Cuprospinel decorated biopolymer functionalized CNFs based electrocatalytic platform integrated with grid search optimized neural network for detection of vital amino acid in beverages

An electrocatalytic platform based on a novel nanocomposite integrated with a grid search-optimized neural network (GSNN) was proposed for intelligent sensing of tryptophan. The cuprospinel-decorated chitosan-functionalized carbon nanofibers (CuFe2O4/Chit-CNFs) fabricated on a disposable electrode revealed exceptional electrocatalytic activity with a low detection limit (2 nM) and good sensitivity (79.18 μAμM−1 cm−2) over a broad linear range (0.05–152.55 μM). Cyclic voltammetry and differential pulse voltammetry were employed, and the sensing mechanism of tryptophan entails its electrocatalytic oxidation, where the synergistic impact of CuFe2O4 and Chit-CNFs boosts electrochemical response owing to their high surface area and conductivity. GSNN-based intelligent sensing returned a root mean square error (RMSE) of 2.76 and a mean absolute error (MAE) of 1.12. Moreover, the sensor's performance was tested on samples from apple juice, tomato juice, pineapple juice, and milk for assessing practicality, demonstrating recovery between 96.93 and 101.06 % and maximum relative standard deviation of 2.63 %. The proposed sensor showcased excellent selectivity, repeatability, reproducibility, and stability. [Display omitted] •Preparation of CuFe2O4/Chit-CNF/SPCE with exceptional electrocatalytic activity.•Ultrasensitive quantification of essential amino acid tryptophan in beverages.•Grid search optimized neural network was used in analytical chemistry for first time.•High sensitivity of 79.18 μAμM−1 cm−2 and low detection limit of 2 nM was achieved.•Good recovery values in apple juice, tomato juice, pineapple juice, and milk.