Cogent Engineering ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/oaen20 Synthesis of nanostructured cupric oxide for visible light assisted degradation of organic wastewater pollutants David Dodoo-Arhin, Etchu E. Mbu, Seteno K. Ntwampe, Edward N. Malenga, Elvis Fosso-Kankeu, Benjamin Agyei-Tuffour, Emmanuel Nyankson, Abu Yaya & Henry Agbe | To cite this article: David Dodoo-Arhin, Etchu E. Mbu, Seteno K. Ntwampe, Edward N. Malenga, Elvis Fosso-Kankeu, Benjamin Agyei-Tuffour, Emmanuel Nyankson, Abu Yaya & Henry Agbe | (2021) Synthesis of nanostructured cupric oxide for visible light assisted degradation of organic wastewater pollutants, Cogent Engineering, 8:1, 1920563, DOI: 10.1080/23311916.2021.1920563 To link to this article: https://doi.org/10.1080/23311916.2021.1920563 © 2021 The Author(s). This open access Published online: 11 May 2021. article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Submit your article to this journal Article views: 537 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaen20 Synthesis of nanostructured cupric oxide for visible light assisted degradation of organic wastewater pollutants David Dodoo-Arhin, Etchu E. Mbu, Seteno K. Ntwampe, Edward N. Malenga, Elvis Fosso-Kankeu, Benjamin Agyei-Tuffour, Emmanuel Nyankson, Abu Yaya and Henry Agbe Cogent Engineering (2021), 8: 1920563 Page 1 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 MATERIALS ENGINEERING | RESEARCH ARTICLE Synthesis of nanostructured cupric oxide for visible light assisted degradation of organic wastewater pollutants Received: 22 November 2020 David Dodoo-Arhin 1*, Etchu E. Mbu2, Seteno K. Ntwampe2, Edward N. Malenga2, Elvis Fosso- Accepted: 13 April 2021 Kankeu 2, Benjamin Agyei-Tuffour1, Emmanuel Nyankson1, Abu Yaya1 and Henry Agbe3 *Corresponding author: David Dodoo- Abstract: When organic dye-containing wastewater from textile industries are Arhin, Department of Materials Science and Engineering, University sometimes released into the environment, the liquids tend to pollute the environ- of Ghana, Legon-Accra, Ghana E-mail: DDARHIN@YAHOO.COM;ddo- ment whilst their solid residue accrues on land after the evaporation of the water. doo-arhin@ug.edu.gh Most of these synthetic compounds are known to be poisonous and carcinogenic to Reviewing editor: living organisms. For this study, a relatively simple, sustainable and cost-effective Julio Sánchez, Departamento De Ciencias Del Ambiente, Universidad approach have been utilized to synthesize CuO nanoparticles using copper precursor De Santiago De Chile, CHILE salts: (CuSO4.5H2O) and (Cu(NO3)2.3H2O), as a remedy for dye pollution reduction in Additional information is available at water. Due to their simplicity of synthesis, insignificant harmfulness and cost, the end of the article copper (II) oxide (CuO) nanoparticles were used to breakdown three generally utilized dyes; Rhodamine B (RhB), Methylene Blue (MB)- [Methylthioninium chloride] and Methyl Orange (MeO). The as-prepared nanoparticles were characterized to ABOUT THE AUTHOR PUBLIC INTEREST STATEMENT Prof. David Dodoo-Arhin is an Associate Professor Textile dye pollutants with the wastewater from in the Department of Materials Science and industries which make use of such dyes are Engineering, University of Ghana. His research sometimes released into the environment. These interest is in ceramics and nanostructured contaminate both water bodies and the sur- materials for energy and environmental applica- rounding land environment. These chemicals are tions. noted for their toxicity to living organisms and Etchu Esther Mbu is an MPhil graduate of the they can cause cancers in human beings when Department of Materials Science and ingested. This paper explores the development of Engineering, University of Ghana. Her research a worthwhile dye polluted waste water treat- interest is in nanomaterials for water purification. ment process using a nanostructured photoca- Prof. Seteno K. Ntwampe, Elvis Fosso-Kankeu and talysts (CuO) and the significantly accessible sun Edward Ntumba Malenga are researchers in the light. In the presence of water, photocatalysts Water Pollution Monitoring and Remediation when illuminated with light creates reactive David Dodoo-Arhin Initiatives Research Group of the North-West species (radicals) which can attack and break University, South Africa. Their research speciali- down organic dye molecules into harmless zations are in Biological Wastewater Treatment compounds. This paper reports that photocata- and Green Chemistry Nanotechnologies. lysis using nanostructured cupric oxide produced Benjamin Agyei-Tuffour, Emmanuel Nyankson under different conditions is very effective in and Abu Yaya are researchers in the Department breaking down textile dye pollutants in water of Materials Science and Engineering. Their when sunlight is shone on the mixture. research interests include Composite Materials for Energy, Water Purification, and Environment. Henry Agbe is a PhD student at the Centre Universitaire de Recherche sur l’Aluminium, Université du Québec à Chicoutimi, Québec, Canada. His research interest includes nanos- tructured materials for water purification and biomedical applications. © 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Page 2 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 determine the ordered arrangement of atoms, functional groups, weight loss, thermal properties, microstructure and surface characteristics. Most significantly, the predominant preferential crystal growth was along the {002}/{-111} plane for the sulphate-based precursor whiles for the nitrate based precursor, it was prefer- entially grown along the {111} direction. The mesoporous nanoparticles had aver- age crystallite sizes of 12 nm and 15 nm; and BET surface areas of 42.9 m2/g, and 69.6 m2/g respectively. The as-prepared nanoparticles were assessed for their photocatalytic behaviour in response to visible light exposure for 100 minutes at 25- min’ intervals. The nitrate precursor-based CuO photocatalysts showed relatively higher photodegradation efficiency (MeO-94.3%; MB- 90.6%; RhB - 99.6%) as com- pared with the sulphate precursor-based CuO photocatalysts (MeO-85.2 %; MB- 87.9%; RhB- 98.8%). Subjects: Environmental Change & PollutionMaterials ScienceChemical EngineeringEnvironmental Keywords: Nanoparticles; Copper Oxide; Photocatalysis; Wastewater; Dye; Degradation 1. Introduction Nanostructured semiconducting materials have over the years inspired intensive research activ- ities for several applications because of their unique characteristics such as their high surface-to- volume ratio, and quantum confinement effects at the nanometre scale. As industrialization rapidly evolves, substantial quantity of waste keeps being discharged into the environment which tends to negatively affect the quality of water for everyday use (Agbe et al., 2018; Dodoo- Arhin et al., 2018; Omaish et al., 2015). Organic dyes (Azo and Xanthene) have a wide variety of applications in numerous industries such as the paper and pulp, edible confectionaries, and leather tanning industries. This makes their utilization on a large-scale, unavoidable. A primary character- istic of Azoic dyes is the unique N = N chromophoric units whiles that of Xanthene is the yellow solid organic compound with the formula CH2[C6H4]2O that is soluble in common organic solvents (Benkhaya et al., 2020). With the textile industry having about 60–70% usage of all available commercial dye products (Saggioro et al., 2011), the dye pollutants from these industries tend to contaminate the environment especially water bodies; when they are indecorously disposed-of (Habib et al., 2013; Rahman et al., 2014; Rezig & Hadjel, 2014). Furthermore, recent advances in environmental remediation strategies such as photocatalysis and flocculation have been researched as an alternative technique for purification of dye-polluted water (Agbe et al., 2018; Diko et al., 2020). Photocatalysis using porous nanostructured semiconducting transition metal oxide photocatalysts such as TiO2, SnO (Byberg et al., 2013), ZnO and Cu2O (Agbe et al., 2019) seem to be the most suitable approach due to the fact that these photocatalysts are energetically sustainable, and can be easily used in combination with other catalysts. These nanostructured semiconductors are environmentally benign, and possess suitable characteristics needed to facil- itate dye decomposition; albeit, under specific process conditions. When investigating complex cuprates, copper oxides can be used as reference materials, since most cuprates have shown high-Tc superconductivity due to a Jahn-Teller distortion associated with the structural characteristics of their divalent copper monoxide structure. This phenomenon tends to introduce strong electron–phonon interactions for the impartation of the required super- conductivity and photocatalytic dye degradation process (Kamimura et al., 2005). To fully under- stand the origin and mechanism of this phenomenon, numerous studies have ensued on simple and complex copper oxides (Elwell et al., 2017). Cupric oxide (CuO) is unique amongst many of the oxides within the 3d transition series. This is largely because of its unique monoclinic structured planar square coordination. The copper bonds with oxygen in a four coplanar arrangement within a distorted tetrahedral environment, and at the same time being coordinated by four other copper Page 3 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 � � atoms. Two sets of 11 CuO4=2 chains directed along the [110] and staggered along the [001] planes then form a three dimensional crystal structure of the CuO (Åsbrink & Norrby, 1970; Tunell et al., 1935). Overall, some research interest on Tenorite (CuO), a p-type semiconductor, is based on its ease of synthesis, benignity to organisms and ease of engineering to give it a variety of morphologies at the nanoscale level which can be enhanced for high catalytic activity by narrow- ing the energy band-gap within 1.2–1.8 eV (Bhattacharjeea & Ahmaruzzaman, 2016). in view of these, CuO has found applications in catalysis, solar energy systems, super-capacitors, and as electrode material for lithium-ion batteries (Shaikh et al., 2011). Exposing the wastewater containing a dye to visible light in the presence of CuO culminates in their degradation via an oxidation reaction mechanism associated with valence-hole creation, with electrons in the conduction bands being responsible. Movement of electrons out of the valence band, generates unstable free radical species with a high oxidation potential. Their availability and contact with the dye molecules in the wastewater, results in its decomposition to by-products which are less harmful (Tran & Nguyen, 2014). Several techniques have been used to synthesize CuO nanostructures with different morphologies. The synthesis techniques include microemulsion synthesis, sonochemical deposition, chemical vapour deposition, double-jet precipitation, high- temperature synthesis, etc. (Black et al., 2010). In this research work, we investigate the influence of precursor salt (CuSO4.5H2O and Cu(NO3)2.3H2O) for the synthesis of CuO nanoparticles for the light-aided catalytic decomposition of the following dyes: Methyl Orange, Methylthioninium chlor- ide (Methylene Blue), and Rhodamine B under varied durations of visible light illumination. Several characterization techniques were used to investigate the structural, thermal, optical and micro- structural properties of the synthesized copper oxide samples. 2. Materials and methods 2.1. Synthesis of the copper oxide nanoparticles In this research, analytical grade chemicals and reagents were used without further purification. These include copper(II) nitrate trihydrate (Cu(NO3)2.3H2O), copper sulphate pentahydrate (CuSO4. 5H2O), sodium hydroxide (NaOH), Rhodamine B dye (C28H31ClN2O3), distilled water, methyl orange (C14H14N3NaO3S), methylene blue [Methylthioninium chloride -(C16H18ClN3S)], 30% hydrogen per- oxide (H2O2) and ethanol (C2H5OH). Simple solution precipitation reaction method was adopted to synthesize the copper oxide (CuO) nanoparticles by using two (2) different precursors. In the typical synthesis process, the copper salts ((Cu(NO3)2.3H2O) and (CuSO4.5H2O)) were separately dissolved in deionised water to prepare 0.02 M aqueous precursor solution, heated to a temperature of 60°C and then 1.6 g/L NaOH pellets added under constant stirring. The sky blue solution changed to milky blue and then gradually changed into a dark-brown precipitate. The reaction was allowed to continue for about 30 min till all blue precipitate converted into the dark brown copper oxide particles. The solution was allowed to cool to room temperature; the precipitate subsequently centrifuged and rinsed with distilled water and ethanol (1:1) several times, then oven dried (70°C) to obtain CuO powder for analysis and photocatalytic application. The CuO powder obtained using the sulphate precursor is denoted as CuO-S60 whiles those obtained using the Nitrate precursor, denoted as CuO-N60. 2.2. Characterisation of the copper oxide nanoparticles The obtained CuO nanoparticles were then characterised using X-Ray Diffraction (XRD), Fourier Transform Infra-Red (FT-IR) spectroscopy, TG-DTA, Scanning Electron Microscopy (SEM) and Brunauer–Emmett–Teller (BET) surface area analysis to determine some primary attributes, i.e. the ordered arrangement of atoms, functional groups, weight loss, thermal properties, the microstructure and surface characteristics (e.g., porosity), respectively. The detailed analytical methods (qualitative) included powder x-ray diffraction (PXRD) to generate profiles within a 20°- 70° 2θ range using 14 s per step at a step size of 0.017°. The attainment of diffraction profiles of all synthesized CuO powders was conducted using a theta-theta geometry aligned Panalytical Page 4 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 Empyrean diffractometer with a Cu Kα (λ = 1.5406 Å) radiation tube (40 kV, 45 mA). Subsequently, a qualitative phase analysis was conducted based on the ICSD database using the X’Pert Highscore plus search match software (Panalytical, Netherlands). Furthermore, a NIST SRM 640d (Si) standard was used for the instruments’ resolution contribution to the diffraction profiles generated (Caglioti et al., 1958), with the finalised peak profiles being comparatively analysed, taking into consideration their shape and breadth, by applying constrained symme- trical pseudo-Voigt functions to the Caglioti equation (Leoni et al., 2006). For microstructure analysis, a one-step microstructure parameter refinement strategy in PM2K software (Scardi & Leoni, 2002) was adopted for whole powder pattern modelling (WPPM) (Luk et al., 2015). The morphological examinations were conducted on a TESCAN Vega-3 Scanning Electron Microscope equipped with EDX analysis software operating within 0.2–30 kV and 2 × 10–5 ms—10 ms per pixel scanning speed on a 0.5 g sample. Prior to the analysis, the CuO powder samples were sputter covered with a thin carbon film to make them conductive and permit for higher magnifications. The surface functional groups were recorded on a PerkinElmer Spectrum Two (PerkinElmer Inc., UK) Fourier Transform Infrared (FTIR) spectrometer. Spectra data were recorded within the 4000–400 cm−1 spectral range in transmission mode, resolution of 4 cm−1, and analyzed using the Spectrum 10 software. The optical property of the nanoparticles was determined on a Thermo Fisher Scientific GENESYS™ 10S UV-Vis Spectrophotometer operated in absorbance mode within a scanning range of 200–900 nm and a 5 nm scan per step. Specific surface area and porosity measurements were conducted on a Tristan II 3020 version 2 (Micrometrics, USA) sorption analyzer by means of the multipoint Brunauer-Emmett-Teller (BET) typical procedure. Preceding the data collection, 0.4 g of the powder specimens were degassed in vacuity at a temperature of 350°C for 24 h using a liquid nitrogen medium and an adsorbate at 77 K. Complete isotherm scans were run between the relative pressures of 4E−6 to 1. The information obtained from the BET profiles, i.e. monolayer adsorption/desorption adsorbate pro- files, were used for surface area including pore size volume determined using a Barrett-Joyner- Halenda (BJH) analysis, respectively (Zhang et al., 2014). 2.3. Photocatalytic activity The photocatalytic activity of the copper oxide nanoparticles from the two precursors were evaluated by determining the decomposition of Rhodamine B, Methyl Orange, and Methylene Blue dyes under visible light irradiation. The experiments were carried out in a 100 mL capacity glass photochemical reactor using a 400 Watt (W) medium pressure mercury visible light source. A solution (200 ml) containing Rhodamine B dye (0.01 g) was used by mixing the dye with distilled water subsequent to H2O2 (1.5 ml) addition as a mediator for increased free radical generation to enhance the photodegradation process using nanostructured CuO as a semiconductor (Modec et al., 2020). A suspension using 0.1 g of the as prepared CuO nano- particles in distilled water (50 mL) was prepared separately to which a dye solution (30 ml) was added prior to visible light irradiation. This suspension was stirred for 30 min in the dark at 1000 rpm for optimised dye adsorption on the CuO particles. Thereafter, the suspension was exposed to visible light (400 W) with periodic sampling at 25 min intervals using polypropylene syringes. The sample aliquots were immediately centrifuged to separate the CuO from the water matrix at 5000 rpm for 10 min to obtain a particle free supernatant. To determine dye removal, a Pelkin-Elmer Two UV-Vis spectrophotometer was used at a scanning range of 200 to 800 nm with the light absorption of the supernatant being quantified in a 3 ml plastic cuvette. For photocatalysis, the light irradiation times were 0, 25, 50, 75, and 100 min. The photocatalytic procedure was repeated as described above for each of the dyes using the as-prepared nanoparticles. Page 5 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 3. Results and discussion 3.1. Synthesis of the copper oxide nanoparticles In aqueous solution, Cu(NO3)2.3H2O and CuSO4. 5H2O dissociates into [Cu(H2O)6]2+ ions (respon- sible for the sky blue colorations) and NO − 3 or SO 2- 4 anions. Coordination of the NO − 3 or SO 2- 4 anions with other copper ions may partially occur in the solution. Concerning the [Cu(H 2+ 2O)6] complex, the structural geometry is such that the Cu2+ ion is completely surrounded by a number (n = 6) of water molecules which results in a shielding effect. Furthermore, the interaction of the water molecules with the dissolved Cu2+ ions form a square-planar solvation complex geometric structure (Cu(OH) 2-4 ) with the other water molecules (n = 4) situated at its axis. Such complexes are well described by the anionic coordination polyhedral theoretical model (Sambandam et al., 2005), with both the Cu2+ existing in the form of complexes whose ligands are OH− ions. For each growth unit, the coordination number will be equivalent to that of the crystal formed. The proliferation of these growth units and their incorporation into the crystal nucleus is largely dependent on dehydration. For this study, the growth unit of the synthesized CuO nanocrystals will then be the intermediate Cu(OH) 4-6 ions which forms a coordinating octahedron structure with the NaOH in solution. Overall, the binding energies of the coordinating OH-groups are different based on their location in the octahedron structure: the binding energies of the OH− ions concen- trated around the octahedron axis are higher than those located on the plane axis (Koehler et al., 2014). For this case, the arrangement is such that two OH− ions will be located on the perpendi- cular axis, with some OH- ions (n = 4) being arranged on a planar square geometry. Meaning, the OH− ions on the octahedron axis are easily replaceable which will culminate in higher dehydration- related CuO nanostructure growth on the axis than on the plane. Thus, the variance in the morphological structure of numerous CuO semiconductors (e.g., nanorods, nanobelts, nanowires, etc) is associated with variability in the growth rates along the crystallographic plane. Therefore, such a variation in the growth rates can be influenced by synthesis conditions one of which is temperature as illustrated elsewhere (Black et al., 2010), with the reactions leading to the forma- tion of the CuO nanoparticles being illustrated as in Equations 1 to 6. Cu2þSO2 þ4 ðaqÞþ2Na OH ðaqÞ !CuðOHÞ2 aq þ Na2SO4ðaqÞ (1) ð Þ � � CuðOHÞ 2 aq þ 2OH ðaqÞ ! CuðOH 2 Þ ð Þ 4 ðaq (2) Þ � � Cu OH 2 heat ð Þ4 aq ! CuOðsÞ þ 2OH ðaqÞ þ H2OðlÞ (3) ð Þ 60�C Or Cu2þNO 3ðaqÞþ2Na þOH ðaqÞ!CuðOHÞ2ðaq þ 2NaNOÞ 3ðaqÞ (4) � � Cu 2ðOHÞ2 aq þ 2OH ðaqÞ ! CuðOHÞ4 aq (5) ð Þ ð Þ � � Cu OH 2 heatð Þ4 aq ! CuOðsÞ þ 2OH ð Þ � ðaqÞ þ H2OðlÞ (6) 60 C For example, when adding NaOH to a low-temperature synthesis precursor solution, intercon- nected hydrogen bonds may form within the hydroxyl groups of the Cu(OH) 4- 6 complex: one consequence of this will be the limited directional growth which will culminate into a variety of shapes for the formed nanocrystals (Vashistha et al., 2016). However, this is not observed at higher temperatures (25 °C < T < 100 °C) whereby nucleation and growth rates will not be hampered as Page 6 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 the hydrogen bonds will be increasingly debilitated with temperature. In this research, and to avoid evaporation due to thermo-agitation effects, a median temperature of 60°C was chosen, which was also deemed sufficient for the reaction to proceed. 3.2. X-ray diffraction, electron microscopy, and energy dispersive X-Ray Spectroscopy (EDX) analyses The XRD patterns (Figure 1a) of the two synthesized CuO samples, showed that the tenorite phase was produced both for the nitrate and sulphate-based precursors with different crystal growth directions. Most significantly, the predominant preferential crystal growth was along the {002}/ {-111} plane for the sulphate-based precursors whiles for the nitrate-based precursor, it was preferentially grown along the {111} direction. In light of the bigger dimension of the sulphate ion in contrast with the relatively small-sized nitrate ions in solution, there is the possibility that the solvated nitrate ions cause a shielding effect on the interaction between the Cu2+ ions and the water molecules leading to the formation of a Cu(OH) 4- 6 complex structure. The described phe- nomenon in the case of the nitrate precursor-based system, could bring about smaller and robust Cu-O bonds resulting in smaller crystallite sizes contrasted with those coming from the sulphate precursor-based system as seen in this work. From Figure 1(a), it can be discovered that for the CuO specimen prepared utilizing the nitrate- based precursor (CuO-N60), the most compactly packed crystal planes (preferential crystallo- graphic plane for the growth of crystals) are the {111}. This could be attributed to that fact that the copper oxide keeps up the majority of its mainstay structure, which begins from a principal metallic copper crystal lattice (Modec et al., 2020) in which the {111} planes are the most compactly packed. For the sulphate precursor-based CuO nanoparticles (CuO-S60), the predomi- nant preferential crystal growth was along the {002}/{-111} plane. For whole powder profile modelling (WPPM) of the XRD profiles, using the one-step microstruc- ture parameter refinement strategy in the PM2K software (Luk et al., 2015), the microstructures of copper oxide specimens are shown in (Figure 1b). The WPPM was conducted taking into considera- tion the presence a unimodal lognormal distribution of spherical crystallites (Figure 1c). The distribution function computes analytical Fourier coefficients corresponding to a distribution of crystallite of a given shape (e.g., sphere”, “cube”, “tetrahedron”, “octahedron”, “cylinder”, etc.). Figure 1. (a) XRD plots of the 90000 CuO nanoparticles showing dif- N60 ferent preferential crystallo- 80000 S60 graphic growth directions. (b) Modelled XRD patterns for (i) 70000 CuO-S60, and (ii) CuO-N60. (c) Lognormal distribution of crys- 60000 tallite sizes. 50000 40000 30000 20000 10000 0 30 35 40 45 50 55 60 65 70 2 Theta (degrees) Page 7 of 17 Intensity (a.u) (110) (002) (111) (-202) (020) (202) (-113) (-311) (200) Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 Figure 1. Continued. 45000 CuO-S60 CuO-N6050000 40000 Experimental Experimental 35000 Calculated 40000 Calculated 30000 Difference Difference 25000 30000 20000 20000 15000 10000 10000 5000 0 0 30 35 40 45 50 55 60 65 70 30 35 40 45 50 55 60 65 70 2 Theta (degrees) 2 Theta (degrees) Figure 1. Continued. 0.10 CuO-N60 CuO-S60 0.08 0.06 0.04 0.02 0.00 0 5 10 15 20 25 30 35 40 Crystallite Size (nm) Typically, the normalised positively defined function g(D) for the lognormal distribution of crystal- lites is given as (Luk et al., 2015): " � � # 1 1 ln D 2 μ gðDÞ ¼ pffiffiffiffiffiffi exp (7) Dσ 2π 2 σ where D is the crystallite size, σ is the variance and µ is the lognormal mean of the distribution. The analytical Fourier coefficients for the distribution are obtained using Equation. (8) (Luk et al., 2015): LK ∫ AcðL;DÞD3gðDÞdD A L 1ð Þ ¼ (8) 0 ∫ D3gðDÞdD 1 Page 8 of 17 Frequency (a.u) Intensity (Counts) Intensity (Counts) Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 where g (D) is the chosen crystallite size distribution, Ac (L, D) is the Fourier transform correspond- ing to the chosen crystallite shape and K is a constant depending on crystallite shape and orientation of the crystallite with respect to the unit cell (i.e., K = K (h, k, l, shape)). The outcome of the WPPM concurred with observed data, which suggested that the assump- tion made of a uniaxial shape was valid for the crystallites investigated. From the lognormal distribution of spheres (Figure 1c), the average crystallite size ranges from 12 nm (CuO-S60) and 15 nm (CuO-N60). The SEM images in (Figure 2) indicate the synthesis of agglomerated “hairy” nanostructures for the two conditions investigated. This suggested the validity of an earlier explanation that the synthesized CuO nanocrystal at median temperature would have 2D-based axes growth, as observed in the images attained, which clearly demonstrate a self- alignment of nanostructured spherical particles arranged in a clearly observable hair-like structure. Further evidence was provided by the XRD spectra which was consistent with hair- like structure spectra of similar aligned and sized nanoparticles. From this, it was deduced that there was non-occurrence of a suitable epitaxy, i.e. that the nanocrystals were aligned along rods without a crystallographic relationship. Figure 3(a) and (b) exhibits the energy dispersive x-ray (EDX) spectra and the corresponding atomic weight distributions for the CuO-S60 and CuO-N60 specimens, respectively. The weight percent (wt %) and atomic percent (at %) demonstrate plainly that the atoms in the specimen exist in an almost 1:1 mole proportion which is the situation in the CuO compound. This subsequently further affirmed that the prepared particles were single phased CuO nanoparticles. 3.3. UV-VIS and FTIR spectroscopy analyses The absorbance spectra for the CuO specimen as presented in Figure 4 exhibit wide shoulders from 255 nm to 450 nm. Utilizing the classical tauc approach, the optical energy band gaps were assessed to be 2.12–- 2.4 eV for CuO-S60 and CuO-N60, respectively. This counselled that the produced nanocrystals were most probable to efficiently take in photons within the visible-light range of the electro- magnetic spectrum. Following the quantum size confinement phenomenon discovered in CuO (Himmetoglu et al., 2011; Raul et al., 2014) whereby the energy band-gap increments with diminishing crystallite size, the observed pattern in the energy band-gaps concurs with the information gotten from the XRD data. The FTIR spectra for the as-prepared CuO nanocrystals is presented in Figure 5. The bands around 3475, 2927 and 3390 cm−1 relate to O-H stretching vibrations of the crystal water clung to the nanoparticles’ surface. The vibrational modes of the Cu- O bond are observed around 1636 cm−1 and 1644 cm−1 while those found around 482, 498, 595, Figure 2. SEM images of (a) CuO-S60 and (b) CuO-N60. Page 9 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 Figure 3. (a) (i) Energy disper- sive x-ray spectrum and (ii) atomic weight distribution of Cu and O in CuO-S60 sample. (b) (i) Energy dispersive x-ray spectrum and (ii) atomic weight distribution of Cu and O in CuO- N60 sample. Figure 3. Continued. 603 cm−1 and 1364 cm−1 can be allocated to the CuO finger print vibrational modes (Dollimore et al., 1976). These absorption bands thusly affirm the presence of CuO nanoparticles. 3.4. Brunauer–Emmett–Teller (BET) Specific Surface area and Barrett–Joyner–Halenda (BJH) Porosimetry analysis The Brunauer–Emmett–Teller (BET) specific surface area and the and Barrett–Joyner–Halenda (BJH) pore architecture of the as-prepared copper oxide samples were examined using the nitrogen adsorption–desorption isotherms (Sing et al., 1985). The nitrogen adsorption–desorption isotherms of the prepared CuO nanocrystals as shown in Figure 6, are of the distinctive type III and IV configuration with characteristic H2 and H3 hysteresis loops in the range of 0.45–0.8P/P0 and 0.85–1.0P/P0 respectively: an indication of pseudo-mesoporous structures (Archina et al., 2016). This pore structure and distributions can help in improving efficient oxidation processes as they result in faster diffusion of various reactants and by-products (Hasieh et al. 2003) into and out of the pores. The corresponding pore size distributions of the CuO nanoparticles were determined using the Barrett–Joyner–Halenda (BJH) method from the adsorption branch of the isotherm. The analysis results on the BET surface area, total pore volume and average pore size of the prepared specimens are shown in Table 1. Page 10 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 Figure 4. UV-Vis spectra of the as-prepared nanostructured 0.8 CuO-N60 CuO specimen. CuO-S60 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 300 400 500 600 700 800 900 Wavelength (nm) Figure 5. FTIR spectra for the synthesized CuO samples. 3.5. Photodegradation of Methyl Orange (MeO), Methylene Blue (MB)and Rhodamine B (RhB) A summary of the degradation efficiency of each of the synthesized CuO species in the respective dyes is shown in Figure 7 while the absorbance (degradation) plots for the individual samples in each dye (MeO, MB and RhB) in the presence of the visible light source are shown in Figure 8. A general decrease in the absorbance (concentration) of dye is observed with time. Specifically, the N60 resulted in 94.3%, 90.6 %, and 99.6% degradation of MeO, MB and RhB dyes, respectively. Similarly, CuO-S60, led to 85.2%, 87.9 % and 98.8 % degradation MeO, MB and RhB dyes, respec- tively (Figure 7). This is presumably due to the continuous production and consumption of reactive Page 11 of 17 Absorbance (a.u) Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 Figure 6. Nitrogen adsorption– desorption isotherms of (a) CuO-S60 and (b) CuO-N60. Table 1. Summary of the analytical parameters for the prepared nanostructured CuO crystals Sample Average Energy Band BET surface BJH surface Pore size (nm) Pore volume Dye Crystallite gap (eV) area (m2/g) area (m2/g) (cm3/g) degradation size (nm) (%) CuO-S60 15.0 2.12 42.9 110.9 11.4 0.1032 90.7 CuO-N60 12.0 2.40 69.6 206.9 24.9 0.3921 95.0 oxygen species (ROS) such as singlet oxygen molecules (1O2), superoxide anion radicals (•O −2 ), and hydroxyl radicals (•OH−) (in the breakdown of the dye). In terms of the rate of degradation, ~ 100 % RhB dye was degraded by both CuO-N60 and CuO-S60 under 75 minutes of visible light irradiation, compared to 91 % and 88 % MB by both CuO-N60 and CuO-S60 under 100 minutes, respectively. Figure 7. Synopsis of mean 120 percentage rate of dye degra- MeO dations for each CuO specimen MB in each dye. 100 RhB 80 60 40 20 0 CuO-S60 CuO-N60 CuO Nanoparticles Page 12 of 17 Degradation (%) Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 Figure 8. UV-Vis absorbance spectra for the degradation of (a)MeO, (b) MB and (c) RhB dyes using CuO-N60. While as the slowest degradation rate was observed for MeO. Thus, 94% and 85% were observed by both CuO-N60 and CuO-S60 for MeO dye degradation after 100 minutes of visible light irradia- tion (Figures 8 and 9). In general, degradation efficiency of the cationic dye such as RhB was relatively higher, compared to the anionic dye such as MeO. This may be due to strong adsorption between the hydroxyl radicals (•OH−) at the CuO-N60 active sites and cationic dyes, as opposed to weak adsorption for anionic MeO (Dodoo-Arhin et al., 2018). For each case, CuO-N60 demonstrated to unfailingly have a higher degradation efficiency, which may be directly linked to the {111} crystallographic facet, the BET surface area and smallest crystallite size when compared with the CuO-S60 specimen. By and large, all the classes of the dyes reacted positively to the photocatalytic degradation system applied in the Page 13 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 Figure 9. Variation in percen- tage dye concentration with time for MeO, MB and RhB (Inset: shows colour change for photocatalysis of: (a) MeO, (b) MB, and (c) RhB, respectively). presence of visible light and the as-prepared CuO nanocrystals. The Rhodamine B dye showed the utmost percentage degradation rates per CuO specimen by the close of the 100-min exposure time. An overall reduction in the concentration of dye molecules in solution with the light exposure time can be seen across every one of the three dyes. As noted earlier, exposing the dyes to the photo- catalytic system leads to their degradation by the action of ROS and in particular, hydroxyl radicals (•OH−). However, while CuO nanoparticles exhibited excellent degradation, it does not mean complete mineralization of dyes into inorganic CO2 and H2O occurred (Agbe et al., 2018). The percentage of the residual dye was determined using Equation 9 taking into account the fact that the change in the amount of dye (concentration) with time is directly proportional to the change in absorbance as appeared in Equation 10. %Dye remaining in solution ¼ ðAt=A0Þx100% (9) ðA0 AtÞ=A0 ¼ ðC0 CtÞ=C0 (10) Page 14 of 17 Dodoo-Arhin et al., Cogent Engineering (2021), 8: 1920563 https://doi.org/10.1080/23311916.2021.1920563 where A0 = Absorbance after 0 minutes of degradation; At = Absorbance after t minof degradation, C0 = Concentration after 0 minutes of degradation and Ct = Concentration after t minof degradation. The percentage of dye degraded was calculated by Equation 11: C Degradation initial Cfinal ð%Þ ¼ � 100 (11) Cfinal where Cintial is the initial concentration of the dye solution and Cfinal is the concentration at time intervals of the irradiation time. 4. Conclusions Ultimately, differently sized CuO nanoparticles had been correctly synthesized with the aid of a surfactant-free solvation technique with the usage of two exclusive copper precursor salts. The prepared porous nanoparticles were effectively tested and found to have average crystallite sizes of 12 nm and 15 nm, respectively. The porous nanostructured powder specimens were utilized to breakdown three organic dyes (Rhodamine B (RhB), Methylene Blue (MB)- [Methylthioninium chloride] and Methyl Orange (MeO)) in the under visible light irradiation for 100 minutes at a 25-min interval. The CuO-N60 porous nanoparticles specimen, with the highest BET surface area performed reliably better in terms of the degradation of all the dyes evaluated substantially more contrasted with the CuO-S60 specimen. The nitrate precursor-based CuO photocatalysts demonstrated gen- erally higher photodegradation effectiveness (MeO 94.3%; MB 90.6%; RhB 99.6%) as compared with the sulphate precursor-based CuO photocatalysts (MeO 85.2%; MB 87.9%; RhB 98.8%). It was accordingly the favoured photocatalyst as far as its predictable proficiency across both dye classes. The outcomes from this exploration propose that the prepared CuO nanoparticles could be reason- ably used for dye waste water treatment. Acknowledgements Disclosure statement The authors acknowledge the funding support from the The authors declare no conflict of interest. University of Ghana BANGA-Africa programme, the African Materials Science and Engineering Network (A Carnegie-IAS Author contributions SIG-RISE Network), Cape Peninsula University of Technology For research articles with several authors, a short paragraph (CPUT) Research Fund and the North West University (NWU- specifying their individual contributions must be provided. UID: RK16). The statements made and views expressed in DDA: Conceptualization, Methodology, Formal analysis, this work are solely the responsibility of the authors. Writing - Original Draft; EM: Conceptualization, Methodology, Formal analysis, Writing - Original Draft; SKN: resources, Funding data collection, Writing - Review & Editing; EM: resources, The authors received no direct funding for this research. Writing - Review & Editing; EFK: resources, Writing - Review & Editing; BAT: Writing - Review & Editing; AY: Writing - Review Author details & Editing; HA: Writing - Review & Editing; EN: Writing - David Dodoo-Arhin1 Review & Editing. All authors have read and agreed to the E-mail: DDARHIN@YAHOO.COM;ddodoo-arhin@ug.edu.gh published version of the manuscript. ORCID ID: http://orcid.org/0000-0002-9657-2489 Etchu E. Mbu2 Citation information Seteno K. Ntwampe2 Cite this article as: Synthesis of nanostructured cupric Edward N. 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