Transport equations in an enzymatic glucose fuel cell

Jariwala, Soham; Krishnamurthy, Balaji

doi:10.1016/j.cplett.2017.11.055

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…Theoretical, numerical and experimental methods for estimating the biofuel cell performance was discussed by various authors. In [51], the authors modelled the effects of convective flux and temperature on the performance of an enzymatic glucose fuel cell based on flow design. The cell employs a cation exchange membrane and glucose oxidase enzyme at the anode.…”

Section: Non-microfluidic Configurationsmentioning

confidence: 99%

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Enzymatic Biofuel Cells: A Review on Flow Designs

et al. 2021

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Because of environmental concerns, there is a growing interest in new ways to produce green energy. Among the several studied applications, enzymatic biofuel cells can be considered as a promising solution to generate electricity from biological catalytic reactions. Indeed, enzymes show very good results as biocatalysts thanks to their excellent intrinsic properties, such as specificity toward substrate, high catalytic activity with low overvoltage for substrate conversion, mild operating conditions like ambient temperature and near-neutral pH. Furthermore, enzymes present low cost, renewability and biodegradability. The wide range of applications moves from miniaturized portable electronic equipment and sensors to integrated lab-on-chip power supplies, advanced in vivo diagnostic medical devices to wearable devices. Nevertheless, enzymatic biofuel cells show great concerns in terms of long-term stability and high power output nowadays, highlighting that this particular technology is still at early stage of development. The main aim of this review concerns the performance assessment of enzymatic biofuel cells based on flow designs, considered to be of great interest for powering biosensors and wearable devices. Different enzymatic flow cell designs are presented and analyzed highlighting the achieved performances in terms of power output and long-term stability and emphasizing new promising fabrication methods both for electrodes and cells.

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Section: Non-microfluidic Configurationsmentioning

confidence: 99%

“…Schematic representation of the glucose enzymatic fuel cell used for the model reported in[51]. Reprinted from[51], with permission from Elsevier.…”

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confidence: 99%

Enzymatic Biofuel Cells: A Review on Flow Designs

et al. 2021

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“…The diffusion of reactant in the pellet porous space can be considered as a process activated by temperature in some important industrial applications. For example, Wang et al have taken into account the temperature dependence of the diffusivities of gaseous solutes, CO, H 2 , and CO 2 , in the liquid solvent, n ‐C 28 H 58 , for modeling of the Fischer‐Tropsch synthesis over Fe‐Cu‐K catalyst; Ávila et al considered the temperature dependence of configurational diffusion inside zeolite channels in the catalytic cracking of hydrocarbons; Jariwala and Krishnamurthy introduced the temperature dependence of diffusivity of glucose in a fuel cell . The temperature dependence of diffusivity is usually assumed to obey the Eyring equation:

D (T) = D^{*} \cdot exp (- \frac{E_{D}}{R_{g} \cdot T}),

where

D^{*}

is the preexponential factor for diffusion, E D is the activation energy for diffusion, R g is the gas constant, and T is the temperature.…”

Section: Introductionmentioning

confidence: 99%

The formation of dead zones in nonisothermal porous catalyst with temperature‐dependent diffusion coefficient

Андреев

Skrzypacz

Golman

2019

Int J of Chemical Kinetics

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This paper considers the formation of dead zones in the porous catalyst pellets due to the chemical reaction and diffusion. We established and investigated the model with nonisothermal reaction of fractional order and activated temperature‐dependent diffusivity. The effects of process parameters, catalyst shape, and reaction and diffusion parameters on the formation of the dead zone are studied numerically and characterized by the critical Thiele modulus. The lower bounds for the critical Thiele modulus are derived analytically in terms of process parameters for exothermic and endothermic reactions and verified numerically. The critical Thiele modulus increases with increasing Arrhenius number for diffusion and decreasing Arrhenius number for reaction in the case of exothermic reactions, whereas the opposite trends hold for the endothermic reactions. The critical Thiele modulus also increases with increasing fractional reaction order as well as with decreasing energy generation function, and increasing Biot numbers for heat and mass transfer. Moreover, the critical Thiele modulus is the highest for spherical pellets and the lowest for pellets with planar shape.

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