Principal Investigator: Bertozzi, Andrea Institution: University of California-Los Angeles Proposal No: 0940417
This research project forges an interdisciplinary intellectual partnership between UCLAs Applied Mathematics program and Lawrence Berkeley Laboratorys Molecular Foundry, with the goal of designing transformative computation-based methods for real-time data acquisition and analysis in atomic force microscopy (AFM). The work combines expertise in (a) high-precision AFM instrumentation for imaging and force spectroscopy experiments, (b) the pioneering use of AFM to investigate the dynamics of oxidation, crystallization, and assembly of inorganic and macromolecular systems with (c) advanced algorithms for real-time mobile data acquisition and state-of-the-art image processing algorithms.
The research focuses on two case studies: Potassium bromide oxidation, an important process in understanding tropospheric chemistry, and S-layer protein array formation on lipid bilayers, an in vitro model of microbial membrane development. Both problems have dynamic behavior on a time-scale too fast for current AFM imaging technologies. The work involves state-of-the-art algorithm development involving compressive sensing, image inpainting, image segmentation and deblurring, combined with real-time tip steering using ideas from recent work in control theory and mobile sensors. In addition, to the new algorithm development, the project addresses new scientific results for the example problems, and a modular software package for control of the AFM sensor that could be adapted for diverse AFM imaging applications.
The research program involves the training of two graduate students, one in mathematics and one in microscopy, in cutting-edge interdisciplinary science. Additionally, undergraduate students are involved in algorithm software and hardware implementation. The impact on science is profound namely the ability to observe biological and chemical processes at higher speeds at the level of detail of AFM and to further increase the resolution and imaging power of existing AFM hardware technologies, through software and control methodologies. The Molecular Foundry is a user facility providing support to nanoscience researchers in academic, government and industrial laboratories around the world. Thus, advances made through this research program have an immediate user audience through the many researchers visiting the Foundry. Technology developed under this research program is also disseminated to commercial AFM manufacturers.
This research project forged an interdisciplinary intellectual partnership between UCLA’s Applied Mathematics program and Lawrence Berkeley Laboratory’s Molecular Foundry, with the goal of designing transformative computation-based methods for real-time data acquisition and analysis in atomic force microscopy (AFM). The work combines expertise in high-precision AFM instrumentation for imaging and force spectroscopy experiments with advanced algorithms for real-time mobile data acquisition and state-of-the-art image processing algorithms. Scanning probe microscopy (SPM) has facilitated many scientific discoveries utilizing its strengths of spatial resolution, non-destructive characterization and realistic in situ environments. However, accurate spatial data are required for quantitative applications but this is challenging for SPM especially when imaging at higher frame rates. We developed a new operation mode for scanning probe microscopy that uses advanced image processing techniques to render accurate images based on position sensor data. This technique, which we call sensor inpainting, frees the scanner to no longer be at a specific location at a given time. This drastically reduces the engineering effort of position control and enables the use of scan waveforms that are better suited for the high inertia nanopositioners of SPM. While in raster scanning, typically only trace or retrace images are used for display, in Archimedean spiral scans 100% of the data can be displayed and at least a two-fold increase in temporal or spatialresolution is achieved. In the new mode, the grid size of the final generated image is an independent variable. Inpainting to a few times more pixels than the samples creates images that more accurately represent the ground truth. We developed a novel method to detect and correct drift in non-raster scanning probe microscopy. In conventional raster scanning drift is usually corrected by subtracting a fitted polynomial from each scan line, but sample tilt or large topographic features can result in severe artifacts. Our method used self-intersecting scan paths to distinguish drift from topographic features. Observing the height differences when passing the same position at different times enables the reconstruction of a continuous function of drift. We showed that a small number of self-intersections is adequate for automatic and reliable drift correction. Additionally, we introduce a fitness function which provides a quantitative measure of drift correctability for any arbitrary scan shape. The research program involved the training of graduate students and postdocs in both mathematics and microscopy. Additionally, undergraduate students were involved in algorithm software and hardware implementation. The impact on science is profound namely the ability to observe biological and chemical processes at higher speeds at the level of detail of AFM and to further increase the resolution and imaging power of existing AFM hardware technologies, through software and control methodologies. The Molecular Foundry is a user facility providing support to nanoscience researchers in academic, government and industrial laboratories around the world. Thus, advances made through this research program have an immediate user audience through the many researchers visiting the Foundry. Technology developed under this research program is also disseminated to commercial AFM manufacturers.
