Bibliographic Details
| Title: |
Printed smart devices for anti-counterfeiting allowing precise identification with household equipment |
| Authors: |
Junfang Zhang, Rong Tan, Yuxin Liu, Matteo Albino, Weinan Zhang, Molly M. Stevens, Felix F. Loeffler |
| Source: |
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024) |
| Publisher Information: |
Nature Portfolio, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Science |
| Subject Terms: |
Science |
| More Details: |
Abstract Counterfeiting has become a serious global problem, causing worldwide losses and disrupting the normal order of society. Physical unclonable functions are promising hardware-based cryptographic primitives, especially those generated by chemical processes showing a massive challenge-response pair space. However, current chemical-based physical unclonable function devices typically require complex fabrication processes or sophisticated characterization methods with only binary (bit) keys, limiting their practical applications and security properties. Here, we report a flexible laser printing method to synthesize unclonable electronics with high randomness, uniqueness, and repeatability. Hexadecimal resistive keys and binary optical keys can be obtained by the challenge with an ohmmeter and an optical microscope. These readout methods not only make the identification process available to general end users without professional expertise, but also guarantee device complexity and data capacity. An adopted open-source deep learning model guarantees precise identification with high reliability. The electrodes and connection wires are directly printed during laser writing, which allows electronics with different structures to be realized through free design. Meanwhile, the electronics exhibit excellent mechanical and thermal stability. The high physical unclonable function performance and the widely accessible readout methods, together with the flexibility and stability, make this synthesis strategy extremely attractive for practical applications. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2041-1723 |
| Relation: |
https://doaj.org/toc/2041-1723 |
| DOI: |
10.1038/s41467-024-45428-3 |
| Access URL: |
https://doaj.org/article/2747e619c2e74593ad373091fb88f19c |
| Accession Number: |
edsdoj.2747e619c2e74593ad373091fb88f19c |
| Database: |
Directory of Open Access Journals |
