journal article·2020-11

Nanostructured boron-doped diamond electrode for degradation of the simulation wastewater of phenol

Lili Shi, Feng Xu, Jiye Gao, Mukfung Yuen, Shuo Sun, Ji Xu, Kunpeng Jia, Dunwen Zuo

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Abstract

Abstract The applications of a boron-doped diamond (BDD) used in electrode application for toxic and refractory organic degradation have attracted much attention, and its efficiency is considered to be an important factor for its practical application. In this study, BDD thin films were prepared on Ti plates by double bias-assisted hot filament chemical vapor deposition (HFCVD) technique. A reactive ion etching process was introduced by a positive grid bias and a negative substrate bias which can generate an electric field in HFCVD system. Then a novel structure of BDD electrode with nanocone arrays was successfully etched from a flat diamond thin film by this system. The addition of the bias greatly improved the etching efficiency and promoted the formation of nanocones structures. The cyclic voltammograms (CV) test showed nanostructured BDD (NBDD) electrodes had excellent electrochemical performance almost the same as that of the electrodes with untreated surfaces. It had a large effective electroactive surface area (EASA), which was 31.0% greater than the unetched electrode. As a result, the NBDD electrode exhibited improved electrocatalytic performance as compared with the untreated one, i.e., an about 24.3% increase of chemical oxygen demand (COD) removal efficiency. Among them, the superiority of NBDD electrode was obvious in the initial stage due to its highest concentration in the initial stage. In addition, the NBDD electrode achieved higher average current efficiency (ACE) as compared with the untreated one.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Diamond and Carbon-based Materials Research · Electrocatalysts for Energy Conversion · Supercapacitor Materials and Fabrication

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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