التفاصيل البيبلوغرافية
| العنوان: |
Generative artificial intelligence and its applications in materials science: Current situation and future perspectives |
| المؤلفون: |
Yue Liu, Zhengwei Yang, Zhenyao Yu, Zitu Liu, Dahui Liu, Hailong Lin, Mingqing Li, Shuchang Ma, Maxim Avdeev, Siqi Shi |
| المصدر: |
Journal of Materiomics, Vol 9, Iss 4, Pp 798-816 (2023) |
| بيانات النشر: |
Elsevier, 2023. |
| سنة النشر: |
2023 |
| المجموعة: |
LCC:Materials of engineering and construction. Mechanics of materials |
| مصطلحات موضوعية: |
Machine learning, Artificial intelligence, Generative artificial intelligence, Materials science, Novel materials discovery, Deep learning, Materials of engineering and construction. Mechanics of materials, TA401-492 |
| الوصف: |
Generative Artificial Intelligence (GAI) is attracting the increasing attention of materials community for its excellent capability of generating required contents. With the introduction of Prompt paradigm and reinforcement learning from human feedback (RLHF), GAI shifts from the task-specific to general pattern gradually, enabling to tackle multiple complicated tasks involved in resolving the structure-activity relationships. Here, we review the development status of GAI comprehensively and analyze pros and cons of various generative models in the view of methodology. The applications of task-specific generative models involving materials inverse design and data augmentation are also dissected. Taking ChatGPT as an example, we explore the potential applications of general GAI in generating multiple materials content, solving differential equation as well as querying materials FAQs. Furthermore, we summarize six challenges encountered for the use of GAI in materials science and provide the corresponding solutions. This work paves the way for providing effective and explainable materials data generation and analysis approaches to accelerate the materials research and development. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2352-8478 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2352847823000771; https://doaj.org/toc/2352-8478 |
| DOI: |
10.1016/j.jmat.2023.05.001 |
| URL الوصول: |
https://doaj.org/article/0de75964923b4f47a60e8d4b928ee91e |
| رقم الانضمام: |
edsdoj.0de75964923b4f47a60e8d4b928ee91e |
| قاعدة البيانات: |
Directory of Open Access Journals |
Full Text Finder