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A physical unclonable function (PUF) is a technology designed to safeguard sensitive information and ensure data security. PUFs generate unique responses for each challenge by leveraging random deviations in the physical microstructures of integrated circuits (ICs), making it incredibly difficult to replicate them. However, traditional silicon PUFs are now susceptible to various attacks, such as modeling attacks using conventional machine learning techniques and reverse engineering strategies. As a result, PUFs based on new materials or methods are being developed to enhance their security. However, in the realm of survey papers, it has come to our attention that there is a notable scarcity of comprehensive summaries and introductions concerning these emerging PUFs. To fill this gap, this article surveys PUFs based on novel technologies in the literature. In particular, we first provide an insightful overview of four types of PUFs that are rooted in advanced technologies: bionic optical PUF, biological PUF, PUF based on printed electronics (PE), and PUF based on memristors. Based on the overview, we further discuss the evaluation results of their performance based on specific metrics and conduct a comparative analysis of their performance. Despite significant progress in areas such as limited entry and regional expertise, it is worth noting that these PUFs still have room for improvement. Therefore, we have identified their potential shortcomings and areas that require further development. Moreover, we outline various applications of PUFs and propose our own future prospects for this technology. To sum up, this article contributes to the understanding of PUFs based on novel technologies by providing an in-depth analysis of their characteristics, performance evaluation, and potential improvements. It also sheds light on the wide range of applications for PUFs and presents enticing prospects for future advancements in this field.

Methane (CH4), as the main component of natural gas and coal mine gas, is widely used in daily life and industrial processes and its leakage always causes undesirable misadventures. Thus, the rapid detection of low concentration methane is quite necessary. However, due to its robust chemical stability resulting from the strong tetrahedral-symmetry structure, the methane molecules are usually chemically inert to the sensing layers in detectors, making the rapid and efficient alert a big challenge. In this work, palladium nanoparticles (Pd NPs) embedded indium oxide porous hollow tubes (In2O3 PHTs) were successfully synthesized using Pd@MIL-68 (In) MOFs as precursors. All In2O3-based samples derived from Pd@MIL-68 (In) MOFs inherited the morphology of the precursors and exhibited the feature of hexagonal hollow tubes with porous architecture. The gas-sensing performances to 5000 ppm CH4 were evaluated and it was found that Pd@In2O3-2 gave the best response (Ra/Rg = 23.2) at 370 °C, which was 15.5 times higher than that of pristine-In2O3 sensors. In addition, the sensing materials also showed superior selectivity against interfering gases and a rather short response/recovery time of 7 s/5 s. The enhancement in sensing performances of Pd@In2O3-2 could be attributed to the large surface area, rich porosity, abundant oxygen vacancies and the catalytic function of Pd NPs.