Ultra‐Robust All‐Weather Perovskite Memristor Protected by Conformal Parylene Nanoscale Coating
ABSTRACT Halide perovskites are promising memristive materials for neuromorphic computing, yet their practical deployment in hardware is severely hindered by instability against moisture, oxygen, and reactive metallic ions. Here, we develop an ultra‐robust perovskite memristor with all‐weather adaptability protected by a ∼100 nm conformal polymeric nanoscale coating. Deposited by low‐temperature, solvent‐free chemical vapor deposition (CVD) technique, the polymeric Parylene serves as an encapsulation, interfacial passivation, and homogeneous dielectric layer. The memristor exhibits excellent bipolar resistive switching under ambient conditions with high uniformity, an endurance of 1.5 × 10 4 cycles (over 12.5‐fold improvement), and a low set voltage of ∼0.27 V. It maintains stable operation under 100% relative humidity, thermal treatment at 348 K, 6‐month ambient storage, and 300 bending cycles at 90°, and even passes the stringent IPX7 waterproof standard. A hardware‐mapped convolutional neural network leveraging the synaptic properties of these memristors achieves a highly reliable MNIST recognition accuracy of 90%±0.4% across 10 independent test cycles. This work demonstrates that conformal Parylene encapsulation offers a comprehensive solution to the perovskite instability, paving the way for flexible and low‐power neuromorphic systems.
Authors
- Tikai Zhang (ORCID: https://orcid.org/0000-0002-7758-453X)
- Gaoyuan Chen
- Yang Li (ORCID: https://orcid.org/0000-0002-0327-4221)
- Cheng Zhang (ORCID: https://orcid.org/0000-0002-4134-2854)
- Shijie Chen (ORCID: https://orcid.org/0000-0001-5133-819X)
- Shiqing Zhao
- Jianlong Shao
- Ruijie Bu
- Guodong Zhang
- Yi Zhang
- Fangchao Li
- Qianwen Zhang
- Lijuan Ge
- Bing Wang
- Chunlan Ma
Institutions
- China Electronics Technology Group Corporation (CN)
- Suzhou University of Science and Technology (CN)
- State Key Laboratory of Chemical Engineering (CN)
- Zhejiang University (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2026-11-07
- DOI
- https://doi.org/10.1002/adfm.79525
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China