Micrographs with Cloud Computing


manage, analyze, and simulate tens of thousands of images from hundreds of datasets collected from different samples, from different wells, and analyzed by different microscopists over several years. For simple rock types, such as Niobrara chalk, a single imaging method is sufficient to capture both the smallest feature and large enough field of view to be rep- resentative (Figures 2a,2b). Relative permeabilities for this extremely tight rock were computed and validated for the first time, which played a critical role in reservoir engineer- ing decisions [6]. By comparison, complex rock types, such as Alaska sandstone, require multiple imaging modalities and more sophisticated modeling (Figures 2c,2d). Imaging of spe- cific configurations of pores over a large size range in a single rock type was essential in this case for building a model that helps in understanding how microstructure variations affect permeability. Materials science. Modern electrochemical energy


storage and power generation devices depend on micro- structures. However, each functional layer, or component, of these devices has a distinctive length scale. Te design, characterization, and optimization of the structures demand both high-resolution imaging and device-scale imaging, which are difficult, if not impossible, to achieve simultane- ously. Te development of 3D microscopy techniques and the use of different instruments to examine the same region allows observations at various length scales. By combining AI and high-performance computing, a massive amount of 3D imaging data at various scales can be integrated. In addi- tion to the benefit of direct visualization of microstructures at various scales, image-based simulation overcomes vari- ous difficulties and challenges from physical experiments. Figure 3 shows DigiM I2S soſtware applied to a proton exchange membrane (PEM) fuel cell. Te raw tomographs were acquired in a Technai Osiris TEM (Termo Fisher Sci- entific, Waltham, MA), in an Helios Nanolab 650 FIB-SEM (Termo Fisher Scientific, Waltham, MA), and in a Versa 520 X-ray MicroCT (Carl Zeiss Microscopy, Pleasanton, CA). Tese 3D images at three length scales, each using a different tomographic technique, were integrated with DigiM I2S. In the catalyst layer, nanometer-scale measurements were con- ducted on the TEM tomography volume, where the Pt cata- lyst particles were fully resolved enabling estimates of their contact surface areas in relation to changes in air flow and electrolyte. Te calculated effective diffusivity and conduc- tivity were then applied as effective properties of the porous media simulations using the FIB-SEM data at micrometer scale. Tese data were then iteratively applied to millimeter- scale effective media simulations using the MicroCT data. Te multiscale imaging combined with multiscale simula- tions, over a scale range of eight orders of magnitude, helped to evaluate microstructures of various designs of PEM fuel cell samples [7].


Limitations Internet availability and bandwidth are essential in


accessing the cloud. Local client software serves as one solution to limited internet availability since the user will only need to access the internet occasionally. Customiza- tion can be incorporated into cloud software, like DigiM’s


32


I2S, to provide bandwidth intelligence to users with limited bandwidth. Browser technology potentially limits memory use


and the graphic visualization of a cloud-based system. However, as cloud-computing becomes more mainstream, browser technology should improve to meet the demand. A common misconception regarding the cloud is that all the stored data is public. Cloud computing is a technology plat- form. Whether or not the data deployed on the technology platform are public or private is solely dependent on user preferences.


Conclusion Cloud computing and AI can be more than just the


solution to the current inadequate state of image data man- agement; it can be an enabling technology for industrial innovation. Without the extraneous costs and equipment that come with desktop-based approaches, a cloud-based approach is a cost-efficient way to store and analyze imag- ing data. With its logical storage and AI-based processing capacities, a cloud-based approach enables advanced algo- rithmic analysis of data that current desktop-based solutions are unable to handle. Te state of cloud-computing today is exciting in that it has already contributed to the advancement of microscopy and microanalysis, but it has yet to reach its full potential.


Acknowledgments Te authors acknowledge their respective organizations


for the permission to publish the images. We greatly appreci- ate the advice and guidance from Professor Charles Lyman, Editor-in-Chief of this publication.


References [1] O Lézoray et al., EURASIP J Adv Sig Pr 2008(1) (2008) 927950.


[2] DigiM I2S. http://www.digimsolution.com/soſtware (accessed December 26, 2018).


[3] S Zhang et al., Microsc Microanal 24 (S1) (2018) 1400–01. [4] D Wu and S Zhang. “Microimaging Characterization and Release Prediction of Controlled Release Microspheres,” 18-A-137-CRS. Controlled Release Society Annual Meeting and Exposition, New York City, New York, July 22–24, 2018.


[5] A Byrnes et al., “Application of Integrated Core and Mul- tiscale 3-D Image Rock Physics to Characterize Porosity, Permeability, Capillary Pressure, and Two- and Tree- Phase Relative Permeability in the Codell Sandstone, Denver Basin, Colorado.” Unconventional Resources Technology Conference, URTeC 2901840, Houston, Texas, July 23–25, 2018.


[6] AP Byrnes et al., “Application of Integrated Core and 3D Image Rock Physics to Characterize Niobrara Chalk Properties Including Relative Permeability with Bound- water Effect.” Unconventional Resources Technology Conference, URTeC 2670963, Austin, Texas, July 24–26, 2017.


[7] J Jankovic et al., “Multi-scale imaging and transport mod- eling for fuel cell electrode,” J Mater Res, 2017 MRS Fall Focus Issue, 34(4) (2019). doi: 10.1557/jmr.2018.458.


www.microscopy-today.com • 2019 March


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