Text

theses

Nanoscale morphological characterization and mechanical properties quantification of soft and biological materials play an important role in areas ranging from nano-composite material synthesis and characterization, cellular mechanics to drug design. Frontier studies in these areas demand the coordination between nanoscale morphological evolution and mechanical behavior variations through simultaneous measurement of these two aspects of properties. Atomic force microscope (AFM) is very promising in achieving such simultaneous measurements at high-speed and broadband owing to its unique capability in applying force stimuli and then, measuring the response at specific locations in a physiologically friendly environment with pico-newton force and nanometer spatial resolution. Challenges, however, arise as current AFM systems are unable to account for the complex and coupled dynamics of the measurement system and probe-sample interaction during high-speed imaging and broadband measurements. In this dissertation, the creation of a set of dynamics and control tools to probe-based high-speed imaging and rapid broadband nanomechanical spectroscopy of soft and biological materials are presented. Firstly, advanced control-based approaches are presented to improve the imaging performance of AFM imaging both in air and in liquid. An adaptive contact mode (ACM) imaging scheme is proposed to to replace the traditional contact mode (CM) imaging by addressing the major concerns in both the speed and the force exerted to the sample. In this work, the image distortion caused by the topography tracking error is accounted for in the topography quantification and the quantified sample topography is utilized in a gradient-based optimization method to adjust the cantilever deflection set-point for each scanline closely around the minimal level needed for maintaining a stable probe-sample contact, and a data-driven iterative feedforward control that utilizes a prediction of the next-line tracking is implemented to enhance the sample topography tracking. An adaptive multi-loop mode (AMLM) imaging approach is proposed to substantially increase the imaging speed of tapping mode (TM) while preserving the advantages of TM over CM by integrating an inner-outer feedback control loop to regulate the TM-deflection on top of the conventional TM-amplitude feedback control to improve the sample topography tracking. Experiments demonstrated that the proposed ACM and AMLM are capable of increasing the imaging speed by at least 20 times for conventional contact and tapping mode imaging, respectively, with no loss of imaging quality and well controlled tip-sample interaction force. In addition, an adaptive mode imaging for in-liquid topography quantification on live cells is presented. The experiment results demonstrated that instead of keeping constant scanning speed, the proposed speed optimization scheme is able to increase the imaging speed on live human prostate cancer cells by at least eight-fold with no loss of imaging quality. Secondly, control based approaches to accurate nanomechanical quantification on soft materials for both broadband and in-liquid force-curve measurements are proposed to address the adverse effects caused by the system coupling dynamics and the cantilever acceleration, which were not compensated for by the conventional AFM measurement approach. The proposed nanomechanical measurement approaches are demonstrated through experiments to measure the viscoelastic properties of different polymer samples in air and live human cells in liquid to study the variation of rate-dependent elastic modulus of cervix cancer cell during the epithelial-mesenchymal transition process.

ETD_6556

Ph.D.

Includes bibliographical references

by Juan Ren

doi:10.7282/T3XK8HJR

ETD doctoral

The author owns the copyright to this work.