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Analytical chemistry · 2026

BiOI Photocatalyzes Dopamine Oxidation for Simultaneous Photoelectrochemical-Photothermal Dual-Mode Biosensing of Pathogenic Bacteria.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Wu He, Guan Yangyang, Yu Haikuo, Jie Guifen

Аннотация

Exploring a novel bifunctional nanomaterial with excellent photoelectrochemical and photocatalytic performance is crucial for developing multifunctional sensors with high sensitivity and reliability. In this work, BiOI hollow microspheres with a unique layered structure were successfully synthesized. Their excellent electron transport capabilities and abundant catalytic sites endow them with both highly efficient photoelectrochemical (PEC) performance and photoresponsive oxidase activity. On the basis of these properties, we have innovatively developed, for the first time, a dual-mode biosensor for the detection of Staphylococcus aureus (S. aureus). During the detection process, utilizing an exonuclease III (Exo III)-mediated target-amplification strategy, we achieved the efficient enrichment of the probe molecule Au@DA on the BiOI surface. Under illumination, BiOI exhibits outstanding oxidase-like catalytic activity, capable of efficiently catalyzing the oxidation of dopamine (DA) to polydopamine (PDA). Concurrently, the Z-type heterojunction formed between BiOI and PDA significantly enhances the photocurrent response, increasing its intensity by 2 orders of magnitude. Furthermore, the generated PDA possesses excellent photothermal conversion properties and can be further utilized for temperature signal detection, thereby establishing a dual-signal output system with photocurrent and temperature signals. This effectively avoids the false-positive issues that may arise from single-signal detection and significantly enhances detection reliability. This study not only provides new insights into the design of PEC sensors enhanced by photoelectrocatalytic synergy but also advances the development of PEC biosensing technology through functional integration and signal diversification strategies, offering significant application prospects in the field of environmental monitoring.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты