An AI-driven robotic system for two-dimensional hetero-assemblies
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913147207548928 |
|---|---|
| author | Li, Xiaoxi He, Jinkun Liu, Haojie Liu, Xipeng Wu, Zewen Li, Jing Zhao, Kai Li, Shan Sun, Xingdan Fan, Xiaoxue Xiong, Zhiren Wu, Xingguang Sha, Xuanzhe Lin, Zhili Yang, Caixia Han, Luosha Xu, Jie Pei, Woye Yang, Kaining Zhang, Jing Feng, Xiaolong Zhang, Tongyao Liang, Zhu Watanabe, Kenji Taniguchi, Takashi Tian, Ming Wan, Neng Zhang, Jing Lu, Jianming Hong, Wenjing Han, Zheng Vitto |
| author_facet | Li, Xiaoxi He, Jinkun Liu, Haojie Liu, Xipeng Wu, Zewen Li, Jing Zhao, Kai Li, Shan Sun, Xingdan Fan, Xiaoxue Xiong, Zhiren Wu, Xingguang Sha, Xuanzhe Lin, Zhili Yang, Caixia Han, Luosha Xu, Jie Pei, Woye Yang, Kaining Zhang, Jing Feng, Xiaolong Zhang, Tongyao Liang, Zhu Watanabe, Kenji Taniguchi, Takashi Tian, Ming Wan, Neng Zhang, Jing Lu, Jianming Hong, Wenjing Han, Zheng Vitto |
| contents | Nanomaterials stacked on-demand, such as rotationally assembled two-dimensional (2D) van der Waals (vdW) layered compounds, provides a versatile platform for quantum simulation and the exploration of exotic electronic phases. Currently, however, such nanoassemblies remain largely confined to inefficiency, manually operated process, limiting their potential for probing emergent physical phenomena. There is a pressing need in the field for high-precision, automated assembling techniques, especially for the scalable fabrication of 2D twistronic heterostructures. Here, we present an intelligent automation system dedicated to the fabrication of van der Waals stacks, following the state-of-the-art protocol for dry transfer of exfoliated 2D materials. The system further employs metadata generated from each automated stacking procedure to perform reinforcement learning, thereby continuously bettering its performances. As a concrete demonstration, we fabricate twisted bilayer graphene (TBLG) -- known for its challenging preparation -- and exhibit its unconventional superconductivity near the magic angle. Our work may pave the way for high-throughput fabrication of low-dimensional nanomaterials including twistronic heterostructures, where integrating data mining and artificial intelligence can accelerate the discovery of novel physical phenomena. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_20420 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | An AI-driven robotic system for two-dimensional hetero-assemblies Li, Xiaoxi He, Jinkun Liu, Haojie Liu, Xipeng Wu, Zewen Li, Jing Zhao, Kai Li, Shan Sun, Xingdan Fan, Xiaoxue Xiong, Zhiren Wu, Xingguang Sha, Xuanzhe Lin, Zhili Yang, Caixia Han, Luosha Xu, Jie Pei, Woye Yang, Kaining Zhang, Jing Feng, Xiaolong Zhang, Tongyao Liang, Zhu Watanabe, Kenji Taniguchi, Takashi Tian, Ming Wan, Neng Zhang, Jing Lu, Jianming Hong, Wenjing Han, Zheng Vitto Mesoscale and Nanoscale Physics Applied Physics Nanomaterials stacked on-demand, such as rotationally assembled two-dimensional (2D) van der Waals (vdW) layered compounds, provides a versatile platform for quantum simulation and the exploration of exotic electronic phases. Currently, however, such nanoassemblies remain largely confined to inefficiency, manually operated process, limiting their potential for probing emergent physical phenomena. There is a pressing need in the field for high-precision, automated assembling techniques, especially for the scalable fabrication of 2D twistronic heterostructures. Here, we present an intelligent automation system dedicated to the fabrication of van der Waals stacks, following the state-of-the-art protocol for dry transfer of exfoliated 2D materials. The system further employs metadata generated from each automated stacking procedure to perform reinforcement learning, thereby continuously bettering its performances. As a concrete demonstration, we fabricate twisted bilayer graphene (TBLG) -- known for its challenging preparation -- and exhibit its unconventional superconductivity near the magic angle. Our work may pave the way for high-throughput fabrication of low-dimensional nanomaterials including twistronic heterostructures, where integrating data mining and artificial intelligence can accelerate the discovery of novel physical phenomena. |
| title | An AI-driven robotic system for two-dimensional hetero-assemblies |
| topic | Mesoscale and Nanoscale Physics Applied Physics |
| url | https://arxiv.org/abs/2605.20420 |