A thermally regenerative ammonia-based battery for efficient harvesting of low-grade thermal energy as electrical power

Fang Zhang, Jia Liu, Wulin Yang, Bruce E. Logan

Research output: Contribution to journalArticlepeer-review

185 Scopus citations


© 2015 The Royal Society of Chemistry. Thermal energy was shown to be efficiently converted into electrical power in a thermally regenerative ammonia-based battery (TRAB) using copper-based redox couples [Cu(NH3)4 2+/Cu and Cu(ii)/Cu]. Ammonia addition to the anolyte (2 M ammonia in a copper-nitrate electrolyte) of a single TRAB cell produced a maximum power density of 115 ± 1 W m-2 (based on projected area of a single copper mesh electrode), with an energy density of 453 W h m-3 (normalized to the total electrolyte volume, under maximum power production conditions). Adding a second cell doubled both the voltage and maximum power. Increasing the anolyte ammonia concentration to 3 M further improved the maximum power density to 136 ± 3 W m-2. Volatilization of ammonia from the spent anolyte by heating (simulating distillation), and re-addition of this ammonia to the spent catholyte chamber with subsequent operation of this chamber as the anode (to regenerate copper on the other electrode), produced a maximum power density of 60 ± 3 W m-2, with an average discharge energy efficiency of ∼29% (electrical energy captured versus chemical energy in the starting solutions). Power was restored to 126 ± 5 W m-2 through acid addition to the regenerated catholyte to decrease pH and dissolve Cu(OH)2 precipitates, suggesting that an inexpensive acid or a waste acid could be used to improve performance. These results demonstrated that TRABs using ammonia-based electrolytes and inexpensive copper electrodes can provide a practical method for efficient conversion of low-grade thermal energy into electricity.
Original languageEnglish (US)
Pages (from-to)343-349
Number of pages7
JournalEnergy Environ. Sci.
Issue number1
StatePublished - 2015
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-I1-003-13
Acknowledgements: The authors thank David Jones for help with the analytical measurements. We also thank Nicole LaBarge for the HYSYS simulation, Dr Marta Hatzell, Dr Mike Hickner and Dr Christopher Gorski for useful discussions. This research was supported by Award KUS-I1-003-13 from the King Abdullah University of Science and Technology (KAUST).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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