C-ZIF-67@PAN nanofiber was prepared as active materials for ampicillin (AMP) detection. MOF materials can provide larger specific surface area and more binding sites. The PAN fiber can make ZIF-67 orderly arranged, further carbonization, enhance the conductivity of the material, and make the response more sensitive. The gold nanoparticles were incorporated into the material, and the aptamer was closely combined with the material by using the Au-S bond. And further enhance the conductivity of the material. Under optimized conditions, the sensor has a wide detection range (0.001~100 μM) and a low detection limit (0.67 nM). In addition, the C-ZIF-67@PAN@Au@Apta nanofiber sensor was successfully applied to AMP residues in milk samples with a recovery rate of 92.77 % ~ 101.95 %.
Machine learning (ML) plays an important role in the electrochemical application of electrode materials. In this work, an emerging machine learning strategy for both electrochemical sensor and supercapacitor using carbonized metal–organic framework (C-ZIF-67) is proposed. The morphology and element analysis of C-ZIF-67 are characterized and further demonstrate the presence of C, N, O, Co elements. The ML model based on artificial neural network (ANN) algorithm as a powerful tool to realize intelligent analysis of niclosamide (NA), the derivative technique as an auxiliary means of voltammogram treatment to reduce personal error from data-reading and improve the sensitivity of electrochemical responses at very low concentrations, and the theoretical calculation is employed for both adsorption and binding energy, optimized structure of the prepared sensing material. The developed sensor displays excellent electrochemical response about 196.6-fold improvement compared with the bare GCE for NA, wider linear ranges of intelligent analysis from 1 nM to 9 μM with low limit of detection of 0.3 nM, and satisfactory practicability. ML model with ANN algorithm is also employed for predicting the performance of supercapacitor. The supercapacitor shows good performance with capacitance of 336.67 F/g at the current density of 2 A/g and excellent prediction with acceptable errors. This work will provide a new strategy for the development and electrochemical application of bifunctional electrode materials using the ML technique combined with theoretical calculation.
危险品化学品经营许可证（带存储）