Organic dyes are the most widely used compounds in industries due to their ability to resist fading when exposed to light, perspiration, water, oxidising agents, and microorganisms (Arunadevi et al., 2018; Saratale, Saratale, Chang, & Govindwar, 2011). Due to their widespread use and large-scale manufacturing, dyes are now found in considerable quantities in wastewater (Kazeminezhad & Sadollahkhani, 2014). Roughly 1–15 percent of synthetic textile dyes are estimated to be dumped into effluents during the manufacturing process (Shahabuddin et al., 2018). These dyes are released directly into water bodies, which caused substantial water contamination owing to their carcinogenic nature (Kumar & Pandey, 2017). Due to their enormous moelcular size and complicated structures, the majority of these dyes are hazardous and non-biodegradable and thus can result in major risks and threats to aquatic and human life (Tanwar, Kumar, Mandal, & Chemistry, 2017). Researchers are wokring hard to overcome this problem using different scientific methods. These dyes are removed via a range of physical, chemical and biological processes such as adsorption, precipitation, ozonisation (Saeed & Khan, 2017). Many of these techniques are non-destructive, insufficient and produce secondary contamination. Furthermore, well-established chemical techniques are non economical. Moreover, aerobic decontamination is inefficient for stable dyes, while anaerobic oxidation process of dyes results in the formation of carcinogenic aromatic amines (Nezamzadeh-Ejhieh & Khorsandi, 2010). Numerous sophisticated oxidation processes, notably sonocatalysis, ozonolysis, photo-Fenton, photocatalysis and photo electro-Fenton, have emerged as promising techniques for degrading toxic chemicals from wastewater (Kansal, Sood, Umar, Mehta, & Compounds, 2013). Modern photocatalysis uses heterogeneous semiconductors to degrade organic dyes/pollutants in water. Metal nanoparticles (NPs) are employed as heterogeneous photocatalysts in this method. TiO2 (Gupta et al., 2007; Kansal et al., 2013), ZnO (Ullah et al., 2015), BiVO4 (Chomkitichai et al., 2019), WO3 (Khan, Khan, Usman, Imran, & Saeed, 2020), Fe2O3 (Abhilash, Akshatha, & Srikantaswamy, 2019) and copper-based NPs have all been reported as potential heterogeneous photocatalysts (Gu, Chen, Chen, Zhou, & Parsaee, 2018).
Copper is one of the most inexpensive metal and has a diverse range of applications, including gas sensors (Mikami, Kido, Akaishi, Quitain, & Kida, 2019), lithium-ion batteries (Ha, Kim, & Choi, 2020; Lin et al., 2017), field emission devices (Banerjee & Joo, 2011), antibacterial agents (Mary, Ansari, & Subramanian, 2019), dye-sensitized solar cells (Cao et al., 2017), adsorption (BATOOL, QURESHI, HASHMI, MEHBOOB, & DAOUSH, 2019; Salehi et al., 2016) and heterogeneous catalysts (Marcelo, Puiatti, Nascimento, Oliveira, & Lopes, 2018; T. Zhang, Souza, Xu, Almeida, & Asefa, 2018). Additionally, copper-based compounds have recently been discovered to be helpful in a variety of photocatalytic applications, including the photoconversion of toxic hydrocarbons into harmless molecules (Arunadevi et al., 2018). Copper-based semiconductors do seem to have a small band gap that can be precisely tuned by using different methods to harvest wide range of natural/synthetic radiation (Salavati-Niasari & Davar, 2009). They were thus extensively employed as a strong heterogeneous photocatalyst. Since the electrons in the conduction band are unstable in phase pure CuO, the majority of the photogenerated electrons migrate to the valance band and recombine with the hole without engaging in the oxidation process (Sonia et al., 2015). This implies that by postponing the recombination of charge carriers in photocatalysis, the overall efficiency of the reaction can be enhanced. Different methods were used to decelerate the photogenerated electron-hole recombination in CuO including surface modification, rare eath and transition metal doping (Abu-Zied, Bawaked, Kosa, & Schwieger, 2016; Devi et al., 2017; Ekthammathat, Phuruangrat, Thongtem, & Thongtem, 2016; Meshram, Adhyapak, Mulik, & Amalnerkar, 2012). Doping of rare earth elements in CuO is one of the most effective method because it can delay the recombination rate of photogenerated charge carriers by introducing localised impurities/defect states near the velance band or the conduction band (or both) which can trap the electrons to enhance photocatalytic efficineicy (Devi et al., 2017). Furthermore, rare-earth elements have been found to decrease the bandgap of CuO, which permits faster charge carriers transition across the forbidden gap, reducing the recombination rate (Abu-Zied et al., 2016).
Nanoparticle preparation methods are significant for determining their properties. CuO NPs can be synthesized using a range of methodologies, including the sol-gel technique (Kayani, Umer, Riaz, & Naseem, 2015), co-precipitation (Vidyasagar, Naik, Venkatesh, & Viswanatha, 2011), hydrothermal method (X. Zhang, Zhang, Ni, & Zheng, 2008), green synthesis (Sutka & Mezinskis, 2012), solid state reaction (Singh & Bedi, 2011), sono-chemical method (Muhammad R Islam, Rahman, Farhad, Podder, & Interfaces, 2019), thermal decomposition (Muhammad R Islam et al., 2020) etc. Among them, the sol-gel method provides a convenient, efficient, simple, and cost-effective route for the synthesis of NPs that involves a self-sustaining reaction in a solution of various oxidizers.
In the present study, pure and La doped CuO nanoparticles have been synthesised using a facile sol-gel method. Analyses of the structural and optical characteristics of the nanoparticles as they were produced were carried out using FTIR, XRD, SEM, PL and UV–vis spectroscopy. Additionally, the impact of the La content on the NPs' photocatalytic activity was examined experimentally. The findings indicate that incorporation of La lowers the band gap of the CuO NPs, thus improving their photocatalytic activity. COMSOL 5.3a Licensced version is used to construct a 2D model of this research work to simulate photocatalytic degradation of MB dye by CuO-NPs in order to study corelation between experiment and simulation.