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At least 919 records · Page 51

Technical note: The role of evolving surface tension in the formation of cloud droplets

The role of surface tension ( σ ) in cloud droplet activation has long been ambiguous. Recent studies have reported observations attributed to the effects of an evolving surface tension in the activation process. However, the adoption of a surface-mediated activation mechanism has been slow and many studies continue to neglect the composition dependence of aerosol–droplet surface tension, using instead a value equal to the surface tension of pure water ( σ w ). In this technical note, we clearly describe the fundamental role of surface tension in the activation of multicomponent aerosol particles into cloud droplets. It is demonstrated that the effects of surface tension in the activation process depend primarily on the evolution of surface tension with droplet size, typically varying in the range 0.5 σ w ≲ σ ≤ σ w due to the partitioning of organic species with a high surface affinity. We go on to report some recent laboratory observations that exhibit behavior that may be associated with surface tension effects and propose a measurement coordinate that will allow surface tension effects to be better identified using standard atmospheric measurement techniques. Unfortunately, interpreting observations using theory based on surface film and liquid–liquid phase separation models remains a challenge. Our findings highlight the need for experimental measurements that better reveal the role of composition-dependent surface tensions, critical for advancing predictive theories and parameterizations of cloud droplet activation.

54 ENVIRONMENTAL SCIENCES↗

Ion mobility spectrometry–mass spectrometry (IMS–MS) for on- and offline analysis of atmospheric gas and aerosol species

Abstract. Measurement techniques that provide molecular-level information are needed to elucidate the multiphase processes that produce secondary organic aerosol (SOA) species in the atmosphere. Here we demonstrate the application of ion mobility spectrometry-mass spectrometry (IMS–MS) to the simultaneous characterization of the elemental composition and molecular structures of organic species in the gas and particulate phases. Molecular ions of gas-phase organic species are measured online with IMS–MS after ionization with a custom-built nitrate chemical ionization (CI) source. This CI–IMS–MS technique is used to obtain time-resolved measurements (5 min) of highly oxidized organic molecules during the 2013 Southern Oxidant and Aerosol Study (SOAS) ambient field campaign in the forested SE US. The ambient IMS–MS signals are consistent with laboratory IMS–MS spectra obtained from single-component carboxylic acids and multicomponent mixtures of isoprene and monoterpene oxidation products. Mass-mobility correlations in the 2-D IMS–MS space provide a means of identifying ions with similar molecular structures within complex mass spectra and are used to separate and identify monoterpene oxidation products in the ambient data that are produced from different chemical pathways. Water-soluble organic carbon (WSOC) constituents of fine aerosol particles that are not resolvable with standard analytical separation methods, such as liquid chromatography (LC), are shown to be separable with IMS–MS coupled to an electrospray ionization (ESI) source. The capability to use ion mobility to differentiate between isomers is demonstrated for organosulfates derived from the reactive uptake of isomers of isoprene epoxydiols (IEPOX) onto wet acidic sulfate aerosol. Controlled fragmentation of precursor ions by collisionally induced dissociation (CID) in the transfer region between the IMS and the MS is used to validate MS peak assignments, elucidate structures of oligomers, and confirm the presence of the organosulfate functional group.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗

The effects of changing climate on estuarine water levels: a United States Pacific Northwest case study

Climate change impacts on extreme water levels (WLs) at two United States Pacific Northwest estuaries are investigated using a multicomponent process-based modeling framework. The integrated impact of climate change on estuarine forcing is considered using a series of sub-models that track changes to oceanic, atmospheric, and hydrologic controls on hydrodynamics. This modeling framework is run at decadal scales for historic (1979–1999) and future (2041–2070) periods with changes to extreme WLs quantified across the two study sites. It is found that there is spatial variability in extreme WLs at both study sites with all recurrence interval events increasing with further distance into the estuary. This spatial variability is found to increase for the 100-year event moving into the future. It is found that the full effect of sea level rise is mitigated by a decrease in forcing. Short-recurrence-interval events are less buffered and therefore more impacted by sea level rise than higher-returninterval events. Finally, results show that annual extremes at the study sites are defined by compound events with a variety of forcing contributing to high WLs.

Parker, Kai↗

Data for "Integrated ab initio modelling of atomic order and magnetic anisotropy for rare-earth-free magnet design: effects of alloying additions in L1 0 FeNi."

We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.

36 MATERIALS SCIENCE↗

Optimal Membrane Cascade Design for Critical Mineral Recovery Through Logic-based Superstructure Optimization

Critical minerals and rare earth elements play an important role in our climate change initiatives, particularly in applications related with energy storage. Here, we use discrete optimization approaches to design a process for the recovery of Lithium and Cobalt from battery recycling, through membrane separation. Our contribution involves proposing a Generalized Disjunctive Programming (GDP) model for the optimal design of a multistage diafiltration cascade for Li-Co separation. By solving the resulting nonconvex mixed-integer nonlinear program model to global optimality, we investigated scalability and solution quality variations with changes in the number of stages and elements per stage. Results demonstrate the computational tractability of the nonlinear GDP formulation for design of membrane separation processes while opening the door for decom-position strategies for multicomponent separation cascades. Future work aims to extend the GDP formulation to account for stage installation and explore various decomposition techniques to enhance solution efficiency.

Ovalle, Daniel↗

Vaccination with mycobacterial lipid loaded nanoparticle leads to lipid antigen persistence and memory differentiation of antigen-specific T cells

Mycobacterium tuberculosis (Mtb) infection elicits both protein and lipid antigen-specific T cell responses. However, the incorporation of lipid antigens into subunit vaccine strategies and formulations has been underexplored, and the characteristics of vaccine-induced Mtb lipid-specific memory T cells have remained elusive. Mycolic acid (MA), a major lipid component of the Mtb cell wall, is presented by human CD1b molecules to unconventional T cell subsets. These MA-specific CD1b-restricted T cells have been detected in the blood and disease sites of Mtb-infected individuals, suggesting that MA is a promising lipid antigen for incorporation into multicomponent subunit vaccines. In this study, we utilized the enhanced stability of bicontinuous nanospheres (BCN) to efficiently encapsulate MA for in vivo delivery to MA-specific T cells, both alone and in combination with an immunodominant Mtb protein antigen (Ag85B). Pulmonary administration of MA-loaded BCN (MA-BCN) elicited MA-specific T cell responses in humanized CD1 transgenic mice. Simultaneous delivery of MA and Ag85B within BCN activated both MA- and Ag85B-specific T cells. Notably, pulmonary vaccination with MA-Ag85B-BCN resulted in the persistence of MA, but not Ag85B, within alveolar macrophages in the lung. Vaccination of MA-BCN through intravenous or subcutaneous route, or with attenuated Mtb likewise reproduced MA persistence. Moreover, MA-specific T cells in MA-BCN-vaccinated mice differentiated into a T follicular helper-like phenotype. Overall, the BCN platform allows for the dual encapsulation and in vivo activation of lipid and protein antigen-specific T cells and leads to persistent lipid depots that could offer long-lasting immune responses.

59 BASIC BIOLOGICAL SCIENCES↗

EMHOLE v. 2.1

Program EMHOLE is an electromagnetic (EM) forward modeling algorithm that calculates time-domain electric vector e (with SI unit V/m) and magnetic vector h (in A/m) responses generated by a variety of point body sources situated within a homogeneous and isotropic wholespace. A mathematically exact (i.e., without low-frequency or far-field approximation) numerical evaluation procedure is utilized to simulate EM responses (alternately, Green functions) observed at a set of multicomponent receivers distributed throughout the wholespace.

Aldridge, David F.↗

iGeoT v1.0

iGeoT v1.0 automates into a stand-alone computer program the multicomponent chemical geothermometry code GeoT v2.1 and the numerical optimization engine of iTOUGH2. iGeoT allows for optimizations of GeoT runs using multiple water chemical analyses. The underlying geothermometry method is that previously developed by Reed and Spycher (1984) using the computed saturation indices of multiple minerals. GeoT automatically reconstitutes deep fluid compositions and estimates reservoir temperature from statistical evaluation of computed mineral saturation indices. The output include estimated temperatures following various statistical methods and their range of uncertainty. The computer program also outputs temperatures predicted using classical geothermometers. Input parameters include water composition and, optionally, gas composition, fraction of gas discharge, dilution/evaporation factor (in case of boiling or mixing with dilute waters), and end-member water composition (in case of mixing with other non-dilute waters). The dilution/evaporation factor, fraction of gas discharge, and concentration of various aqueous and gas species can be automatically estimated by numerical optimization. This program was designed for geothermal applications.

Spycher, Nicolas↗

eSTOMP-WR

The eSTOMP-WR mode is designed to efficiently simulate isothermal variably saturated flow (Richards Equation) and multicomponent reactions in porous media on the most powerful computers available.

Source record↗

Corrosion Evaluation of CoCrFeMnNi High-Entropy Alloys (HEAs) for Corrosion Protection of Natural Gas Transmission Pipelines

High-entropy alloys (HEAs), are multicomponent alloys composed of at least five elements with compositions of 5-35 atomic % for each element. These alloys are being investigated for corrosion protection of natural gas transmission pipelines by studying their behavior under aqueous acidic conditions. Electrochemical and immersion experiments were carried out in 3.5 weight % NaCl solution at pH 4 and 40°C. Oxygen was purged out from the solution by using CO2 as stripping gas. The electrochemical experiments included potentiodynamic and electrochemical impedance spectroscopy tests, used to calculate corrosion rates. Potentiodynamic polarization curves, including cyclic voltammograms, were used to explain active, active-passive, and passive regions of these alloys and susceptibility to localized corrosion. Surface characterization of the corroded samples were performed using scanning electron microscopy (SEM) and x-ray diffraction (XRD). The results of the immersion and electrochemical testing indicate that some of the HEAs have better corrosion performance than commercial alloys UNS N10276, UNS K03014, and UNS 31600.

03 NATURAL GAS↗

Provisional Conceptual Model of the Camas Prairie (ID) Geothermal System from Play Fairway Analysis

Camas Prairie, Idaho, is an EW-trending structural graben that lies north of the Snake River Plain hotspot track. It is bounded on the north by the Idaho Batholith, and on the south by the Mount Bennett Hills. This region was investigated by the SRP Geothermal Play Fairway Analysis team, which included focused geologic, geochemical, and geophysical studies. The Camas Prairie geothermal system resource is indicated by warm springs and wells, geophysical analysis of buried faults and basins, mapped faults, structural analysis of all faults and lineaments, high 3He/4He, cation and multicomponent geothermometry, and the occurrence of young basalt vents and lava flows along the range front. Our provisional conceptual model includes the following components: (1) High permeability is indicated by the confluence of intersecting faults, including the major range front system and The Pothole fault system, with releasing bends as deduced from detailed field studies, and the presence of springs along mapped structural features; (2) High heat is inferred to result from mid- to shallow crustal sills, as evidenced by the location of vents along the range front; the youngest dated vent is 692 ka, but 2 ka vents lie to NW; (3) an effective seal is indicated by magnetotelluric studies, which suggest a clay seal over the prospective target area that is likely a result of hydrothermal alteration. This model is similar to that proposed for the western SRP but is less energetic due to the smaller volume of magma inferred. It is also similar to Basin-and-Range geothermal systems, but differs by including a distinct magmatic heat component.

15 GEOTHERMAL ENERGY↗

Experimental and modeling study of the autoignition behavior of a standard oxygenated gasoline fuel

Gasoline surrogate models can be conveniently used to simulate the combustion behavior of fuels in internal combustion engines. Because of limitations in the number of robust models available and the high computational cost of running them, simple surrogates with only 2 or 3 components (namely n-heptane, iso-octane and toluene) have been long preferred to simulate the ignition behavior of gasoline in engine calculations. More recently, thanks to the development of new, well-validated kinetic models and the access to cheap high-performance computing, the scientific and engineering community is utilizing the higher fidelity provided by more complex mixture models. The added detail in composition can in fact better reproduce variation in the fuel reactivity with pressure (an important feature for downsized, boosted conditions) and blending behavior of real fuels. In this study, the ignition behavior of a research grade full blend oxygenated fuel matching the typical specification of US standard grade gasoline has been investigated by means of rapid compression experiments and detailed kinetic calculations. A multicomponent fuel surrogate model has been developed using compositional information and a surrogate optimization tool. Based on the experimental and computational results presented in this study, general considerations about guidelines in the formulation of gasoline fuel surrogates are provided.

autoignition↗

Phase Formation in Nuclear Fallout

An understanding of the physical and chemical process occurring in a nuclear explosion enables predictions of the effects of nuclear weapons, including characteristics of radioactive fallout resulting from the explosion. Near-surface nuclear explosions are of particular interest due to the potential for significant amounts of environmental material to interact with and alter the physical and chemical behavior of the fireball. Such interactions have the potential to affect the distribution of radioactive species in the fireball and subsequently become incorporated into fallout through a process known as radiochemical fractionation. Studying variations in fallout formed in different historical testing environments allows us to understand the influence of local environments on fallout formation processes. In particular, constraining variations in thermal evolution and redox conditions during the evolution of the fireball can be useful to understanding how sensitive fallout radiochemical fractionation may be to the local explosion environment. However, untangling these conditions in complex, multicomponent fallout is a challenge. Here we present one method of constraining and interpreting fallout formation conditions by relating computationally derived phase stability predictions to observations in historic fallout. Development of such approaches will help improve physics-based models of fallout formation and radiochemical fractionation in complex, near surface nuclear detonations.

36 MATERIALS SCIENCE↗

Spatially-Resolved Characterization Techniques and Their Implications for Nuclear Debris Formation.

Debris from nuclear tests has a complex formation process and can inform multiple fields of study such as geology, atmospheric science, shock physics, and chemistry under extreme conditions. Macroscopic nuclear debris forms as the result of fireball interaction with surrounding materials (e.g., structural and environmental component), which rapidly undergo melting and vaporization followed by condensation, convective/diffusive mixing, and solidification over the course of seconds. In atmospheric events, some of this material may disperse over long distances, but much of the material is deposited close-in to ground zero, often in multicomponent, partially (or entirely) amorphous debris formations. During the U.S. nuclear testing program, this material was collected and analyzed, particularly for radionuclide composition. Fallout formation models were developed from nuclear test data based on such radionuclide compositional analyses. These models were not just used to understand fallout dispersion (i.e. the spread of radioactivity over geographical regions) but also guide radiochemical interpretations of historical nuclear tests.6 Developments in analytical techniques over the past several decades have made it possible to make new analyses on historical debris, some of which may be more than a half-century old. For example, inductively-coupled plasma mass spectrometry (ICP-MS) has been used to look at the trace elements in glassy fallout material from aboveground nuclear tests (including the Trinity test). Advanced analyses using X-ray absorption allowed for the measurement of oxidation state of fallout constituents, including actinides. The ability to measure trace actinides and their subsequent oxidation state is important to understanding how the surrounding environment may have influenced the resultant fallout composition and may have implications for why certain fractionation trends have been observed. Here we present data from historic nuclear test debris illustrating the power of spatially resolved methods to connect interaction of the near-field environment with the explosion and provide new insights into nuclear debris formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon dioxide capture system and spectroscopic evaluation thereof

A chemical processing system for removing carbon dioxide from a gas mixture using a multicomponent amine-based scrubbing solution includes a spectroscopic evaluation system with a liquid contact probe for spectroscopic investigation, an energy source connected with the liquid contact probe to provide the spectroscopic stimulation energy to the probe, a spectrometer connected with the liquid contact probe to detect the spectroscopic response energy to the probe and to output spectral data corresponding to the spectroscopic response energy, and a machine learning spectral data analyzer connected to the spectrometer for evaluation of the spectral data to determine a concentration value for each of water, amine component and captured carbon dioxide in the scrubbing solution, the machine learning spectral data analyzer being trained for each such component over a corresponding trained concentration range, and optionally over a trained temperature range to provide a temperature-compensated concentration value.

Panaccione, Charles↗

Advances in PFAS Monitoring and Remediation Using a Functionalized Material Approach

The growing global concerns about the effects to public health from human exposure to per- and polyfluoroalkyl substances (PFAS) motivates the development of strategies for reliable monitoring of PFAS in environmental streams, as well as for their rapid, effective removal if detected. For the continuous PFAS monitoring, an inexpensive, field-deployable, in situ sensor is urgently needed; yet the prevalent in situ techniques often struggle to strike a balance between the practical sensitivity and selectivity demands of the real world. Similarly, for effective PFAS removal, strategies for their fast, selective, and quantitative capture are desired, yet the present commercially available sorbents are unable to meet the requirements of rapid, quantitative capture of all PFAS components, and are notably inefficient in removing the more toxic smaller chains. To address these twin challenges, Pacific Northwest National Laboratory is developing strategies for improved detection and remediation of PFAS. For the rapid, selective, quantitative removal of PFAS from environmental streams, the strategy relies on designing capture probes with exclusively tailored electronic and spatial affinities for the PFAS that are able to selectively capture them from environmental streams. For the in situ detection and quantification of PFAS in complex, multicomponent matrices such as groundwater, the approach relies on the targeted capture of specific PFAS by these PFAS-specific capture probes immobilized on a platform. The platform acts as an electrode to directly measure PFAS concentration through a proportional change in electrical response upon their capture. A combination of optimization of platform design and incorporation of additional, sensitive detection modalities have allowed us to achieve detection limits as low as 0.5 ng/L for detection of PFAS compounds (compared to the 70 ng/L Health Advisory Limit of the U.S. Environmental Protection Agency).

Per- and poly-fluorinated alkyl substances (PFAS),↗

Simulation and Optimization of Volatile Fatty Acid Upgrading Strategies for Sustainable Transportation Fuel Production

The multicomponent nature of and variability of biomass makes chemical upgrading via a single process stream to a single end use infeasible for most feedstocks. A more promising approach is to identify upgrading strategies (encompassing bioprocessing, catalysis, and separations) which valorize varied biomass fractions to distinct products to which each is best suited. A robust procedure to carry out this goal should incorporate comparison of various upgrading procedures as well as suitability of products to a slate of identified end uses. We applied this strategy to one biomass-derived feedstock, volatile fatty acids (VFAs) derived from wet waste arrested anaerobic digestion, by developing a computer program, VFA Upgrading to Liquid Transportation fUels Refinery Estimation (VULTURE) which evaluates VFA catalytic upgrading to liquid transportation fuels. VULTURE considers multiple separations, catalysis (ketonization, hydrogenation), and fuel application options, generating hundreds of candidate scenarios for a given VFA stream, then selects several promising strategies that optimize bio-content of products with properties best suited for target fuel types. We find that VFAs are upgraded most efficiently when separate light alcohol (C3-6) and heavy hydrocarbon or alcohol (C7-13) fractions are targeted to create gasoline and heavy-duty (diesel or jet) fuels or fuel blends. Surrogate property testing of VULTURE-recommended fuels reveals that most predictive models employed are robust, while rigorous process simulation shows that the simple unit operation assumptions used in VULTURE are largely accurate, especially for heavy-duty fuel synthesis. Techno-economic and life-cycle analyses show that VFA-derived fuels are profitable and have dramatically (=57%) lower carbon intensities than fossil analogs.

BIOMASS FUELS↗