A STROBE team led by Prof. Waller, created a novel computational imaging autofocusing system for microscopes utilizing an of-the-shelf LED and a machine learning algorithm with optical physics knowledge incorporated into its design.
Artificial neural networks enable the extraction of multiple parameters, including spectral and depth information, from unmodified experimental single-molecule images for multidimensional super-resolution microscopy. Good color separation is thus achieved in fixed cells using two dyes ~80 nm apart in emission wavelength.
Label-free chemical nano-imaging in dense molecular environments has remained a long-standing challenge. STROBE Thrust lead Markus Raschke led a team of academic and national laboratory scientists from LBNL, Boulder and Berkeley to speed-up scanning near-field optical microscopy (s-SNOM) by a factor of 10! This remarkable achievement allowed the team to image the surface shape and chemistry of biological samples, including mollusk shells, with nanometer spatial resolution.
UCLA STROBE researchers show how a radiofrequency cavity can be used as an electron longitudinal lens in order to produce a highly magnified temporal replica of an ultrafast process, and, in combination with a deflecting cavity, enable streaked electron images of optical-frequency phenomena, taking advantage of the time-stretch concept.
Imaging fast moving samples such as living biological samples is challenging because the images can appear blurred if the strobe light is not fast enough. This is an issue for high-quality quantitative phase imaging, which was too slow for many samples (image on right). STROBE faculty Laura Waller from Berkeley led a team to develop a new approach to reduce this blur, that enhances the speed to match the frame rate of the detector, to enable much clearer imaging of many biological systems (image on left).
A STROBE team led by Prof. Miao, in collaboration with Argonne National Laboratory, implemented hybrid 3D X-ray microscopy by combining cryogenic hard X-ray ptychography and X-ray fluorescence microscopy. Here, STROBE’s advanced GENFIRE tomography algorithm was used to correlate high resolution ultrastructure mapping and elemental distributions in an unlabeled, frozen-hydrated green algae.
Traditional transmission electron microscopy (TEM) excels at determining the physical structure of a sample, but reveals little about the electronic structure. STROBE faculty Chris Regan at UCLA developed a new technique based on secondary electron emission (SE) and electron beam induced current (EBIC) to image the electronic structure of functioning devices with a TEM-like spatial resolution. He used this new SEEBIC technique to map the conductance of a nanodevice containing a thin silicon membrane (brown and green) separating two electrodes (blue).
The first demonstration of computational ghost imaging with electrons has been carried out at UCLA. A digital micromirror device is used to directly modulate the photocathode drive laser to control the transverse distribution of a relativistic electron beam incident on a sample. Correlating the structured illumination pattern to the total sample transmission then retrieves the target image, avoiding need for a pixelated detector. In our example, we use a compressed sensing framework to improve the reconstruction quality and reduce the number of shots compared to raster scanning a small beam across the target. Compressed electron ghost imaging can reduce both acquisition time and sample damage in experiments for which spatially resolved detectors are unavailable (e.g. spectroscopy) or in which the experimental architecture precludes full frame direct imaging.
A STROBE team led by Ke Xu at Berkeley adapted advanced super-resolution microscopy techniques developed by the Weiss group at UCLA, to rapidly image graphene nanoribbons (GNRs) and carbon nanotubes (CNTs). These are important functional materials with great promise in nano-electronics and other applications. However, it has been a challenge to visualize and characterize them in a high-throughput manner due to their small physical dimensions. Temporal fluorescence intensity fluctuations in these samples enabled the reconstruction of SRM images through superresolution optical fluctuation imaging (SOFI) and the related superresolution radial fluctuation (SRRF) analysis methods.
The Miao group at UCLA developed a new coherent diffractive imaging technique for capturing fast nanoscale dynamics. The concept leveraged time-invariant spatial redundancy in the field of view as a powerful constraint in the phase retrieval process. In addition, the introduction of high scattering features in the spatially redundant region also suggests the potential for dose-reduced imaging. Boulder and UCLA are collaborating to apply this in-situ imaging to materials undergoing phase transitions.