Precise lifetime predictions for lithium‐ion cells are crucial for efficient battery development and thus enable profitable electric vehicles and a sustainable transformation towards zero‐emission mobility. However, limitations remain due to the complex degradation of lithium‐ion cells, strongly influenced by cell design as well as operating and storage conditions. To overcome them, a machine learning framework is developed based on symbolic regression via genetic programming. This evolutionary algorithm is capable of inferring physically interpretable models from cell aging data without requiring domain knowledge. This novel approach is compared against established approaches in case studies, which represent common tasks of lifetime prediction based on cycle and calendar aging data of 104 automotive lithium‐ion pouch‐cells. On average, predictive accuracy for extrapolations over storage time and energy throughput is increased by 38% and 13%, respectively. For predictions over other stress factors, error reductions of up to 77% are achieved. Furthermore, the evolutionary generated aging models meet requirements regarding applicability, generalizability, and interpretability. This highlights the potential of evolutionary algorithms to enhance cell aging predictions as well as insights.
Aim: To simplify and enhance safety in the generation of a stabilizing intracorneal scar by circular keratotomy (CKT). A femtosecond laser was used to perform individually sized intraparenchymal cuts. Materials and methods: As equipped, the Ziemer Z6 femto second laser cuts a 400µmdeep incision with a diameter of 7.0 mm around the optical axis. The epithelium, Bowmann's membrane, the internal borders of Descemet's membrane, and the endothelium are not affected. The 3, 6, and 12month postoperative values were com pared with the 1month postoperative keratometric readings and astigmatism. The preoperative best corrected visual acuity (BCVA) with glasses was compared with the values found at the same time points as noted above. Results: Statistical evaluation indicated that keratometry within ±1.5D remained in 96.6, 93.1, and 96.6% of cases at the 3, 6, and 12month time points respectively. Astigmatism was stable at the same time points in 100, 95.8, and 92.3%. The BCVA improved in 12 cases throughout the first post operative year (48%, n = 25); however, 11 cases did not change (44%) and 2 cases lost at least one line (8.0%). Conclusion: Femto CKT halts the progression of keratoconus for at least 1 year in 96.6% of cases. This treatment provides keratometric and refractive stability for over 1 year. This result, in conjunction with the significant improvement in BCVA, dem onstrates the potential of this method for patients with stage I and II keratoconus.
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