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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.18468 |
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| _version_ | 1866910118035062784 |
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| author | Zhang, Hanyi Ma, Wanting Zhou, Wen Xing, Xueqi Zhang, Junying Huang, Tiankuo Xu, Ding Wang, Xiaozhe Mazzarello, Riccardo Ma, En Wang, Jiang-Jing Zhang, Wei |
| author_facet | Zhang, Hanyi Ma, Wanting Zhou, Wen Xing, Xueqi Zhang, Junying Huang, Tiankuo Xu, Ding Wang, Xiaozhe Mazzarello, Riccardo Ma, En Wang, Jiang-Jing Zhang, Wei |
| contents | Photonic computing using chalcogenide phase-change materials (PCMs) is under active development for energy-efficient artificial intelligence (AI) applications. A key requirement is to enable as many optically programmable levels per device as possible, while maintaining relatively low optical loss. In this work, we carry out multiscale simulations using density functional theory and finite-difference time-domain methods, proposing a "the shorter the better" strategy to optimize the performance of Sb2Te photonic waveguide devices. Our subsequent experimental characterizations of Sb2Te thin films and optical device measurements fully verify our theoretical predictions. In particular, we reveal the unconventional optical properties of metastable crystalline Sb2Te, and utilize these features for device design, yielding a simultaneous improvement in both the programming window and the optical loss. Overall, an optical programming precision exceeding 7-bit is achieved using a single waveguide cell, setting a new record for all-optical phase-change memory devices. Our work serves as a compelling example of computational material design, which demonstrates the predictive power of multiscale simulations in guiding the design of phase-change photonic devices for enhanced performance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_18468 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Multiscale simulations guided advances for all-optical phase-change waveguides Zhang, Hanyi Ma, Wanting Zhou, Wen Xing, Xueqi Zhang, Junying Huang, Tiankuo Xu, Ding Wang, Xiaozhe Mazzarello, Riccardo Ma, En Wang, Jiang-Jing Zhang, Wei Materials Science Photonic computing using chalcogenide phase-change materials (PCMs) is under active development for energy-efficient artificial intelligence (AI) applications. A key requirement is to enable as many optically programmable levels per device as possible, while maintaining relatively low optical loss. In this work, we carry out multiscale simulations using density functional theory and finite-difference time-domain methods, proposing a "the shorter the better" strategy to optimize the performance of Sb2Te photonic waveguide devices. Our subsequent experimental characterizations of Sb2Te thin films and optical device measurements fully verify our theoretical predictions. In particular, we reveal the unconventional optical properties of metastable crystalline Sb2Te, and utilize these features for device design, yielding a simultaneous improvement in both the programming window and the optical loss. Overall, an optical programming precision exceeding 7-bit is achieved using a single waveguide cell, setting a new record for all-optical phase-change memory devices. Our work serves as a compelling example of computational material design, which demonstrates the predictive power of multiscale simulations in guiding the design of phase-change photonic devices for enhanced performance. |
| title | Multiscale simulations guided advances for all-optical phase-change waveguides |
| topic | Materials Science |
| url | https://arxiv.org/abs/2603.18468 |