Microsc. Microanal. 23, 1150–1158, 2017 doi:10.1017/S1431927617012764
© MICROSCOPY SOCIETY OF AMERICA 2017
A Simple Preparation Method for Full-Range Electron Tomography of Nanoparticles and Fine Powders
Elliot Padgett,1,* Robert Hovden,1,2 Jessica C. DaSilva,3 Barnaby D. A. Levin,1 John L. Grazul,4 Tobias Hanrath,3 and David A. Muller1,5
1School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14853, USA 2Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109 USA 3School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, USA 4Cornell Center for Materials Research, Cornell University, Ithaca, NY 14853, USA 5Kavli Institute at Cornell for Nanoscale Science, Ithaca, NY 14853, USA
Abstract: Electron tomography has become a valuable and widely used tool for studying the three-dimensional nanostructure of materials and biological specimens. However, the incomplete tilt range provided by conventional sample holders limits the fidelity and quantitative interpretability of tomographic images by leaving a “missing wedge” of unknown information in Fourier space. Imaging over a complete range of angles eliminates missing wedge artifacts and dramatically improves tomogram quality. Full-range tomography is usually accomplished using needle-shaped samples milled from bulk material with focused ion beams, but versatile specimen preparation methods for nanoparticles and other fine powders are lacking. In this work, we present a new preparation technique in which powder specimens are supported on carbon nanofibers that extend beyond the end of a tungsten needle. Using this approach, we produced tomograms of platinum fuel cell catalysts and gold-decorated strontium titanate photocatalyst specimens. Without the missing wedge, these tomograms are free from elongation artifacts, supporting straightforward automatic segmentation and quantitative analysis of key materials properties such as void size and connectivity, and surface area and curvature. This approach may be generalized to other samples that can be dispersed in liquids, such as biological structures, creating new opportunities for high-quality electron tomography across disciplines.
Key words: electron tomography, missing wedge, nanoparticles, sample preparation, carbon nanofiber INTRODUCTION
Electron tomography is a widely used tool in biological and physical science and engineering due to its ability to reveal the three-dimensional (3D) structure of inhomogeneous specimens at nanometer length scales (Weyland & Midgley, 2016). Tomography provides valuable information unavail- able in conventional two-dimensional (2D) imaging by resolving structures that are ambiguous in projection and allowing quantitative measurement of intrinsically 3D geo- metric properties, such as surface area and volume. A 3D tomogram is produced by combining the information in a series of 2D projection images taken at different specimen tilts, where, conceptually, each image contributes informa- tion to fill a corresponding 2D plane in the 3D Fourier transform of the specimen. Ideally, the specimen would be imaged over a complete 180° rotation to provide knowledge of the specimen covering all of Fourier space. In practice, however, a complete rotation cannot be achieved with con- ventional specimen holders in a (scanning) transmission elec- tron microscope [(S)TEM], as the sides of the holder or grid obscure the sample at high tilts (above about ±75° for com- mercial electron tomography holders currently available).
*Corresponding author.
esp85@cornell.edu Received July 28, 2017; accepted October 30, 2017
The lack of images at high tilts leaves a “missing wedge” of unsampled information in Fourier space. The missing wedge degrades reconstruction quality by introducing blurring along the optic axis and shadow artifacts in the perpendicular direction in the reconstructed plane (e.g., Mastronarde, 1997; Midgley & Weyland, 2003). These artifacts reduce the 3D imaging resolution, introduce spurious intensity variations, and distort apparent shapes in the tomogram. In complex, real- world structures this makes qualitative interpretation challen- ging and compromises the accuracy of segmentation and quantitative analysis. Multiple methods have been developed to mitigate or
solve the missingwedge problem, fromalgorithms that reduce artifacts to milling needle-shaped samples for imaging over a complete angular range. Recently developed reconstruction algorithms, such as discrete tomography (Batenburg et al., 2009) and compressive sensing tomography (Saghi et al., 2011; Goris et al., 2012; Leary et al., 2013), have shown some ability to reduce artifacts caused by the missing wedge. These algorithms are based on assumed prior knowledge of the specimen,which provides ameans to make an informed guess at the missing information. However, the assumptions embedded in each algorithm and its reconstruction para- meters are not universally applicable and the reconstruction will thus depend on subjective choices made by the user. Furthermore, these advanced algorithms remain poorly
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