Environmental and Economic Impact of an Innovative Biocide-Free Antifouling Coating for Naval Applications.

The work provides an economic sustainability and environmental impact analysis for the validation of a biocide-free antifouling coating for marine applications able to reduce fuel consumption during navigation, CO emissions, and the overall environmental impacts associated with shipping, thanks to the reduction of incrustation and the avoidance of biocides release into the water. The results, related to the life cycle of the coating of a motor yacht, with an average sailing life of 25 years, show around 8.8% reduction in overall costs compared to a conventional paint, thanks to a more efficient antifouling action, which reduces the annual fuel consumption by ~13,700 kg/y, or ~9.

Additive Manufacturing for Neurosurgery: Digital Light Processing of Individualized Patient-Specific Cerebral Aneurysms.

This study aims at demonstrating the feasibility of reproducing individualized patient-specific three-dimensional models of cerebral aneurysms by using the direct light processing (DLP) 3D printing technique in a low-time and inexpensive way. Such models were used to help neurosurgeons understand the anatomy of the aneurysms together with the surrounding vessels and their relationships, providing, therefore, a tangible supporting tool with which to train and plan surgical operations. The starting 3D models were obtained by processing the computed tomography angiographies and the digital subtraction angiographies of three patients.

Soft Computing Techniques for Laser-Induced Surface Wettability Control.

Making decisions and deducing control actions in manufacturing environments requires considering many uncertainties. The ability of fuzzy logic to incorporate imperfect information into a decision model has made it suitable for the optimization of both productivity and final quality. In laser surface texturing for wettability control, in fact, these aspects are governed by a complex interaction of many process parameters, ranging from those connected with the laser source to those concerning the properties of the processed material.

Combined Fuzzy and Genetic Algorithm for the Optimisation of Hybrid Composite-Polymer Joints Obtained by Two-Step Laser Joining Process.

In the present work, genetic algorithms and fuzzy logic were combined to model and optimise the shear strength of hybrid composite-polymer joints obtained by two step laser joining process. The first step of the process consists of a surface treatment (cleaning) of the carbon fibre-reinforced polymer (CFRP) laminate, by way of a 30 W nanosecond laser. This phase allows removing the first matrix layer from the CFRP and was performed under fixed process parameters condition.