| Technical Name | Biomedical Ultralow-Young＇s Modulus Low-Niobium Ti Alloys Developed by Machine Learning | ||
|---|---|---|---|
| Project Operator | National Taiwan University | ||
| Project Host | 顏鴻威 | ||
| Summary | The materials demands for biomedical implants will significantly increase with coming super-aged society. The current work applied artificial neural network to build a materials search engine for Beta-Ti alloys. New alloys were predicteddiscovered under the conditions of low Young＇s moduluslow niobium content in the machine. Then, the real materials have been successfully developedp |
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| Scientific Breakthrough | - |
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| Industrial Applicability | - |
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