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.

In this paper a promising method of recognizing spatial contact state between carbon nanotubes (CNTs) and atomic force microscope (AFM) probe inside scanning electron microscope (SEM) is proposed. The CNTs can be picked up simply and effectively by van der Waals force without knowing depth information of SEM images by using this method. And a micro-nanorobotic manipulation system with 16 DOFs, which allows the automatic pick-up of CNTs based on visual feedback, is presented. The micro-nanorobotic manipulators are assembled into 4 units with 4 DOFs individually. Namely, a manipulator has 4 DOFs i.e., three linear motions and a rotational motion. Manipulators are actuated by picomotors with better than 30 nm linear resolution and less than 1 micro-rad rotary resolution. The van der Waals force mechanics model between CNTs and AFM probe in the picking up manuplation is established. In reality, the van der Waals force is the main attractive force under the vacuum condition inside SEM when the influence of staticelectricity is ignored. It is shown that the van der Waals force under horizontal (sphere-plane) contact model is significantly larger with appropriate overlapping length. Though the positions in both x and y directions of the CNTs and AFM cantilever are acquired, the relative positions of those two objects in the z direction remain unclear. In the gradually ascending process of AFM cantilever to contact the CNTs, the CNTs abruptly drop on the surface of AFM probe due to the van der Waals force. According to the relative coordinate system of SEM visual feedback images, the detection of contact state between carbon nanotubes and AFM probe are completed by using the inclination changing value of fitting line. The experimental results suggest that the abrupt contact between CNTs and AFM probe happens when the inclination changing value of the regression line is found to be 3.0263. The spatial contact state between carbon nanotubes and AFM probe includes line contact (Model a) and point contact (Model b, Model c). Then the dynamic difference method is introduced to identify the spatial contact model of CNTs and AFM probe. The results demonstrate that contact model of CNTs and AFM probe is line contact when the dynamic difference is approximately zero. The position of carbon nanotubes is corrected by moving AFM cantilever automatically underneath the CNTs. The picking-up of CNTs from substrate under line contact model is completed by choosing the optimum contact angle, contact length and pickup speed.

A humidity sensor is a crucial device in daily life; therefore, in the present study, a novel humidity sensor was designed to increase its specific surface area to improve its humid sensing capacity and conductivity. Titanium dioxide nanoparticles (TiNP) consisting of zero-dimensional nanospheres and one-dimensional nanotubes were prepared by anodic oxidation. Rod-shaped cellulose nanocrystals (CNCs) with average length and diameter of 60 nm and 800 nm, respectively, were obtained by enzymatic hydrolysis and high pressure homogenization. TiNP/CNC composite films exhibited superior hydrophilicity and large specific surface areas based on Fourier transform infrared spectroscopy and nitrogen adsorption–desorption results. The humidity sensing characteristics of sensors based on TiNP/CNC flexible composite films with varying contents of TiNP were investigated under a relative humidity range of 11–97%. The 6% TiNP/CNC-based humidity sensor exhibited high humidity response, rapid response/recovery speed, and high stability. Furthermore, the humidity sensing mechanism of TiNP/CNC composite films was analyzed based on the density functional theory. TiNP/CNC-based humidity sensors could be applied in flexible and wearable electronics.

This paper presents our system submission to task 5: Toxic Spans Detection of the SemEval-2021 competition. The competition aims at detecting the spans that make a toxic span toxic. In this paper, we demonstrate our system for detecting toxic spans, which includes expanding the toxic training set with Local Interpretable Model-Agnostic Explanations (LIME), fine-tuning RoBERTa model for detection, and error analysis. We found that feeding the model with an expanded training set using Reddit comments of polarizedtoxicity and labeling with LIME on top of logistic regression classification could help RoBERTa more accurately learn to recognize toxic spans. We achieved a span-level F1 score of 0.6715 on the testing phase. Our quantitative and qualitative results show that the predictions from our system could be a good supplement to the gold training set's annotations.