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Mohr, Fabian

Publications and source records attributed to Mohr, Fabian.

Synthesis, characterization, and recycling of bio-derivable polyester covalently adaptable networks for industrial composite applications

Fiber-reinforced polymers (FRPs) are critical for energy-relevant applications such as wind turbine blades. Despite this, the end-of-life options for FRPs are limited as they are permanently cross-linked thermosets. To enable the circularity of FRPs, we formulated a bio-derivable polyester covalently adaptable network (PECAN), sometimes referred to as a polyester vitrimer, to manufacture FRPs at >1 kg scale, which is accomplished as the resin is infusible (175-425 cP at 25 °C viscosity), can be cured at 80 °C within 5 h and is depolymerizable via methanolysis yielding high-quality fibers and recoverable hardener. The FRPs exhibit a transverse tensile modulus comparable with today's wind relevant FRPs (10.4-11.9 GPa). Modeling estimates a resin minimum selling price of $2.28/kg and, relative to an epoxy-amine resin, PECAN manufacture requires 19%-21% less supply chain energy and emits 33%-35% less greenhouse gas emissions. Overall, this study suggests that redesigned thermosets can yield beneficial circularity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian learning for rapid prediction of lithium-ion battery-cycling protocols

Advancing lithium-ion battery technology requires the optimization of cycling protocols. A new data-driven methodology is demonstrated for rapid, accurate prediction of the cycle life obtained by new cycling protocols using a single test lasting only 3 cycles, enabling rapid exploration of cycling protocol design spaces with orders of magnitude reduction in testing time. We achieve this by combining lifetime early prediction with a hierarchical Bayesian model (HBM) to rapidly predict performance distributions without the need for extensive repetitive testing. The methodology is applied to a comprehensive dataset of lithium-iron-phosphate/graphite comprising 29 different fast-charging protocols. HBM alone provides high protocol-lifetime prediction performance, with 6.5% of overall test average percent error, after cycling only one battery to failure. Here, by combining HBM with a battery lifetime prediction model, we achieve a test error of 8.8% using a single 3-cycle test. In addition, the generalizability of the HBM approach is demonstrated for lithium-manganese-cobalt-oxide/graphite cells.

25 ENERGY STORAGE↗