Electromechanical and elastic probing of bacteria in a cell culture medium.

Rapid phenotype characterization and identification of cultured cells, which is needed for progress in tissue engineering and drug testing, requires an experimental technique that measures physical properties of cells with sub-micron resolution. Recently, band excitation piezoresponse force microscopy (BEPFM) has been proven useful for recognition and imaging of bacteria of different types in pure water. Here, the BEPFM method is performed for the first time on physiologically relevant electrolyte media, such as Dulbecco's phosphate-buffered saline (DPBS) and Dulbecco's modified Eagle's medium (DMEM). Distinct electromechanical responses for Micrococcus lysodeikticus (Gram-positive) and Pseudomonas fluorescens (Gram-negative) bacteria in DPBS are demonstrated. The results suggest that mechanical properties of the outer surface coating each bacterium, as well as the electrical double layer around them, are responsible for the BEPFM image formation mechanism in electrolyte media.

Double-layer mediated electromechanical response of amyloid fibrils in liquid environment.

Harnessing electrical bias-induced mechanical motion on the nanometer and molecular scale is a critical step toward understanding the fundamental mechanisms of redox processes and implementation of molecular electromechanical machines. Probing these phenomena in biomolecular systems requires electromechanical measurements be performed in liquid environments. Here we demonstrate the use of band excitation piezoresponse force microscopy for probing electromechanical coupling in amyloid fibrils. The approaches for separating the elastic and electromechanical contributions based on functional fits and multivariate statistical analysis are presented. We demonstrate that in the bulk of the fibril the electromechanical response is dominated by double-layer effects (consistent with shear piezoelectricity of biomolecules), while a number of electromechanically active hot spots possibly related to structural defects are observed.

Spatially resolved spectroscopic mapping of polarization reversal in polycrystalline ferroelectric films: crossing the resolution barrier.

The mesoscopic reversible and irreversible polarization dynamics in polycrystalline PZT thin film capacitors are studied using local spectroscopic mapping and macroscopic first-order reversal curve measurements. The transition from a regime of short range domain wall motion to the formation of mesoscopic clusters to complete switching is observed. The fractal dimension of the clusters is consistent with the random-bond disorder model. The combination of macroscopic and local measurements allows the characteristics length scales corresponding to the transition from Rayleigh to Preisach behaviors and onset of macroscopic averaging to be determined.

Probing the temperature dependence of the mechanical properties of polymers at the nanoscale with band excitation thermal scanning probe microscopy.

Understanding local mechanisms for temperature-induced phase transitions in polymers requires quantitative measurements of the thermomechanical behavior, including glass transition and melting temperatures as well as temperature dependent elastic and loss modulus and thermal expansion coefficients in nanoscale volumes. Here, we demonstrate an approach for probing local thermal phase transitions based on the combination of thermal field confinement by a heated SPM probe and multi-frequency thermomechanical detection. The local measurement of the glass transition temperature is demonstrated and the detection limits are established.

Functional recognition imaging using artificial neural networks: applications to rapid cellular identification via broadband electromechanical response.

Functional recognition imaging in scanning probe microscopy (SPM) using artificial neural network identification is demonstrated. This approach utilizes statistical analysis of complex SPM responses at a single spatial location to identify the target behavior, which is reminiscent of associative thinking in the human brain, obviating the need for analytical models. We demonstrate, as an example of recognition imaging, rapid identification of cellular organisms using the difference in electromechanical activity over a broad frequency range. Single-pixel identification of model Micrococcus lysodeikticus and Pseudomonas fluorescens bacteria is achieved, demonstrating the viability of the method.