AI for Science期刊第一期文章出版
在松山湖材料实验室的支持下，目前作者发表无需支付任何费用，读者亦可免费获取所有内容。
在第一期文章中，您将看到人工智能如何变革材料科学、成像、催化等多个研究方向：
- AI辅助二维材料晶圆级剥离；
- 基于深度学习的超导材料发现；
- 机器学习赋能水处理技术；
- 面向纤维网络设计的人工智能；
- 人工智能助力化学科学中的风险控制；
- 4D-MISR：低剂量超分辨成像；
- Fast Track：用于高通量材料筛选的机器学习。
文章介绍
Editorial
AI for Science―a journal to serve the AI-driven scientific innovation
Weihua Wang and Gian-Marco Rignanese
Topical Review
Artificial intelligence for fibrous network design and mechanics
Yunhao Yang, Leitao Cao, Jing Ren, Wenli Gao and Shengjie Ling
Perspectives
Computational catalysis and machine learning applications to water treatment technologies
Duo Wang, Ao Xie, Shengcun Ma, Wei Tong, Shiqiang Zou and Anubhav Jain
Haoyu Ge, Jialin Liu, Matej Sebek, Zhuoshen Li, Wei Fu, Ziyu Wang and Zeng Wang
Papers
A deep learning approach to search for superconductors from electronic bands
Jun Li, Wenqi Fang, Shangjian Jin, Chenyu Suo, Tengdong Zhang, Yanling Wu, Xiaodan Xu, Yong Liu and Dao-Xin Yao
Focus Issue on Machine Learning Potentials and Mapping of Atomic Structures
Controlling risks of AI in chemical science with agents
Jiyan He, Haoxiang Guan, Weitao Feng, Yaosen Min, Jingwei Yi, Kunsheng Tang, Shuai Li, Jie Zhang, Kejiang Chen, Wenbo Zhou, Xing Xie, Weiming Zhang, Nenghai Yu and Shuxin Zheng
4D-MISR: a unified model for low-dose super-resolution imaging via feature fusion
Zifei Wang, Zian Mao, Xiaoya He, Xi Huang, Haoran Zhang, Chun Cheng, Shufen Chu, Tingzheng Hou, Xiaoqin Zeng and Yujun Xie
Hanwen Kang, Tenglong Lu, Zhanbin Qi, Jiandong Guo, Sheng Meng and Miao Liu
期刊介绍
AI for Science
- AI for Science是一本跨学科、国际同行评审的钻石开放获取期刊，致力于发表具有重大影响力的原创研究、综述和观点文章，聚焦人工智能（AI）在推动科学创新方面的变革性应用。本刊由IOP出版社和松山湖材料实验室合办。