Data encryption/decryption and medical image reconstruction based on a sustainable biomemristor designed logic gate circuit
Memristors are considered one of the most promising new-generation memory technologies due to their high integration density, fast read/write speeds, and ultra-low power consumption. Natural biomaterials have attracted interest in integrated circuits and electronics because of their environmental friendliness, sustainability, low cost, and excellent biocompatibility. In this study, a sustainable biomemristor with Ag/mugwort:PVDF/ITO structure was prepared using spin-coating and magnetron sputtering methods, which exhibited excellent durability, significant resistance switching (RS) behavior and unidirectional conduction properties when three metals were used as top electrode. By studying the conductivity mechanism of the device, a charge conduction model was established by the combination of F-N tunneling, redox, and complexation reaction. Finally, the novel logic gate circuits were constructed using the as-prepared memristor, and further memristor based encryption circuit using 3-8 decoder was innovatively designed, which can realize uniform rule encryption and decryption of medical information for data and medical images. Therefore, this work realizes the integration of memristor with traditional electronic technology and expands the applications of sustainable biomemristors in digital circuits, data encryption, and medical image security.
Authors
- Zelin Cao (ORCID: https://orcid.org/0009-0006-3695-5759)
- Qiang Lu (ORCID: https://orcid.org/0000-0002-8294-4966)
- Dinghui Dong
- Bai Tao Sun (ORCID: https://orcid.org/0000-0002-5840-509X)
- Fenggang Ren (ORCID: https://orcid.org/0000-0002-9239-9279)
- Shiyang Wang (ORCID: https://orcid.org/0000-0003-2442-2788)
- Wei Peng (ORCID: https://orcid.org/0000-0002-5027-7695)
- Chengjiang Wang (ORCID: https://orcid.org/0000-0002-6294-5128)
- Fulai Lin
- Yu Cui (ORCID: https://orcid.org/0000-0002-1781-4735)
- Kun Zhu (ORCID: https://orcid.org/0000-0003-3030-9212)
- Zhuoqun Li (ORCID: https://orcid.org/0009-0000-7559-1157)
- Yu‐Chen Cheng (ORCID: https://orcid.org/0009-0003-2938-4933)
- Yi Lyu
- Kaikai Gao
Institutions
- First Affiliated Hospital of Xi'an Jiaotong University (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- Materials Today Bio
- Published
- 2024-09-17
- DOI
- https://doi.org/10.1016/j.mtbio.2024.101257
- Citations
- 11
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.30
Funders
- National Natural Science Foundation of China
- Xi’an Jiaotong University
- Shaanxi Provincial Science and Technology Department