Use of recycled linear low-density polyethylene carbon in Li-ion anodes
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Lithium-ion batteries are commonly used in many small electronics around the world. Efforts to make components of Li-ion batteries more sustainable have ranged from use of a brown algae extract in Li-ion anodes to efforts to recycle lithium. Linear-low density polyethylene (LLDPE) has been shown to exhibit the strong conductive properties required of a conductive agent in a Li-ion anode and can be made from recycled waste plastics such as cling wrap and poly-gloves. Electrodes were fabricated using polyethylene glycol (PEG) coated magnetite as the active material, PPBT polymeric binder, and LLDPE Carbon. Electrodes made with 14.3 wt.% LLDPE did not cycle well and exhibited a poor morphology with a cracked surface and large aggregates. Simple conductivity testing using a 4-point probe and profilometry measurements showed that Super-P was orders of magnitude more conductive than LLDPE. Increasing the carbon loading to 33.3 wt.% LLDPE in the electrode drastically improved rate capabilities and capacity retention. SEM analysis showed that a higher carbon loading of LLDPE had a better morphology overall and demonstrated less cracking. However, when compared to Super-P, the electrode had larger aggregates and a higher density of clumping. EDX SEM imaging and elemental (Fe, O, C) image mapping confirmed the presence of Fe3O4 nanoparticles, carbon additives, and PPBT binder. XPS analysis after 100 cycles confirmed the presence of an SEI layer in the LLDPE electrode. XPS on electrode slurries showed the presence of satellite peaks which confirm interactions between the polymeric binder and active material surface, regardless of carbon used. EIS testing provided information on the charge transfer resistances of Super-P and LLDPE which was consistent with the cycling trends. Overall, use of LLDPE in Li-ion batteries has been shown to work in a half-cell assembly. The performance of LLDPE does not beat the current industry standard, Super-P, but demonstrates promise for use after further optimization and analysis.