4.6 Article

PCN-224/rGO nanocomposite based photoelectrochemical sensor with intrinsic recognition ability for efficient p-arsanilic acid detection

期刊

ENVIRONMENTAL SCIENCE-NANO
卷 6, 期 1, 页码 207-215

出版社

ROYAL SOC CHEMISTRY
DOI: 10.1039/c8en00913a

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资金

  1. National Natural Science Foundation of China [21836002, 21607045, 21777046]
  2. Guangdong Innovative and Entrepreneurial Research Team Program [2016ZT06N569]
  3. Guangzhou Science and Technology Project [201804010189]
  4. Shaoguan special fund for soil pollution prevention and control [2017sgtyfz103]

向作者/读者索取更多资源

Considering p-arsanilic acid (p-ASA) as an organoarsenic pollutant, monitoring concentration of p-ASA is significant to maintain environmental security. Photoelectrochemical (PEC) detection is promisingly applied in environmental monitoring for its lower cost and simpler operation, compared to traditional techniques. However, general electrode materials of PEC sensors need to be modified with biological probes due to lack of specific binding sites to analytes, which may lead to complicated sensor fabrication and bio-recognizers inactivation during storage. Herein, a porphyrinic metal-organic framework/reduced graphene oxide (PCN-224/rGO) nanocomposite with simultaneously excellent photoelectric activity and strong binding characteristics was prepared and used to fabricate a PEC sensor for p-ASA detection avoiding the modification of bio-recognizers. Benefiting from the high conductivity of rGO, the separation efficiency of charge carriers was improved in PCN-224/rGO and thereby photocurrent gained an amplification of about 12 times. The PCN-224/rGO nanocomposite had strong affinity to p-ASA via Zr-O-As coordination and - stacking. Significantly, the binding of p-ASA could adjust the band position of PCN-224/rGO and facilitate oxygen reduction by releasing more photogenerated electrons, achieving photocurrent enhancement. The developed PEC sensor had a wide detection range, from 10 ng L-1 to 10 mg L-1, with a detection limit of 5.47 ng L-1. Furthermore, the sensor was successfully applied to monitor p-ASA in simulated natural water and swine manure lixivium. This study paved the way for the design of more efficient PEC sensors for environmental monitoring.

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