Mediating anion-cation interactions to improve aqueous flow battery electrolytes
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This dataset contains gridded estimates of total runoff (mm/day); subsurface runoff (mm/day); snow water equivalent (SWE, mm/day); vertical upward water flux of combined surface evaporation, evapotranspiration, and snow sublimation (mm/day); and soil temperature (C) across the pan-Arctic basin from simulations of the Permafrost Water Balance Model (PWBM v4). These data were generated to allow researchers to advance understanding of the changes unfolding in the Arctic's terrestrial water cycle under the influences of climate warming, hydrological cycle intensification, and permafrost thaw. The dataset will enable researchers to address important questions spanning multiple disciplines. For example, how will rising river flows exported to the coast impact critical zone ecosystems, near-shore ice dynamics, and ocean biogeochemical processes. Spatial resolution is 25x25 km with N=39926 grid cells spanning the domain. Three forcing datasets were used to drive simulations at an implicit daily time step over the period 1980-2100. Daily air temperature, precipitation, and wind speed data from the WATCH Forcing Data methodology applied to ERA5 reanalysis (W5E5) were used for meteorological forcings over the period 1980-2019. Simulations for the period 1980-2100 used meteorological data from two global climate models; IPSL-CM6A-LR and MPI-ESM1-2-HR. The PWBM hydrological outputs are organized by grid and month in gzipped ASCII text files within each archived tar file. Soil temperature is organized by grid cell and day of year from DOY 205 to DOY 260. No special software is required to work with these data. The package contains spatial domain and river basin information files. These data are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and soil thermal dynamics. A manuscript describing the model simulations and associated analysis has been accepted for publication in The Cryosphere (Rawlins and Karmalkar, 2024).
This work introduces the area localized coupled (ALC) model, which extends the applicability of approaches that couple classical wake superposition models and atmospheric boundary layer models to wind farms with arbitrary layouts. Coupling wake and top–down boundary layer models is particularly challenging since the latter requires averaging over planform areas associated with turbine-specific regions of the flow that need to be specified. The ALC model uses Voronoi tessellation to define this local area around each turbine. A top–down description of a developing internal boundary layer is then applied over Voronoi cells upstream of each turbine to estimate the local mean velocity profile. Coupling between the velocity at hub-height based on this localized top–down model and a wake model is achieved by enforcing a minimum least-square-error in mean velocity in each cell. The wake model in the present implementation takes into account variations in wind farm inflow velocity and represents the wake profile behind each turbine as a super-Gaussian function that smoothly transitions between a top-hat shape in the region immediately following the turbine to a Gaussian profile downstream. Detailed comparisons to large-eddy simulation (LES) data from two different wind farms demonstrate the efficacy of the model in accurately predicting both wind farm power output and local turbine hub-height velocity for different wind farm geometries. These validations using data generated from two different LES codes demonstrate the model's versatility with respect to capturing results from different simulation setups and wind farm configurations.
Estimation of the permeability tensor is crucial for many natural and industrial porous media applications. Homogenization provides a rigorous framework to calculate effective parameters from pore-scale images of a representative unit cell of the porous medium by solving a boundary value problem, also known as closure problem, subject to global constraints. However, the latter are hard to satisfy for arbitrarily complex geometries. We have developed a novel computational algorithm to calculate rigorously the permeability tensor. The approach, here referred to as τ-SIMPLE, is based on introducing an artificial time scale τ to satisfy the global constraint within the SIMPLE iteration. Here, we show that the proposed algorithm has high accuracy for both two-dimensional and three-dimensional periodically arranged geometries.
Four major and accomplishments for the project "Electron/hole selectivity in organic semiconductor contacts for solar energy conversion.'' are reported. The first is a development of a model describing the contact-determined behavior of a solar cell. The most basic solar cell consists of an intrinsic (pure) semiconductor that acts as an absorber to which contacts are made that provide the asymmetry needed to create a driving force (voltage) for the directional flow of electrons (current), in other words, to convert sunlight into electrical energy. The asymmetry at the contacts comes from the different rate at which electrons and holes, the charge carriers generated by illumination, are collected. We developed a model that describes the ideal current-voltage, and hence energy converting properties, of an ideal photovoltaic that is entirely determined by the kinetics for these charge collection processes. Second, we measured how organic semiconductor interfacial layers impact contact electron and hole transfer rates at semiconductor interfaces and described how these concepts do or do not determine the open-circuit voltage of a solar cell. The work clearly controverts common general misconceptions about the action of contact interfacial layers, such as the idea that improved selectivity for one carrier over the other results from decreased recombination, and quantitatively demonstrates how specific interfacial layer materials act to improve the efficiency of a solar cell. Third, we measured the sub-band gap external quantum efficiency (EQE) of a series of organometal halide perovskite (“perovskite”) solar cells. These measurements quantified band-tailing and revealed defect states, which can cause recombination, that correlate with composition, performance, and hysteresis. Finally, we developed a semiconductor bipolar membrane that uses light to pump ions. This structure is unique among systems that drive ion gradients using light in that it is designed to pump salt rather than one sign of ion; it is a photochemical salt pump.
Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36–81 fb -1 of proton–proton collision data with a centre-of-mass energy of √s=13 TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti-k t jet algorithm with radius parameter R=0.4 is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets (|η|<1.2) vary from 1% for a wide range of high-p T jets (250 T <2000 GeV), to 5% at very low p T (20 GeV) and 3.5% at very high p T (>2.5 TeV). The relative jet energy resolution is measured and ranges from (24±1.5)% at 20 GeV to (6±0.5)% at 300 GeV.
This study presents a new method for modeling the interaction between compressible flow, shock waves, and deformable structures, emphasizing destructive dynamics. Extending advances in time-splitting compressible flow and the Material Point Methods (MPM), we develop a hybrid Eulerian and Lagrangian/Eulerian scheme for monolithic flow-structure interactions. We adopt the second-order WENO scheme to advance the continuity equation. To stably resolve deforming boundaries with sub-cell particles, we propose a blending treatment of reflective and passable boundary conditions inspired by the theory of porous media. The strongly coupled velocity-pressure system is discretized with a new mixed-order finite element formulation employing B-spline shape functions. Shock wave propagation, temperature/density-induced buoyancy effects, and topology changes in solids are unitedly captured.
The goal of this project was to advance the systems biology understanding and predictive modeling of synthetic & syntrophic Clostridium microbial consortia, focusing on elucidation of metabolic networks and environmental signals in the consortia. The project has direct applicability to lignocellulosic-biomass based production of higher alcohols as advanced biofuels and C6-C8 metabolites, that can be used as chemicals or serve as biofuel precursors. This project studied and optimized three synthetic syntrophic systems. It examined the population dynamics using flow-cytometry, time-lapse microscopy and PCR analysis. 13C-based tracer analyses was used to examine the metabolite exchange between the syntrophic cell populations and the impact of those interactions on the transcriptome of the individual populations. To enhance our analytical and predictive capabilities, genome-scale models (GSMs) for these syntrophies was developed. RNAseq data for these syntrophic coculture systems were acquired to enable a molecular level understanding of the syntrophies aiming to identify the genetic networks of each organism in the co-culture and compare those against the networks of pure cultures.
Electron emission and transport through and over potential barriers is an essential process requiring modeling and simulation to meet the design needs and characterization of an exceedingly broad range of technologically important devices and processes. The simulation and description of thermal, field, and photoemission, and the related concerns of space–charge affected electron flow, often make use of specialized formulations developed in the early days of quantum mechanics. Advancements in the utilization of electron sources and particularly the simulation of devices and applications using advanced particle-in-cell and trajectory methods for beam optics codes create a strong need for a pedagogical account of the emission models to ensure correct numerical evaluation of their equations. This Tutorial starts from simple phenomenological accounts and progressively builds to comprehensive models emphasizing straightforward and often rapid calculation. It recommends formulations to supplant the canonical Richardson–Laue–Dushman (thermal), Fowler–Nordheim (field), Fowler–DuBridge (photo), and Baroody (secondary) equations and provides a useful formulation of space–charge affected flow commonly described by the Child–Langmuir relation that takes into account cathode dependence on surface field.
This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A table in ('Deployment Schedule.PNG') outlines the various dates when each instrument was operational, and more details can be found via literature listed in 'Related Publications'.txt. This dataset includes zipped folders for each instrument containing data in .csv files for the relevant duration specific to each instrument, along with separate README file for each measurement. Some instrument files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. All data contained in this submission is unfiltered/unprocessed data unless otherwise noted in the README file. Blade strain was measured using 8 foil-based strain gauges along the span of a single turbine blade. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) both upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal flow with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Chancey 2019. The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. A single blade of this turbine was further modified to accommodate 8 full-bridge strain gauges (Bharath et al 2023, Bichanich et al 2024). For power performance and other relevant details on the turbine and its characteristics, see O'Byrne 2022.
The first-ever lithium-ion battery cycler capable of testing the coin and pouch cells under ultralow (≤40 °C) temperatures down to -175 °C to simulate extreme climates found in the lunar and space missions, high-altitude air vehicles, polar regions of Earth, and military expeditionary missions is enthusiastically reported. The extremely cold temperatures are achieved through a tailored extreme low-temperature system (ELTS) with liquid nitrogen flow and the ability to reach temperatures between -175 and 25 °C, using 1 kΩ and 1 MΩ resistors at varying currents of 1–4 mA and 1–4 μA, respectively, is validated. Employing the ELTS, Li 4 Ti 5 O 12 (LTO)||Li cells with 1 m lithium bis(fluorosulfonyl)imide in cyclopentyl methyl ether as an electrolyte developed in this research group are charged and discharged at room temperature (cycling rate C/5), -20 (C/10), -40 (C/40), and -60 °C (C/50), which exhibited discharge capacities of 159.04, 119.12, 101.79, and 33.06 mAh g -1 , respectively. Moreover, the LTO||Li cell produced a reversible capacity of 7.12 mAh g -1 tested at -100 °C for the first time.
Establishing an inexpensive and environmentally friendly scandium (Sc) supply is critical for the development of clean energy technologies. However, refining Sc from Sc-bearing sources using current technologies poses economic and environmental challenges due to its low concentration relative to base metals and chemically similar lanthanides. In this work, we developed a biosorption-based flow-through process for extraction of Sc from low-grade feedstocks. A novel biosorbent material was synthesized by encapsulating Arthrobacter nicotianae, a bacterium that selectively adsorbs Sc, within a porous silica matrix. Through the use of several complementary microscopy techniques, we demonstrated a highly porous biosorbent structure with a high cell-loading density and a homogenous cell distribution. Batch adsorption assays revealed selective Sc adsorption over lanthanides and common based metals, with the exception of Fe(III), as evidenced by separation factors greater than 50. The MESG particles were packed into fixed-bed columns to enable adsorption under flow-through conditions, which demonstrated effective Sc extraction at flow rates up to 0.08 cm/s and high stability for reuse; greater than 95% of the adsorption capacity was maintained after 10 consecutive adsorption/desorption cycles. When applied to a lignite coal leachate, whose Fe content was depleted through pH-mediated precipitation, the MESG particles yielded Sc breakthrough at 30 bed volumes, whereas all other metals broke through after only a few bed volumes. Following desorption, an eluate with a 124-fold increase in Sc purity was achieved relative to the lignite leachate with Sc constituting 96.4% of the total REEs. This study established a rapid, facile, and scalable cell immobilization approach that enables the use of microbial biomass for Sc recovery from low-grade sources.
Thermally activated batteries undergo a series of coupled physical changes during activation that influence battery performance. These processes include energetic material burning, heat transfer, electrolyte phase change, capillary-driven two-phase porous flow, ion transport, electrochemical reactions, and electrical transport. Several of these processes are strongly coupled and have a significant effect on battery performance, but others have minimal impact or may be suitably represented by reduced-order models. Additionally, assessing the relative importance of these phenomena must be based on comparisons to a high-fidelity model including all known processes. In this work, we first present and demonstrate a high-fidelity, multi-physics model of electrochemical performance. This novel multi-physics model enables predictions of how competing physical processes affect battery performance and provides unique insights into the difficult-to-measure processes that happen during battery activation. We introduce four categories of model fidelity that include different physical simplifications, assumptions, and reduced-order models to decouple or remove costly elements of the simulation. Using this approach, we show an order-of-magnitude reduction in computational cost while preserving all design-relevant quantities of interest within 5 percent. The validity of this approach and these model reductions is demonstrated by comparison between results from the full fidelity model and the different reduced models.
Highlights: • Adipose-derived stem cells modulate immune responses in a plastic manner. • The persistence of pro- and anti-inflammatory phenotypes was explored over time. • IL-6 was present at all time points; IDO1 was induced after cytokine stimulation. • Phenotypes persisted 96–168 h after returning to control conditions. • Macrophages showed reaction to ASC culture but without time effect. We determined the role of time in adipose-derived stem/stromal cell (ASC) response to a model inflammatory environment. ASCs and other mesenchymal stem/stromal cells exhibit immune plasticity. We evaluated the persistence of pro- and anti-inflammatory phenotypes for ASCs exposed to a sustained or pulse inflammatory stimulus. Using qPCR, flow cytometry, and immunocytochemistry, we monitored the temporal expression and up-regulation patterns of a pro-inflammatory gene (caspase 1), a pleiotropic gene/protein (interleukin 6, IL-6), and an anti-inflammatory gene/protein (indoleamine 2, 3-dioxygenase, IDO1) after exposing ASCs to the cytokines tumor necrosis factor-α and interferon-γ. In response to sustained cytokine stimulation, we discovered that time played a role in the balance of pro- and anti-inflammatory ASC phenotypes. IL-6 was present at all time points for both cytokine-stimulated and non-stimulated conditions, whereas IDO1 was heterogeneously up-regulated in stimulated conditions at later time points. After a pulse stimulus, ASC immunoresponse remained consistent for 96–168 h. As a final measure of immune plasticity, we cultured cytokine-stimulated ASCs with blood-derived macrophages to observe macrophage polarization. While the presence of ASCs altered macrophage phenotype, there was no dependency on the length of ASC cytokine exposure time.
Flowable carbon slurry electrodes promise continuous, scalable electrochemical desalination and energy storage when their rheology (flow and stability) and electronic connectivity are jointly optimized. This report integrates six complementary thrusts that we executed under the Laboratory Directed Research and Development (LDRD) project: (i) a fast, ex situ, centrifuge-compatible method to quantify pellet (packed slurry) electronic conductivity, with a validated cell constant (“shape factor”) and quantitative structure–property insights for carbon mixtures; (ii) a controlled circulation study showing that peristaltic pumping can irreversibly alter particle size and morphology over laboratory-relevant durations; (iii) development of a miniature jet pump that preserves particle integrity while achieving entrainment ratios of 2–4 at practical flow rates; (iv) a comprehensive mapping of how a representative non-ionic surfactant (Tween 20) collapses the carbon gel network, separating network-percolation losses from intrinsic particle contact resistance; (v) in-situ visualization revealing how gravitational settling and flow-driven mixing compete to control charge transport, with dynamic bed layers preventing saturation while achieving 30-fold local concentration enhancement; and (vi) a simple, widely adoptable fabrication route to structured, gas-nitrided titanium nitride (TiN) titanium current collectors that dramatically lower interfacial losses and enable geometry-driven performance gains. Together, these results provide a coherent toolchain and design rules to accelerate formulation screening, de-risk device prototyping, and standardize characterization for carbon slurry electrodes in flow-electrode capacitive deionization (FCDI), electrochemical flow capacitor (EFC), and related systems.
In recent years, research into the electrochemical reduction of CO 2 has grown exponentially. Formic acid (FA) has become a particular value product from CO 2 due to its versatility [1], optimal atom economy [2], and thermodynamic favorable [3]. FA can be produced electrochemically via a direct two-electron transfer process involving CO 2 with a proton source, requiring less energy input and fewer reaction steps than the conventional Kemira process. However, product selectivity, electrode stability, and low faradic efficiency due to increased resistance under constant current, remain key issues for CO 2 reduction to FA [4]. University of Kentucky’s Center for Applied Energy Research (UK CAER) is currently investigating reactor designs to address the challenges associated with electrochemical CO 2 conversion to FA [5]. The current reactor system employs: (1) an organic-based charge carrier which shuttles charge directly to the catalyst to enable CO 2 reduction to FA; (2) novel electrode materials to mitigate large voltages and improve conductivity; and (3) a flow system which not only allows for the volumetric scale-up of both charge carrier and catalyst, but also decouples the charger carrier re-energized and FA production processes to protect the catalyst’s stability due to overpotential. Through careful adjustment of electrode, charge carrier, and electrolyte selection, cell resistances have decreased by over 15%, facilitating conduction necessary for effective CO 2 reduction to FA. The system uses a highly specific engineered catalyst, which has produced over 100 mM FA at a rate of over 10 mM FA/hour following the aforementioned electrode/charge carrier changes. System design considerations (flow rate, bulk volume) and modeling of the system will also be discussed.
In this work, we present the Pele suite of software tools for compressible and incompressible reacting flows. The Pele suite leverages several different libraries, notably AMReX and SUNDIALS, to achieve performance portability on heterogeneous computing architectures across the supercomputing landscape. The Pele suite is comprised of PeleC, a compressible reacting flow block-structured adaptive mesh refinement solver, PeleLMeX, a low-Mach number reacting flow block-structured adaptive mesh refinement solver, Pele-Physics, a library for transport, thermodynamics, finite rate chemistry, soot, spray and radiation physics. The objective of this paper is (i) to present the code development efforts necessary to achieve highly effective and scalable applications for exascale machines and (ii) to detail the performance results of the Combustion-Pele project applications on Oak Ridge National Laboratory's Frontier. We show good weak and strong scaling results for both PeleC and PeleLMeX up to more than 50 billion cells on more than 4096 Frontier graphics processing unit nodes. We also present a capability demonstration simulation of a dual-fuel pulse compression ignition engine (six adaptive mesh refinement levels, and 60 billion cells or 2.1 trillion degrees of freedom) on Frontier, to date one of the largest simulations performed on the first exascale-class supercomputer.
Thermal radiation is a dominant mode of heat transfer in combustion/gasification, packed/circulating bed reactors, and energy storage/conversion devices. In hydrocarbon fuel combustion, the high absorption and emission of product gases like CO 2 and H 2 O significantly affect the heat transfer characteristics. It is essential to understand the radiative energy propagation in such applications. In the present study, we developed a framework to implement the P-1 radiation model in MFiX for Eulerian-Eulerian (Two fluid-TFM) and Eulerian-Lagrangian (Discrete element-DEM and Particle in cell-PIC) models. The P-1 is a simplification of the spherical harmonics method. The framework has been verified on various flue gas conditions. The verified solver results are validated against the benchmark results available in the literature. The verified and validated gray and non-gray weighted sum of gray gas models is evaluated for dry and wet flue gas conditions. Further, they are also used to study gas-solid flows in a fluidized bed/riser.