Flow synthesis and multidimensional parameter screening enables exploration and optimization of copper oxide nanoparticle synthesis†

IF 4.6 3区 材料科学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Neal Munyebvu, Zarina Akhmetbayeva, Steven Dunn and Philip D. Howes
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引用次数: 0

Abstract

Copper-based nanoparticles (NPs) are highly valued for their wide-ranging applications, with particular significance in CO2 reduction. However current synthesis methods encounter challenges in scalability, batch-to-batch variation, and high energy costs. In this work, we describe a novel continuous flow synthesis approach performed at room temperature to help address these issues, producing spherical, colloidally stable copper(II) oxide (CuO) NPs. This approach leverages stabilizing ligands like oleic acid, oleylamine, and soy-lecithin, a novel choice for CuO NPs. The automated flow platform facilitates facile, real-time parameter screening of Cu-based nanomaterials using optical spectroscopy, achieving rapid optimization of NP properties including size, size dispersity, and colloidal stability through tuning of reaction parameters. This study highlights the potential of continuous flow synthesis for efficient parameter exploration to accelerate understanding, optimization, and eventually enable scale-up of copper-based NPs. This promises significant benefits for various sectors, including energy, healthcare, and environmental conservation, by enabling reliable production with reduced energy and cost requirements.

Abstract Image

流动合成和多维参数筛选使氧化铜纳米颗粒合成的探索和优化。
铜基纳米颗粒(NPs)因其广泛的应用而受到高度重视,特别是在二氧化碳减排方面具有重要意义。然而,目前的合成方法面临着可扩展性、批间差异和高能源成本等方面的挑战。在这项工作中,我们描述了一种在室温下进行的新型连续流合成方法,以帮助解决这些问题,生产球形,胶体稳定的氧化铜(CuO) NPs。这种方法利用了稳定配体,如油酸、油胺和大豆卵磷脂,这是CuO NPs的一种新选择。自动化流程平台便于使用光谱学对cu基纳米材料进行方便、实时的参数筛选,通过调整反应参数实现NP性能的快速优化,包括粒径、粒径分散性和胶体稳定性。该研究强调了连续流综合在有效参数探索方面的潜力,以加速理解、优化,并最终实现铜基NPs的规模化。通过降低能源和成本要求,实现可靠的生产,这将为包括能源、医疗保健和环境保护在内的各个部门带来显著的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nanoscale Advances
Nanoscale Advances Multiple-
CiteScore
8.00
自引率
2.10%
发文量
461
审稿时长
9 weeks
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