Nanomanipulation under scanning electron microscopy (SEM) has been demonstrated as an enabling technique for the manipulation and characterization of nanomaterials. We recently developed nanomanipulation techniques for the extraction and identification of DNA contained within sub-nuclear locations of a single cell nucleus. In nanomanipulation of DNA, a key step is target identification through SEM-fluorescence correlative imaging. Existing image correlation techniques often require fiducial marks and/or manual feature selection or data training, which are unsuitable for DNA nanomanipulation. This paper presents an approach for correlating SEM-fluorescence microscopy images, proven effective in processing images taken under poor SEM imaging conditions imposed by the necessity of preserving DNA's biochemical integrity. The performance of the image correlation approach under different imaging conditions was quantitatively evaluated. Compared to manual correlation by skilled operators, the automated correlation approach demonstrated an order of magnitude higher speed. The SEM-fluorescence correlation approach enables targeted nanomanipulation of sub-cellular structures under SEM.

Probing nanometer-sized structures to evaluate the performance of integrated circuits (IC) for design verification and manufacturing quality monitoring demands precision nanomanipulation technologies. To minimize electron-induced damage and improve measurement accuracy, scanning electron microscopy (SEM) imaging parameters must be cautiously chosen to ensure low electron energy and dosage. This results in significant image noise and drift. This paper presents automated nanoprobing with a nanomanipulation system inside a standard SEM. We achieved SEM image denoising and drift compensation in real time. This capability is necessary for achieving robust visual tracking and servo control of nanomanipulators for probing nanostructures in automated operation. This capability also proves highly useful to conventional manual operation by rendering real-time SEM images that have little noise and drift. The automated system probed nanostructures on an SEM metrology chip as surrogates of electronic features on IC chips. Success rates in visual tracking and Z-contact detection under various imaging conditions were quantitatively discussed. The experimental results demonstrate the system's capability for automated probing of nanostructures under IC-chip-probing relevant electron microscope imaging conditions.

Nanomanipulation inside electron microscopes enables a multitude of precision applications. The semiconductor industry employs this capability to probe sub-micrometer-sized features to evaluate the performance of integrated circuits (IC) for design/quality monitoring. In electron microscopy imaging, the use of low accelerating voltages and high magnifications, as required for IC nanoprobing tasks, results in significant image noise and drift. This paper presents automated nanoprobing with a nanomanipulation system inside a standard scanning electron microscope (SEM). We achieved SEM image denoising and drift compensation in real time. This capability is necessary for achieving robust visual tracking and servo control of nanoprobes for probing nanostructures in automated operation. This capability also proves highly useful to conventional manual operation by rendering real-time SEM images that have little noise and drift. The automated system probed nanostructures on an SEM metrology chip as surrogates of electronic features on IC chips. Success rates in visual tracking and Z-contact detection under various imaging conditions were quantitatively discussed. The experimental results demonstrate the system's capability for automated probing of nanostructures under IC-chip-probing relevant EM imaging conditions.

This paper presents a robotic system that is capable of both picking up and releasing microobjects with high accuracy, reliability, and speed. Due to force-scaling laws, large adhesion forces at the microscale make rapid, accurate release of microobjects a long-standing challenge in micromanipulation, thus representing a hurdle toward automated robotic pick-and-place of micrometer-sized objects. The system employs a novel microelectromechanical systems (MEMS) microgripper with a controllable plunging structure to impact a microobject that gains sufficient momentum to overcome adhesion forces. The performance was experimentally quantified through the manipulation of 7.5-10.9 ¿m borosilicate glass spheres in an ambient environment. Experimental results demonstrate that the system, for the first time, achieves a 100% success rate in release (which is based on 700 trials) and a release accuracy of 0.45 ± 0.24 ¿m. High-speed, automated microrobotic pick-and-place was realized by visually recognizing the microgripper and microspheres, by visually detecting the contact of the microgripper with the substrate, and by vision-based control. Example patterns were constructed through automated microrobotic pick-and-place of microspheres, achieving a speed of 6 s/sphere, which is an order of magnitude faster than the highest speed that has been reported in the literature.

Due to force scaling laws, rapid, accurate release of micro objects has been a long-standing challenge for microrobotic manipulation. This paper presents an active release technique that for the first time, achieves 100% repeatability and a release accuracy of 0.70plusmn0.46mum, experimentally quantified through the manipulation of 10mum glass spheres under an optical microscope. Using a new MEMS (microelectromechanical systems) microgripper, this technique employs a controllable plunging mechanism for the micro object to gain sufficient momentum to overcome adhesion forces. Experimental results also confirmed that this technique is not substrate dependent. Theoretical analyses were conducted to understand the release principle. Based on this preliminary study, the technique may also prove to be an effective solution to active release of sub-micron objects in robotic pick-place.