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At least 307 records · Page 17

Sustainable Synthesis of NiMo Alloy Nanoparticles for Hydrogen Evolution Catalysis Using a Recyclable Ionic Liquid Solvent

Advancing the sustainability of nanoparticle electrocatalyst synthesis requires reducing solvent waste without compromising catalytic performance. Here, we report a rapid, microwave‐assisted colloidal synthesis of NiMo alloy nanoparticles in the ionic liquid 1‐butyl‐3‐methylimidazolium bis(trifluoromethylsulfonyl)imide (BMIM‐NTf 2 ), which serves as both reaction medium and recyclable solvent. NiMo nanoparticles with tunable compositions were obtained within 1 min at 230 °C, with Ni 0.86 Mo 0.14 giving the highest activity toward the hydrogen evolution reaction (HER), achieving an onset potential of −129 mV, an overpotential at 10 mA cm −2 of −290 mV versus RHE in acidic electrolyte, and >99% Faradaic efficiency. The ionic liquid was recovered and purified via aqueous NH 4 OH extraction, removing over 99% of residual Mo species, and reused for up to five successive syntheses. Nanoparticles prepared in recycled BMIM‐NTf 2 retained comparable crystallinity, morphology, and catalytic activity, with stable HER performance over 45 h of electrolysis. These results demonstrate that ionic liquid recycling can improve the sustainability of the preparation of NiMo nanoparticle electrocatalysts while preserving performance and material integrity.

bimetallic alloy↗

Templated native silk smectic gels

One aspect of the present invention relates to a method of preparing a fibrous protein smectic hydrogel by way of a solvent templating process, comprising the steps of pouring an aqueous fibrous protein solution into a container comprising a solvent that is not miscible with water; sealing the container and allowing it to age at about room temperature; and collecting the resulting fibrous protein smectic hydrogel and allowing it to dry. Another aspect of the present invention relates to a method of obtaining predominantly one enantiomer from a racemic mixture, comprising the steps of pouring an aqueous fibrous protein solution into a container comprising a solvent that is not miscible with water; sealing the container and allowing it to age at about room temperature; allowing the enantiomers of racemic mixture to diffuse selectively into the smectic hydrogel in solution; removing the smectic hydrogel from the solution; rinsing predominantly one enantiomer from the surface of the smectic hydrogel; and extracting predominantly one enantiomer from the interior of the smectic hydrogel. The present invention also relates to a smectic hydrogel prepared according to an aforementioned method.

Jin, Hyoung-Joon↗

Templated Native Silk Smectic Gels

One aspect of the present invention relates to a method of preparing a fibrous protein smectic hydrogel by way of a solvent templating process, comprising the steps of pouring an aqueous fibrous protein solution into a container comprising a solvent that is not miscible with water; sealing the container and allowing it to age at about room temperature; and collecting the resulting fibrous protein smectic hydrogel and allowing it to dry. Another aspect of the present invention relates to a method of obtaining predominantly one enantiomer from a racemic mixture, comprising the steps of pouring an aqueous fibrous protein solution into a container comprising a solvent that is not miscible with water; sealing the container and allowing it to age at about room temperature; allowing the enantiomers of racemic mixture to diffuse selectively into the smectic hydrogel in solution; removing the smectic hydrogel from the solution; rinsing predominantly one enantiomer from the surface of the smectic hydrogel; and extracting predominantly one enantiomer from the interior of the smectic hydrogel. The present invention also relates to a smectic hydrogel prepared according to an aforementioned method.

Jin, Hyoung-Joon↗

Templated Native Silk Smectic Gels

One aspect of the present invention relates to a method of preparing a fibrous protein smectic hydrogel by way of a solvent templating process, comprising the steps of pouring an aqueous fibrous protein solution into a container comprising a solvent that is not miscible with water; sealing the container and allowing it to age at about room temperature; and collecting the resulting fibrous protein smectic hydrogel and allowing it to dry. Another aspect of the present invention relates to a method of obtaining predominantly one enantiomer from a racemic mixture, comprising the steps of pouring an aqueous fibrous protein solution into a container comprising a solvent that is not miscible with water; sealing the container and allowing it to age at about room temperature; allowing the enantiomers of racemic mixture to diffuse selectively into the smectic hydrogel in solution; removing the smectic hydrogel from the solution; rinsing predominantly one enantiomer from the surface of the smectic hydrogel; and extracting predominantly one enantiomer from the interior of the smectic hydrogel. The present invention also relates to a smectic hydrogel prepared according to an aforementioned method.

Jin, Hyoung-Joon↗

Phase-Selective Fractionation of Lignocellulosic Biomass Using a Lignin-Based Hydrophobic Deep Eutectic Solvent Biphasic System

Lignocellulose fractionation is a critical step in biomass valorization. Herein, we report a hydrophobic deep eutectic solvent (HDES)-mediated biphasic fractionation strategy that enables the simultaneous and selective separation of cellulose, hemicellulose, and lignin in a single process. Lignin-derived HDESs composed of thymol and 2,6-dimethoxyphenol (syringol) were combined with an acidic aqueous phase to create a water-HDES biphasic system, in which lignin was preferentially extracted into the HDES phase, hemicellulose-derived sugars were selectively solubilized in the aqueous phase, and cellulose was retained in the solid residue. Using wheat straw and poplar wood as representative herbaceous and woody biomass feedstocks, the HDES-acid system exhibited strong synergistic effects, achieving delignification up to 69.8% and xylan removal up to 93.6%. Structural characterization confirmed effective disruption of the lignocellulosic matrix and increased cellulose accessibility, resulting in markedly enhanced enzymatic saccharification, with glucose yields up to 96.2% for wheat straw. This work demonstrates a sustainable and efficient HDES-based biphasic fractionation platform that enables phase-selective separation of major lignocellulosic components and provides a foundation for further development of closed-loop biorefinery processes.

09 BIOMASS FUELS↗

QM Investigation of Rare Earth Ion Interactions with First Hydration Shell Waters and Protein-Based Coordination Models

Here, conventional methods for extracting rare earth metals (REMs) from mined mineral ores are inefficient, expensive, and environmentally damaging. Recent discovery of lanmodulin (LanM), a protein that coordinates REMs with high-affinity and selectivity over competing ions, provides inspiration for new REM refinement methods. Here, we used quantum mechanical (QM) methods to investigate trivalent lanthanide cation (Ln 3+ ) interactions with coordination systems representing bulk solvent water and protein binding sites. Energy decomposition analysis (EDA) showed differences in the energetic components of Ln 3+ interaction with representatives of solvent (water, H 2 O) and protein binding sites (acetate, CH 3 COO – ), highlighting the importance of accurate description of electrostatics and polarization in computational modeling of REM interactions with biological and bioinspired molecules. Relative binding free energies were obtained for Ln 3+ with coordination complexes originating from binding sites in PDB structures of a lanthanum binding peptide (PDB entry 7CCO) and LanM, with explicit consideration of the first hydration shell waters, according to quasi-chemical theory (QCT). Beyond the first shell, the bulk solvent environment was represented with an implicit continuum model. Ln 3+ interactions with (H 2 O) 9 and both binding site models became more favorable, moving down the periodic series. This trend was more pronounced with the protein binding site models than with water, resulting in affinity increasing with periodic number, except for the last REM, Lu 3+ , which bound less favorably than the preceding element, Yb 3+ . Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. Conversely, the previously reported experimental data for LanM show a preference for the earlier lanthanides; this is likely due to longer-range interactions and cooperative effects, which are not represented by the reduced models. Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. In contrast to the previously reported experimental data for LanM, the peptide preferentially binds the earlier lanthanides. This difference likely arises due to longer-range interactions and cooperative effects not represented by the peptide. Further investigation of Ln 3+ interactions with whole proteins using polarizable molecular mechanics models with explicit solvent is warranted to understand the influence of longer-ranged interactions, cooperativity, and bulk solvent. Nevertheless, the present work provides new insights into Ln 3+ interactions with biomolecules and presents an effective computational platform for designing specific single-site REM binding peptides more efficiently.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lignin molecular weights of Populus trichocarpa residues after CELF pretreatment

Here we present a dataset of molecular weights of lignin from a woody energy crop (Populus trichocarpa) residues after a series of co-solvent enhanced lignocellulosic fractionation (CELF) pretreatment. The natural poplar variant GW-9947 from the Center for Bioenergy Innovation (CBI) was used. The poplar was knife milled and passed through a 1 mm sieve and CELF pretreatment was performed in a Parr autoclave reactor with 7.5 wt % solids loading, 0.5 wt% H2SO4 as catalyst at 150°C with various time. Tetrahydrofuran was added in a 1:1 mass ratio with water as the pretreatment solvent. Lignin was isolated from the pretreated samples after ball-milling in a porcelain jar with ceramic balls via Retsch PM 200 at 580 rpm for 2.5 h followed by enzymatic hydrolysis in acetate buffer (pH 4.8, 50 °C) for 48 h. The solid residue was isolated by centrifugation and hydrolyzed again with freshly added buffer and enzymes for another 48 h. After filtration, the solid residue was extracted twice with 96% (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover lignin. The lignin samples were then derivatized in an acetic anhydride/pyridine (1:1, v/v) mixture and stirred at room temperature for 24 h. Ethanol was added to the reaction mixture, left for 30 min and then removed with a rotary evaporator. The addition and removal of ethanol was repeated at least 3 times until all traces of acetic acid were removed. Acetylated lignin samples were then dissolved in tetrahydrofuran (THF) at a concentration of 1.0 mg/mL. The molecular weight of acetylated lignin was measured by a gel permeation chromatography (GPC) on a PSS-Polymer Standards Service (Warwick, RI, USA) GPC SECurity 1200 system featuring Agilent HPLC 1200 components equipped with four Waters Styragel columns (HR1, HR2, HR4 and HR6) and an UV detector (270 nm). Tetrahydrofuran was used as the mobile phase and flow rate was 0.3 mL/min. The Polymer Standards Service WinGPC Unity software (Build 6807) was used for data processing for all the samples. The data provides information about the effects of CELF pretreatment time at 150 ºC on lignin molecular weights.

09 BIOMASS FUELS↗

Improving the reliability of machine learned potentials for modeling inhomogeneous liquids

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids—including the density response, surface tension and size-dependent cavitation free energies—for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biotechnological solutions for critical mineral recovery from unconventional feedstocks

Secure and sustainable metal recovery from unconventional feedstocks is needed to meet the mineral demands of energy, defense, and electronic technologies. Here, we highlight the potential to leverage nature’s ability to extract and differentiate metal ions in biotechnologies that could become the next generation of mining and refining. We describe bulk and trace processes and then discuss the advances and opportunities of two key bioprocesses: microbially mediated solubilization of metal ions from solid matrices (termed ‘bioleaching’) and bio-based separation of solubilized ions via selective adsorption to proteins. Both biotechnologies have advantages such as reduced energy input for leaching low-grade feedstocks and reduced organic solvent demand for separating ions with similar physiochemical properties but require more development for industrial scale recovery from unconventional feedstocks. Innovation in biological science and engineering may bring timely solutions to key challenges toward recovering critical minerals from unconventional feedstocks.

organic↗

Theory of hydrophobicity: transient cavities in molecular liquids

Observation of the size distribution of transient cavities in computer simulations of water, n-hexane, and n-dodecane under benchtop conditions shows that the sizes of cavities are more sharply defined in liquid water but the most-probable-size cavities are about the same size in each of these liquids. The calculated solvent atomic density in contact with these cavities shows that water applies more force per unit area of cavity surface than do the hydrocarbon liquids. This contact density, or "squeezing" force, reaches a maximum near cavity diameters of 2.4 angstroms. The results for liquid water are compared to the predictions of simple theories and, in addition, to results for a reference simple liquid. The numerical data for water at a range of temperatures are analyzed to extract a surface free energy contribution to the work of formation of atomic-size cavities. Comparison with the liquid-vapor interfacial tensions of the model liquids studied here indicates that the surface free energies extracted for atomic-size cavities cannot be accurately identified with the macroscopic surface tensions of the systems.

NASA Center ARC↗

Emergence of deep eutectic solvents (DES): chemistry, preparation, properties, and applications in biorefineries and critical materials

The emergence of renewable deep eutectic solvents (DES) as clean and efficient catalysts and solvents has created new opportunities for lignocellulosic biorefineries and critical material sectors, including chemical, energy, pharmaceutical, textile, and hydrometallurgical industries. This review provides an in-depth overview of DES, covering their chemistry, classifications, preparation methods, processing characteristics, and recyclability, while highlighting their unique attributes and industry relevant applications. Emphasis is placed on the integration of DES into advanced biorefinery systems, focusing on their tunable physicochemical and thermodynamic properties for biomass pretreatment and the production of value-added products. The review explores how DES can be tuned for selective dissolution of biomass components and evaluates production and valorization of DES-derived biochemicals, with attention to lignin extraction mechanisms and conversion of biomass into bioproducts and biofuels. Beyond biorefineries, the scope extends to DES applications in electrochemical energy devices, where they serve as electrolytes, synthesis media for electrode materials, and leaching agents in battery recycling. The multifunctional roles of DES in pharmaceutical, hydrometallurgical, and textile sectors are also explored for contributions to sustainable processing. Finally, the review identifies future research directions, outlining benefits, challenges, and knowledge gaps, for continued industrial development.

09 BIOMASS FUELS↗

Whole metagenome sequencing and 16S rRNA gene amplicon analyses reveal the complex microbiome responsible for the success of enhanced in-situ reductive dechlorination (ERD) of a tetrachloroethene-contaminated Superfund site

The North Railroad Avenue Plume (NRAP) Superfund site in New Mexico, USA exemplifies successful chlorinated solvent bioremediation. NRAP was the result of leakage from a dry-cleaning that operated for 37 years. The presence of tetrachloroethene biodegradation byproducts, organohalide respiring genera (OHRG), and reductive dehalogenase (rdh) genes detected in groundwater samples indicated that enhanced reductive dechlorination (ERD) was the remedy of choice. This was achieved through biostimulation by mixing emulsified vegetable oil into the contaminated aquifer. This report combines metagenomic techniques with site monitoring metadata to reveal new details of ERD. DNA extracts from groundwater samples collected prior to and at four, 23 and 39 months after remedy implementation were subjected to whole metagenome sequencing (WMS) and 16S rRNA gene amplicon (16S) analyses. The response of the indigenous NRAP microbiome to ERD protocols is consistent with results obtained from microcosms, dechlorinating consortia, and observations at other contaminated sites. WMS detects three times as many phyla and six times as many genera as 16S. Both techniques reveal abundance changes in Dehalococcoides and Dehalobacter that reflect organohalide form and availability. Methane was not detected before biostimulation but appeared afterwards, corresponding to an increase in methanogenic Archaea. Assembly of WMS reads produced scaffolds containing rdh genes from Dehalococcoides, Dehalobacter, Dehalogenimonas, Desulfocarbo, and Desulfobacula. Anaerobic and aerobic cometabolic organohalide degrading microbes that increase in abundance include methanogenic Archaea, methanotrophs, Dechloromonas, and Xanthobacter, some of which contain hydrolytic dehalogenase genes. Aerobic cometabolism may be supported by oxygen gradients existing in aquifer microenvironments or by microbes that produce O 2 via microbial dismutation. The NRAP model for successful ERD is consistent with the established pathway and identifies new taxa and processes that support this syntrophic process. This project explores the potential of metagenomic tools (MGT) as the next advancement in bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solution-processed tungsten diselenide as an inorganic hole transport material for moisture-stable perovskite solar cells in the n-i-p architecture

Some of the obstacles to the commercialization of perovskite solar cells (PSCs) are their long-term moisture stability and material cost of the constituent layers, such as the commonly used spiro-OMeTAD hole transport layer (HTL). Replacing the spiro-OMeTAD with low-cost inorganic hole transport materials (HTMs) are important to further elevate the attractiveness of PSCs for commercialization. Perovskite-compatible, solution-exfoliated two-dimensional (2D) transition metal dichalcogenides (TMDCs) are being considered as viable candidates for inorganic HTMs. We consider one such TMDC, WSe 2 which was chemically exfoliated using dichlorobenzene (DCB), a perovskite-compatible solvent, as it was integrated with triple cation perovskite absorbers within the solar cell stack. Here, the WSe 2 HTL required heat treatment processes to be maintained below 100°C in order to preserve the integrity of the underlying perovskite; despite this lower temperature post treatment process, the structural morphology of the film revealed its dense and pinhole-free nature. Temperature-dependent transport studies conducted on the WSe 2 film provided evidence of its semiconducting character and its ability to extract holes well from the underlying triple-cation Cs 0.05 FA 0.79 MA 0.16 PbI 2.45 Br 0.55 absorber. The inorganic HTL offered better environmental stability in moisture-rich environments of up to 60% relative humidity, in comparison to spiro-OMeTAD HTL-based devices which degraded faster as a result of pinholes

14 SOLAR ENERGY↗

Release of volatile mercury from vascular plants

Volatile, organic solvent soluble mercury has been found in leaves and seeds of several angiosperms. Leaves of garlic vine, avocado, and haole-koa release mercury in volatile form rapidly at room temperature. In garlic vine, the most active release is temperature dependent, but does not parallel the vapor-pressure temperature relationship for mercury. Mercury can be trapped in nitric-perchloric acid digestion fluid, or n-hexane, but is lost from the hexane unless the acid mixture is present. Seeds of haole-koa also contain extractable mercury but volatility declines in the series n-hexane (90%), methanol (50%), water (10%). This suggests that reduced volatility may accompany solvolysis in the more polar media.

Siegel, S. M.↗

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗

Isothermal separation processes

The isothermal processes of membrane separation, supercritical extraction and chromatography were examined using availability analysis. The general approach was to derive equations that identified where energy is consumed in these processes and how they compare with conventional separation methods. These separation methods are characterized by pure work inputs, chiefly in the form of a pressure drop which supplies the required energy. Equations were derived for the energy requirement in terms of regular solution theory. This approach is believed to accurately predict the work of separation in terms of the heat of solution and the entropy of mixing. It can form the basis of a convenient calculation method for optimizing membrane and solvent properties for particular applications. Calculations were made on the energy requirements for a membrane process separating air into its components.

England, C.↗

Components Refurbishment and Chemical Analysis Facility, Hot Spot 1 SWMU #041 Year 3 Annual Performance Monitoring Report Kennedy Space Center, Florida

This Year 3 Annual Performance Monitoring Report (PMR) presents the operations, maintenance, and monitoring activities for the Hydraulic Containment System (HCS) Interim Measure (IM) at the Components Refurbishment and Chemical Analysis (CRCA) facility located at John F. Kennedy Space Center (KSC), Florida. The primary objective of the HCS is to attain hydraulic control of the dissolved-phase chlorinated volatile organic compound (CVOC) plume, with the secondary objective to reduce concentrations of CVOCs in the high-concentration plume to support transition to monitored natural attenuation (MNA). CRCA has been designated Solid Waste Management Unit 041 under the KSC Resource Conservation and Recovery Act Corrective Action Program. The timeframe for activities documented in this Year 3 PMR extends from September 2021 through October 2022. Baseline sampling activities were completed in June 2019, and full-scale startup of the HCS IM was completed in July-August 2019. The operational runtime of the HCS for the Year 3 reporting period was approximately 91%, with the majority of downtime attributed to system maintenance and repair. This is generally consistent with Year 1 and Year 2 runtimes of 85% and 92%, respectively. To help reduce downtime, an anti-scaling amendment, Redux 390, has been used to reduce scaling and help maintain system design parameters. Over nine million gallons of groundwater were treated during Year 3 of HCS operations, and concentrations of the site’s contaminants of concern (trans-1,2-dichloroethene and vinyl chloride) have been reduced by over 97%. This PMR describes the activities that were performed during Year 3 to operate and monitor the HCS IM, which includes three extraction wells, seven injection wells, and conveyance piping to a modular structure containing the control panel and an air stripper. Influent and effluent sampling results from the air stripper show that the system is operating as designed and is reducing concentrations of contaminants of concern to below detection limits. In addition to HCS operation, this PMR also discusses performance monitoring that has been implemented to assess progress of the HCS IM and overall plume conditions through scheduled groundwater (quarterly and semi-annual) and sub-slab soil gas (quarterly) sampling and analysis. Two ambient air samples were also collected on a quarterly basis in the vicinity of the modular structure and the paved driveway east of the Solvent Reclamation Area during routine operation and maintenance (O&M) activities to ensure safe breathing zone air quality for on-site personnel. All sub-slab soil gas and ambient air sampling conducted during the Year 3 operational period showed results below applicable regulatory air screening limits. Predictions made during the Year 2 groundwater model updates were in close correlation to post Year 3 plume conditions. Therefore, it can be assumed that the projected path remains valid for transition to MNA in one to two years of continuous HCS operation. The contents of this Year 3 PMR were presented during the February 2023 KSC Remediation Team meeting, where Team consensus was reached on several items including continued O&M of the HCS, and continued monitoring of groundwater, ambient air, and sub-slab soil gas. Replacement of MW0019 and VMP04 was also recommended, as well as additional direct-push technology sampling to further delineate the downgradient plume and confirm overall site-wide low-concentration plume boundaries. Sampling for per- and polyfluoroalkyl substances at CRCA is ongoing and will be submitted under separate cover.

K. Alex Murphy↗