Research demonstrates improved selectivity and performance of glucose sensors using CuBTC MOFs, suggesting effective non-enzymatic alternatives.
Glucose sensing is critical for the prevention and treatment of diabetes, with natural enzyme limited by poor environmental stability as well as high cost, which promotes the development of non-enzymatic sensors. Metal organic frameworks (MOFs) have been applied as promising electrocatalysts for glucose oxidation, but the intrinsic catalytic activity is often overlooked. In this work, by varying the amount of surfactant, cubic CuBTC (BTC = 1, 3, 5-benzentricarboxylic acid) with {100} crystal planes exposed, octahedral CuBTC with {111} faces exposed, and tetradecahedral CuBTC with both {100} and {111} faces exposed, were synthesized. We have discovered that regulating the exposed crystal facets is highly beneficial for improving the selectivity, and by optimizing the detection voltage of optimally cubic CuBTC, the performance was further enhanced. Furthermore, the cubic CuBTC displayed a superior activity for the electro-oxidation of glucose when compared with octahedral CuBTC and tetradecahedral CuBTC, attributing to the larger electrochemical active surface area (ECSA), faster charge transfer rates. As a result, the constructed cubic CuBTC based glucose sensor possesses a high sensitivity of 510.51 μA·mM −1 ·cm −2 , a low detection limit of 0.53 μM, good stability and reproducibility. The present study establishes crystal facet engineering as a viable route for improving non-enzymatic sensing performance, where tailored plane exposure optimizes both catalytic activity and selectivity.
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Jiao et al. (2025) studied this question.
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