#01 Multiscale and multimodal structure analysis with quantum beams and informatics
Project Leader: ONO, Kanta
We develop an innovative multi-scale and multi-modal analysis framework (CaaS: Characterization as a Service) that enables to measure, analyze, and gain knowledge of hierarchical heterogeneity of materials from micro to macro scales.
Objectives
A methodology to automatically determine optimal measurement conditions:
Adaptive experimental design method
Extracting information from measurement data with low signal-to-noise ratio:
high-throughput measurement
Automation of measurement data analysis: Multi-objective optimization by machine learning
Extracting information from multi-scale and multi-modal measurement data: Modality transformation
Key aspects
This research is not a mere analysis of individual measurement data, but aims for a synergistic framework
integrating quantum beam measurement and information science (AI technology).
We integrate multimodal measurement data into a database using information science
in order to extract the knowledge necessary to advance multilateral research
