Technical Symposium CM
This Symposium focuses on recent advances in microstructural, chemical, electrical, optical, and mechanical characterization of coatings and thin films, as well as advanced modelling and computation techniques, which enhance our understanding of the fundamental structure-property-processing relationships. In addition, the symposium will cover topics related to high-throughput thin film development including combinatorial synthesis, automated characterization, and data science approaches such as machine learning or artificial intelligence for large data processing. Of interest are contributions that either highlight the application of recent advances in analytical methods, characterization techniques, and nano-mechanical testing methods for coating evaluation or present advanced and innovative modelling techniques to understand coating properties.
CM1: Spatially-resolved and in situ Characterization of Thin Films, Coating and Engineered Surfaces
This session deals with novel spatially-resolved structural/chemical and microstructural characterization techniques, especially those that advance the in-depth understanding of the relationship between processing, structure, and properties of thin films and engineered surfaces. Particular attention will be given to cutting-edge experiments providing in situ information on structure or microstructural evolution during growth or during post-growth stimuli (mechanical, thermal,..). Especially, the session will focus on the emerging area of three-dimensional microstructural characterization in small volumes, such as atom probe tomography, TEM characterization, FIB/SEM/EBSD tomography, and ToF-SIMS 3D mapping, dynamic characterization of thin film growth, ellipsometry, wide- and small-angle X-ray/neutron scattering, reflectometry, micro-Raman spectroscopy, etc.
CM1 Invited Speakers:
- Ryota Gemma, Tokai University, Japan
- Alice Lassnig, Austrian Academy of Sciences, Austria
- Remi Lazzari, CNRS, Sorbonne Université, Institut des NanoSciences de Paris, France, “Real-Time Monitoring of Sputter Deposition Process: Application in the Context of Ag-Based Low-Emissive Coatings”
- Pierre-Olivier Renault, Institut Pprime, CNRS-Université de Poitiers, France, “Exploring Mechanical Properties of Thin Films Through Synchrotron X-Ray Diffraction, Digital Image Correlation and Electrical Resistivity”
CM2: Advanced Mechanical Testing of Surfaces, Thin Films, Coatings and Small Volumes
This session covers advanced mechanical characterization techniques for surfaces, thin films, and coatings with a focus on the development of novel methods. This includes novel methods for performing nanoindentation and advanced micro-scale testing on coatings, thin films, and nanostructures produced by FIB or other lithography techniques, emphasizing multi-techniques nanomechanical testing: performed in situ in the SEM, TEM, Raman, X-ray beamline, etc. Particular attention will be given to papers providing characterization in non-ambient and extreme conditions (high or cryogenic temperatures, radiation, hydrogen – characterization and its effect on the deformation mechanism and embrittlement of coatings and thin films), and challenging loading (cyclic and high strain rates).
CM2 Invited Speakers:
- Hanna Bishara, Tel Aviv University, Israel, “The Local Electrical Fingerprint of Deformation-Induced Defects in Alloys”
- Christoph Gammer, The Erich Schmid Institute of Materials Science (ESI) of the Austrian Academy of Sciences, Austria, “Mechanical Properties of Thin Films Studied using 4D-STEM”
- Dong Liu, University of Oxford, UK, “Micromechanical Testing of Ceramic Coatings for Nuclear Applications”
- Takahito Ohmura, Kyushu University/NIMS, Japan, “Nano-Mechanical Characterization and Modeling of Plasticity in Metallic Materials”
CM3: Accelerated Thin Film Development: High-throughput Synthesis, Automated Characterization and Data Analysis
This session covers all topics related to accelerated, high-throughput thin films and coatings development. This includes studies on rapid thin film materials development and coatings optimization but also recent advances and developments in high-throughput research methods. Of particular interest are advanced approaches for synthesis, such as combinatorial or autonomous thin film deposition, but also automated characterization techniques. An emphasis is put on the role of data, the efficient handling of large data sets as well as the application of data science techniques and machine learning to high-throughput experimental workflows. This session complements CM4 which focusses on advanced theoretical approaches for materials discovery and design.
CM3 Invited Speakers:
- Hannah-Noa Barad, Bar Ilan University, Israel
- Sage Bauers, National Renewable Energy Laboratory, USA, “Applying Combinatorial Research Methods to Accelerate Energy Materials Discovery”
- Taro Hitosugi, University of Tokyo, Japan
- Ian Sharp, Technical University Munich, Germany
- Helge Stein, Technical University Munich, Germany
CM4: Simulations, Machine Learning, and Data Science for Materials Design and Discovery
This session presents computational and simulation methods, machine learning, artificial intelligence, and visualization algorithms, as well as best practices of their applications for knowledge-based materials design and discovery. It welcomes contributions devoted to (1) aid understanding of material structures and properties based on computations and simulations spanning from the atomic level to macroscale, (2) use of machine-learning algorithms for describing material properties or rapidly screen compositional landscapes, (3) generation, curation, and exploration of big materials data from a wide range of sources, including computations and experiments. Additionally, (4) predictive process modeling and simulations will be discussed as a tool that provides irreplaceable insight into process conditions and quantities that cannot be measured. Process modeling provides an additional layer of physics-based metadata that can be leveraged by machine learning and AI methods. This session complements CM3 focusing on experimental high throughput synthesis, characterization, and data analysis.
CM4 Invited Speakers:
- Kevin Kauffman, University of California San Diego, USA, “Crystal Symmetry Determination in Electron Diffraction Using Machine Learning”
- Chao-Cheng Kaun, Research Center for Applied Sciences, Academia Sinica, Taiwan , “Computational Modeling of Nanoelectronics and Emerging Materials”
- Vladyslav Turlo, EMPA (Swiss Federal Laboratories for Materials Science and Technology), Switzerland, “Computational Approach to Probing Hydrogen in Atomic Layer-Deposited Barrier Coatings”