliable measurements. Also described is the current data reduction process using the PowderReduceP2D algorithm implemented in Mantid [Arnold et al. (2014). Nucl. Instrum. Methods Phys. Res. A , 764 , 156–166]. The final part of the data treatment chain, namely a novel multi-dimensional refinement using a modified version of the GSAS-II software suite [Toby & Von Dreele (2013). J. Appl. Cryst. 46 , 544–549], is compared with a standard data treatment of the same event data conventionally reduced as TOF diffraction patterns and refined with the unmodified version of GSAS-II . This involves both determining the instrumental resolution parameters using POWGEN's powdered diamond standard sample and the refinement of a friendly-user sample, BaZn(NCN) 2 . Although each structural parameter on its own looks similar upon comparing the conventional (1D) and multi-dimensional (2D) treatments, also in terms of precision, a closer view shows small but possibly significant differences. For example, the somewhat suspicious proximity of the a and b lattice parameters of BaZn(NCN) 2 crystallizing in Pbca as resulting from the 1D refinement (0.008 Å) is five times less pronounced in the 2D refinement (0.038 Å). Similar features are found when comparing bond lengths and bond angles, e.g. the two N—C—N units are less differently bent in the 1D results (173 and 175°) than in the 2D results (167 and 173°). The results are of importance not only for POWTEX but also for other neutron TOF diffractometers with large-area detectors, like POWGEN at the SNS or the future DREAM beamline at the European Spallation Source.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CHESS 2025: Waveform LiDAR data from NEON AOP surveys

This dataset provides Level 1 (L1) full-waveform light detection and ranging (LiDAR) data collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). These data were acquired to enable characterization of vegetation structure and other three-dimensional features of the land surface, and to evaluate structural changes that may have occurred between a prior LiDAR acquisition in 2018 and the 2025 overflight. Waveform LiDAR data can provide more detailed information about objects on the ground than discrete point clouds typically do, and they are often used for granular target segmentation and characterization of subcanopy vegetation. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. LiDAR data were acquired using the Optech Galaxy Prime Airborne LiDAR Terrain Mapper onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). These are the primary waveform LiDAR data delivered by NEON and are provided per flightline in compressed Pulsewaves format, an open-source binary file standard. A Pulsewaves object comprises a two files: a pulse (.pls) file, which stores the geographic origin, outgoing vector, and metadata for every laser pulse emitted by the scanner, and a wave file (.wvs), which stores the sequential amplitude samples of the outgoing pulse and the returning signals. The files are published here in their compressed forms (.plz, .wvz). All waveform data were processed following the theoretical workflow described in the NEON L0-to-L1 Waveform LiDAR Algorithm Theoretical Basis Document (Krause and Goulden 2022a); however, the Pulsewaves output format differs from a legacy format described in that document. Waveform amplitude samples are recorded at 1 nanosecond intervals. All coordinates are provided in meters. Horizontal coordinates are referenced in Universal Transverse Mercator (UTM) zone 13N and the World Geodetic System (WGS) 1984 ensemble datum. Elevations are referenced to Geoid12A. Waveform data for the UPTA survey area were collected without incident and the published records are complete. However, both the ALMO and CRBU collections experienced issues that resulted in incomplete data for those areas. On collection day 2018-06-16 a hardware failure caused the waveform digitizer to lose data from the eastern edge of the ALMO site (Figure 22). The waveform data for flightlines 2–20 could not be extracted from the digitizer, and the data proved unrecoverable. As a result, a portion of the site does not have coverage with waveform data. Although no hardware failure was observed during collection over the CRBU area, final waveform files generated by vendor software contained only ~25% of the expected number of return pulses. After discovery, NEON initiated troubleshooting with the vendor. The root cause of the data ablation had not been identified at the time of publication. Additional data will be published in an update to this package if further recovery proves successful. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

Integrating ytopt and libEnsemble to autotune OpenMC

Ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that consists of sampling a small number of input parameter configurations and progressively fitting a surrogate model over the input-output space until exhausting the user-defined maximum number of evaluations or the wall-clock time. libEnsemble is a Python toolkit for coordinating workflows of asynchronous and dynamic ensembles of calculations across massively parallel resources developed within the ECP PETSc/TAO project. libEnsemble helps users take advantage of massively parallel resources to solve design, decision, and inference problems and expands the class of problems that can benefit from increased parallelism. In this paper we present our methodology and framework to integrate ytopt and libEnsemble to take advantage of massively parallel resources to accelerate the autotuning process. Specifically, we focus on using the proposed framework to autotune the ECP ExaSMR application OpenMC, an open source Monte Carlo particle transport code. OpenMC has seven tunable parameters some of which have large ranges such as the number of particles in-flight, which is in the range of 100,000 to 8 million, with its default setting of 1 million. Setting the proper combination of these parameter values to achieve the best performance is extremely time-consuming. Therefore, we apply the proposed framework to autotune the MPI/OpenMP offload version of OpenMC based on a user-defined metric such as the figure of merit (FoM) (particles/s) or energy efficiency energy-delay product (EDP) on Crusher at Oak Ridge Leadership Computing Facility. In conclusion, the experimental results show that we achieve the improvement up to 29.49% in FoM and up to 30.44% in EDP.

Autotuning↗