Understanding energy-loss mechanisms at the nanoscale is the holy grail of surface physicists, surface chemists and biologists. As such, it is gaining importance across all branches of physics, medicine, biology, experimental biophysics, and material science for predicting kinetics at the nanoscale. For example, the key to identifying cues in mechanobiology and bio-kinetics lies with understanding the thermodynamics of single biomolecules and cells. Curiously, nature adopts soft-touch mechanisms to discern and navigate thermodynamic loss mechanisms in probing its environment at the nanoscale. This is abundant in the insect world.
Researchers at the University of Calgary have developed an ultra-light tapping atomic force microscopy (AFM) technique mimicking nature’s soft-touch. The method generates a unique two-stage energy distribution response from tip-surface interactions during the transitional tapping operation. This allows the decoupling of the elastic and viscous loss components simultaneously while generating AFM images. The method is the first of its kind to image and map thermodynamic heterogeneities at the nanoscale and does not enforce surface indentation.
Soft biological samples, polymers, electronic interconnects relevant to both semiconductor and battery industry can benefit from this novel surface characterization technology. The technology can be implemented as an advanced mode into existing AFM systems or can be developed into a standalone device with novel artificial intelligence (AI) algorithms to seamlessly adapt and optimize parameter-sets necessary to achieve transitional tapping for a particular sample.
AREAS OF APPLICATION
- Soft-matter physics
- Biomolecular/cellular imaging – cancer and protein research
- Semiconductor Industry
- Energy storage industry for Li-ion battery electrodes or transport losses at supercapacitor electrode interfaces
- Fundamental Science – A way to couple mechanical, electromechanical, electrical, and transport phenomena at the nanoscale.
- Device – Potential for a new class of scanning probe microscopy that exploits stochastic fluctuations in energy at interfaces without indentation to generate new information.
- Applications – Wide prospects with a large potential market in various sectors such as medicine, biophysics, semiconductor, and energy research with significant returns.
- Technology – Multi-modal, high-speed image acquisition with simultaneous data science as feedback for operational automation. Integration and incorporation of AI tools for data science to automate physics extraction from nanoscale resolved images.
STAGE OF DEVELOPMENT
- A consolidated collaboration effort with industrial partners targeting core research areas in biology & medicine, semiconductor and energy research industries is envisioned.
- Provisional patent application filed
- Researcher profile: Dr. Seongwhan (Sam) Kim