A novel graphene-like titanium carbide MXene/Au–Ag nanoshuttles bifunctional nanosensor for electrochemical and SERS intelligent analysis of ultra-trace carbendazim coupled with machine learning. Issue 1 (1st January 2021)

• Record Type: Journal Article
• Authors: Zhu, Xiaoyu; Liu, Peng; Xue, Ting; Ge, Yu; Ai, Shirong; Sheng, Yingying; Wu, Ruimei; Xu, Lulu; Tang, Kaijie; Wen, Yangping
• Is Part Of: Ceramics international. Volume 47:Issue 1(2021)
• Page Start: 173
• Page End: 184
• Publication Date: 2021-01-01
• Subjects: Ti2C MXene -- Au–Ag nanoshuttles -- Nanosensor -- Surface-enhanced Raman scattering -- Electrochemical analysis -- Machine learning; Ceramics -- Periodicals; Céramique industrielle -- Périodiques; Ceramics; Periodicals; Electronic journals; 666
• DOI: 10.1016/j.ceramint.2020.08.121
• Languages: English
• ISSNs: 0272-8842

Abstract

Abstract: A new bifunctional intelligent nanosensing platform based on graphene-like titanium carbide MXene (Ti2 C MXene)/Au–Ag nanoshuttles (NSs) for both electrochemical and surface-enhanced Raman scattering (SERS) intelligent analysis of ultra-trace carbendazim (CBZ) residues in tea and rice coupled with machine learning (ML) was successfully designed. Ti2 C MXene was synthesized by selectively etching Al layers of Ti2 AlC with hydrofluoric acid and high-temperature calcination. Ti2 C MXene/Au–Ag NSs prepared by the ultrasonic dispersion of graphene-like Ti2 C MXene into Au–Ag NSs solution under dark conditions displayed large and rough surface, enhanced conductivity, excellent electrochemical response, prominent Raman enhancement, and high stability. The ML via different algorithms such as artificial neural network, support vector machine, and relevance vector machine (RVM) for the intelligent analysis of CBZ was contrasted and discussed. RVM displayed more superiority for the electrochemical analysis of CBZ in a wide linear range of 0.006 – 9.8 μM with low limit of detection (LOD) of 0.002 μM and SERS detection of CBZ in the wide linear range of 0.033 – 10 μM with low LOD of 0.01 μM. This will provide a new bifunctional intelligent sensing platform via different ML algorithms for improving accuracy of sensor via mutual verification of two or more methods of detection and a new bifunctional nanosensing platform based on the development of graphene-like nanohybrid for food and agro-products safety.