Scattering scanning near-field optical microscopy (s-SNOM) provides for spectroscopic imaging from molecular to quantum materials with few nanometer deep sub-diffraction limited spatial resolution. However, conventional acquisition methods are often too slow to fully capture a large field of view spatio-spectral dataset. Through this collaboration, STROBE researchers, at CU Boulder and the ALS –Berkeley, demonstrated how the data acquisition time and sampling rate can be significantly reduced while maintaining or even enhancing the physical or chemical image information content. The novel data acquisition and mathematical concepts implemented are based on advanced data compressed sampling, matrix completion, and adaptive random sampling. This research is of particular interest in synchrotron based nano-imaging facilities. This work paves the way to true spatio-spectral chemical and materials nano-spectroscopy with a reduction of sampling rate by up to 30 times.
About Lauren MasonThis author has not yet filled in any details.
So far Lauren Mason has created 78 blog entries.
The need for rapid and accurate image analysis is increasing in electron microscopy studies of nanomaterials. With newly developed fast, high-efficiency electron detectors and automated imaging protocols, incorporating electron microscopy into high throughput materials design efforts is becoming possible. These new capabilities strongly motivate automated methods to extract relevant structural features, such as nanoparticle size, shape, and defect content, from high resolution transmission electron microscopy (HRTEM) data to link these features to bulk properties and study the influence of heterogeneity on bulk behavior. In general, protocols that surpass the accuracy of traditional image analysis and do not require time-consuming manual analysis are needed. Recent advances in image interpretation using deep learning using machine learning make it a promising route toward automatic interpretation of HRTEM micrographs.
In this STROBE collaboration, we demonstrate a pipeline to detect and classify regions of interest in HRTEM micrographs. Our pipeline uses a convolutional neural net (CNN) to identify crystalline regions (nanoparticles) from an amorphous background in the images, and then feeds individual regions of interest into a random forest classifier to detect whether or not they contain a crystallographic defect. Our CNN has a lightweight U-Net architecture and accurately segments a diverse population of nanoparticles with only a small number of training images. After segmentation, individual nanoparticle regions can be isolated and fed directly into existing python tools to extract size and shape statistics. To detect the presence of defects in nanoparticle regions, we implement a random forest classifier. We demonstrated the random forest classifier’s ability to detect stacking faults in the CdSe subset of identified nanoparticles. Both the CNN and classifier demonstrate state of the art performance at their respective tasks. While this work focuses on HRTEM images of nanoparticles supported on a carbon substrate, in principle the tool can be used to detect any regions of crystallinity in HRTEM data.
Nondestructive, high-resolution, chemically specific 3D nanostructure characterization using phase-sensitive EUV imaging reflectometry
Next-generation nano and quantum devices have increasingly complex 3D structure. As the dimensions of these devices shrink to the nanoscale, their performance is often governed by interface quality or precise chemical or dopant composition. A STROBE team from CU Boulder, UCLA, UC Berkeley, as well as laser and nanoelectronics industry partners, worked together for 4 years to design, construct and commission the first phase-sensitive extreme ultraviolet imaging reflectometer. It combines the excellent phase stability of tabletop coherent extreme UV (EUV) light sources, the unique chemical- and phase-sensitivity of coherent EUV imaging, and state-of-the-art algorithms. This tabletop microscope can non-destructively probe surface topography, layer thicknesses, and interface quality, as well as dopant concentrations and profiles. High-fidelity imaging was achieved by implementing phase sensitive imaging at different angles, by using advanced methods to mitigate noise and artifacts in the reconstructed image, and by using a high-brightness, EUV source with excellent intensity and wavefront stability. These measurements were validated through multiscale electron and atomic force microscopy imaging to show that this approach has unique advantages compared with others. Critical to this project were new photon and electron-based imaging methods, advanced algorithms, unique samples, as well STROBE advances in tabletop coherent imaging in transmission and reflection mode. Several STROBE trainees received awards for this effort.
Setting bounds on the absorption cross-sections of molecular systems. There has been a long-running controversy regarding the “quantum advantage” for multiphoton excitation of molecules with entangled photons and if quantum multiphoton imaging can be realized. Although theoretical proposals have been advanced for decades, no experimental work (with the exception of a publication by Jeff Kimble’s group in the 1990s) appeared in the literature until 2006 when reports from a small number of groups began to emerge of a large quantum enhancement (e.g. up to 10 orders of magnitude) of the two photon excitation rate using entangled pairs compared to classical light. Last year, a paper describing a microscope based on the “entangled two-photon absorption” (E2PA) effect was published in Journal of the American Chemical Society. On the other hand, it has emerged from discussions at scientific meetings that many researchers have failed to replicate the results in these numerous publications, or to find any other evidence for this enhancement. As a result, there is considerable skepticism of the publications making these remarkable claims. Unfortunately, these negative results haven’t been published and therefore a rigorous basis for resolving the controversy hasn’t yet been established. Finally, new experiments at JILA have finally set upper-bounds for the E2PA cross-sections in molecular fluorophores, including those investigated in previous reports. We performed both classical and quantum light excitation in the same optical transmission and fluorescence-based systems with rigorously characterized states of light and measurement sensitivities. We find that E2PA cross-sections are at least four to five orders of magnitude smaller than previously reported. Our results imply that the signals and images reported in previous publications are artifacts. Although we don’t expect this contribution to be the last word on the subject, this work introduces a new level of experimental rigor that will lead towards new designs for quantum microscopes and sensors.
Congrats to James Ferguson for Receiving the 2021 Outstanding CE Student Award from the Fort Lewis College Physics & Engineering Department
Congratulations to James Ferguson for Receiving the 2021 Outstanding CE Student Award from the Fort Lewis College Physics & Engineering Department.
Congrats to Elizabeth Blackwater for Receiving the 2021 Don Rabern Department Service Award from the Fort Lewis College Physics & Engineering Department
Congratulations to Elizabeth Blackwater for Receiving the 2021 Don Rabern Department Service Award from the Fort Lewis College Physics & Engineering Department.
Congratulations to Philipp Pelz for receiving an M&M 2020 Postdoctoral Scholar Award for “Determining Atomic Structures from Digitally Defined Regions of Nanocrystals.”
Congratulations to Philipp Pelz for receiving an M&M 2020 Postdoctoral Scholar Award for “Phase Contrast Imaging in Thick, Heterogeneous Samples via S-Matrix Phase Retrieval and Depth Sectioning.”
STROBE is one of the 12 nationwide NSF funded Science and Technology centers. According to Ellen Keister, the STROBE Director of Education: “STROBE research groups have common challenges associated with big data, detectors, as well as pushing the limits of x-ray, electron and visible nano-imaging. STROBE enables research groups to address common challenges, enhance tabletop and national facilities and use new capabilities to address current nano and bio materials challenges.”
While STROBE works on collaboration between investigators within its center, it also encourages collaboration from a younger generation. “STROBE encompasses K-12 outreach, undergraduate education, graduate education programming, essentially focusing on how to build and maintain a top STEM workforce,” Keister comments. “- and do it in a way that is inclusive, and that provides students and trainees with the technical and soft skills and tools they need to be prepared and successful when they go out into the 21st century workforce.”
Welcome to the inaugural episode of the President’s Innovation Podcast, a special CU on the Air series. Host Emily Davies speaks with distinguished professor Margaret Murnane, a fellow at JILA, which is a joint institute of the University of Colorado Boulder and the National Institute of Standards and Technology. Dr. Murnane is also a faculty member in the department of physics and electrical and computer engineering at CU Boulder, and has earned numerous prestigious awards for her work in ultrafast laser and x-ray science.