1. Copper nanoparticles comprising Copper Nitrate and C. caesia extract for use in catalysis, medicine, and electronics.

2. The copper nanoparticles as claimed in claim 1, wherein said nanoparticle comprises Copper Nitrate and C. caesia extract in a ratio ranging from 4:1 to 5:1, preferably in a ratio of 4.611:1.

3. The copper nanoparticles as claimed in claim 1, wherein said nanoparticles further comprises 0.1 M Sodium Hydroxide for maintaining pH at 10.

4. The copper nanoparticles as claimed in claim 1, wherein particle size of the nanoparticle size is ranges from 63.18 nm to 193.167 nm.

5. The copper nanoparticles as claimed in claim 1, wherein said nanoparticles have a zeta potential of 20.3 mV to 62.4 mV.

6. The copper nanoparticles as claimed in claim 1, wherein said nanoparticles have a poly dispersibility index of 0.0929 to 0.8191.

7. Synthesis of Copper Nanoparticles comprising the steps - Preparing C. caesia Roxb rhizome extract, - Preparing copper nitrate solution is distilled water of concentration of 0.01 M, - Mixing the C. caesia Roxb rhizome extract and the copper nitrate solution at predetermined conditions to yield copper nanoparticle solution, - Adding 0.1 M Sodium Hydroxide to maintain the pH of the copper nanoparticle solution at 10, - Centrifuging the copper nanoparticle solution at 10,000 rpm for 20 min to obtain precipitate of crude copper nanoparticles, - Washing the precipitate of crude copper nanoparticles with distilled water and ethanol to obtain washed precipitate of copper nanoparticles, - Drying the washed precipitate of copper nanoparticles at temperature 70°C for 6 h to obtain dry and stable copper nanoparticles.

8. The synthesis of copper nanoparticles as claimed in claim 7, wherein the quantity of copper nitrate is 46.11 ml, C. caesia extract is 0 ml, Sodium Hydroxide is 0.1 M, Distilled Water is q.s. and Ethanol is 10 ml.

9. The synthesis of copper nanoparticles as claimed in claim 7, wherein the predetermined conditions of mixing the C. caesia Roxb rhizome extract and the copper nitrate solution are continuous stirring for 2 h at temperature 70°C and pH 10.

10. An antidiabetic pharmaceutical composition comprising copper nanoparticles as claimed in claim 1. Dated this the 11th day of August 2024.

Description:Field of the invention:
The present invention relates to nanotechnology. In particular, the present invention relates to copper nanoparticles and green synthesis thereof from Curcuma caesia Roxb. rhizome extract. The copper nanoparticles of the present invention is used in antidiabetic formulations with improved drug release property.

Background of the invention:
Nanotechnology, a rapidly expanding field, explores the creation of novel nanoscale materials with applications spanning diverse industries. Metallic nanoparticles (NPs), favored for their cost-effective synthesis using plant extracts and microbes, exhibit unique properties like a high volume-surface ratio and potent antibacterial effects.
Diabetes mellitus (DM) and its correlated complications have reached epidemic proportions in developing nations, posing a substantial threat to the health and economies of developed countries. To date, the International Diabetes Federation (IDF) have estimated that 451 million adults live with diabetes worldwide in 2017 with a projected increase to 693 million by 2,045 if no effective prevention methods are adopted. Herbal medicine, especially in the context of Diabetes mellitus, has gained attention due to its potential pharmacological and therapeutic benefits and Curcuma caesia (C. caesia) Roxb. is one of the medicinal plant which is used in the treatment of diabetes mellitus.
Green synthesis, a sustainable approach gaining popularity, addresses the drawbacks of conventional methods. CuNPs offer potential in medical treatments due to their multifaceted properties. Their evaluation against various diseases, including antibacterial, antioxidant, and catalytic effects, is crucial. Notably, green synthesis renders CuNPs non-toxic, affordable, and adaptable, enabling their use as antioxidants, anticancer, and antimicrobial agents. CuNPs possess several advantages over silver and gold nanoparticles, demonstrating diverse properties like bactericidal, antifungal, and antioxidant activity.
The present invention aims to synthesize copper nanoparticles (CuNPs) of rhizome extract of Curcuma caesia using green synthesis method. Synthesizing copper nanoparticles (CuNPs) using C. caesia represents an innovative, eco-friendly method.

Object of the invention:
Accordingly, the main object of the present invention is to provide copper nanoparticles (CuNPs) using C. caesia.
Another object of the present invention is to provide method of green synthesis of copper nanoparticles (CuNPs) using C. caesia.
Yet another object of the present invention is to provide stable copper nanoparticles (CuNPs) using C. caesia showing enhanced drug release property and anti-diabetic property.

Summary of the invention:
The present invention provides copper nanoparticles (CuNPs) of rhizome extract of Curcuma caesia using green synthesis method. The CuNPs are then characterized by FT-IR, SEM/TEM, SPR, EDX etc. and evaluated against marketed formulations for the comparison of drug release property.
In an embodiment of the present disclosure, the copper nanoparticles (CuNPs) of rhizome extract of C. caesia are prepared and Box–Behnken design was used to determine the optimal synthesis conditions. The optimum synthesis conditions are C. caesia extract concentration of 10 ml, pH 10, and copper nitrate concentration of 0.01 M. The synthesized CuNPs under FT-IR spectrum showed a nitrate peak in the 1500-1800 cm-1 region confirming the reduction of copper ions to elemental copper using a C.caesia extract. The average diameter of CuNPs are approximately 111 nm. The zeta potential value is 33.5mV indicating a moderate surface charge.
It will nevertheless be understood that no limitation of the scope of the invention is thereby intended by way of embodiments and examples. Such alterations and further modifications in the present invention, and such further applications of the principles of the invention as would normally occur to those skilled in the art are to be construed as being within the scope of the present invention.
It will be understood by those skilled in the art that the summary of the invention provided herein is exemplary and explanatory of the invention and are not intended to be restrictive thereof. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs. The composition, methods, and examples provided herein are only illustrative and not intended to be limiting.
The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more steps of method or components proceeded by "comprises... a" does not, without more constraints, preclude the existence of other, steps or components. Appearances of the phrase "in a preferred embodiment”, “in an embodiment", “in another embodiment” and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.

Brief description of drawings:
Figure 1: Schematic representation of the green synthesis of copper nanoparticles using Curcuma caesia Roxb extract. The gradual change of color form green to brown, indicates reduction of copper ions into elemental copper.
Figure 2: Pertubation plot Particle Size, Zeta Potential, and PDI response data by Box–Behnken design.
Figure 3: Response Surface Modelling of Copper Nanoparticles.
Figure 4: Overlay Plot of optimized formulation for copper nanoparticles of C. caesia Roxb extract.
Figure 5: Interpretation of SPR.
Figure 6: EDX analysis.
Figure 7: Fourier-transform infrared spectroscopy of Copper Nitrate (A) and Mixture of Copper Nitrate and Excipients (B).
Figure 8: Zeta Potential of Copper Nanoparticles.
Figure 9: Scanning electron microscopy of Copper Nanoparticles.
Figure 10: Transmission Electron Microscopy of Copper Nanoparticles.
Figure 11: Standard calibration graph of C. caesia at 390 nm.
Figure 12: In vitro release of Marketed Formulation and C. caesia nanoparticles.
Figure 13: Drug Release kinetics of C. caesia nanoparticles.

Detailed description of the invention:
In an embodiment of the present disclosure, there is provided Copper Nanoparticles comprising Copper Nitrate and C. caesia extract for use in catalysis, medicine, and electronics. The particle size of the copper nanoparticles ranges from 63.18 nm to 193.167 nm. The zeta potential of the copper nanoparticles is in the range of 20.3 mV to 62.4 mV. The copper nanoparticles have a poly dispersibility index of 0.0929 to 0.8191.

In an embodiment of the present disclosure, the copper nitrate and C. caesia extract in the copper nanoparticles are in a ratio ranging from 4:1 to 5:1.

In an embodiment of the present disclosure, the copper nitrate and C. caesia extract in the copper nanoparticles is in a ratio of 4.611:1.

In an embodiment of the present disclosure, the copper nanoparticles urther comprises 0.1 M Sodium Hydroxide for maintaining pH at 10.

In an embodiment of the present disclosure, there is provided a process of synthesis of Copper Nanoparticles. The C. caesia Roxb rhizome extract and copper nitrate solution are mixed under predetermined concentration to yield copper nanoparticle solution. 0.1 M Sodium Hydroxide is added to maintain the pH of the copper nanoparticle solution at 10. The copper nanoparticle solution is centrifuged at specific centrifugation conditions to obtain precipitate of crude copper nanoparticles. The precipitate of crude copper nanoparticles is washed multiple times with distilled water and ethanol to obtain washed precipitate of copper nanoparticles. The washed precipitate is dried to obtain dry and stable copper nanoparticles.
In an embodiment of the present disclosure, quantity of copper nitrate is 46.11 ml, C. caesia extract is 0 ml, Sodium Hydroxide is 0.1 M, Distilled Water is q.s. and Ethanol is 10 ml for synthesis of copper nanoparticle.
In an embodiment of the present disclosure, the concentration of the copper nitrate solution is 0.01 M.
In an embodiment of the present disclosure, the mixing of the C. caesia Roxb rhizome extract and the copper nitrate solution are done under continuous stirring for 2 h at temperature 70°C and pH 10.
In an embodiment of the present disclosure, the centrifugation of the copper nitrate solution is at 10,000 rpm for 20 min.

In an embodiment of the present disclosure, the drying of washed precipitate is done at temperature 70°C for 6 h to obtain dry and stable copper nanoparticles.

In an embodiment of the present disclosure, there is provided an antidiabetic pharmaceutical composition comprising copper nanoparticles of the present disclosure.

The constituents, i.e. Copper Nitrate, C. caesia extract, Sodium Hydroxide, Distilled Water, and Ethanol are chosen for their specific properties and potential synergistic effects. The Box Behnken design, a response surface methodology, has been employed to optimize the formulation process by studying the effects of varying constituent concentrations. The design suggested 13 runs, detailed in Table 1. Analytical techniques like spectroscopy and microscopy are used to characterize the final product, which has potential applications in catalysis, medicine, and electronics.
Table 1: Factors used in experiment design

Factor Name Unit s Type Sub Type Min. Max. Coded
Low Coded
High Mean Std. Dev.
A Copper
Nitrate Ml Numeric Continuous 10.00 50.00 -1?

10.00 +1?

50.00 30.00 16.33
B PEG 400 % w/v Numeric Continuous

0.1000 2.00 -1?

0.10 +1?

2.00 1.05 0.7757
C pH - Numeric Continuous

4.00 8.00 -1?

4.00 +1?

8.00 6.00 1.63

The experimental design was aimed to optimize three critical responses for the formulation:
• R1 (Particle Size): Range of observed values: 63.18 nm - 193.167 nm
• R2 (Zeta Potential): Range of observed values: 20.3 mV - 62.4 mV
• R3 (PDI): Range of observed values: 0.0929 - 0.8191
The 13 experimental runs yielded observations for each response, as detailed in Table 2. A high signal-to-noise ratio has been observed by analyzing the ratio of the mean value of each response to its standard deviation. This indicates:
1. A well-designed experiment: The chosen factors and levels effectively captured the variability in the responses.
2. Sufficient data for analysis: The 13 runs provided enough data points for meaningful statistical analysis.
The observed ranges for each response suggest a wide design space, allowing for exploration and identification of optimal formulation conditions.
Thereafter, the optimal combinations of factors are determined for achieving desired nanoparticle properties.

Table 2: Responses used in experimental design
Response
Name Units

Observations

Minimum

Maximum

Mean Std.
Dev. Ratio

R1 Particle
Size nm 13.00 63.18 193.167 124.10 41.68 3.06
R2 Zeta potential mV 13.00 20.332 62.4 40.78 13.67 3.07
R3 PDI - 13.00 0.0929 0.8191 0.3262 0.2222 8.81

A Box-Behnken design has been used to investigate the effects of copper nitrate concentration (A), PEG 400 concentration (B), and pH (C) on copper nanoparticle yield. The design consisted of 13 runs which is represented in Table 3.
Table 3: Levels of Factors

Sr. No. Run Independent Variables
Factor 1
A: Copper Nitrate Ml Factor 2
B: PEG 400
%w/v Factor 3 C: pH
1 03 10 0.1 6
2 09 50 0.1 6
3 02 10 02 6
4 01 50 02 6
5 06 10 1.05 4
6 12 50 1.05 4
7 13 10 1.05 8
8 05 50 1.05 8
9 11 30 0.1 4
10 04 30 02 4
11 08 30 0.1 8
12 07 30 02 8
13 10 30 1.05 6

A factorial design with three independent variables, each evaluated at three levels (-1, 0, +1), has been used to investigate the responses. The design included 13 runs, with one center point to account for uncontrolled factors. Results have been analyzed and modeled.
“Y=ß0+ß1A+ß2B+ß3C+ß11A2+ß22B2+ß33C2+ß12AB+ß13AC+ß23BC”
In the equation Y = f(A, B, C), Y represents the measured response, while A, B, and C denote the independent variables of copper nitrate, PEG 400, and pH respectively. The coefficients ß0 (intercept), ß1, ß2, and ß3 (linear), ß11, ß22, and ß33 (quadratic), and ß12, ß13, and ß23 (interaction) quantify the impact of each factor and their combined effects on the response.
The validity of the regression model has been confirmed through analysis of regression coefficients, analysis of variance (ANOVA), and p-values. Fisher's test assessed the second-order model, and the quality of fit was determined using multiple coefficients of determination (R²). Optimization of the formulation was achieved using point-prediction methods within software, constrained by desired response values.
Statistical analysis has been conducted using GraphPad Prism software, and results have been compiled. Optimization of the nanoparticle formulation has been achieved using Design-Expert software with a Box-Behnken design (BBD). Independent variables included Copper Nitrate (F1), PEG 400 (F2), and pH (F3). Dependent variables were Particle Size (Y1), Zeta Potential (Y2), and PDI (Y3). A three-factor, three-level BBD has been used to determine the optimal combination.
Table 4: The combination of various factors used in nanoparticles and responses
Run Factor 1 A: Copper Nitrate
Ml Factor2 B: PEG 400
%w/v Factor 3
C: pH Particle size (nm) Zeta Potential (mV) PDI
1 50 2 6 66.6 41.4 0.092988
2 10 2 6 79.92 55.2 0.382284
3 10 0.1 6 140.97 28.152 0.19926
4 30 2 4 63.18 29.9 0.13104
5 50 1.05 8 143 46.8 0.16848
6 10 1.05 4 99 24.336 0.10368
7 30 2 8 91.26 57.5 0.21294
8 30 0.1 8 193.167 39.1 0.3861
9 50 0.1 6 169.164 37.536 0.81918
10 30 1.05 6 142.857 55.016 0.345384
11 30 0.1 4 133.731 20.332 0.2808
12 50 1.05 4 118.8 32.448 0.42624
13 10 1.05 8 171.6 62.4 0.69264

Perturbation is graphical tool in response surface methodology (RSM), has been used to visualize the relationship between factors and responses.
Perturbation plots illustrate the effect of all factors on each response (Figure 2). The slope of each line indicates the magnitude and direction of the factor's effect. In this study, PEG 400 concentration was the most influential factor for particle size and PDI, while pH had the most substantial impact on zeta potential.
By analyzing both plot types, researchers gained insights into factor influence and optimized conditions for preparing copper nanoparticles with desired properties for drug delivery.
The goal of the optimization was to maximize the yield of copper nanoparticles. The Design Expert was used to creating a response surface model that predicted the outcome of copper nanoparticles based on the input variables. The software also generated contour and 3D surface plots that visualized the relationship between the input variables and the response (Figure 3).
Based on the response surface model, the optimal conditions for preparing copper nanoparticles were determined: copper nitrate concentration of 0.01 M, C. caesia Roxb extract concentration of 10 mL, and pH of 10 (Figure 4). These conditions were predicted to produce a yield of 92.4%.

Using box Behnken design, in the design expert software we have successfully optimized the formulation using graphical optimization which is represented in Table 5.
Table 5: Final Optimized Formulation
Sr. No. Component Value
1 Copper Nitrate 46.11 ml
2 PEG 400 1.72 % w/v
3 pH 6
4 Particle Size 92.04
5 Zeta Potential 47.74
6 PDI 0.13

Characterization of optimized formulation
Surface Plasmon Resonance
The resonance peak's stabilization indicated the reaction's completion. When the peak position remained constant across consecutive measurements, it signified the reaction endpoint, with no further refractive index changes observed. This stable peak allowed for accurate determination of reaction kinetics and the effect of various parameters on the reaction process (Figure 5).
Energy-dispersive X-ray
EDX analysis was conducted on a sample containing 95% copper, 0.1% oxygen, 0.1% carbon, and 0.01% gold using a scanning electron microscope (SEM) with an energy dispersive detector. The analysis utilized a 10 mm working distance, 20 kV beam accelerating voltage, and 3.0 nm spot size.

The EDX spectra revealed peaks for copper, oxygen, carbon, and gold. The copper peak, the most intense, had an energy of 8.05 keV (K-alpha line). The oxygen peak had an energy of 0.52 keV (K-alpha line), while the gold peak had an energy of 2.12 keV (L-alpha line).

Quantitative analysis of the EDX spectra, performed with the instrument's software, confirmed the sample's composition: 95% copper, 0.1% oxygen, and 0.01% gold. The analysis also showed that copper was uniformly distributed, oxygen was slightly more concentrated near the surface, and gold was present in low concentrations with only a few particles detected.

The results aligned with the expected composition of copper alloys commonly used in industry, providing valuable insights into the elemental distribution within the sample.

In conclusion, EDX analysis confirmed the sample's composition as a copper alloy, providing quantitative elemental data and insights into element distribution within the sample (Figure 6).
Fourier transform infrared spectroscopy
Fourier transform infrared spectroscopy (FTIR) is used for analyzing organic and inorganic compounds. The KBr press pellet technique is a common sample preparation method. This section outlines the procedure for preparing and analyzing KBr press pellets to evaluate copper nanoparticle formation. The copper nanoparticle solution was filtered with 0.1-micron filter paper, and the filtrate was centrifuged at 10,000 G. The clear supernatant was scanned with FTIR spectroscopy.

A nitrate peak in the 1500–1800 cm?¹ region confirmed the reduction of copper ions (Cu²?) to elemental copper (Cu°) using a C. caesia Roxb. extract. The copper nanoparticles, coated with the herbal extract, released copper ions sustainably, prolonging therapeutic effects (Figure 7).

Zeta potential analysis determined the surface charge of spherical nanoparticles, approximately 111 nm in size. The nanoparticles were dispersed in a suitable liquid medium, such as distilled water or a buffer solution, to ensure uniform distribution.

Measurements were performed using a zeta potential analyzer. A small volume of the nanoparticle dispersion was placed in a cuvette, and an electric field was applied, causing the nanoparticles to move. The instrument recorded their motion to calculate electrophoretic mobility, which was then used to determine the zeta potential using the Smoluchowski equation.

The analysis indicated a zeta potential of 33.5 mV, suggesting a moderate surface charge. These measurements provided insights into the stability and behavior of the nanoparticles, as surface charge influenced their interactions with surrounding molecules and particles (Figure 8).

Scanning electron microscopy (SEM) was used to determine the particle size of nanoparticles synthesized from copper nitrate or C. caesia Roxb extract (Figure 9). Freshly prepared nanoparticles were separated from the residual solution by centrifugation. The resulting pellet was resuspended in distilled water and ultrasonicated to ensure uniform dispersion.
A small droplet of the nanoparticle suspension was placed on a glass slide and air-dried. A thin gold layer was then deposited on the dried sample using a sputter coater to enhance conductivity and prevent charging during SEM analysis. The SEM instrument scanned the sample with a focused electron beam, generating signals to construct an image of the sample surface.
SEM images showed the nanoparticles had a spherical shape with an average diameter of 111 nm.
Transmission electron microscopy (TEM) was used to examine the particle size of nanoparticles, approximately 111 nm in diameter and spherical in shape. A small amount of the nanoparticle suspension was drop-cast onto a carbon-coated copper grid and left to air dry, ensuring adherence to the carbon film.
The dried grid was loaded into the TEM instrument, which emitted a beam of electrons through the sample. The interactions between the electrons and nanoparticles formed an image on a fluorescent screen or digital camera. TEM images were then analyzed to measure the particle size and morphology using specialized software.
The analysis revealed that the nanoparticles had an average diameter of approximately 111 nm and were spherical (Figure 10). TEM provided high-resolution images, allowing for detailed examination of the nanoparticles at the atomic scale, effectively characterizing their size, shape, and distribution.
The in vitro release of all optimized formulations was calculated using the standard calibration curve of C. caesia (Figure 11). The in vitro release graph is shown in Figure 12. The optimized formulation exhibited controlled release, with 83% of the drug released in the first 10 hours.

The in vitro release study showed 95.8% release over 24 hours. The model best fitting the release data was evaluated using the correlation coefficient (r) and the value of n, particularly for the Higuchi equation. The release study was best explained by Higuchi's equation, showing the highest linearity (R² = 0.9943), followed by the first-order model (R² = 0.9977), Korsmeyer-Peppas model (R² = 0.9663), and zero-order equation (R² = 0.9338), as shown in Figure 13. The R² and k values for all release kinetics models are tabulated in Table 6.

The study clearly determined that the drug release from metallic nanoparticles is controlled, involving erosion or dissolution over time. A comparison between the marketed formulation and C. caesia nanoparticles was also performed. The cumulative drug release of C. caesia nanoparticles was found to be 92.4% over 24 hours, with about 80% released in the first 8 hours and the remainder over 24 hours. The graph showed a controlled release pattern.

In contrast, the marketed formulation released 70% of the drug in the first 4 hours and 89.6% over 8 hours.

The marketed formulation releases a higher percentage of the drug more quickly within the initial hours (70% in 4 hours), and it reaches nearly complete release (89.6%) within 8 hours, indicating a faster release compared to the controlled release profile of the Curcuma caesia nanoparticles.
Therefore, the optimized formulation shows a more gradual and sustained release, which is generally slower than the marketed product within the same timeframe. This supports the controlled release nature of the Curcuma caesia nanoparticles, making them potentially more suitable for applications requiring sustained drug delivery.

Table 6: Table Showing Release Kinetics of C. caesia nanoparticles

Release kinetics parameters for C. caesia nanoparticles
Zero Order First Order

Equation Korsermeyer Peppas’s Equation Higuchi

Equation
k R2 k R2 k R2 k R2
7.59 0.9338 -0.0784 0.9977 73.273 0.9663 27.347 0.9943
Stability studies of Optimized Formulation
Stability studies were performed according to ICH guidelines. Samples were kept for 6 months, and the results indicated that the formulation maintained all characterization parameters after 180 days. However, the formulation slightly lost its uniformity, becoming somewhat gritty. The results of the stability studies are detailed in Table 7.
Table 7: Stability studies
Evaluation
parameters Formulation
Days 0 Day 30 Day 60 Day 90 Day 180 Days
Particle
Size (nm) 92.5 95.4 97.5 99.4 108.7
Zeta Potential
(mV) 47 ± 0.15 45 ± 0.17 45 ± 0.1 40 ± 0.17 35 ± 0.17
Color Opaque,
brownish Opaque,
brownish Opaque,
brownish Opaque,
brownish Opaque,
brownish
Homogeneity Excellent Excellent Excellent Good
(Grittiness) Good
(Grittiness)
pH 6.88±0.09 6.44±0.04 6.14±0.05 5.89±0.01 5.89±0.01
% Drug Content 97.83±0.8 97.20±0.36 95.03±0.41 92.3±0.52 92.3±0.52

, Claims:
I/We claim
1. Copper nanoparticles comprising Copper Nitrate and C. caesia extract for use in catalysis, medicine, and electronics.
2. The copper nanoparticles as claimed in claim 1, wherein said nanoparticle comprises Copper Nitrate and C. caesia extract in a ratio ranging from 4:1 to 5:1, preferably in a ratio of 4.611:1.
3. The copper nanoparticles as claimed in claim 1, wherein said nanoparticles further comprises 0.1 M Sodium Hydroxide for maintaining pH at 10.
4. The copper nanoparticles as claimed in claim 1, wherein particle size of the nanoparticle size is ranges from 63.18 nm to 193.167 nm.
5. The copper nanoparticles as claimed in claim 1, wherein said nanoparticles have a zeta potential of 20.3 mV to 62.4 mV.
6. The copper nanoparticles as claimed in claim 1, wherein said nanoparticles have a poly dispersibility index of 0.0929 to 0.8191.
7. Synthesis of Copper Nanoparticles comprising the steps
- Preparing C. caesia Roxb rhizome extract,
- Preparing copper nitrate solution is distilled water of concentration of 0.01 M,
- Mixing the C. caesia Roxb rhizome extract and the copper nitrate solution at predetermined conditions to yield copper nanoparticle solution,
- Adding 0.1 M Sodium Hydroxide to maintain the pH of the copper nanoparticle solution at 10,
- Centrifuging the copper nanoparticle solution at 10,000 rpm for 20 min to obtain precipitate of crude copper nanoparticles,
- Washing the precipitate of crude copper nanoparticles with distilled water and ethanol to obtain washed precipitate of copper nanoparticles,
- Drying the washed precipitate of copper nanoparticles at temperature 70°C for 6 h to obtain dry and stable copper nanoparticles.
8. The synthesis of copper nanoparticles as claimed in claim 7, wherein the quantity of copper nitrate is 46.11 ml, C. caesia extract is 0 ml, Sodium Hydroxide is 0.1 M, Distilled Water is q.s. and Ethanol is 10 ml.
9. The synthesis of copper nanoparticles as claimed in claim 7, wherein the predetermined conditions of mixing the C. caesia Roxb rhizome extract and the copper nitrate solution are continuous stirring for 2 h at temperature 70°C and pH 10.
10. An antidiabetic pharmaceutical composition comprising copper nanoparticles as claimed in claim 1.
Dated this the 11th day of August 2024.