Pith. sign in

REVIEW 1 cited by

A Brief Review of Current Lithium Ion Battery Technology and Potential Solid State Battery Technologies

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1803.04317 v1 pith:JCTLEZHG submitted 2018-03-12 physics.app-ph cond-mat.mtrl-sci

classification physics.app-phcond-mat.mtrl-sci
keywords statesolidbatterycurrentbatterieslibslithiumanode
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Solid state battery technology has recently garnered considerable interest from companies including Toyota, BMW, Dyson, and others. The primary driver behind the commercialization of solid state batteries (SSBs) is to enable the use of lithium metal as the anode, as opposed to the currently used carbon anode, which would result in ~20% energy density improvement. However, no reported solid state battery to date meets all of the performance metrics of state of the art liquid electrolyte lithium ion batteries (LIBs) and indeed several solid state electrolyte (SSE) technologies may never reach parity with current LIBs. We begin with a review of state of the art LIBs, including their current performance characteristics, commercial trends in cost, and future possibilities. We then discuss current SSB research by focusing on three classes of solid state electrolytes: Sulfides, Polymers, and Oxides. We discuss recent and ongoing commercialization attempts in the SSB field. Finally, we conclude with our perspective and timeline for the future of commercial batteries.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Learning Aerodynamics for the Control of Flying Humanoid Robots

    cs.RO 2025-05 conditional novelty 6.0 of 10

    Aerodynamic forces on a jet-powered humanoid robot are measured, simulated, learned by neural network and linear models, and used in a controller that stabilizes the robot under wind in simulation and ground tests.

Pith tools