Domenico Mundo

PEEK is a thermoplastic polymer widely employed in the orthopedic field for the fabrication of prosthetic devices, owing to its Young’s modulus being comparable to that of cortical human bone. Surface functionalization through biomaterial micropatterning represents an effective strategy to enhance osteointegration. To this end, an innovative vibration-assisted surface embossing process was applied to PEEK samples. The surface patterning was performed using a square punch with a side length of 0.5 [mm], fabricated via CNC milling. The process is enabled by a linear actuator capable of generating controlled vibrations to induce localized sub-Tg heating of the polymer surface. After that, the application of a post-load is required for the embossing stage. This system allows frequency tuning in the range of 1–4 [kHz]. Finally, the patterned surfaces were sonicated through an ultrasound cleaner and characterized through contact angle measurements and white-light interferometry, confirming the feasibility of the process and demonstrating an increase in both the polar component of the surface free energy and the hydrophilicity compared with merely polished specimens. Enhancing the polar component of surface free energy is an effective strategy to improve biomaterial biocompatibility, confirming the relevance of the proposed surface modifications. Slightly hydrophilic surfaces promote preferential osteoblast adhesion and stable cytoskeletal organization, demonstrating the complementary roles of surface topography in shaping cellular responses.

Continuous fiber-reinforced polymers (CFRPs) offer high strength-to-weight ratios, which makes them an attractive choice for applications in transportation, biomedical devices, and sports equipment. Additive manufacturing presents new opportunities for producing CFRPs with improved geometric freedom and digital fabrication flexibility. However, achieving adequate fiber impregnation and strong interfacial bonding remains a major challenge. This paper presents a novel rotating impregnation die, patented by some of the authors, designed to produce fiber-reinforced polymer filaments at a die speed of 15 rad/s. These filaments, characterized by a final diameter of 0.65 mm and a fiber volume fraction of 5.4%, are compatible with fused deposition modelling for 3D printing. The die is engineered to improve polymer–fiber interaction during filament fabrication. Specifically, its rotating geometry induces a swirling flow pattern in the molten polymer, which enhances fiber wetting and promotes partial fiber interlacing. The performance of the system was evaluated through both numerical simulations and experimental tests. In the computational fluid dynamics analysis, an inlet velocity of 5 mm/s was imposed, showing that the rotational motion generates a tangential velocity component that improves fiber-polymer interaction and locally reduces viscosity at the fiber surface, leveraging the shear-thinning behaviour of the polymer. This results in improved impregnation efficiency without affecting the internal pressure of the die. Two filament configurations were produced for comparison: one using the rotating impregnation die PLAGF-B (PolyLactic Acid – Glass Fiber Braided) and one using a static die PLAGF-UB (PolyLactic Acid – Glass Fiber UnBraided). The produced filaments consisted of three glass-fiber bundles impregnated with PLA resin and were subjected to standard tensile testing, after being pulled at a controlled speed of 6 mm/s. The PLAGF-B samples exhibited higher tensile strength (~ 70 MPa vs. ~60 MPa) and elongation at break (~ 0.023 mm/mm vs. ~0.018 mm/mm), attributed to enhanced twisting and compaction induced by the die’s rotation.

All machining processes involve vibrations originating from either the structural dynamics of the machinery system or the impact phenomena related to the interaction between the cutting tools and the workpieces. The latter can lead to a chip regeneration effect, which negatively impacts the machining quality, resulting in poor surface finishes or, in severe cases, damage to the machine tool or workpiece. Traditionally, analytical methods such as stability lobe diagrams and analytical models in the time and frequency domains have been employed to predict and mitigate chatter. These methods offer advantages such as simplicity, low computational cost, and ease of implementation. However, they often rely on assumptions that limit their accuracy, particularly under complex machining conditions. This paper presents the development of a novel analytical algorithm for chatter detection in the time domain, based on signal filtering and energy ratio evaluation. A comparison with the corresponding frequency domain and with other analytical approaches was conducted. The results show that the proposed method demonstrates performance for detection of chatter-free and severe chatter-affected machining processes. Moreover, the proposed analytical time domain algorithm (ATDA) exhibits greater sensitivity in handling non-stationary signals, especially in intermediate machining states, where moderate chatter is observed or where a severe transition from stable to unstable machining occurs. Furthermore, the evaluation of the computational costs confirmed that the proposed time domain method offers good computational performance, highlighting its suitability for in-process applications.

As stroke is becoming more frequent nowadays, cutting edge rehabilitation approaches are required to recover upper limb functionalities and to support patients during daily activities. Recently, focus has moved to robotic rehabilitation; however, therapeutic devices are still highly expensive, making rehabilitation not easily affordable. Moreover, devices are not easily accepted by patients, who can refuse to use them due to not feeling comfortable. The presented work proposes the exploitation of a virtual prototype of the human–robot ecosystem for the study and analysis of patient–robot interactions, enabling their simulation-based investigation in multiple scenarios. For the accomplishment of this task, the Dynamics of Multi-physical Systems platform, previously presented by the authors, is further developed to enable the integration of biomechanical models of the human body with mechatronics models of robotic devices for motion assistance, as well as with PID-based control strategies. The work begins with (1) a description of the background; hence, the current state of the art and purpose of the study; (2) the platform is then presented and the system is formalized, first from a general side and then (3) in the application-specific scenario. (4) The use case is described, presenting a controlled gym weightlifting exercise supported by an exoskeleton and the results are analyzed in a final paragraph (5).