2017
DOI: 10.1002/anie.201610582
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Macromolecular Design Strategies for Preventing Active‐Material Crossover in Non‐Aqueous All‐Organic Redox‐Flow Batteries

Abstract: Intermittent energy sources, including solar and wind, require scalable, low‐cost, multi‐hour energy storage solutions in order to be effectively incorporated into the grid. All‐Organic non‐aqueous redox‐flow batteries offer a solution, but suffer from rapid capacity fade and low Coulombic efficiency due to the high permeability of redox‐active species across the battery's membrane. Here we show that active‐species crossover is arrested by scaling the membrane's pore size to molecular dimensions and in turn in… Show more

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Cited by 123 publications
(130 citation statements)
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References 29 publications
(14 reference statements)
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“…Identifying thinner or more conductive separators can alleviate ohmic resistances; recent literature on size selective separators for NAqRFBs is providing a pathway toward separators that are sufficiently conductive and selective. [54][55][56][57] Interestingly, the ohmic loss through the porous electrode is negligible compared to the ohmic loss through the separator. Mass transfer losses are the second largest impediment to flow cell performance and can be alleviated by increasing electrolyte flow rate, increasing active species concentration, or decreasing electrolyte viscosity.…”
Section: Discussionmentioning
confidence: 99%
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“…Identifying thinner or more conductive separators can alleviate ohmic resistances; recent literature on size selective separators for NAqRFBs is providing a pathway toward separators that are sufficiently conductive and selective. [54][55][56][57] Interestingly, the ohmic loss through the porous electrode is negligible compared to the ohmic loss through the separator. Mass transfer losses are the second largest impediment to flow cell performance and can be alleviated by increasing electrolyte flow rate, increasing active species concentration, or decreasing electrolyte viscosity.…”
Section: Discussionmentioning
confidence: 99%
“…Simultaneously tailoring active species radius and separator pore size offers a promising strategy to enabling NAqRFBs with sufficiently low ASR, high selectivity, and good mass transport. 54 Further, while RFBs typically exhibit improved safety over other battery types (e.g., lithium-ion, sodium-sulfur), 4 the safety associated with the implementation of nonaqueous solvents in RFBs must be investigated as the technology continues to advance. Ultimately, the performance depicted in Figure 10 sets a benchmark for the electrochemical performance of nonaqueous flow cells, however, numerous other criteria must be simultaneously met (i.e., cell potential, stable actives) to achieve economically viable battery designs.…”
Section: 76mentioning
confidence: 99%
“…From this realization emerged a different approach, first proposed in 2011, 62 of pairing SSS with larger active species where the separator allows smaller supporting ions to exchange between the two electrolyte streams while blocking crossover of the larger active species. [59][60][61][62][63][67][68][69] Since SSS are comprised of non-functionalized polymers, they promise higher conductivities and lower costs as compared to their functionalized IEM counterparts. However, to date, SSS have only been reported in a small number of literature studies, 60,62,63,[68][69][70][71] limiting the amount of available experimental data.…”
Section: Estimating Materials Parametersmentioning
confidence: 99%
“…[59][60][61][62][63][67][68][69] Since SSS are comprised of non-functionalized polymers, they promise higher conductivities and lower costs as compared to their functionalized IEM counterparts. However, to date, SSS have only been reported in a small number of literature studies, 60,62,63,[68][69][70][71] limiting the amount of available experimental data. As such, we estimate their effective conductivities (κ eff , mS cm −1 ) using the Bruggeman relation (Equation 1), where κ is the electrolyte conductivity (mS cm −1 ) in the pore phase of the SSS, ε is the SSS porosity (-), and b is the Bruggeman coefficient (b = 1.5).…”
Section: Estimating Materials Parametersmentioning
confidence: 99%
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