Model and Measurement Based Insights into Double Layer Capacitors: Voltage-Dependent Capacitance and Low Ionic Conductivity in Pores

Abstract

Electrochemical double layer capacitors (EDLCs) store electrical energy by accumulating ions near charged interfaces in porous electrodes. The available transport models for their characteristics often ignore the associated complexities: electrode-specific capacitance, its dependence on local potential difference and electrolyte concentration, and ionic conductivity in charged pores. As a result, modelling efforts are yet to be supported, supplemented, and validated with measurements. Detailed electrode specific measurements are reported in this work on discharge of porous carbon-H 2 SO 4 EDLCs. A substantially decreased charge recovery at high currents and subsequent prolonged potential recovery in open circuit mode are salient features. These are compared with predictions of a comprehensive transport model, which uses potential dependent electrode capacitances retrieved from measurements. The model, with no fitted parameters and Bruggeman correction for ionic conductivity in pores, fails to capture observed features, unless an order of magnitude decrease beyond Bruggeman correction is effected. The required decrease is larger at higher electrolyte concentrations and for electrode with double layer of larger size ions. The corrected model quantitatively explains the unusual features observed, in addition to matching measured cyclic-voltammograms with substantial chargeredistribution as the cause of lag between current and voltage.

Robust poly(p‐phenylene oxide) anion exchange membranes reinforced with pore‐filling technique for water electrolysis

“…The tortuosity factor can be obtained via the reciprocal of porosity, 1.5 in this case 34–36 . For the composite membrane, the composite membrane's anticipated conductivity compared with that of homogenous QPPO‐based AEM would be a factor of 0.1 (0.21 1.5 ), which can be obtained from the porosity to the power of tortuosity 33,37,38 …”

“…[34][35][36] For the composite membrane, the composite membrane's anticipated conductivity compared with that of homogenous QPPO-based AEM would be a factor of 0.1 (0.21 1.5 ), which can be obtained from the porosity to the power of tortuosity. 33,37,38 The pure PTFE is hydrophobic, while the PPO/PTFE composite membrane becomes hydrophilic due to the high hydrophobic property of PPO. As is shown in Figure 1, the fibers of PTFE are apparent and separated from each other.…”

Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons

“…This V g -induced change in C is similar to results observed in experiments using other electric double layers. 31,32 In detail, a positive gate voltage expels Ag + ions outside of the region beneath the gate electrode and results in an increase in the concentration of Ag in the channel region (x Ag,ch ) beneath the top electrode. These Ag + ions act as trapping sources in addition to VAPs, resulting in a reduction of the distance between hopping sites.…”

Topology optimization for the design of porous electrodes

“…Several researchers have proposed correction factors but there is still no consensus model (Koresh and Soffer, 1977;Thorat et al, 2009). In addition to the original Bruggeman correlation in (3), we thus consider a modification that results in lower effective ionic conductivity of the form κ = f κ η κ 0 , where f κ takes values in the range [0.02, 0.79] depending on the electrode material (Madabattula and Kumar, 2020). We penalize the electrode porosity N in (6) so we do not affect the conductivity in the pure electrolyte phase, i.e.…”

“…(3). The second set of examples uses the modified Bruggeman correlation in (8) with f p = 0.02 2/3 , which corresponds to the lowest factor in Madabattula and Kumar (2020). All our optimized designs start with an initial uniform γ = 0.5 everywhere in the domain.…”