University of Nevada - Reno
Contact Resonance Atomic Force Microscopy using advanced sensors and post-processing techniques
Abstract
dc:description.abstractMicro-sensors are used within the Atomic Force Microscope for topographic and sampleproperty measurements and can achieve a nano-scale resolution. Contact resonance spectroscopy allows the estimation of mechanical properties by measuring the sensor-sample coupled system resonance frequency. To date, contact resonance has been limited to conventional sensors, thus, new advanced sensors with large tip modifications were incompatible with current contact resonance models and data analysis techniques. In this work, we combine experimental and analytical frameworks for the derivation, verification, and validation of advanced contact resonance models for dynamic measurements using cantilever sensors with significant tip dimensions. Furthermore, we develop a new data analysis technique, applicable for all contact-resonance models. We find our new model to accurately describe the sample stiffness in contact resonance mode, using a cantilever sensor with a long massive tip, for both a rigid tip and an elastic one. Our new data analysis technique not only provides improved accuracy over conventional data analysis techniques in use today, but it is the only available technique capable of handling multi-variable contact resonance models without a priori knowledge of the sensor geometry.
Degree
thesis:*- Level thesis:degree_level
- Doctorate Degree
- Year dc:date.issued
- 2023
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Zimron-Politi, Nadav
- Advisor dc:contributor.advisor
-
- Tung, Ryan
- Committee members dc:contributor.committeemember
-
- Aureli, Matteo
- Hanna, James
- Hand, Emily
- White, Thomas
Subjects
dc:subject × 5Rights
dc:rights- Statement dc:rights
-
- Creative Commons Attribution-NonCommercial-ShareAlike 4.0 United States
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/11714/10816
- OAI identifier oai:identifier
- oai:scholarwolf.unr.edu:11714/10816