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Author | Title | Accn# | Year | Item Type | Claims |
| 1 |
Joshi, Nirav |
Machine Learning for Advanced Functional Materials |
I12655 |
2023 |
eBook |
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| Title | Machine Learning for Advanced Functional Materials |
| Author(s) | Joshi, Nirav;Kushvaha, Vinod;Madhushri, Priyanka |
| Publication | Singapore, 1. Imprint: Springer
2. Springer Nature Singapore, 2023. |
| Description | VIII, 303 p. 102 illus., 94 illus. in color : online resource |
| Abstract Note | This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material???s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods |
| ISBN,Price | 9789819903931 |
| Keyword(s) | 1. DETECTORS
2. EBOOK - SPRINGER
3. MACHINE LEARNING
4. MATERIALS
5. OPTICAL ENGINEERING
6. OPTICS
7. Optics and Photonics
8. Photonic Devices
9. PHOTONICS
10. Photonics and Optical Engineering
11. Sensors and biosensors
12. Tumor markers
13. Tumour Biomarkers
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| Item Type | eBook |
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| I12655 |
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