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Bibliographic Details
Main Authors: Yao, Adrian, Benson, Sally M., Chueh, William C.
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2403.13759
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author Yao, Adrian
Benson, Sally M.
Chueh, William C.
author_facet Yao, Adrian
Benson, Sally M.
Chueh, William C.
contents Sodium-ion batteries have garnered significant attention as a potentially low-cost alternative to lithium-ion batteries, which have experienced supply shortages and pricing volatility of key minerals. Here we assess their techno-economic competitiveness against incumbent lithium-ion batteries using a modeling framework incorporating componential learning curves constrained by minerals prices and engineering design floors. We compare projected sodium-ion and lithium-ion price trends across over 6,000 scenarios while varying Na-ion technology development roadmaps, supply chain scenarios, market penetration, and learning rates. Assuming substantial progress can be made along technology roadmaps via targeted R&D, we identify many sodium-ion pathways that might reach cost-competitiveness with low-cost lithium-ion variants in the early 2030s. Additionally, we show timelines are highly sensitive to movements in critical minerals supply chains -- namely that of lithium, graphite, and nickel. Modeled outcomes suggest increasing sodium-ion energy densities to decrease materials intensity to be among the most impactful ways to improve competitiveness.
format Preprint
id arxiv_https___arxiv_org_abs_2403_13759
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle How quickly can sodium-ion learn? Assessing scenarios for techno-economic competitiveness against lithium-ion batteries
Yao, Adrian
Benson, Sally M.
Chueh, William C.
Chemical Physics
Materials Science
Sodium-ion batteries have garnered significant attention as a potentially low-cost alternative to lithium-ion batteries, which have experienced supply shortages and pricing volatility of key minerals. Here we assess their techno-economic competitiveness against incumbent lithium-ion batteries using a modeling framework incorporating componential learning curves constrained by minerals prices and engineering design floors. We compare projected sodium-ion and lithium-ion price trends across over 6,000 scenarios while varying Na-ion technology development roadmaps, supply chain scenarios, market penetration, and learning rates. Assuming substantial progress can be made along technology roadmaps via targeted R&D, we identify many sodium-ion pathways that might reach cost-competitiveness with low-cost lithium-ion variants in the early 2030s. Additionally, we show timelines are highly sensitive to movements in critical minerals supply chains -- namely that of lithium, graphite, and nickel. Modeled outcomes suggest increasing sodium-ion energy densities to decrease materials intensity to be among the most impactful ways to improve competitiveness.
title How quickly can sodium-ion learn? Assessing scenarios for techno-economic competitiveness against lithium-ion batteries
topic Chemical Physics
Materials Science
url https://arxiv.org/abs/2403.13759