How is material development in aircraft construction

Artificial intelligence in material development

Superconductors: Energy gain through loss-free current conduction

The example of superconducting materials shows how successfully AI can be used in materials research. Thanks to this property, these materials can conduct electricity without loss. However, this requires extremely low temperatures in the area of ‚Äč‚Äčabsolute zero at minus 273 degrees Celsius. A few years ago, more or less by chance, scientists discovered a high-temperature conductor made of copper oxide sandwiches that becomes superconducting at temperatures as low as minus 196 degrees Celsius. Further superconductors were identified which became superconducting even at minus 13 and minus 23 degrees. So far it has only been impossible to explain what happens physically, that substances above a certain temperature show this special property of superconductivity. Enlightenment is expected from the use of AI. If it is possible to develop substances that become superconducting at room temperature, huge amounts of electricity could be saved for cooling, since the transition temperature is already below the temperature at room temperature and the superconductor no longer needs to be cooled. That would be a groundbreaking development for the future.

Artificial intelligence in additive manufacturing: expanding the range of materials

In additive manufacturing, workpieces are built up in layers based on digital 3D design data. This makes it possible to produce highly complex structures that are extremely light and stable at the same time. However, the development of materials that are specially optimized for additive manufacturing requires a very large amount of work. In many additive processes, such as powder bed melting or powder deposition welding, materials are used in powder form. It must be ensured that the powder properties are constant and thus the component properties are reproducible. Handling and understanding the interactions between material and process require further development work in order to understand and reduce fluctuations in the process and the component properties. That is why people are increasingly relying on the use of artificial intelligence. If you combine artificial intelligence and 3D printing, it is possible to expand the range of compatible materials to the compatible materials and, for example, to control the process based on the material reaction. Thus, the requirements of industries such as aerospace, which require safe and reliable materials with the best properties, can be met.

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