Advances in functional photonic crystal materials for the analysis of chemical hazards in food.

Chemical contaminants in food generally include natural toxins (mycotoxins, animal toxins, and phytotoxins), pesticides, veterinary drugs, environmental pollutants, heavy metals, and illegal additives. Developing a low-cost, simple, and rapid detection technology for harmful substances in food is urgently needed. Analytical methods based on different advanced materials have been developed into rapid detection methods for food samples. In particular, photonic crystal (PC) materials have a unique surface periodic structure, structural color, a large surface area, easy integration with photoelectronic and magnetic devices which have great advantages in the development of rapid, low-cost, and highly sensitive analytical methods. This review focuses on the PC materials in the view of their fabrication processes, functionalized recognition components for the specific recognition of hazardous substances, and applications in the separation, enrichment, and detection of chemical hazards in real samples. Suspension array based on three-dimensional PC microspheres by droplet-based microfluidic assembly is a great promising and powerful platform for food safety detection fields. For the PCs selective analysis, biological antibodies, aptamers, and molecularly imprinted polymers (MIPs) could be modified for specific recognition of target substances, particularly MIPs because of their low-cost and easy mass production. Based on these functional PCs, various toxic and hazardous substances can be selectively enriched or recognized in real samples and further quantified in combination of liquid chromatography method or optical detection methods including fluorescence, chemiluminescence, and Raman spectroscopy.

Machine learning-assisted Te-CdS@Mn3O4 nano-enzyme induced self-enhanced molecularly imprinted ratiometric electrochemiluminescence sensor with smartphone for portable and visual monitoring of 2,4-D.

Here, a novel and portable machine learning-assisted smartphone-based visual molecularly imprinted ratiometric electrochemiluminescence (MIRECL) sensing platform was constructed for highly selective sensitive detection of 2,4-Dichlorophenoxyacetic acid (2,4-D) for the first time. Te doped CdS-coated Mn3O4 (Te-CdS@Mn3O4) with catalase-like activity served as cathode-emitter, while luminol as anode luminophore accompanied H2O2 as co-reactant, and Te-CdS@Mn3O4 decorated molecularly imprinted polymers (MIPs) as recognition unit, respectively. Molecular models were constructed and MIP band and binding energies were calculated to elucidate the luminescence mechanism and select the best functional monomers. The peroxidase activity and the large specific surface area of Mn3O4 and the electrochemical effect can significantly improve the ECL intensity and analytical sensitivity of Te-CdS@Mn3O4. 2,4-D-MIPs were fabricated by in-situ electrochemical polymerization, and the rebinding of 2,4-D inhibits the binding of H2O2 to the anode emitter, and with the increase of the cathode impedance, the ECL response of Te-CdS@Mn3O4 decreases significantly. However, the blocked reaction of luminol on the anode surface also reduces the ECL response. Thus, a double-reduced MIRECL sensing system was designed and exhibited remarkable performance in sensitivity and selectivity due to the specific recognition of MIPs and the inherent ratio correction effect. Wider linear range in the range of 1 nM-100 µM with a detection limit of 0.63 nM for 2,4-D detection. Interestingly, a portable and visual smartphone-based MIRECL analysis system was established based on the capture of luminescence images by smartphones, classification and recognition by convolutional neural networks, and color analysis by self-developed software. Therefore, the developed MIRECL sensor is suitable for integration with portable devices for intelligent, convenient, and fast detection of 2,4-D in real samples.

Three-Dimensional Ordered Macroporous Magnetic Inverse Photonic Crystal Microsphere-Based Molecularly Imprinted Polymer for Selective Capture of Aflatoxin B1.

Development of an efficient detection method to monitor residual mycotoxins in food is very important to ensure food safety, but the complex food matrix seriously affects the detection sensitivity and accuracy. Here, using a three-dimensional ordered macroporous magnetic inverse photonic crystal microsphere (MPCM) as the supporting material, a molecularly imprinted polymer (MIP) that can selectively recognize aflatoxin B1 (AFB1) was synthesized through the dummy template imprinting strategy. The MPCM@MIP prepared by employing 5,7-dimethoxycoumarin as the template and methacrylic acid as the functional monomer displayed selectivity toward AFB1 (imprinting factor of 1.5) and could be used as a solid-phase extraction material. By coupling with high-performance liquid chromatography, an analytical method targeting AFB1 was established and displayed a wide linear range of 5-1000 ng/mL with a low detection limit of 0.4 ng/mL. The method showed a good recovery rate of 73-92% in AFB1-spiked soy sauce and vinegar samples. Moreover, the MPCM@MIP could be separated from the sample solution easily because of its magnetic performance, displaying a promising future not only in the enrichment of AFB1 to improve the detection sensitivity and accuracy but also in the removal of AFB1 from food and environmental samples.