TechConnect World 2020
Co-Located with Nanotech 2020 SBIR/STTR Spring AI TechConnect
Nanotech 2020
 

Materials Characterization & Imaging

Nanoscale Materials Characterization

Submit your Poster Abstract - due April 10

Please first review the information for authors — abstract submission guidelines.

 

Symposium Co-Chairs

Greg HaugstadGreg Haugstad
Technical Staff Member & Director, Characterization Facility (CharFac)
University of Minnesota

Dalia YablonDalia Yablon
Technical Program Chair
TechConnect World Innovation Conference

Key Speakers

Bede PittengerProbing the time-temperature relationship of mechanical properties in polymer composites
Bede Pittenger
Application Scientist, Bruker Nano

This year's symposium will focus on innovations in nanoscale materials characterization including new method development as well as industry-specific applications. Submissions are also invited for special sessions focused on machine learning for materials characterization and imaging (in conjunction with the AI TechConnect Conference); and on industrial applications of x-ray scattering methods.

 
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Symposium Sessions

Monday June 29

10:30Machine Learning for Optical and Radiative Microscopy
1:30Machine Learning for Probe and Electron Microscopy

Tuesday June 30

10:30Frontiers of Characterization
4:00Materials Characterization - Posters
4:00Machine Learning for Materials Characterization & Imaging - Posters

Symposium Program

Monday June 29

10:30Machine Learning for Optical and Radiative Microscopy
Session chair: Greg Haugstad, University of Minnesota, Dalia Yablon, TechConnect, US
Autonomous Synchrotron X-ray Diffraction for Phase Mapping and Materials Optimization
A.G. Kusne, National Institute of Standards & Technology, US
Real-time 3D Coherent Diffraction Data Inversion Through Deep Learning
M. Cherukara, H. Chan, T. Zhou, Y. Nashed, S. Sankaranarayanan, M. Holt, R. Harder, Argonne National Lab, US
Machine learning based detection and deep learning based image inpainting of preparation artefacts in micrographs
A. Jansche, A.K. Choudhary, T. Bernthaler, G. Schneider, Aalen University, DE
Improvement of Oil Spill Mapping from Satellite Image Using Directional Median Filtering with Articicial Neural Network
S.H. Park, H.S. Jung, University of Seoul, KR
Application of deep convolutional neural networks (DCNN) in materials microscopy for the automated detection of defects
O. Badmos, A. Kopp, D. Hohs, R. Büttner, T. Bernthaler, G. Schneider, Hochschule Aalen, DE
Machine Learning for Materials Characterization and Imaging
M.K.Y. Chan, Argonne National Laboratory, US
1:30Machine Learning for Probe and Electron Microscopy
Session chair: Dalia Yablon, TechConnect, US, Greg Haugstad, University of Minnesota, US
TBA
M. Scott, University of California, Berkeley, US
Artificially Intelligent Transmission Electron Microscopy
H. Xin, University of California, Irvine, US
Correlative and causal machine learning in scanning probe and electron microscopy
M. Ziatdinov, Oak Ridge National Laboratory, US
Opportunities in Machine Learning for Atomic Force Microscopy
I. Chakraborty, D. Yablon, Stress Engineering Services, Inc., US
Intermodulation AFM a novel multifrequency technique for material insight
D. Forchheimer, Intermodulation Products AB, SE
Fourier-reconstructed force fingerprints in AFM: machine learning for novel contrast
G. Haugstad, A. Avery, R. Rahn, S. Hubig, B. Luo, H.-S. Lee, A. McCormick, D. Forschheimer, University of Minnesota, US

Tuesday June 30

10:30Frontiers of Characterization
Session chair: Greg Haugstad, University of Minnesota, US
Probing the time-temperature relationship of mechanical properties in polymer composites
B. Pittenger, S. Osechinskiy, J. Thornton, S. Loire, T. Mueller, Bruker AXS, US
Innovations in Electron Microscopy for Quantum Materials Discovery
D.C. Bell, C.O. Keskinbora, Harvard University, US
Temperature-Dependent Thermal Diffuse Scattering Measurements of Nanomaterials using Scanning Transmission Electron Microscopy
G. Wehmeyer, Rice University, US
Unique Analytical Capabilities in FE-SEM Utilizing Soft X-Ray Spectrometer (SXES)
N. Erdman, S. Asahina, Y. Uetake, JEOL USA Inc, US
Nanofluidic Cells Imaging and Scattering Measurements of Liquids and Gases
A. Kanwal, E.H. Gann, B.R. Ilic, G. Holland, S. Mukherjee, D. DeLongchamp, J.A. Liddle, National Institute of Standards and Technology, US
4:00Materials Characterization - Posters
Effects of Ga–Cr substitution on structural and magnetic properties of hexaferrite (BaFe12O19) synthesized by sol–gel auto-combustion route
I. Ali, Higher Education Department, Government of Punjab, PK
X-ray imaging of colloidal packing
Y. Kim, G. Oh, W. Jung, B.M. Weon, SungKyunKwan University, KR
Portable material analyser
V. Vishnyakov, University of Huddersfield, UK
Line Confocal Imaging Technology in In-situ 3D, 2D and Tomographic Characterization of Specular and Transparent Parts, Assemblies and Continuous Products
J. Saily, FocalSpec - LMI Technologies (USA), Inc., US
Secondary Ion Mass Spectrometry Image Depth Profiling for Visualizing the Uptake and Biodistribution of Gold Nanoparticles in Caenorhabditis elegans
M.E. Johnson, J. Bennett, A.R. Montoro Bustos, S.K. Hanna, A. Kolmakov, N. Sharp, E.J. Petersen, P.E. Lapasset, C.M. Sims, K.E. Murphy, B.C. Nelson, National Institute of Standards & Technology, US
Spectral Characterization of Tin Dioxide for Gas-Sensing Applications
B. Concepcion, H. Alghamdi, S. Baliga, P. Misra, Howard University, US
Phenomenological modeling of apparent viscosity based on the degree of cure of an EPDM elastomer
S. Gómez-Jimenez, A.M. Becerra-Ferreiro., E. Jareño-Betancourt, J. Vázquez-Penagos, Autonomous University of Zacatecas, MX
A Self-Driving Laboratory for Accelerated Materials Discovery
C.P. Berlinguette, J.E. Hein, A. Aspuru-Guzik, B.P. MacLeod, F.G.L. Parlane, The University of British Columbia, CA
Characterization and Growth Mechanism of APCVD Grown 2D monolayer WS2
M.B. Azim, M. Adachi, Simon Fraser University, CA
4:00Machine Learning for Materials Characterization & Imaging - Posters
Machine learning for microstructures classification in functional materials
A.K. Choudhary, A. Jansche, O. Badmos, T. Bernthaler, G. Schneider, Aalen University, DE
A Machine Learning Driven Damage Quantification Algorithm in moisture-contaminated composites.
R.D. Guha, North Carolina State University, US
Application of Savitzky-Golay(SG) filter in image processing
S. Karmakar, S. Karmakar, Farmingdale State College- State University of New York, US

Topics & Application Areas

  • Innovations in Nanomaterials Characterization
  • Special Session: Machine Learning for Materials Characterization and Imaging
  • Special Session: Scattering Methods in Industrial Applications
  • Other
 
 
2019 Sponsors & Partners
2019 Sponsors & Partners