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Opportunities for Disruptive Advances through Engineering for Next Generation Energy Storage

Authors: Gregory James Offer; Martina De Marco; Teddy Szemberg O'Connor;

Opportunities for Disruptive Advances through Engineering for Next Generation Energy Storage

Abstract

{"references": ["http://www.canvas.instructure.com/courses/949415.", "G. Crabtree, E. K\u00f3cs and L. Trahey, \"The energy-storage frontier: Lithium-ion batteries and beyond,\" MRS Bulletin, vol. 40, no. 12, pp. 1067-1078, 2015.", "B. Nykvist and M. Nilsson, \"Rapidly falling costs of battery packs for electric vehicles.,\" Nature Climate Change, vol. 5, no. April, pp. 100-103, 2015.", "S. Bourderau, T. Brousse and D. M. Schleich, \"Amorphous silicon as a possible anode material for Li-ion batteries,\" Journal of Power Sources, Vols. 81-82, pp. 223-236, 1999.", "G. J. Kramer and M. Haigh, \"No quick switch to low-carbon energy.,\" Nature, vol. 462, no. 7273, pp. 568-569, 2009.", "R. Van Noorden, \"The rechargeable revolution: A better battery,\" Nature, vol. 507, no. 7490, pp. 26-28, 2014.", "S. J. Harris, D. J. Harris and C. Li, \"Failure statistics for commercial lithium ion batteries: A study of 24 pouch cells,\" Journal of Power Sources, pp. 589-597, 2017.", "I. A. Hunt, Y. Zhao, Y. Patel and G. J. Offer, \"Surface Cooling Causes Accelerated Degradation Compared to Tab Cooling for Lithium-Ion Pouch Cells,\" Journal of The Electrochemical Society, vol. 163, no. 9, pp. A1846-A1852, 2016.", "Y. Zhao, L. Bravo Diaz, Y. Patel, T. Zhang and G. J. Offer, \"How to Cool Lithium Ion Batteries: Optimising Cell Design using a Thermally Coupled Model,\" Journal of The Electrochemical Society, vol. 166, no. 13, pp. A2849-A2859, 2019.", "J. Harlow, X. Ma, J. Li, E. Logan, Y. Liu, N. Zhang, L. Ma, S. L. Glazier, M. M. E. Cormier, M. Genovese, S. Buteau, A. Cameron, J. E. Stark and J. R. Dahn, \"A Wide Range of Testing Results on an Excellent Lithium-Ion CellChemistry to be used as Benchmarks for New Battery Technologies,\" Journal of The Electrochemical Society, vol. 166, no. 13, pp. A3031-A3044, 2019."]}

Throughout human history, major economic disruption has been due to technological breakthroughs. Since 1990 the energy density of lithium-ion cells has increased by a factor of four and the cost has dropped by a factor of 10. This has caused disruption to the energy industry, but advances are slowing. The manufacturing and supply chain complexity means that the next big technology will take 15 years to dominate. The academic literature charts this process of development and can be used to show what is in the pipeline. Three candidates that have had a large increase in publication count are: lithium sulphur, solid-state, and sodium-ion technology. From the level of investments in start-ups and academic publication counts, solid‑state cells are closest to maturity. To identify disruption potential, look at uncertainty in performance. Cell lifetime in lithium-ion cells indicates room for improvement. Define a new disruption metric: . Look for areas of industry that lower this metric. Thermal management is a lucrative area for improvement. Cooling the cell tabs of a 5Ah cell reduces the lifetime cost by 66%, compared to 8%/pa for 13 years relying on cost reduction. Second life applications lower the lifetime cost by using the remaining 75% of energy throughput available in a cell after use in an electric vehicle. Drop-in changes to standard manufacturing processes enable huge disruption. Electrolyte additives can increase cell life by 10 times, lowering lifetime cost by 90% in a simple manufacturing intervention.

Country
United Kingdom
Keywords

energy storage, battery, 600, disruption, 620

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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