Scholarlink

<p>Decoding arbitrary polarization information in a cost-effective way is a key target for next-generation optical sensing. However, the design of full-Stokes detectors capable of resolving polarization states in a single shot remains challenging. Here we introduce GOStokes, an approach that leverages heterogeneous grain orientation in solution-processed metal halide semiconductors to extract Stokes parameters in a single measurement. By developing polycrystalline films exhibiting strong inherent circular and linear dichroism, we harness randomly oriented grains to produce varied polarization selectivity across the spatial domain. Integrating these films as multi-channel optical filters with commercial cameras enables real-time polarimetric detection and imaging, each generating a transmission map from a single exposure. Using deep learning, GOStokes precisely determines arbitrary polarization states with an averaged mean absolute error below 1%. Our demonstration underscores the potential of combining low-cost, scalable, polycrystalline films with reconstruction algorithms for advanced polarimetric applications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Accurate single-shot full-Stokes detection enabled by heterogeneous grain orientations in polycrystalline films

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月1日

查看全文
  • Mingwei Ge,
  • Yuan Yao,
  • Tyler Wang,
  • Subhrangsu Mukherjee,
  • Harald Ade,
  • Mengxia Liu

摘要

Decoding arbitrary polarization information in a cost-effective way is a key target for next-generation optical sensing. However, the design of full-Stokes detectors capable of resolving polarization states in a single shot remains challenging. Here we introduce GOStokes, an approach that leverages heterogeneous grain orientation in solution-processed metal halide semiconductors to extract Stokes parameters in a single measurement. By developing polycrystalline films exhibiting strong inherent circular and linear dichroism, we harness randomly oriented grains to produce varied polarization selectivity across the spatial domain. Integrating these films as multi-channel optical filters with commercial cameras enables real-time polarimetric detection and imaging, each generating a transmission map from a single exposure. Using deep learning, GOStokes precisely determines arbitrary polarization states with an averaged mean absolute error below 1%. Our demonstration underscores the potential of combining low-cost, scalable, polycrystalline films with reconstruction algorithms for advanced polarimetric applications.