Abstract With the rapid growth in intelligent metasurfaces in the recent years, deep learning has attracted attention to transform the ways in which metasurfaces are simulated and designed. The unique advantages of deep learning lie in the powerful data‐driven modality, which allows a computational model to learn useful information using hierarchically structured layers. Among the various successful examples, there are forward and inverse designs. However, such designs are inherently data‐hungry. Thus, the data utilization efficiency must be maximized, and green metasurface design must be achieved. Here, the authors propose heterogeneous transfer learning to allow transferrable and data‐efficient metasurface design. The key to this method is a flexible network framework, which integrates feature augmentation and dimensionality reduction. The concept is demonstrated through three scenarios, i.e., metasurfaces with different parameterizations, different physical sizes, and completely different geometries, where the relative error reduction reaches up to 50%. Furthermore, an inverse metasurface design is proposed, which combines the forward predicted network and heuristic algorithm. This work considerably reduces the workload on data collection and overcomes the limitation that previous works only focused on fixed physical structures. The authors have also envisioned a “global metasurface gene bank,” in which researchers can freely “withdraw and save data” for various applications.

Jie Zhang

Chao Qian

Zhixiang Fan

Jieting Chen

Erping Li

Jianming Jin

Hongsheng Chen

Advanced Optical Materials

先进光学材料的范围致力于光子学、等离子体激元学、超材料等方面的突破性发现和基础研究。以下是高级光学材料中涵盖的主题的非详尽列表：光子晶体非线性光学光学纳米结构光电子学光学器件、探测器和传感器全息光声材料光学数据存储微/纳米谐振器光波导。

The journal "Advanced Optical Materials" focuses on groundbreaking discoveries and fundamental research in the fields of photonics, plasmonics, and metamaterials. Topics covered include, but are not limited to: photonic crystals, nonlinear optics, optical nanostructures, optoelectronics, optical devices, detectors and sensors, holography, photoacoustic materials, optical data storage, micro/nano resonators, and optical waveguides.

《Advanced Optical Materials》期刊专注于光子学、等离子体激元学、超材料等领域的突破性发现和基础研究。期刊涵盖的主题包括但不限于：光子晶体、非线性光学、光学纳米结构、光电子学、光学器件、探测器和传感器、全息技术、光声材料、光学数据存储、微/纳米谐振器及光波导等。

Heterogeneous Transfer‐Learning‐Enabled Diverse Metasurface Design

An inverse metasurface design is proposed, which combines the forward predicted network and heuristic algorithm and overcomes the limitation that previous works only focused on fixed physical structures.

Category	Quartile
材料科学	2
材料科学, 材料科学综合	2
材料科学, 光学	2

Heterogeneous Transfer‐Learning‐Enabled Diverse Metasurface Design

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