CuO-coated Pd hollow porous nanocage as well as preparation method and application thereof

Abstract

According to the CuO (at) Pd hollow porous nanocage and the preparation method and application thereof, a Cu2O nanocube serves as an etching template, the hollow porous CuO (at) Pd nanocage is obtained through the redox electrode potential relation of palladium and copper, a unique three-dimensional open frame of the hollow porous CuO (at) Pd nanocage provides high-density active site exposure and a three-dimensional confinement effect for oxygen deficiency engineering, and the hollow porous CuO (at) Pd nanocage can be applied to oxygen deficiency engineering. The multi-enzyme activity of peroxidase, oxidase and laccase is remarkable, a three-channel sensor array is constructed aiming at high toxicity, difficult degradability and reducibility of phenolic pollutants and differential response of phenolic antioxidants to the activities of the three enzymes, the multi-enzyme activity can be dynamically adjusted through pH and temperature, and the detection sensitivity is high. The sensor array has the advantages that the pH limit neglected by the existing sensor array is solved, phenolic isomers with different concentrations and under the same concentration are distinguished at the same time, the linear range is wide, the sensitivity is high, the specificity and the anti-interference capability are excellent, and efficient oxidative degradation and accurate recognition of six phenolic substances are realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of chemical detection, and particularly relates to a CuO@Pd hollow porous nanocage as well as a preparation method and application thereof. BACKGROUND

[0002] Phenolic antioxidants are a class of common food preservatives and additives containing phenolic hydroxyl groups, which are widely used in industrial synthesis and food preservation due to their excellent antioxidant capacity and thermal stability. However, high concentrations of phenolic antioxidants, while eliminating free radicals, inhibiting oxidation and odor, also have significant harmfulness and carcinogenic risks. For example, tertiary butylhydroquinone (TBHQ), which is widely used in various fat-containing foods, can cause chromosomal loss and breakage by damaging deoxyribonucleic acid, induce cell death and cancer; butylated hydroxyanisole (BHA) can cause thyroid system damage, metabolic and growth disorders, neurotoxicity and carcinogenicity; and butylated hydroxytoluene (BHT) has hepatotoxicity risk. With the increasing use of food preservatives, the distribution of phenolic antioxidants in food and environmental media has gradually expanded, but the related detection techniques still face challenges.

[0003] Nanocatalysts are nanomaterials with enzyme-like activity, which have received extensive attention and application in the fields of biomedicine, nanosensing, and cellular immunity in recent years. Studies have shown that laccase-like nanocatalysts can directly oxidize phenolic substances and produce characteristic absorption peaks in the presence of chromogenic agent 4-antipyrine, realizing the selective detection of phenolic substances. The potential of laccase-like nanocatalysts in phenolic monitoring, but the research on laccase-like nanocatalysts with high activity and high selectivity is still scarce, and the feasibility of their use in rapid quantitative detection of phenolic antioxidants remains to be further explored.

[0004] Oxygen vacancy engineering, which introduces oxygen vacancies to regulate the electronic structure and surface chemical environment of materials, is an effective strategy to improve the performance of nanocatalysts. Oxygen vacancy engineering introduces oxygen defect sites through various methods, which regulate the electronic structure, surface chemical environment, and reaction path of the material surface, accelerate the electron transfer speed, reduce the chemical reaction energy barrier, and improve the catalytic efficiency of the catalyst. There are many methods for generating oxygen vacancy defects (OVDs), including reaction temperature regulation, surface element doping, and in-situ surface treatment. Among them, the atomic substitution method, which replaces lattice metal atoms with hetero-metal atoms to achieve crystal phase reconstruction, is one of the key ways to improve catalytic performance. Cuprous oxide (Cu2O) is a p-type semiconductor material with a polycrystalline surface structure, which can form precise pore structures due to its sacrificial template characteristics, and the potential laccase-like activity of copper active sites has great development prospects in phenolic detection. SUMMARY

[0005] The purpose of the present application is to provide a CuO@Pd hollow porous nanocage based on the prior art, which has a unique three-dimensional open framework that provides high-density active site exposure and three-dimensional confinement effect for oxygen defect engineering, exhibits significant peroxidase (POD), oxidase (OXD) and laccase (LAC) multi-enzyme activity, and constructs a three-channel sensor array for the efficient oxidation and degradation and accurate identification of six phenolic substances in view of the high toxicity, difficulty in degradation and reduction of phenolic pollutants and the differential response of phenolic antioxidants to the three enzyme activities.

[0006] The second purpose of the present application is to provide a preparation method of the above-mentioned CuO@Pd hollow porous nanocage.

[0007] The third purpose of the present application is to construct a three-channel sensor array using the CuO@Pd hollow porous nanocage, which can dynamically adjust the multi-enzyme activity through pH and temperature, solve the pH limitation ignored by the current sensor array, distinguish phenolic isomers at different concentrations and at the same concentration, have a wide linear range and high sensitivity, have excellent specificity and anti-interference ability, and provide a direct method for regulating nanoenzyme activity through oxygen defect engineering.

[0008] The fourth purpose of the present application is to provide a construction method of the above-mentioned three-channel sensor array.

[0009] The fifth purpose of the present application is to use the above-mentioned three-channel sensor array for detecting target phenolic compounds, which can be successfully used for the detection and identification of phenolic antioxidants in food, and provides a new and reliable detection scheme for the evaluation and detection of phenolic substances in food and natural environment.

[0010] The technical scheme of the present application is as follows:

[0011] A preparation method of a CuO@Pd hollow porous nanocage, comprising the following steps:

[0012] (1) mixing anhydrous copper sulfate, sodium citrate, sodium hydroxide, ascorbic acid and water, and stirring and reacting at 20-30 DEG C to prepare a mixed solution containing Cu2O nanocubes;

[0013] (2) adding ascorbic acid and sodium tetrachloropalladate to the mixed solution obtained in step (1), stirring and reacting at 20-30 DEG C, centrifuging, washing and drying the reaction solution to obtain CuO@Pd hollow porous nanocage.

[0014] For the present application, in step (1), the mass ratio of anhydrous copper sulfate to sodium citrate is 110-140:49, preferably 120-130:49, and more preferably 125:49.

[0015] In step (1), the alkaline solution is a sodium hydroxide solution or a potassium hydroxide solution, preferably a sodium hydroxide solution.

[0016] In step (1), the molar ratio of anhydrous copper sulfate to ascorbic acid is 1:0.5-1.5, preferably 1:0.8-1.2, and more preferably 1:1.0.

[0017] In step (1), the size of the Cu2O nanocube is 195-205 nm, preferably 200 nm.

[0018] In this invention, in step (2), the mass ratio of anhydrous copper sulfate to ascorbic acid is 10-25:1, preferably 15-20:1, and more preferably 18.75:1.

[0019] In step (2), the molar ratio of anhydrous copper sulfate and sodium tetrachloropalladium is 1:0.5-1.5, preferably 1:0.8-1.2, and more preferably 1:0.93.

[0020] In step (2), the size of the CuO@Pd hollow porous nanocage is 275-285 nm, preferably 277 nm.

[0021] The CuO@Pd hollow porous nanocages prepared using the above method were used as etching templates with Cu2O nanocubes. Based on the redox electrode potential relationship between palladium and copper, a hollow porous CuO@Pd nanocage was designed. Its unique three-dimensional open framework provides high-density exposure of active sites and a three-dimensional confinement effect for oxygen defect engineering. Through controllable reduction treatment, lattice oxygen (O2O3) was achieved on the surface and inner walls of the nanocage channels. lat ), adsorbed oxygen (O) ads ) and oxygen vacancies (V o Collaborative optimization of ).

[0022] Experiments show that the material exhibits significant multi-enzyme activities, including peroxidase (POD), oxidase (OXD), and laccase (LAC), which are attributed to: (1) the high specific surface area of ​​the porous framework significantly increases the accessibility of oxygen vacancies; (2) the three-dimensional confinement effect promotes the diffusion of reactants (H2O2); and (3) the local selective electroreplacement of palladium ions optimizes the electron transport path and enhances Cu. 2+ / Cu + Redox cycle efficiency. Its multi-enzyme activity can be dynamically adjusted by pH and temperature, overcoming the application limitations of existing nanozymes in weakly acidic pH conditions.

[0023] This invention discloses a method for constructing a three-channel sensor array using CuO@Pd hollow porous nanocages. The three-channel sensor array includes a POD active channel, an OXD active channel, and a LAC active channel, and comprises the following steps:

[0024] (1) POD active channel: 3,3′,5,5′-tetramethylbenzidine, H2O2 solution, CuO@Pd hollow porous nanocage and target phenolic compound were added to HAc-NaAc buffer to carry out catalytic reaction. The absorbance change data of the reaction system (referring to the mixed solution before and after the reaction) at 652 nm was collected using a UV-Vis spectrophotometer to obtain the POD active channel.

[0025] (2) OXD active channel: 3,3′,5,5′-tetramethylbenzidine and CuO@Pd hollow porous nanocages were added to HAc-NaAc buffer to carry out catalytic reaction, and the change in absorbance of the reaction system before and after the addition of the target phenolic compound was collected at 652 nm using a UV-Vis spectrophotometer to obtain the OXD active channel.

[0026] (3) LAC active channel: 4-antipyrine, CuO@Pd hollow porous nanocage and target phenolic compound were added to MES buffer to carry out catalytic reaction, and absorbance data at 510 nm were collected using a UV-Vis spectrophotometer to obtain LAC active channel;

[0027] The target phenolic compounds are 2,4-dichlorophenol, bisphenol A, butylated hydroxytoluene, butylated hydroxyanisole, tert-butylhydroquinone, and propyl gallate.

[0028] For the purposes of this invention, in step (1), the pH value of the HAc-NaAc buffer solution is 3.5-4.5, preferably 4.0.

[0029] In step (1), the mass ratio of 3,3′,5,5′-tetramethylbenzidine to CuO@Pd hollow porous nanocage is 45-65:1, preferably 50-60:1, and more preferably 54:1.

[0030] In step (1), the temperature during the catalytic reaction is 20-30℃ and the reaction time is 110-130s, preferably 120s.

[0031] For the purposes of this invention, in step (2), the pH value of the HAc-NaAc buffer solution is 3.5-4.5, preferably 4.0.

[0032] In step (2), the mass ratio of 3,3′,5,5′-tetramethylbenzidine to CuO@Pd hollow porous nanocage is 45-65:1, preferably 50-60:1, and more preferably 54:1.

[0033] In step (2), the temperature of the catalytic reaction is 20-30℃ and the reaction time is 8-12 min, preferably 10 min.

[0034] For the purposes of this invention, in step (3), the pH value of the MES buffer is 7.0-8.0, preferably 7.4.

[0035] In step (3), the mass ratio of 4-antipyrine to CuO@Pd hollow porous nanocage is 5-25:1, preferably 10-20:1, and more preferably 15:1.

[0036] In step (3), the temperature during the catalytic reaction is 45-55℃, preferably 50℃, and the reaction time is 4-6 min, preferably 5 min.

[0037] A three-channel sensor array constructed using the aforementioned CuO@Pd nanocages was employed to identify six phenolic substances by utilizing LAC / POD / OXD activity. Linear discriminant analysis (LDA) was used to resolve the cross-response patterns, verifying the reliability of distinguishing binary and ternary phenolic mixtures. This not only simplifies the construction of the sensing unit but also overcomes the limitation of "one-to-one" detection. Furthermore, it holds significant importance for the efficient construction of other nanozyme detection array units and for improving the effective identification of phenolic antioxidants in complex foods.

[0038] This invention also provides the application of the above-mentioned three-channel sensor array in the detection of target phenolic compounds, achieving efficient oxidative degradation and accurate identification of six phenolic substances. It can be successfully used for the detection and identification of phenolic antioxidants in food, providing a new and reliable detection solution for the evaluation and detection of phenolic substances in food and the natural environment.

[0039] The advantages of using the technical solution of this invention are as follows:

[0040] This invention uses Cu2O nanocubes as etching templates and obtains hollow porous CuO@Pd nanocages through the redox electrode potential relationship of palladium and copper. Its unique three-dimensional open framework provides high-density exposure of active sites and a three-dimensional confinement effect for oxygen defect engineering, exhibiting significant multi-enzyme activities of peroxidase (POD), oxidase (OXD), and laccase (LAC). Targeting the high toxicity, recalcitrant nature, and reductive properties of phenolic pollutants, as well as the differentiated responses of phenolic antioxidants to the activities of the three enzymes, a three-channel sensor array is constructed. Its multi-enzyme activity can be dynamically adjusted by pH and temperature, overcoming the pH limitation neglected by current sensor arrays. It also distinguishes phenolic isomers at different and the same concentrations, possessing both a wide linear range and high sensitivity, excellent specificity and anti-interference capabilities. This enables efficient oxidative degradation and accurate identification of six phenolic substances and can be successfully applied to the detection and identification of phenolic antioxidants in food, providing a novel and reliable detection scheme for the assessment and detection of phenolic substances in food and the natural environment. Attached Figure Description

[0041] Figure 1This is a schematic diagram of the preparation process of CuO@Pd hollow porous nanocages;

[0042] Figure 2 This is a particle size distribution diagram and a Zeta potential diagram of Cu2O;

[0043] Figure 3 These are relevant spectra during the preparation process of CuO@Pd hollow porous nanocages; among them, Figure 3 In the image, 'a' is the SEM image of Cu2O; Figure 3 b and c are SEM images and magnified views of CuO@Pd, respectively. Figure 3 In the image, d and e are TEM images and magnified views of CuO@Pd, respectively. Figure 3 f is the elemental distribution diagram of CuO@Pd;

[0044] Figure 4 It is an XPS spectrum; among which, Figure 4 The spectrum of Cu2O is shown in the middle g. Figure 4 In the image, h represents the Cu 2p spectrum of Cu₂O; Figure 4 In the image, i represents the O1s spectrum of Cu2O; Figure 4 In the middle, j is the full spectrum of CuO@Pd;

[0045] Figure 5 It is an XPS spectrum; among which, Figure 5 In the image, k is the Cu 2p spectrum of CuO@Pd; Figure 5 In the image, l represents the Pd 3d spectrum of CuO@Pd; Figure 5 In the image, m is the O1s spectrum of CuO@Pd;

[0046] Figure 6 This is a particle size distribution diagram and a Zeta potential diagram for CuO@Pd.

[0047] Figure 7 This is a correlation spectrum of triple enzyme-like activities of CuO@Pd nanocages; among them, Figure 7 In Figure 'a', it is a schematic diagram of the three enzyme activities of CuO@Pd; Figure 7 b is the UV-Vis absorption spectrum of peroxidase and oxidase in different reaction systems; Figure 7 In the image, c represents the UV-Vis absorption spectra for verifying laccase in different reaction systems;

[0048] Figure 8 This is a correlation spectrum of triple enzyme-like activities of CuO@Pd nanocages; among them, Figure 8 In the diagram, d represents the effect of temperature on the catalytic activity of CuO@Pd. Figure 8 In the figure, e represents the effect of pH on the catalytic activity of CuO@Pd. Figure 8 f represents the effect of enzyme concentration on the catalytic activity of CuO@Pd; Figure 8The steady-state kinetics of TMB at different concentrations in CuO@Pd nanocages containing H2O2 are determined.

[0049] Figure 9 This is a correlation spectrum of triple enzyme-like activities of CuO@Pd nanocages; among them, Figure 9 The h in the figure represents the steady-state kinetics of different concentrations of H2O2 in CuO@Pd nanocages containing TMB. Figure 9 The steady-state kinetics of CuO@Pd nanocages with 2,4-DP as substrate were determined.

[0050] Figure 10 This is a correlation spectrum of triple enzyme-like activities of CuO@Pd nanocages; among them, Figure 10 The middle j represents the steady-state kinetics of the change in TMB concentration in the absence of H2O2 in CuO@Pd nanocages; Figure 10 In the figure, k represents the steady-state kinetics of TMB at different concentrations in Cu2O nanocubes containing H2O2; Figure 10 The image shows the steady-state kinetics of different concentrations of H2O2 in Cu2O nanocubes containing TMB.

[0051] Figure 11 The enzymatic reaction kinetics of Cu2O@Pd OXD simulated catalytic activity; the absorbance at 652 nm changes over time in the catalytic oxidation of TMB;

[0052] Figure 12 The activity of OXD and POD was verified by using OPD as an oxidation substrate.

[0053] Figure 13 This describes the change in POD activity after 10 minutes of nitrogen flow.

[0054] Figure 14 This describes the change in OXD activity after 10 minutes of nitrogen flow.

[0055] Figure 15 These are spectra related to the catalytic mechanism of CuO@Pd; among them, Figure 15 The relative activity of CuO@Pd when isopropanol, L-histidine, and p-benzoquinone are used as scavenging agents isopropanol; Figure 15 b represents O2 induced by CuO@Pd. - ESR spectra; Figure 15 c is induced by CuO@Pd 1 ESR spectrum of O2;

[0056] Figure 16 These are the correlation spectra of the nanosensor array, among which, Figure 16 In the formula 'a', there are six different chemical structural formulas of phenolic compounds. Figure 16In the figure, b represents the LAC activity of CuO@Pd against six different phenolic substances at the same concentration (50 μM);

[0057] Figure 17 These are the correlation spectra of the nanosensor array, among which, Figure 17 c represents the OXD activity of CuO@Pd against six different phenolic substances at the same concentration (50 μM); Figure 17 In the middle, d represents the POD active array sensing channel;

[0058] Figure 18 These are the correlation spectra of the nanosensor array, among which, Figure 18 In Figure 'a', fingerprint signal spectrum is generated by six phenolic substances at a concentration of 25 μM. Figure 18 b is the fingerprint signal spectrum generated by six phenolic substances at a concentration of 50 μM; Figure 12 c represents the fingerprint signal spectrum generated by six phenolic substances at a concentration of 100 μM;

[0059] Figure 19 These are the correlation spectra of the nanosensor array, among which, Figure 19 d is a radar image of six phenolic substances at a concentration of 25 μM; Figure 19 The image in section 'e' is a radar image of six phenolic substances at a concentration of 50 μM. Figure 19 f is a radar image of six phenolic substances at a concentration of 100 μM;

[0060] Figure 20 These are the correlation spectra of the nanosensor array, among which, Figure 20 The value in g is the principal component analysis (PCA) of six phenolic compounds at 25 μM. Figure 20 The value of h represents the linear discriminant analysis (LDA) of six phenolic substances at 25 μM. Figure 20 In the middle i, the hierarchical clustering analysis (HCA) of six phenolic substances was performed at 25 μM. Figure 20 The image in section j is a thermogram of six phenolic substances at 25 μM;

[0061] Figure 21 These are the correlation spectra of the nanosensor array, among which, Figure 21 The value of k is the principal component analysis (PCA) of six phenolic compounds at 50 μM. Figure 21 The value in l is a linear discriminant analysis (LDA) of six phenolic substances at 50 μM; Figure 21 The value of m is the hierarchical clustering analysis (HCA) of six phenolic substances at 50 μM. Figure 21 The value of n is a thermogram of six phenolic substances at 50 μM;

[0062] Figure 22 These are the correlation spectra of the nanosensor array, among which,Figure 22 The result is a principal component analysis (PCA) of six phenolic compounds at 100 μM. Figure 22 p represents the linear discriminant analysis (LDA) of six phenolic substances at 100 μM; Figure 22 The value of q is the hierarchical clustering analysis (HCA) of six phenolic substances at 100 μM. Figure 22 r is a thermogram of six phenolic substances at 100 μM;

[0063] Figure 23 These are the correlation spectra of the nanosensor array, among which, Figure 23 The value of 's' represents the principal component analysis (PCA) result of the sensor needle array on the mixture of diphenolic antioxidants. Figure 23 The value of t represents the principal component analysis (PCA) result of the sensor needle array on the mixture of triphenolic antioxidants;

[0064] Figure 24 These are the relevant spectra of the nanosensor array, among which, Figure 24 Principal component analysis (PCA) score plots of different concentrations of antioxidants identified by the sensor (a, 24d, 24g, 24j, 24m, and 24p);

[0065] Figure 25 These are the relevant spectra of the nanosensor array, among which, Figure 25 Linear relationship between different concentrations of antioxidants (b, 25e, 25h, 25k, 25n, and 25q) and PC1;

[0066] Figure 26 These are the relevant spectra of the nanosensor array. Figure 26 Heat maps of different concentrations of antioxidants c, 26f, 26i, 26l, 26o and 26r;

[0067] Figure 27 It is a radar diagram of three active channels of six different phenolic substances at concentrations of 1-100 μM;

[0068] Figure 28 This involves the selective analysis of six different phenolic compounds in the presence of interfering substances such as metal ions, amino acids, and urea. Figure 28 In the image 'a', the fingerprint image is a three-channel image. Figure 28 b in the middle is the PCA score chart; Figure 28 In the diagram, 'c' represents the HCA tree.

[0069] Figure 29 This study analyzed the interference of six different phenolic substances in the presence of interfering substances such as metal ions, amino acids, and urea. Figure 29 In the image 'a', the fingerprint image is a three-channel image. Figure 29 b in the middle is the PCA score chart; Figure 29In the diagram, 'c' represents the HCA tree.

[0070] Figure 30 PCA analysis was performed on six additional phenolic compounds in three different oily matrices. Figure 30 In sunflower seed oil, 'a' is... Figure 30 b is a tree diagram of HCA in sunflower seed oil; Figure 30 In the middle, c is in mayonnaise; Figure 30 In the diagram, d is the HCA tree diagram in mayonnaise; Figure 30 The "e" in the middle is in the butter; Figure 30 In the diagram, d is the HCA tree diagram in butter;

[0071] Figure 31 The three oily matrices were successfully distinguished using three-channel data analysis; namely... Figure 31 PCA analysis in a; Figure 31 Analysis of the violin diagram in section b; Figure 31 HCA tree analysis of C. Detailed Implementation

[0072] The present invention can be better understood from the following embodiments. However, those skilled in the art will readily understand that the descriptions in the embodiments are for illustrative purposes only and should not, and will not, limit the invention as detailed in the claims.

[0073] I. Experimental Methods

[0074] 1. Experimental Section

[0075] 1.1 Materials and Reagents

[0076] Anhydrous copper sulfate (Cu₂SO₄), sodium hydroxide (NaOH), ascorbic acid (AA), sodium tetrachloropalladium (Na₂PdCl₄), sodium citrate (C₆H₅Na₃O₇), 3,3′,5,5′-tetramethylbenzidine (TMB), p-benzoquinone, methanol, isopropanol, ethanol, bisphenol A (BPA), butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), propyl gallate (PG), tert-butylhydroquinone (TBHQ), 2,4-dichlorophenol (2,4-DP), 4-antipyrine (4-AP), and 4-morpholine ethanesulfonic acid (MES) were purchased from Aladdin Reagent Co., Ltd. (Shanghai, China). H₂O₂, acetic acid, and sodium acetate were purchased from Shanghai Maclean Biochemical Technology Co., Ltd.

[0077] 1.2 Instruments and Characterization

[0078] The morphology of the samples was obtained using scanning electron microscopy (FEIQuanta FEG 200) and high-resolution transmission electron microscopy (JEOL JEMFb-2000). The particle size distribution and zeta potential of the samples were characterized using nanoparticle potentiometry (Malvin Nano S). The absorption spectra of the samples were measured using a UV-Vis spectrophotometer (Meipuda UV-8000). X-ray photoelectron spectroscopy and X-ray Auger spectroscopy were also performed on the samples.

[0079] 2. Preparation of CuO@Pd hollow porous nanocages

[0080] CuO@Pd hollow porous nanocages were prepared using Cu2O nanocubes as etching templates. The specific steps included: dissolving anhydrous copper sulfate (Cu2SO4, 0.375 g, 1.5 mmol) and 0.147 mg sodium citrate (C6H5Na3O7, 0.147 mg, 0.00057 mmol) in 80 ml of distilled water and stirring until homogeneous. Then, 20 ml of 1.25 M sodium hydroxide (NaOH) solution was added dropwise and stirred until homogeneous. Finally, ascorbic acid (AA, 50 ml, 0.03 M, 1.5 mmol) aqueous solution was added dropwise to the resulting mixed solution. Stir at 20-30℃ for 30 min, then let stand for one hour. After natural sedimentation, remove the supernatant. Add 20 mg of ascorbic acid (AA) to the resulting solution, and while rotating at high speed, add 10 ml of sodium tetrachloropalladium aqueous solution (Na2PdCl4, 0.1392 M, 1.4 mmol) dropwise. The solution immediately turns black. Stir the reaction at 20-30℃ for 30 min. Centrifuge the resulting reaction solution at 12000 r / min for 10 min. After centrifugation, wash with distilled water and ethanol. Repeat the centrifugation step twice. Dry to obtain CuO@Pd hollow porous nanocages.

[0081] 3. Evaluation of the activities of three enzymes in CuO@Pd hollow porous nanocages

[0082] Using 3,3',5,5'-tetramethylbenzidine (TMB) as a substrate, the peroxidase (POD) and oxidase (OXD) activities of CuO@Pd hollow porous nanocages were studied by adjusting the presence of H2O2. The specific method is as follows: 2.25 μg / mL of CuO@Pd hollow porous nanocage aqueous solution was added to 1.5 mL of sodium acetate buffer (pH 4.0), followed by the addition of 0.6 mM TMB and 30 mM H2O2 (for POD detection) or no H2O2 (for OXD detection). After incubation at 37 °C for 5 min, the absorbance at 652 nm was measured.

[0083] Laccase (LAC) activity was assessed using 4-aminoantipyrine (4-AP) and 2,4-dichlorophenol (2,4-DP) as substrates: 60 μL of 4-AP (1 mg / mL), 60 μL of 2,4-DP (1 mg / mL), and 2.25 μg / mL of CuO@Pd hollow porous nanocage aqueous solution were added sequentially to 1 mL of MES buffer (pH 7.4), and the reaction was carried out at 50 °C for 5 min before the absorbance at 510 nm was measured.

[0084] 4. Steady-state dynamics detection

[0085] The substrates TMB and H2O2 were used in experiments evaluating peroxidase-like (POD) activity. The TMB concentration was varied in the presence of H2O2 to dynamically analyze POD activity. In the experimental setup, the H2O2 concentration was kept constant at 30 mM in 1.5 mL of sodium acetate buffer (pH 4.0), while the TMB concentration was varied within the range of 0.06–0.6 mM, and the absorbance at 652 nm was measured over time. Similarly, the experiment was repeated with the H2O2 concentration varied within the range of 3 mM–120 mM, keeping the TMB concentration constant at 0.6 mM, to obtain kinetic data for the peroxidase-like (POD) activity. In the experiment evaluating oxidase (OXD) activity, a 5 μg / ml aqueous solution of CuO@Pd hollow porous nanocages was added to 1.5 ml of sodium acetate buffer (pH 4.0), and TMB at concentrations between 0.06 mM and 6 mM was added. Kinetic data were collected and investigated. In the experiment evaluating laccase (LAC) activity, a 5 μg / ml aqueous solution of CuO@Pd hollow porous nanocages was added to 1 ml of MES buffer (pH 7.4), and 2,4-DP and 4-AP at concentrations between 0.012 mM and 0.8 mM were added. Kinetic data were collected and investigated.

[0086] The catalytic behavior of enzymes was found to conform to the Michaelis-Menten equation (1), which describes factors such as the maximum reaction rate (Vt). max ), Michaelis constant (K) m The parameters included the initial reaction rate (V0) and substrate concentration ([S]). Apparent kinetic parameters were then determined by constructing a bi-inverse plot using the Lineweaver-Burk method (2).

[0087]

[0088] 5. Construct a three-channel sensor array

[0089] A three-channel sensor array was constructed using the three catalytic activities (POD, OXD, and LAC) of CuO@Pd for the recognition of phenolic compounds. The construction methods of the POD, OXD, and LAC active channels are shown below:

[0090] POD active channel: 50 μl TMB solution (4.32 mg / ml), 30 μl 3% H2O2 solution (0.9 M), 10 μl 0.4 mg / ml CuO@Pd hollow porous nanocage aqueous solution, and target phenolic substances (2,4-DP, BPA, BHT, BHA, TBHQ, PG) were added to 1.5 ml HAc-NaAc buffer (20 mM, pH 4.0) to carry out the catalytic reaction. The reaction temperature was 20-30℃ and the reaction time was 120 s. The concentrations of the target phenolic substances (2,4-DP, BPA, BHT, BHA, TBHQ, PG) in the reaction system were kept at 25 μM, 50 μM, and 100 μM, respectively. The change in absorbance at 652 nm within 0-120 s was recorded to obtain the POD active channel.

[0091] OXD active channels: 50 μl of TMB solution (4.32 mg / ml) and 10 μl of 0.4 mg / ml hollow porous nanocage aqueous solution were added to 1.5 ml of HAc-NaAc buffer (20 mM, pH 4.0) for catalytic reaction at 20-30℃ for 10 min. After the reaction, target phenolic substances (2,4-DP, BPA, BHT, BHA, TBHQ, PG) were added to ensure that the concentrations of the target phenolic substances (2,4-DP, BPA, BHT, BHA, TBHQ, PG) in the reaction system were 25 μM, 50 μM, and 100 μM, respectively. The change in absorbance at 652 nm before and after the addition of the target phenolic substances was detected to obtain the OXD active channels.

[0092] LAC active channel: 60 μl of 1 mg / mL 4-AP solution, 10 μl of 0.4 mg / mL hollow porous nanocage aqueous solution, and target phenolic substances (2,4-DP, BPA, BHT, BHA, TBHQ, PG) were added to 1 mL of MES buffer (0.25 M, pH 7.4) to carry out the catalytic reaction. The reaction temperature was 50 °C and the reaction time was 5 min. The concentrations of the target phenolic substances (2,4-DP, BPA, BHT, BHA, TBHQ, PG) in the reaction system were ensured to be 25 μM, 50 μM, and 100 μM, respectively. The absorbance data at 510 nm was recorded to obtain the LAC active channel.

[0093] The procedure was repeated for six phenolic analytes, six times for each analyte. Therefore, six phenolic analytes were tested across three sensor channels. Each test generated a training data matrix of 6 phenolic analytes × 3 channels × 6 replicates. Principal component analysis (PCA), linear discriminant analysis (LDA), and hierarchical cluster analysis (HCA) were performed on the data in SYSTAT V13.0.

[0094] II. Results and Discussion

[0095] 2.1 Preparation and characterization of CuO@Pd hollow porous nanocages

[0096] The preparation process of CuO@Pd nanocages is as follows: Figure 1 As shown. Sodium citrate (C6H5Na3O7), copper sulfate (Cu2SO4), sodium hydroxide (NaOH), and ascorbic acid (AA) were mixed via a one-step hydrothermal method, and the mixture was stirred to form Cu2O nanocubes with a size of 200 nm. Figure 2 Subsequently, an electrodisplacement reaction was performed using Na₂PdCl₄ to transform solid Cu₂O into hollow porous CuO@Pd nanocages, exhibiting significant multi-enzyme activities of peroxidase (POD), oxidase (OXD), and laccase (LAC). Based on the differentiated responses of phenolic antioxidants to the activities of the three enzymes, a three-channel ratio sensor array was constructed to achieve high-resolution detection of six phenolic substances.

[0097] Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) characterization revealed the morphological evolution process: the Cu2O cubes generated by the one-step hydrothermal reaction had smooth surfaces, sharp edges, and uniform dispersion. Figure 3 a) After being loaded with Pd, a porous structure is formed on the surface of the cube. Figure 3 b-3c), with the size increasing from 200nm to 277nm. Figure 6 The core area is etched into a hollow structure.

[0098] During the electrochemical displacement process, Pd 2+ Continuous etching of Cu₂O, serving as a sacrificial template, creates pores on the surface of the Cu₂O nanocubes. These pores then form cavities as electroreplacement continues. The formation of these cavities provides more Cu-O exposure sites, further promoting the replacement reaction. Ultimately, porous walls form on the surface of the nanocage, while the interior is etched into cavities, resulting in a hollow, porous nanocage structure. Figure 3 The d-3e structure increases the contact area between the material and the substrate, and the three-dimensional confinement effect promotes the binding of substrate molecules to the active site, significantly enhancing enzyme catalytic activity. Elemental analysis ( Figure 3 f) shows that Pd, Cu, and O are uniformly distributed, confirming that Pd atoms have been successfully doped into the Cu lattice.

[0099] The chemical composition and elemental distribution of Cu₂O and CuO@Pd were also investigated using X-ray photoelectron spectroscopy (XPS). In the Cu 2p spectrum of Cu₂O, 932.18 eV (Cu 2p...) 3 / 2 ) and 951.93 eV (Cu 2p 3 / 2 Peak fitting results show that Cu + Main valence state ( Figure 4 h), confirming the successful synthesis of Cu2O; while CuO@Pd contains Cu + The proportion decreased significantly, Cu + / Cu 2+ The ratio is close to 1:1. Figure 5 k), which facilitates valence state cycling and electron transfer during the catalytic process. According to the redox potential theory, the standard electrode potential of palladium is 0.987V, while that of copper is only 0.153V. The potential of palladium is much higher than that of copper. In the synthesis, Cu in the solution... + It will partially lose electrons and be oxidized to Cu. 2+ Furthermore, the Cu-O bonds in the cubic Cu₂O structure are broken and replaced by Pd-O bonds. XPS analysis shows that palladium is most abundantly bonded to oxygen. Since the O bond in the Cu₂O structure is primarily composed of Cu... + This further proves that palladium is produced by replacing Cu. + The form of attachment is carried into the interior of the material ( Figure 5 l).

[0100] 2.2 Exploring the triple enzyme-like activity of CuO@Pd nanocages

[0101] We investigated the triple enzyme-like activity of CuO@Pd. Figure 7 a) Peroxidase-like (POD) and oxidase-like (OXD) activities can catalyze the oxidation of TMB under aerobic conditions. For example... Figure 7As shown in b, in the presence of CuO@Pd and TMB, the system exhibits an absorption peak at 652 nm, indicating that TMB is oxidized to oxidized TMB, confirming that CuO@Pd possesses OXD-like enzyme activity. In the system containing CuO@Pd, TMB, and H2O2, the absorption peak at 652 nm is significantly elevated, with absorbance significantly higher than the system containing only CuO@Pd and TMB (while the solution containing only TMB and H2O2 is colorless), demonstrating that CuO@Pd can enhance its oxidation ability of TMB through H2O2, i.e., it possesses POD-like activity. Furthermore, the absorbance of the system containing CuO@Pd, TMB, and H2O2 is higher than that of the system containing Cu2O, indicating that CuO@Pd prepared by palladium ion electrodisplacement significantly enhances its catalytic activity. To confirm its POD-like activity, we conducted tests at a low TMB concentration (0.06 mM), finding that the characteristic absorption peak at 652 nm gradually increases with increasing H2O2 concentration. Figure 11 This further demonstrates its excellent POD-like activity. When the chromogenic substrate was changed from TMB to o-phenylenediamine (OPD), the CuO@Pd-catalyzed oxidation reaction exhibited a characteristic absorption peak at 450 nm. Figure 12 Although both can serve as chromogenic substrates, due to the high toxicity of OPD, we used TMB as the chromogenic substrate for the POD and OXD activities of the enzyme CuO@Pd. To further elucidate the POD and OXD activities of CuO@Pd, we conducted deoxygenation experiments. Figure 13-14 As shown, after introducing N2 into the reaction system to remove dissolved oxygen (regardless of whether H2O2 was added), the absorption peaks of the products were significantly reduced, indicating that O2 is crucial for the catalytic activity of both enzyme-like activities, especially for OXD-like activities. Laccase (LAC) is a polyphenol oxidase containing four copper ions, which can catalyze the oxidation of phenolic compounds under aerobic conditions and is widely used in various fields such as biosensing, environmental remediation, and industrial production.

[0102] Here we used 2,4-DP as a chromogenic substrate to evaluate the LAC-like activity of CuO@Pd ( Figure 7 c). In the presence of CuO@Pd, 2,4-DP can be oxidized to a quinone intermediate, which further reacts with 4-AP to generate a wine-red product with a characteristic absorption peak at 510 nm. Figure 7 As shown in Figure c, the mixture containing only 2,4-DP and 4-AP showed no significant change in absorbance or color; however, after adding CuO@Pd, the solution changed from colorless to wine red, and the absorbance at 510 nm increased significantly, proving that it has LAC-like activity.

[0103] Similar to natural enzymes, the catalytic activity of nanozymes is affected by various factors such as temperature, pH, and storage time. Since enzyme activity is related to specific stereostructures, most natural enzymes exhibit high catalytic activity under suitable pH and temperature conditions. However, under certain extreme conditions, their stereostructures may be disrupted, leading to a sharp decrease in activity. In contrast, metal nanozymes may exhibit stronger stability and activity under extreme conditions. Therefore, we investigated the optimal catalytic activity conditions by controlling the reaction system at different pH and temperature conditions. We systematically examined the catalytic activity of CuO@Pd under different pH (2-9.2) and temperature (20-75℃) conditions (by detecting changes in characteristic substrate absorption peaks). Figure 8 (d-8e). The results showed that the optimal conditions for POD-like and LAC-like activities differed: the optimal conditions for POD-like activity were pH 4.5 and 40℃, outside which its activity rapidly decreased; while the optimal conditions for LAC-like activity were 70℃ and pH 7.5. Notably, under higher temperatures and alkaline conditions, CuO@Pd tended to exhibit predominantly LAC-like activity; while under lower temperatures and acidic conditions, it tended to exhibit POD-like activity. This provides guidance for utilizing its catalytic performance under different conditions.

[0104] To further evaluate its catalytic activity, we investigated the enzymatic reaction kinetics of CuO@Pd. Typical Michaelis-Menten kinetic curves were obtained by varying the substrate concentration (H₂O₂, TMB, or 2,4-DP), corresponding to its POD-like, OXD-like, and LAC-like activities, respectively. Based on the Michaelis-Menten equation, we can obtain the Vt of CuO@Pd. max K m Parameter. K m K represents the substrate concentration at which the enzyme reaction rate reaches half of its maximum value, and this is related to the enzyme's affinity for the substrate. m A lower value indicates a higher affinity of the enzyme for the substrate. V... max The higher the value, the higher the catalytic activity of the enzyme. For example... Figure 8 As shown in f, with a constant H2O2 concentration, the enzymatic reaction rate of POD enzyme gradually reaches a plateau as the TMB concentration increases. The Kc of CuO@Pd was calculated through function fitting. m and V max The values ​​are 0.230 mM and 99.013 × 10⁻⁶. -8 Ms -1 Regarding the POD activity of CuO@Pd, its kinetic parameters are superior to those of similar nanozymes, demonstrating that our developed CuO@Pd exhibits excellent POD activity. We also calculated another set of kinetic parameters for the POD enzyme by continuously increasing the H2O2 concentration while maintaining a constant TMB concentration. m and Vmax The values ​​are 3.5582 mM and 157.567 × 10⁻⁶ mM. -8 Ms -1 ( Figure 8 g). Similarly, we also obtained the kinetic parameters related to OXD and LAC by controlling the concentrations of TMB and 2,4-DP to increase continuously, respectively: K m 0.19776mM, V max 12.005×10 -8 Ms -1 ;K m 0.199mM, V max The value is 92.004 × 10 -8 Ms -1 ( Figure 9 h-9i and Figure 10 ).

[0105] 2.3 Catalytic Mechanism of CuO@Pd Nanocages

[0106] To elucidate the catalytic mechanism of CuO@Pd, we identified the types of reactive oxygen species (ROS) involved in the catalytic process using radical scavenging experiments and electron spin resonance (ESR) spectroscopy. These ROS can be captured and eliminated by radical scavengers. To verify the types of ROS present in the catalytic process, we used three concentrations of isopropanol (IPA), p-benzoquinone (PBQ), and L-histidine (L-HIS) to scavenge hydroxyl radicals (·OH) and superoxide anions (·O2) in the reaction system. - ) and singlet oxygen ( 1 O2)( Figure 15 a). Experiments showed that the absorbance of the system decreased significantly after the addition of p-benzoquinone (·O2- scavenger) and L-histidine (1O2- scavenger), while isopropanol (·OH- scavenger) did not cause significant changes, indicating that the reaction was dominated by ·O2- and 1O2- reactive oxygen species. Figure 15 a). The ESR spectrum further confirms the characteristic signals of ·O2- and 1O2 (a). Figure 15 b-15c) reveals that CuO@Pd can efficiently catalyze the decomposition of H2O2 to produce these two types of ROS.

[0107] Based on the above detection and XPS characterization of the catalytic mechanism of CuO@Pd, and combined with some reported nanozyme catalytic models exhibiting pseudo-peroxidase, oxidase, and laccase activities, we summarize the possible catalytic mechanism of CuO@Pd. Under acidic conditions (pH ~ 4.5) and low temperatures (< 45 °C), CuO@Pd exhibits both POD and OXD activities. Under these conditions, CuO@Pd can bind to H₂O₂ and undergo oxidative decomposition to generate ROS. In the catalytic cycle, Cu… 1 and Cu 2+ The valence state transition is the core mechanism of its catalytic oxidation of substrates, through substrate oxidation and decomposition, electron transfer, and the conversion of O2 to O2. - All of these occur at these copper active sites. During the catalytic cycle, Cu... + and Cu 2+ The interactive redox reaction transfers electrons from the substrate to O2. Specifically, H2O2 first reacts with CuO@Pd on Cu... 2+ Active site binding. Subsequently, H2O2 is oxidized and decomposed to produce O2. - , 1 O2, H + It reacts with H2O, oxidizing TMB to form the blue oxide form of TMB. Simultaneously, Cu... 2+ Reduced to Cu + , forming Cu + Active sites. Since the redox potential of Pd(II) / Pd(0) (+0.915V) is significantly higher than that of Cu(II) / Cu(I) (+0.153V), adjacent Pd(II) acts as an electron acceptor to oxidize Cu(I) and regenerate it into Cu(II), while the generated Pd(0) is re-oxidized into Pd(II) by dissolved oxygen and produces ·O2. - This completes a POD / OXD-like catalytic cycle. XPS results show that two valence states of copper exist in CuO@Pd: Cu Ⅰ Cu Ⅱ The two valence states of palladium: Pd 0 and Pd Ⅱ In this context, it is reasonable to speculate that the electronic redox reaction between Pd and Cu may also participate in the catalytic process of CuO@Pd nanozymes, serving as an active site for the catalytic reaction. Simultaneously, inspired by the mechanisms of POD and OXD activities, we also propose a possible LAC-active catalytic mechanism for CuO@Pd. Under near-neutral pH conditions (approximately pH 7.4) or higher temperature conditions (approximately 70°C), the phenolic substrate (2,4-DP) first reacts with CuO@Pd... Ⅱ The site binds and oxidizes it to a quinone intermediate, which then reacts with 4-AP to generate a wine-red product, while Cu... ⅡThe site accepts an electron and is reduced to Cu. Ⅰ Similarly, Cu Ⅰ Will be Pd Ⅱ Re-oxidized to Cu Ⅱ Pd that has lost electrons 0 When combined with O2, oxygen is reduced to O2. - The catalytic cycle for the enzyme's LAC activity is completed. XPS analysis detected the coexistence of Cu(I) / Cu(II) and Pd(0) / Pd(II) states in the material, confirming that the synergistic electron transfer between the bimetals is the core of the catalysis. In summary, the triple enzyme activity of CuO@Pd depends on substrate specificity regulated by reaction conditions (pH / temperature) and bimetallic valence state switching. Its support-interface synergistic effect provides a new approach for the design of enzyme-mimicking catalysts.

[0108] 2.4 Construction of CuO@Pd nanosensor array

[0109] CuO@Pd porous nanocages with tri-enzyme activity can generate characteristic spectral responses under different conditions by selecting specific substrates (TMB or 2,4-DP). For example, its oxidase-like (OXD) activity can activate dissolved oxygen in water to generate reactive oxygen species (ROS), which in turn oxidizes TMB to form a blue product (characteristic absorbance A at 652 nm). When five types of food phenolic antioxidants and 2,4-DP are present, the difference in molecular reducing power leads to the partial reduction of oxidized TMB (oxTMB), causing the absorbance to decrease to value A. This yields the fingerprint signal ΔA (defined as AA) of the OXD pathway. Figure 16 a). In the peroxidase-like (POD) pathway, the four antioxidants exhibit different scavenging abilities for the active intermediates generated by HO activation, forming a kinetic fingerprint signal ΔA (calculated as AA, where A is the absorbance at the initial moment of substrate mixing and A' is the absorbance after 120 seconds of reaction). Furthermore, under the synergistic effect of laccase-like (LAC) activity and 4-AP, phenolic hydroxyl groups are oxidized to form quinone chromogenic compounds, producing a characteristic absorbance A at 510 nm (…). Figure 16 (b, 17c, and 17d). Based on the above mechanisms, the six phenolic antioxidants act on three enzyme activity pathways, and finally, independent fingerprint signals ΔA, ΔA, and A are extracted to achieve multidimensional characterization of antioxidant capacity.

[0110] A three-dimensional sensor array based on ΔA (OXD-like activity reduction capacity signal), ΔA (POD-like activity inhibition effect signal), and A (LAC-like activity oxidation response signal) was used to accurately identify six phenolic antioxidants through multivariate statistical methods. Deep analysis was performed on 108 sets of fingerprint signals (3 indicators × 6 substances × 6 replicates) obtained from 6 replicate experiments for each substance: Principal component analysis (PCA) revealed the essential structure of the data through dimensionality reduction; linear discriminant analysis (LDA) constructed a classification model to maximize inter-group differences; and hierarchical clustering analysis (HCA) performed unsupervised grouping based on the similarity of the substances' chemical properties.

[0111] Figure 18 a-18c displays fingerprint spectra at concentration gradients of 25 μM, 50 μM, and 100 μM, showing highly specific response patterns for different phenolic compounds. (Radar image channel contribution changes...) Figure 19 d-19f) reveals a key pattern: as the concentration increases, the POD pathway signal ΔA (reflecting the rate of enzymatic reaction within 120 seconds) decreases significantly, indicating that high concentrations of phenolic substances strongly inhibit the H2O2 activation process; conversely, the OXD pathway signal ΔA (representing the ability of phenols to reduce oxTMB) and the LAC pathway signal A (derived from the characteristic absorption of quinone chromogenic products) both increase positively with concentration, intuitively demonstrating the concentration dependence of phenolic hydroxyl content on oxidation sensitivity.

[0112] Statistical analysis further validated the reliability of the sensing system: PCA score plot ( Figure 20 (g, 21k, 22o) shows that parallel samples of the same substance cluster into tight clusters, and different substances are completely separated in the PC1 / PC2 projection space (discrimination 100%), and the sample dispersion increases with increasing concentration; LDA model ( Figure 20 h, 21l, 22p) achieve 100% accuracy in classification, with each group of samples distributed in an independent decision region; HCA dendrogram ( Figure 20 Based on three main characteristics—reducing power, free radical scavenging efficiency, and phenolic hydroxyl oxidation activity—the substances are divided into distinct clusters.

[0113] The CuO@Pd sensor outperforms traditional detection methods, and its multi-component detection capability is verified through experiments with a three-component system: under a fixed total concentration of 50 μM, fingerprint spectra of 2,4-DP, TBHQ, and BHA (including single components, binary mixtures, and ternary mixtures) in any proportion were obtained with significantly distinguishable fingerprint spectra. Figure 23 Of particular importance, the ternary mixture exhibits a unique and stable signal combination (s). Figure 23 (t), proving that the sensor can accurately analyze coexisting antioxidant components in complex matrices through multidimensional signal decoupling technology.

[0114] Figure 24-26 The system demonstrates the quantitative identification capability of CuO@Pd sensor array for phenolic antioxidants. (Radar chart) Figure 27 This shows the different responses of each channel to different concentrations of a single phenolic antioxidant. Principal component analysis (PCA) score plot ( Figure 24 (a, 24d, 24g, 24j, 24m, 24p) clearly demonstrates the separation characteristics of six different concentrations of phenolic antioxidants at concentration gradients (1-100 μM): taking 2,4-DP as an example ( Figure 24 a) The 50 μM sample clusters are tightly clustered in the characteristic space formed by PC1 (53% of variance explained) and PC2 (cluster center coordinates PC1 = 0.4, PC2 = 0.01), with no overlap between samples of different concentrations; parallel samples of all substances form independent clusters (intergroup interval > 1.36 units), achieving 100% discrimination. Standard curve ( Figure 25 b, 25e, 25h, 25k, 25n, 25q) reveal a key quantitative law: PC1 (principal component comprehensive variable) shows a strong linear correlation with antioxidant concentration. For example, the quantitative model for 2,4-DP is Y = 0.056X - 1.733. Figure 25 (b) A slope of 0.056 indicates that for every 1 μM increase in concentration, the overall response value increases by 0.056 AU, and the coefficient of determination R0 2 >0.98 confirms the model's reliability. The thermodynamic response mode is visually represented by a red-blue gradient. Figure 26 c, 26f, 26i, 26l, 26o, 26r): Color scales from 1.71 to 0.01 represent signal enhancement and suppression effects, respectively. Taking 2,4-DP as an example... Figure 26 c) As concentration increases, the signal intensity of the LAC channel rises from 0.01 to 1.71, while that of the POD channel decreases from 1.37 to 0.68, and the OXD channel remains around 0.98. These differences in response form a unique "fingerprint-like" concentration-dependent trend. Comprehensive analysis shows that this sensor array achieves high-precision identification of phenolic antioxidants and simultaneous analysis of complex matrices through a three-pronged approach of PCA spatial separation, linear quantitative model, and thermographic characteristic spectrum.

[0115] 2.5 Selectivity and anti-interference analysis of CuO@Pd nanosensor array

[0116] In addition to conventional performance evaluation, the assessment of sensor performance also considers the importance of selectivity and anti-interference capabilities. Therefore, we selected common metal ions, amino acids, sugars, and urea as interfering substances to analyze selectivity. For example... Figure 28 The fingerprint spectrum in a is shown. The effect of the interfering substance (10 μM) on the three-channel signal of the sensor is almost negligible. Principal component analysis (PCA) score plot ( Figure 28b) and Hierarchical Cluster Analysis (HCA) diagram ( Figure 28 c) indicates that the six phenolic substances and interfering substances were clustered into seven distinct clusters, completely separated from each other without mutual interference. Furthermore, the ability to distinguish phenolic substances in the presence of interfering substances was also tested. The results show that the fingerprint spectra of the six antioxidants still exhibit significant distinguishability. Figure 29 a), and the principal component analysis (PCA) score plot ( Figure 29 b) and Hierarchical Cluster Analysis (HCA) diagram ( Figure 29 c) This confirmed that six phenolic substances could be accurately identified. These results demonstrate that the sensor array possesses excellent specificity and anti-interference capabilities.

[0117] 2.6 Actual Sample Testing

[0118] The constructed sensor array was also used for the detection of real samples. Butter, sunflower oil, and mayonnaise were used as real samples for analysis. Through spiking experiments, 100 μM of 2,4-DP, BPA, BHT, BHA, TBHQ, and PG were added to samples diluted 100-fold in three different matrices. Each phenolic substance exhibited a unique response pattern. Principal component analysis score plots and hierarchical clustering analysis plots showed that these six phenolic substances were successfully distributed in different regions in the three different matrices without any interference or misclassification. Figure 30 a-30e).

[0119] To further evaluate the practical applications of the sensor array, we differentiated three real-world samples. For example... Figure 31 As shown in Figure a, each sample exhibits a unique response pattern. The principal component analysis score plot shows that the three samples are distributed in different regions without overlap, indicating that this method can be used to distinguish the phenolic content in food samples. The violin plot clearly demonstrates the significant differences between the three samples with different phenolic content. Figure 31 a). Furthermore, the hierarchical clustering analysis (HCA) plot further demonstrates that the three samples can be accurately classified based on the content of phenolic substances. Figure 31 c) The results of actual sample measurements show that the sensor array is feasible for the analysis of distinguishing and detecting phenolic substances in real food samples.

[0120] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications may still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions may be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for preparing CuO@Pd hollow porous nanocages, characterized in that, Includes the following steps: (1) Anhydrous copper sulfate, sodium citrate, sodium hydroxide, ascorbic acid and water are mixed and stirred at 20-30℃ to prepare a mixed solution containing Cu2O nanocubes. (2) Add ascorbic acid and sodium tetrachloropalladium to the mixed solution obtained in step (1), and stir the reaction at 20-30℃. Centrifuge, wash and dry the resulting reaction solution to obtain CuO@Pd hollow porous nanocage.

2. The method for preparing CuO@Pd hollow porous nanocages according to claim 1, characterized in that, In step (1), the mass ratio of anhydrous copper sulfate to sodium citrate is 110-140:49, preferably 120-130:49, and more preferably 125:49; the alkaline solution is a sodium hydroxide solution or a potassium hydroxide solution, preferably a sodium hydroxide solution; the molar ratio of anhydrous copper sulfate to ascorbic acid is 1:0.5-1.5, preferably 1:0.8-1.2, and more preferably 1:1.0; the size of the Cu2O nanocubes is 195-205 nm, preferably 200 nm.

3. The method for preparing CuO@Pd hollow porous nanocages according to claim 1, characterized in that, In step (2), the mass ratio of anhydrous copper sulfate to ascorbic acid is 10-25:1, preferably 15-20:1, and more preferably 18.75:1; The molar ratio of anhydrous copper sulfate to sodium tetrachloropalladium is 1:0.5-1.5, preferably 1:0.8-1.2, and more preferably 1:0.93; The size of the CuO@Pd hollow porous nanocage is 275-285 nm, preferably 277 nm.

4. The CuO@Pd hollow porous nanocage obtained by the preparation method according to any one of claims 1-3.

5. A method for constructing a three-channel sensor array using the CuO@Pd hollow porous nanocage as described in claim 1, characterized in that, The three-channel sensor array includes a POD active channel, an OXD active channel, and an LAC active channel, and includes the following steps: (1) POD active channel: 3,3′,5,5′-tetramethylbenzidine, H2O2 solution, CuO@Pd hollow porous nanocage and target phenolic compound were added to HAc-NaAc buffer to carry out catalytic reaction. The absorbance change data of the reaction system at 652nm was collected using a UV-Vis spectrophotometer to obtain the POD active channel. (2) OXD active channel: 3,3′,5,5′-tetramethylbenzidine and CuO@Pd hollow porous nanocages were added to HAc-NaAc buffer to carry out catalytic reaction, and the change in absorbance of the reaction system before and after the addition of the target phenolic compound was collected at 652 nm using a UV-Vis spectrophotometer to obtain the OXD active channel. (3) LAC active channel: 4-antipyrine, CuO@Pd hollow porous nanocage and target phenolic compound were added to MES buffer to carry out catalytic reaction, and absorbance data at 510 nm were collected using a UV-Vis spectrophotometer to obtain LAC active channel; The target phenolic compounds are 2,4-dichlorophenol, bisphenol A, butylated hydroxytoluene, butylated hydroxyanisole, tert-butylhydroquinone, and propyl gallate.

6. According to the method of claim 5, in step (1), the pH value of the HAc-NaAc buffer is 3.5-4.5, preferably 4.0; the mass ratio of 3,3′,5,5′-tetramethylbenzidine to CuO@Pd hollow porous nanocage is 45-65:1, preferably 50-60:1, more preferably 54:1; the temperature of the catalytic reaction is 20-30℃, and the reaction time is 110-130s, preferably 120s.

7. According to the method of claim 5, in step (2), the pH value of the HAc-NaAc buffer is 3.5-4.5, preferably 4.0; the mass ratio of 3,3′,5,5′-tetramethylbenzidine to CuO@Pd hollow porous nanocage is 45-65:1, preferably 50-60:1, more preferably 54:1; the temperature of the catalytic reaction is 20-30℃, and the reaction time is 8-12 min, preferably 10 min.

8. According to the method of claim 5, in step (3), the pH value of the MES buffer is 7.0-8.0, preferably 7.4; the mass ratio of 4-antipyrine to CuO@Pd hollow porous nanocage is 5-25:1, preferably 10-20:1, more preferably 15:1; the temperature of the catalytic reaction is 45-55℃, preferably 50℃, and the reaction time is 4-6 min, preferably 5 min.

9. A three-channel sensor array constructed using the method described in any one of claims 5-8.

10. The application of the three-channel sensor array as described in claim 5 in the detection of target phenolic compounds, wherein, The target phenolic compounds are 2,4-dichlorophenol, bisphenol A, butylated hydroxytoluene, butylated hydroxyanisole, tert-butylhydroquinone, and propyl gallate.

Images