Concentration Distribution Of Species Research Articles

Mercury cycling in contaminated coastal environments: modeling the benthic-pelagic coupling and microbial resistance in the Venice Lagoon

Anthropogenic activities have been releasing mercury for centuries, and despite global efforts to control emissions, concentrations in environmental media remain high. Coastal sediments can be a long-term repository for mercury, but also a secondary source, and competing processes in marine ecosystems can lead to the conversion of mercury into the toxic and bioaccumulative species methylmercury, which threatens ecosystem and human health. We investigate the fate and transport of three mercury species in a coastal lagoon affected by historical pollution using a novel high-resolution finite element model that integrates mercury biogeochemistry, sediment dynamics and hydrodynamics. The model resolves mercury dynamics in the seawater and the seabed taking into account partitioning, transport driven by water and sediment, and photochemical and microbial transformations. We simulated three years (early 2000s, 2019, and 2020) to assess the spatio-temporal distribution of mercury species concentrations and performed a sensitivity analysis to account for uncertainties. The modeled mercury species concentrations show high temporal and spatial variability, with water concentrations in some areas of the lagoon exceeding those of the open Mediterranean Sea by two orders of magnitude, consistent with available observations from the early 2000s. The results support conclusions about the importance of different processes in shaping the environmental gradients of mercury species. Due to the past accumulation of mercury in the lagoon sediments, inorganic mercury in the water is closely related to the resuspension of contaminated sediments, which is significantly reduced by the presence of benthic vegetation. The gradients of methylmercury depend on the combination of several factors, of which sediment resuspension and mercury methylation are the most relevant. The results add insights into mercury dynamics at coastal sites characterized by a combination of past pollution (i.e. sediment enrichment) and erosive processes, and suggest possible nature-based mitigation strategies such as the preservation of the integrity of benthic vegetation and morphology.

Detailed kinetics modeling of sulfur species evolution in alternating reducing/oxidizing atmosphere

Under conditions of deep load fluctuation, the furnace of a coal-fired boiler experiences alternating reduction/oxidation atmospheres, which directly impact the evolution of sulfur species. Building upon our previous mechanism (Model I), this study specifically considered the influence of alternating atmospheres and proposed a comprehensive reaction model (Model II), incorporating 8 additional elementary reactions. The relative error in predicting the concentration distribution of sulfur species was reduced from 18% (Model I) to 13% (Model II). In the alternating atmospheres, the predominant sulfur species remained as SO2 and H2S. Sensitivity analysis revealed that S, SH, SO, HSO, and HOSO were the critical free radicals. The new supplementary reactions (118) H2S + M = SH + H + M and (116) H2S + O2=HSO + OH played a significant role in the generation and consumption of H2S and SO2. Rate of production analysis demonstrated that the alternating atmosphere impacted the production and consumption primary free radicals like O/H/OH, thus potentially causing changes of S, SH, SO, HSO, and HOSO; moreover, it introduced new reaction pathways for SH and SO. Finally, a simplified reaction pathway for the sulfur species evolution was proposed. This study seeks to provide insights into the sulfur species evolution under the peak regulation conditions in coal-fired boilers.

CSTNet: A Dual-Branch Convolutional Neural Network for Imaging of Reactive Flows Using Chemical Species Tomography.

Chemical species tomography (CST) has been widely used for in situ imaging of critical parameters, e.g., species concentration and temperature, in reactive flows. However, even with state-of-the-art computational algorithms, the method is limited due to the inherently ill-posed and rank-deficient tomographic data inversion and by high computational cost. These issues hinder its application for real-time flow diagnosis. To address them, we present here a novel convolutional neural network, namely CSTNet, for high-fidelity, rapid, and simultaneous imaging of species concentration and temperature using CST. CSTNet introduces a shared feature extractor that incorporates the CST measurements and sensor layout into the learning network. In addition, a dual-branch decoder with internal crosstalk, which automatically learns the naturally correlated distributions of species concentration and temperature, is proposed for image reconstructions. The proposed CSTNet is validated both with simulated datasets and with measured data from real flames in experiments using an industry-oriented sensor. Superior performance is found relative to previous approaches in terms of reconstruction accuracy and robustness to measurement noise. This is the first time, to the best of our knowledge, that a deep learning-based method for CST has been experimentally validated for simultaneous imaging of multiple critical parameters in reactive flows using a low-complexity optical sensor with a severely limited number of laser beams.

A Spatially Progressive Neural Network for Locally/Globally Prioritized TDLAS Tomography

Tunable diode laser absorption spectroscopy tomography (TDLAST) has been widely applied for imaging two-dimensional distributions of industrial flow-field parameters, e.g., temperature and species concentration. Two main interested imaging objectives in TDLAST are the local combustion and its radiation in the entire sensing region. State-of-the-art algorithms were developed to retrieve either of the two objectives. In this paper, we address the both by developing a novel multi-output imaging neural network, named as Spatially Progressive Neural Network (SpaProNet). This network consists of locally and globally prioritized reconstruction stages. The former enables hierarchical imaging of the finely resolved and highly accurate local combustion, but coarsely resolved background. The later retrieves a fine-resolved image for the entire sensing region, at the cost of slightly trading off the reconstruction accuracy in the combustion zone. Furthermore, the proposed network is driven by the hydrodynamics of the real reactive flows, in which the training dataset is obtained from large eddy simulation. The proposed SpaProNet is validated by both simulation and lab-scale experiment. In all test cases, the visual and quantitative metric comparisons show that the proposed SpaProNet outperforms the existing methods from the following two perspectives: a) the locally prioritized stage provides ever-better accuracy in the combustion zone; b) the globally prioritized stage shows turbulence-indicative accuracy in the entire sensing region for diagnosis of heat radiation from the flame and flame-air interactions.

Structural and solution speciation studies on selected [Cu(NN)(OO)] complexes and an investigation of their biomimetic activity, ROS generation and their cytotoxicity in normoxic, hypoxic and anoxic environments in MCF-7 breast cancer-derived cells

Reactive oxygen species(ROS) generation with subsequent DNA damage is one of the principle mechanisms of action assigned to copper-based anticancer complexes. The efficacy of this type of chemotherapeutic may be reduced in the low oxygen environment of tumours. In this study the cytotoxicity of three complexes, [Cu(dips)(phen)] (1), [Cu(ph)(phen)]·2H2O (2) and [Cu(ph)(bpy)]·H2O (3) (disp: 3,5-diisopropylsalicylate, phen: 1,10- phenanthroline, ph: phthalate, bpy: 2,2′-bipyridyl) were assessed for anticancer activity in the breast-cancer derived MCF-7 line under normoxic, hypoxic and anoxic conditions. In an immortalised keratinocyte HaCaT cell line, the cytotoxicity of complexes 2 and 3 was significantly reduced under both normoxic and hypoxic conditions, whilst the cytotoxicity of complex 1 was increased under hypoxic conditions. The ability of the complexes to generate ROS in the MCF-7 cell line was evaluated as was their ability to act as superoxide dismutase(SOD) and catalase mimics using a yeast cell assay. ROS generation was significant for complexes 2 and 3, less so for complex 1 though all three complexes had SOD mimetic ability. Given the ternary nature of the complexes, solution speciation studies were undertaken but were only successful for complex 3, due to solubility issues with the other two complexes. The concentration distribution of various species, formed in aqueous solution, was evaluated as a function of pH and confirmed that complex 3 is the dominant species at physiological pH in the mM concentration range. However, as its concentration diminishes, it experiences a progressive dissociation, leading to the formation of binary complexes of bpy alongside unbound phthalate.

A numerical study on the effects of using combined flow fields and obstacles on the performance of proton exchange membrane fuel cells

AbstractThe flow field structure has an important influence on the comprehensive performance of the proton exchange membrane fuel cell (PEMFC). This research investigates the effects of combined flow fields on the distribution of species concentration, the pressure drop, and the overall performance of PEMFC based on the polarization curve and power consumption ratio (PCR). Obstacles are arranged in different areas to study the mass transfer of the gas inside the combined flow field. The results show that the combined serpentine flow field improves the concentration distribution of species and the performance of the cell is enhanced with the increase of the proportion of the single‐channel serpentine structure in the combined flow field, but the PCR is decreased. The energy efficiency conversion in the low voltage region is better when the obstacles are arranged in the entire flow field. Moreover, the vortex effect generated by the obstacles enhances the convection ability under the rib parallel to the inlet direction, while the transverse vortex and secondary flow perpendicular to the inlet direction are weakened by the flow field structure so that the mass transfer of gas is enhanced.

Pore-scale study of calcite dissolution during CO2-saturated brine injection for sequestration in carbonate aquifers

The calcite reaction with carbonate acid is a prerequisite to release cations providing the reactant for mineral trapping, however, the complicated multiple physicochemical processes during calcite dissolution are hardly precisely captured in carbonate aquifers, impeding the CO2 sequestration technology. In this work, a pore-scale numerical study based on the lattice Boltzmann method coupled fluid flow, mass transport, heterogeneous reactions, and calcite structure evolution is implemented to investigate the calcite dissolution process. Firstly, the impact of pressure difference on this reaction is analyzed to identify two characteristic dissolution patterns. Selecting two typical pressure differences, namely 0.036 and 0.36 Pa, the dissolution dynamics under different temperatures from 25 to 85 °C is then investigated by species concentration and solid distributions elucidating that the effect of pressure difference on calcite dissolution will drop with the increment of temperature. Moreover, the regime diagram of calcite dissolution is plotted based on the relation between temperature and pressure. Finally, to upscale the simulation results to the representative element volume scale, the temporal evolution of normalized permeability, the normalized permeability-porosity relationship and the optimal operations are explored to find that the maximum discrepancy of the normalized permeability with the time among all cases is approximately seven times and the best operating conditions promoting the mineral trapping are a high-temperature formation with a high injection rate.

Concentration Distribution of Molecules and Other Species in the Model System Fe–NaCl–Na2S–H2SO4–H2O at Various Temperatures of the Electrocoagulation Process

Concentration Distribution of Molecules and Other Species in the Model System Fe–NaCl–Na2S–H2SO4–H2O at Various Temperatures of the Electrocoagulation Process

A Turbulent Mass Diffusivity Model for Predicting Species Concentration Distribution in the Biodegradation of Phenol Wastewater in an Airlift Reactor

In this study, a three-dimensional CFD transient model is established for predicting species concentration distribution in the biodegradation of phenol in an airlift reactor (ALR). The gas–liquid flow in the ALR is determined by the Euler–Euler method coupled with the standard k-ε model, and the bubble size is predicted by the population balance model (PBM). A turbulent mass diffusivity model is developed to simulate the turbulent mass transfer process and to predict the species concentration distribution. No empirical methods are needed as the turbulent mass diffusivity can be expressed by the concentration variance c2¯ and its dissipation rate εc. A good agreement is found between simulated and experimental results in the literature. It is not reasonable to assume a constant turbulent Schmidt number because the calculated distribution of turbulent mass diffusivity is not identical to that of turbulent viscosity. Finally, the hydrodynamic characteristics and biodegradation performance of the proposed model in a novel ALR are compared with that in the original ALR.

Analytical and experimental study on binary droplet evaporation: Inhibitory effect of adding mineral oil adjuvant to water

This work fundamentally explains the inhibitory effect of adjuvant on water droplet evaporation in pesticide application. An analytical droplet evaporation model coupled with the instantaneous distribution of temperature and species concentrations in the vapor film boundary layer accompanying with the droplet diameter decrease is developed to describe not only the droplet evaporation but also the surrounding boundary layer evolution process. Thermal and concentration boundary layer thicknesses as well as the property variations at the liquid-vapor interface are updated at each time step during the calculation. An adjuvant factor is defined to assess the inhibitory effect of the adjuvant on water droplet evaporation. The results show that adding a tiny amount of mineral oil adjuvant can inhibit water droplet evaporation. The analysis of droplet evaporation evolution demonstrates that the inhibitory effect is mainly controlled by mass diffusion where the concentration gradient surrounding the liquid-vapor interface dominates the overall phase change. A regression formula is introduced to express the dependence of droplet lifetime on temperature and humidity. The proposed model is proved to be suitable for the mixing condition with a tiny amount of adjuvant, which can be used to describe the mechanism of evaporation inhibition of pesticide adjuvant in plant protection.

Polyvinyl alcohol–potassium iodide gel probe to monitor the distribution of reactive species generation around atmospheric-pressure plasma jet

This study proposes polyvinyl alcohol–potassium iodide (PVA–KI) as a novel gel chemical probe. The probe uses the reactions among PVA, KI, water, borax, and oxidative species to visualize the distribution of reactive species. This method provides information regarding the distribution of reactive species by coloration on the gel surface. The effects of the surrounding gas phase on the distribution and diffusion of the reactive species are also investigated using the PVA–KI gel probe. Further, the relationship between the irradiation distance and reactive species diffusion is determined on the surface of the PVA–KI probe with and without plastic shielding. Adjusting the irradiation distance appropriately leads to an increase in the modified area as detected by the PVA–KI gel probe analysis. The relative concentration distributions of the reactive species are also obtained from visualized color distributions measured using a colorimeter. Furthermore, reactive species generation by long-scale line plasma is confirmed by the color reaction on the PVA–KI gel surface, with a greater area being covered by an atmospheric-pressure pulsed microwave line plasma source.

The electrostatic effect and its role in promoting electrocatalytic reactions by specifically adsorbed anions.

The adsorption of anions and its impact on electrocatalytic reactions are fundamental topics in electrocatalysis. Previous studies revealed that adsorbed anions display an overall poisoning effect in most cases. However, for a few reactions such as the hydrogen evolution reaction (HER), oxidation of small organic molecules (SOMs), and reduction of CO2 and O2, some specifically adsorbed anions can promote their reaction kinetics under certain conditions. The promotion effect is frequently attributed to the adsorbate induced modification of the nature of the active sites, the change of the adsorption configuration and free energy of the key reactive intermediate which consequently change the activation energy, the pre-exponential factor of the rate determining step etc. In this paper, we will give a mini review of the indispensable role of the classical double layer effect in enhancing the kinetics of electrocatalytic reactions by anion adsorption. The ubiquitous electrostatic interactions change both the potential distribution and the concentration distribution of ionic species across the electric double layer (EDL), which alters the electrochemical driving force and effective concentration of the reactants. The contribution to the overall kinetics is highlighted by taking HER, oxidation of SOMs, reduction of CO2 and O2, as examples.

Modelling a Turbulent Non-Premixed Combustion in a Full-Scale Rotary Cement Kiln Using reactingFoam

No alternatives are currently available to operate industrial furnaces, except for hydrocarbon fuels. Plant managers, therefore, face at least two challenges. First, environmental legislation demands emission reduction. Second, changes in the origin of the fuel might cause unforeseen changes in the heat release. This paper develops the hypothesis for the detailed control of the combustion process using computational fluid dynamic models. A full-scale mock-up of a rotary cement kiln is selected as a case study. The kiln is fired by the non-premixed combustion of Dutch natural gas. The gas is injected at Mach 0.6 via a multi-nozzle burner located at the outlet of an axially mounted fuel pipe. The preheated combustion air is fed in (co-flow) through a rectangular inlet situated above the attachment of the fuel pipe. The multi-jet nozzle burner enhances the entrainment of the air in the fuel jet. A diffusion flame is formed by thin reaction zones where the fuel and oxidizer meet. The heat formed is transported through the freeboard, mainly via radiation in a participating medium. This turbulent combustion process is modeled using unsteady Favre-averaged compressible Navier–Stokes equations. The standard k-ϵ equations and standard wall functions close the turbulent flow description. The eddy dissipation concept model is used to describe the combustion process. Here, only the presence of methane in the composition of the fuel is accounted for. Furthermore, the single-step reaction mechanism is chosen. The heat released radiates throughout the freeboard space. This process is described using a P1-radiation model with a constant thermal absorption coefficient. The flow, combustion, and radiative heat transfer are solved numerically using the OpenFoam simulation software. The equations for flow, combustion, and radiant heat transfer are discretized on a mesh locally refined near the burner outlet and solved numerically using the OpenFoam simulation software. The main results are as follows. The meticulously crafted mesh combined with the outlet condition that avoids pressure reflections cause the solver to converge in a stable manner. Predictions for velocity, pressure, temperature, and species distribution are now closer to manufacturing conditions. Computed temperate and species values are key to deducing the flame length and shape. The radiative heat flux to the wall peaks at the tip of the flame. This should allow us to measure the flame length indirectly from exterior wall temperature values. The amount of thermal nitric oxide formed in the flame is quantified. The main implication of this study is that the numerical model developed in this paper reveals valuable information on the combustion process in the kiln that otherwise would not be available. This information can be used to increase fuel efficiency, reduce spurious peak temperatures, and reduce pollutant emissions. The impact of the unsteady nature of the flow on the chemical species concentration and temperature distribution is illustrated in an accompanying video.

Coupling a neural network technique with CFD simulations for predicting 2-D atmospheric dispersion analyzing wind and composition effects

The Computational Fluid Dynamics (CFD) tool has a remarkable applicability for the prediction of gas dispersion flows by numerically solving the proper governing equations in realistic scenarios. Depending on the problem complexity, undesirably high computational costs can be incurred, which has encouraged the combined use of Machine Learning (ML) seeking to attenuate the CFD simulations requirement for multiple scenario studies. The present work aims at demonstrating the employment the coupling between CFD and the Artificial Neural Network (ANN) algorithm for representative problems in atmospheric dispersion in a preliminary assessment. A limited set of CFD simulation results was used for training neural networks, whose output is given by flow field interpolators, the potential uses of which include digital twin designing and optimization procedures. One possible strategy is the local approach, which treats the network as a transition rule in the scope of Cellular Automata (CA) modeling, allowing it to learn the dynamic behavior of the addressed physics locally. This method gives rise to simpler neural network architectures with closer computing relatively to the CFD calculation. Assessments have been done by predicting, initially, a scalar field time evolution governed by a 1-D advection-diffusion transport equation to verify the method implementation. Subsequently, species concentration distributions were sought in atmospheric dispersion cases from CFD simulations datasets, comprising four case studies followed in the performed analysis, all considering a bidimensional flow domain and a scenario involving methane leaks. The first one indicated an accurate reproduction of subsequent time steps concentration field referring to the displacement of a methane cloud. The second and third cases concerned a plume formation, in transient and steady-state regimes, respectively; their main outcome was the evidence of the CA-ANN methodology's flexibility to address time-dependent and permanent flow simulations interpolation. The last CFD-based case study comprised an additional complexity feature of gas dispersion problems: the wind influence. By redesigning the investigated data-driven approach in terms of ANN's features and labels choice, promising results followed from the analysis with respect to the simultaneous capturing of two global simulation parameters (wind and leakage speeds boundary conditions) in the species concentration field interpolation.

In English

The goal of this study is unraveling the specific features of non-stationary surface concentration distribution of electroactive and inactive species in a model electrochemical process with a preceding homogeneous first-order chemical reaction (CE mechanism). For this purpose, the exact analytical expressions for the non-stationary concentration distributions of electroactive and inactive species in the thin layer attached to a planar electrode are analyzed. The both cases of equal and unequal diffusion coefficients of species taking part in the preceding chemical reaction are considered. In the former case, the exact analytical expressions for the concentration distributions of electroactive and inactive species on a planar electrode are obtained. The peculiarities of the limiting cases of zero and infinite frequency of an applied alternating current for the both cases of equal and unequal diffusion coefficients of species are discussed. It is shown that there is a phase shift between AC and the surface concentration of species that changes under the action of this current. At low frequencies, the phase angle tends to p/2, whereas at high frequencies it decreases to p/4. The phase angle is the function of the two important measures, namely, the ratio of the Nernst diffusion layer thickness to the oscillation diffusion layer thickness, and the ratio of the Nernst diffusion layer thickness to the reaction layer one. It is shown that the phase angle depends on the diffusion coefficient of species in different manner for low and high values of the rate constants of the chemical reaction. At low values of these parameters, the phase angle shifts slightly to the range of high frequencies with an increase of diffusion coefficient. At the high rate constants, the phase angle decreases with frequency more slowly, and its dependence on diffusion coefficient is observed only at middle frequencies. The surface concentration of electroactive and inactive species decreases with an increase of frequency, but for the inactive species this process is faster than that for the electroactive species. The influence of the inactive species on the surface concentration of electroactive species decreases at high frequencies and at low rate constants of the preceding chemical reaction. The results obtained shed the light on complex dynamics at an electrode/electrolyte interface under non-stationary conditions.

Effect of Rib Width and Cathode Thickness on the Performance of MOLB-Type SOFC

AbstractIn this study, a typical three-dimensional model of single channel mono-block-layer build solid oxide fuel cell (MOLB-type SOFC) was developed. The effects of rib width and cathode thickness on the species concentration distribution, electrochemical performance, and temperature distribution of MOLB-type SOFC were investigated. The results show that adapting a smaller rib width can improve the uniformity of gas distribution, decrease the concentration polarization, and improve the output performance of SOFC. The performance of the cell can be significantly improved by thickening the cathode electrode. When the cathode thickness is 0.45 mm, the maximum output power density is improved by 53.69% compared with that at 0.15 mm. With the increase of the cathode thickness, the enhancement of the cell performance by increasing the cathode thickness gradually decreases. In addition, as the cathode thickness increases, the concentration polarization and temperature gradient of the cell gradually rise, while the activation polarization gradually decreases.

Numerical calculation of temperature, velocity, and species concentration distributions in a hot filament chemical vapor deposition in a reactor using a CH4/H2 mixture

This study is a numerical modeling of transport phenomena occurring in the reaction chamber during diamond or amorphous hydrogenated carbon films growth by a hot filament chemical vapor deposition (HFCVD) technique. A two-dimensional model was adopted to study the HFCVD reactor. The equations of heat, momentum, and mass transfer were solved numerically; the simulation was performed using a program in FORTRAN language. All temperature, velocity, and species concentration distributions were similar at the filaments and they were also similar between the filaments. The results show that the gas temperature increases when the number of filaments increases from three to four filaments. We also noted an increase in the production of CH3 and C2H5 radicals near the surface; there was also an increase in the growth rate of the thin film. The concentrations of C2H6, C2H4, and C2H5 were very high. Temperature and concentrations were affected by the distance between filaments and the distance filaments-substrates.

Operando characterization of heterogeneously catalyzed gas- and multi-phase reactions using nuclear magnetic resonance imaging

Nuclear magnetic resonance imaging (MRI), a series of techniques exploiting the phenomenon of nuclear magnetic resonance (NMR), is a powerful toolkit for operando investigations of catalytic reactions. For instance, in a single experiment MRI can be used to generate two or three-dimensional images of species concentration, gas and liquid distribution, local temperatures, and gas or liquid flow. Performing such operando measurements of catalytic reactions allows to better understand how catalytic activity depends on the surface of the catalyst as well as on the surrounding reaction conditions. In combination with multi-scale models, this helps to understand and improve reaction processes.In this perspective article, we discuss recent operando studies of gas and multi-phase reactions using MRI. We further list current challenges and discuss possible future directions of the field.

Large eddy simulation of hydrodynamics and deNOx process in a coal-fired power plant SCR system

This paper presents a CFD modeling of deNOx process in a coal-fired power plant selective catalytic reduction (SCR) system, with focus on the transient hydrodynamics of multi-species flow and the influence of vortex on the deNOx process. For this purpose, a comprehensive CFD model is established, parameter study and model validation are performed, and the hydrodynamics, vortex evolution and species concentration distribution are numerically investigated. Simulation results indicate that many vortices with various scale/intensity/shape exist in the SCR system, causing apparent pressure pulsations and velocity fluctuations. High-intensity eddies are mainly distributed in the deflector group Ι, the NH3 nozzles, the static mixer, and the right part of the rectifying grille. The number of eddies decreases significantly with reducing the unit loads. Affected by vortex evolution, the NH3 concentration fluctuates in the SCR system, especially in the vertical flue. The deNOx process completes within 6 s, and the ammonia slip is less than 1.0 ppm, which well meets the requirement of industrial standards. In addition, the static mixer severely destroys the velocity uniformity but favors the mixing of NH3 and NOx. The rectifying grille improves the uniformity of flow field and species concentration field significantly.

Neutron Radiography As a Powerful Method to Visualize Reactive Flows in Redox Flow Batteries

Spatial and temporal gradients in reactant concentration, influenced by local microstructure and surface properties, govern the performance and durability of various advanced electrochemical systems. The cell and stack performance is typically assessed using traditional electrochemical diagnostics (e.g. polarization curves, electrochemical impedance spectroscopy) and the influence of materials is macroscopically evaluated based on empirical comparison of novel materials with the current state-of-the-art. While this is a valid approach to identify promising candidates, valuable information is lost due to the difficulty of identifying performance-limiting factors. Operando imaging of electrochemical systems, in tandem with complementary electrochemical diagnostics, has been instrumental in the development of advanced polymer electrolyte fuel cells1,2 and, more recently, lithium-ion batteries3,4. Over the past few years, several groups have developed novel imaging and spectroscopic techniques for operando characterization of redox flow batteries, which is the focus of this work. Wong et al. employed fluorescence microscopy and particle velocimetry to image concentration and velocity distributions near the electrode-flow field interface5. Tanaka et al. visualized flow distribution in redox flow batteries with infrared thermography6. Zhao et al. employed in-situ nuclear magnetic resonance to track reaction mechanisms occurring within the electrolyte7. Finally, several groups recently employed X-ray tomographic microscopy to visualize gas pockets within the liquid electrolyte imbibed porous electrode8–10. While these methods have provided important insights, an approach that enables quantitative mapping of species concentrations, in a non-invasive fashion and within an operating cell, has remained elusive.In this presentation, I will discuss our recent efforts to develop neutron radiography as an operando characterization method for non-aqueous redox flow batteries. We leverage the high attenuation of organic materials (i.e., high hydrogen content) in solution and, combined with isotopic labelling, we perform subtractive neutron imaging to quantify the concentration of active species and supporting electrolytes. To demonstrate the potential of this diagnostic tool, we characterize active species concentration distribution within a redox flow cell in a single electrolyte configuration with a non-aqueous electrolyte containing a TEMPO/TEMPO+ redox couple and study the influence of electrode microstructure, membrane type (e.g. porous or dense), and flow field design. To resolve the concentration profiles across the different layers, we employ the in-plane imaging configuration11 and correlate these concentration profiles to cell performance via polarization measurements under different operating conditions. In the final part of the talk, I will discuss our latest experimental campaign in which we investigated the use of energy-selective neutron radiography to deconvolute concentrations of active species and supporting electrodes during operation. References 1 P. Boillat, E. H. Lehmann, P. Trtik and M. Cochet, Curr. Opin. Electrochem., , DOI:https://doi.org/10.1016/j.coelec.2017.07.012.2 J. Eller, T. Rosén, F. Marone, M. Stampanoni, A. Wokaun and F. N. Büchi, J. Electrochem. Soc., 2011, 158, B963.3 B. Michalak, H. Sommer, D. Mannes, A. Kaestner, T. Brezesinski and J. Janek, Sci. Rep., 2015, 5, 15627.4 D. P. Finegan, M. Scheel, J. B. Robinson, B. Tjaden, I. Hunt, T. J. Mason, J. Millichamp, M. Di Michiel, G. J. Offer, G. Hinds, D. J. L. Brett and P. R. Shearing, Nat. Commun., 2015, 6, 6924.5 A. A. Wong, M. J. Aziz and S. Rubinstein, ECS Trans. , 2017, 77, 153–161.6 H. Tanaka, Y. Miyafuji, J. Fukushima, T. Tayama, T. Sugita, M. Takezawa and T. Muta, J. Energy Storage, 2018, 19, 67–72.7 E. W. Zhao, T. Liu, E. Jónsson, J. Lee, I. Temprano, R. B. Jethwa, A. Wang, H. Smith, J. Carretero-González, Q. Song and C. P. Grey, Nature, 2020, 579, 224–228.8 R. Jervis, L. D. Brown, T. P. Neville, J. Millichamp, D. P. Finegan, T. M. M. Heenan, D. J. L. Brett and P. R. Shearing, J. Phys. D. Appl. Phys., , DOI:10.1088/0022-3727/49/43/434002.9 F. Tariq, J. Rubio-Garcia, V. Yufit, A. Bertei, B. K. Chakrabarti, A. Kucernak and N. Brandon, Sustain. Energy Fuels, 2018, 2, 2068–2080.10 K. Köble, L. Eifert, N. Bevilacqua, K. F. Fahy, A. Bazylak and R. Zeis, J. Power Sources, , DOI:10.1016/j.jpowsour.2021.229660.11 P. Boillat, D. Kramer, B. C. Seyfang, G. Frei, E. Lehmann, G. G. Scherer, A. Wokaun, Y. Ichikawa, Y. Tasaki and K. Shinohara, Electrochem. commun., 2008, 10, 546–550.