We describe in detail, the design, construction, and testing of a specimen holder that allows for the nanoindentation of surfaces while viewing in cross-section in a high voltage transmission electron microscope (TEM). This nanoindentation specimen holder, having three-axis position control of a diamond indenter in combination with micromachined specimens, allows for the first time the dynamic observation of subsurface microstructure evolution under an indenter tip. Additionally, the sample design techniques that have been developed for these procedures may eliminate the need for TEM specimen preparation for additional ex situ nanoindentation experiments. Initial experimental results from in situ indentation of Si samples in the high voltage electron microscope are reported here to demonstrate the capability of this new specimen holder.

Abstract-The propulsion of nano-ferromagnetic objects by means of MRI gradients is a promising approach to enable new forms of therapy. In this work, necessary techniques are presented to make this approach work. This includes path planning algorithms working on MRI data, ferromagnetic artifact imaging and a tracking algorithm which delivers position feedback for the microdevice and a propulsion sequence to enable interleaved magnetic propulsion and imaging. Using a dedicated software environment integrating path-planning methods and real-time tracking, a clinical MRI system is adapted to provide this new functionality for potential controlled interventional targeted therapeutic applications. Through MRI-based sensing analysis, this paper aims to propose a framework to plan a robust pathway to enhance the navigation ability to reach deep locations in human body. The proposed approaches are validated with different experiments.

Microrobotics is a field of high interest in the recent past. Commonly used imaging modalities in this field include optical microscopes and scanning electron microscopes (SEM). Due to the scanning principle of the SEMs, objects in motion may not be represented in the SEM images the same way as they really are. Movement leads to movement artifacts. This effect strongly limits the possibilities for the use of image based methods for tracking and recognition and it also limits the possible speeds achievable for automated procedures. In this work, a tracking algorithm is proposed which is robust to artifacts and distortions generated by object motion. The algorithm is tested and validated in experiments.