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Title: Nanomaterial datasets to advance tomography in scanning transmission electron microscopy

Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co 2 P nanocrystal, platinum nanoparticles on a carbon nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data.
Authors:
 [1] ;  [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [4] ;  [7] ;  [8] ;  [8] ;  [9] ;  [10] ;  [10] ;  [8] ; ORCiD logo [7] ;  [11] ;  [4] ; ORCiD logo [11] ;  [1]
  1. Cornell Univ., Ithaca, NY (United States). School of Applied and Engineering Physics
  2. Univ. of California, Los Angeles, CA (United States). Dept. of Physics and Astronomy, California NanoSystems Inst.; National Sun Yat-SEn Univ., Kaohsiung (Taiwan). Dept. of Physics
  3. Univ. of California, Los Angeles, CA (United States). Dept. of Physics and Astronomy, California NanoSystems Inst.; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Center for Electron Microscopy
  4. Univ. of California, Los Angeles, CA (United States). Dept. of Physics and Astronomy, California NanoSystems Inst.
  5. Univ. of Birmingham (United Kingdom). Nanoscale Physics Research Lab.
  6. Cornell Univ., Ithaca, NY (United States). Dept. of Physics
  7. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Center for Electron Microscopy
  8. Cornell Univ., Ithaca, NY (United States). Dept. of Materials Science and Engineering
  9. Cornell Univ., Ithaca, NY (United States). Dept. of Chemistry and Chemical Biology; Huazhong Univ. of Science and Technology, Wuhan (China). School of Chemistry and Chemical Engineering
  10. Cornell Univ., Ithaca, NY (United States). Dept. of Chemistry and Chemical Biology
  11. Cornell Univ., Ithaca, NY (United States). School of Applied and Engineering Physics, Kavli Inst. for Nanoscale Science
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Scientific Data
Additional Journal Information:
Journal Volume: 3; Journal ID: ISSN 2052-4463
Publisher:
Nature Publishing Group
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; fuel cells; nanoparticles; transmission electron microscopy
OSTI Identifier:
1379388

Levin, Barnaby D. A., Padgett, Elliot, Chen, Chien-Chun, Scott, M. C., Xu, Rui, Theis, Wolfgang, Jiang, Yi, Yang, Yongsoo, Ophus, Colin, Zhang, Haitao, Ha, Don-Hyung, Wang, Deli, Yu, Yingchao, Abruña, Hector D., Robinson, Richard D., Ercius, Peter, Kourkoutis, Lena F., Miao, Jianwei, Muller, David A., and Hovden, Robert. Nanomaterial datasets to advance tomography in scanning transmission electron microscopy. United States: N. p., Web. doi:10.1038/sdata.2016.41.
Levin, Barnaby D. A., Padgett, Elliot, Chen, Chien-Chun, Scott, M. C., Xu, Rui, Theis, Wolfgang, Jiang, Yi, Yang, Yongsoo, Ophus, Colin, Zhang, Haitao, Ha, Don-Hyung, Wang, Deli, Yu, Yingchao, Abruña, Hector D., Robinson, Richard D., Ercius, Peter, Kourkoutis, Lena F., Miao, Jianwei, Muller, David A., & Hovden, Robert. Nanomaterial datasets to advance tomography in scanning transmission electron microscopy. United States. doi:10.1038/sdata.2016.41.
Levin, Barnaby D. A., Padgett, Elliot, Chen, Chien-Chun, Scott, M. C., Xu, Rui, Theis, Wolfgang, Jiang, Yi, Yang, Yongsoo, Ophus, Colin, Zhang, Haitao, Ha, Don-Hyung, Wang, Deli, Yu, Yingchao, Abruña, Hector D., Robinson, Richard D., Ercius, Peter, Kourkoutis, Lena F., Miao, Jianwei, Muller, David A., and Hovden, Robert. 2016. "Nanomaterial datasets to advance tomography in scanning transmission electron microscopy". United States. doi:10.1038/sdata.2016.41. https://www.osti.gov/servlets/purl/1379388.
@article{osti_1379388,
title = {Nanomaterial datasets to advance tomography in scanning transmission electron microscopy},
author = {Levin, Barnaby D. A. and Padgett, Elliot and Chen, Chien-Chun and Scott, M. C. and Xu, Rui and Theis, Wolfgang and Jiang, Yi and Yang, Yongsoo and Ophus, Colin and Zhang, Haitao and Ha, Don-Hyung and Wang, Deli and Yu, Yingchao and Abruña, Hector D. and Robinson, Richard D. and Ercius, Peter and Kourkoutis, Lena F. and Miao, Jianwei and Muller, David A. and Hovden, Robert},
abstractNote = {Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co 2 P nanocrystal, platinum nanoparticles on a carbon nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data.},
doi = {10.1038/sdata.2016.41},
journal = {Scientific Data},
number = ,
volume = 3,
place = {United States},
year = {2016},
month = {6}
}

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