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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Mechanistic mass transfer in hollow fiber membrane solvent extraction for bio-based isobutanol

Membrane solvent extraction (MSE) has emerged as a promising method for selectively recovering bioproducts from complex aqueous streams. Bio-isobutanol, a next-generation feedstock for biofuel, remains challenging to recover because of its low concentration and the presence of inhibitory substances. This study explores the potential of hollow fiber (HF) MSE for bio-isobutanol recovery and systematically examines the coupled effects of fiber packing, shell-side flow dynamics, and aqueous chemistry on performance. A resistance-in-series model is applied to understand mass transfer in the HF MSE modules, quantify local resistances, and validate overall performance. The results show that increasing the fiber packing provides a larger interfacial area but induces poor flow distribution and channeling, hindering effective isobutanol transport. Meanwhile, increasing the shell-side velocity improves isobutanol recovery due to reductions in the boundary layer thickness. The presence of salts, added to mimic fermentation broth, increases the partition coefficient through salting-out effects, further improving isobutanol flux. A modified correlation for the shell-side mass transfer coefficient (k s,ϕ+v ), integrating geometric and hydrodynamic effects, was developed and validated. The proposed model achieves highly predictive accuracy (r 2 = 0.9808) across a wide range of conditions, outperforming previous models. The findings provide mechanistic insight into the interaction of geometric packing, hydrodynamics, and chemistry in governing mass transfer in HF MSE. Overall, this work demonstrates the potential of HF MSE for efficient bio-isobutanol recovery and also provides practical guidelines on critical factors (packing fraction, partition coefficient, and shell-side velocity), aiding in the design and scaling of MSE systems for resource recovery.

Aqueous chemistry↗
DOE OSTI2025

Quantum chemically calculated Abraham parameters for quantifying and predicting polymer hydrophobicity

The leakage and accumulation of plastic in the environment is a significant and growing problem with numerous detrimental impacts and has led to a push toward the design and development of more environmentally benign materials. To this end, we have developed a quantum chemistry-based model for predicting the mobility of polymer materials from molecular structure. Hydrophobicity is used as a surrogate for mobility given that hydrophobic interactions drive much of the partitioning of contaminants in and out of various environmentally relevant compartments. To model polymer hydrophobicity, we adjusted a previously developed Quantum Chemically Calculated Abraham Parameter model to calculate Abraham parameters of small molecules from molecular structure information. The resulting model predicted the octanol-water partition coefficient (K OW ) of polymer repeating units with a root mean square error (RMSE) of 0.48 (log scale). Additionally, the hydrophobicity of high molecular weight polymer materials was captured through solubility parameters and Nile red staining experiments from the literature and predicted with RMSEs of 1.21 (J/cc) 0.5 and 3.42 nm, respectively. Finally, to test the environmental applicability of the model, the relative adsorption capacity of three polymers was predicted and used to unify sorption isotherms across multiple sorbates and polymer sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Adsorption Studies of Dilute Krypton and Xenon from Nitrogen on SBMOF-1 and Activated Charcoal for Applications in Isotope Harvesting

Adsorptive partitioning of dilute krypton (Kr) and xenon (Xe) onto Stony Brook Metal–Organic Framework (SBMOF-1) and activated charcoal (AC) from carrier nitrogen was experimentally measured at temperatures ranging from 195 to 293 K. For this purpose, a closed-loop system for gas adsorption experiments was developed. From the Kr adsorption measurements, the adsorption equilibrium constant for Kr on SBMOF-1 was calculated, yielding a value for the enthalpy of adsorption of −19 ± 1 kJ·mol –1 . The partition coefficients were utilized to estimate the extraction rates of 76 Kr, 77 Kr, and 122 Xe isotopes during isotope harvesting at the Facility for Rare Isotope Beams (FRIB). We conclude that both materials showed promising results for the extraction of noble gases from FRIB effluents using temperature swing adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Predicting Liquid–Liquid Phase Separation of Submicrometer Proxies for Atmospheric Secondary Aerosol

Liquid–liquid phase separation (LLPS) of atmospheric aerosols can significantly impact climate, air quality, and human health. However, their complex composition, small size, and history-dependent properties result in great uncertainty in the modeling of aerosol phase state and atmospheric processes. Herein, using cryogenic transmission electron microscopy (cryo-TEM), we examined model submicron aerosols composed of organic compounds and ammonium sulfate, and established a parameterization for the separation relative humidity (SRH) that accounts for chemical composition, particle size, and equilibration time. We evaluated different variables that describe chemical composition: O/C ratio, partition coefficient, solubility, molar mass, and polarizability. The O/C ratio fits the SRH of micrometer droplets best, and by using a scaling factor to translate the micrometer SRH parameterization to submicron aerosols, we incorporate the effects of size and equilibration time. The measured scaling factor for the submicron mean SRH (30nm – 1μm, 20 min equilibration times) is 0.80, the factor becomes 1 with equilibration time over 1 hour, and is equal to 0, meaning that SRH is absent, when the aerosol dry diameter is smaller than 30 nm. Furthermore, our parameterization will aid in universal SRH modeling, potentially leading to more accurate predictions of aerosol mass, optical properties, hygroscopicity, and heterogeneous chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine Learning-Driven Solvent Screening for Biobased 2,3-Butanediol Extraction

Biobased 2,3-butanediol (2,3-BDO) is a valuable biomass-derived chemical due to its versatility in being transformed into a wide variety of products. However, the separation and purification of 2,3-BDO from fermentation broth remain a significant challenge owing to its high boiling point and hydrophilic nature. Herein, we developed a machine learning (ML)-based screening workflow that uses molecular calculations as training data and requires only a small number of experimental measurements for validation to identify alternative solvent candidates for the liquid–liquid extraction (LLE) of 2,3-BDO from aqueous solution. In particular, 130 density functional theory (DFT) calculations with the implicit solvation method not only built a correlation between the computational partition coefficient and the experimental distribution coefficient of 2,3-BDO but also parameterized an Extra-Trees ML model to screen the distribution coefficient for a wider range of 6717 organic solvents. The experimental measurements of only 24 solvents were needed to validate the computational results. A list of 50 prioritized solvents was proposed for 2,3-BDO LLE, and seven additional experimental measurements were conducted to further verify our selected solvents. The impact of the extraction temperature and solvent-to-feed ratio was also investigated for selected solvents in experiments. Furthermore, this work suggested alternative solvents for 2,3-BDO LLE and proposed a versatile workflow that requires fewer experiments and can be applied to a broader range of LLE studies.

Extraction↗
DOE OSTI2024

Liquid–Liquid Equilibrium Prediction in Fast Pyrolysis Bio-Oil Systems: A Framework for Incorporating Bio-Oil Complexity

The study of mixtures of bio-oil, water and organic solvents in different proportions can serve as a cost-effective analysis of its content due to the formation of immiscible phases. This manuscript attempts to replicate experimentally determined partition coefficients (K OW ) of relevant species present in fast pyrolysis bio-oil (FPBO). A commercial flowsheeting simulator with surrogate bio-oil model representation is used. Concurrently, pyrolytic lignins in FPBO (‘pyrolignin’) do not have an agreed-upon structural representation, and the literature is ripe with wide variations of said representations. Thus, during the description of FPBO, this pyrolignin fraction was modeled using 20 possible structures (phenolic dimers to tetramers), with the goal of determining the structures for which the experimental data are best described. Two cases were considered: Case 1 normalized the reported experimental mass balance, while Case 2 included the unreported fraction in the mass balance to the total pyroligin. Please, add here a comment on the prediction of the Water oil equilibrium. The best KOW predictions for levoglucosan (LVG) were obtained when the system was modeled with no pyrolignin, presenting an MRE under 10% for both systems WO and BO. Among the possible structures, D2 (dimer), F1 (trimer) and I1, and I3 (tetramers) presented MRE ≤ 13% for both cases.

09 BIOMASS FUELS↗
DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
DOE OSTI2024

Identifying Green Solvent Mixtures for Bioproduct Separation Using Bayesian Experimental Design

Liquid–liquid extraction (LLE) is a widely used technique for the separation and purification of liquid-phase products with applications in various industries, including pharmaceuticals, petrochemicals, and renewable chemistry. A critical step in the design of an LLE process is the selection of appropriate solvents. This study presents a new methodology for identifying solvent mixtures for bioproduct separation using Bayesian experimental design (BED). Motivated by the need for environmentally friendly and effective separation methods, we address the challenge of selecting solvent systems that balance separation efficiency, selectivity, and environmental impact while also tackling the difficulty of separating multiple bioproducts using complex solvent systems. Our approach specifically seeks to predict product partition coefficients (log10 Kp values) as thermodynamic parameters underlying solvent selection. The iterative approach integrates Bayesian optimization with experimental measurements to guide solvent selection and leverages COSMO-RS simulations to enhance high-throughput experimentation. Using the design of solvent systems for the separation of lignin-derived aromatic products via centrifugal partition chromatography (CPC) as a case study, we show that within seven iterations/cycles of the methodology, we can identify new mixtures of green solvents that align with CPC design principles. Furthermore, these results demonstrate the efficacy of the BED framework in optimizing green solvent systems for complex separations, highlighting the potential of this method to advance the field of green chemistry and contribute to the development of sustainable industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Temperature dependence of uranium and thorium partitioning in igneous zircons

Zircon is a key mineral in geochronology because of its chemical and physical durability and tendency to incorporate radioactive trace elements such as U and Th. Quantifying the partitioning of the actinide elements is critical to constrain initial non-secular equilibrium amounts of 230 Th in zircon. An excess or deficit of 206 Pb will be produced from such an initial excess/deficit of 230 Th from the secular equilibrium condition, which influences the calculated 206 Pb/ 238 U age (Schärer, 1984, Mattinson, 1973). However, there is no standard way to calculate Th/U partitioning ratios when applying age corrections to young igneous zircon, making uncertainties hard to estimate. To better understand U and Th partitioning of zircon/melt that is the cornerstone of the secular disequilibrium correction, zircon was synthesized in one-atmosphere experiments using basaltic andesite, andesite, and rhyolite starting materials, doped with Zr, U, and Th. Different experimental temperatures and oxygen fugacity conditions (ΔQFM−4 to ΔQFM+4) were explored to examine their effects on U and Th partitioning. In addition, we specifically quantify the effects of sector zoning, fractional crystallization, and melt composition on U and Th partitioning. By combining experimental and natural zircon data, we find that temperature has the primary control on the partitioning of U and Th in the zircon and calibrate an inverse relationship between these partition coefficients and crystallization temperatures. The calibrated equation can be applied to the 230 Th correction for an improvement in the accuracy of Th-corrected 206 Pb/ 238 U dates when the zircon crystallization temperature is known.

206Pb/238U dating↗
DOE OSTI2025

Screening green solvents for multilayer plastic film recycling processes

Multilayer (ML) plastic films are essential packaging materials that help protect products from diverse external factors; however, only 5% of all ML films are recycled in the United States. Solvent-based technologies are a promising alternative for recycling ML films because they enable recovery of constituent polymer resins. For example, the Solvent Targeted Recovery and Precipitation (STRAPTM) process sequentially dissolves and separates polymer components using a series of targeted solvent washes. A crucial design aspect of this process is the impact of selected solvents on human health and on the environment. Here, this work introduces a computational framework that integrates molecular modeling, process modeling, techno-economic analysis (TEA), and life-cycle analysis (LCA) to quickly screen green solvents for solvent-based ML recycling processes. Initial screening for solvents based on selectivity is performed by estimating temperature-dependent solubilities using molecular-scale models. Subsequent screening uses basic estimates of energy use and octanol-water partition coefficients (logP) as key measures of health, safety, and environmental hazards. Detailed process modeling, TEA, and LCA are used on a reduced set of promising solvents identified in early screening steps to more accurately determine how solvent selection and associated operating conditions impact overall economics and environmental impacts. The framework is used for the identification of green solvents (from a database of 1,000 solvents) that separate an industrial ML film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). Our analysis shows the effectiveness of the framework and reveals fundamental trade-offs between solvent greenness, solubility, and economics. Our work emphasizes the importance of taking a holistic systems view during solvent design and aims to inform the development of new processes for ML film recycling and the identification of new ML films that are easier to recycle.

economics↗
DOE OSTI2024

Sorption kinetics and stability of conventional adsorbents for mercury remediation

In-situ remediation of mercury at numerous contaminated sites worldwide is a challenging and costly endeavor due to the persistency of this contaminant. In this study, we evaluated eight commercially available sorbent media ranging from carbon-, clays- and silica-based materials (PBC– Biochar, eSorb – Sorbster, nsPAC – Powdered Activated Carbon, fsPAC – Powdered Activated Carbon with Mackinawite, F300 – Filtrasorb 300, Si-SH – Silica Thiol, eBind – RemBind, Q-Clay – Organoclay PM-199), for their effectiveness in sorbing mercury (Hg 2+ ) and mercury complexed with dissolved organic matter (Hg-DOM). Under the chosen experimental conditions of this study, results showed that in the absence of DOM, the kinetic rates of Hg 2+ sorption onto the evaluated sorbents were in the order of 0.31 min-1 (Si-SH) to 2.98 min -1 (nsPAC), whereas in the presence of DOM, the rates varied from 0.16 min-1 (F300) to 0.95 min -1 (nsPAC). The measured sorption capacity for Hg 2+ in the absence of DOM varied from 3.02 mg/g (Q-Clay) to 35.15 mg/g (Si-SH), whereas in the presence of DOM, calculated partition coefficient (KD) ranged from 69.7 mL/g (Q-Clay) to 41,510 mL/g (Si-SH). Furthermore, kinetic data suggest liquid film diffusion was the rate-limiting steps governing mercury sorption onto the studied media. Overall, the obtained study parameters (kinetics/isotherm) are particularly important in informing robust engineering designs for deployment of the vast majority of evaluated sorbents. Thus, sorbent-based strategies offer viable solutions for cost-effective cleanup of mercury at industrially contaminated sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Solidification behavior and cracking mechanisms of Ru-containing BCC-B2 superalloys

Many precipitation-strengthened alloys are highly susceptible to cracking during additive manufacturing (AM), which often requires compositional adjustments to mitigate. Recently, it has been demonstrated that refractory BCC alloys can be precipitation strengthened with ordered Ru-containing B2 precipitates to temperatures exceeding 1200 °C. This motivates a study of the potential fabricability of quaternary and quinary refractory BCC-B2 alloys by AM using single track laser experiments. Alloys with greater than 9 at.% Ru exhibit crack formation upon cooling. Solidification cracking was observed in all Zr-containing alloys, which can be mitigated by substituting Hf. Furthermore, this cracking is attributed to the strong partitioning of Zr during solidification, as revealed by characterization of alloy solidus, liquidus, and partition coefficients. Hf 5 Ru 4 -Nb 63 V 28 is identified as a promising BCC-B2 composition with a high B2 solvus (>1300 °C) and solidus (1695 °C) along with a high resistance to cracking.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impact of a Novel Nickel-Based Catalyst and Phenyl-Acrylate-Based Anion-Exchange Membrane in a Direct Urea Fuel Cell

Developing target-specific catalysts and anion-exchange membranes (AEMs) is crucial for direct urea fuel cell (DUFC) performance. To advance the DUFC system, we developed an anode catalyst with a nickel–iron oxyhydroxide/carbon (NiFeOOH/C) nanofibrous structure for the urea oxidation reaction (UOR), where we optimized the Ni/Fe molar ratio as 6:4. The enhanced electrocatalytic activity of the anode (Ni 6 Fe 4 OOH/C) is attributed to the hydroxide group, which responds with urea molecules to enhance the UOR in a pH-neutral system. Here, we employed a recently developed cross-linked phenyl-acrylate-based AEM (PA/M). A DUFC prepared with the anode and PA/M generates a maximum power density of 11.1 mW/cm 2 and 0.92 V open-circuit voltage under 3 M urea as fuel at 25 °C. We further analyzed the applicability of PA/M in a DUFC system by measuring the urea partition coefficients and permeabilities over a range of concentrations.

10 SYNTHETIC FUELS↗
DOE OSTI2025

PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Finding relevant chemicals in the vast (known) chemical space is a major challenge for environmental and exposomics studies leveraging nontarget high resolution mass spectrometry (NT-HRMS) methods. Chemical databases now contain hundreds of millions of chemicals, yet many are not relevant. This article details an extensive collaborative, open science effort to provide a dynamic collection of chemicals for environmental, metabolomics, and exposomics research, along with supporting information about their relevance to assist researchers in the interpretation of candidate hits. The PubChemLite for Exposomics collection is compiled from ten annotation categories within PubChem, enhanced with patent, literature and annotation counts, predicted partition coefficient (logP) values, as well as predicted collision cross section (CCS) values using CCSbase. Monthly versions are archived on Zenodo under a CC-BY license, supporting reproducible research, and a new interface has been developed, including historical trends of patent and literature data, for researchers to browse the collection. This article details how PubChemLite can support researchers in environmental and exposomics studies, describes efforts to increase the availability of experimental CCS values, and explores known limitations and potential for future developments. The data and code behind these efforts are openly available.

PubChem↗
DOE OSTI2025

A mixture parameterized biologically based dosimetry model to predict body burdens of polycyclic aromatic hydrocarbons in developmental zebrafish toxicity assays

Polycyclic aromatic hydrocarbons (PAHs) are a group of environmental toxicants found ubiquitously as complex mixtures in human-impacted environments. Developmental zebrafish exposures have been used widely to study PAH toxicity, but most studies report nominal exposure concentrations. Nominal exposure concentrations can be unreliable dose metrics due to differences in toxicant bioavailability resulting from disparate exposure methodologies and chemical properties. Toxicokinetic modeling can predict toxicant tissue doses to facilitate comparison between exposures of different chemicals, methodologies, and biological models. We parameterize a biologically based dosimetry model for developmental zebrafish toxicity assays for 9 PAHs. The model was optimized with measurements from media, tissue, and plastic plate walls throughout a static developmental exposure to a mixture of 10 PAHs of high abundance within the Portland Harbor Superfund Site. Plate binding, volatilization, zebrafish permeability, and tissue—media partitioning coefficients vary widely between PAHs. Model predictions accounted for 83% and 54% of 48 hpf body burdens within a factor of 2 resulting from exposures to mixtures and individual PAHs, respectively. Accounting for solubility significantly improves model performance. Competition for active sites in metabolizing enzymes may change biotransformation kinetics between individual PAH and mixture exposures. Area under the curve estimations of concentrations in zebrafish resulted in altered hazard rankings from nominal exposure concentrations. Future work will be oriented to generalizing the model to other PAHs. This PAH dosimetry model improves the interpretability of developmental zebrafish toxicity assays by providing time-resolved body burdens from nominal exposure concentrations.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2024

Affinity of LDR Organics to Cementitious Materials: Sorption and Leaching Tests

SRNL is working to identify and test the physiochemical interactions of organic contaminants of potential concern with minerals in grout/cementitious materials. Organic species may interact with cementitious minerals including slag, fly ash, cement, and other components/dopants like carbon in fly ash. The identification of such interactions will support the solidification process design, performance assessments for the chemicals of concern, and a proposed Resource Conservation and Recovery Act (RCRA) treatment variance the technology-based treatment standard specified for the Land Disposal Restriction (LDR) organics associated with Hanford tank waste. In FY24, a list of the 132 reasonably expected to be present LDR organics associated with Hanford tank waste (RPP-RPT-63493, Rev 1a) was screened by functional groups, octanol-water partitioning coefficients, and detection frequency in Hanford tank waste samples. A subset of 10 compounds spanning the identified properties were tested using sorption and leachate tests. These compounds were subject to traditional batch sorption tests and leaching tests on/from Cast Stone cementitious material with and without activated carbon (a potential organic adsorption additive). The tests have been completed and analysis is underway but as yet currently unavailable. The analytical results (and conclusions) will be included in a forthcoming revision to this report as soon as they are available

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Affinity of LDR Organics to Cementitious Materials: Sorption and Leaching Tests

SRNL is working to identify and test the physiochemical interactions of organic contaminants of potential concern with minerals in grout/cementitious materials. Organic species may interact with cementitious minerals including slag, fly ash, cement, and other components/dopants like carbon in fly ash. The identification of such interactions will support the solidification process design, performance assessments for the chemicals of concern, and a proposed Resource Conservation and Recovery Act (RCRA) treatment variance specified for the Land Disposal Restriction (LDR) organics associated with Hanford tank waste. Inably expected to be present LDR organics associated with Hanford tank waste (RPP-RPT-63493, Rev 1a) was screened by functional groups, octanol-water partitioning coefficients, and detection frequency in Hanford tank waste samples. A subset of 10 compounds, spanning the identified properties, were tested using sorption and leachate tests. These compounds were subjected to traditional batch sorption tests and leaching tests on/from Cast Stone cementitious material with and without activated carbon (a potential organic adsorption additive). The interactions between organic compounds were observed in traditional batch sorption and modified Toxic Characteristic Leaching Procedure (TCLP) leachate tests for a surrogate Cast Stone material with and without an activated carbon addition. Specifically, phthalic acids (negatively charged) and 4-chloroaniline (polar) sorbed strongly to unmodified Cast Stone and a group of 3 phenolic compounds (2,4,6-Trichlorophenol, Pentachlorophenol, o-Cresol) were sorbed to and were retained by Cast Stone with a 1% activated carbon amendment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Uptake, Efflux, and Sequestration of Mercury in the Asian Clam, Corbicula fluminea , at Environmentally Relevant Concentrations, and the Implications for Mercury Remediation

(1) Mercury (Hg) is a persistent, ubiquitous contaminant that readily biomagnifies into higher trophic level species in aquatic environments across the globe. It is crucial to understand the movement of environmentally relevant concentrations of Hg in impacted freshwater streams to minimize risks to ecological and human health. (2) The bioconcentration kinetics of aqueous Hg exposure (20, 100, and 200 ng/L) in the invasive Asian Clam, Corbicula fluminea, were measured. A toxicokinetic model, the first parameterized for Hg accumulation in freshwater clams, was developed to estimate uptake and efflux parameters and compared to previous parameter values estimated for other mollusk species. (3) Results demonstrated that even at low Hg concentrations, Corbicula record signals of contamination through bioconcentration, and both direct measurement and toxicokinetic models demonstrate large Hg bioconcentration factors (as high as 1.34 × 10 5 mL/g dry tissue), similar to partitioning coefficients seen in engineered Hg sorbents. (4) Our study found that Corbicula accumulated Hg at aqueous concentrations relevant to impacted streams, but well below regulatory drinking water limits, demonstrating their utility as a sensitive sentinel species and potential bioremediator.

bioaccumulation↗