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At least 127 records · Page 7

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DOE OSTI2024

Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm2) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Understanding the Effect of Sample Geometry on Temperature Distribution during Optical Floating Zone Crystal Growth in Vacuum Environment through Heat Transfer Modeling

Optical floating zone furnaces (OFZ) have had a transformative impact on fundamental science due to their ability to rapidly produce large single crystals of a wide variety of complex materials. However, a quantitative understanding of the OFZ growth environment is generally lacking due to the difficulty of measuring the local sample temperatures during OFZ growth, as well as to the general lack of information about the temperature-dependent physical parameters needed to model heat transfer. To overcome these challenges, we apply a physics-based heat transfer model, parametrized by measurements from synchrotron experiments and a machine-learning (ML) algorithm, to simulate the temperature distributions of samples heated in an OFZ furnace in a vacuum environment. This model is used to quantitatively understand how the sample maximum temperature and temperature gradient (key parameters that influence the success of crystal growth) are affected by the rod size, rod shape, and heat-zone position on the rod. The results of this study can be applied to make informed decisions on how crystal growth parameters can be tuned to modify temperature profiles and to optimize crystal growth outcomes even when data on internal sample temperature profiles (e.g., those obtained through in situ synchrotron experiments) are not accessible.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Quasi-In-Situ Analysis of Electrode Top Atomic Layers via High-Sensitivity Low-Energy Ion Scattering and Potential-Controlled Sample Transfer

Electrocatalytic reactions involve interfacial interactions between the surfaces of electrodes and reactive species at an electrolyte interface. There are presently no universal or unambiguous methods to directly assay the active top atomic layer composition that influences the reactivity of these electrodes under relevant operating conditions. Low-energy ion scattering (LEIS) spectroscopy is a surface characterization technique that yields compositional analysis of the outermost atomic layer of a material, but it must be performed in ultrahigh vacuum (UHV). Application of LEIS measurements to electrochemical materials that are removed from ambient liquid-phase environments thus leaves an open question as to whether the surface that is transferred to UHV is truly the surface that manifested during the electrochemical reaction. Toward the goal of preserving the active surface state, we developed a sample transfer workflow for LEIS enabling air-free removal and drying of an electrode from an electrochemical cell while maintaining control of the potential using an auxiliary electrode. The potential-controlled emersion method was demonstrated to give distinct potential-dependent surface compositions for a Cu−Pd alloy relative to removal after uncontrolled return to open-circuit potential. A Cu-enriched surface was found at anodic potential and a Pd-enriched surface at cathodic potential, suggesting that the approach can be used to retain representative atomic configurations during transfer. Since adsorbates will often persist from the reaction environment, conventional sample pretreatment methods for removal, including atomic O and atomic H exposure, were also contrasted. Both methods were found to differ with results from incidental low-dose depth profiling by the LEIS primary ion source, which removes adventitious species and surface atoms during the course of repeated measurements. These depth profiles were found to be sensitive to sample history and thus qualitatively informative, despite the possible changes induced by ion damage. The results exhibit (i) the need for complete control over the polarization state of the sample at all times (no excursions to open circuit during transfer) and (ii) the utility of low-dose depth profiling to capture changes in the near-surface composition.

Alloys↗

DOE OSTI2024

X-ray Photoelectron Spectroscopy Analysis of Nafion-Containing Samples: Pitfalls, Protocols, and Perceptions of Physicochemical Properties

X-ray photoelectron spectroscopy (XPS) is one of the most common techniques used to analyze the surface composition of catalysts and support materials used in polymer electrolyte membrane (PEM) fuel cells and electrolyzers, providing important insights for further improvement of their properties. Characterization of catalyst layers (CLs) is more challenging, which can be at least partially attributed to the instability of ionomer materials such as Nafion during measurements. This work explores the stability of Nafion during XPS measurements, illuminating and addressing Nafion degradation concerns. The extent of Nafion damage as a function of XPS instrumentation, measurement conditions, and sample properties was evaluated across multiple instruments. Results revealed that significant Nafion damage to the ion-conducting sulfonic acid species (>50% loss in sulfur signal) may occur in a relatively short time frame (tens of minutes) depending on the exact nature of the sample and XPS instrument. This motivated the development and validation of a multipoint XPS data acquisition protocol that minimizes Nafion damage, resulting in reliable data acquisition by avoiding significant artifacts from Nafion instability. The developed protocol was then used to analyze both thin film ionomer samples and Pt/C-based CLs. Comparison of PEM fuel cell CLs to Nafion thin films revealed several changes in Nafion spectral features attributed to charge transfer due to interaction with conductive catalyst and support species. This study provides a method to reliably characterize ionomer-containing samples, facilitating fundamental studies of the catalyst-ionomer interface and more applied investigations of structure-processing-performance correlations in PEM fuel cell and electrolyzer CLs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Citywide indoor air sampling mirrors wastewater and clinical for environmental surveillance of respiratory viruses

Wastewater surveillance of respiratory pathogens can provide timely estimates of viral activity and disease trends in a population. Indoor air surveillance could be used similarly with some advantages but remains largely unvalidated at the community -scale. Here, an indoor air surveillance program was employed as part of public health environmental surveillance in Chicago, Illinois, USA. Ten air samplers were placed in healthcare and congregate living settings across the city. Weekly air samples were evaluated for influenza A, influenza B, respiratory syncytial virus, and SARS -CoV-2 over two respiratory virus seasons (2023 -2025). Citywide, aggregated air sample positivity and viral load were closely correlated with local clinical case and wastewater surveillance data across all respiratory viruses. Virus trends in air data often preceded clinical and wastewater, although this varied across pathogens and respiratory virus seasons. Further, whole -genome sequencing of SARS -CoV-2 showed close correlation of variant proportions across all datasets. At the building -scale, air samples obtained from a single sampling device provided efficient respiratory virus surveillance, with respiratory pathogen levels mirroring citywide clinical surveillance data. These data demonstrate that air surveillance can provide respiratory virus case and variant trend data at a building or community -scale, serving as an alternative or complementary tool for public health environmental surveillance.

Wilton, Rosemarie↗

DOE OSTI2024

Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22–1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Sample changers for direct geometry neutron chopper spectrometers

The advent of higher flux neutron sources has made the use of sample changers appropriate across the instrument suites at neutron scattering facilities. We examine the efficiency, design, and operation of two sample changers used at the thermal chopper spectrometers at the Spallation Neutron Source. We also present case studies of sample holders designed to accommodate multiple single crystal or powder samples for the Cold Neutron Chopper Spectrometer at the Spallation Neutron Source. [This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).]

Stone, Matthew B. [Oak Ridge National Laboratory (↗

DOE OSTI2025

Sample glue layer investigation and mitigation for laser induced prompt impulse experiments

Understanding longer timescale material reactions under dynamic stress loading is critical for applications in materials engineering, shock physics, and planetary science. Prompt impulse experiments generate lower pressures since the ablator—the material first removed by the laser—is thicker and farther from the diagnostic plane, capturing aggregate material responses from the initial shock wave, rarefaction waves, and later time effects. This complexity demands thorough material characterization and simulation support. Since traditional sample construction is specific to supported shock experiments, designing prompt impulse experiments requires reconsideration around target design and sample engineering. Here, we present sample preparation techniques, experimental investigations, and theoretical simulations to investigate glue layer impacts, aiming to standardize samples for consistent data at lower laser fluences. We find that glue layers <30 μm have a minimal impact on peak velocity and pulse shape. The peak velocity scales linearly with glue layer thickness until a glue layer of 75 μm. For glue layers >75 μm, the peak velocity no longer scales with thickness; however, the pulse shape continues to degrade as described by simulations.

Lasers↗

DOE OSTI2025

Experimental Setup to Investigate Hydrogen Isotope Retention on Powder Samples as Slag/Dust Proxies for Advanced Fusion Reactors

Slag/dust formation is one of the critical issues regarding tritium retention in advanced fusion reactors. We upgraded an ultrahigh vacuum device, the sample exposure station (SES), to perform temperature-programmed desorption (TPD), also known as thermal desorption spectroscopy, to investigate deuterium (D) retention in powder samples that are utilized as proxies for slag/dust particles formed in fusion reactors. TPD analysis, calibrated for the desorption rate, was successfully performed on commercially available crystalline/amorphous boron (B) powder after D 2 neutral gas or D + ion exposure. We calibrated the B powder temperature measurement for TPD analysis utilizing a D 2 desorption peak from B-D bonding known for its desorption temperature ~700 K. We introduce a separation procedure of observed D TPD signals, convoluted for corresponding D retention pathways, that was necessary for TPD analysis. This is the first report on the retention of D 2 neutral gas to B, and this observation was enabled by utilizing the B powder sample, which has a larger surface area than films commonly used in laboratory experiments. In conclusion, the upgraded SES system will enable us to investigate hydrogen isotope behaviors for powder/dust samples of various elemental compositions, including metals.

Plasma-facing component debris↗

DOE OSTI2025

Simulation driven adaptive sampling for neutron-diffraction based strain mapping of additively manufactured parts

Neutron diffraction based strain mapping is a useful technique for measuring residual strains in additively manufactured (AM) metal parts. The measurement is traditionally done by scanning the sample in a point-wise raster pattern to extract the strain at each position. Since the overall scan can span several hours, adaptive sampling approaches using Bayesian optimization based on Gaussian process (BO-GP) regression have been introduced—demonstrating that even with a fraction of the typically made measurements the dominant strain patterns in the sample can be reconstructed. However, the parameters of the BO-GP algorithm have to be carefully chosen for best performance, and the movement time between arbitrary points can offset the time savings from a reduced number of measurement locations. In this paper, we propose algorithms to refine the BO-GP based methods by using simulations of strain patterns in AM parts based on the materials and the process used to print them. We demonstrate that the simulated strain patterns can be used to help choose better parameters for the BO-GP based framework—leading to low reconstruction error for the final strain pattern. Furthermore, we show that the strain mapping experiment can be initialized with a sampling pattern learnt from the simulation data and ordered to reduce movement time, dramatically enabling reduction in the overall time required to run the baseline BO-GP method.

Gaussian process regression↗

DOE OSTI2024

Generating mock galaxy catalogues for flux-limited samples like the DESI Bright Galaxy Survey

ABSTRACT Accurate mock galaxy catalogues are crucial to validate analysis pipelines used to constrain dark energy models. We present a fast HOD-fitting method which we apply to the AbacusSummit simulations to create a set of mock catalogues for the DESI Bright Galaxy Survey, which contain r-band magnitudes and $(g-r)$ colours. The halo tabulation method fits HODs for different absolute magnitude threshold samples simultaneously, preventing unphysical HOD crossing between samples. We validate the HOD fitting procedure by fitting to real-space clustering measurements and galaxy number densities from the MXXL BGS mock, which was tuned to the SDSS and GAMA surveys. The best-fitting clustering measurements and number densities are mostly within the assumed errors, but the clustering for the faint samples is low on large scales. The best-fitting HOD parameters are robust when fitting to simulations with different realizations of the initial conditions. When varying the cosmology, trends are seen as a function of each cosmological parameter. We use the best-fitting HOD parameters to create cubic box and cut sky mocks from the AbacusSummit simulations, in a range of cosmologies. As an illustration, we compare the ${}^{0.1}M_r\lt -20$ sample of galaxies in the mock with BGS measurements from the DESI one-percent survey. We find good agreement in the number densities, and the projected correlation function is reasonable, with differences that can be improved in the future by fitting directly to BGS clustering measurements. The cubic box and cut-sky mocks in different cosmologies are made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Improving statistical precision in Monte Carlo samples with negative weights via reweighting and uncertainty quantification

High statistical precision is critical for Monte Carlo (MC) samples in high energy physics and is degraded by negatively weighted events. This paper investigates a procedure to learn the relationship between the negative and positive weight distributions of any sample, allowing the reduction of statistical uncertainty by reweighting kinematically equivalent events with the same sign. A robust uncertainty quantification method is required for the practical application of such method. Two methods for the estimation of the reweighting uncertainty are developed: one at the event and another one at the final observable level. The latter method is strongly favored. The gains in statistical precision are then quantified. The method is demonstrated on Sherpa vector boson plus jets samples when using all generated events and when restricted to the signal region of a mock analysis. It is demonstrated to significantly reduce stochastic behavior in sparse MC samples while decreasing the overall uncertainty with a sufficiently well-known reweighting function.

Monte Carlo methods↗

DOE OSTI2025

A fully contained sample holder capable of electron-yield detection at soft X-ray energies

A holder has been developed that enables electron yield-detected soft X-ray spectroscopy of fully contained samples at low temperature. Crucially, this design uses elements of the sample containment to collect ejected electrons, removing the need to expose samples directly to the vacuum environment of the spectrometer. The design is modular and should be adaptable to a number of different endstation configurations, enabling spectroscopy of air-sensitive, radioactive and vacuum-sensitive (biological) samples.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Sampling in Long-Screened Wells: Issues, Misconceptions, and Solutions

The issues associated with long-screened wells (LSWs) (and open boreholes) at contaminated sites are well documented in the groundwater literature but are still not fully appreciated in practice. As established in seminal and review papers going back over three decades, the interpretation of sampling results from LSWs is challenging in the presence of vertical hydraulic gradients and borehole flow; furthermore, LSWs allow for vertical redistribution of contamination between aquifer layers. Acknowledgment of these issues has led to the development of new technologies and well designs to enable discrete-zone monitoring (DZM), yet LSWs remain common for many reasons, for example, as multipurpose wells, for geophysical logging, and (or) as legacy installations. Despite the literature on LSWs and despite the adoption of DZM at many sites, the use of LSWs persists and the challenges of interpreting sampling results from LSWs remain. In this issue paper, we provide a conceptual overview of the problems posed by LSWs and review existing literature and past work to improve the interpretation of sampling in LSWs. We draw on experience from previous studies at the Hanford Site in eastern WA, USA, and use synthetic examples to illustrate key concepts and challenges for interpretation. A recently published analytical modeling framework is used to develop illustrative synthetic examples and demonstrate a workflow for building scientific intuition to understand issues around interpreting samples from LSWs, which is critical to effective characterization and groundwater remediation at sites with LSWs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Untargeted, tandem mass spectrometry (LC/MS-MS) metaproteomes from soil samples in control and warming plots in Blodgett Forest, CA (2014-2021)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization. This package contains soil metaproteomics data in the context of site specific metagenomes from soil depth profiles in three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. These metaproteomes were collected in 2018 after 4.5 years of warming from five depth intervals (0-10 cm, 10-30 cm, 30-45 cm, 45-60 cm, 60-80 cm). For protein identification, the collected spectra were searched following a target-decoy search strategy against a database of metagenome predicted proteins (covering 96 samples from 2014 to 2021) representing the complete sequence diversity at the site. Data was searched with mass spectrometry database search tool (MS-GF+) using Pacific Northwest National Laboratory (PNNL)'s Data Management System (DMS) Processing pipeline. The metagenomes are published as part of another data package. Raw metaproteomic data and the data products from MS-GF+ are deposited in the Mass Spectrometry Interactive Virtual Environment (MassIVE) database under accession no. MSV000097826. Here we present a dataset that includes spectral counts for the detected proteins across samples (EMSL50964_BrodieAllMAGs_Globals_SC.txt), the sequences of the detected proteins, and sample metadata file that contains site information for the soil metaproteome samples.

Belowground Biogeochemistry Science Focus Area↗

DOE OSTI2024

Results of Long-Term Analyses of the Salt (Macro) Batch 11 Tank 21H Qualification Sample

Savannah River National Laboratory (SRNL) analyzed samples from Tank 21H in support of qualification of Salt Waste Processing Facility (SWPF) Salt Batch 11. This document reports the long-term results of the analyses of the sample of Tank 21H. Analysis of this sample indicates that the material does not display any unusual characteristics or observations, such as visually apparent solids. However, the sample was dark colored. This report satisfies Deliverable 3 of the Technical Task Request (TTR).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Results of Long-Term Analyses of the Salt (Macro) Batch 11 Tank 21H Qualification Sample

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Compressed sensing methods with applications to advanced air sampling

Environmental sampling methods developed by the Savannah River National Laboratory (SRNL) employ collectors with sorbent media tubes set at various locations to collect airborne emissions. Laboratory analyses of these tubes results in one-dimensional signals regarding what chemicals are being released and transported within the atmosphere. The analysis process is time consuming especially when analyzing a full year’s worth of tubes (hourly sample collection results in nearly 9,000 tubes per year). Using a signal processing method such as compressed sensing allows for recreation of the full signal while greatly reducing the number of analyzed samples required. Due to the sparsity of data retrieved from the air tubes, it is possible to use measurements a fraction of the size of the original data to gain much of the same information. This would improve the overall time and cost of analysis when modeling one-dimensional sampling signals.

54 ENVIRONMENTAL SCIENCES↗