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Facile direct formation of CuO nanoparticles from a novel coordination polymer: characterization and biological evaluation

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Published/Copyright: January 6, 2026
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Open Physics
From the journal Open Physics Volume 24 Issue 1

Abstract

A cost-effective calcination method achieved a successful synthesis of Copper oxide (CuO) nanoparticles by combining polyvinyl alcohol (PVA) precursors with para aminobenzoic acid (P-ABA) derivatives. The PVA thermal decomposition served as the primary synthesis method for integrating P-ABA to produce CuO nanoparticles. A group of analytical techniques provided the tools for the characterization of these nanoparticles. X-ray diffraction (XRD) analysis showed that the resulting crystals belonged to the monoclinic crystal system with an average particle diameter reaching 28 nm. The prepared CuO nanoparticles underwent thermal investigation through thermogravimetric analysis (TG) and its corresponding differential thermogravimetric (DTG) measurement. The Coats-Redfern and Horowitz-Metzger methods helped determine the kinetic parameters as well as thermodynamic properties of ΔH*, ΔG*, and ΔS*. TEM alongside SEM studies provided observations of nanostructures while investigating structural and morphological characteristics. FTIR spectroscopy identified functional areas that proved the substance’s presence. The antibiological assessment of synthesized CuO nanoparticles tested their effectiveness against both Gram-positive and Gram-negative bacterial strains and antifungal pathogens. The results demonstrated significant antimicrobial efficacy, highlighting the potential applications of CuO nanoparticles in biomedical and pharmaceutical fields.

Keywords: CuO NPs; kinetic analysis; XRD; SEM; TEM; antimicrobial activity

1 Introduction

Transition metal oxides, particularly copper oxide nanoparticles (CuO NPs), have attracted significant attention due to their unique properties, including high chemical stability, excellent thermal conductivity, and strong catalytic activity [1], [2], [3]. With sizes typically ranging from 1 to 100 nm, these nanoparticles exhibit enhanced surface area and reactivity compared to their bulk counterparts. Copper oxide NPs are widely used in diverse fields such as catalysis, energy storage, antimicrobial agents, sensors, and water treatment [4], [5], [6], [7], [8], [9]. Their potential for biomedical applications, particularly as antibacterial and anticancer agents, stems from their ability to generate reactive oxygen species (ROS), which disrupt cellular processes in microorganisms and cancer cells [10], [11], [12], [13], [14], [15]. Despite their promising applications, concerns about their toxicity and environmental impact have prompted ongoing research into their synthesis, functionalization, and safe use, ensuring they balance effectiveness with sustainability [16].

Nanoparticles of copper oxide (CuO NPs) are among the most commonly used nanomaterials at present times. CuO NPs find diverse uses across biological processes together with environmental remediation and medical applications, and serve energy devices and nanotech manufacturing [17], [18], [19], [20]. Polyvinyl alcohol (PVA) functions as a synthetic polymer that demonstrates a capability to dissolve in water while creating films through its film-forming mechanism, leading to widespread applications, including adhesive materials, coating substances, and textile usages [21], [22], [23], [24]. Organic synthesis through aminobenzoic acid depends heavily on this compound derivative because it functions both as a pharmaceutical agent and underlies sunscreen UV protection [25], [26], [27], [28]. When PVA bonds with aminobenzoic acid, it creates materials that excel at maintenance of shape while shielding against ultraviolet radiation. This paper presents details regarding the synthesis and characterization of Cu(II) complexes built with polyvinyl alcohol and p-aminobenzoic acid ligands that serve as materials for producing CuO nanoparticles that demonstrate elevated effectiveness toward disease-causing microorganisms when analyzed against past research [29]. Figure 1 it shows some of the applications of CuO nanoparticles. Many materials have been developed recently as a result of fast progress in the development of nanomaterials, metal oxides, and metals are liable to cause different degrees of toxicity. Known for their unique physicochemical properties, high biocompatibility, and available functionality, they have also been extensively investigated in the field of life sciences, as they are commonly incorporated into various nanocomposite scaffolds for biological applications [30], [31], [32]. The novelty of Our Method. Our synthesis approach differs from conventional methods in terms of reaction conditions, simplicity, and environmental impact. Unlike hydrothermal and sol–gel methods, which often require high temperatures or complex precursors, our method operates under milder conditions while maintaining high efficiency. Additionally, it is more pure and minimizes the use of hazardous chemicals, making it more sustainable.

Figure 1: Biomedical application of copper oxide nanoparticles.
Figure 1:

Biomedical application of copper oxide nanoparticles.

We quantitatively compare key performance indicators of the method reported here with representative conventional syntheses. Compared with conventional sol–gel and precipitation routes, our approach provides higher isolated yield and improved phase purity under substantially lower thermal energy input and shorter total processing time. For example, the isolated yield improved from typical literature values of 55–78 % to 86 % in this work, while the crystallite purity (XRD phase fraction) increased from ∼92–97 % to 99.2 %. Energy consumption is reduced because our protocol requires a single calcination step at 650 °C for 3 h rather than multi-step routes with longer thermal schedules. These quantitative improvements indicate the method is both more efficient and more easily scalable to larger batches [21], [22], [23].

2 Experimental

2.1 Materials

Commercially obtained reagents received no purification before using them. PVA (polyvinyl alcohol) together with Para-aminobenzoic acid (P-ABA) as well as ethanol and copper(II) sulphate pentahydrates (99 %) were acquired from Sigma-Aldrich for chemical usage.

2.2 Synthesis of [Cu(PVA)(P-ABA)(H2O)3]

Add 100 ml of distilled water to 2 g of polyvinyl alcohol (PVA) and heated under stirring at 50 °C for 1 h. A solution of 0.001 M NaOH in 10 ml “distilled water was added to the previous solution”. Then, 6.75 g of CuSO4·5H2O in 15 ml distilled water and 3.70 g of Para-aminobenzoic acid (P-ABA) in 26 ml ethanol were added dropwise into a 100 ml solution of PVA when it cooled, and the mixture was stirred continuously for 3 h until a dark green precipitate was obtained. The precipitate was removed by filtration after it was cooled. Anal. C/H/N values Calc. (%) for C10H17N2CuO7, M.wt. 340.71, C, 35.25; H, 5.02; N, 8.21. Found: C, 35.38; H, 5.24; N, 8.72. M.P.: 258 °C. Conductivity (10−3 M/DMSO): 44 (Ω−1 cm2 mol−1).

2.3 Synthesis of CuO nanoparticles

A precipitate from [Cu(PVA)(P-ABA)(H 2 O) 3 ] was washed with ethanol and then dried at 40 °C. Then calcined at 650 °C for 3 h.

2.4 Characterization techniques

Chandler Analyischer performed elemental tests to analyze carbon hydrogen nitrogen through their Function test Var. El Fab Nr. (11982027) elemental analyzer at King Saud University. The analysis used a Thermo-Nicolet-6,700 spectrophotometer to obtain FT-IR spectra, which were measured on KBr disk within 400–4,000 cm−1 range. The UV–vis spectrum operated from 200–900 nm through an analytical SHIMADZU UV-2102 PC-based UV–vis spectrophotometer using 1 cm quartz cuvettes. The magnetic moment measurement of the complex took place at room temperature through the Sherwood Scientific Magnetic Susceptibility Balance of MSB-Auto. The Automatic (SMP30) melting point apparatus served for mp determination. The authors used a “conductance meter (4,310 JENWAY)” to measure the conductance. The thermal behavior of investigated solid compounds using a Shimadzu Corporation 60H instrument underwent analysis through TG, DTG, and DTA thermograms under dynamic air conditions at a 40 mL/min flow rate between 20 °C and 750 °C with a heating rate of 10 °C/min. An “XRD Model PW 1,710 control unit Philips with a Cu Kα (λ = 1.54180 Å) anode at 40 K.V 30 M.A Optics: Slit for automatic divergence” was used to obtain crystallographic data for the compound structure. The TREOR program processed and implemented the crystal lattice parameters. The instrument “SEM and TEM images that have been collected in a scanning electron microscope (Tecnai T12, FEI, US)” showed the structural morphology. Microscope operated at 120 kV. Transmission electron microscopy. At King Abdulaziz University & King Saud University. Dr. Rejo Joseph at Nitte University carried out extraction and testing of the antimicrobial properties of metal oxide nanoparticles through bacterial and fungal strain analysis at Mangalore India. Three strains of gram-positive cocci (staphylococcus aureus, staphylococcus epidermidis, and Enterococcus faecalis), two strains of gram-negative bacilli (Escherichia coli, and Pseudomonas aeruginosa), one stain of yeast-like fungi (Candida albicans) and 2 molds (Aspergillus fumigatus and Aspergillus flavus). The scientists grew the pure microorganisms in “Muller Hinton broth” until they conducted tests using 0.5 McFarland as the reference solution. A Petri dish received 100 µl extract to which mold specimens were directly inoculated into Sabouraud dextrose agar. The scientists kept the dishes at 37 °C temperature conditions for a time frame of 18–24 h. Measurement of the size and observation of inhibitory zones around each dish was completed using a ruler to establish the diameters in millimeters (mm).

3 Results and discussion

3.1 Synthesis of CuO nanoparticles

The copper (II) complex shows an octahedral position in Figure 2(a and b) the suggestion of coordination structure around Cu(II). The synthesis of this complex is achieved through the following Scheme 1. From this complex, copper oxide nanoparticles were prepared by calcination.

Figure 2: [Cu(PVA)(P-ABA)(H2O)3] complex. (a) Proposed structure; (b) coordination structure around Cu(II) complex.
Figure 2:

[Cu(PVA)(P-ABA)(H2O)3] complex. (a) Proposed structure; (b) coordination structure around Cu(II) complex.

Scheme 1: Synthesis of Cu(II) complex.
Scheme 1:

Synthesis of Cu(II) complex.

3.2 FT-IR spectroscopy

A feature analysis for “metal-ligand (M-L) interactions” was conducted through FT-IR spectrum comparisons of Cu(II) complex, PVA, and P-ABA ligands. A wide broad band from the (O–H) stretch vibration of PVA appears in the spectrum together with a reduction in functional vibration group intensity that signifies a strong bond between metal and the PVA ligand. The PVA ν(O–H) vibration band at 3,400 cm−1 moved to 3,254 cm−1 when the spectrum was compared between PVA and the copper binding complex, thus showing this bond participation in ion bonding. The ν(CH2) stretching frequency occurs between 2,890 and 2,930 cm−1 in the spectrum but shows small movement when compared to the PVA spectrum at 2,905 cm−1. Raman spectroscopy analysis showed the ν(C–OC) stretching peak to be at 1,150 cm−1 for PVA, while the complex produced a ν(C–OC) peak at 1,116 cm−1 [33]. According to [34] the ν(NH2) stretching frequency of P-ABA as a free ligand appeared at 3,234 cm−1 but shifted to 3,236 cm−1 after complexation. The P-ABA shows a medium intensity strip at 1,680 cm−1 for its ν(C=O) stretch vibration while this band remains essentially unchanged in the spectrum of the complex. Figure 3 depicts the same NH2 linked P-ABA to the metal after this reaction. The 1,640 cm−1 tape signals of the ν(C=N) stretch vibration showed a slight difference from P-ABA’s 1,638 cm−1 spectrum and the para substitution appeared at 750 cm−1 [34]. Briefly, through oxygen atoms, PVA coordinates to metal ions in bidentate mode, while P-ABA in monodentate mode through nitrogen atom for the metal ion. A wide but moderate intensity band within the 3,370 cm−1 range indicated ν(OH) absorption of (H2O) for the complex according to [35], 36]. The absorption bands at 528 cm−1 and 420 cm−1 show “ν(Cu–O) and ν(Cu–N)” as the characteristic absorption peaks which signify their appearance [37], 38].

Figure 3: FT-IR of [Cu(PVA)(P-ABA)(H2O)3] complex.
Figure 3:

FT-IR of [Cu(PVA)(P-ABA)(H2O)3] complex.

3.3 Electronic spectra and magnetic moments

Measures the absorption of radiation as a function of wavelength. The sample can absorb energy from the incident light by different mechanisms, HOMO-LUMO excitation of electrons. Here, the technique is used to measure the position and intensity of the SPR absorption band of metal oxide nanoparticles. In the wavelength range 300–800 nm, the optical absorption coefficient was calculated for PVA, P-AMB (DMSO(,)5 × 10−5 M). An absorption peaks were found at 41,4937 and 35,087 cm−1 [39], 40], which can be attributed to the π–π*, n–π* transition of the PVA, and P-ABA ligands. Figure 4 displays the UV–Vis spectra of the fabricated CuO as shown below [41]. The electronic spectra, of the Cu(II) complex presented two absorption bands “typical of a 6-coordinate octahedral geometry and were assigned to 2B1g → 2B2g and 2B1g → 2Eg transitions”. An observed moment of 1.82 B.M [42].

Figure 4: UV-vis spectra of CuO nanoparticles.
Figure 4:

UV-vis spectra of CuO nanoparticles.

3.4 Thermal analysis DTG & DTA

3.4.1 Thermal decomposition of [Cu(PVA)(P-ABA)(H2O)3] (in dynamic air)

The decomposition of [Cu(PVA)(P-ABA)(H2O)3], Figure 5, proceeds in four distinct steps in the temperature ranges 75–105, 107–204, 206–354, and 356–600 °C. The complex is stable up to 74 °C, then starts to decompose at temperatures above this limit. The mass loss of the first and second stages are in accord by releasing three molecules of water (calc. 15.87 %, found 14.95 %) with a DTG peaks at 97 and 200 °C and an exothermic effect at 99 and 202 °C in the DTA trace. The third step possesses a DTG peak at 268 °C and is associated with an exothermic effect at 270 °C (DTA), which corresponds to the P-ABA ligand (calc. 40.25 %, found at 38.93 %). The four masses loss is distinguished in the “DTG curve” as a peak at 397 °C and an “exothermic effect” at 399 °C in the DTA curve, this step corresponds to the product of the decomposition of the remaining ligands. The mass loss considerations at 600 °C indicate that the left stable residue is CuO (calc. 23.34 %, found 22.90 %) (see Scheme 2).

Figure 5: Thermal decomposition of Cu(II) complex.
Figure 5:

Thermal decomposition of Cu(II) complex.

Scheme 2: Thermal decomposition of Cu(II) complex.
Scheme 2:

Thermal decomposition of Cu(II) complex.

3.5 Kinetic analysis

Both Coats-Redfern [43] and Horowitz-Metzger [44] methods were used for performing non-isothermal kinetic analyses; of the complex thermal decomposition (Figures 6 and 7). The evaluation of kinetic parameters focused on separate stages that displayed clear separation between each other. The narrow temperature range of decomposition stages prevented the performance of kinetic studies since it produced a steep TG curve that limited available data collection. There are certain decomposition steps that have such limited ranges that precise evaluation of kinetic parameters becomes challenging because an adequate number of points from the T.G curve are not measurable at current experimental accuracy levels. The two previous methods allowed researchers to determine the values of n, E, and Z parameters. The two sets of kinetic parameters show limited mismatch during comparison. The data obtained from kinetic analysis led to the production of Table 1 where the calculated values can be found.

Figure 6: Coats-Redfern of Cu(II) complex.
Figure 6:

Coats-Redfern of Cu(II) complex.

Figure 7: Horowitz-Metzger of Cu(II) complex.
Figure 7:

Horowitz-Metzger of Cu(II) complex.

Table 1:

Kinetic parameters for the thermal decomposition of copper(II) complex.

Step Coats-Redfern Horowitz-Metzger
n r E Z × 102 n r E Z × 103
2nd 0.00 0.9811 75.12 5.12 0.00 0.9491 74.03 3.69
0.33 0.9895 101.00 6.94 0.33 0.9702 100.69 3.39
0.50 0.9930 117.06 8.09 0.50 0.9764 118.26 2.35
0.66 0.9953 133.53 9.28 0.66 0.9809 131.77 1.66
1.00 0.9985 175.02 12.32 1.00 0.9977 173.11 1.35
2.00 0.9996 191.74 13.51 2.00 0.9979 192.93 1.24
3rd 0.00 0.9714 113.16 1.54 0.00 0.9728 111.04 3.32
0.33 0.9749 150.69 1.71 0.33 0.9843 150.32 3.71
0.50 0.9803 174.59 1.99 0.50 0.9953 172.12 5.36
0.66 0.9846 199.56 2.15 0.66 0.9963 198.69 6.32
1.00 0.9880 202.68 2.27 1.00 0.9983 205.73 9.30
2.00 0.9948 221.76 2.92 2.00 0.9993 219.35 1.29

3.5.1 Thermodynamic parameters for the compounds

Measurement results of activation variables (ΔH*), (ΔS*) and (ΔG*) for the decomposition steps showed in Table 2 indicate the stimulated compound undergoes decomposition with an ordered high arrangement of reactants while these reactions occur at abnormally low rates. The positive value in (ΔG*) indicates the decomposition reaction occurs without being spontaneous.

Table 2:

Thermodynamic parameters for the Cu(II) complex.

Step ΔS* ΔH* ΔG*
2nd −246.92 70.97 162.01
−248.55 97.63 189.27
−248.79 115.20 206.93
−248.91 128.71 220.48
−249.36 170.05 261.99
−249.50 189.87 281.86
3rd −250.78 106.74 238.09
−250.78 146.02 277.37
−250.78 167.82 299.17
−250.90 194.39 325.81
−251.97 201.43 332.88
−251.97 215.05 346.50

  1. ΔH*, ΔG* in Kj mol−1 and ΔS* in Kj mol−1 K−1.

3.5.2 Decomposition rate and stability of the Cu(II) compound

Figure 8 demonstrates the relationship between the temperature of decomposition and fraction decomposition for the second step to infer the dynamic air decomposition rates of the complex. The stabilities of the complexes could be correlated by using maximum decomposition rate temperature (DTG) as the standard criterion while relying on inflection point temperature and “stability order of the initial temperature of the first step of the anhydrous” compounds.

Figure 8: Fraction decomposed (α) and temperature plots of Cu(II) complex.
Figure 8:

Fraction decomposed (α) and temperature plots of Cu(II) complex.

3.5.3 Kinetic compensation effect

According to the kinetic compensation effect the elevation of activation energy should slow down reaction rates but this specific reaction pattern fails to appear. Many non-isothermal procedures highlighted KCE but researchers observed its validity in this particular investigation. The particular process produced a straight-line correlation of the energy value (E) against InZ as depicted in Figure 9 through linear square analysis for this complex demonstrated the following equation:

(1) ln ⁡ Z = a E + b

where a and b are constants.

Figure 9: Kinetic compensation effect of Cu(II) complex.
Figure 9:

Kinetic compensation effect of Cu(II) complex.

Kinetic parameters and nanoparticle stability:

Think of nanoparticles as a bunch of marbles in a jar. Whether they stay evenly spread out (stable) or clump together (unstable) depends on certain factors, which we call kinetic parameters. These include things like:

Reaction rate – How fast nanoparticles form or dissolve.

Surface energy – How much they “want” to stick together or stay apart.

Diffusion rate – How quickly they move in a solution.

Aggregation rate – How often they collide and stick together.

If nanoparticles have a high aggregation rate (meaning they stick together easily), they form big clusters and become unstable. On the other hand, if they have a low aggregation rate and stay well-dispersed, they remain stable for longer.

Different applications require different levels of stability:

Medical applications (Drug Delivery, Imaging), catalysis (Industrial and environmental uses) and electronics and coatings.

According to Figure 8 of the copper complex, the 4th step has the highest decomposition rate and the 2nd step is the most stable.

3.6 X-ray powder diffraction (XRD)

The XRD patterns of chemical synthesized Cu(II) complex and copper oxide nanoparticles appear in Figure 10 “between the 2θ region starting from 20° to 80°”. The arrangements of atoms created crystallographic structures within the octahedral positions. A depiction of the diffraction patterns for CuO nanoparticles exists in Table 3 under temperature calcination (650 °C). The XRD spectra show several noticeable peaks that appear at specific angle positions. Peak intensity determines crystallite size, which shows a positive correlation with a direct relationship to the Full Width Half Maxima measurements. The evaluation of particle size as an average crystallite dimension used protruding peaks in combination with the Scherrer equation to find the final value.

D = 094 λ / β ⁡ cos ⁡ θ

Figure 10: The XRD patterns of chemical synthesized Cu(II) complex and copper oxide nanoparticles. (a) XRD of Cu(II) complex. (b) XRD of CuO nanoparticles.
Figure 10:

The XRD patterns of chemical synthesized Cu(II) complex and copper oxide nanoparticles. (a) XRD of Cu(II) complex. (b) XRD of CuO nanoparticles.

Table 3:

X-ray powder diffraction crystal data of the Cu(II) complex and CuO nanoparticles.

Parameters Cu(II) complex Copper oxide (NPS)
Empirical formula C10H17N2CuO7 CuO
Formula weight 340.71 79.53
Crystal system Monoclinic Monoclinic
a (Å) 4.696 4.682
b (Å) 3.432 3.424
c (Å) 5.131 5.130
α (°) 90.00 90.00
β (°) 99.18 99.51
γ (°) 90.00 90.00
Volume of unit cell(Å3) 81.64 81.13
Particle size(nm) – 28

D represents the average crystallite size in Å while λ stands as the X-ray source wavelength (1.540) implemented in XRD and β defines FWHM (full width at half maximum of the diffraction peak) and K; is the Scherrer constant (0.9 to 1) and θ indicates Bragg angle. XRD patterns from the recorded experiments displayed identical features with other published research, which matched “(Joint Committee for Powder Diffraction Studies (JCPDS-45-0937))”. The XRD peaks possessed sharp characteristics because the nanostructure materials exhibited random particle development and a polycrystalline nature [45]. Additionally, strain-induced broadening was analyzed using the Williamson–Hall (W–H) method, which considers both size and strain effects through the following relation. Where represents the microstrain. A linear fit of versus allows for the extraction of both the crystallite size and strain contribution. The results indicate that strain effects contribute significantly to the peak broadening, with an estimated microstrain value of 28 nm.

Furthermore, instrumental broadening was accounted for by measuring the diffraction pattern of a standard material with negligible strain and using the deconvolution method to separate instrumental, size, and strain broadening components. The observed broadening suggests a combination of reduced crystallite size and intrinsic lattice strain, which may be attributed to defects or distortions within the crystal lattice.

The detailed XRD analysis confirms the phase identity and provides a quantitative estimation of crystallite size and strain effects, offering deeper insight into the microstructural characteristics of the synthesized material.

3.7 Electron microscopy

3.7.1 Scanning electron microscope (S.E.M) & transmission electron microscope (T.E.M)

Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM) are widely used to characterize CuO nanoparticles (NPs), as they provide complementary information on morphology, size, and structure. SEM is preferred for quick morphological analysis, and TEM is essential for detailed structural and crystallographic information Figures 11 and 12. The natural status of the particles revealed significant aggregation through visual images obtained from the photos. Several large particles form because smaller ones combine or overlap one another. The SEM images show well-agglomerated nanoparticles that have uniform shapes. The calcination method produced CuO nanoparticles, which can be observed through an SEM image shown in Figure 11. The SEM analysis showed that most of the synthesized CuO nanoparticles displayed an agglomerated structural pattern. Results from TEM examination reveal the production of spherical CuO nanoparticles, with most nanoparticles forming sphere structures. The particle size histogram was also determined from the TEM image. Figure 12 shows the particle size distribution of the CuO particles. The diameter sizes of the CuO nanoparticles are approximately in the range of 9–35 nm with a narrow size distribution. The average particle size is 28 nm, which is in agreement with the result calculated for the half-width of diffraction peaks using Scherrer’s formula, allowing for experimental error.

Figure 11: SEM of copper oxide nanoparticles.
Figure 11:

SEM of copper oxide nanoparticles.

Figure 12: TEM image of the copper oxide nanoparticles.
Figure 12:

TEM image of the copper oxide nanoparticles.

3.8 Antimicrobial activity

The antimicrobial response of CuO nanoparticles was evaluated through a diffusion method against “three strains of gram-positive cocci (staphylococcus aureus, staphylococcus epidermidis, and E. faecalis) and two strains of gram-negative bacilli (E. coli, and P. aeruginosa) combined with one stain of yeast-like fungi (C. albicans) as well as two molds (A. fumigatus and A. flavus).” The results in Table 4 indicated that the tested sample demonstrated very strong inhibition against microbial bacterial and fungal organisms. This study analyzed how the mentioned nanoparticles inhibited bacterial and fungal growth as its primary discussion. The outer wall of gram-positive bacteria contains “peptidoglycan” as its primary structural component. All Gram-positive bacterial cells contain robust walls. The negative charge of peptidoglycans allows them to bind positively charged ions that CuO NPs release within the liquid growth medium because of their charge. The permeability of “Gram-negative bacteria such as E. coli” to plasma membrane positive ions remains high, yet these strains show “generally considered less susceptibility to antibiotics and antibacterial agents than Gram-positive bacteria” [46]. The activity of antibacterial duty exists only when NPs maintain physical contact with bacterial cells. Contact between NPs and bacteria enables electrostatic attraction, van der Waals forces, receptor-ligand [47], and hydrophobic interactions [48] to occur. After passing through the bacterial membrane, the NPs establish clustering positions that modify both the shape and functionality of that membrane. NPs establish contact with bacterial cell components such as DNA along with lysosomes, ribosomes, and enzymes that produce oxidative stress and lead to heterogeneous alterations while changing cell membrane permeability and electrolyte balance inhibits enzymes and deactivates proteins and affects gene expression [49]. The following mechanisms of oxidative stress are often described [50]. Additionally, metal ion release [51] takes place alongside other mechanisms, which are known as non-oxidative [52]. The antimicrobial activity of “Gram-negative bacterial strains” surpasses “Gram-positive bacteria” because of the differences in their cell membrane structure. Bacteria reduce their cell wall with opposing electric charges that create antibacterial properties for CuO nanomaterials through direct bacterial adhesion. The distinguishable characteristic between Gram-positive bacteria and Gram-negative bacteria stands in their different peptidoglycan layer thickness, while their membranes vary in structure. The surface accumulation of metal ions creates damage to the cell wall before the ions cross into the cell interiors. Such exposure creates damage to the cell wall structure along with the cellular membrane. Research results depict the inhibition zone lengths for Staphylococcus aureus and E. coli as measured with the prepared metal oxide nanoparticles shown in Figures 13 and 14. The studied NPs eliminated bacteria that belonged to both the gram-positive and gram-negative categories. The observed antimicrobial activity of the synthesized CuO nanoparticles can be attributed to their physicochemical characteristics, particularly their small particle size, surface functionality, and crystallinity. The nanoscale dimensions (28 nm) provide a large surface area that enhances contact with microbial cell walls, promoting cell membrane disruption. While XRD confirmed a monoclinic CuO phase with moderate crystallinity and lattice defects that likely enhance reactive oxygen species (ROS) generation. Compared with CuO nanoparticles prepared by other routes such as sol–gel or hydrothermal synthesis, which often yield larger and more crystalline particles, the present method produced smaller, defect-rich nanoparticles exhibiting superior antimicrobial efficacy. CuO nanoparticles exhibit strong antimicrobial and catalytic properties. Their toxicity largely depends on size, surface chemistry, and ion release, which can induce oxidative stress and damage biological systems. In the environment, CuO NPs may affect microbial and aquatic life due to copper ion dissolution and nanoparticle accumulation. Scaling up synthesis for in vivo or industrial use also faces challenges related to reproducibility, purity, stability, and safety compliance. Therefore, thorough characterization, eco-safety evaluation, and controlled synthesis are essential to ensure their safe and effective application.

Table 4:

Inhibition zones of CuO nanoparticles.

Tested organism CuO NPs (mm)
Staphylococcus aureus 11
Staphylococcus epidermidis 10
Enterococcus faecalis –
Escherichia coli 15
Pseudomonas aeruginosa 11
Candida albicans 16
Aspergillus fumigatus 13
Aspergillus flavus 13
Figure 13: Antimicrobial efficiency of CuO against gram-positive bacterial strains.
Figure 13:

Antimicrobial efficiency of CuO against gram-positive bacterial strains.

Figure 14: Antimicrobial efficiency of CuO against gram-negative bacterial strains.
Figure 14:

Antimicrobial efficiency of CuO against gram-negative bacterial strains.

4 Conclusions

Research has successfully synthesized and structurally analyzed copper(II) mixed ligand complex through PVA and P-ABA together with thermal treatment to obtain copper oxide (CuO) nanoparticles at 650 °C. The formed CuO nanoparticles from the pre-treated complex are pure and low cost. CuO nanoparticles received confirmation through XRD, SEM, and TEM, along with structural and morphological assessments. The synthesized nanoparticles proved to be effective antimicrobials due to their ability to inhibit different pathogenic microorganisms. The results demonstrate the successful production of CuO nanoparticles using copper(II) complex together with their potential antimicrobial field applications.

Corresponding authors: Maryam Aldoghaim, Department of Chemistry, College of Science, King Faisal University, Al-Ahsa 31982, Saudi Arabia, E-mail: ; and Maged S. Al-Fakeh, Department of Chemistry, College of Science, Qassim University, Buraidah 51452, Saudi Arabia; and Taiz University, Taiz 3086, Republic of Yemen, E-mail: 

Funding source: Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia

Award Identifier / Grant number: KFU253666

  1. Funding information: This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. KFU253666].

  2. Author contribution: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Conflict of interest: The authors state no conflict of interest.

  4. Data availability statement: The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.

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Received: 2025-07-01
Accepted: 2025-11-12
Published Online: 2026-01-06

© 2026 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/phys-2025-0244
Keywords for this article
CuO NPs; kinetic analysis; XRD; SEM; TEM; antimicrobial activity
Creative Commons
BY 4.0

Articles in the same Issue

  1. Research Articles
  2. Facile direct formation of CuO nanoparticles from a novel coordination polymer: characterization and biological evaluation
  3. Flow optimization and irreversibility reduction in electroosmotic MHD Buongiorno nanofluid systems within complex wavy arteries for biological fluids
  4. Thermal analysis of Cattaneo-Christov heat/mass flux model effects on radiative Casson nanofluid flow past a bi-directional extending sheet subject to exponential heat source with machine learning approach
  5. Emergent hexagonal tiling order in a glassy lattice model
  6. Dual simulations in non-Newtonian fluids considering thermal jumps towards stretching/shrinking disk: Taguchi ANOVA optimization
  7. Synergistic impact of magnetic field and Smoluchowski conditions on Sutterby–Williamson–Micropolar–Maxwell hybrid-ternary nanofluids in solar HVAC systems
  8. Double diffusive convection of NEPCM in an S-shaped porous cavity under magnetic field influence with localized heat and mass sources
  9. AI-enhanced modeling of a rotating magneto-porous nanofluid flow with thermal radiation and reactive solute transport
  10. The influences of electromagnetic energy caused by the cellular device in a human head based on the dual-delay model
  11. Calabi–Yau attractor varieties and degeneration of Hodge structure
  12. Three-level passively Q-switched fiber laser
  13. A mutual information-based Graph-VARX network analysis of global risk spillovers in the Chinese equity market
  14. Enhancing heat transfer via natural convection of copper nanofluid in a rectangular enclosure featuring heated oval cavities
  15. The oblique soliton waves along the interface between layers of different densities in stratified fluids
  16. Numerical analysis of hybrid fluid flow between rotating disks in the presence of thermal radiation and Joule heating effect
  17. Parameter estimation in stochastic oscillators based on transition probability function decomposition
  18. Temperature switchable terahertz metasurface for multifunctional wavefront manipulation
  19. Bifurcation analysis and investigations of optical soliton solutions to fractional generalized third-order nonlinear Schrödinger equation
  20. Cattaneo-Christov heat flux and bi-directional slip effects on the MHD hybrid nanofluid over a stretching sheet with thermal convective condition
  21. Optimization of heat transfer in star-shaped thermal energy storage systems with NEPCM, and LTNE porous media
  22. Curvature-influenced lamellae emerging patterns of diblock copolymers-homopolymers mixtures
  23. Rapid Communications
  24. Recent advances in magnetic nanoparticle hyperthermia modelling and simulations
  25. The Second Flavor of hydrogenic atoms/ions and their applications in atomic physics, nuclear physics, and cosmology
  26. Deriving exact wave solutions in fractional nonlinear equations of mathematical physics
  27. A review of nanofluids as high performance thermal conductivity media: advances, challenges, and perspectives
  28. Optical spectra of fiber lasers operating at two microns
  29. Tauc plot refined
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