Due to its outstanding physical, chemical, and thermal properties, an increasing consideration has been paid to produce copper (Cu) nanoparticles (NPs). Various methods are accessible for producing Cu NPs by conceiving the top–down and bottom–up approaches. Electrodeposition is a bottom–up method to synthesize high-quality Cu NPs at a low cost. The attributes of Cu NPs rely on their way of deduction and electrochemical process parameters. This work aims to deduce the mean size of Cu NPs. Artificial neural networks (ANN) and nature-inspired algorithms, namely genetic algorithm (GA), firefly algorithm (FA), and cuckoo search (CS) algorithm were used to predict and optimize the electrochemical parameters. The results obtained from ANN prediction agreed with data from the electrodeposition process. All nature-inspired algorithms reveal similar operating conditions as optimal parameters. The minimum NP size of 20 nm was obtained for the process parameters of 4 g·l⁻¹ of CuSO₄ concentration, electrode distance of 3 cm, and a potential difference of 27 V. The synthesized NP size was in line with the anticipated NP size. The scanning electron microscope and X-ray diffractometer (XRD) were performed to analyze the nanoparticle size and morphology.

中文翻译：

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使用 ANN 和自然启发算法对铜纳米粒子合成的电沉积过程进行建模和优化

由于其出色的物理、化学和热性能，人们越来越多地考虑生产铜（Cu）纳米颗粒（NP）。通过自上而下和自下而上的方法，可以使用多种方法来生产铜纳米粒子。电沉积是一种自下而上的方法，可以低成本合成高质量的铜纳米粒子。Cu NPs 的属性取决于其推导方式和电化学过程参数。这项工作旨在推导 Cu 纳米颗粒的平均尺寸。使用人工神经网络（ANN）和自然启发算法，即遗传算法（GA）、萤火虫算法（FA）和布谷鸟搜索（CS）算法来预测和优化电化学参数。ANN 预测获得的结果与电沉积过程的数据一致。所有受自然启发的算法都揭示了类似的操作条件作为最佳参数。在工艺参数为 4 g·l 的情况下，获得了 20 nm 的最小 NP 尺寸CuSO _4浓度为^-1，电极距离为3 cm，电势差为27 V。合成的NP尺寸与预期的NP尺寸一致。使用扫描电子显微镜和X射线衍射仪（XRD）分析纳米颗粒的尺寸和形貌。