Materials Characterization & Imaging

Nanoscale Materials Characterization

Symposium Co-Chairs

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

Dalia Yablon
Technical Program Chair
TechConnect World Innovation Conference

Alex Norman
Executive Director
Princeton Institute of Materials

2022 Key Speakers

Machine learning for recognition and classification of AFM images
Igor Sokolov
Professor, Tufts University

Effect of user fees on core facility income and user behavior: It’s not what you think
Jerry Hunter
Director, Wisconsin Centers for Nanoscale Technology

Enhancing or Diminishing Sensitivity in Multifrequency AFM
Babak Eslami
Assistant Professor, Widener University

Friction Property of Ti3C2Tx MXene at the Nanoscale
Arzu Colak
Research Assistant Professor, Clarkson University

Voxel Scale Characterization of Photopolymer Additive Manufacturing
Jason Killgore
Project Leader, National Institute of Standards and Technology

Nanoscale Materials Analysis using AFM-IR
Liang Gong
Senior Research Scientist, 3M

Imaging and analysis - an engine for the discovery and innovation
Nan Yao
Professor & Founding Director, Princeton University Imaging and Analysis Center

The North Carolina Research Triangle Nanotechnology Network (RTNN)
Jacob Jones
Professor, North Carolina State University

Comparison Analysis of 2D Nanomaterial Dispersions using Analytical Ultracentrifugation and Microscopy Methods
Christopher Sims
Research Chemist, National Institute of Standards and Technology

Quantitative Piezoresponse Force Microscopy for Every User
Jason Killgore
Project Leader, NIST

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.

Back to Top ↑ 2022 Symposium Sessions
	Monday June 13
10:30	Advanced Characterization Opportunities at Academic Centers of Excellence
1:30	Material Characterization & Imaging
	Tuesday June 14
9:00	Characterization with Scanning Probe Microscopy
1:30	Machine Learning for Characterization

2022 Symposium Program
	Monday June 13

10:30	Advanced Characterization Opportunities at Academic Centers of Excellence	Chesapeake A
	Session chair: Alex Norman, Modern Meadow, US
10:30	Imaging and analysis - an engine for the discovery and innovation N. Yao, Princeton University, US
10:55	Effect of user fees on core facility income and user behavior: It’s not what you think J. Hunter, University of Wisconsin-Madison, US
11:20	The North Carolina Research Triangle Nanotechnology Network (RTNN) J.L. Jones, North Carolina State University, US

1:30	Material Characterization & Imaging	Chesapeake A
	Session chair: Greg Haugstad, University of Minnesota, US
1:30	Comparison Analysis of 2D Nanomaterial Dispersions using Analytical Ultracentrifugation and Microscopy Methods C. Sims, National Institute of Standards and Technology, US
1:55	Nanoplastic arrays – a new order of microspectroscopy standards A. Madison, D. Westly, B. Ilic, C. Copeland, A. Pintar, C. Camp, J. Liddle, S. Stavis, National Institute of Standards and Technology, US
2:15	Ceramic sintering and properties characterization based on solid mechanics H. Camacho Montes, Y. Espinosa Almeyda, J.D. Gamboa Garay, L.E. Barraza de León, A. Vega Siverio, I.M. Espinoza Ochoa, J.A. Otero Hernández, R. Rodríguez Ramos, B.J. Mederos Madrazo, F.J. Sabina, R.K. Bordia, Universidad Autónoma de Ciudad Juárez, MX
2:35	Rheo-Raman microscopy for crystallization and crosslinking A. Kotula, National Institute of Standards and Technology, US
2:55	Rapid multiphoton autofluorescence lifetime imaging of retinal tissue Y-I Chen, T.D. Nguyen, Y-J Chang, S-C Liao, Y-A Kuo, S. Hong, G. Rylander III, S.R. Santacruz, T. Yeh, University of Texas at Austin, US
	Tuesday June 14

9:00	Characterization with Scanning Probe Microscopy	Chesapeake 10
	Session chair: Greg Haugstad, University of Minnesota, US
9:00	Quantitative Piezoresponse Force Microscopy for Every User J. Killgore, National Institute of Standards and Technology, US
9:25	Nanoscale Materials Analysis using AFM-IR L. Gong, 3M Company, US
9:50	Friction Property of Ti3C2Tx MXene at the Nanoscale A. Colak, Clarkson University, US
10:15	Enhancing or Diminishing Sensitivity in Multifrequency AFM B. Eslami, Widener, US

1:30	Machine Learning for Characterization	Chesapeake 10
	Session chair: Alex Norman, Modern Meadow, US
1:30	Machine Learning for Automated Experiments in Charged Particle Beam Tools A. Belianinov, Sandia National Laboratories, US
1:55	Machine learning for recognition and classification of AFM images I. Sokolov, Tufts University, US
2:20	Deep learning to predict structure property relationships with AFM D. Yablon, I. Chakraborty, SurfaceChar LLC, Cognite, US
2:40	Automated Classification of Defected Images by Means of Machine Learning for Improved Analysis of Vehicle Undercarriages W.V. Giegerich, A. Stone, L. Forte III, P.J. Schneider, K.W. Oh, University at Buffalo, US