Dear Colleagues,

materials research and development as well as manufacturing processes are becoming more and more complex. Shorter product lifecycles and increasing customer requirements force new and faster solutions. To support this, data-driven methods can help to discover new ways and efficient processes in different areas: creating new materials, visualizing processes, recognizing patterns, predicting material properties or supporting decision-making. The application of data-driven methods such as machine learning for regression and classification play a crucial role in taking advantage of these potentials. Based on certain challenges in material sciences and manufacturing, this Special Issue shall address the development and application of data-driven methods to contribute to a solution. Understanding the field of application and its data preparation, data modeling, model evaluation, and especially its deployment are important steps to make efficient use of data-driven methods. Hence, with this Special Issue, we aim to increase the visibility of significant, application-oriented research devoted to data-driven methods for various objectives in material science and manufacturing processes.

We are particularly interested in (but not limited to) contributions that focus on topics such as:

- Applications of machine learning/AI for material sciences

- Applications of machine learning/AI for manufacturing processes

- Innovative characterization methods, e.g., for material fingerprinting

- Sensor concepts for data-driven methods in the application field

- Intelligent process management

- (Big) data preparation, algorithms, modeling, and evaluation approaches

- Deployment of data-driven methods in applications

- Frameworks and concepts for the application of data-driven methods in the field of application

- Data analytics, data prediction, data classification

- (Big) data metrology and quality assurance

- Data security, data integrity, data safety

Prof. Dr. Jan Schmitt
Prof. Dr. Jürgen Hartmann
Guest Editors

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