Stereolithography 3D printing is today recognized as an effective rapid prototyping technique in the field of polymeric materials, which represents both the strengths and the weaknesses of this technique. The strengths relate to their easy handling and the low energy required for processing, which allow for the production of structures down to the sub-micrometric scale. The weaknesses are a result of the relatively poor mechanical properties. Unfortunately, the choice of the right material is not sufficient, as the printing parameters also play a crucial role. For this reason, it is important to deepen and clarify the effect of different printing conditions on final product characteristics. In this paper, the behavior of commercial Standard Blend (ST Blend) acrylic resin printed with stereolithography (SL) apparatus is reported, investigating the influence of printing parameters on both the tensile properties of the printed parts and the build accuracy. Twenty-four samples were printed under different printing conditions, then dimensional analyses and tensile tests were performed. It was possible to find out the optimum printing setup to obtain the best result in terms of mechanical resistance and printing accuracy for this kind of resin. Finally, a micrometric spring was printed under the optimal conditions to demonstrate the possibility of printing accurate and tiny parts with the commercial and inexpensive STBlend resin.

The present paper deals with the selective laser writing of textile yarns in order to induce a conductive path useful for smart textiles application. The incident power of the laser induces a conversion of an aramid fiber surface into graphene-based conductive material with tunable electrical properties depending on the laser writing parameters. The physical-chemical properties of the resulting smart yarns have been intensively characterized by electron microscopy, Raman spectroscopy, electrical and mechanical investigations. The results confirm the few-layer graphene fingerprint of the written paths onto the textile yarn with suitable properties for their application into electronic textiles. Indeed, a yarn-shape strain sensor with excellent performance has been developed and characterized to demonstrate the potential application of the proposed technology to the wearable electronic field.

Concerning environmental safety and mitigating the risk of water pollution, the electroplating industry, historically reliant on the use of elevated concentrations of heavy metals to achieve high-quality products, faces a crucial challenge in monitoring wastewater enriched with these metals, notorious for their adverse effects on ecosystems and human health. Chromium, in both oxidation states Cr (III) and Cr (VI), emerges as a prominently employed metal, yielding noteworthy outcomes throughout the galvanisation process. This research showcases the prototype of an automatic in situ sensor tailored to industry sustainability efforts to facilitate real-time monitoring and efficient water management. This custom sensor, characterized by sensitivity, reliability, and user-friendliness, utilizes UV-Vis colorimetric principle to detect Cr in both oxidation forms ranging from grams per litre (g/L) to parts per million (ppm). This is made possible by the unique vibrant colours induced by chromium ions, enabling the precise measurement of analyte concentrations. Thanks to 3D printing, this sensor system interacts with customized parts, designed and validated through simulation processes, for filtering out particulate that may interfere with the analysis. The outcome represents a synergistic blend of technology and environmental responsibility, aligning industrial processes with the goal of safeguarding water resources and ecosystems.

Underground fluid storage is gaining increasing attention as a means to balance energy production and consumption, ensure energy supply security, and contribute to greenhouse gas reduction in the atmosphere by CO₂ geological sequestration. However, underground fluid storage generates pressure changes, which in turn induce stress variations and rock deformations. Numerical geomechanical models are typically used to predict the response of a given storage to fluid injection and withdrawal, but validation is required for such a model to be considered reliable. This paper focuses on the technology and methodology that we developed to monitor seabed movements and verify the predictions of the impact caused by offshore underground fluid storage. To this end, we put together a measurement system, integrated into an Autonomous Underwater Vehicle, to periodically monitor the seabed bathymetry. Measurements repeated during and after storage activities can be compared with the outcome of numerical simulations and indirectly confirm the existence of safety conditions. To simulate the storage system response to fluid storage, we applied the Virtual Element Method. To illustrate and discuss our methodology, we present a possible application to a depleted gas reservoir in the Adriatic Sea, Italy, where several underground geological formations could be potentially converted into storage in the future.