Energy breakdown in capacitive deionization

Ali Hemmatifar

doi:10.1016/j.watres.2016.08.020

2016-11-01

124

DOI：10.1016/j.watres.2016.08.020

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We explored the energy loss mechanisms in capacitive deionization (CDI). We hypothesize that resistive and parasitic losses are two main sources of energy losses. We measured contribution from each loss mechanism in water desalination with constant current (CC) charge/discharge cycling. Resistive energy loss is expected to dominate in high current charging cases, as it increases approximately linearly with current for fixed charge transfer (resistive power loss scales as square of current and charging time scales as inverse of current). On the other hand, parasitic loss is dominant in low current cases, as the electrodes spend more time at higher voltages. We built a CDI cell with five electrode pairs and standard flow between architecture. We performed a series of experiments with various cycling currents and cut-off voltages (voltage at which current is reversed) and studied these energy losses. To this end, we measured series resistance of the cell (contact resistances, resistance of wires, and resistance of solution in spacers) during charging and discharging from voltage response of a small amplitude AC current signal added to the underlying cycling current. We performed a separate set of experiments to quantify parasitic (or leakage) current of the cell versus cell voltage. We then used these data to estimate parasitic losses under the assumption that leakage current is primarily voltage (and not current) dependent. Our results confirmed that resistive and parasitic losses respectively dominate in the limit of high and low currents. We also measured salt adsorption and report energy-normalized adsorbed salt (ENAS, energy loss per ion removed) and average salt adsorption rate (ASAR). We show a clear tradeoff between ASAR and ENAS and show that balancing these losses leads to optimal energy efficiency. (C) 2016 Elsevier Ltd. All rights reserved.

Keyword:

Capacitive deionization

Water desalination

Energy consumption

Porous carbon electrodes

Performance optimization