Extended scene deep learning wavefront sensing.

We have applied a combination of blind deconvolution and deep learning to the processing of Shack-Hartmann images. By using the intensity information contained in spot positions, and the fine structure of the separate images created by the lenslets, we have increased the sensitivity and resolution of the sensor over the limit defined by standard processing of spot displacements only. We also have demonstrated the applicability of the method to wavefront sensing using extended objects as a reference.

Nickel-Containing Perovskites, PrNiFeO and PrNiCoO, as Potential Electrodes for Protonic Ceramic Electrochemical Cells.

Protonic ceramic fuel cells (PCFCs) offer a convenient means of converting chemical energy into electricity with high performance and efficiency at low- and intermediate-temperature ranges. However, in order to ensure good life-time stability of PCFCs, it is necessary to ensure rational chemical design in functional materials. Within the present work, we propose new Ni-based perovskite phases of PrNiMO (where M = Co, Fe) for potential utilization in protonic ceramic electrochemical cells.

Large volume holographic imaging for biological sample analysis.

Significance: Particle field holography is a versatile technique to determine the size and distribution of moving or stationary particles in air or in a liquid without significant disturbance of the sample volume. Although this technique is applied in biological sample analysis, it is limited to small sample volumes, thus increasing the number of measurements per sample. In this work, we characterize the maximum achievable volume limit based on the specification of a given sensor to realize the development of a potentially low-cost, single-shot, large-volume holographic microscope.

Anisoplanatic adaptive optics in parallelized laser scanning microscopy.

Inhomogeneities in the refractive index of a biological microscopy sample can introduce phase aberrations, severely impairing the quality of images. Adaptive optics can be employed to correct for phase aberrations and improve image quality. However, conventional adaptive optics can only correct a single phase aberration for the whole field of view (isoplanatic correction) while, due to the highly heterogeneous nature of biological tissues, the sample induced aberrations in microscopy often vary throughout the field of view (anisoplanatic aberration), limiting significantly the effectiveness of adaptive optics.

Hartmann-Shack wavefront reconstruction with bitmap image processing.

In this Letter, we report on an algorithm and its implementation to reconstruct the wavefront as a continuous function from a bitmap image of the Hartmann-Shack pattern. The approach works with arbitrary raster geometry and does not require explicit spot definition and phase unwrapping. The system matrix, defining the coefficients of wavefront decomposition in the system of basis functions, is obtained as a result of a series of convolutions and thresholding operations on the reference and sample images.