Tunable hierarchical surfaces of CuO derived from metal–organic frameworks for non-enzymatic glucose sensing

Luo, Yumei; Wang, Qingyong; Li, Jinghua; Xu, Fen; Sun, Lixian; Bu, Yiting; Zou, Yongjin; Kraatz, Heinz‐Bernhard; Rosei, Federico

doi:10.1039/d0qi00104j

Cited by 46 publications

(24 citation statements)

References 68 publications

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“…The experimental results show that an obvious current corresponding to the addition of glucose emerged and no obvious current change corresponding to the addition of the interferents, proving that the glucose sensor has a superior selectivity. 40 Xin et al used porous flower-like Ni 5 P 4 to construct an electrochemical glucose sensor. The selective experiment was conducted by selecting uric acid, ascorbic acid, and dopamine as interferents by DPV technology.…”

Section: Selectivitymentioning

confidence: 99%

Electrochemical non-enzymatic glucose sensors: recent progress and perspectives

et al. 2020

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Section: Selectivitymentioning

confidence: 99%

Electrochemical non-enzymatic glucose sensors: recent progress and perspectives

et al. 2020

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“…[106][107][108][109][110] Recently, nanomaterials derived from MOFs showed promising aspects for electrochemical glucose sensing due to their high surface area, improved chemical stability, high electrical conductivity, and tunable 9a). [111] The porous hierarchical CuO nanospheres with controllable porosity and surface area showed better glucose sensing properties in an alkaline solution than hierarchical CuO clusters. The sensing mechanism of this sensor involves the oxidation of glucose by the electrochemically generated CuOOH in an alkaline medium.…”

Section: Mof Derived Materialsmentioning

confidence: 96%

“…prepared hierarchical CuO nanospheres derived from a Cu‐MOF by thermal decomposition ( Figure ). [ 111 ] The porous hierarchical CuO nanospheres with controllable porosity and surface area showed better glucose sensing properties in an alkaline solution than hierarchical CuO clusters. The sensing mechanism of this sensor involves the oxidation of glucose by the electrochemically generated CuOOH in an alkaline medium.…”

Section: Mof‐based Nonenzymatic Electrochemical Glucose Sensorsmentioning

confidence: 99%

Glucose Detection Devices and Methods Based on Metal–Organic Frameworks and Related Materials

Adeel

Asif

Rahman

et al. 2021

Adv Funct Materials

121

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Assessment of glucose concentration is important in the diagnosis and treatment of diabetes. Since the introduction of enzymatic glucose biosensors, scientific and technological advances in nanomaterials have led to the development of new generations of glucose sensors. This field has witnessed major developments over the last decade, as the novel nanomaterials are capable of efficiently catalyzing glucose directly (i.e., act as artificial enzymes, therefore defined nanozymes) or to entrap enzymes that are able to oxidize glucose. Among other nanomaterials, metal-organic frameworks (MOFs) have recently provided a tremendous basis to construct glucose sensing devices. MOFs are large porous crystalline compounds with versatile structural and tuneable chemical properties. In addition, they possess catalytic, peroxidase-like, and electrochemical redox activity. This review comprehensively summarizes the general characteristics of MOFs, their subtypes, and MOF composites, as well as MOF-derived materials employed to construct electrochemical, optical, transistor, and microfluidic devices for the detection of glucose. They include enzymatic, nonenzymatic, wearable, and flexible sensing devices and methods. The review also outlines the design and synthesis of MOFs and the working principles of the different transductionbased glucose sensors and highlights the current challenges and future perspectives.

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“…In addition to metal-based materials, metal oxides synthesized from MOFs have also been applied in glucose sensing. For example, Luo et al utilized a Cu-based MOF to create CuO using a pyrolysis process [82]. This catalyst was coated on GCE, which operates as an anode for glucose oxidation, and exhibited outstanding activity with a low LOD of 0.15 µM and a high sensitivity of 1806.1 µA cm −2 mM −1 .…”

Section: Mof-derived Metal Compoundsmentioning

confidence: 99%

Metal–Organic-Framework- and MXene-Based Taste Sensors and Glucose Detection

Huu

Cho

Han

et al. 2021

Sensors

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Taste sensors can identify various tastes, including saltiness, bitterness, sweetness, sourness, and umami, and have been useful in the food and beverage industry. Metal–organic frameworks (MOFs) and MXenes have recently received considerable attention for the fabrication of high-performance biosensors owing to their large surface area, high ion transfer ability, adjustable chemical structure. Notably, MOFs with large surface areas, tunable chemical structures, and high stability have been explored in various applications, whereas MXenes with good conductivity, excellent ion-transport characteristics, and ease of modification have exhibited great potential in biochemical sensing. This review first outlines the importance of taste sensors, their operation mechanism, and measuring methods in sensing utilization. Then, recent studies focusing on MOFs and MXenes for the detection of different tastes are discussed. Finally, future directions for biomimetic tongues based on MOFs and MXenes are discussed.

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Tunable hierarchical surfaces of CuO derived from metal–organic frameworks for non-enzymatic glucose sensing

Abstract: A facile thermal treatment is conducted to prepare nanosphere stacking CuO derived from Cu-MOF, which achieves good glucose sensing performance and is expected to be effective for developing non-enzyme and non-invasive glucose sensors.

Cited by 46 publications

References 68 publications

Electrochemical non-enzymatic glucose sensors: recent progress and perspectives

Electrochemical non-enzymatic glucose sensors: recent progress and perspectives

Glucose Detection Devices and Methods Based on Metal–Organic Frameworks and Related Materials

Metal–Organic-Framework- and MXene-Based Taste Sensors and Glucose Detection

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