科研速览 · Science Skim继续刷下去 · Keep skimming →
◆ Talanta2026-05-15· Chemistry

Multi-potential laser-induced graphene fluidic paper-based array for in-flow differential analysis of phenolic compounds

Ida Valeria Di Cristoforo, Flavio Della Pelle, Annalisa Scroccarello, Filippo Silveri, Marcello Mascini, Daniel Rojas, Davide Paolini, Dario Compagnone

原始摘要(英文原文)· Original abstract
CO 2 laser-based technologies are relevant to the sensor scenario; however, integrating arrays of laser-induced sensing systems with paper's fluidic capabilities warrants further investigation. Herein, a CO 2 laser plotter was employed to define an integrated, pump-free paper-based microfluidic device that encloses an array of four independent laser-induced graphene (LIG) sensors. The multichannel-LIG fluidic paper-based analytical device (fLIG-PAD) ensures continuous, spontaneous sample flow within the LIG array, where each electrode operates at a different potential simultaneously. The fLIG-PAD enables the quantitative determination of phenolic content in food matrices and the partitioning of the phenolic profile into reactivity classes based on electrochemical reactivity. Initially, the CO 2 laser parameters were carefully optimized to maximize the charge transfer of the LIG sensing films while examining the resulting morpho-electrochemical features. The system's electroanalytical performance was tested on several phenolic compounds (PC) commonly found in foods; notable electrocatalytic properties were observed, allowing the differentiation of PC into four reactivity levels by applying different potentials at the various LIG sensors. The fLIG-PAD performs simultaneous flow amperometry measurements in continuous mode thanks to the functional design, providing quantitative responses for PCs' continuous analysis (R2 ≥ 0.990), with fast and complete signal recovery (≤570 s), offering repeatable (RSD ≤12%, n = 8) and reproducible (RSD ≤6.3%, n = 3) measurements. The fLIG-PAD, tested on 17 food samples containing PCs from different chemical classes, enables food classification based on their PC patterns, providing PC content quantification correlated with HPLC–MS/MS (r = 0.97).
读原文 · Read the paper ↗

AI 追问PRO

登录后使用 AI 追问

讨论区

登录后参与讨论

相关论文 · Related

Multi-potential laser-induced graphene fluidic paper-based array for in-flow differential analysis of phenolic compounds — 科研速览 Science Skim