PublicSeptember 24, 2024 at 7:00 AM – September 26, 2024 at 3:00 PM
Symposium: Materials Science in the era of Digital Transformation and Machine Learning
Digital transformation enables the acceleration of the design, discovery, development and delivery of new functional and structural material solutions.
Traditional methods for developing new materials, such as the empirical trial-and-error method, cannot keep pace with the current development of materials science due to their long development cycles and high costs.
Data-driven approaches, especially machine learning methods, already play an important role in materials science today and will continue to play in the near future. These include effective work with high-dimensional data sets, prediction of material properties, high-throughput methods for determining phase diagrams and crystal structures, material design, and efficient and cost-effective methods for controlling material processes.
The current diversity of possibilities, but also the limits of data-centered methods such as artificial intelligence, autonomous laboratories, high-throughput material synthesis and characterization as well as material combinatorics, will be brought together at this symposium.
