We report, for the first time, the detection and specific localization of long-chain acylcarnitines (LC ACs) along the lesion margins in an experimental model of spinal cord injury (SCI) using 3D mass spectrometry imaging (MSI). Acylcarnitines palmitoylcarnitine (AC(16:0)), palmitoleoylcarnitine (AC(16:1)), elaidic carnitine (AC(18:1)) and tetradecanoylcarnitine (AC(14:1)) were detected as early as 3 days post injury, and were present along the lesion margins 7 and 10 days after SCI induced by balloon compression technique in the rat. 3D MSI revealed the heterogeneous distribution of these lipids across the injured spinal cord, appearing well-defined at the lesion margins rostral to the lesion center, and becoming widespread and less confined to the margins at the region located caudally. The assigned acylcarnitines co-localize with resident microglia/macrophages detected along the lesion margins by immunofluorescence. Given the reported pro-inflammatory role of these acylcarnitines, their specific spatial localization along the lesion margin could hint at their potential pathophysiological roles in the progression of SCI.

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Micro milling is a flexible technique for the production of micro mechanical components like dies and moulds and process control is the key to reach the strong production requirements. Requirements, given by engineers and designers, are addressed mainly to the functional performance of the produced part, therfore topographic features are most decisive. Surface parameters, mainly of statistical origin, have been used for a long time in surface characterisation and process monitoring. Furthermore, it is known that these parameters correlate with the desired functional behaviour, but this knowledge is usually not used for a deterministic process design, uneconomic try and error approaches are still common.Mathematical investigations can use the full process flexibility for an in-process functionalization by selecting optimal conditions and process parameters with respect to a set of relevant surface parameters. In this study, micro ball-end milling is investigated and process parameters in order meet a predefined bearing ratio curve as accurately as possible are identified. Therefore, a mechanistic surface generation model has been developed and is used as a forward model for an iterative optimisation. Static and dynamic process geometry and a micro mechanical material removal operator are the main features of the model. In the first part of the paper the semi-empirical model is calibrated for certain tool and workpiece materials. In the second part optimal feed speed and width of cut are determined. Finally, an experimental validation is presented and the comparison of the predefined, the predicted and the experimental bearing ratio curves shows a good agreement.

In this paper we propose a new mathematical model for micro milling operations. To achieve the desired quality of the final product or the desired structure on the product's surface the process kinematics as well as tool-workpiece interaction are considered. The presented model takes into account the relative motion between tool and workpiece. We consider the input infeed rate which is reduced by the elastic deflection of the tool due to the cutting forces appearing during the process. The tool wear and surface texture depend on the cutting force; therefore the analysis of the forces plays an important role in characterizing the cutting process. Moreover, the analyzing these forces during the simulation we can calculate the effective cross-sectional area of the cut in each time step of the process. This gives us a forward model for the full production chain. This model is extended in order to include a surface generation model as well as quality parameters for the resulting micro-milling surface.

In this paper a model for a simulation based prediction of temperature induced shape deviations in dry milling is presented. A closed loop between Boolean material removal, process forces, heat flux and thermoelastic deformation is established. Therefore, an efficient dexel based machining simulation is extended by a contact zone analysis to model the local workpiece load. Based on the computed contact zone the cutting forces and heat flux are calculated using a semi-empirical process model. For a detailed consideration of the loads they are discretized and localized on the dexel-represented workpiece surface. A projection of the localized workpiece loads on the boundary of the finite element domain, taking into account the Boolean material removal during the process, allows the calculation of the current temperature and deformation of the workpiece. By transforming these thermomechanical characteristics back to the dexel-model a consideration in the machining simulation is possible. An extended contact zone analysis is developed for the prediction of the localized shape deviations. Finally, the results of the simulation are compared with measured data. The comparison shows that workpiece temperatures, workpiece deformation and shape deviations in different workpiece areas are predicted accurately.