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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An Expanded Set of Los Alamos OPLIB Tables in MESA: Type-1 Rosseland-mean Opacities and Solar Models

Abstract We present a set of 1194 Type-1 Rosseland-mean opacity tables for four different metallicity mixtures. These new Los Alamos OPLIB atomic radiative opacity tables are an order of magnitude larger in number than any previous opacity table release, and span regimes where previous opacity tables have not existed. For example, the new set of opacity tables expands the metallicity range to Z = 10 −6 to Z = 0.2, which allows improved accuracy of opacities at low and high metallicity, increases the table density in the metallicity range Z = 10 −4 to Z = 0.1 to enhance the accuracy of opacities drawn from interpolations across neighboring metallicities, and adds entries for hydrogen mass fractions between X = 0 and X = 0.1 including X = 10 −2 , 10 −3 , 10 −4 , 10 −5 , 10 −6 that can improve stellar models of hydrogen deficient stars. We implement these new OPLIB radiative opacity tables in MESA and find that calibrated solar models agree broadly with previously published helioseismic and solar neutrino results. We find differences between using the new 1194 OPLIB opacity tables and the 126 OPAL opacity tables range from ≈20% to 80% across individual chemical mixtures, up to ≈8% and ≈15% at the bottom and top of the solar convection zone respectively, and ≈7% in the solar core. We also find differences between standard solar models using different opacity table sources that are on par with altering the initial abundance mixture. We conclude that this new, open-access set of OPLIB opacity tables does not solve the solar modeling problem, and suggest the investigation of physical mechanisms other than the atomic radiative opacity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A two-equation soot-in-flamelet modeling approach applied under Spray A conditions

Soot production (including formation and oxidation) is studied in the transient, high-pressure and turbulent n-dodecane Spray A flames from the Engine Combustion Network (ECN) using computational fluid dynamics (CFD) simulations. A two-equation soot-in-flamelet modeling approach is applied within the framework of the Unsteady Flamelet Progress Variable (UFPV) model and results are validated against experimental data. Equations for soot mass fraction and soot number density derived in the mixture fraction space are solved in the context of detailed flamelet calculations. Source terms for the different steps in the soot chemistry are tabulated and incorporated in the flamelet manifold. For the reference condition, the modeling approach based on the tabulated flamelet manifold reduces the computational cost of a CFD calculation by approximately 40 times compared to a non-tabulated well-mixed (WM) modeling approach. The soot-in-flamelet approach is then extended to study the effect of ambient oxygen concentration, ambient mixture composition and ambient temperature on soot production. Results show that the modeling approach is able to capture the experimental trends for the soot volume fraction (SVF) with good quantitative agreement, especially in the soot ramp-up region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

On the modes of nanosecond pulsed plasmas for combustion ignition of quiescent CH 4 -air mixtures

The effect of transient plasma modes on ignition kernel development are discussed here for a quiescent CH 4 -air combustion model system. A 10 ns high-voltage pulse was applied to a pin-to-pin electrode in lean fuel-air mixtures at room temperature and atmospheric pressure. High-impedance streamer, transient spark and low-impedance spark discharges were identified based on pulse waveforms of voltage and current. A sustained ignition kernel expansion was observed when the plasma discharge transitioned into a transient spark or spark discharge. The minimum ignition energy was obtained at the transient spark mode, which has less than a third of the energy or Coulomb transfer compared to the low-impedance spark. Employing repetitive 10-pulse sequence at 10 kHz, the lean-fuel limit was extended from an equivalence ratio of 0.6 for the single pulse ignition to 0.5. The use of repetitive pulses also allowed streamer breakdown or spark initiation to occur at a lower voltage.

CH 4↗
DOE OSTI2023

Quantitative Analysis of The High‐Yield Hydrolysis of Kelp by Laminarinase and Alginate Lyase

Abstract Kelp is an abundant, farmable biomass‐containing laminarin and alginate as major polysaccharides, providing an excellent model substrate to study their deconstruction by simple enzyme mixtures. Our previous study showed strong reactivity of the glycoside hydrolase family 55 during hydrolysis of purified laminarin, raising the question of its reactivity with intact kelp. In this study, we determined that a combination of a single glycoside hydrolase family 55 β‐1,3‐exoglucanase with a broad‐specificity alginate lyase from the polysaccharide lyase family 18 gives efficient hydrolysis of untreated kelp to a mixture of simple sugars, that is, glucose, gentiobiose, mannitol‐end glucose, and mannuronic and guluronic acids and their soluble oligomers. Quantitative assignments from nanostructure initiator mass spectrometry (NIMS) and 2D HSQC NMR spectroscopy and analysis of the reaction time‐course are provided. The data suggest that binary combinations of enzymes targeted to the unique polysaccharide composition of marine biomass are sufficient to deconstruct kelp into soluble sugars for microbial fermentation.

2D HSQC NMR↗
DOE OSTI2021

Modeling molybdeneum-99 production in molten salt reactors

Molten salt reactors (MSRs) are being investigated as a possible source of 99 Mo for medical uses. This paper describes computational modeling being performed to determine the feasibility for use of several MSR concepts in 99 Mo production: the Molten Salt Breeder Reactor (MSBR), the Molten Salt Demonstration Reactor (MSDR), and the Molten Salt Reactor Experiment (MSRE). This modeling is accomplished with SCALE/TRITON using a three-mixture system and estimated removal terms. Results showed that the MSBR, MSDR and MSRE were capable of supplying an estimated 35,800,000, 13,700,000, and 132,000 six-day Ci/week of 99 Mo, respectively, which is far more than the global demand. In conclusion, a range of operating parameters has been determined in which each reactor type is expected to have sufficient production capability to meet global demand.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Recent advances in computational mathematics and applications

We are honored to bring you this special issue dedicated to recent advances in computational mathematics and applications in science and engineering. The papers in this special issue were presented in ”Conference on Computational Mathematics and Applications (CCMA)” held at the University of Nevada Las Vegas (UNLV) during October 25–27, 2019. The conference has attracted about 90 attendees from six countries. The 15 papers in the special issue comprise a diverse collection of theoretical numerical analysis as well as applications in various subjects. Topics cover optimal control of PDEs, discontinuous Galerkin methods, fluid flow in porous media, turbulence flow, static and moving interface problems, complex fluids composed by the mixture of Newtonian fluid and nematic (liquid crystal) flows, modeling of ocean–atmosphere system, image segmentation algorithm, uncertainty quantification problems for turbulence model and Maxwell’s equations, iterative solver for systems resulting from mixed methods, and novel methods for solving systems of nonlinear equations. As the Guest Editors we would like to thank Dr. Leland Jameson at NSF (National Science Foundation) for kindly supporting our conference proposal which made this conference possible. We would also like to thank Darren Sugrue from Elsevier who provided partial support for our conference, and Thennarasu Gunasekaran and his production team from Elsevier who produced this nice special issue. We are grateful to many people (Dr. Zhijian Wu, Lori Ornelas, Elsa Juarez, and many Ph.D. students) at the Department of Mathematical Sciences of UNLV who provided tremendous support for the conference. Finally, we very much appreciate all authors who contributed their precious results to this special issue.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Combining High-Throughput Experiments and Active Learning to Characterize Deep Eutectic Solvents

The high tunability of deep eutectic solvents (DESs) stems from the ease of changing their precursors and relative compositions. However, measuring the physicochemical properties across large composition and temperature ranges, necessary to properly design target-specific DESs, is tedious and error-prone and represents a bottleneck in the advancement and scalability of DES-based applications. As such, active learning (AL) methodologies based on Gaussian processes (GPs) were developed in this work to minimize the experimental effort necessary to characterize DESs. Owing to its importance for large-scale applications, the reduction of DES viscosity through the addition of a low-molecular-weight solvent was explored as a case study. A high-throughput experimental screening was initially performed on nine different ternary DESs. Then, GPs were successfully trained to predict DES viscosity from its composition and temperature, showcasing the ability of these stochastic, nonparametric models to accurately describe the physicochemical properties of complex mixtures. Finally, the ability of GPs to provide estimates of their own uncertainty was leveraged through an AL framework to minimize the number of data points necessary to obtain accurate viscosity modes. This led to a significant reduction in data requirements, with many systems requiring only five independent viscosity data points to be properly described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Decomposition of methane diluted with inert gas in an RF discharge cell

Decomposition of methane using non-thermal plasmas is an attractive route for producing hydrogen-rich gases and valuable carbon nanomaterials. Understanding how plasma discharge modes influence methane decomposition in optimizing plasma-assisted chemical conversion remains unexplored. This study explores the coupling between the discharge structure and product selectivity in RF capacitively coupled discharges operating in methane/inert gas mixtures in the pressure range of 2–3 torr. Under our experimental conditions the discharge exhibits mode transitions from uniform to striated in Ar and Kr and from diffuse to contracted in Ar and Kr with <5% CH 4 . The discharges in He and Ne remained uniform under our operating conditions, and their mixtures with CH 4 remained diffuse. A 0-d model for Ar/CH 4 discharge established a threshold for contraction while also asserting the importance of Ar$^{*}_{\textrm{m}}$ in the dissociation and ionization processes. The highest degree of methane decomposition, >99.7% with the main products of acetylene and graphitized solid carbon was achieved in the contracted discharge mode for both Kr or Ar with ⩽5% CH 4 . We demonstrate that contraction can play a crucial role in the effective decomposition of methane with value-added products and that both the electronic and thermal properties of plasma gas are responsible for this effect.

RF plasma↗
DOE OSTI2025

Three and Two Phase Rotating Field Inductive Couplers for Wireless Power Transfer with One Phase per Layer Windings

Multiphase inductive wireless charging coils have been proposed recently to improve coupler surface power density, reduce component stress and size, and provide near-constant power delivery to charge mobile electric systems. Several aspects for the fundamental characterization of multiphase coils are explored up to six phases including approximate mutual inductance with size and turn variation, induced voltage, and output power estimation. The relative component stress and size of passive components for resonant operation are compared between the multiphase variants. A combination of an experimentally validated 3D electromagnetic finite element analysis (FEA) and power electronic co-simulations are used to validate the estimated quantities approximated with a mixture of analytical equations and an artificial neural network model for mutual inductance. A novel three-phase transmitter, two-phase receiver coil pair is also proposed for electric vehicle charging to reduce the number of connections and compensation complexity on the vehicle-side with improved power output compared to a two-phase configuration.

Lewis, Donovin D. [University of Kentucky]↗
DOE OSTI2023

Fundamental Studies of Bifunctional Catalysts for Tandem Reactions

During the past few years of our funding from DOE Basic Energy Sciences, we have focused on the catalytic conversion of biomass-derived 5-hydroxymethyl furfural (HMF) as a platform molecule for sustainable synthesis of value-added chemicals. The combination of the diene and aldehyde functionalities in HMF enables catalytic production of acetalized HMF derivatives with diol or epoxy reactants to allow reversible synthesis of norcantharimide derivatives upon Diels-Alder reaction with maleimides. Whereas the electron-withdrawing nature of aldehyde group inhibits the reactivity of diene group in HMF to undergo Diels-Alder reactions with dienophiles, by converting the aldehyde group in HMF to an electron-donating hydroxyl group, HMF can append maleimide-based chemicals through Diels-Alder coupling. Acetalization of HMF not only produces an electron-rich diene for Diels-Alder reaction, but it also alters the reversibility of acetal formation and thereby allows for the controlled release of chemicals by hydrolysis. Therefore, we synthesized various norcantharimide derivatives from biomass-derived HMF by acetalization over an acid catalyst, Amberlyst-15, followed by Diels-Alder reaction with maleimide. The norcantharimides release the starting materials by retro Diels-Alder reaction that is triggered by acetal hydrolysis under acidic (≤pH 3) conditions. In subsequent work, we explored the synthesis and properties of functional polyurethanes and polyesters with tunable properties from biomass-derived (HMF)-Acetone-HMF (HAH) monomers. HAH can be selectively hydrogenated over Cu and Ru catalysts to produce partially-hydrogenated HAH (PHAH) and fully-hydrogenated HAH (FHAH). HAH contains functional groups, including hydroxyl, furan, enone, and ketone functionalities, that can be exploited to further tune the polymer properties. The π-electron conjugation between the enone and furan groups in HAH monomer stabilizes the furan group to prevent the uncontrolled degradation of furans during reactions, such as etherification. Therefore, HAH is a renewable monomer that can be used to synthesize polymers, having high molecular weight, symmetric functionalities, an inexpensive production price, and being derived from renewable resources without competition with food resources. We demonstrated the synthesis of functional polyurethanes and a renewable polyester from HAH-derived monomers, and 4,4’-methylenebis(phenyl isocyanate) (MDI). We showed that it is essential to be able to selective hydrogenate C=C double bonds in HAH to be able to achieve effective Diels Alder reactions of the furan ring. Therefore, we studied the hydrogenation at temperatures from 313 – 393 K of HAH over Pd, Ru, and Cu based catalysts. HAH was selectively hydrogenated to produce partially-hydrogenated monomers (PHAH) over Cu and Ru catalysts and to fully-hydrogenated HAH monomers (FHAH) over the Ru catalyst. Pd based catalysts yielded a mixture of partially and fully hydrogenated monomers. Reaction kinetics models were employed to quantify the kinetic behavior for hydrogenation over Ru, Cu, and Pd catalysts. A 5-step pathway exhibited over Pd and Ru catalysts consists of both series and parallel reaction steps, where HAH is both converted to fully hydrogenated products sequentially via series reactions of partially hydrogenated intermediates, as well as converted directly in parallel reactions to form the fully hydrogenated products. In contrast, a 3-step pathway over the Cu catalyst consists only of the consecutive reaction steps, where the final product was formed via series reactions of intermediate products. Additionally, reaction over the Cu catalyst did not hydrogenate the furan rings of the HAH molecule and yielded a different final product than those hydrogenation over Pd and Ru catalysts. Using the results from our detailed reaction kinetics studies, we developed universal conditions for the maximum production of the various hydrogenated products for both batch and plug flow systems. In subsequent work, we employed reaction schemes to optimize the yields of products from selective hydrogenations of HAH in isopropanol solvent and in the presence of liquid water. Reaction schemes consisting of 7, 9, and 11 steps were examined to describe the rates of formation of the observed products and reaction intermediates for hydrogenation of HAH over Ru and Pd catalysts, and a 3-step scheme was studied over Cu catalysts. Rate constants and activation energies were calculated using these reaction schemes, and we then apply these reaction schemes to explore the effects of water addition on the hydrogenation pathways. The effects of water addition to isopropanol (IPA) solvents on the hydrogenation of HAH were markedly different over Pd, Ru, and Cu catalysts. Over the Pd catalyst, the addition of water to IPA increased hydrogenation rates and promoted hydrogenation of furan rings. The addition of water to IPA yielded significant carbon losses over the Ru catalyst, and slowed hydrogenation steps over Cu, while significantly inhibiting hydrogenation of the ketone group. This behavior opened routes toward increased production rates of PHAH=O (a partially hydrogenated form of HAH containing a C=O bond), a product in which the diene groups of the furan rings were not hydrogenated. Addition of water also allowed increased feed concentrations of HAH that were previously not possible in pure IPA solvents.

09 BIOMASS FUELS↗
DOE OSTI2023

Ethane-CO2 Mixture Adsorption in Silicalite: Influence of Tortuosity and Connectivity of Pores on Selectivity

Selective adsorption using nanoporous materials is an efficient strategy for separating gas mixtures. In a nanoporous material, pores can exist in different shapes and can have different degrees of inter-connectivity. In recent studies, both pore connectivity and tortuosity have been found to affect the adsorption and dynamical properties of ethane and CO2 in silicalite differently. Here, using Monte Carlo simulations, we investigate if these two attributes can affect the selective adsorption of one component from a mixture of ethane and CO2 in silicalite. For this, the adsorption of an equimolar mixture of ethane and CO2 is simulated in 12 models of silicalite—SnZm (n, m = 0, 1, 2, 3 or 4; with n and m denoting, respectively, the fraction (out of 4) of straight and zigzag channels of silicalite that are available for adsorption)—differing in degrees of pore connectivity and tortuosity. The adsorption selectivity in this system is found to exhibit a reversal with the adsorption dominated by ethane at low pressures (below ~1 atm) and by CO2 at higher pressures (above ~10 atm). Pore connectivity is found to suppress the selective adsorption of CO2 at higher pressures and also shifts the selectivity reversal to higher pressures. The selectivity reversal results from a competition between the polarizability-affected adsorption at lower pressures and efficient packing at higher pressures. The efficient packing of CO2 is a compounded effect resulting from the larger effective pore volume available for CO2 due to its stronger interaction with the pore surface and smaller molecular volume. CO2 molecules show a preference to adsorb in non-tortuous pores, and this preference is found to be stronger in the presence of ethane. The effects of pore connectivity and tortuosity elucidated here should be applicable to a wide range of natural and engineered nanoporous materials, and this knowledge could be used to identify materials with better capability for separating and storing CO2 based on their pore attributes.

Gautam, Siddharth (ORCID:0000000314435382)↗
DOE OSTI2023

An Assessment of Kinetic Models for Ammonia Flame Extinction

The growing interest in using ammonia as a carbon-neutral replacement fuel has prompted numerous recent research efforts towards understanding fundamental combustion characteristics and chemical kinetics of ammonia oxidation. Despite these recent efforts, there remains a large deficiency in extinction limit data for ammonia flames, particularly under elevated pressure and temperature conditions relevant to gas turbines. Even the literature reaction mechanisms developed specifically for ammonia have been untested under gas turbine relevant conditions, and existing kinetic models have shown large variations in laminar flame speed, extinction strain rate, and speciation predictions for NH3–H2 mixtures at ambient conditions. Recent work by Thomas and co-workers, for example, compared different ammonia kinetic models in the literature for predicting their extinction strain rate measurements for non-premixed NH3-H2 counterflow flames, and again have highlighted the discrepancies in model predictions. Here, our work has undertaken to further highlight important reaction pathways for ammonia oxidation that may be responsible for these discrepancies for extinction strain rate predictions, as well as elucidate sensitive reaction steps with large uncertainties that require further attention. This work points to a need for an improved understanding of ammonia combustion chemistry as well as new datasets at elevated pressure and temperature conditions to better constrain rate expressions for key reaction steps.

ammonia, flame, combustion, kinetic, kinetics↗
DOE OSTI2020

Sorption of Anionic Iodine and Molybdenum to Multi-sorbing Barrier (MSB) Materials - 20030

A multi-sorbing barrier (MSB) material containing sodium bentonite (NaB), organoclay, and anion resin is being evaluated for containment of anionic radionuclides. Batch tests on the MSB were conducted using two non-radioactive analog isotopes ({sup 127}I, {sup 95}Mo) as surrogates for {sup 129}I and {sup 99}Tc due to their similar valence and molecular weight relative to the radionuclides. Tests were conducted on the organoclay, anion resin, and NaB individually and on NaB-resin blends with resin contents of 1% and 5% by mass. The anion resin exhibits very strong sorption of {sup 127}I and {sup 95}Mo relative to the other materials. The organoclay exhibited modest sorption of {sup 95}Mo and {sup 127}I, and NaB little sorption. The sorption isotherms follow a linear model for NaB, a Freundlich model for the organoclay, and a Langmuir model for the anion resin and NaB-resin mixtures. Combining resin with NaB significantly enhances sorption relative to NaB alone, with a larger resin fraction yielding greater sorption. (authors)

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

Autonomous hybrid optimization of a SiO 2 plasma etching mechanism

Computational modeling of plasma etching processes at the feature scale relevant to the fabrication of nanometer semiconductor devices is critically dependent on the reaction mechanism representing the physical processes occurring between plasma produced reactant fluxes and the surface, reaction probabilities, yields, rate coefficients, and threshold energies that characterize these processes. The increasing complexity of the structures being fabricated, new materials, and novel gas mixtures increase the complexity of the reaction mechanism used in feature scale models and increase the difficulty in developing the fundamental data required for the mechanism. This challenge is further exacerbated by the fact that acquiring these fundamental data through more complex computational models or experiments is often limited by cost, technical complexity, or inadequate models. In this paper, we discuss a method to automate the selection of fundamental data in a reduced reaction mechanism for feature scale plasma etching of SiO 2 using a fluorocarbon gas mixture by matching predictions of etch profiles to experimental data using a gradient descent (GD)/Nelder–Mead (NM) method hybrid optimization scheme. These methods produce a reaction mechanism that replicates the experimental training data as well as experimental data using related but different etch processes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fluctuating hydrodynamics and the Rayleigh–Plateau instability

The Rayleigh–Plateau instability occurs when surface tension makes a fluid column become unstable to small perturbations. At nanometer scales, thermal fluctuations are comparable to interfacial energy densities. Consequently, at these scales, thermal fluctuations play a significant role in the dynamics of the instability. These microscopic effects have previously been investigated numerically using particle-based simulations, such as molecular dynamics (MD), and stochastic partial differential equation–based hydrodynamic models, such as stochastic lubrication theory. In this paper, we present an incompressible fluctuating hydrodynamics model with a diffuse-interface formulation for binary fluid mixtures designed for the study of stochastic interfacial phenomena. An efficient numerical algorithm is outlined and validated in numerical simulations of stable equilibrium interfaces. We present results from simulations of the Rayleigh–Plateau instability for long cylinders pinching into droplets for Ohnesorge numbers of Oh = 0.5 and 5.0. Both stochastic and perturbed deterministic simulations are analyzed and ensemble results show significant differences in the temporal evolution of the minimum radius near pinching. Short cylinders, with lengths less than their circumference, were also investigated. As previously observed in MD simulations, we find that thermal fluctuations cause these to pinch in cases where a perturbed cylinder would be stable deterministically. Finally, we show that the fluctuating hydrodynamics model can be applied to study a broader range of surface tension–driven phenomena.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Separation of volatile organic contaminants from water using a direct-contact dehumidifier: An experimental study and modeling

A packed-bed, direct-contact dehumidifier (PB-DCD) has been developed to selectively condense water from a gaseous mixture of organic contaminants. In this process, hot air is humidified by mixing with wastewater vapor in a static mixer and is dehumidified by subcooled fresh water passing through the PB-DCD in a counter-current configuration. The goal of this study is to understand the relationship between various operating parameters and how they affect separation of isopropyl alcohol (IPA) from the gaseous mixture with the purpose of expanding the investigation to other contaminants in the future. The process has been successfully used to separate IPA from wastewater. Different parameters including the concentration of IPA in water, feed temperature, air-to-vapor ratio, and cooling-water-to-vapor mass ratio, as well as residence time were examined to determine their influence on contaminant separation and clean water recovery rate. The Buckingham Pi theorem was applied to reduce the number of studying variables by generating non-dimensional groups. Experiments were performed to determine the relationship between the non-dimensional parameters and model mass transfer in the system. Mass transfer coefficients for multicomponent gaseous mixture condensation in a packed-bed direct contact condenser column are calculated and a modified correlation of mass transfer is developed. The parameters of the mass transfer model are obtained from operating conditions of the PB-DCD, stream conditions and thermodynamic properties. A modified Sherwood correlation is developed to predict IPA separation from a gaseous mixture consisting of air, water, and IPA. The modified Sherwood correlation is applied to successfully predict the Sherwood number with a mean absolute error equal to 6.6 %. According to the experimental results, the maximum IPA separation achieved was 76.3 %, which corresponds to a water recovery rate of 58.7 %.

42 ENGINEERING↗
DOE OSTI2024

Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

Abstract The assessment and regulation of chemical toxicity to protect human health and the environment are done one chemical at a time and seldom at environmentally relevant concentrations. However, chemicals are found in the environment as mixtures, and their toxicity is largely unknown. Understanding the hazard posed by chemicals within the mixture is critical to enforce protective measures. Here, we demonstrate the application of bioactivity profiling of environmental water samples using the sentinel and ecotoxicology model species Daphnia to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a Daphnia strain to 30 sampled waters of the Chaobai River and measured the gene expression response profiles. Using a multiblock correlation analysis, we establish correlations between chemical mixtures identified in 30 water samples with gene expression patterns induced by these chemical mixtures. We identified 80 metabolic pathways putatively activated by mixtures of inorganic ions, heavy metals, polycyclic aromatic hydrocarbons, industrial chemicals, and a set of biocides, pesticides, and pharmacologically active substances. Our data-driven approach discovered both known bioactivity signatures with previously described modes of action and new pathways linked to undiscovered potential hazards. This study demonstrates the feasibility of reducing the complexity of real-world mixture toxicity to characterize the biomolecular effects of a defined number of chemical components based on gene expression monitoring of the sentinel species Daphnia.

Engineering↗