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In this study, laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) was applied to previously aged carbonaceous anodes from lithium ion batteries (LIBs). The electrodes were treated by cyclic aging in a lithium ion cell set-up with LiNi 0.5 Mn 1,5 O 4 (LNMO) cathodes and hard carbon (HC)/mesocarbon microbead (MCMB) anodes. An inhomogeneous transition metal deposition pattern could be induced by replacing the spacer in a standard coin cell set-up with a washer. The inhomogeneity pattern matched the dimension of the washer depicted by the hole in the center. These transition metal (TM) patterns were used to optimize higher lateral scanning speeds and frequencies on the spatial resolution of the mapping experiments using LA-ICP-MS. Higher scanning speeds had an observable influence on the resolution of the obtained image and an overall saving of 60% with regard to time and gas consumption could be achieved. Additionally, the optimized method was applied to the cathode and separator in order to visualize the distribution and deposition pattern, respectively.

The optimal design and operation of dynamic bioprocesses gives in practice often rise to optimisation problems with multiple and conflicting objectives. As a result typically not a single optimal solution but a set of Pareto optimal solutions exist. From this set of Pareto optimal solutions, one has to be chosen by the decision maker. Hence, efficient approaches are required for a fast and accurate generation of the Pareto set such that the decision maker can easily and systematically evaluate optimal alternatives. In the current paper the multi-objective optimisation of several dynamic bioprocess examples is performed using the freely available ACADO Multi-Objective Toolkit ( http://www.acadotoolkit.org ). This toolkit integrates efficient multiple objective scalarisation strategies (e.g., Normal Boundary Intersection and (Enhanced) Normalised Normal Constraint) with fast deterministic approaches for dynamic optimisation (e.g., single and multiple shooting). It has been found that the toolkit is able to efficiently and accurately produce the Pareto sets for all bioprocess examples. The resulting Pareto sets are added as supplementary material to this paper.