Adv. Funct. Mater. 2024, 2405239

DOI: 10.1002/adfm.202405239

Correction to “Robust PUF Label Authentication System Synergistically Constructed by Hierarchical Pattern of Self-assembled Phase-separation Encrypted Wrinkle and Deep Learning Model”. We apologize for the error with the manuscript, due to our negligence, we have submitted a previously uncalibrated image version. There are two errors in the submitted images in the main text (Figure 3, page 6). 1) There was an error in the thickness annotation (100 µm) of the third image in Figure 3A, which should be 80 µm. 2) There was a sample size error in the similarity heatmap of Hamming distance of phase separation in Figure 3G. The errors do not affect the results, discussion, or conclusion of the article. The revised version is shown below.

The authors sincerely apologize for this error.

Primary Figure 3

Figure 3. The information description of hierarchical pattern in PUF label. (A) The distribution of information points of wrinkles at different thickness (scale bar: 200 µm). (B) The distribution of information points of phase separation of SBS-CAN (scale bar: 300 nm). (C) The distribution of information points of fingerprint (scale bar: 5 mm). Comparison of bifurcation (D) and ending (E) information density between hierarchical pattern and human fingerprint. (F) The binarization of wrinkle pattern, similarity heatmap of twice measurement results and intra distance and inter distance of the 50 patterns of wrinkle based on Hamming distance. (G) The binarization of phase separation pattern, similarity heatmap of twice measurement results and intra distance and inter distance of the 50 patterns of phase separation based on Hamming distance.

Corrected Figure 3

Figure 3. The information description of hierarchical pattern in PUF label. A) The distribution of information points of wrinkles at different thickness (scale bar: 200 µm). B) The distribution of information points of phase separation of SBS-CAN (scale bar: 300 nm). C) The distribution of information points of fingerprint (scale bar: 5 mm). Comparison of bifurcation D) and ending E) information density between the hierarchical pattern and human fingerprint. F) The binarization of wrinkle pattern, similarity heatmap of twice measurement results and intra distance and inter distance of the 50 patterns of wrinkle based on Hamming distance. G) The binarization of phase separation pattern, similarity heatmap of twice measurement results and intra distance and inter distance of the 50 patterns of phase separation based on Hamming distance.