Microrobots for targeted drug delivery in blood vessels have attracted increasing interest from researchers. In this work, hydrogel-based capsule microrobots are used to wrap drugs and deliver drugs in blood vessels. In order to prepare capsule microrobots of different sizes, a triaxial microfluidic chip is designed and built, and the formation mechanism of three flow phases including the plug flow phase, bullet flow phase and droplet phase during the preparation of capsule microrobots is studied. The analysis and simulation results show that the size of the capsule microrobots can be controlled by the flow rate ratio of two phases in the microfluidic chip, and when the flow rate of the outer phase is 20 times that of the inner phase in the microfluidic chip, irregular multicore capsule microrobots can be prepared. On this basis, a three degree of freedom magnetic drive system is developed to drive the capsule microrobots to reach the destination along the predetermined trajectory in the low Reynolds number environment, and the magnetic field performance of the magnetic drive system is simulated and analyzed. Finally, in order to verify the feasibility of targeted drug delivery of the capsule microrobots in the blood vessel, the motion process of the capsule microrobots in the vascular microchannel is simulated, and the relationship between the motion performance of the capsule microrobots and the magnetic field is studied. The experimental results show that the capsule microrobots can reach a speed of 800 μm s⁻¹ at a low frequency of 0.4 Hz. At the same time, the capsule microrobots can reach a peak speed of 3077 μm s⁻¹ and can continuously climb over a 1000 μm high obstacle under a rotating magnetic field of 2.4 Hz and 14.4 mT. Experiments show that the capsule microrobots have excellent drug delivery potential in similar vascular curved channels driven by this system.

Determining the metallicity and semiconductivity of a multi-walled carbon nanotube (MWCNT) bundle plays a particularly vital role in its interconnection with the metal electrode of an integrated circuit. In this paper, an effective method is proposed to determine the electrical transport properties of an MWCNT bundle using a current–voltage characteristic curve during its electrical breakdown. We established the reliable electrical nanoscale contact between the MWCNT bundle and metal electrode using a robotic manipulation system under scanning electron microscope (SEM) vacuum conditions. The experimental results show that the current–voltage curve appears as saw-tooth-like current changes including up and down steps, which signify the conductance and breakdown of carbon shells in the MWCNT bundle, respectively. Additionally, the power law nonlinear behavior of the current–voltage curve indicates that the MWCNT bundle is semiconducting. The molecular dynamics simulation explains that the electron transport between the inner carbon shells, between the outermost carbon shells and gold metal electrode and between the outermost carbons shells of two adjacent individual three-walled carbon nanotubes (TWCNTs) is through their radial deformation. Density functional theory (DFT) calculations elucidate the electron transport mechanism between the gold surface and double-wall carbon nanotube (DWCNT) and between the inner and outermost carbon shells of DWCNT using the charge density difference, electrostatic potential and partial density of states.

The maneuvering and electrical characterization of nanotubes inside a scanning electron microscope (SEM) has historically been time-consuming and laborious for operators. Before the development of automated nanomanipulation-enabled techniques for the performance of pick-and-place and characterization of nanoobjects, these functions were still incomplete and largely operated manually. In this paper, a dual-probe nanomanipulation system vision-based feedback was demonstrated to automatically perform 3D nanomanipulation tasks, to investigate the electrical characterization of nanotubes. The XY-position of Atomic Force Microscope (AFM) cantilevers and individual carbon nanotubes (CNTs) were precisely recognized via a series of image processing operations. A coarse-to-fine positioning strategy in the Z-direction was applied through the combination of the sharpness-based depth estimation method and the contact-detection method. The use of nanorobotic magnification-regulated speed aided in improving working efficiency and reliability. Additionally, we proposed automated alignment of manipulator axes by visual tracking the movement trajectory of the end effector. The experimental results indicate the system’s capability for automated measurement electrical characterization of CNTs. Furthermore, the automated nanomanipulation system has the potential to be extended to other nanomanipulation tasks.