Atomic Force Microscope for Materials Characterization

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This proposal requests an atomic force microscope (AFM). This urgent request is to replace our current instrument that has suffered a catastrophic failure and cannot be repaired.  The new AFM will continue to be housed in a shared, open access, facility at the Department of Chemistry/Center for Advanced Materials and Technologies (CAMTEC). The AFM is a routine tool for materials science research. It is regularly used by several researchers (about 67 individuals in the last 5 years) from 16 research groups from UVic science and engineering plus scientists from materials-related companies based in Victoria (BC). The requested AFM will replace and upgrade the only equipment (a 20+ years old system) of its kind in Vancouver Island. The requested new instrument is a state of the art equipment that allows imaging of very small features (in the nanometric range - the width of an human hair is about 100,000 namometers) with high spatial resolution and signal-to-noise ratio. The system is equipped with advanced hardware and software that allows for fast imaging acquisition and the simultaneous measurement of mechanical and electrical characteristics. This new AFM permit the generation of massive amounts microscopic images that can offer a full characterization of the system being investigated. These unique characteristics will be explored in the investigation of nanostructured solar cell devices that present enhanced performance for the light to electricity conversion. Highly efficient solar cells are required for the implementation of a sustainable energy system in a near future. The use of novel nanomaterials, including semiconductors, plasmonic particles and perovskites, provide potential approaches to achieve maximum efficiency. However, the control of the morphology and the presence of defects are generally limiting steps in the performance for those types of devices. The requested AFM will allow characterization that will reveal the relationship between morphology and performance at the nanoscale dimensions. The massive amount of data generated by the requested AFM will also be used to improve fabrication and predict properties of chiral interfaces. The AFM will allow the general of a large amount of images in short time of different types of chiral surfaces (different types of sulfur-containing amino acids and peptides). This massive data set will be combined with computational data obtained by density functional theory and artificial intelligence methods for big data analysis. The goal is to train machine learning models to make predictions regarding potential structure and reactivity of these chiral interfaces that will impact the development of heterogeneous asymmetric catalysts and biosensors. The new AFM will not only provide advanced training for a new generation of materials scientists, but also enable research that will benefit the development of new industrial technologies in sustainable energy, catalysis and biosensors.