Fully soft continuum magnetic (FSCMs) microrobots with highly deformable structures have emerged as a potential solution to robotically controlled endovascular interventions. The microrobot's structure is made of magneto-responsive material, which offers full body control under a magnetic field instead of limited tip deformation. The shape control for these microrobots enables steering in complex paths with limited contact with the environment. We studied full body control under fields generated using up to two robotically controlled permanent magnets and in combination with an electromagnetic system. The effect of different parameters, such as the number of permanent magnets, position of the permanent magnets and intensity and direction of the electromagnetic field, on the robot's shape has been experimentally investigated. A mathematical model to predict tip deformation angle (TDA) was introduced and verified experimentally (root mean square error (RMSE) 6.5). Ten different characteristic body shapes were identified based on the curvature of the soft robot. Based on the obtained data, a proof-of-concept demo is presented for the full body controlled soft robots. The accuracy of steering soft robots on a continuous path with all three magnetic control strategies was investigated. The results show that the proposed method effectively enables shape forming and minimizes contact with the surrounding environment (the average distance to the centerline was 1.24 mm). The proposed approach hold promises to elevate endovascular interventions towards the least invasive surgery.

The position control of magnetic medical microrobots is influenced by several environmental uncertainties including the unknown characteristics of the medium and the imaging precision. Furthermore, measuring the physical attributes of the microrobots is a challenging issue. To provide a model-free position control approach for the magnetic medical microrobots, a saturation-tolerant Adaptive Fuzzy Sliding-Mode Control (AFSMC) is designed in this study. In the proposed approach, each control input comprises a fuzzy inference term utilized to approximate an unknown nonlinear function including uncertain forces, a robust part derived to compensate for the fuzzy approximation error and disturbances, and a compensating gain for input saturation. By utilizing the second theorem of Lyapunov and Barbalat’s lemma, it is proved that the closed-loop system is asymptotically stable. The effectuality of the presented controller is assessed by means of two experimental scenarios. The results show that the magnitudes of the tracking errors corresponding to a spiral reference path are less than 0.2 mm at the end of the motion. Moreover, in the test conducted in a 3D printed Aorta phantom, the minimum and the maximum values of the tracking errors are $-$ 1.22 mm and 0.95 mm, respectively. Note to Practitioners —This article introduces an innovative, model-free technique specifically designed to tackle the complex challenges of position control in magnetic medical microrobots. Achieving precise control over these microrobots is a challenging task, compounded by the complexity of accurately measuring their physical properties and the characteristics of their surrounding medium. This challenge is further exacerbated by the issue of input saturation, which can compromise system stability. Our pioneering control method is designed to navigate these obstacles effectively. It functions under the assumption that both the lower and upper saturation limits are unknown, and it eliminates the necessity to model the forces acting on the microrobot. Experimental results confirm the method’s effectiveness in accurately tracking various reference trajectories. These findings suggest that our method holds significant promise for various medical applications.

The invasive presence of nanoplastics in various ecosystems makes them a significant environmental problem nowadays. One of the main production mechanisms of nanoplastics is mechanical wear. The combination of friction, abrasion, and shear forces can indeed lead to the progressive fragmentation of polymeric materials. The high surface area–volume ratio of the resulting nanoparticles not only alters the physicochemical properties of the polymers but also leads to increased interaction with biological systems, which raises questions about the persistence of nanoplastics in the environment and their potential toxicity. Despite the growing body of research on microplastics, studies specifically addressing the formation, characterization, and impact of wear-induced nanoplastics remain limited. This article describes current research on the formation mechanisms of nanoplastics generated by mechanical wear, highlighting the tribological processes underlying their release. Advanced characterization techniques used to identify the morphology and composition of these particles are also mentioned. The techniques include atomic force microscopy (AFM), scanning electron microscopy (SEM), and, to some extent, Raman spectroscopy. In the case of AFM, an example of application to the extrusion of nanoplastics from polystyrene surfaces subjected to repeated nanoscratching is also provided.