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<p>Developing high-security anticounterfeiting with reliable authentication remains a significant challenge in preventing information leakage and economic losses from counterfeiting. Here, we successfully reported physically uncopiable optical system based on piezochromic polymer hydrogels (PPH). Pressure treatment induces a clustering-triggered emission transition from red to blue, driven by suppressed through-space interactions and reduced electron delocalization, with the blue-emissive state stably retained after pressure release. Stochastic spatial distribution of red- and blue-emissive particles generates physically unclonable patterns with high distinguishability. Statistical analysis reveals near-ideal randomness together with high uniqueness and reliability. A similarity-based machine learning framework enables rapid and robust authentication, overcoming the subjectivity and inefficiency of human-eye recognition. This work establishes piezochromic polymer hydrogels as a platform for physically unclonable optical systems for secure anti-counterfeiting.</p>

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Piezochromic hydrogels for physically unclonable optical anti-counterfeiting with machine-learning assisted automatic identification

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月8日

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  • Jiayi Yang,
  • Jiayu Wu,
  • Guoliang Xiao,
  • Zhenxing Jin,
  • Cun You,
  • Changcheng Bai,
  • Runnan Ye,
  • Pinwen Zhu,
  • Guanjun Xiao,
  • Shunxin Li,
  • Xiaolong Wang,
  • Bo Zou

摘要

Developing high-security anticounterfeiting with reliable authentication remains a significant challenge in preventing information leakage and economic losses from counterfeiting. Here, we successfully reported physically uncopiable optical system based on piezochromic polymer hydrogels (PPH). Pressure treatment induces a clustering-triggered emission transition from red to blue, driven by suppressed through-space interactions and reduced electron delocalization, with the blue-emissive state stably retained after pressure release. Stochastic spatial distribution of red- and blue-emissive particles generates physically unclonable patterns with high distinguishability. Statistical analysis reveals near-ideal randomness together with high uniqueness and reliability. A similarity-based machine learning framework enables rapid and robust authentication, overcoming the subjectivity and inefficiency of human-eye recognition. This work establishes piezochromic polymer hydrogels as a platform for physically unclonable optical systems for secure anti-counterfeiting.