From waste to wealth: iron oxide doped hydroxyapatite-based biosensor for the colorimetric detection of ascorbic acid

Abstract

Ascorbic acid plays a pivotal role in the human body. It maintains the robustness, enlargement, and elasticity of the collagen triple helix. However, the abnormal concentration of ascorbic acid causes various diseases, such as scurvy, cardiovascular diseases, gingival bleeding, urinary stones, diarrhea, stomach convulsions, etc. In the present work, an iron-doped hydroxyapatite (HAp@Fe₂O₃)-based biosensor was developed for the colorimetric detection of ascorbic acid based on a low-cost, biocompatible, and ubiquitous material. Due to the catalytic nature of HAp owing to the acidic and basic moieties within the structure, it was used as a template for HAp@Fe₂O₃ synthesis. This approach provides an active as well as large surface area for the sensing of ascorbic acid. The synthesized platform was characterized by various techniques, such as UV-Vis, FTIR, SEM, XRD, TGA, EDX, etc. The HAp@Fe₂O₃ demonstrated inherent peroxidase-like activity in the presence of 3,3′,5,5′-tetramethylbenzidine (TMB) oxidized with the assistance of H₂O₂. It resulted in the color changing to blue-green, and after the addition of ascorbic acid, the color changed to colorless, resulting in the reduction of TMB. To achieve optimal sensing parameters, experimental conditions were optimized. The quantity of HAp@Fe₂O₃, H₂O₂, pH, TMB, time, and the concentration of ascorbic acid were fine-tuned. The linear range for the proposed sensor was 0.6–56 μM, along with a limit of detection of 0.16 μM and a limit of quantification of 0.53 μM. The proposed sensor detects ascorbic acid within 75 seconds at room temperature. The proposed platform was also applied to quantitatively check the concentration of ascorbic acid in a physiological solution.

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1 Introduction

Ascorbic acid (AA), also known as vitamin C, plays an important role in various redox metabolic reactions in the human body. As an efficient antioxidant, it helps in scavenging free radicals in the body to protect the cells from oxidative damage, enhance immunity, prevent scurvy, the common cold, cancer, etc. Its main source is fruits and vegetables, and it cannot be synthesized in the human body.¹ It is highly desirable to develop a robust, low-cost, and reliable platform for the sensing and monitoring of AA.

Various techniques have been used for the detection of ascorbic acid, such as electrochemical techniques,² fluorometric methods,³ high-performance liquid chromatography, etc.⁴ These techniques, despite their merits, have some drawbacks, such as complicated sample preparation steps that are time-consuming, costly, and require highly sophisticated instrumentation. These techniques require highly skilled operators, and acquiring and sustaining them in laboratories with limited resources is a big challenge. On the other hand, the colorimetric method has great potential for ascorbic acid detection owing to its simplicity, rapid operation, and cost-effectiveness.⁵ The added advantage associated with this approach is that its results can be visualized by the unaided eye.⁶

Hydroxyapatite (HAp) holds a prime position among biomaterials and has been utilized for bone implants. HAp comprises the major component of bone mineral and is expressed through the chemical formula Ca₁₀(PO₄)₆(OH).⁷ HAp has been produced utilizing a variety of precursors as well as extracted from natural sources. The most common natural sources of HAp extraction are marine organisms, animals, algae, and minerals.⁸ For the extraction of HAp, both marine and terrestrial animal bones, scales, and shells have been employed. Similarly, fruit peels, wood, flowers, leaves, and stalks, are considered other suitable sources of HAp.⁹ In the present work, we have used waste chicken bones as a precursor for HAp extraction. Chicken is a highly consumed product worldwide, and it is estimated that its consumption generates around 68 billion tons of waste annually. This enormous amount of waste needs to be used in a beneficial manner.¹⁰ The extraction of HAp and fabrication of the colorimetric sensor reported in this work are an attempt to sustainably and beneficially use chicken waste. Various techniques have been reported to isolate HAp from waste materials, such as mechanochemical,¹¹ wet chemical methods, etc.¹² However, the above-mentioned methods are laborious and require sophisticated equipment and apparatus. Therefore, in the present work, the calcination method has been used for the preparation of HAp because of its easy handling and the use of common instruments for the isolation of HAp.¹³

HAp and its nanocomposites have been used in various fields, such as diagnosis and overcoming environmental hazards.¹⁴ These composites are efficient in the removal of dyes like Congo red, methylene blue, etc.¹⁵ According to reports, HAp/chitosan nanocomposite is a promising option for tissue engineering, especially for scaffolds made of bone and cartilage.¹⁶ Novel immunosensors have been reported using HAp nanocrystals, gold nanoparticles, and chitosan mixed thoroughly with anti-PSA antibodies for the diagnosis of prostate cancer.¹⁷

Various methods, such as ion-beam sputter coating¹⁸ and electrophoretic deposition¹⁹ are used for adding metal ions to HAp. In comparison to these methods, doping is more efficient because ionic doping can result in crystallinity of HAp, changes in thermal stability, grain size, lattice parameters, crystal structure phase decomposition, microstructure, and solubility depending on the amount and size of the dopant.²⁰

In the current work, we synthesized HAp@Fe₂O₃ using the calcination method. The novelty of this work lies in the use of HAp@Fe₂O₃ for the sensing of ascorbic acid using chromogenic substrate (TMB) with the assistance of H₂O₂. In this process, the mimic enzyme (HAp@Fe₂O₃) provides a platform for the conversion of TMB into an oxidized form with the help of the oxidizing agent H₂O₂. Upon addition of AA, the oxidized form of TMB reversed back to its reduced (colorless) form, as observed with the naked eye and confirmed through a UV-Vis spectrophotometer. A new, fast, extremely sensitive, and selective AA detection method was developed. Different reaction conditions, such as HAp@Fe₂O₃ quantity, pH, TMB concentration, and incubation time, were optimized to get the best performance of the proposed platform. The proposed sensor was also applied to quantitatively check the concentration of ascorbic acid in physiological samples.

2 Experimental

2.1. Reagents-and-materials

All of the studies employed analytical-grade compounds; no additional purification was carried out. Double-distilled water was utilized to prepare the solutions. Ascorbic acid (≥97.0%), iron nitrate nonahydrate (Fe(NO₃)₃·9H₂O), NaOH (≥97.0%), hydrogen chloride (98%), H₂O₂ (35%), and TMB were utilized. We acquired all of the chemicals from Sigma-Aldrich.

2.2. Instrumentation

Fourier transform infrared spectroscopy (FTIR) was used for the identification of the characteristic peaks of HAp@Fe₂O₃ in the range 4000–500 cm⁻¹ (Agilent Technologies, Danbury, Conn, USA). The resolution of 4 cm⁻¹ and 256 scans per sample were selected. A scanning electron microscope coupled to an energy dispersive X-ray spectrophotometer (SEM-EDS) with a TESCAN VEGA (LMU) SEM with INCAx-act (Oxford Instruments) was used to study the morphology and elemental composition of the synthesized platform. Phase identification of the prepared HAp@Fe₂O₃ was confirmed by X-ray diffraction (Shimadzu, LabX XRD-6100). The thermal stability was observed by thermogravimetric analysis of TGA (Pyris-1, V-3.81 PerkinElmer). A UV-Vis spectrophotometer was used for taking the absorption spectra (Shimadzu, UV, 1,800, Japan).

2.3. Synthesis of hydroxyapatite

Chicken waste bones were collected from a local restaurant. To remove any visible fleshy tissues adhering to bones, a thorough cleansing procedure was carried out. First of all, the bones were washed thoroughly with distilled water. Subsequently, the bones were crushed into small pieces and subjected to distilled water and acetone treatment. The meticulously cleaned waste bones were immersed in a 1 M NaOH solution. This was followed by proper washing and drying for 24 hours at 70 °C.²¹ The extraction of inorganic HAp from the processed chicken bones was achieved through calcination at 800 °C. Pre-treated and dried bone pieces (10 g) were placed in alumina crucibles and subjected to calcinations in order to remove all the organic components. The temperature was gradually increased at a heating rate of 5 °C per minute and heated to 800 °C for a period of 8 hours.

2.4. Synthesis of iron doped HAp

The process involves treating iron nitrate nonahydrate (Fe(NO₃)₃·9H₂O) with HA powder derived from broiler chicken bone in a ratio of 1 : 9 by weight. The resulting mixture of powdered substances was gradually heated and fused within high-alumina crucibles while being covered. This fusion was performed at a rate of 5 °C per minute and maintained for three hours at a temperature of 800 °C. Subsequently, the crucibles were allowed to cool down to room temperature.²²

2.5. Detection of ascorbic acid

For the colorimetric detection of ascorbic acid, TMB was used as a chromogenic substrate in the presence of HAp@Fe₂O₃. The experiment was performed as follows: TMB underwent oxidation assisted by H₂O₂ in the presence of the synthesized platform. This resulted in a color change from colorless to blue-green. The protocol involves the mixing of 4 mg of HAp@Fe₂O₃, 500 μL of PBS buffer solution (6 mM), 200 μL of TMB (12 mM), and 100 μL of hydrogen peroxide (24 mM). Subsequently, 100 μL of ascorbic acid (0.6–56 μM) were added to the reaction mixture. This was followed by the incubation of the reaction mixture for 75 seconds. After the addition of ascorbic acid, the color changes from blue-green to colorless owing to the reduction of TMB. The anticipated change in visible range was also authenticated through a UV-Vis spectrophotometer.²³

3 Results and discussions

3.1. Characterization result

3.1.1. FTIR analysis of HAp and HAp@Fe₂O₃. Fig. 1(i) shows the Fourier transform infrared spectroscopy of pure HAp and HAp@Fe₂O₃. The FTIR spectra indicate a lack of substantial disparity between the HAp and HAp@Fe₂O₃ materials. Each peak corresponds to a distinctive feature of HAp. The bands falling around 558 cm⁻¹ and 1020 cm⁻¹ correspond to the phosphate group present in the synthesized platform. Additionally, the peaks around 1440 cm⁻¹, represent the presence of the carbonate group, which remains in the structure from organic moieties despite pyrolysis at high temperatures.²⁴ The peaks above 3000 cm⁻¹ represent the presence of OH group functionality in the proposed synthesized platform and HAp.²⁵

Fig. 1 (i) FTIR spectra of the prepared (A) HAp and (B) HAp@Fe₂O₃ indicate the presence of phosphate, carbonate, and hydroxyl groups. (ii) XRD spectra of the prepared (A) HAp and (B) HAp@Fe₂O₃. The HAp crystal lattice contracts due to the ion exchange of Ca²⁺ with Fe³⁺, which facilitates the reduction of crystalline size. (iii) EDX analysis of the prepared Hap; and (iv) HAp@Fe₂O₃. The HAp spectrum displays the distinctive peaks of Ca, P, and O; on the other hand, the HAp@Fe₂O₃ spectrum displays the additional peak indicating the presence of Fe. Moreover, it demonstrates that when Fe is added to the HAp structure, the intensity of Ca decreases. SEM analysis spectra of prepared (v) HAp and (vi) HAp@Fe₂O₃ indicate its nanoporous structure, which is highly desirable for an expanded surface area. (Vii) TGA analysis of synthesized HAp and HAp@Fe₂O₃ indicates the high thermal stability of the synthesized platform.

3.1.2. X-ray diffraction (XRD) pattern of fabricated nanocomposite. The crystalline structure of both HAp and HAp@Fe₂O₃ was identified using the XRD patterns as shown in Fig. 1(ii). Diffraction peaks for HAp were visible at 2θ values of 26.12°, 31.14°, 32.16°, and 34.46°, respectively, which correspond to the (002), (211), (112), and (202) planes. Similarly, the 2θ values of 26.16° (002), 31.7° (211), 32.2° (112), and 34.72° (202), diffraction peaks of iron oxide HAp@Fe₂O₃ were found, confirming the formation of a crystallized hexagonal HAp@Fe₂O₃ structure. It is clear from the figure that the pristine form of HAp shows sharp peaks, whereas HAp@Fe₂O₃ shows slight broadening and comparatively less intense peaks. This broadening of the peaks can be attributed to the incorporation of Fe₂O₃ in the structure of HAp. It results in the generation of a slight amorphous phase within the crystalline structure of Hap.²⁶ This incorporation is performed strategically to achieve a balance between the crystallinity of the material and the amount of Fe₂O₃. The Scherrer equation was used to determine the crystal size of the prepared HAp and HAp@Fe₂O₃. The average crystalline size of HAp and HAp@Fe₂O₃ is 32.54 and 27.91 nm, respectively. This result indicates that the incorporation of Fe into HAp results in a reduction in crystallite size.²⁵

3.1.3. EDX analysis of HAp and HAp@Fe₂O₃. Energy-dispersive X-ray (EDX) analysis was used to evaluate the elemental composition of HAp and HAp@Fe₂O₃. For the HAp specimen, the EDX investigation identified multiple elements²⁷ including carbon (6.87%), oxygen (26.72%), sodium (3.70%), magnesium (0.57%), aluminum (0.27%), phosphorus (20.76%), and calcium (41.12%) as shown in Table 1 and Fig. 1(iii). Similarly, for the HAp@Fe₂O₃ sample, the elemental composition was identified as phosphorus (15.54%), calcium (32.08%), oxygen (47.68%), sodium (2.59%), iron (1.61%), and sulfur (0.50%) by weight, as shown in Table 1 and Fig. 1(iv).

Table 1 EDX analysis of HAp and HAp@Fe₂O₃

Element	HAp		HAp@Fe2O3
	Weight (%)	Atomic (%)	Weight (%)	Atomic (%)
C	6.87	13.84	—	—
O	26.72	40.41	47.68	67.13
Na	3.70	3.89	2.59	2.54
Mg	0.57	0.57	—	—
Al	0.27	0.24	—	—
P	20.76	16.22	15.54	11.30
Ca	41.12	24.83	32.08	18.03
S	—	—	0.50	0.35
Fe	—	—	1.61	0.65
Total	100.00	100.00	100.00	100.00

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3.1.4. SEM analysis of the prepared HAp and HAp@Fe₂O₃. The SEM images of the synthesized HAp and HAp@Fe₂O₃ are shown in Fig. 1(v and vi). The morphology shows the nanostructure of the synthesized HAp and HAp@Fe₂O₃. This shows that the successful synthesis of the HAp (A) and HAp@Fe₂O₃ (B) nanoparticles having a structure with an expanded surface area is highly needed for the catalytic activity of our synthesized platform. By introducing iron into the HAp, we can further decrease the particle size, increase the surface area, and make it a better reactive surface for catalytic activities due to the enrichment of electrons. The structure of HAp, combined with its biocompatibility and osteoconductivity, the presence of both acidic and basic moieties, and the doping with Fe, make it an excellent surface for catalytic reactions.²⁸

3.1.5. TGA analysis of HAp and HAp@Fe₂O₃. The TGA study of the synthesized HAp and HAp@Fe₂O₃ was carried out in order to find their thermal stability as shown in Fig. 1(vii). There is a steady decrease in the weight of the HAp with an increase in temperature after 250–700 °C, indicating the loss of organic material present in the sample. On the other hand, in HAp@Fe₂O₃, there is no decrease in weight up to around 650 °C, indicating the robustness and high thermal stability of our synthesized platform. A sudden, slight weight loss of up to 3% in HAp@Fe₂O₃ can be observed beyond 650 °C, indicating its high thermal stability. Beyond 700 °C, no visible weight loss was observed, as shown in the TGA curve.

3.2. Colorimetric determination of ascorbic acid

Fig. 2 shows the colorimetric detection of ascorbic acid. The following optimum experimental conditions were followed: HAp@Fe₂O₃ (4 mg) was mixed with 500 μL of PBS solution (6 mM) and 200 μL of TMB solution (12 mM), followed by the addition of 100 μL of hydrogen peroxide solution (24 mM) in an Eppendorf tube. This combination led to a color change from colorless to blue-green, which was observed with the naked eye. After the addition of ascorbic acid to 120 μL (56 μM), the blue-green color changed to a colorless form. Fig. 6 presents both the UV-Vis spectra and a visual colorimetric change.²⁹

Fig. 2 UV-Vis spectra of the sensing reaction. The addition of 4 mg HAp@Fe₂O₃, 150 μL TMB (12 mM), 100 μL (24 mM) hydrogen peroxide, and 120 μL (A) without ascorbic acid and (B) with 150 μL ascorbic acid (56 μM).

3.3. Proposed mechanism of the reaction

In the current work, the proposed sensor, HAp@Fe₂O₃, functions as a mimic enzyme. With the assistance of H₂O₂, the mimic enzyme converts the TMB into oxidized TMB, resulting in the formation of a blue-green color. Here, H₂O₂ helps in the generation of hydroxyl free radicals, which attack TMB and generate a colored complex. The generation of hydroxyl free radicals from H₂O₂ is catalyzed by the mimic enzyme. The addition of ascorbic acid to this complex results in the reduction of TMB, which becomes colorless in its reduced form. The oxidation of ascorbic acid results in the formation of dehydroascorbic acid. With the addition of ascorbic acid, the free radical generated from hydrogen peroxide by the catalytic action of HAp@Fe₂O₃ was scavenged. This scavenging of free radicals by ascorbic acid results in no oxidation of TMB. This colorimetric change was also confirmed with a UV-Vis spectrophotometer. The oxidized TMB showed maximum absorption at 652 nm (Scheme 1).

Scheme 1 Proposed mechanism for the sensing of ascorbic acid based on the HAp@Fe₂O₃ mimic enzyme assisted by H₂O₂.

3.4. Optimization of various parameters

3.4.1. Effect of HAp@Fe₂O₃ amount. Fig. 3(i) shows the concentration optimization of the mimic enzyme (HAp@Fe₂O₃). For the optimization of HAp@Fe₂O₃, various concentrations of the platform (1–7 mg) were added to the reaction at optimized conditions. The best colorimetric response was observed at 4 mg. So the 4 mg of HAp@Fe₂O₃ was used for further experiments. The reaction was performed as follows: 4 mg of HAp@Fe₂O₃ was added to an Eppendorf tube along with 500 μL of phosphate-buffer solution (6 mM), 200 μL of TMB solution, 100 μL of H₂O₂, and 100 μL of ascorbic acid solution with a concentration of 56 μM. Upon the addition of ascorbic acid after 75 seconds, the color completely changed from blue-green to a colorless product in the presence of 4 mg HAp@Fe₂O₃. Deniz Uzunoğlu et al. reported that 100 μL of Fe NPs solution was optimum for the colorimetric detection of ascorbic acid.³⁰

Fig. 3 (i) HAp@Fe₂O₃ was optimized at 1–7 mg. The best colorimetric response was observed at 4 mg HAp@Fe₂O₃. Conditions: 4 mg HAp@Fe₂O₃, 150 μL TMB (12 mM), 100 μL (24 mM) hydrogen peroxide, and 120 μL ascorbic acid (56 μM). (ii) AA, HAp@Fe₂O₃, and TMB solution interaction is demonstrated at different pH levels (3–9) in PBS at 4 mg HAp@Fe₂O₃ [ascorbic acid] = 56 μM (120 μL). The ideal colorimetric response was obtained at a pH of 6. (iii) Effect of time (15–105 seconds) at 4 mg HAp@Fe₂O₃, ascorbic acid 56 μM (150 μL). The reduction of TMB in the presence of ascorbic acid is very fast due to the high reducing power of AA. The color of the mixture changed from blue-green to transparent in a few seconds. (iv) Effect of TMB (2–20 mM) on the reaction oxidized by catalyst and H₂O₂ at 4 mg HAp@Fe₂O₃, ascorbic acid 56 μM (150 μL) were optimized, and the optimal concentration of TMB was found to be 12 mM. (v) The effect of H₂O₂ (6–42 mM) at 4 mg HAp@Fe₂O₃ [ascorbic acid] = 56 μM (150 μL) on the reaction was optimized, and the optimal response was shown at 24 mM.

3.4.2. pH optimization. Fig. 3(ii) shows the optimization of pH for the proposed fabricated sensor. To efficiently control and adjust the response of the suggested sensor, various pH values ranging from 3 to 9 were examined. The best colorimetric response of the proposed biosensor was observed at pH 6. TMB's poor solubility in aqueous solutions—which is enhanced by the protonation of one of these substrates' amino groups—is the cause of its acid-dependent reactivity. Nevertheless, further pH reduction causes both amino groups to become protonated, rendering the substrate resistant to catalytic oxidation processes.³¹ In the case of graphitic carbon nitride nanosheets, pH 4 was observed as the optimum pH for the sensing of chromium(VI) and ascorbic acid.³²

3.4.3. Effect of time on sensitivity. Fig. 3(iii) shows the optimization of time for the proposed sensor. Ascorbic acid was colorimetrically detected in the presence of the peroxidase-like activity of HAp@Fe₂O₃. For the optimization of time, we performed the experiments at different time intervals of 15–105 seconds under optimized conditions. The best colorimetric response was observed at 75 seconds. The optimization of time was done at the optimum experimental conditions: 4 mg of HAp@Fe₂O₃, 500 μL of phosphate-buffer solution (6 mM), 200 μL of TMB solution, 100 μL of H₂O₂, and 100 μL of an ascorbic acid solution with a concentration of 56 μM. While Edwin et al. reported that 3 minutes is optimum for the colorimetric detection of ascorbic acid.³³

3.4.4. Optimization of TMB concentration. Fig. 3(iv) shows the optimization of TMB concentration. The ability of HAp@Fe₂O₃ was evaluated using TMB as a substrate. Optimization of TMB concentration was done using various solutions of TMB in the range of 3–21 mM. 12 mM TMB concentration was observed to be optimal for the proposed sensor, as can be seen in the figure. The color changed from colorless to blue-green upon the addition of 4 mg HAp@Fe₂O₃, 150 μL TMB (12 mM), 100 μL (24 mM) hydrogen peroxide, and 120 μL Ascorbic Acid (56 μM). While in the reported literature 0.8 mM concentration, 15.4 μL TMB (52 mM concentration) was observed to be optimal for the proposed sensor.³⁴

3.4.5. Optimization of H₂O₂. Fig. 3(v) shows the optimization of hydrogen peroxide. The preferred oxidizing agent for the reporter TMB solution is H₂O_2. As a result, various H₂O₂ concentrations (6–42 mM) were used to achieve the optimum H₂O₂ concentration. The optimum (24 mM) H₂O₂ concentration was observed for the proposed sensor at optimum experimental conditions of 4 mg HAp@Fe₂O₃, 150 μL TMB (12 mM), 100 μL (24 mM) hydrogen peroxide, and 120 μL ascorbic acid (56 μM). While E. Davidson et al. reported that a (2 M) H₂O₂ concentration was optimum for the sensing of ascorbic acid.³³

3.4.6. Peroxidase like activity of HAp@Fe₂O₃. The peroxidase-like activity of the mimic enzyme (HAp@Fe₂O₃) was analyzed using Michaelis–Menten kinetics. Catalysts with high values of V_max and lower values of K_m are desirable. The results of the current work and comparison with the reported literature are given in Table 2. It is clear from the results that the mimic enzyme shows comparable values of V_max when compared to horseradish peroxidase (HRP) for both substrates.

Table 2 Comparsion of peroxidase like activity of HAp@Fe₂O₃ and HRP

Catalysts	Substrate	Vmax (10^−8 M s^−1)	Km (mM)	Reference
HRP	TMB	17.19	0.424	35
HRP	H2O2	10.55	3.240
HAp@Fe2O3	TMB	15.4	3.11	This work
HAp@Fe2O3	H2O2	23.5	6.90

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3.4.7. Effect of ascorbic acid concentration. The proposed biosensor was applied to measure the concentration of ascorbic acid. Fig. 4(i) shows the absorbance spectra of ascorbic acid by using various concentrations of AA in the range of 0.6–56 μM in an optimized condition. Utilizing the peroxidase mimic activity of HAp@Fe₂O₃ in the presence of TMB substrate, a sensitive approach was developed for the colorimetric detection of ascorbic acid under optimal experimental conditions. In the absence of ascorbic acid, a peak at 652 nm was observed by using a UV-Vis spectrophotometer. After the addition of ascorbic acid, the peaks gradually decreased by increasing the concentration of ascorbic acid. At a concentration of 56 μM of AA, the peak was completely reduced, and the color changed from blue-green to colorless. By using the calibration graph as shown in Fig. 4(ii), the proposed colorimetric sensor of ascorbic acid within a linear range of 0.6–56 μM with a limit of detection (LOD) of 0.16 μM and a LOQ of 0.53 μM were calculated using the formulas LOD (3*SD/slope) and LOQ (10*SD/slope). The limit of detection and linear range of the present study were compared with the reported literature, as shown in Table 3. It is clear from the table that the fabricated platform has exceptional sensitivity and a wide linear range.

Fig. 4 HAp@Fe₂O₃-based AA biosensor (i) UV-Vis spectra and colorimetric change with respect to change in different concentrations (0.6–56 μM) of ascorbic acid. (ii) Calibration plot of AA concentrations versus absorbance conditions: 4 mg HAp@Fe₂O₃, 150 μL TMB (12 mM), 100 μL (24 mM) hydrogen peroxide, and 120 μL ascorbic acid (56 μM).

Table 3 Comparative analysis of proposed biosensor

S. no.	Materials used	Method applied	Linear range (μM)	LOD (μM)	References
1	CQDs	Colorimetric	1.0–105	0.14	36
2	Cu–Ag/rGO	Colorimetric	5–30	3.8	37
3	Papain-Ag NPs	Colorimetric	0.25–50	0.079	38
4	Pt/CeO2 nanocomposites	Colorimetric	0.5–30	0.08	39
5	Smartphone based CD spectrometer	Colorimetric	0.6250–40	0.4946	40
6	Silica coated Au nanorods	Colorimetric	0.1–2.5	0.049	41
7	Graphene quantum dots	Colorimetric	0.3–10	0.094	42
8	M-CQDs	Colorimetric	10–70	3.26	43
9	HAp@Fe2O3	Colorimetric	0.6–56	0.16	Present work

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3.5. Selectivity study of the proposed method

The selectivity of the proposed sensor, HAp@Fe₂O₃, is shown in Fig. 5. In the presence of commonly co-existing substances, including dopamine, uric acid, Mg²⁺, glucose, creatinine, and Ca²⁺, the selectivity of the proposed sensor was found to be excellent. The results illustrate that with the addition of ascorbic acid, the color completely changed from blue-green to colorless, while with the addition of dopamine, uric acid, Mg²⁺, glucose, creatinine, and Ca²⁺, no color change was observed. The proposed biosensor showed significant selectivity for the detection of ascorbic acid, as indicated in the results.

Fig. 5 Selectivity of the fabricated sensor was checked at optimized conditions (56 μM) for dopamine, Mg²⁺, Ca²⁺, glucose, uric acid, creatinine, and ascorbic acid. It can be seen that the TMB is completely reduced by AA at the optimized experimental conditions.

Under the aforementioned experimental conditions, the reproducibility of the proposed sensors was tested after each preparation. We observed a high level of reproducibility in the results. The response of the fabricated sensor was tested over a period of 6 months. For this purpose, periodically each month, the sensor response was evaluated. There was no considerable difference in the response of the sensor over the mentioned period of time. This highlighted the stability of the proposed sensing platform.

3.6. Application of the fabricated sensor

To examine the practical use of the fabricated platform, we employed the proposed sensor for detecting ascorbic acid in physiological solutions, as shown in Fig. 6(i). We applied the proposed sensor for the detection of ascorbic acid concentrations within the range of 0.6–56 μM in physiological solutions. Different concentrations of ascorbic acid in physiological solutions, such as 10, 18, and 33 μM, were prepared and introduced to the fabricated sensor. Using a UV-Vis spectrophotometer, we investigated the alteration in colorimetric detection of ascorbic acid within physiological solutions. We observed an absorption peak at 652 nm that exhibited a linear decrease in absorbance with the rise in ascorbic acid concentration within the optimized time.³⁴ It proves that our suggested sensor is highly effective for detecting ascorbic acid in physiological solutions. Subsequently, blood plasma samples were collected from the Al-Habib clinical laboratory near the DHQ hospital in Kohat, KP, Pakistan. The samples were screened for the detection of ascorbic acid in the linear range of the proposed sensor. Strategic dilution of the real samples was performed to bring the analyte concentration into the linear range of our proposed sensor as and when needed. The response was observed with the naked eye and confirmed through a UV-Vis spectrophotometer, as shown in Fig. 6(ii).

Fig. 6 (i) Physiological sample analysis spectra of the proposed sensor. Different concentrations of ascorbic acid in physiological solution at optimized conditions [4 mg HAp@Fe₂O₃, 150 μL TMB (12 mM), 100 μL (24 mM) hydrogen peroxide, and 120 μL ascorbic acid (56 μM)]. (ii) shows the colorimetric response of the proposed sensor and the corresponding UV-Vis spectra under optimized conditions for the sensing of ascorbic acid in real samples.

4 Conclusion

In conclusion, a new, straight-forward, highly thermally stable, low-cost, biocompatible, highly sensitive, and selective sensing platform for ascorbic acid was fabricated. All the characterizations confirmed the successful synthesis of the mimic enzyme (HAp@Fe₂O₃). The fabricated sensor detected ascorbic acid with high sensitivity and selectivity in the presence of a bunch of potential interfering species. Comprehensive optimization studies were performed to fine-tune the sensing parameters, such as the amount of mimic enzyme (4 mg), pH (6), time (75 seconds), TMB concentration (12 mM), and H₂O₂ concentration (24 mM). The proposed sensor exhibited an extensive linear range of 0.6–56 μM, with a very low limit of detection (0.16 μM) and limit of quantification (0.53 μM) and an R² value of 0.998. These results indicate the fabricated platform is highly sensitive, and there is a strong correlation between absorption and concentration. The fabricated sensor was successfully used to detect ascorbic acid in physiological solutions. The sensing platform has the potential to be used for the diagnosis of diseases caused by the change in ascorbic acid. It can also be used in the food industry for the monitoring of different food samples.

Conflicts of interest

The authors declare that there is no conflict of interests.

Acknowledgements

Authors wish to thanks Researchers Supporting Project Number (RSP2024R45) at King Saud University Riyadh Saudi Arabia for financial support.

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