Selective conversion of CO2 to CO using earth abundant tin modified copper gas diffusion electrodes

Preetam K. Sharma , Shahid Rasul , Da Li , Eileen H. Yu
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引用次数: 1

Abstract

Earth-abundant copper-tin (CuSn) electrocatalysts are potential candidates for cost-effective and sustainable production of CO from electrochemical carbon dioxide reduction (eCO2R). However, the requirement of high-overpotential for obtaining reasonable current, low Faradaic efficiencies (FE) and low intrinsic catalytic activities require the optimisation of the CuSn nanoarchitecture for the further advancement in the field. In the current work, we have optimised Sn loading on Cu gas diffusion electrodes (GDEs) by electrochemical spontaneous precipitation. Samples with various Sn loadings were tested in a three-chamber GDE reactor to evaluate their CO2 reduction performances. The best performance of 92% CO Faradaic efficiency at a cathodic current density of 120 mA cm−2 was obtained from the 20 min Sn deposited Cu2O sample operated at −1.13 V vs. RHE. The electrocatalyst had ∼13% surface coverage of Sn on Cu GDE surface, and had Sn in oxide form and copper in metallic form. The catalyst also showed stable performance and was operable for >3 h under chronoamperometric conditions. The surface of the GDE reduces from Cu2O to Cu during eCO2R and goes further reconstruction during the eCO2R. This study demonstrates the potential of Cu–Sn for selective CO production at high current densities.

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用富含稀土的锡改性铜气体扩散电极选择性转化CO2为CO
地球上储量丰富的铜锡(CuSn)电催化剂是电化学二氧化碳还原(eCO2R)经济高效、可持续生产CO的潜在候选材料。然而,为了获得合理的电流,需要高过电位,低法拉第效率(FE)和低内在催化活性,需要优化CuSn纳米结构以进一步推进该领域的发展。在目前的工作中,我们利用电化学自发沉淀法优化了Cu气体扩散电极(GDEs)上的Sn负载。在三室GDE反应器中测试了不同Sn负载的样品,以评估其CO2还原性能。当阴极电流密度为120 mA cm−2时,在−1.13 V / RHE下工作20 min的Cu2O样品获得了92%的CO法拉第效率。该电催化剂在Cu GDE表面上Sn的表面覆盖率为~ 13%,并且Sn以氧化物形式存在,铜以金属形式存在。该催化剂表现出稳定的性能,在计时电流条件下可运行3小时。在eCO2R过程中,GDE表面由Cu2O还原为Cu,并在eCO2R过程中进一步重构。该研究证明了Cu-Sn在高电流密度下选择性CO生产的潜力。
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来源期刊
材料导报:能源(英文)
材料导报:能源(英文) Renewable Energy, Sustainability and the Environment, Nanotechnology
CiteScore
13.00
自引率
0.00%
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0
审稿时长
50 days
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