Upscaling Salinity Gradient CRED Cell for Blue Energy Harvesting
Authors: Fins Carreira Adérito , Wu Nan , Man Zhiyi , Colin Annie , Levant Michael 
Published: December 2024

CRED (Capacitive reverse electrodialysis) cells are a hybrid technology that were originally introduced by David A. Vermaas to extract electrical energy from salinity gradient [1]. They use selective IME (ion membranes exchange) just like RED (Reverse Electrodialysis) systems but borrow long-lasting, non-faradaic and inexpensive capacitive electrodes from Capmix (Capacitive Mixing) systems achieving power densities around 0.9 W/m² of IME - 5 times higher than Capmix systems [2] but 2 times lower than RED systems [3].

Since then, we reviewed this CRED cell in the MIE lab in order to simplify and optimize it. The current system designed by Youcef BRAHMI [4] only uses one IME and carbon felts as capacitive electrodes (Figure 1). The whole cell is equivalent to an ideal generator Ecell, an internal resistance Rcell and an internal capacitor C in series (Figure 2b). Due to the charge of the internal capacitor, the cell must be used in an alternative regime by switching the concentrated and diluted solutions of sodium chloride over a half-period T (Figure 2a). The uptake of these 3D electrodes increases drastically the capacitance allowing us to achieve around 2.3 W/m² by stabilizing the potential (Middle of Figure 5); which can even reach 3.3 W/m² by choosing an appropriate half-period and reducing the internal resistance by employing thinner membranes and higher concentrations (Figure 2e) [5]. Yet, this still represents about 2/3 of the maximum theoretical power obtained for a square potential generator like in RED systems. The maximal power is obtained for loading resistances Rload slightly higher than Rcell (Figure 2d).

Very recently, Nan Wu proposed a very surprising technique to recover around 90% of the theoretical power density [5]. She used an additional power supply in phase with the fluid switching (Figure 3). For a given half-period, using this boosting technique ads 60% of the power compared to the non-boosting functioning after retrieving the power contribution of the external source (Figure 4). The boosting acts formally like an additional resistance that increases the characteristic time of the RC circuit stabilizing the whole cell potential at its highest value. It also allows to work with higher external resistances (up to 10 times).

Currently, our techno-economic analysis estimates that our cell can produce energy at a cost of 200 €/MWh in the best conditions [6]. Given the decrease of the cost of the IME, these systems could become quite soon a profitable renewable energy. This motivates us in building a cell capable of producing 50 W. For that, we will upscale our CRED cell. The first approach is to increase the surface of a single membrane. We will focus on the effect of the extension of the length - along the flow - and the width – perpendicular to it. The extension of the length highlights the problem of the filling time that has to be as short as possible in order to reach the maximal potential as quick as possible and approach a square signal while not spending too much energy fighting viscous dissipations. Extending the length also amplifies the non-ideal selectivity of the membrane requiring an adjustment of the relative volume flows of the saline solutions. Preliminary results showed that during a switch, the potential of the cell is mostly given by the Donnan potential and its spatial mean considering a plug flow (Figure 5). Regarding the width, the mechanism is different. As the system displays an invariance regarding the flow, the main goal is to improve the transmission line along the current collectors that sets a limit width due to the linear resistance of the collectors. Increasing the surface of one membrane helps reducing the total inner resistance of the cell resulting in a higher current. We will then associate in series the CRED cells to obtain cumulative potential and power while preserving power density on small cells (Figure 6) [7].

[1] D. A. Vermaas et al., Energy & Environmental Science, 2013

[2] F. Liu et al., Energy & Environmental Science, 2012

[3] D. A. Vermaas et al., Environmental Science & Technology, 2011

[4] Y. Brahmi et al., Energy Conversion and Management, 2022

[5] N. Wu et al., Environmental Science & Technology, 2023

[6] N. Wu et al., Scientific Reports, 2024 (Under Review)

[7] Z. MAN, PhD Student, 2023 - Now

Figure 1