Rational design of oxygen evolution reaction (OER) catalysts at low cost would greatly benefit the economy. Taking advantage of earth-abundant elements Si, Co and Ni, we produce a unique-structure where cobalt-nickel silicate hydroxide [Co2.5Ni0.5Si2O5(OH)4] is vertically grown on a reduced graphene oxide (rGO) support (CNS@rGO). This is developed as a low-cost and prospective OER catalyst. Compared to cobalt or nickel silicate hydroxide@rGO (CS@rGO and NS@rGO, respectively) nanoarrays, the bimetal CNS@rGO nanoarray exhibits impressive OER performance with an overpotential of 307 mV@10 mA cm−2. This value is higher than that of CS@rGO and NS@rGO. The CNS@rGO nanoarray has an overpotential of 446 mV@100 mA cm−2, about 1.4 times that of the commercial RuO2 electrocatalyst. The achieved OER activity is superior to the state-of-the-art metal oxides/hydroxides and their derivatives. The vertically grown nanostructure and optimized metal-support electronic interactions play an indispensable role for OER performance improvement, including a fast electron transfer pathway, short proton/electron diffusion distance, more active metal centers, as well as optimized dual-atomic electron density. Taking advantage of interlay chemical regulation and the in-situ growth method, the advanced-structural CNS@rGO nanoarrays provide a new horizon to the rational and flexible design of efficient and promising OER electrocatalysts.
合理设计低成本的析氧反应(OER)催化剂将大大提高经济效益。利用地球上丰富的元素Si, Co和Ni，我们生产了一种独特的结构，将钴镍硅酸盐氢氧化物[Co2.5Ni0.5Si2O5(OH)4]垂直生长在还原氧化石墨烯(rGO)载体上(CNS@rGO)。这是一种低成本、有前景的OER催化剂。与钴或硅酸镍hydroxide@rGO(分别为CS@rGO和NS@rGO)纳米阵列相比，双金属CNS@rGO纳米阵列表现出令人印象深刻的OER性能，过电位为307 mV@10 mA cm−2。该值高于CS@rGO和NS@rGO。CNS@rGO纳米阵列的过电位为446 mV@100 mA cm−2，约为商用RuO2电催化剂的1.4倍。所获得的OER活性优于最先进的金属氧化物/氢氧化物及其衍生物。垂直生长的纳米结构和优化的金属-支撑电子相互作用对OER性能的提高起着不可或缺的作用，包括快速的电子转移途径、更短的质子/电子扩散距离、更活跃的金属中心以及优化的双原子电子密度。利用层间化学调控和原位生长的方法，先进结构的CNS@rGO纳米阵列为合理、灵活地设计高效、有前途的OER电催化剂提供了新的视野。
{"title":"In situ confined vertical growth of Co2.5Ni0.5Si2O5(OH)4 nanoarrays on rGO for an efficient oxygen evolution reaction","authors":"Yang Mu, Xiaoyu Pei, Yunfeng Zhao, Xueying Dong, Zongkui Kou, Miao Cui, Changgong Meng, Yifu Zhang","doi":"10.1016/j.nanoms.2022.04.002","DOIUrl":"https://doi.org/10.1016/j.nanoms.2022.04.002","url":null,"abstract":"<p>Rational design of oxygen evolution reaction (OER) catalysts at low cost would greatly benefit the economy. Taking advantage of earth-abundant elements Si, Co and Ni, we produce a unique-structure where cobalt-nickel silicate hydroxide [Co<sub>2.5</sub>Ni<sub>0.5</sub>Si<sub>2</sub>O<sub>5</sub>(OH)<sub>4</sub>] is vertically grown on a reduced graphene oxide (rGO) support (CNS@rGO). This is developed as a low-cost and prospective OER catalyst. Compared to cobalt or nickel silicate hydroxide@rGO (CS@rGO and NS@rGO, respectively) nanoarrays, the bimetal CNS@rGO nanoarray exhibits impressive OER performance with an overpotential of 307 mV@10 mA cm<sup>−2</sup>. This value is higher than that of CS@rGO and NS@rGO. The CNS@rGO nanoarray has an overpotential of 446 mV@100 mA cm<sup>−2</sup>, about 1.4 times that of the commercial RuO<sub>2</sub> electrocatalyst. The achieved OER activity is superior to the state-of-the-art metal oxides/hydroxides and their derivatives. The vertically grown nanostructure and optimized metal-support electronic interactions play an indispensable role for OER performance improvement, including a fast electron transfer pathway, short proton/electron diffusion distance, more active metal centers, as well as optimized dual-atomic electron density. Taking advantage of interlay chemical regulation and the <em>in-situ</em> growth method, the advanced-structural CNS@rGO nanoarrays provide a new horizon to the rational and flexible design of efficient and promising OER electrocatalysts.</p>","PeriodicalId":501090,"journal":{"name":"Nano Materials Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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