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At least 325 records · Page 18

SPARTAN and IMPROVE Comparison Experiment (SPICE) Interim Campaign Report

SPICE (the SPARTAN and IMPROVE Comparison Experiment) aims to obtain and quantify comparisons between aerosol PM 2.5 mass concentration measurements from the University of Oklahoma (OU) Surface Particulate Matter Network (SPARTAN) station and the U.S. Environmental Protection Agency (EPA) Interagency Monitoring of Protected Visual Environments (IMPROVE) station hosted by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility at ARM’s Southern Great Plains (SGP) observatory in Oklahoma. Aerosols—both natural and anthropogenic—affect human populations in multiple ways. Much of ARM’s research focuses on how aerosols influence weather and climate through their optical and radiative effects, as well as their impacts on clouds and precipitation. However, aerosols also pose direct risks to humans and other organisms through inhalation, with the severity of health impacts depending on particle size, chemical composition, and duration of exposure. The IMPROVE network was established by the U.S. EPA to monitor air quality, including visible clarity as well as total and chemically speciated aerosol mass concentrations. The ARM SGP site hosts the IMPROVE SOGP station. Separately, the SPARTAN network operates a globally distributed set of stations similar to IMPROVE but with an emphasis on remote deployment and semi-autonomous operation for use beyond the borders of the United States (IMPROVE only operates within the U.S.). The University of Oklahoma operates a SPARTAN station. To establish confidence in the OU SPARTAN instrumentation and measurement protocol relative to the EPA-certified IMPROVE station, the OU SPARTAN station is currently deployed at SGP in close proximity to the IMPROVE SOGP station. The SPICE campaign was envisioned as a contiguous calendar-year effort for 2025 to capture seasonal variation in mass loading as well as composition. However, independent of the SPICE campaign, the SPARTAN network adopted a new filter construction part-way through the year, interrupting our contiguous data set. Thus, to obtain a contiguous data set with a uniform consistent configuration, SPICE desires an extension through 2026.

54 ENVIRONMENTAL SCIENCES↗

High-performance and stable AgSbTe 2 -based thermoelectric materials for near room temperature applications

AgSbTe 2 -based ternary chalcogenides show excellent thermoelectric performance at low- and middle-temperature ranges, yet their practical applications are greatly limited by their intrinsic poor thermodynamic stability. In this work, we demonstrate that AgSbTe 2 -based ternary chalcogenides can be stabilized for service below their decomposition threshold. A series of Ag x Sb 2-x Te 3-x (x = 1.0, 0.9, 0.8 and 0.7) samples have been prepared by the melt-quenching method. Among them, phase pure Ag 0.9 Sb 1.1 Te 2.1 is verified by comprehensive structural characterizations from macroscale by X-ray diffraction to microscale by energy-dispersive spectroscopy and then to sub-nanometer scale by atom probe tomography. This composition is further chosen for the stability investigation. The decomposition threshold of Ag 0.9 Sb 1.1 Te 2.1 appears around 473K. Below this temperature, the chemical compositions and thermoelectric properties are barely changed even after 720 h annealing at 473 K. The figure-of-merit (zT) value of Ag 0.9 Sb 1.1 Te 2.1 below the decomposition threshold is very competitive for real applications even compared with Bi 2 Te 3 -based alloys. The average zT of Ag 0.9 Sb 1.1 Te 2.1 at 300–473 K reaches 0.84, which is higher than most other thermoelectric materials in a similar temperature range, promising applications in miniaturized refrigeration and power generation near room temperature.

36 MATERIALS SCIENCE↗

Strain rate sensitivity, microstructure variations, and stress-assisted β → α" phase transformation investigation on the mechanical behavior of dual-phase titanium alloys

In this study, the microstructures of three widely used dual-phase titanium alloys: Ti-6Al-4V, Ti-6Al-2Sn-4Zr-2Mo, and Ti-6Al-2Sn-4Zr-6Mo are characterized using backscatter electron imaging and the deformation behaviors in their individual α and β phases are investigated using in situ high-energy X-ray diffraction during uniaxial tension experiments. This is accompanied by calculation of the strain rate sensitivity (SRS) in these alloys, as a function of applied loading. The results of the calculated SRS and the mechanical response (in terms of lattice strains and hardening behaviors) are rationalized based on the local microstructure, composition, and texture of the alloy. A stress-induced β (BCC) to α" (orthorhombic) phase transformation is observed during the in-situ diffraction experiment, which permitted analysis of the lattice strain evolution during the phase transformation. Results from this study provide insights into the relationship between microstructure, composition, applied loading, and the deformation behavior, including effects on loading with time holds. Specifically, the results show that the microstructure, and not necessarily the chemical composition (Mo content), along with the applied loading have a dominant role in the observed SRS variation in titanium alloys. Further, the evolution of the α" (orthorhombic) phase is observed for the first time during deformation of an industrially relevant titanium alloy, Ti-6246.

36 MATERIALS SCIENCE↗

Organic matter concentration and composition of experimentally burned open air and muffle furnace vegetation chars across differing burn severity and feedstock types from Pacific Northwest, USA (v4).

This dataset represents results from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and feedstock materials. The dataset provides both solid and dissolved phase bulk concentration and organic matter characterization data from experimentally generated chars. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. This data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), fourteen burn table videos, burn table video metadata and three folders containing (A) data; (B) metadata and protocols; and (C) photos. The folder names and the file name of the data package readme include a version number which will be updated with future iterations of this data package. The data folder includes (1) solid carbon and solid nitrogen; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and total dissolved nitrogen (TN); (3) pH; (4) thermocouple time series temperature; (5) methods codes; (6) installation methods; (7) excitation emissions matrix (EEM) methods information; (8) a folder of excitation emissions matrix (EEM) fluorescence and absorbance spectra in dissolved organic matter and EEMs processing instructions; (9) solid state carbon-13 and solution state phosphorus nuclear magnetic resonance (13-C NMR and 31-P NMR) data and methods; (10) benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (11) FTICR-MS methods; (12) Inductively coupled plasma (ICP) data for total calcium, magnesium, iron, aluminum, potassium, phosphorus, sodium, and sulfur along with sodium hydroxide-ethylenediaminetetraacetic acid (sodium hydroxide-EDTA) extractable calcium, magnesium, iron, aluminum, potassium, phosphorus, and sulfur; (13) a folder of phosphorus, carbon, and nitrogen X-ray absorption near edge structure (P-XANES, N-XANES, C-XANES) data for samples and standards; (14) P-XANES, N-XANES, C-XANES methods; (15) molybdate reactive phosphorus; and (16) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains .txt data files and a subfolder containing instruments for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. The metadata and protocols folder includes (1) international geo-sample number (IGSN) mapping file (2) burn and laboratory metadata; (3) burn protocol; (4) laboratory protocol; (5) vegetation collection metadata; and (6) vegetation collection protocol. The folder contains photos of the solid chars. All files are .csv, .txt, .pdf, .jpg, .jpeg, .R, .ref, or .mp4. The data package was originally published October 2022 (v1). It was updated April 2023 (v2; new data files), September 2023 (v3; new and corrected data files), and September 2024 (v4; new and added/updated files). Metadata files were also updated to reflect these changes. See the change history section in the readme for more details.

54 ENVIRONMENTAL SCIENCES↗

Multimodal analysis and characterization of the boehmite layer formed on AA6061 before and after alkaline etching

Low-enriched uranium (LEU) alloyed with 10% Mo (U-10Mo) is being considered as a promising alternative to oxide-based dispersion fuel with high-enriched uranium for use in research reactors. The configuration of this proposed LEU monolithic LEU fuel plate consists of a U-10Mo plate-type fuel foil with a 25 µm zirconium interlayer barrier clad with an aluminum alloy (AA6061). In certain research reactors, the clad AA6061 is coated with a boehmite layer to prevent corrosion. The boehmite layer has a high-pH passivation range, which makes it resistant to oxidation. Boehmite is usually formed on the AA6061 surface by autoclave processing. Before the boehmite layer is added, the surface of the AA6061 is cleaned using techniques such as polishing and wet etching. In this study, we use multimodal analysis to examine how pretreatment of AA6061 using polishing followed by alkaline etching affects the chemical composition of the boehmite layer. X-ray photoelectron microscopy (XPS), transmission electron microscopy (TEM), and x-ray diffraction (XRD) were used to study the chemical changes in the boehmite layer caused by alkaline etching pretreatment. XPS provides quantitative analysis for the Al:O ratio as well as oxidation states present on the surface, which suggests slight oxidation of the boehmite surface after alkaline etching of the AA6061 surface. We further explored this suggested oxidation of the boehmite surface using high-resolution transmission electron microscopy with selected area electron diffraction (SAED) and grazing incidence x-ray diffraction (GI-XRD), which suggested only a small amount of aluminum oxide at the surface. The multimodal analysis and imaging yielded new insights for optimizing boehmite growth on AA6061 for research reactors.

36 MATERIALS SCIENCE↗

Influence of Clay Wettability Alteration on Relative Permeability

Abstract Understanding the wettability of porous materials is important to model fluid flow in the subsurface. One of the critical factors that influences wetting in real reservoirs is the composition of geologic materials. The wetting properties for clay minerals can have a particularly strong impact on flow and transport. In this work, we analyze the chemical composition of a Mt. Simon sandstone core to resolve the microscopic structure of clay regions and assess how alterations to the local wetting properties influence multiphase transport based on core flooding experiments and relative permeability simulations. We show that whichever fluid has greater affinity toward clay minerals will tend to accumulate within these high surface area regions, leading to dramatic shifts in the relative permeability. This work establishes the essential importance of the mineral composition and associated wetting properties in the modeling of flow and transport in reservoir‐scale systems.

Fan, Ming↗

Editorial: Functionalization of porous materials for sustainable energy applications

Global energy demands are shifting toward a more sustainable future, with the goal of achieving carbon neutrality by 2050. Emerging technologies are driving this transition. The industry, academia, government, non-profit organizations, and the broader community are collaboratively working to reduce greenhouse gas (GHG) emissions and address climate change to ensure a sustainable future. According to the International Energy Agency, in 2022, the production, transportation, and processing of oil and gas resulted in 5.1 billion tons of CO 2 -equivalent emissions, representing nearly 15% of all energy-related GHG emissions. Moreover, the end-use of oil and gas accounted for an additional 40% of emissions. The IEA’s Net Zero Emissions by 2050 Scenario calls for immediate, collective action from the industry, transportation and other stakeholders to mitigate these emissions. In this effort, the development of energy materials will play a critical role in reducing emissions. Among these, porous materials offer an innovative solution, leveraging their high surface area, adjustable pore sizes, and chemical versatility to address these pressing challenges effectively. By carefully designing their nanostructures, the architecture and properties of these materials can be tailored for specific applications. Key factors such as chemical composition, particle size, pore distribution, and surface area optimization enhance the reactivity and energy conversion efficiency. Additionally, pre- and post-functionalization processes can introduce targeted chemical properties, further improving their performance. This Research Topic explores recent advancements in energy and materials science through four scholarly papers, showcasing innovative solutions for sustainable energy technologies while providing valuable insights into the unique properties and structure of porous materials (Figure 1). Li et al. present their work on highly defective NiFeV layered triple hydroxides, highlighting enhanced electrocatalytic activity and stability for oxygen evolution reactions (OER). Kovalskii et al. contribute a mini-review on hydrogen storage using hexagonal boron nitride (h-BN) and BN-based materials, offering an insightful overview of these promising materials. Chava et al. discuss their recent achievements in ceramic electrolytes used for improvement of performance of solid-state batteries. Lastly, Li et al. review the properties of porous materials with a focus on shrinkage behavior during the drying process, shedding light on key considerations for material design.

36 MATERIALS SCIENCE↗

Exploration of Electrochemical Reactions at Organic–Inorganic Halide Perovskite Interfaces via Machine Learning in In Situ Time-of-Flight Secondary Ion Mass Spectrometry

The instability of hybrid organic–inorganic perovskite (HOIP) devices is one of the significant challenges preventing commercialization. Exploring these phenomena is severely limited by the complexity of the intrinsic electrochemistry of HOIPs, the presence of multiple volatile and mobile ionic species, and the possible role of environmentally induced reactions at surfaces and triple-phase junctions. Here, in situ studies of the electrochemistry of methylammonium lead bromide perovskite with the Au electrode interface are reported via light- and voltage-dependent time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging of lateral perovskite heterostructures. While ToF-SIMS allows for the visualization of the chemical composition along the surface and its evolution with light and electrical bias, the interpretation of the multidimensional data obtained is often limited due to strong correlations between chemical signatures and the need to track multiple peaks at once. Here, a machine learning workflow combining the Hough transform and non-negative matrix factorization and no-negative tensor decomposition is developed to avoid this limitation and extract salient features of associated chemical changes and to separate the light- and voltage-dependent dynamics. Finally, combining these in situ characterizations and the machine learning workflow provides comprehensive information on the chemical nature of moving species, ion accumulation, and interfacial electrochemical reactions in HOIP devices.

36 MATERIALS SCIENCE↗

Review: Recent advances of ToF-SIMS for environmental analysis and imaging

Background: Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis technique, initially developed and applied in inorganic materials and semiconductors. In past decades, ToF-SIMS has attracted more attention in its analysis capabilities of organic materials, with increased applications in biology, medical, and health development. It has also become a versatile and effective tool in environmental analysis due to its high mass resolution, mass accuracy, and depth profiling. Results: In this review, we first give an overview of the principle of ToF-SIMS and follow with recent ToF-SIMS applications in exemplary environmental study cases, including atmospheric aerosol, soil, water, plant, and organic solvent analysis. Moreover, sample preparation techniques are summarized in relation to corresponding environmental applications. Specifically, we call attention to ToF-SIMS investigations showcasing studies in surface chemical compositions, images, and depth profile analysis. These findings emphasize the important role of interfacial chemistry in environmental processes and provide valuable insights into dynamic processes, such as chemical transformation, particle formation, plant biology, and microbial inspired biotechnology development. The mass spectral imaging results acquired by ToF-SIMS offer a deeper understanding of intermediate stages and transient phases for environmental specimens. Significance: In situ and operando imaging offer new possibilities in studying phenomena in real time with high spatial resolution. Furthermore, it is anticipated that more research groups will use ToF-SIMS in environmental research given recent advances in measurement capabilities and surging needs in chemical mapping of complex analytes and systems.

Aerosol↗

Synthesis of a Hybrid Nanostructure of ZnO-Decorated MoS 2 by Atomic Layer Deposition

We introduce here the synthesis of hybrid nanostructures comprised of ZnO nanocrystals (NCs) decorating nanosheets and nanowires (NWs) of MoS 2 prepared by atomic layer deposition (ALD). The concentration, size, and surface-to-volume ratio of the ZnO NCs can be systematically engineered by controlling both the number of ZnO ALD cycles and the properties of the MoS 2 substrates, which are prepared by sulfurizing ALD MoO 3 . Analysis of the chemical composition combined with electron microscopy and synchrotron X-ray techniques as a function of the number of ZnO ALD cycles, together with the results of quantum chemical calculations, help elucidate the ZnO growth mechanism and its dependence on the properties of the MoS 2 substrate. The defect density and grain size of MoS 2 nanosheets are controlled by the sulfurization temperature of ALD MoO 3 , and the ZnO NCs in turn nucleate selectively at defect sites on MoS 2 surface and enlarge with increasing ALD cycle numbers. At higher ALD cycle numbers, the coalescence of ZnO NCs contributes to an increase in areal coverage and NC size. Furthermore, the geometry of the hybrid structures can be tuned by changing the dimensionality of the MoS 2 , by employing vertical NWs of MoS 2 as the substrate for ALD ZnO NCs, which in turn leads to improvement of the relevant surface-to-volume ratio. Such materials are expected to find use in newly expanded applications, especially those such as sensors or photo-devices based on a p-n heterojunction which relies on coupling transition metal dichalcogenides (TMDCs) with NCs.

36 MATERIALS SCIENCE↗

Extrusion‐Spheronization of Energetic Materials

The prevailing method to produce plastic‐bonded explosive (PBX) molding powder, or “prills”, is a complex, multiphase, and bespoke process that was developed by the high explosives (HEs) manufacturing industry several decades ago. This work demonstrates the utility of a simpler, widely‐used mechanical process—extrusion‐spheronization—to produce PBX prills. We begin by detailing precautions taken to enable safe remote operation of extrusion‐spheronization equipment with HE. We then perform a study investigating the effect of lacquer solvent composition on the particle packing, pressed density, and compressive strength properties of a 95 wt.% TATB/5 wt.% polymer binder formulation akin to PBX 9502. It was found that increased composition of low vapor pressure solvents caused prolonged retention of the solvent, resulting in tackier materials that would agglomerate and form larger prills. The larger prills also led to lower poured density and tapped density of HE prills and compressive strength of pressed PBX articles. The samples prepared with a 75% propyl acetate/25% butyl acetate lacquer solvent composition exhibited the highest compressive strength. However, it is believed that the prill packing and compressive strength properties are primarily driven by the prill size rather than the chemical composition of the lacquer itself. Extrusion‐spheronization remains a promising method to reliably and repeatably produce HE prills that is less sensitive to feedstock or process variation than traditional methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monolayer Films of Binary Metal Oxide Nanoparticles for Carbon Nanotube Synthesis

Binary metal oxide nanoparticles (biMO-NPs) combining transition and main-group metals with well-organized atomic architectures have unique potential as robust and economical heterogeneous catalysts. Herein, metal oxide nanoparticles (CoAlxOy) using cobalt and aluminum were synthesized, and their structure, morphology, and chemical composition were investigated using various characterization techniques. The biMO-NPs, which had a Gaussian-type size distribution (∼6 nm), were assembled on plain silicon substrates modified chemically with linker molecules bearing suitable end groups. Surface analysis revealed an ordered, uniform, close-packed arrangement of biMO-NPs forming a monolayer architecture with nanoscale thickness (∼12 nm), high surface uniformity, and negligible defects. The nanoparticle monolayer film (NP-MF) was employed as a catalyst to grow carbon nanotube (CNT) forests via the thermal chemical vapor deposition (CVD) method, similar to those grown from catalyst thin films deposited by physical vapor deposition. Structural characterization confirmed the growth of a dense, uniform, high-quality vertically aligned carbon nanotube (VA-CNT) forest with a length of ∼125 µm, which is comparable to the VA-CNTs grown from expensive thin films. Thus, CNT growth was successfully catalyzed by the biMO-NPs, highlighting a simple and inexpensive alternative for catalyst deposition. In this innovative wet-chemistry approach, the catalyst and catalyst support are combined within a single nanoparticle before NP-MF assembly. Interestingly, this approach provides a scalable and cost-effective pathway for CNT growth, eliminating the need for expensive thin deposition techniques.

Regmi, Bishow [University of Cincinnati]↗

Manuscript Workflows from and Processed Organic Matter Composition of Experimentally Burned Open Air and Muffle Furnace Vegetation Chars across Differing Burn Severity and Feedstock Types from Pacific Northwest, USA (v3)

This dataset includes processed organic matter chemistry data from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and vegetation materials representative of major land cover types of the Pacific Northwest, USA. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. Source data and associated metadata (including methods and geospatial information) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1894135 (Grieger et al. 2022). This dataset provides processing scripts and processed data for both solid and dissolved phase organic matter characterization data from experimentally generated chars. These processed data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. The processed data were subsequently analyzed; and the results and ecological implications of the findings were published in peer-reviewed manuscripts. The scripts and workflows used to develop the manuscripts are also included in this data package.This data package was originally published June 2024. It was updated September 2024 (new and modified files) and in January 2025 (modified files). See the change history section in the readme for more details.This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), and folders containing (A) processed data; (B) general processing scripts; and (C) additional folders with specific manuscript analysis scripts and processed data. Step-by-step instructions to assist the user in recreating the workflow used to generate the results in the manuscripts is also provided. The processed data folder includes (1) a folder of processed Parallel Factor Analysis (PARAFAC) and spectra indices outputs from excitation emissions matrix (EEM) fluorescence and absorbance data; (2) a folder of processed solid state carbon-13 (13-C NMR) integrals; (3) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) processed data outputs from Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude), blank corrections and data aggregation, and calculated molecular indices. All files are .pdf, .csv, .html, .Rmd, .R, or .RData.

54 ENVIRONMENTAL SCIENCES↗

Solvent Hold Tank Sample Results for MCU-19-557- 558-559 (July 2019), MCU-19-560-561-562 (August 2019), MCU-19-566-567-568 (September 2019) (Quarterly Report)

In late FY13, MCU implemented the Next Generation Solvent (NGS) flow sheet. Facility personnel added a non-radioactive, NGS “cocktail” containing the new Extractant (MaxCalix) and a new Suppressor (TiDG) to the SHT heel to implement the NGS flow sheet. The resulting “blend” solvent (“NGS blend solvent”) is essentially NGS with residual amounts of calix[4]arene-bis(tert-octylbenzo-crown-6) (BOBCalixC6) and trioctylamine (TOA). For process monitoring, SHT samples are sent to Savannah River National Laboratory (SRNL) to examine solvent composition changes over time. With the exception of Isopar™ L which is regularly added to the SHT due to its high vapor pressure, this report shows the cumulative chemical composition data, including impurities like mercury, of three SHT samples: MCU-19-557-558-559, MCU- 19-560-561-562, and MCU-19-566-567-568. A summary report for each of the SHT monthly samples was issued previously. This report examines the cumulative results from these and several past monthly reports.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Solvent Hold Tank Sample Results for MCU-20-32-33-34 (Quarterly Report, September 2020)

In late FY13, MCU implemented the Next Generation Solvent (NGS) flow sheet. Facility personnel added a non-radioactive, NGS “cocktail” containing the new Extractant (MaxCalix) and a new Suppressor (TiDG) to the SHT heel to implement the NGS flow sheet. The resulting “blend” solvent (“NGS blend solvent”) is essentially NGS with residual amounts of calix[4]arene-bis(tert-octylbenzo-crown-6) (BOBCalixC6) and trioctylamine (TOA). For process monitoring, SHT samples are sent to Savannah River National Laboratory (SRNL) to examine solvent composition changes over time. With the exception of Isopar™ L which is regularly added to the SHT due to its high vapor pressure, this report shows the cumulative chemical composition data, including impurities like mercury, of the September 2020 (MCU-20-32-33-34) solvent SHT sample. A summary report of the September SHT solvent sample was issued earlier. This report examines the cumulative results from these and several past monthly reports. These samples are intended to verify that the solvent is within the specified composition range. A baseline “scratch” solvent - a scratch solvent is a preparation of all 6 solvent components (this includes the old extractant BoBCalix and the old suppressor TrioctylAmine that remained when solvent was converted to Next Generation Solvent [NGS]) of the composition that approximates the blend of cocktail and heel solvent - was prepared in the lab (September 2018) and used for comparison and evaluation. The results from the analyses are presented in this document. This report is the last characterization analysis of the SHT solvent. MCU entered a lay-up state and about 128 gallons of the SHT solvent were pumped into 55 gallons drums for future disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multidimensional Diagnostics of the Interface Evolutions in Solid-State Lithium Batteries

All-solid-state lithium metal batteries hold tremendous potential as next-generation energy storage solutions. However, their performance is hindered by complex chemo-mechanical instabilities at the interface, which encompass electrolyte decomposition, loss of contact due to volume changes, and the growth of lithium filaments. Given the complexity of these failure mechanisms, it is imperative to employ multidimensional diagnostics that leverage a combination of tools capable of quantifying formed voids and filaments, identifying the chemical and mechanical properties of lithium dendrites and electrolyte decomposition products, as well as monitoring the evolution of these processes in situ. The primary objective of this project is to develop a comprehensive characterization platform for solid-state battery interfaces, integrating FIB-SEM tomography, ToF-SIMS, in-SEM nanoindentation, and in-SIMS AFM-based stiffness mapping to enable structural, chemical, and mechanical analyses. The project team has accomplished significant milestones, including: 1) The successful development of a characterization platform that combines FIB-SEM, ToF-SIMS, nanoindentation, and AFM. 2) The creation of solid-state cells at various scales. 3) Real-time visualization of the plating and stripping of lithium. 4) Operando analysis of the chemical composition and evolution of electrolyte decomposition products, encompassing intermediate and metastable species, at both the cathode and anode interfaces. 5) In situ analysis of mechanical properties coupled with chemical mapping. 6) The implementation of the multiscale characterization technique has yielded valuable insights into cell failure mechanisms and has led to the development of a solid-state lithium cell that exhibits exceptional durability, surpassing 2500 cycles. This project has resulted in 10 publications, 1 invention disclosure, 8 manuscripts under review or in preparation.

25 ENERGY STORAGE↗

Machine-learning based approach to examine ecological processes influencing the diversity of riverine dissolved organic matter composition

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes ( 2 H and 18 O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

54 ENVIRONMENTAL SCIENCES↗