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The exploration of nanomaterials with mimic enzyme activity (named nanozyme) has gained extensive attention in the fields of advanced analytical chemistry and materials science. Herein, the gold nanoparticles doped covalent organic frameworks (COFs) were prepared, which exhibited not only excellent mimic nitroreductase activity but also robust stability. By replacing the traditional natural enzyme tag in an enzyme-linked immunosorbent assay (ELISA), we employed the proposed nanozyme to label the detecting antibody. According to the catalytic properties of the nanozyme, 4-nitrothiophenol (4-NTP) was introduced as the substrate, which can be transformed to 4-aminothiophenol (4-ATP) in the presence of NaBH 4 . In a surface enhanced Raman scattering (SERS) assay, 4-ATP was capable of functioning as a powerful bridge to connect the gold nanostars (with excellent SERS performance) by both the Au−S bond and electrostatic force to further produce a Raman "hot spot". Meanwhile, the Raman signal of 4-nitrothiophenol at 1573 cm −1 was weakened, and a new signal at 1591 cm −1 generated by 4-ATP was turned on, leading to the generation of a ratiometric SERS signal. Based on this performance, a ratiometric nanozymelinked immunosorbent assay (NELISA) strategy was developed delicately, which was applied to detect β-lactoglobulin (allergenic protein) by monitoring the ratiometric signal of I 1591 /I 1573 with a limit of detection (LOD) of 0.01 ng/mL. The linear range is 25.65−6.2 × 10 4 ng/mL, covering more than 3 orders of magnitude. The developed method showed many advantages such as low-cost, higher recovery, and lower cross-reactivity, providing new insight into the application of SERS technology for trace target analysis.

Summary The hybrid finite‐discrete element method (FDEM) is widely used for engineering applications, which, however, is computationally expensive and needs further development, especially when rock fracture process is modeled. This study aims to further develop a sequential hybrid FDEM code formerly proposed by the authors and parallelize it using compute unified device architecture (CUDA) C/C++ on the basis of a general‐purpose graphics processing unit (GPGPU) for rock engineering applications. Because the contact detection algorithm in the sequential code is not suitable for GPGPU parallelization, a different contact detection algorithm is implemented in the GPGPU‐parallelized hybrid FDEM. Moreover, a number of new features are implemented in the hybrid FDEM code, including the local damping technique for efficient geostatic stress analysis, contact damping, contact friction, and the absorbing boundary. Then, a number of simulations with both quasi‐static and dynamic loading conditions are conducted using the GPGPU‐parallelized hybrid FDEM, and the obtained results are compared both quantitatively and qualitatively with those from either theoretical analysis or the literature to calibrate the implementations. Finally, the speed‐up performance of the hybrid FDEM is discussed in terms of its performance on various GPGPU accelerators and a comparison with the sequential code, which reveals that the GPGPU‐parallelized hybrid FDEM can run more than 128 times faster than the sequential code if it is run on appropriate GPGPU accelerators, such as the Quadro GP100. It is concluded that the GPGPU‐parallelized hybrid FDEM developed in this study is a valuable and powerful numerical tool for rock engineering applications.

A hybrid finite-discrete element method was implemented to study the fracture process of rough rock joints under direct shearing. The hybrid method reproduced the joint shear resistance evolution process from asperity sliding to degradation and from gouge formation to grinding. It is found that, in the direct shear test of rough rock joints under constant normal displacement loading conditions, higher shearing rate promotes the asperity degradation but constraints the volume dilation, which then results in higher peak shear resistance, more gouge formation and grinding, and smoother new joint surfaces. Moreover, it is found that the joint roughness affects the joint shear resistance evolution through influencing the joint fracture micro mechanism. The asperity degradation and gouge grinding are the main failure micro-mechanism in shearing rougher rock joints with deeper asperities while the asperity sliding is the main failure micro-mechanism in shearing smoother rock joints with shallower asperities. It is concluded that the hybrid finite-discrete element method is a valuable numerical tool better than traditional finite element method and discrete element method for modelling the joint sliding, asperity degradation, gouge formation, and gouge grinding occurred in the direct shear tests of rough rock joints.

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