984 results about "Analytic chemistry" patented technology

The invention belongs to the technical field of SERS (Surface Enhanced Raman Scattering) detection, and particularly relates to a preparation method and application of an Ag-coated NiFe2O4 composite SERS substrate. The preparation method comprises the following steps: firstly, preparing Ag nanoparticles which are uniformly distributed and have the same size through a sodium citrate reduction method; secondly, a nanometer flower type NiFe2O4 material is prepared through a hydrothermal method and a calcination method; and finally, the novel SERS substrate Ag-coated NiFe2O4 is prepared through a physical stirring method. The novel SERS substrate made of the Ag nano particles and the nano-flower type NiFe2O4 material is constructed, and compared with a conventional SERS substrate made of independent Ag nano particles, the SERS substrate can detect stronger intrinsic Raman signals of probe molecules. As the SERS substrate needs to be compounded with a nano-flower type NiFe2O4 material during preparation, a charge transfer phenomenon can occur at an interface where the SERS substrate is in contact with probe molecules, so that intrinsic Raman signals of the probe molecules can be enhanced, and the SERS substrate can be better used for detecting and analyzing chemical substances.

The invention discloses an unknown pollutant non-target identification method and system based on mass spectrum and a generative model, and is applied to the technical field of environmental monitoring and analytical chemistry. The method comprises the following steps: collecting mass spectrum data of a water body sample to be detected; preprocessing the original mass spectrum data, and outputting standardized features; inputting the standardized features into a pre-trained generative model to generate a plurality of candidate molecular formulas; using chemical and physical constraints to eliminate candidate molecular formulas which do not conform to rules; executing a rule-driven algorithm to obtain candidate pollutant molecular structures; carrying out comprehensive scoring and sorting on candidate pollutant molecular structures through chemical prior and environmental prior; and semi-quantitative or relatively quantitative concentration determination is carried out. According to the method, a rule-driven expert system and a data-driven generation model are combined, unknown pollutants which do not exist in a standard library can be effectively recognized and analyzed, and full-process automatic processing from original mass spectrum data to pollutant structures and concentrations is achieved.

The invention discloses a metabonomics data batch correction method based on multi-kernel learning, and belongs to the cross technical field of bioinformatics and analytical chemistry. According to the method, the multi-kernel learning technology is utilized, the advantages of different kernel functions are fused in a self-adaptive mode, a model conforming to data reality is constructed, complex drift characteristics of metabolite signals are accurately captured, and efficient and accurate normalization processing of metabonomics data is achieved. Compared with traditional data standardization methods such as SVR and LOESS, the method has the advantages that the performance is excellent in the aspect of reducing the metabolite peak intensity variability, and the data stability is remarkably improved. In the subsequent multivariate statistical analysis, the classification accuracy is greatly improved, the comparability among different batches of data is also remarkably enhanced, reliable data support can be provided for discovery of disease biomarkers, and the method plays a key role in large-scale metabonomics research.

The invention belongs to the technical field of SERS (Surface Enhanced Raman Scattering) detection, and particularly relates to an Ag-MoO2 composite SERS substrate as well as a preparation method and application thereof. The preparation method comprises the following steps: firstly, preparing Ag nanoparticles which are uniformly distributed and have the same size by a sodium citrate reduction method; secondly, a MoO2 material is prepared through a hydrothermal method; and finally, the novel SERS substrate Ag-MoO2 is prepared through a physical stirring method. According to the invention, the novel SERS substrate made of Ag nanoparticles and MoO2 materials is constructed, which is different from the conventional SERS substrate made of independent Ag nanoparticles, and can detect stronger intrinsic Raman signals of probe molecules. As the SERS substrate needs to be compounded with a MoO2 material during preparation, a charge transfer phenomenon can occur at an interface where the SERS substrate is in contact with probe molecules, so that intrinsic Raman signals of the probe molecules can be enhanced, and the SERS substrate can be better used for detecting and analyzing chemical substances.

The invention discloses a multi-component heavy metal spectrum deep learning detection method and system, and belongs to the technical field of analytical chemistry and instrument analysis. According to the method, the UV-Vis spectral difference of multi-component heavy metals is enhanced through a combined chemical probe color development technology, complex nonlinear spectral signals are analyzed in combination with a deep learning model, and the generalization ability of the model is improved through a data enhancement strategy. The system is integrated with a lightweight end-to-end detection platform, is adaptive to low-cost portable equipment, and realizes minute-level multi-component synchronous detection. According to the method, a closed-loop technical path is formed through three core technologies (probe combination, spectrum enhancement and deep learning), the technical bottleneck of a traditional method in a multi-component, small-sample and complex scene is broken through, and an efficient, accurate and low-cost complete solution is provided for heavy metal pollution prevention and control; the method solves the problems of expensive equipment, low detection efficiency and insufficient multi-component analysis capability of a traditional method, and is suitable for scenes of environmental monitoring, sewage treatment and the like.

The invention belongs to the field of analytical chemistry and mathematical modeling, and particularly relates to a method for predicting and identifying whether soy sauce contains yeast extracts, which comprises the following steps: 1) taking different types of soy sauce as modeling samples; 2) carrying out decolorization pretreatment on the modeling sample; (3) carrying out spectrum scanning on the modeling sample by adopting a Raman spectrum technology to obtain original Raman spectrum information; 4) preprocessing the Raman spectrum data obtained in the step 3); 5) sampling for multiple times to establish a sparse logistic regression model, and recording important wave numbers; 6) counting wavenumber importance; 7) selecting an important wave number; 8) using TabPFN to establish a prediction model; (9) predicting and judging whether the yeast extract is added into the soy sauce sample or not by utilizing the established prediction model; compared with the prior art, the method can quickly and accurately identify whether the soy sauce such as light soy sauce and dark soy sauce contains the yeast extract or not, and is simple and quick in identification process, short in analysis time, high in accuracy and high in practicability.

The invention provides a rapid visual D-limonene detection method and application thereof, and belongs to the technical field of analytical chemistry, the method comprises the following steps: uniformly mixing ethanol and water to form a solvent system, sequentially adding template agents Pluronic P123 and Pluronic F127, phloroglucinol, 1, 3, 5-trimethylbenzene and ethylenediamine, and uniformly stirring at room temperature; after the reaction is completed, washing, centrifuging, drying and calcining an obtained sample to obtain DNCzyme; the method comprises the following steps: adding TMB, H2O2 and DNCzyme into an acetic acid-sodium acetate buffer solution HAc-NaAc, finally adding D-limonene, incubating, and carrying out visual detection on the solution. The method for detecting the D-limonene through colorimetric sensing is rapid, simple, convenient, low in cost, high in sensitivity and good in selectivity, and visual detection is achieved by combining a smart phone.

The invention relates to the field of pharmaceutical analytical chemistry, in particular to a method for determining tandospirone and salt intermediates thereof, high performance liquid chromatography is adopted, and chromatographic conditions include that a chromatographic column with octadecylsilane chemically bonded silica as a filler is adopted, and gradient elution is performed by a mobile phase A and a mobile phase B; wherein the mobile phase A consists of a first water phase and acetonitrile; the mobile phase B is composed of a second water phase and acetonitrile; the first water phase is a water solution containing monopotassium phosphate and sodium hexanesulfonate, and the pH value of the first water phase is 3.0-3.8; the second water phase is an aqueous solution containing monopotassium phosphate and sodium hexanesulfonate, and the pH value of the second water phase is 1.8-2.6. The testing method disclosed by the invention has good specificity, accuracy and repeatability, and can be used for monitoring the quality of the tandospirone raw material medicine.

The invention discloses a method for determining the content of total carbon, inorganic carbon and organic carbon in titanium tetrachloride, and belongs to the technical field of analytical chemistry. The determination method comprises the following steps: under inert atmosphere protection and a low-temperature environment, adding a titanium tetrachloride sample into an inorganic acid solution, fully hydrolyzing, and fixing the volume to obtain hydrolysate; analyzing the concentration of total carbon and inorganic carbon in the hydrolysate by using a TOC (Total Organic Carbon) analyzer; and calculating the contents of total carbon, inorganic carbon and organic carbon in the titanium tetrachloride sample according to the concentrations of total carbon and inorganic carbon in the hydrolysate. According to the method, inorganic carbon and total carbon in the hydrolysate can be directly measured, the content of organic carbon is calculated through a difference value method, and accurate typing of carbon forms is achieved. The method is simple to operate, short in detection period, high in efficiency and lower in cost. The method can effectively solve the problem that blind areas exist in impurity traceability and accurate control due to the fact that detection data of total carbon, inorganic carbon and organic carbon cannot be accurately separated through an existing method for measuring the carbon-containing compounds in titanium tetrachloride.

The invention provides a method for visually and rapidly detecting carbosulfan pesticide by using medium-entropy nano-enzyme and application of the medium-entropy nano-enzyme, and belongs to the technical field of analytical chemistry. On the basis of a metal ligand cross-linking strategy, the medium-entropy nano-enzyme FeCeCu MEzymes is synthesized through self-assembly of the chelating ability of dopamine phenolic hydroxyl and multi-metal ions of Fe < 3 + >, Ce < 3 + > and Cu < 2 + >, and the medium-entropy nano-enzyme FeCeCu MEzymes sensor is designed to be combined with a smart phone to realize rapid visual detection of carbosulfan; the rapid and visual carbosulfan detection method provided by the invention has the advantages of rapidness, high sensitivity, good selectivity, visual detection result and the like, and is simple and easy to operate and relatively low in cost.

The invention belongs to the field of environmental analytical chemistry, and provides a method for preparing micro / nano plastic based on stable isotope labeling and application of the micro / nano plastic. Specifically, an initiator, a pH buffer solution, ultrapure water, an emulsifier and a deuterated styrene monomer are mixed and emulsified through an emulsion polymerization method, a polymerization reaction is performed after emulsification, and then the deuterated polystyrene microspheres are obtained through cleaning and drying. According to the method, high sensitivity, high accuracy and safety of deuterium labeling are utilized, and a new research thought is provided for deeply researching the migration and transformation rule of the micro / nano plastic in the environment and long-term influence of the micro / nano plastic on organisms. The method is expected to promote the wide application of a hydrogen stable isotope labeling quantitative technology in the field of environmental science, and provides a scientific basis for evaluating the influence of the micro / nano plastic on the ecological environment and human health.

The invention relates to the technical field of analytical chemistry, and particularly discloses a double-signal ratio type up-conversion luminescent probe, a preparation method thereof and application of the double-signal ratio type up-conversion luminescent probe in oxalate detection, and the double-signal ratio type up-conversion luminescent probe comprises up-conversion nanoparticles UCNPs and an iron-chromium cyanine R compound. The upconversion nanoparticles UCNPs are combined with the iron-chromium cyanine R compound to construct a double-emission-peak regulation and control system, when the system is used for oxalate detection, oxalate can be chelated with Fe < 3 + > in the iron-chromium cyanine R compound, blue shift of an induced absorption spectrum is achieved, green and red emission peaks of the UCNPs are synchronously regulated and controlled, and the detection sensitivity is high. The fluorescent-colorimetric bimodal high-sensitivity detection of the oxalate is realized.

The invention discloses a qualitative and quantitative analysis method for autonomously identifying halogenated organic matters in a non-targeted manner, and belongs to the technical field of environmental analytical chemistry and water quality monitoring. The qualitative and quantitative analysis method of the halogenated organic matter comprises the following steps: adding an oxidizing agent or a disinfectant into an original water sample for complete oxidation or disinfection to obtain a water sample to be detected; detecting the water sample to be detected by using ultra-high performance liquid chromatography (UPLC)-Orbitrap mass spectrometry (MS), and detecting the original water sample which is not oxidized or disinfected at the same time to obtain two groups of liquid mass data; performing automatic data processing and contrastive analysis on the two groups of liquid quality data by using Compressed Discovery software, and identifying to obtain a newly generated halogenated organic matter; and establishing a calibration curve by using a total ion chromatogram and an external standard method, and carrying out quantitative analysis on the identified halogenated organic matter. According to the method, the purposes of efficient screening and accurate quantification of the non-targeted halogenated organic matter in the complex water body matrix are achieved, accurate quantification is conducted in combination with an external standard method, and rapid data analysis and result output are achieved.

The invention belongs to the technical field of analytical chemistry detection, and particularly relates to a construction method and application of a tobacco mosaic virus molecular imprinting sensor based on MIL-101 (Fe). The construction method comprises the following steps: by taking a tobacco mosaic virus TMV as a template virus, preparing a molecularly imprinted polymer MIPs with a TMV specific recognition cavity on the surface of MIL-101 (Fe) through a free radical polymerization reaction; the template virus is removed in the preparation process of the molecularly imprinted polymer MIPs, and a TMV specific recognition cavity of the molecularly imprinted polymer MIPs contains MIL-101 (Fe); the molecularly imprinted polymer MIPs is the tobacco mosaic virus molecularly imprinted sensor based on MIL-101 (Fe). Hydrochloric acid is introduced, so that the TMV specific recognition cavity structure of the molecularly imprinted polymer MIPs is cracked to release Fe < 3 + >, then potassium thiocyanate is added, and the Fe < 3 + > and KSCN are subjected to a complexation reaction to generate a red complex. And the complexation reaction of Fe < 3 + > and KSCN is used as a signal probe, the rapid semi-quantitative visual detection of the target virus TMV by naked eyes is realized, and quantitative detection and analysis are carried out through an ultraviolet spectrophotometer.

The invention discloses a pesticide residue quantitative analysis system based on Raman spectrum, and relates to the technical field of analytical chemistry and detection.The pesticide residue quantitative analysis system comprises an acquisition module, a processing module, an analysis module and a regulation and control module, the acquisition module is used for acquiring samples and Raman scattering signals, converting the Raman scattering signals into original spectrum data and transmitting the original spectrum data to the processing module; calibrating the original spectrum data, acquiring calibrated spectrum data, transmitting the calibrated spectrum data to an analysis module, comparing the calibrated spectrum data with a pesticide standard spectrum library, outputting a quantitative analysis result of pesticide residues, transmitting the quantitative analysis result to a regulation and control module, storing the pesticide standard spectrum library and the calibrated spectrum data, and correcting sample detection deviation by using the calibrated spectrum data. And through the regulation and control unit, full-process automatic operation from sample processing to result output is realized, the detection reliability is improved through spectrum compensation and characteristic peak comparison, efficient automation is realized through task scheduling and time sequence synchronization, and hardware fault tolerance, authority management and multi-scene adaptation capabilities are realized.

The invention belongs to the technical field of analytical chemistry and pesticide residue detection, and relates to a phosphate hydrolysis nano-enzyme sensing array-based p-nitrophenol pesticide identification and detection method, which comprises the following steps of: performing five groups of parallel data matrixes on each type of p-nitrophenol pesticide to distinguish single / five types of p-nitrophenol pesticides with different concentrations; establishing a discrimination model of different concentrations / types of pesticides by using the data matrix, and obtaining an HCA map and an LDA score map of the p-nitrophenol pesticides through hierarchical clustering analysis and linear discriminant analysis; after the absorbance value of the sample to be detected is measured, the sample to be detected can be identified and detected through comparison. According to the present invention, by using the inherent dynamic difference existing during the catalytic hydrolysis of different p-nitrophenol pesticides by CeO2, a plurality of reaction time points are selected to measure the absorbance change, the time-resolved sensing array fingerprint is constructed, and the type identification and the concentration quantification of a variety of p-nitrophenol pesticides and the mixture thereof are achieved by combining the pattern identification algorithm, such that the sensitivity is high, and the detection result is accurate. The measurable concentration range is 1-50 mu g / mL.

The invention relates to the technical field of analytical chemistry, and particularly discloses an HPLC (High Performance Liquid Chromatography) detection method for related impurities in a vitamin B6 injection. The invention provides an HPLC detection method for related impurities in vitamin B6 injection. The HPLC detection method comprises the following steps: carrying out separation detection on a to-be-detected sample by adopting a chromatographic column taking octadecylsilane chemically bonded silica as a filler and a mobile phase gradient elution method; the mobile phase A is 0.04% sodium pentane sulfonate solution-methanol with the volume ratio of 95: 5, and the pH value of the 0.04% sodium pentane sulfonate solution is adjusted to 3.0 by adopting phosphoric acid; the mobile phase B is methanol. The HPLC detection method provided by the invention can detect 13 impurities in the vitamin B6 injection at the same time, the detection specificity is high, the sensitivity is high, the separation degree is good, and the quality of the vitamin B6 injection can be effectively controlled when the detection method is applied to production of the vitamin B6 injection.

The invention relates to the technical field of titration detection in analytical chemistry, in particular to a thymol phenolphthalein-TBPE composite indicated cyanide high-precision detection method which comprises the following steps: step 1, after a water sample to be detected is distilled and separated, adjusting the pH value of distillate to a strong alkaline environment required by thymol phenolphthalein color development; 2, adding a composite indicator containing thymol phenolphthalein and tetrabromo phenolphthalein ethyl ester, wherein the mass ratio of the two components in the composite indicator is determined through a color change sensitivity optimization experiment; step 3, titrating with a silver nitrate solution, and judging an end point according to three-order color mutation: the initial state is light yellow, the intermediate state is green, and the end point state is purple red; and 4, adding an auxiliary masking agent before titration, and blocking the reaction between the auxiliary masking agent and silver ions by preferentially complexing interference ions. By optimizing the ratio of the composite indicator and using the masking agent, interference of other substances can be effectively prevented, and accurate detection of cyanide is ensured.

The invention discloses an online floating electrochemical scanning and electrospray ionization mass spectrometry combined device, relates to the technical field of analytical chemistry, and can improve the electrochemical detection efficiency and detection accuracy. According to the device, a three-electrode probe is arranged in a reaction cavity and is used for containing a target solution to be detected; the floating type electrochemical controller comprises a high-voltage module, a power supply module, a floating electrochemical measurement and control circuit and a three-electrode probe, the high-voltage module raises the first potential of the floating ground end of the power supply module into a second potential; the power supply module is used for converting the voltage of the floating battery into a preset voltage and then supplying power to the floating electrochemical measurement and control circuit; the floating electrochemical measurement and control circuit is used for controlling the three-electrode probe to output a continuous high-voltage signal or a continuous current signal, the continuous high-voltage signal or the continuous current signal acts on a target solution to generate an electrochemical reaction and directly generate spray ions, and the three-electrode probe is used for detecting voltage and current in the electrochemical reaction process of the target solution; and detection voltage and detection current are obtained.

The invention discloses a cloud computing analysis system and method based on a high performance liquid chromatograph, and belongs to the technical field of analytical chemistry and information. The system comprises a data acquisition module, a data transmission module, a cloud storage module, a data analysis module, a user interface module and a real-time analysis and feedback module. The data acquisition module is used for acquiring data detected by the high performance liquid chromatograph; the data transmission module is used for determining a protocol adopted by data transmission; the cloud storage module is used for storing the data transmitted to the cloud; the data analysis module is used for training an intelligent clustering analysis model and inputting data for automatic data analysis; the user interface module is used for providing an interface for a user to check an analysis result; and the real-time analysis and feedback module is used for carrying out real-time analysis and judgment on the data. Automatic data analysis is realized by using a machine learning training model, and manual intervention is reduced.

The invention belongs to the field of analytical chemistry, relates to material preparation, and particularly discloses a preparation method of a copper-doped covalent organic framework and application of the copper-doped covalent organic framework in adrenaline colorimetric detection. Firstly, 1H-indazole-4, 7-diamine (Iz) and 1, 3, 5-triformyl phloroglucinol (Tp) are used as monomers to synthesize a novel covalent organic framework (Iz-Tp COF) through a Schiff base reaction, copper ions are introduced into the Iz-Tp COF framework to prepare a novel metal covalent organic framework (Iz-Tp (at) Cu), and then according to the phenomenon that the Iz-Tp (at) Cu can catalyze oxidation color development of epinephrine, the metal covalent organic framework (Iz-Tp (at) Cu can catalyze oxidation color development of epinephrine. According to the present invention, the simple, sensitive and efficient adrenaline colorimetric detection method is established, the test conditions are finally optimized, the standard addition method is combined to accurately determine the adrenaline concentration in the urine, and the good practical application value is provided.

The invention relates to a multi-scale prediction method for the oxidative ablation behavior of a carbon / carbon porous heat-proof material, and belongs to the technical field of aerospace science, in particular to a multi-scale prediction model for the oxidative ablation behavior of the carbon / carbon porous heat-proof material. A chemical reaction standard enthalpy value and reaction activation energy are analyzed based on a gas-solid interface micro-model of a carbon / carbon porous heat-proof material, and then pore scale fluid mechanics calculation is performed in combination with a porous medium model; explaining an evolution mechanism between gas-solid interfaces by using a micro-scale and pore-scale simulation method, and predicting an ablation process surface evolution process; according to the invention, fluid flow, thermal reaction and heterogeneous chemical reaction in the porous medium in the ablation process can be coupled and simulated at the same time; according to the method, the action mechanism of the heterogeneous chemical reaction at the gas-solid interface in the oxidation ablation process of the carbon / carbon porous heat-proof material can be disclosed, and the distance change after ablation and the ablation surface roughness in the ablation process can be predicted more accurately.

The invention relates to the technical field of analytical chemistry and information processing, in particular to a weighted characteristic peak quality accuracy-based forward and reverse mass spectrogram similarity matching method, which is suitable for high-throughput screening of risk substances in food safety detection, and comprises the following steps: acquiring mass spectrogram data to be queried and standard mass spectrogram data in a database; fragment ions with the peak intensity ranked in the first 7 or larger than or equal to 10 in the mass spectrum to be inquired and the standard mass spectrum are selected; judging whether the m / z difference value of fragment ions in the mass spectrum to be queried and the standard mass spectrum is less than or equal to 5ppm or not; calculating a forward matching degree score of the to-be-queried mass spectrum and the standard mass spectrum, and a reverse matching degree score of the standard mass spectrum and the to-be-queried mass spectrum; calculating a mean value according to the forward matching degree score and the reverse matching degree score; the average value is output as the similarity score of the mass spectrum to be queried and the standard mass spectrum, and the possibility that the screening result shows false negative is greatly reduced by considering the quality accuracy of fragment ions.

The invention discloses construction and application of a confinement enhanced photoelectrochemistry-electrochemiluminescence dual-mode biosensor, and relates to the technical field of biosensing and analytical chemistry. The preparation method of the biosensor comprises the following steps: taking a CdS (at) SiO2 (at) NaYF4: Yb / Tm nano composite material as a substrate to obtain a confinement enhanced photoelectrochemistry (PEC) and electrochemiluminescence (ECL) sensing interface; in combination with a DNA wheel nanostructure triggered by target acetamiprid, signal amplification is realized; and synchronous dual-mode quenching detection of PEC and ECL signals is realized by virtue of peroxidase-like catalytic precipitation and wide-spectrum absorption characteristics of the PtPd-CoSnO3 nanocube. The biosensor prepared by the invention has the advantages of high sensitivity, strong reliability, good selectivity and the like, can be applied to accurate detection of acetamiprid in samples such as agricultural products and the like, and has important application value in the aspects of environmental monitoring and food safety control.

The invention provides a sample dissolving method of a nickel-based alloy, and belongs to the technical field of analytical chemistry, and the nickel-based alloy comprises the following components in percentage by mass: 0.15-0.20% of C, 0.15-0.20% of B, 0.15-0.20% of C, and the balance of Fe and inevitable impurities. Comprising the following steps: preliminarily dissolving a sample through concentrated hydrochloric acid and concentrated nitric acid; adding perchloric acid, and preserving heat for 1-2 minutes at the temperature of 100-120 DEG C to obtain a yellow insoluble substance, the ratio of the adding volume of the perchloric acid to the mass of the sample being (110-130) mL: 1g; transferring the liquid and the yellow insoluble substance into a second reaction cup, adding hydrofluoric acid, and keeping the temperature at 50-60 DEG C for 2-4 minutes; and fixing the volume after dissolving. Firstly, concentrated hydrochloric acid and concentrated nitric acid are adopted for dissolution, due to the fact that the content of Cr, Mo and W is high, and detection of Ce, Si and other metals cannot be affected, the adding mode of the concentrated nitric acid and the concentrated hydrochloric acid is limited, then perchloric acid is added, fuming of the perchloric acid is controlled, and the content of the perchloric acid and the content of the concentrated nitric acid which are added in the earlier stage are combined; the method has the advantages that low Cr content due to generation of CrO2Cl2 is avoided while metal carbides are dissolved, undissolved yellow substances are dissolved in combination with hydrofluoric acid, and low Si content due to generation of SiF4 is avoided.

The invention discloses a DNA silver nanocluster and a preparation method and application thereof, and belongs to the technical field of analytical chemistry. The method comprises the following steps: adding a template containing a DNA sequence and an AgNO3 solution into a PBS (Phosphate Buffer Solution), mixing, and carrying out a first dark reaction; then, adding a NaBH4 solution, and carrying out a second light-shielding reaction, so as to obtain the DNA-Ag NCs fluorescent probe; the DNA silver nano-cluster is applied to the determination of the cationic surface active agent; the fluorescence quenching effect is remarkable, the lowest detection limit can reach 2.0 mu M, the selectivity is good, common anionic surfactants, nonionic surfactants, metal ions in sewage and other interferents do not affect detection, and the accuracy and reliability of the method are improved.

The invention belongs to the technical field of analytical chemistry and the field of early screening of Alzheimer's disease, and particularly relates to an array sensor based on zirconium-based MOF nano-enzyme and application of the array sensor to detection of amyloid protein. The zirconium-based MOF nano-enzyme for detecting amyloid protein comprises UiO-66 (at) Pt, UiO-66 (at) Pd and UiO-66 (at) PtPd, and the array sensor based on the zirconium-based MOF nano-enzyme is constructed by sensing units which are respectively added with the UiO-66 (at) Pt, the UiO-66 (at) Pd and the UiO-66 (at) PtPd. According to the amyloid protein detection method based on the zirconium-based MOF nano-enzyme, rapid and sensitive detection of amyloid protein can be realized, the cost is low, the repeatability is good, and a new idea is provided for detection of amyloid protein related diseases.

The present invention relates to the field of analytical chemistry, and discloses a mass spectrum ionization element for macrolide antibiotic detection and a preparation method thereof, the mass spectrum ionization element comprises: a conductive substrate made of stainless steel; the adsorption layer is attached to at least part of the surface of the substrate, the adsorption layer is formed by a boric acid functionalized covalent organic framework, and the boric acid functionalized covalent organic framework is of a polycyclic structure composed of repeated units shown in the formula I in the specification. The mass spectrum ionization element is uniform in coating, high in selectivity on macrolide enriched antibiotics in a complex matrix and high in enrichment capacity, an eluent of the mass spectrum ionization element can be used for detection based on a liquid chromatography method and can also serve as a mass spectrum ion source solid substrate, mass spectrum detection is conducted through electrospray ionization, the detection steps are simple, and the mass spectrum ionization element is suitable for mass spectrum detection. And the detected background noise is low.

The invention belongs to the field of analytical chemistry, and particularly relates to a method and a kit for identifying freshness of apple juice, and the method specifically comprises the following steps: S1, selecting apple juice prepared from known apples with different freshness, and analyzing and detecting the apple juice by using a chromatography-mass spectrometry system to obtain a corresponding fingerprint spectrum; s2, clustering and defining the fingerprints by using K-means clustering analysis and orthogonal partial least squares discriminant analysis based on peak information of the fingerprints corresponding to the apple juices with different freshness in S1 as characteristic variables, and defining the fingerprints as a fresh group or a rotten group to obtain a data set; s3, based on the data set in the S2, constructing an identification model by adopting a supervised machine learning algorithm; s4, to-be-detected unknown apple juice is taken, the fingerprint spectrum of the unknown apple juice is obtained under the same detection conditions in the step S1, and the freshness of the unknown apple juice is identified based on the identification model in the step S3. The method is high in identification accuracy.

The invention provides a method for detecting vitamin B6 related substances in a multivitamin preparation, and belongs to the field of analytical chemistry. According to the method, a high performance liquid chromatograph is adopted, and chromatographic conditions are as follows: an octadecyl silane bonded silica gel chromatographic column is adopted, a mobile phase is a phosphate buffered solution (containing sodium hexanesulfonate)-acetonitrile, and a mobile phase A and a mobile phase B are performed according to a gradient procedure; the flow velocity is 0.8 to 1.2 mL / min; the column temperature is 28-40 DEG C, the detection wavelength is 320-340nm, and the sample size is 20-50mu L. The detection method has the advantages of high sensitivity and good linear relationship, and is suitable for analysis and content determination of vitamin B6 related substances in various vitamin preparations.