Artificial Intelligence-Powered Materials Science
Highlights A detailed exploration is provided of how artificial intelligence (AI) and machine learning techniques are applied across various aspects of materials science. Major challenges in AI-driven materials science are evaluated. Novel case studies are incorporated, demonstrating their impact on...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-02-01
|
| Series: | Nano-Micro Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40820-024-01634-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823861637277286400 |
|---|---|
| author | Xiaopeng Bai Xingcai Zhang |
| author_facet | Xiaopeng Bai Xingcai Zhang |
| author_sort | Xiaopeng Bai |
| collection | DOAJ |
| description | Highlights A detailed exploration is provided of how artificial intelligence (AI) and machine learning techniques are applied across various aspects of materials science. Major challenges in AI-driven materials science are evaluated. Novel case studies are incorporated, demonstrating their impact on accelerating material development and discovery. |
| format | Article |
| id | doaj-art-56e6acc8901e4ff09b8658a7e278f005 |
| institution | Kabale University |
| issn | 2311-6706 2150-5551 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Nano-Micro Letters |
| spelling | doaj-art-56e6acc8901e4ff09b8658a7e278f0052025-02-09T12:51:01ZengSpringerOpenNano-Micro Letters2311-67062150-55512025-02-0117113010.1007/s40820-024-01634-8Artificial Intelligence-Powered Materials ScienceXiaopeng Bai0Xingcai Zhang1Department of Mechanical Engineering, The University of Hong KongDepartment of Materials Science and Engineering, Stanford UniversityHighlights A detailed exploration is provided of how artificial intelligence (AI) and machine learning techniques are applied across various aspects of materials science. Major challenges in AI-driven materials science are evaluated. Novel case studies are incorporated, demonstrating their impact on accelerating material development and discovery.https://doi.org/10.1007/s40820-024-01634-8Artificial intelligenceMachine learningSustainable materialsData-drivenMaterials innovation |
| spellingShingle | Xiaopeng Bai Xingcai Zhang Artificial Intelligence-Powered Materials Science Nano-Micro Letters Artificial intelligence Machine learning Sustainable materials Data-driven Materials innovation |
| title | Artificial Intelligence-Powered Materials Science |
| title_full | Artificial Intelligence-Powered Materials Science |
| title_fullStr | Artificial Intelligence-Powered Materials Science |
| title_full_unstemmed | Artificial Intelligence-Powered Materials Science |
| title_short | Artificial Intelligence-Powered Materials Science |
| title_sort | artificial intelligence powered materials science |
| topic | Artificial intelligence Machine learning Sustainable materials Data-driven Materials innovation |
| url | https://doi.org/10.1007/s40820-024-01634-8 |
| work_keys_str_mv | AT xiaopengbai artificialintelligencepoweredmaterialsscience AT xingcaizhang artificialintelligencepoweredmaterialsscience |