Microscopy Conference 2023

Novel nanostructures and materials enabled by graphene embedding and sandwiching

MS 3: Low-dimensional and quantum materials

Poster session MS 3: Low-dimensional and quantum materials

Poster

IM 1: Progress in instrumentation and ultrafast EM

Analyzing and assembling layered materials, atom by atom and layer by layer, in 2D and 3D

This session focuses on the development and application of advanced imaging, diffraction and spectroscopy to provide new insight into the structural, compositional and functional properties of low-dimensional and quantum materials. A specific focus will be placed on methods for imaging individual defects, enhancing the contrast of light atoms, preparing and cleaning ultra-thin samples, developing automated workflows for low dose imaging of beam sensitive materials and linking electron microscopy with complementary characterisation techniques. Other topics of interest include in situ experiments carried out at cryogenic or elevated temperature, as well as in the presence of external stimuli such as applied voltage, field, gases or light.

Low-dimensional and quantum materials

Invited talk

Plenary

Putting your data into the void

Workshop 1: Data management

Modern microscopes are capable of quickly producing terabytes of multidimensional and multimodal data in form of (correlated) images, spectra, diffraction patterns. While managing and (online) processing such large amounts of data may require some investment in computer hard- and software, the even bigger challenge lies in the effective utilization of such data, often in an international team. Ultimately, the paradigm of FAIR (findable, accessible, interoperable, and re-purposable) data aims at data re-utilization by others, potentially with completely different research questions in mind. 
This session welcomes contributions describing solutions that enable handling and processing of big data in microscopy, but also solutions that make microscopy data FAIR.  An important aspect here, is the (automated) annotation of the experimental data by relevant metadata that is both human and machine readable. In addition, this session shall provide room for the demonstration of examples where FAIR research data management helps to lower the threshold for sharing data with collaborators and the scientific community and as such enabling synergistic combining of data from various sources or techniques. 


Data management 

poster session 1

Poster presentations

Prof. Dr.

Jani Kotakoski

Vortrag

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