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Organic and organometallic reactants in aqueous electrolytes, being composed of earth-abundant elements, are promising redox active candidates for cost-effective organic redox flow batteries (ORFBs). Various compounds of ferrocene and methyl viologen have been examined as promising redox actives for this application. Herein, we examined the influence of the electrolyte pH and the salt anion on model redox active organic cations, bis((3-trimethylammonio) propyl)- ferrocene dichloride (BTMAP-Fc) and bis(3-trimethylammonio) propyl viologen tetrachloride (BTMAP-Vi), which have exhibited excellent cycling stability and capacity retention at ≥1.00 M concentration [E. S. Beh, et al. ACS Energy Lett. 2, 639-644 (2017)]. We examined the solvation shell around BTMAP-Fc and BTMAP-Vi at acidic and neutral pH with SO42-, Cl-, and CH3SO3- counterions and elucidated their impact on cation diffusion coefficient, first electron transfer rate constant, and thereby the electrochemical Thiele modulus. The electrochemical Thiele modulus was found to be exponentially correlated with the solvent reorganizational energy (λ) in both neutral and acidic pH. Thus, λ is proposed as a universal descriptor and selection criteria for organic redox flow battery electrolyte compositions. In the specific case of the BTMAP-Fc/BTMAP-Vi ORFB, low pH electrolytes with methanesulfonate or chloride counterions were identified as offering the best balance of transport and kinetic requirements.
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Preclinical in vivo studies form the cornerstone of drug development and translation, bridging in vitro experiments with first-in-human trials. However, despite the utility of animal models, translation from the bench to bedside remains difficult, particularly for biologics and agents with unique mechanisms of action. The limitations of these animal models may advance agents that are ineffective in the clinic, or worse, screen out compounds that would be successful drugs. One reason for such failure is that animal models often allow clinically intolerable doses, which can undermine translation from otherwise promising efficacy studies. Other times, tolerability makes it challenging to identify the necessary dose range for clinical testing. With the ability to predict pharmacokinetic and pharmacodynamic responses, mechanistic simulations can help advance candidates from in vitro to in vivo and clinical studies. Here, we use basic insights into drug disposition to analyze the dosing of antibody drug conjugates (ADC) and checkpoint inhibitor dosing (PD-1 and PD-L1) in the clinic. The results demonstrate how simulations can identify the most promising clinical compounds rather than the most effective in vitro and preclinical in vivo agents. Likewise, the importance of quantifying absolute target expression and antibody internalization is critical to accurately scale dosing. These predictive models are capable of simulating clinical scenarios and providing results that can be validated and updated along the entire development pipeline starting in drug discovery. Combined with experimental approaches, simulations can guide the selection of compounds at early stages that are predicted to have the highest efficacy in the clinic.
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In biotechnology, immobilization of functional reactants is often done as a surface immobilization on small particles. Examples are chromatography columns and fixed-bed reactors. However, the available surface for immobilization is directly linked to particle diameter and bed porosity for these systems, leading to high backpressure for small particle sizes. When larger molecules, such as enzymes are immobilized, physical entrapment within porous materials like hydrogels is an alternative. An emerging technique for the production of geometrically structured, three-dimensional and scalable hollow bodies is 3D-printing. Different bioprinting methods are available to produce structures of the desired size, resolution and solids content. However, in case of entrapped enzymes mass transfer limitations often determine the achievable reactivities. With increasing complexity of the system, for example a fixed-bed reactor, 3D-simulation is indispensable to understand the local reaction conditions to be able to highlight the optimization potential. Based on experimental data, this manuscript shows the application of the dimensionless numbers effectiveness factor and Thiele modulus for the design of a 3D-printed flow-through reactor. Within the reactor, enzymes are physically entrapped in 3D-printed hydrogel lattices. The local reaction rate of the enzymes is directly dependent on the provided substrate amount at the site of reaction which is limited by the diffusion properties of the hydrogel matrix and the diffusion distance. All three parameters can be summed up by one key figure, the Thiele modulus, which, in short, quantifies mass transfer limitations of a catalytic system. Depending on the rate of the enzymatic reaction in correlation to the diffusional transport, mass transfer limitations will shift the optimum of the system, favoring slow enzyme kinetics and small diffusion distances. Comparison with the enzymatic reaction rate in solution yields the effectiveness factor of the system. As a result, the optimization potential of varying the 3D-printed geometries or the reaction rate within the experimentally available design space can be estimated.
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Carbon-based porous electrodes have led to remarkable improvements in the performance of thermochemical cells or thermocells that electrochemically harvest low-grade waste thermal energy. However, the output current from the thermocells is hampered by the diffusion effect, which leads to depleted ion concentration as the ions permeate through the porous electrode. Here, we advance a theoretical basis for a quantitative description of the diffusion effect on current generation in such porous electrodes. One single dimensionless parameter of Thiele modulus describes the effect according to the theory adopted from the well-established results in the literature. Experimental results for carbon fiber electrodes are illustrated and quantified by the theory. The theory presented here would provide a basis for the choice and design of porous electrodes for thermocells. The results should also provide a basis for devising electrochemical devices with highly porous electrodes.
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The combination of biological and electrochemical techniques enhances the bioremediation efficiency of treating oil-contaminated water. In this study a non-growing fungal whole cell biocatalyst (BC; Aspergillus brasiliensis attached to perlite) pretreated with an electric field (EF), was used to degrade a hydrocarbon blend (hexadecane-phenanthrene-pyrene; 100:1:1w/w) in an airlift bioreactor (ALB). During hydrocarbon degradation, all mass transfer resistances (internal and external) and sorption capacity were experimentally quantified. Internal mass transfer resistances were evaluated through BC effectiveness factor analysis as a function of the Thiele modulus (using first order reaction kinetics, assuming a spherical BC, five particle diameters). External (interfacial) mass transfer resistances were evaluated by kLa determination. EF pretreatment during BC production promoted surface changes in BC and production of an emulsifier protein in the ALB. The BC surface modifications enhanced the affinity for hydrocarbons, improving hydrocarbon uptake by direct contact. The resulting emulsion was associated with decreased internal and external mass transfer resistances. EF pretreatment effects can be summarized as: a combined uptake mechanism (direct contact dominant followed by emulsified form dominant) diminishing mass transfer limitations, resulting in a non-specific hydrocarbon degradation in blend. The pretreated BC is a good applicant for oil-contaminated water remediation.
Assuntos
Alcanos/metabolismo , Aspergillus/metabolismo , Biocatálise , Reatores Biológicos , Recuperação e Remediação Ambiental/instrumentação , Poluição por Petróleo , Fenantrenos/metabolismo , Pirenos/metabolismo , Poluentes Químicos da Água/metabolismo , Biodegradação Ambiental , Eletricidade , Emulsões , Proteínas Fúngicas/biossíntese , Cinética , TermodinâmicaRESUMO
The size of the gel preparation, the concentration of the encapsulated enzyme and the ratio of the preparation volume to the volume of the reaction mixture influence the reaction efficiency with encapsulated biocatalysts. A model of first order enzymatic reaction with substrate diffusion is presented and validated by the decomposition reaction of hydrogen peroxide by catalase. The Thiele modulus (Ф) contains the modified (including the enzyme concentration) enzymatic reaction constant (k'). Based on the model analysis, the Thiele modulus should not exceed a value of 2 (optimally less than 0.5). This value can be controlled by appropriate selection of the enzyme concentration inside and the size of the capsule. A lower Ф value gives a flat substrate concentration profile inside the gel capsule and all the enzyme molecules are involved in the reaction. The optimal diameter of the gel capsule with respect to their separation from the reaction mixture is 1-2 mm.
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Computational modeling of tissue-scale cardiac electrophysiology requires numerically converged solutions to avoid spurious artifacts. The steep gradients inherent to cardiac action potential propagation necessitate fine spatial scales and therefore a substantial computational burden. The use of high-order interpolation methods has previously been proposed for these simulations due to their theoretical convergence advantage. In this study, we compare the convergence behavior of linear Lagrange, cubic Hermite, and the newly proposed cubic Hermite-style serendipity interpolation methods for finite element simulations of the cardiac monodomain equation. The high-order methods reach converged solutions with fewer degrees of freedom and longer element edge lengths than traditional linear elements. Additionally, we propose a dimensionless number, the cell Thiele modulus, as a more useful metric for determining solution convergence than element size alone. Finally, we use the cell Thiele modulus to examine convergence criteria for obtaining clinically useful activation patterns for applications such as patient-specific modeling where the total activation time is known a priori.
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Several hundred papers are published yearly reporting liquid-phase adsorption kinetics data. In general the data is analyzed using a variety of standard models such as the pseudo first- and second-order models and the Intraparticle-Diffusion model. The validity of these models is often assessed empirically via their ability to fit the data, independently of their physicochemical soundness. The aim of the present paper is to rationalize the analysis of liquid-phase adsorption kinetics data, and to investigate experimental factors that influence the adsorption kinetics, in addition to the characteristics of the adsorbent material itself. For that purpose we use a simple Langmuir adsorption-diffusion model, which enables us to identify three dimensionless numbers that characterize the working regime of any batch adsorption experiment: an adsorption Thiele modulus, a saturation modulus, and a loading modulus. The standard models are found to be particular cases of the general adsorption-diffusion model for specific values of the dimensionless numbers. This provides sound physicochemical criteria for the validity of the models. Based on our modeling, we also propose a general yet simple data analysis procedure to practically estimate the diffusion coefficient in adsorbent pellets starting from adsorption half-times.
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The limited permeability of the E. coli outer membrane can significantly hinder whole-cell biocatalyst performance. In this study, the SARS coronavirus small envelope protein (SCVE) was expressed in E. coli cells previously engineered for periplasmic expression of carbonic anhydrase (CA) activity. This maneuver increased small molecule uptake by the cells, resulting in increased apparent CA activity of the biocatalysts. The enhancements in activity were quantified using methods developed for traditional heterogeneous catalysis. The expression of the SCVE protein was found to significantly reduce the Thiele moduli (Ï), as well as increase the effectiveness factors (η), effective diffusivities (De), and permeabilities (P) of the biocatalysts. These catalytic improvements translated into superior performance of the biocatalysts for the precipitation of calcium carbonate from solution which is an attractive strategy for long-term sequestration of captured carbon dioxide. Overall, these results demonstrate that synthetic biology approaches can be used to enhance heterogeneous catalysts incorporated into microbial whole-cell scaffolds.