Conference Agenda

Topical Meetings and Sessions:

TOM 1 - Silicon Photonics and Guided-Wave Optics
TOM 2 - Computational, Adaptive and Freeform Optics
TOM 3 - Optical System Design, Tolerancing and Manufacturing
TOM 4 - Bio-Medical Optics
TOM 5 - Resonant Nanophotonics
TOM 6 - Optical Materials: crystals, thin films, organic molecules & polymers, syntheses, characterization and applications
TOM 7 - Thermal radiation and energy management
TOM 8 - Non-linear and Quantum Optics
TOM 9 - Opto-electronic Nanotechnologies and Complex Systems
TOM 10 - Frontiers in Optical Metrology
TOM 11 - Tapered optical fibers, from fundamental to applications
TOM 12 - Optofluidics
TOM 13 - Advances and Applications of Optics and Photonics
EU Project Session
Early Stage Researcher Session

More information on the Topical Meetings

Select a date or location to show only sessions at that day or location. Select a single session for a detailed view (with abstracts and downloads when you are logged in as a registered attendee). The rest of the TOM sessions, EU project session, tutorials, and Early Stage Researcher session will be updated soon. Thank you for your patience!

Please note that all times are shown in the time zone of the conference. The current conference time is: 26th Nov 2022, 07:42:29pm WET

Session Overview
TOM10 S05: Frontiers in Optical Metrology: Microscopy
Friday, 16/Sept/2022:
8:30am - 10:00am

Session Chair: Poul-Erik Hansen, DFM, Denmark
Location: B031

Ground floor, 60 seats

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8:30am - 9:00am
ID: 359 / TOM10 S05: 1
TOM 10 Frontiers in Optical Metrology

Can brillouin microscopy really measure mechanical properties of biomedical samples?

Török Peter

Nottingham Trent University, United Kingdom

Can Brillouin microscopy really measure mechanical properties of biomedical samples?

9:00am - 9:15am
ID: 299 / TOM10 S05: 2
TOM 10 Frontiers in Optical Metrology

Elementary, my dear Zernike: model order reduction for accelerating optical dimensional microscopy

Phillip Manley1,2, Jan Krüger3, Lin Zschiedrich1,2, Martin Hammerschmidt1,2, Bernd Bodermann3, Rainer Köning3, Philipp-Immanuel Schnieder1,2

1JCMwave GmbH, Bolivarallee 22, 14050 Berlin, Germany; 2Zuse Institute Berlin, Takustraße 7, 14195 Berlin, Germany; 3Physikalisch-Technische Bundesanstalt, Bundesallee 100, 38116 Braunschweig, Germany

Dimensional microscopy is an essential tool for non-destructive and fast inspection of manufacturing processes. Standard approaches process only the measured images. By modelling the imaged structure and solving an inverse problem, the uncertainty on dimensional estimates can be reduced by orders of magnitude. At the same time, the inverse problem needs to be solved in a timely manner. Here we present a method of accelerating the inverse problem by reducing images to their elementary features, thereby extracting the relevant information and distinguishing it from noise. The resulting reduction in complexity allows the inverse problem to be solved more efficiently by utilize cutting edge machine learning based optimization techniques. By employing the techniques presented here, we are able to perform for highly accurate and fast dimensional microscopy.

9:15am - 9:30am
ID: 125 / TOM10 S05: 3
TOM 10 Frontiers in Optical Metrology

Near-process indirect surface characterization of laser-chemically produced removal contours

Merlin Mikulewitsch1, Dirk Stöbener1,2, Andreas Fischer1,2

1University of Bremen, Bremen Institute for Metrology, Automation & Quality Science (BIMAQ), Linzer Str. 13, 28359 Bremen, Germany; 2MAPEX Center for Materials and Processes, P. O. box 330 440, 28334 Bremen, Germany

The manufacturing rate of laser chemical machining (LCM) is currently restricted to avoid disruptive boiling bubbles in the process fluid. An increase necessitates adjustments to the laser beam or fluid properties. However, the current understanding of the surface removal mechanisms is insufficient to achieve a consistent removal quality under these conditions. For an improved process modeling, in-process measurements of the surface geometry, the surface temperature and the boiling bubbles are required. Due to the complex process environment, no suitable in-process measurement technique for the geometry or surface temperature exists. This contribution presents an indirect geometry measurement approach based on confocal fluorescence microscopy that offers the potential for near-process application in the LCM process environment. As a result, the micro-geometry of different surfaces is shown to be indirectly measurable under LCM-equivalent process conditions such as thick fluid layers or gas bubbles in the beam path. Furthermore, a combined fluorescence-based measurement of geometry and temperature is proposed.

9:30am - 9:45am
ID: 232 / TOM10 S05: 4
TOM 10 Frontiers in Optical Metrology

Alignment autocollimator-based microscope adjustment and its quality assessment

Jan Krüger, Detlef Bergmann, Matthias Sturm, Wolfgang Häßler-Grohne, Rainer Köning, Bernd Bodermann

Physikalisch-Technische Bundesanstalt (PTB), Germany

We report a custom microscope setup whose mechanical and optical components are adjusted by the means of an alignment autocollimator (AAC). Residual centring and angular misalignments of the components towards the microscope’s optical axis are below 500 µm and 1 mrad, respectively. We further perform measurements of dot structures with diameters close to the diffraction limit (nominal diameter = 200 nm; chrome on glass mask) as suitable measures for the evaluation of the microscope’s adjustment and to determine/ visualize the optical aberrations, which affect the image formation of microscopes.

9:45am - 10:00am
ID: 207 / TOM10 S05: 5
TOM 10 Frontiers in Optical Metrology

Nanoform evaluation approach using Mueller matrix microscopy and machine learning concepts

Tim Käseberg1, Jana Grundmann1, Stefanie Kroker2, Bernd Bodermann1

1Physikalisch-Technische Bundesanstalt, Germany; 2Institut für Halbleitertechnik, Laboratory for Emerging Nanometrology, Technische Universität Braunschweig, Germany

We realized an imaging Mueller matrix microscope for nanostructure characterization. For investigations on nanoform characterization via Mueller matrix images, we measured and simulated Mueller matrix images of specially designed nanostructures. As an approach towards machine learning evaluation in imaging ellipsometry, we calculated Haar-like features of the images and observed a higher sensitivity to subwavelength features in off-diagonal matrix elements compared to microscopy.