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Open Access Publications from the University of California

Scholarly Works (7 results)

  • Thesis
  • Peer Reviewed
UCLA Electronic Theses and Dissertations (2018)

Three-dimensional image reconstruction is a scientific undertaking of fundamental importance spanning numerous fields including molecular biology, physical chemistry, materials science, physics, and medicine across length scales ranging from the astronomical to the atomic. Despite the broad-reaching nature of this topic, the underlying mechanics and core mathematics are shared, with the ultimate objective being achieving an interpretable representation of some 3D structure from a series of 2D measurements, and, at the time of this writing, at least three Nobel prizes have been awarded for quantitative 3D imaging applications. Although enormous strides have been made over the past several decades in instrumentation, sample preparation, and experimental methodology, comparatively few improvements have been made to tomgraphic reconstruction algorithms. With the ever-increasing availability of high-performance computing resources, a more compelling argument than ever before can be made for the value of developing novel algorithms and the pursuit of accessible scientific software.

In this work, a set of such developments are reported along with several applications. A new tomographic reconstruction algorithm, termed Generalized Fourier Iterative Reconstruction (GENFIRE), is described in detail. By combining powerful, general constraints in both real and reciprocal space, GENFIRE is shown to produce superior reconstructions compared to existing techniques and provides additional benefits including freedom from single-tilt axis restrictions, denoising through a novel Fourier technique termed resolution extension/suppression, and cross-validation through an adapted version of crystallographic $R_{free}$. In subsequent chapters, GENFIRE is applied in a diverse range of experiments including X-ray ptychographic imaging of cells, cryo-electron tomography of bacteria, correlative X-ray fluorescence imaging of algae, and scanning transmission electron microscopy (STEM) of bimetallic nanoparticles at atomic resolution. GENFIRE is fully open-source with a graphical user interface and is freely-available online.

In the appendices, two additional parallel algorithms are described. The first is an optimized graphics processing unit (GPU) implementation of traditional multislice simulation for simulation of STEM image formation as well as the new Plane Wave Reciprocal-space Interpolated Scattering Matrix (PRISM) algorithm that is capable of reducing computation times of routine calculations from several weeks to a few minutes, and the second is a parallel framework for large-scale 3D phase retrieval of symmetric nanostructures from single diffraction patterns.

    Cover page: Novel 3D Imaging Algorithms and Applications
    • Article
    • Peer Reviewed
    LBL Publications (2017)
    Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. Here, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditional multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic, using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic.
      Cover page: A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy
      • Article
      • Peer Reviewed
      UCLA Previously Published Works (2017)
      Precise localization of nanoparticles within a cell is crucial to the understanding of cell-particle interactions and has broad applications in nanomedicine. Here, we report a proof-of-principle experiment for imaging individual functionalized nanoparticles within a mammalian cell by correlative microscopy. Using a chemically-fixed HeLa cell labeled with fluorescent core-shell nanoparticles as a model system, we implemented a graphene-oxide layer as a substrate to significantly reduce background scattering. We identified cellular features of interest by fluorescence microscopy, followed by scanning transmission X-ray tomography to localize the particles in 3D, and ptychographic coherent diffractive imaging of the fine features in the region at high resolution. By tuning the X-ray energy to the Fe L-edge, we demonstrated sensitive detection of nanoparticles composed of a 22 nm magnetic Fe3O4 core encased by a 25-nm-thick fluorescent silica (SiO2) shell. These fluorescent core-shell nanoparticles act as landmarks and offer clarity in a cellular context. Our correlative microscopy results confirmed a subset of particles to be fully internalized, and high-contrast ptychographic images showed two oxidation states of individual nanoparticles with a resolution of ~16.5 nm. The ability to precisely localize individual fluorescent nanoparticles within mammalian cells will expand our understanding of the structure/function relationships for functionalized nanoparticles.
        Cover page: Correlative cellular ptychography with functionalized nanoparticles at the Fe L-edge
        • Article
        • Peer Reviewed
        UCLA Previously Published Works (2017)
        Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE), for high-resolution 3D reconstruction from a limited number of 2D projections. GENFIRE first assembles a 3D Fourier grid with oversampling and then iterates between real and reciprocal space to search for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques through numerical simulations and by experimentally reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. Equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines.
          Cover page: GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging
          • Article
          • Peer Reviewed
          UCLA Previously Published Works (2015)
          A structural understanding of whole cells in three dimensions at high spatial resolution remains a significant challenge and, in the case of X-rays, has been limited by radiation damage. By alleviating this limitation, cryogenic coherent diffractive imaging (cryo-CDI) can in principle be used to bridge the important resolution gap between optical and electron microscopy in bio-imaging. Here, the first experimental demonstration of cryo-CDI for quantitative three-dimensional imaging of whole frozen-hydrated cells using 8 keV X-rays is reported. As a proof of principle, a tilt series of 72 diffraction patterns was collected from a frozen-hydrated Neospora caninum cell and the three-dimensional mass density of the cell was reconstructed and quantified based on its natural contrast. This three-dimensional reconstruction reveals the surface and internal morphology of the cell, including its complex polarized sub-cellular structure. It is believed that this work represents an experimental milestone towards routine quantitative three-dimensional imaging of whole cells in their natural state with spatial resolutions in the tens of nanometres.
            Cover page: Three-dimensional coherent X-ray diffractive imaging of whole frozen-hydrated cells
            • Article
            • Peer Reviewed
            UC Berkeley Previously Published Works (2017)
            Perfect crystals are rare in nature. Real materials often contain crystal defects and chemical order/disorder such as grain boundaries, dislocations, interfaces, surface reconstructions and point defects. Such disruption in periodicity strongly affects material properties and functionality. Despite rapid development of quantitative material characterization methods, correlating three-dimensional (3D) atomic arrangements of chemical order/disorder and crystal defects with material properties remains a challenge. On a parallel front, quantum mechanics calculations such as density functional theory (DFT) have progressed from the modelling of ideal bulk systems to modelling 'real' materials with dopants, dislocations, grain boundaries and interfaces; but these calculations rely heavily on average atomic models extracted from crystallography. To improve the predictive power of first-principles calculations, there is a pressing need to use atomic coordinates of real systems beyond average crystallographic measurements. Here we determine the 3D coordinates of 6,569 iron and 16,627 platinum atoms in an iron-platinum nanoparticle, and correlate chemical order/disorder and crystal defects with material properties at the single-atom level. We identify rich structural variety with unprecedented 3D detail including atomic composition, grain boundaries, anti-phase boundaries, anti-site point defects and swap defects. We show that the experimentally measured coordinates and chemical species with 22 picometre precision can be used as direct input for DFT calculations of material properties such as atomic spin and orbital magnetic moments and local magnetocrystalline anisotropy. This work combines 3D atomic structure determination of crystal defects with DFT calculations, which is expected to advance our understanding of structure-property relationships at the fundamental level.
              Cover page: Deciphering chemical order/disorder and material properties at the single-atom level
              • Article
              • Peer Reviewed
              UCLA Previously Published Works (2018)
              We report 3D coherent diffractive imaging (CDI) of Au/Pd core-shell nanoparticles with 6.1 nm spatial resolution with elemental specificity. We measured single-shot diffraction patterns of the nanoparticles using intense x-ray free electron laser pulses. By exploiting the curvature of the Ewald sphere and the symmetry of the nanoparticle, we reconstructed the 3D electron density of 34 core-shell structures from these diffraction patterns. To extract 3D structural information beyond the diffraction signal, we implemented a super-resolution technique by taking advantage of CDI's quantitative reconstruction capabilities. We used high-resolution model fitting to determine the Au core size and the Pd shell thickness to be 65.0 ± 1.0 nm and 4.0 ± 0.5 nm, respectively. We also identified the 3D elemental distribution inside the nanoparticles with an accuracy of 3%. To further examine the model fitting procedure, we simulated noisy diffraction patterns from a Au/Pd core-shell model and a solid Au model and confirmed the validity of the method. We anticipate this super-resolution CDI method can be generally used for quantitative 3D imaging of symmetrical nanostructures with elemental specificity.
                Cover page: Single-shot 3D coherent diffractive imaging of core-shell nanoparticles with elemental specificity.
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