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Title: A sub-sampled approach to extremely low-dose STEM

Abstract

The inpainting of randomly sub-sampled images acquired by scanning transmission electron microscopy (STEM) is an attractive method for imaging under low-dose conditions (≤ 1 e -2) without changing either the operation of the microscope or the physics of the imaging process. We show that 1) adaptive sub-sampling increases acquisition speed, resolution, and sensitivity; and 2) random (non-adaptive) sub-sampling is equivalent, but faster than, traditional low-dose techniques. Adaptive sub-sampling opens numerous possibilities for the analysis of beam sensitive materials and in-situ dynamic processes at the resolution limit of the aberration corrected microscope and is demonstrated here for the analysis of the node distribution in metal-organic frameworks (MOFs).

Authors:
 [1];  [2];  [3];  [4];  [5];  [4];  [6];  [5]
  1. OptimalSensing, Southlake, Texas 76092, USA; Duke University, ECE, Durham, North Carolina 27708, USA
  2. Rice University, ECE, Houston, Texas 77005, USA
  3. Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
  4. Pacific NW National Laboratory, Richland, Washington 99354, USA
  5. Pacific NW National Laboratory, Richland, Washington 99354, USA; University of Liverpool, Materials Engineering, Liverpool L69 3GH, United Kingdom
  6. Duke University, ECE, Durham, North Carolina 27708, USA
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1421341
Report Number(s):
PNNL-SA-126577
Journal ID: ISSN 0003-6951
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Applied Physics Letters; Journal Volume: 112; Journal Issue: 4
Country of Publication:
United States
Language:
English
Subject:
compressive sensing

Citation Formats

Stevens, A., Luzi, L., Yang, H., Kovarik, L., Mehdi, B. L., Liyu, A., Gehm, M. E., and Browning, N. D.. A sub-sampled approach to extremely low-dose STEM. United States: N. p., 2018. Web. doi:10.1063/1.5016192.
Stevens, A., Luzi, L., Yang, H., Kovarik, L., Mehdi, B. L., Liyu, A., Gehm, M. E., & Browning, N. D.. A sub-sampled approach to extremely low-dose STEM. United States. doi:10.1063/1.5016192.
Stevens, A., Luzi, L., Yang, H., Kovarik, L., Mehdi, B. L., Liyu, A., Gehm, M. E., and Browning, N. D.. Mon . "A sub-sampled approach to extremely low-dose STEM". United States. doi:10.1063/1.5016192.
@article{osti_1421341,
title = {A sub-sampled approach to extremely low-dose STEM},
author = {Stevens, A. and Luzi, L. and Yang, H. and Kovarik, L. and Mehdi, B. L. and Liyu, A. and Gehm, M. E. and Browning, N. D.},
abstractNote = {The inpainting of randomly sub-sampled images acquired by scanning transmission electron microscopy (STEM) is an attractive method for imaging under low-dose conditions (≤ 1 e-Å2) without changing either the operation of the microscope or the physics of the imaging process. We show that 1) adaptive sub-sampling increases acquisition speed, resolution, and sensitivity; and 2) random (non-adaptive) sub-sampling is equivalent, but faster than, traditional low-dose techniques. Adaptive sub-sampling opens numerous possibilities for the analysis of beam sensitive materials and in-situ dynamic processes at the resolution limit of the aberration corrected microscope and is demonstrated here for the analysis of the node distribution in metal-organic frameworks (MOFs).},
doi = {10.1063/1.5016192},
journal = {Applied Physics Letters},
number = 4,
volume = 112,
place = {United States},
year = {Mon Jan 22 00:00:00 EST 2018},
month = {Mon Jan 22 00:00:00 EST 2018}
}