Novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance technology and molecular imprinting technology

Abstract

The invention relates to a novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance and a molecular imprinting technology. The sensor is composed of a sample collection and storage unit, a reagent box, a sample pretreatment system, a stirring device, a bubble removing device, a sample flowing module, a molecularly imprinted polymer sensing chip, a quartz crystal microbalance, an Internet of Things system, an integrated circuit board system, a valve pump system, a cooling system, software, a cloud database, a power supply and a sensor shell. The molecularly imprinted polymer sensing chip has the advantages of high selectivity, strong anti-interference capability, no generation of false positive signals, capability of accurately reporting the concentration of a target analyte in a real sample, low detection limit and high specificity to the target analyte, and the molecularly imprinted polymer sensing chip can be immediately regenerated and repeatedly used on line. The sensor perfectly solves the main pain points of the existing on-line sensor: false positive signals appear when no target analyte exists, no signals or weak signals exist when the target analyte exists, the sensitivity is low, the specificity is low, and an electrochemical electrode is prone to poisoning.

Description

Technical Field

[0001] The present invention relates to the field of online water quality analysis instruments, and in particular to a novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance and molecular imprinting technology. Background Art

[0002] Most of the existing online sensors (chemical oxygen demand COD, total phosphorus, total nitrogen, ammonia nitrogen, permanganate index, phosphate, nitrate, nitrite, volatile phenol, cyanide, fluoride, residual chlorine, etc.) and heavy metal online sensors are based on colorimetry and electrochemical methods, which have the advantages of fast response speed, but it is difficult to detect the analytes in real samples (no signal) due to matrix interference, and false positive signals (false alarms) often occur in the absence of analytes in actual samples.

[0003] Colorimetry is used for online monitoring of many metal ions, including Cu, Zn, Cr, Ni, Mn, Fe, Pb, Cd, Ag, Sn, etc. The colorimetric method for online monitoring of metal ions is based on the color change of metal ions. The interaction between the chromophore molecule and the analyte ion. The colorimetric method quantifies the peak intensity of the specific wavelength characteristic of the color change. The advantage is that the reagents do not require special storage costs and the operating cost is low. However, wastewater contains a variety of organic and inorganic substances, many of which may also interact with the chromophore, and the color produced by the interaction between the chromophore and the analyte is similar or overlapped, resulting in false positives or high positives, and some will interfere (inhibit or enhance) the interaction between the chromophore and the analyte, causing the expected color change to change or even disappear (no signal). It is well known that colorimetry has the problems of false positives (false positive signals) and no signals (inability to establish a calibration curve).

[0004] Electrochemical methods are used for some metals, such as sodium and arsenic, and for most anions, including fluoride, nitrate, etc. Electrochemical methods can be based on the potential change caused by ion exchange, redox or stripping voltammetry between the analyte and the electrode sensing layer. In general, they face serious problems with electrode poisoning, which can easily poison and passivate the electrode surface due to ions and other contaminants in real samples. For example, PbS-based electrodes used for Pb(II) monitoring cannot tolerate Ag(I) and Hg(II) ions at all, nor can they tolerate Fe(III) and Cd(II) ions at concentrations exceeding 1 / 10 of Pb(II). Once the electrode is poisoned, it must be tediously polished manually with special strips. The manual polishing technique varies from person to person. Therefore, electrochemical methods have difficulty in overcoming the problem of electrode poisoning caused by contaminants, which can greatly reduce or even eliminate the signal, and there is also the problem of false alarms.

[0005] Chinese patent publication number CN105866448B describes a water quality heavy metal monitoring instrument, including an online sample rejection system, an online sample detection system, and an online colorimetric measurement and control system. In the absence of a target heavy metal analyte, the system is prone to false positive signals, and sometimes reports no signal in the presence of a high concentration of the target heavy metal analyte. Summary of the invention

[0006] In order to solve the defects and problems of existing online sensors based on colorimetry and electrochemical methods in the prior art, a novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance technology and molecular imprinting technology is provided.

[0007] The technical solution adopted by the present invention to solve its technical problems is: a novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance technology and molecular imprinting technology of the present invention is composed of a sample collection and storage unit, a reagent box, a sample pretreatment system, a stirring device, a bubble elimination device, a sample flow module, a molecular imprinting polymer (MIP) sensor chip, a quartz crystal microbalance (QCM), an Internet of Things system, an integrated circuit board system, a valve pump system, a cooling system, software, a cloud database, a power supply and a sensor housing; the sensor can include a single channel for analyzing a single substance, or multiple channels for analyzing multiple substances;

[0008] The overall process includes automated sample collection, storage and pretreatment, sample delivery through a flow control system with a multi-way valve and an injection pump, etc., conductivity detection through an online conductivity meter and preliminary determination of the first automatic dilution ratio of the sample, sample dilution in a pH adjustment pool through a pump valve system, determination of the second automatic dilution ratio of the sample by the sample signal strength of a quartz crystal microbalance, pH value measurement through an online pH meter, delivery of standard samples and anti-interference agents and acid-base regulators through a flow control system with a multi-way valve and an injection pump to automatically adjust the pH value, uniform stirring of samples and reagents through a stirring device, elimination of bubbles through a debubbling device to prevent bubbles from entering the sample detection pool and affecting sample detection, specific capture of analytes in the sample through a molecular imprinting coating, measurement and monitoring of analyte signals in the sample through a quartz crystal microbalance, and data analysis and data report sending using software; issuing commands to the flow control system through the software, storing data in the cloud through encrypted data transmission, and reporting results and alarms through a client data viewer and a mobile device;

[0009] The automated sample collection is completed by a software-controlled liquid delivery pump, and the sample collection volume is controlled; the sample pretreatment consists of a series of steps: conductivity detection, sample dilution, solid phase extraction, pH detection, anti-interference agent addition and pH adjustment; solid phase extraction is used to remove interfering organic matter or to concentrate organic analytes; after pretreatment, the sample is delivered to the flow module;

[0010] The sample delivery is accomplished by a flow control system, including a multi-way valve, a syringe pump, a peristaltic pump, a pipeline, etc.; the bubbles are accomplished by a defoamer and a vacuum pump; the automatic measurement of the sample analyte is accomplished by a quartz crystal microbalance;

[0011] The quartz crystal microbalance is mainly composed of an integrated circuit board system, a flow module for fixing a chip holder and a chip, a sensing quartz chip coated with a highly specific molecular imprinting polymer film coating, a chip holder, and a power supply; the signals generated by the quartz crystal microbalance are automatically recorded, monitored and analyzed by the software; the commands of the flow control system are automatically sent by the software; the generated data is automatically stored in the cloud through encrypted transmission; the results are automatically reported, and alarms are automatically sent through the client data viewer and mobile devices;

[0012] The workflow of the online sensor system includes automated sample collection storage, sample pretreatment, bubble removal, temperature measurement, analyte measurement, regeneration, data analysis, and data reporting;

[0013] The removal of bubbles is accomplished by combining a bubble remover and a vacuum pump to prevent dissolved air and bubbles generated during liquid transfer from entering the detection cell and interfering with sample detection;

[0014] The temperature measurement is completed by a software-controlled thermometer; the automatic measurement of the sample analyte is completed by a quartz crystal microbalance. After the sample analyte is measured, two regeneration reagents are transported through a pump valve to flow wash online in sequence for a certain period of time to regenerate the sensor chip;

[0015] The sample pretreatment process includes automatic conductivity measurement to determine the dilution ratio, automatic dilution according to the measured conductivity, automatic filtration, automatic solid phase extraction, automatic pH measurement, automatic addition of acid-base regulator based on pH meter to adjust pH value, automatic addition of standard and automatic addition of anti-interference reagent; the first dilution ratio of the sample is determined by measuring the conductivity by a conductivity meter; the second dilution ratio of the sample is determined by the signal strength of a quartz crystal microbalance; when the conductivity of the sample is high, the dilution factor can be high, otherwise, the dilution factor is low; after the conductivity measurement, deionized water is added to the sample under sufficient stirring to obtain the dilution ratio; The collected samples are automatically diluted; before entering the conductivity cell and pH cell, the samples are automatically filtered through the filter connected to the pipeline entry end; the particles are removed by filtration; the solid phase extraction is automatically completed by the solid phase extractor (SPE) driven by the vacuum pressure generated by the pump; the conductivity is measured by an online conductivity meter with an automatic timed calibration function; the pH value is automatically measured by an online pH meter with an automatic timed calibration function; the pH value adjustment is completed by adding a certain volume of acid and / or base to the sample through a pump valve under the pH meter; the standard and anti-interference reagents are automatically added to the sample using a multi-way valve and injection pump controlled by the software;

[0016] The automated online sensor system has three compartments: compartment 1, compartment 2 and compartment 3; compartment 1 mainly includes electronic systems, control systems, power devices, cooling systems, Internet of Things systems, and computers; compartment 2 has conductivity meters, pH meters, QCMs, flow modules, pumps, valves, defoamers, solid phase extractors, etc.; compartment 3 is for wet processing, where filters, sample bottles, reagent bottles, deionized water bottles, and waste water bottles are located;

[0017] The interactions between the compartments of the automated online sensor system and the interactions between the components in each compartment are as follows: in compartment 1, the computer controls the QCM electronic equipment, the automated control system and the Internet of Things system; the power supply unit supplies power to the QCM electronic system and the automated control system; the cooling system cools the QCM electronic system, the computer and the automated control system; in compartment 2, the pump is connected to the dilution, solid phase extractor, reagent addition, standard addition, flow module and valve; the conductivity meter is connected to the diluter, and the diluter is further connected to the filter; the filter is connected to the solid phase extractor, and the solid phase extractor is connected to the pH meter; the pH meter is connected to the reagent addition, and is further connected to the standard addition; after the pH measurement, the reagent (acid, base) is added by the pump to adjust the pH value to the designed value; before the sample analyte is measured, the standard and anti-interference reagent are added to the sample and then its pH value is adjusted and fully stirred; then, the sample is removed from the residual bubbles by the debubbler, and then flows into the flow module connected to the QCM.

[0018] Typical operation of an online sensor: a certain volume of sample is automatically drawn from a designated sampling point into a sample collection bottle by a pump; the conductivity of the sample is measured and the result is used to determine the first dilution ratio; this ratio is a balance between low background, detection limit and regulatory lower limit; the sample is automatically diluted to a certain ratio under sufficient stirring according to the conductivity; the diluted sample is then filtered and subjected to solid phase extraction, and then an anti-interference agent is introduced by a pump valve and pH measurement and pH adjustment are performed; a certain volume of internal standard and anti-interference agent are added to the pretreated sample and stirred thoroughly, and the sample is degassed by a defoamer and flows into the QCM flow module connected to the QCM for signal measurement and recording; the second dilution ratio of the sample is determined by the strength of the QCM signal; the QCM flow module contains a quartz crystal chip with a thin layer of highly specific molecularly imprinted polymer film on it to capture the target analyte; after the measurement, the quartz crystal chip is regenerated by two regeneration solutions flowing online in sequence; after regeneration, deionized water is introduced into the flow module to establish a baseline.

[0019] 10-100 ml of sample is automatically drawn from a designated sampling point into a sample collection bottle by a pump; filtered online; the conductivity of the sample is measured and the result is used to determine the dilution ratio; this ratio is a balance between low background, detection limit and regulatory lower limit; the sample is automatically diluted to a certain ratio under sufficient stirring according to the conductivity; when the sample conductivity is high, the dilution factor can be higher, otherwise, the dilution factor is lower; if the conductivity is as low as 300 μS / cm, no dilution is required; if the conductivity is higher than 300 μS / cm, it is diluted to within 300 μS / cm according to the dilution factor; then, solid phase extraction is performed, a certain volume (30-300 μl) of internal standard and anti-interference agent is added, stirred thoroughly, and then pH measurement and pH adjustment are performed; stirred thoroughly, the sample is then degassed through a debubbler and flows into the QCM flow module connected to the QCM for analysis; signal measurement and recording; the QCM measures the sample analyte (e.g. Pb 2 + ions), the baseline should technically be a flat value determined by the software; the analysis time is set to 5-10 minutes; the QCM flow module contains a quartz crystal chip coated with a highly specific molecular imprinted polymer film layer for capturing target analytes; after the measurement, the quartz crystal chip is regenerated by the online flow of regeneration solution; the regeneration time is 5-10 minutes; after regeneration, deionized water is introduced into the flow module for baseline establishment, which usually takes 5-15 minutes.

[0020] Synthesis of molecular imprinting polymer: The polymerization mixture for synthesizing molecular imprinting polymer consists of 20-50 μL of free radical initiator (e.g., azobisisobutyronitrile), 200-500 μL of monomer (e.g., methacrylic acid), and 200-800 μL of crosslinker (e.g., ethylene glycol dimethacrylate); 1-5 mL of solvent (e.g., methanol or ethanol) is used as the solvent system; 10-60 μL of a certain concentration of template solution (e.g., 1% lead nitrate) is added to the above mixture as the target template; the mixture is then degassed with nitrogen for 5 to 10 minutes to remove any dissolved oxygen present; after degassing, the mixture is stirred and heated at a certain temperature (e.g., 60-80°C) for polymerization. ; a molecular imprinting polymer is synthesized by polymerization reaction; it is then immersed in a solution of a template eluent (e.g., 0.01-0.1% nitric acid) for a certain time (e.g., 3-8 hours) to remove the template (e.g., lead nitrate) used as a template from the molecular imprinting polymer; this allows the formation of complementary cavities on the molecular imprinting polymer, which are capable of selectively recognizing template ions (e.g., lead ions) or molecules used as templates during the synthesis process; the molecular imprinting polymer is then obtained by vacuum filtration or centrifugation and dried for 24-48 hours; finally, the molecular imprinting polymer is ground into fine powder using a mortar and pestle; a certain amount (e.g., 0.2-0.5 g) of light yellow molecular imprinting polymer (MIP) powder is obtained.

[0021] The QCM chip is prepared as follows: first, the bare QCM chip is cleaned with Piranha solution; then, 0.1-0.5 mg of the molecular imprinting polymer powder in statement 4 is added in the form of fine powder to 1-10 mL of methanol or ethanol; the powder is dispersed by shaking the solution; then, 0.1-0.5 μL of the solution is evenly coated on the QCM chip and dried in an oven at 60-100° C. for 1-2 hours before being used for analysis.

[0022] The QCM is a quartz crystal microbalance with dissipation (QCM-D), on which a 10MHz QCM quartz crystal chip can be used; together with other components and devices, programming software can be used to build an automatic real-time online single-channel sensor prototype based on a quartz crystal microbalance and molecular imprinting polymer for water quality and safety monitoring.

[0023] After the online sensor prototype is built, it can be self-calibrated every day, and the standard addition method can effectively offset the matrix effect - the matrix material usually enhances or suppresses the signal. The calibration steps are carried out in order: QCM establishes the baseline with deionized water flowing into the detection cell, performs standard sample one calibration, regenerates the sensing quartz crystal MIP chip, establishes the baseline again with deionized water, performs standard sample two calibration, regenerates the MIP chip, baseline, performs standard sample three calibration and regenerates the MIP chip (calibration is completed); Typical data points of the constructed online sensor prototype are obtained by the following steps: baseline equilibration with deionized water (5-10 minutes), standard or sample measurement (5-10 minutes) and MIP chip regeneration (5-10 minutes);

[0024] The online sensor prototype obtained satisfactory results on laboratory simulated samples (tap water and wastewater containing lead standards); compared with the results of ICP / MS verification, the RSD was within 5% and the accuracy was within 100±5%; Pb calibration data for tap water samples on the online sensor prototype were also obtained; 0, 1 and 2ppm Pb(II) standards were added for calibration; the calibration curve was very linear, with R2 equal to 0.9854 close to 1; the calculated Pb(II) concentration in the tap water sample was -2.38ppb (reported as "not detected"); the test results were compared with the ICP / MS results (0ppb), and its accuracy was 99.76%; in this example, the online sensor prototype did not report an erroneous signal (or false positive signal);

[0025] The test results of the online sensor prototype on the sample spiked with 1ppm Pb(II) - 2000 times diluted palm oil mill wastewater showed that the 2000 times diluted palm oil mill wastewater sample spiked with 1ppm Pb(II) had a measured Pb(II) concentration of 0.98ppm and 0.98ppm (double measurement), with an average of 0.98ppm, an accuracy of 98.0%, and an RSD of 0%; the two sets of data obtained proved that the online sensor prototype did not have a "no signal" problem in the actual sample, but could detect Pb(II) well, with an accuracy range of 95–105% and an RSD range of 0–5% in the actual sample with 1ppm Pb(II) added. The ICP-AES test result was 1.0ppm Pb.

[0026] The present invention is a novel online single-channel and multi-channel water quality and safety detection instrument that combines quartz crystal resonance technology and molecular imprinting technology. It is different from traditional online water quality monitoring instruments using colorimetry, new online water quality monitoring instruments using electrochemical or fluorescence methods, and also different from conventional laboratory instruments - gas chromatography-mass spectrometer, high-performance liquid chromatography-mass spectrometer, spectrophotometer, atomic absorption spectrometer, induced coupled plasma mass spectrometer, induced coupled plasma atomic emission spectrometer, etc. The sensor solves several major pain points of existing online sensors based on colorimetry and electrochemical methods: false positive signals when there is no target analyte; low signal or no signal when the target analyte is present; low sensitivity (ppm level); low specificity; electrochemical electrode poisoning. For the first time, QCM technology and MIP technology are integrated, and the MIP technology accurately captures the analyte to be measured, and the QCM technology detects the signal, creating a brand-new instrument. This new technology successfully avoids false positive signals when there is no target analyte, low signal or no signal when the target analyte is present, and electrode poisoning (the chip can be used for a long time). This new technology has high specificity and low detection limit (ppb to sub-ppb level). It is fully automated, including sample pretreatment (filtration, conductivity measurement, first dilution, solid phase extraction (eliminating organic contamination interference or concentrating the organic matter to be tested), standard sample addition (offsetting matrix effect), anti-interference agent addition, uniform mixing, pH value measurement, pH value adjustment), bubble elimination (defoamer, vacuum pump-bubbles interfere greatly with detection), sample detection, second automatic dilution (when necessary), immediate online chip regeneration (long-term use), pipeline and container cleaning (no cross contamination), daily automatic calibration (offsetting baseline drift), automatic measurement, data reporting, real-time data transmission, etc. The present invention can also use the same MIP coating on the same chip to perform species analysis of different forms of the same element, such as the distinction of different forms of metal ions, including divalent iron and trivalent iron, trivalent arsenic and pentavalent arsenic, trivalent chromium and hexavalent chromium, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The following is a further description of a novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance technology and molecular imprinting technology of the present invention in conjunction with the accompanying drawings and specific embodiments.

[0028] Figure 1 It is the overall flow chart of the automated online sensor system of the present invention.

[0029] Figure 2 It is a flow chart of the workflow of the automated online sensor system of the present invention.

[0030] Figure 3 This is the automated sample pre-processing process of the automated online sensor system of the present invention.

[0031] Figure 4These are the three compartments of the automated online sensor system of the present invention.

[0032] Figure 5 is an illustrative overall diagram of the automated in-line sensor system of the present invention, showing the interactions between compartments and the interactions between components in each compartment.

[0033] Figure 6 It is an automatic real-time online single-channel sensor prototype that combines quartz crystal resonance technology and molecular imprinting technology for water quality and safety monitoring controlled by programming software.

[0034] Figure 7 is the daily calibration procedure for the online sensor prototype built in Example 3.

[0035] Figure 8 are typical data points from an in-line sensor prototype that has been built.

[0036] Fig. 9 The Pb on the online sensor prototype was calibrated using tap water samples (M1 and M2 are two anti-interference agents purchased from MIPS Innovation Pte Ltd).

[0037] Fig.10 This is the inhibition mechanism and analysis results of KCl inhibiting Hg detection of Pb.

[0038] Fig.11 Shown are the Fe concentrations detected in the presence of cations.

[0039] Fig.12 Shows the Fe concentration detected in the presence of anions.

[0040] Fig.13 Shown are the Fe concentrations detected in the presence of surfactant.

[0041] Fig.14 Shown are the Fe concentrations detected in the presence of solvent.

[0042] Fig.15 Shown is the Fe concentration detected in the presence of dissolved organic matter.

[0043] Fig.16 Shown are the Fe concentrations detected in the presence of insoluble particles.

[0044] Fig.17 Shows the Fe concentration detected in the presence of dissolved particles.

[0045] Fig.18 The real-time analysis graph shows the frequency change over time while performing 2 cycles of a 5-point calibration.

[0046] Figure 19 (1) Concentration of prepared Fe solution verified by ICP-MS with an accuracy of over 90%. Figure 19 (2) Calibration curve obtained from QCM system with R2 value of 0.99.

[0047] Fig. 20 The results of 1080 cycles of Fe ion analysis by Fe(III) sensor. The deviation between the results obtained by Fe sensor and those obtained by ICP-MS is within ±30%.

[0048] Fig.21 The results obtained by the Fe(III) sensor after 200 cycles of analysis of Fe ions. The results obtained by the Fe sensor and the results obtained by ICP-MS are within ±30%.

[0049] Fig. 22 The results of 90 cycles of Fe ion analysis by the Fe(III) sensor. The deviation between the results obtained by the Fe sensor and the results obtained by ICP-MS is within ±10%.

[0050] Fig.23 Detection of speciation differentiation protocol for Cr(III) and Cr(VI).

[0051] Fig.24 Calibration curves and detection results of Cr(III) and Cr(VI). DETAILED DESCRIPTION

[0052] The present invention relates to an automatic online sensor for real-time detection, monitoring and quantitative analysis of substances of interest in water. The sensor is composed of a sample collection unit, a sample pretreatment system, a defoaming unit, a sample flow module, a molecular imprinting polymer-based sensor chip, a quartz crystal microbalance, a regeneration unit, an Internet of Things system, an integrated circuit board system, a cooling system, software, a cloud database and a sensor case. The pretreatment system is composed of a filtration unit, a conductivity measurement unit, a dilution unit, a solid phase extraction unit, a standard addition, an anti-interference reagent addition, a pH measurement unit and a pH adjustment unit. The sensor can include a single channel for analyzing a single substance, or multiple channels for analyzing multiple substances. The sensor can automatically extract a sample from a pipe or an outlet or other water source, filter the sample to remove solid particles, measure conductivity, dilute the sample, perform solid phase extraction to remove organic matter, add a standard to the sample, add an anti-interference reagent to the sample, measure pH, adjust the sample pH to a desired value, eliminate bubbles, perform calibration, perform sample analysis, analyze data, obtain analysis results, send the results and data to a user through the Internet of Things, regenerate, self-clean, send necessary maintenance reminders, and provide data transmission and database services. This sensor has significant advantages over existing online water quality and safety monitoring sensors based on colorimetry and electrochemical methods. The sensor does not generate false positive signals, can accurately report the concentration of target analytes in real samples, has low detection limits (ppb and sub-ppb levels), has high specificity for target analytes, and does not poison electrodes / sensing elements (can be used for a long time). This sensor perfectly solves the main pain points of existing online sensors based on colorimetry and electrochemical methods: false positive signals when there is no target analyte, no signal when there is a target analyte, low sensitivity (ppm level), low specificity, and poisoning of electrochemical electrodes.

[0053] like Figure 1 As shown, the overall flow chart of the automated online sensor system of the present invention includes automated sample collection, storage and pretreatment, sample delivery through flow control systems such as multi-way valves, syringe pumps, and peristaltic pumps, removal of organic interferents or enrichment of organic matter to be tested through solid phase extraction, precise capture of the test object through the MIP coating of the quartz crystal chip, indication of the change in the signal of the test object captured by the MIP through the change in the resonance frequency of the quartz crystal chip of the quartz crystal microbalance, signal monitoring and data analysis through computer software, issuing commands to the liquid flow control system through software, storing data in the cloud through encrypted data transmission, and reporting results and alarms through client data viewers and mobile devices. Automatic sample collection is completed by liquid delivery pumps and valves controlled by software, and the sample collection volume is controlled. Automated sample pretreatment consists of a series of steps,

[0054] like Figure 3As shown. After pretreatment, the sample is delivered to the flow module. Automatic sample delivery is accomplished through a flow control system, including multi-way valves, syringe pumps, pipelines (switch valves, three-way valves, six-way valves, 13-way valves, 16-way valves, other multi-way valves, syringe pumps, peristaltic pumps, etc.). Accurate capture of the analyte is achieved through the MIP coating of the quartz crystal chip. The automated measurement of sample analytes is accomplished through a quartz crystal microbalance, which mainly consists of an integrated circuit board system, a flow module, a sensing quartz chip coated with a highly specific molecular imprinted polymer film, a chip holder, a power supply, and software. The signals generated by the quartz crystal microbalance are automatically recorded, monitored, and analyzed by the software. The software automatically sends commands to the flow control system to control the liquid flow. The generated data and data analysis are automatically stored in the cloud through encrypted transmission. Results are automatically reported and alerts are automatically sent through client data viewers and mobile devices.

[0055] like Figure 2 As shown in FIG. 1 , the workflow of the automated online sensor system of the present invention includes automated sample collection and storage, sample pretreatment, bubble removal, temperature measurement, analyte measurement, regeneration, data analysis, and data reporting. Automated sample collection is accomplished by a software-controlled liquid delivery pump valve, and the sample collection volume is controlled. Automated sample pretreatment consists of a series of steps, such as Figure 3 As shown. Automatic defoaming is accomplished by a bubble eliminator to eliminate the interference of dissolved air and bubbles generated during liquid transfer. Automatic temperature measurement is accomplished by a software-controlled thermometer. The automated measurement of sample analytes is accomplished by a quartz crystal microbalance, which is mainly composed of an integrated circuit board system, a flow module for fixing the chip holder and the chip, a sensing quartz chip coated with a highly specific molecular imprinting polymer film, a chip holder, a power supply, and software. After the sample analyte is detected, a large number of analytes are specifically adsorbed on the molecular ion imprinting site of the molecular imprinting polymer film, which will affect the next detection. Therefore, the molecular ion imprinting site of the sensing chip is regenerated by using a regeneration reagent to wash online for a certain period of time. The signals generated by the quartz crystal microbalance are automatically recorded, monitored, and analyzed by the software. The commands of the flow control system are automatically sent by the software. The generated data is automatically stored in the cloud through encrypted transmission. The results are automatically reported, and alerts are automatically sent through the client data viewer and mobile devices.

[0056] like Figure 3As shown, the automated sample pretreatment process of the automated online sensor system of the present invention includes automatic filtration, automatic conductivity measurement to determine the first dilution ratio, the first automatic dilution according to the measured conductivity, automatic solid phase extraction, automatic addition of standard, automatic addition of interfering reagent, automatic pH measurement, automatic adjustment of pH according to the measured pH value, and the second dilution ratio and the second dilution determined according to the QCM signal value. The pipeline inlet connected to the sample storage container is connected to the filter for automatic filtration. Filtering removes particles. The conductivity is measured by a conductivity meter to determine the dilution ratio. When the sample conductivity is high, the dilution multiple can be high, otherwise, the dilution multiple can be low. The conductivity meter has a timed automatic calibration function. After the conductivity measurement, the collected sample is automatically diluted by adding deionized water thereto under sufficient stirring. Solid phase extraction is automatically completed by a solid phase extractor (SPE) driven by the vacuum pressure generated by the pump. The pH value is automatically measured by an online pH meter, and has a timed automatic pH calibration function. The pH value adjustment is completed by adding a certain volume of acid and / or alkali to the sample under the pH meter through software control. Standards and anti-interference reagents were automatically added to the samples using a multi-port syringe pump valve controlled by the software.

[0057] like Figure 4 As shown, the automated online sensor system of the present invention has three compartments: compartment 1, compartment 2 and compartment 3. Compartment 1 mainly includes electronic system, control system, power unit, cooling system (QCM, conductivity meter and pH meter are sensitive to temperature), computer and Internet of Things system. Compartment 2 has conductivity meter, pH meter, QCM, flow module, pump, valve, defoamer, solid phase extractor, etc. Compartment 3 is a wet chamber, where sample bottles, filters, reagent bottles, deionized water bottles and waste water tanks are located.

[0058] Figure 5A schematic overall diagram of the automated online sensor system of the present invention is shown, showing the interaction between compartments and the interaction between components in each compartment. In compartment 1, the computer controls the QCM electronic equipment, the automated control system, and the Internet of Things system. The power supply unit supplies power to the QCM circuit board system and the automated control system. The cooling system cools the QCM electronic system, the computer, and the automated control system. In the middle compartment, the pump is connected to the dilution, filter, solid phase extractor, reagent addition, standard addition, flow module, and valve. The conductivity meter is connected to the pump valve, the dilution is completed by the pump valve and the conductivity chamber or the pH adjustment chamber, the solid phase extraction is completed by the pump valve, the vacuum pump, and the solid phase extraction column, and the pH measurement and adjustment are completed by the pump valve, the pH adjustment chamber, and the pH meter. The addition of reagents and standards is completed by the pump valve and the pH adjustment chamber. After the sample enters the pH adjustment chamber, the standard and anti-interference reagent are added and stirred thoroughly. Then, the pH value is adjusted to the design value by adding the pH adjuster (acid, alkali) through the pump valve. Subsequently, the sample passes through a debubbler to remove residual bubbles, and then flows into a flow module containing a QCM quartz crystal chip. The MIP coating on the chip accurately captures the analyte, and the chip resonance frequency signal is collected and processed by the QCM integrated circuit board and microcontroller under software control to output the analyte content signal in the standard or sample.

[0059] Compartment 1 is connected to compartment 2 via a conductive wire, and compartment 2 is connected to compartment 3 via a liquid pipe for liquid transmission. The instrument display screen is located on the housing surface or outside (embedded or independent) of the online sensor system.

[0060] For typical operation, the instrument automatically pumps a certain volume of sample from a designated sampling point into a sample collection bottle through a pump valve. The conductivity of the sample is automatically measured and the result is used to determine the first dilution ratio. This ratio is a balance between low background, detection limit and regulatory lower limit. Based on the conductivity, the sample is automatically diluted to a certain ratio under sufficient stirring. Subsequently, solid phase extraction is performed, a certain volume of internal standard and anti-interference reagent is added, and sufficient stirring is performed, followed by pH measurement and pH adjustment. After degassing by a debubbler, the sample flows into the QCM flow module for signal measurement and recording. Each QCM flow module can be placed with a chip holder and a quartz crystal chip with a thin layer of highly specific molecular imprinted polymer film on it to capture the target analyte. After the measurement is completed, the quartz crystal chip is regenerated by the online flow of regeneration fluid. After regeneration, deionized water is introduced into the flow module to establish a baseline in preparation for the next measurement.

[0061] After the QCM detects the signal value, the system will automatically determine whether the signal is too high, and decide whether a second dilution is needed based on the signal value. If necessary, how many times should it be diluted. Then, based on the first and second dilution ratios, the final dilution ratio is calculated and the standard or sample is restarted.

[0062] One QCM flow module is one channel. Two QCM flow modules are two channels. Multiple QCM flow modules are multiple channels. The more channels there are, the more components are needed. Some components can be shared by multiple channels. Multi-channel is not a simple superposition of single channel. The design needs to be optimized and the software needs to integrate the tasks of each channel so that the channels will not conflict with each other.

[0063] More specifically, 10-100 ml of sample is automatically drawn from the designated sampling point by a pump into a sample collection bottle. After filtration, the conductivity of the sample is measured and the result is used to determine the first dilution ratio. This ratio is a balance between low background, detection limit and regulatory lower limit. According to the conductivity, the sample is automatically diluted to a certain ratio under sufficient stirring. If the conductivity is as low as 300 μS / cm, no dilution is required. If the conductivity is higher than 300 μS / cm, it is diluted to about 300 μS / cm according to the dilution factor. Subsequently, solid phase extraction is performed, and a certain volume (50–150 μl) of internal standard and anti-interference reagent is added to the pretreated sample and stirred well, followed by pH measurement and pH adjustment. Next, the sample is degassed through a debubbler and flows into the QCM flow module connected to the QCM for signal measurement analysis and recording. After the QCM measures the sample analyte (e.g. Pb 2 + ions), the baseline should technically be a flat value determined by the software. The analysis time is set to 5-10 minutes. Each QCM flow module houses a chip holder and a quartz crystal chip with a thin layer of highly specific molecularly imprinted polymer film coating for capturing the target analyte. After the measurement, the quartz crystal chip is regenerated by the online flow of regeneration solution. The regeneration time is 5-10 minutes. After regeneration, deionized water is introduced into the flow module for baseline establishment, which usually takes 5-15 minutes.

[0064] QCM is a quartz crystal microbalance with dissipation, and the fundamental resonance frequency of the quartz crystal is 10MHz. On the molecularly imprinted polymer film coating, the molecularly imprinted polymer is a polymer imprinted with target ions and / or molecules. The molecularly imprinted polymer should contain suitable functional groups to interact with the target ions and / or molecules. The molecularly imprinted polymer can accurately capture the analyte molecules or ions, but does not capture other interfering molecules or ions or the capture amount is very low.

[0065] Example 1

[0066] Synthesis of lead molecular imprinting polymer: The polymerization mixture consists of 20-50 μL of free radical initiator azobisisobutyronitrile, 200-500 μL of monomer methacrylic acid, and 200-800 μL of crosslinker ethylene glycol dimethacrylate. 1-5 mL of methanol or ethanol is used as the solvent system. 10-60 μL of 1% lead nitrate is added to the above mixture as the target template. The mixture is then degassed with nitrogen for 5 to 10 minutes to remove any dissolved oxygen present. After degassing, the mixture is heated at 60-80°C with stirring until polymerization. The reaction time is 5-24 hours, preferably 5-8 hours. Molecularly imprinted polymers are synthesized by polymerization. It is then immersed in a 0.01-0.1% nitric acid solution for 6 hours to remove the lead nitrate used as a template from the molecularly imprinted polymer. This allows the formation of specific complementary cavities on the molecularly imprinted polymer, which can selectively recognize the lead ions used as templates during the synthesis process. The molecularly imprinted polymer was then obtained by vacuum filtration or high-speed centrifugation and dried at 60-80°C for 24-48 hours. The molecularly imprinted polymer was finally ground into fine powder using a mortar and pestle to obtain about 0.2-0.5 g of light yellow molecularly imprinted polymer (MIP) powder.

[0067] Example 2

[0068] Preparation of QCM quartz crystal chip MIP coating: First, clean the QCM chip with Piranha solution. Then add 0.1-0.5 mg of the molecular imprinting polymer powder in Example 1 in the form of fine powder to 1-10 mL of methanol or ethanol. Disperse the powder by shaking the solution. Then apply 0.1-0.5 μL of the solution to the QCM chip and dry it in an oven at 80°C for 1-2 hours.

[0069] Example 3

[0070] The QCM was a QCM-D quartz crystal microbalance purchased from MIPS Innovations Pte Ltd, and the 10MHz QCM chip was also purchased from the same company. Together with more common components and elements, a prototype of an automated real-time online single-channel sensor combining a quartz crystal microbalance and molecularly imprinted polymer was constructed using programming software for water quality and safety monitoring ( Figure 6 ).

[0071] Example 4

[0072] The online sensor prototype in Example 3 can be self-calibrated daily as shown below, using the standard addition method, which can effectively offset the matrix effect - matrix substances usually enhance or suppress the signal. Figure 7), the calibration steps are carried out in sequence: establish a baseline with deionized water flowing into and out of the circulation pool, perform standard one calibration, regenerate the sensing quartz crystal MIP chip, re-establish the baseline with deionized water, standard two calibration, regeneration, baseline, standard three calibration and regeneration (calibration completed).

[0073] Typical data points of the constructed online sensor prototype are obtained by the following steps ( Figure 8 ): Baseline equilibration with deionized water (5-10 minutes), standard or sample measurement (5-10 minutes), regeneration (5-10 minutes). At present, the online sensor prototype has achieved satisfactory results on laboratory simulated samples (tap water and wastewater containing lead standards). Compared with the results of ICP / MS verification, the RSD is within 5% and the accuracy is within 100±5%.

[0074] Fig. 9 The Pb calibration data of the online sensor prototype and tap water samples are shown. Calibration was performed with the addition of 0, 1, and 2 ppm Pb(II) standards. The calibration curve is very linear with R 2 0.9854 is close to 1. The calculated concentration of Pb(II) in the tap water sample is -2.38 ppb. The accuracy of the test result and the ICP / MS result (0 ppb) is 99.76%. In this example, the online sensor prototype did not report an erroneous signal (also known as a false alarm signal).

[0075] Table 1 shows the test results of 1ppm Pb(II) spiked sample (2000 times diluted palm oil mill wastewater) on the online sensor prototype. As shown in Table 1, the 2000 times diluted palm oil mill wastewater sample spiked with 1ppm Pb(II) has a measured Pb(II) concentration of 0.98ppm and 0.98ppm (double measurement), with an average of 0.98ppm, an accuracy of 98.0%, and RSD0%. The two sets of data listed in Table 1 prove that the online sensor prototype does not have a "no signal" problem in the actual sample, but can detect Pb(II) well, with an accuracy range of 95–105% and a wide RSD range of 0–5% when 1ppm Pb(II) is added to the actual sample.

[0076] Example 5

[0077] Prevent false positives, verify using ICP-MS and report verification results:

[0078] The system prevents false positives and verifies results via ICP-MS. Lead was selected as the target analyte, with mercury being a common interferent for lead ions. Mercury was added to the sample to stimulate conditions that would lead to false positives, while potassium chloride was used to suppress interference with the sensor. The lead sensor was calibrated using a 0 to 2 ppm lead standard solution. The lead sample was first measured, and then mercury was added. Subsequently, potassium chloride was added to the sample and the results were compared. The results showed that the sensor without the addition of an anti-interference reagent (KCl) detected lead concentrations higher than the actual level, resulting in a false positive. However, after the addition of an anti-interference reagent (KCl), the QCM only detected lead in the presence of mercury, which agreed well with the ICP-MS results. Therefore, the QCM results were verified by ICP-MS with an accuracy of 95.5% ( Fig.10 ).

[0079] Example 6

[0080] Preventing false negatives:

[0081] Operational testing of the integrated system was performed to demonstrate the ability to prevent false negatives by adding cations, anions, surfactants, solvents, dissolved organic particles, undissolved particles, and dissolved particles under simulated operating conditions. The system was able to correctly detect the target analytes under various strong interferences, demonstrating the ability to prevent false negatives.

[0082] Example 7

[0083] Common cation interferences:

[0084] We tested whether the presence of common cations could affect the accuracy of the results obtained by our sensor. Fig.11 The Fe concentration detected before adding cations as interference, the concentration of Na+, K+, Ca+, 2 + and Mg 2 + Fe concentration detected as interference and Fe concentration detected after interference test. The obtained results indicate that the presence of cations does not affect the performance of the sensor.

[0085] Example 8

[0086] Common anion interferences:

[0087] We tested whether the presence of common anions could affect the accuracy of the results obtained by the sensor. Fig.12 The Fe concentration detected before adding anions as interference, the concentration of SO4 2 -, Cl-, H2PO4- and CO3 2- as the Fe concentration detected during the interference and after the interference test. The results show that high concentrations of H2PO4- can affect the performance of the sensor. NaH2PO4 binds to Fe, resulting in a decrease in the detected Fe concentration.

[0088] Example 9

[0089] Interference of surfactants:

[0090] We tested whether the presence of surfactants could affect the accuracy of the results obtained by our sensor. Fig.13 The Fe concentration detected before adding surfactant as interference, the Fe concentration detected when adding Tween 20 and SDS- as interference, and the Fe concentration detected after the interference test are shown. The obtained results show that the presence of high concentration of SDS affects the performance of the sensor due to the presence of bubbles during the analysis.

[0091] Example 10

[0092] Common solvent interferences:

[0093] We tested whether the presence of solvents could affect the accuracy of the results obtained by the sensor. Fig.14 The Fe concentration detected before adding solvent as interference, the Fe concentration detected when adding isopropyl alcohol (IPA) and dimethylformamide (DMF) as interference, and the Fe concentration detected after the interference test are shown. The results show that the presence of solvent does not affect the performance of the sensor.

[0094] Embodiment 11

[0095] Dissolved organic matter interference:

[0096] We tested whether the presence of dissolved organic matter could affect the accuracy of the results obtained by our sensor. Fig.15 The Fe concentration detected before adding dissolved organic particles as interference, the Fe concentration detected when adding glucose and lactic acid as interference, and the Fe concentration detected after the interference test are shown. The obtained results indicate that the presence of dissolved organic matter does not affect the performance of the sensor.

[0097] Example 12

[0098] Presence of undissolved particles:

[0099] We tested whether the presence of undissolved particles could affect the accuracy of the results obtained by the sensor. Fig.16The Fe concentration detected before adding insoluble particles as interference, the Fe concentration detected when adding sea sand as interference, and the Fe concentration detected after the interference test are shown. The obtained results show that the presence of insoluble particles does not affect the performance of the sensor.

[0100] Embodiment 13

[0101] Dissolved particles interference:

[0102] We tested whether the presence of dissolved particles could affect the accuracy of the results obtained by the sensor. Fig.17 The Fe concentration detected before adding undissolved particles as interference, the Fe concentration detected when adding gold nanoparticles as interference, and the Fe concentration detected after the interference test are shown. The results obtained indicate that the presence of dissolved particles can affect the performance of the sensor. Gold nanoparticles bind to Fe, resulting in a decrease in the detected Fe concentration. Under various strong interferences (Examples 6-13), the system is still able to correctly detect the target analyte, which proves the effectiveness of the method of preventing false negatives of the present invention.

[0103] Embodiment 14

[0104] Verification of MIP production process and calibration using ICP-MS:

[0105] We validated the MIP production process and its calibration using ICP MS. The MIP production and calibration using ICP-MS has been successfully validated on a Fe(III) sensor. After the MIP was successfully coated on the gold surface of the QCM sensor chip, the sensor was calibrated and the detection of heavy metal ions was validated separately. The entire calibration process consisted of 2 cycles of 5-point calibration, starting with 10, 20, 50, 80 and 100 ppb Fe(III) standard solutions ( Fig.18 ). The baseline level was taken from a point of one minute duration before the introduction of the heavy metal ion transition. The response signal was then calculated by subtracting the frequency at 7 minutes after the introduction of the Fe(III) solution. All solutions were verified by ICP-MS and the accuracy of the tested solutions was above 90%. The calibration curve showed good linearity and the calculated slope and intercept values ​​were used to calculate the concentration of Fe(III) in the analyte (Figure 19).

[0106] Embodiment 15

[0107] Verify chip life and long-term use conditions:

[0108] We verified the sensor's lifetime and long-term use conditions ( Fig. 20). The service life and long-term use conditions were verified using the Fe(III) sensor. The assigned process was considered as 1 cycle by following the steps below; using deionized water to obtain a baseline, introducing a Fe(III) standard solution 65ppb, and regenerating the sensor using alkaline and acid solutions respectively. By performing 3 cycles per day, the sensor can perform 1080 cycles of verification, which is equivalent to 360 days of testing. The overall results of Fe(III) detected by the sensor were verified by ICP-MS with an accuracy of ±30%. The performance of the sensor can extend the working time by 3 to 6 months.

[0109] Example 16

[0110] Verify regeneration conditions:

[0111] We validated the regeneration conditions of the sensor. The regeneration conditions were validated using a Fe(III) sensor. The assigned process was considered 1 cycle by following the steps below; using deionized water to obtain a baseline, introducing a Fe(III) standard solution of 65 ppb, and regenerating the sensor using alkaline and acid solutions, respectively. The sensor was validated for 200 cycles by performing 10 cycles per day. The overall results of Fe(III) detected by the sensor were validated by ICP-MS with an accuracy of ±30%. The sensor performance was reproducible and could be regenerated and cycled for more than 200 times ( Fig.21 ).

[0112] Embodiment 17

[0113] Verify detection time and measurement frequency:

[0114] We validated the sensor’s detection time and measurement frequency. A 65 ppb solution of Fe(III) was used to validate this milestone. Three cycles were performed per day with a 40-minute interval between each measurement. The detection time was 7 minutes from the introduction of the Fe(III) solution to the 7th minute. The validation was performed continuously over 30 days. The overall results of Fe(III) detected by the sensor were validated by ICP-MS with an accuracy of ±10% ( Fig. 22 ).

[0115] Embodiment 18

[0116] Validation of the metal speciation method and confirmation of results by HPLC-ICP-MS:

[0117] We validated the metal speciation method and confirmed the results using HPLC-ICP-MS ( Fig.23). Cr(III) and Cr(VI) were used for metal speciation analysis. Speciation is crucial because toxicity, bioavailability, and environmental mobility in general strongly depend on the chemical form of the metal. The developed sensor can selectively detect Cr(III), and the sensor was calibrated with Cr(III) and total Cr, respectively. Samples containing both Cr(III) and Cr(VI) were measured. Cr(VI) was reduced to Cr(III) using the reducing agent NaBH4 under a nitrogen purge. The measurement was performed after all Cr ions in the sample were reduced to Cr(III), and the portion of Cr(III) was subtracted from the total Cr to determine the final concentration of Cr(VI).

[0118] Overall, the results of QCM and ICP-MS showed similar detection numbers with an accuracy of more than 90%. The LODs for Cr(III) and Cr(VI) were 6.3 and 16 ppb, respectively. Fig.24 ).

[0119] Embodiment 19

[0120] The prototype product is verified in the relevant operating environment:

[0121] We completed the validation of the prototype in a relevant operating environment (Table 2). The developed prototype integrates dilution, pH adjustment, self-calibration and IoT functions. The obtained calibration curve has a high correlation coefficient close to 1. Four real water samples were tested and the results obtained by the prototype were consistent with those obtained by ICP-OES.

[0122] Embodiment 20

[0123] In-situ heavy metal sensor prototype validated in an operational environment:

[0124] The prototype on-site heavy metal sensor has been validated in an operational environment using the 10 real samples listed below and cross-validated using ICP-OES. The results for half of the samples were identical to those for ICP-OES, while the results for the other half deviated slightly from those for ICP-OES, probably because the lower detection limit of ICP-OES was higher than that of our sensor (Table III).

[0125] Embodiment 21

[0126] Prototype in-line heavy metal sensor validated in an operational environment:

[0127] The prototype on-line heavy metal sensor has been validated in an operational environment using the 10 real samples listed below and cross-validated using ICP-OES. The results obtained for all samples showed a deviation of less than ±30% compared to the results obtained by ICP-OES (Table IV).

[0128] Embodiment 22

[0129] The comprehensive pilot system was validated in an operational environment:

[0130] The integrated online Pb sensor has been validated in an operating environment with the 10 real samples listed below and cross-validated using ICP-OES. The results obtained for all samples were the same as those obtained by ICP-OES (Table V). We added 1ppm of lead to many of the samples to determine if the sensor can accurately detect the concentration of lead. The integrated online Pb sensor has been validated in an operating environment with the 5 real samples listed below and cross-validated using ICP OES. The results obtained for all samples had a deviation of less than ±30% compared to the results obtained by ICP-OES. (Table VI)

[0131] We have completed and implemented the development and validation of the present invention. Through this research project, an automated sensor system with IoT capabilities combining QCM and MIP technologies has been successfully developed. The developed sensor system has been validated for service life and long-term use conditions, regeneration conditions, prevention of ICP-MS false positives, and metal speciation analysis methods for HPLC-ICP-MS. In addition, software for automated sample handling, data collection, and data processing has been developed. The sensor system prototype has been manufactured and tested in the field, online, simulated operating environment, and real operating environment.

[0132] Compared with online water quality analysis instruments using optics, colorimetry, fluorescence, spectrophotometry and anodic stripping voltammetry technology, the present invention has obvious advantages in selectivity, interference resistance and sensitivity. Compared with ICP-MS, the developed sensor system can basically realize the functions of ICP-MS, and the advantage is that it is fully automatic and does not require professional operation. When the present invention is developed to 5 channels or more, it can be equivalent to ICP-MS multi-element rapid detection.

[0133]

[0134] Table 1 Comparison of test results of 1 ppm Pb(II) spiked sample - 2000 times diluted palm oil mill wastewater (M1 M2 are the two masking agents mentioned above).

[0135]

[0136]

[0137] Table 2 Comparison of the results obtained by ICP-OES and the prototype online Pb sensor in actual water samples.

[0138]

[0139] Table III Comparison of the results obtained by ICP-OES and the prototype in situ Pb sensor in 10 different water samples.

[0140]

[0141]

[0142] Table IV Comparison of the results obtained by ICP-OES and the prototype online Pb sensor in 10 different water samples.

[0143]

[0144]

[0145] Table 5 Comparison of the results obtained by ICP-OES and integrated online Pb sensor in 10 different water samples.

[0146]

[0147] Table 6 Comparison of the results obtained by ICP-OES and integrated online Pb sensor in 5 different water samples spiked with 1 ppm lead.

[0148] The present invention has been described illustratively and not restrictively according to the embodiments of the present invention, but it should be understood that changes and / or modifications may be made by those skilled in the art without departing from the relevant protection scope defined by the claims.

Claims

1. A novel online single-channel and multi-channel water quality and safety testing instrument that combines quartz crystal resonance technology and molecular imprinting technology, characterized by: It consists of a sample collection and storage unit, a reagent box, a sample pretreatment system, a stirring device, a bubble elimination device, a sample flow module, a molecular imprinting polymer (MIP) sensor chip, a quartz crystal microbalance (QCM), an Internet of Things system, an integrated circuit board system, a valve pump system, a cooling system, software, a cloud database, a power supply and a sensor housing; the sensor may include a single channel for analyzing a single substance, or multiple channels for analyzing multiple substances; The overall process includes automated sample collection, storage and pretreatment, sample delivery through a flow control system with a multi-way valve and a syringe pump, etc., conductivity detection through an online conductivity meter and preliminary determination of the first automatic dilution ratio of the sample, sample dilution in a pH adjustment pool through a pump valve system, determination of the second automatic dilution ratio of the sample by the sample signal strength of a quartz crystal microbalance, pH value measurement through an online pH meter, delivery of standard samples and anti-interference agents and acid-base regulators through a flow control system with a multi-way valve and a syringe pump to automatically adjust the pH value, uniform stirring of samples and reagents through a stirring device, elimination of bubbles through a debubbling device to prevent bubbles from entering the sample detection pool and affecting sample detection, specific capture of the analyte in the sample through a molecular imprinting coating, measurement and monitoring of the analyte signal in the sample through a quartz crystal microbalance, and data analysis and data report sending using software; Issue commands to the flow control system via software, store data in the cloud via encrypted data transmission, and report results and alarms via client data viewers and mobile devices; The automated sample collection is completed by a liquid delivery pump controlled by software, and the sample collection volume is controlled; Sample pretreatment consists of a series of steps: conductivity detection, sample dilution, solid phase extraction, pH detection, anti-interference agent addition and pH adjustment; solid phase extraction is used to remove interfering organic matter or to concentrate organic analytes; after pretreatment, the sample is transported to the flow module; The sample delivery is accomplished by a flow control system, including a multi-way valve, a syringe pump, a peristaltic pump, a pipeline, etc.; the bubbles are accomplished by a defoamer and a vacuum pump; the automatic measurement of the sample analyte is accomplished by a quartz crystal microbalance; The quartz crystal microbalance is mainly composed of an integrated circuit board system, a flow module for fixing a chip holder and a chip, a sensing quartz chip coated with a highly specific molecular imprinting polymer film coating, a chip holder, and a power supply; the signals generated by the quartz crystal microbalance are automatically recorded, monitored and analyzed by the software; the commands of the flow control system are automatically sent by the software; the generated data is automatically stored in the cloud through encrypted transmission; the results are automatically reported, and alarms are automatically sent through the client data viewer and mobile devices; The workflow of the online sensor system includes automated sample collection storage, sample pretreatment, bubble removal, temperature measurement, analyte measurement, regeneration, data analysis, and data reporting; The removal of bubbles is accomplished by combining a bubble remover and a vacuum pump to prevent dissolved air and bubbles generated during liquid transfer from entering the detection cell and interfering with sample detection; The temperature measurement is completed by a software-controlled thermometer; the automatic measurement of the sample analyte is completed by a quartz crystal microbalance. After the sample analyte is measured, two regeneration reagents are transported through a pump valve to flow wash online in sequence for a certain period of time to regenerate the sensor chip; The sample pretreatment process includes automatic conductivity measurement to determine the dilution ratio, automatic dilution according to the measured conductivity, automatic filtration, automatic solid phase extraction, automatic pH measurement, automatic addition of acid-base regulator based on pH meter to adjust pH value, automatic addition of standard and automatic addition of anti-interference reagent; the first dilution ratio of the sample is determined by measuring the conductivity by a conductivity meter; the second dilution ratio of the sample is determined by the signal strength of a quartz crystal microbalance; when the conductivity of the sample is high, the dilution factor can be high, otherwise, the dilution factor is low; after the conductivity measurement, deionized water is added to the sample under sufficient stirring to obtain the dilution ratio; The collected samples are automatically diluted; before entering the conductivity cell and pH cell, the samples are automatically filtered through the filter connected to the pipeline entry end; the particles are removed by filtration; the solid phase extraction is automatically completed by the solid phase extractor (SPE) driven by the vacuum pressure generated by the pump; the conductivity is measured by an online conductivity meter with an automatic timed calibration function; the pH value is automatically measured by an online pH meter with an automatic timed calibration function; the pH value adjustment is completed by adding a certain volume of acid and / or base to the sample through a pump valve under the pH meter; the standard and anti-interference reagents are automatically added to the sample using a multi-way valve and injection pump controlled by the software; The automated online sensor system has three compartments: compartment 1, compartment 2 and compartment 3; compartment 1 mainly includes electronic systems, control systems, power devices, cooling systems, Internet of Things systems, and computers; compartment 2 has conductivity meters, pH meters, QCMs, flow modules, pumps, valves, defoamers, solid phase extractors, etc.; compartment 3 is for wet processing, where filters, sample bottles, reagent bottles, deionized water bottles, and waste water bottles are located; The interactions between the compartments of the automated online sensor system and the interactions between the components in each compartment are as follows: in compartment 1, the computer controls the QCM electronic equipment, the automated control system and the Internet of Things system; the power supply unit supplies power to the QCM electronic system and the automated control system; the cooling system cools the QCM electronic system, the computer and the automated control system; in compartment 2, the pump is connected to the dilution, solid phase extractor, reagent addition, standard addition, flow module and valve; the conductivity meter is connected to the diluter, and the diluter is further connected to the filter; the filter is connected to the solid phase extractor, and the solid phase extractor is connected to the pH meter; the pH meter is connected to the reagent addition, and is further connected to the standard addition; after the pH measurement, the reagent (acid, base) is added by the pump to adjust the pH value to the designed value; before the sample analyte is measured, the standard and anti-interference reagent are added to the sample and then its pH value is adjusted and fully stirred; then, the sample is removed from the residual bubbles by the debubbler, and then flows into the flow module connected to the QCM.

2. A novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance technology and molecular imprinting technology according to claim 1, characterized in that: Typical operation of an online sensor: a certain volume of sample is automatically drawn from a designated sampling point into a sample collection bottle by a pump; the conductivity of the sample is measured and the result is used to determine the first dilution ratio; this ratio is a balance between low background, detection limit and regulatory lower limit; the sample is automatically diluted to a certain ratio under sufficient stirring according to the conductivity; the diluted sample is then filtered and subjected to solid phase extraction, and then an anti-interference agent is introduced by a pump valve and pH measurement and pH adjustment are performed; a certain volume of internal standard and anti-interference agent are added to the pretreated sample and stirred thoroughly, and the sample is degassed by a defoamer and flows into the QCM flow module connected to the QCM for signal measurement and recording; the second dilution ratio of the sample is determined by the strength of the QCM signal; the QCM flow module contains a quartz crystal chip with a thin layer of highly specific molecularly imprinted polymer film on it to capture the target analyte; after the measurement, the quartz crystal chip is regenerated by two regeneration solutions flowing online in sequence; after regeneration, deionized water is introduced into the flow module to establish a baseline.

3. A novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance technology and molecular imprinting technology according to claim 2, characterized in that: 10-100 ml of sample is automatically drawn from a designated sampling point into a sample collection bottle by a pump; filtered online; the conductivity of the sample is measured and the result is used to determine the dilution ratio; this ratio is a balance between low background, detection limit and regulatory lower limit; the sample is automatically diluted to a certain ratio under sufficient stirring according to the conductivity; when the sample conductivity is high, the dilution factor can be higher, otherwise, the dilution factor is lower; if the conductivity is as low as 300 μS / cm, no dilution is required; if the conductivity is higher than 300 μS / cm, it is diluted to within 300 μS / cm according to the dilution factor; then, solid phase extraction is performed, a certain volume (30-300 μl) of internal standard and anti-interference agent is added, stirred thoroughly, and then pH measurement and pH adjustment are performed; stirred thoroughly, the sample is then degassed through a debubbler and flows into the QCM flow module connected to the QCM for analysis; signal measurement and recording; the QCM measures the sample analyte (e.g. Pb 2 + ions), the baseline should technically be a flat value determined by the software; the analysis time is set to 5-10 minutes; the QCM flow module contains a quartz crystal chip coated with a highly specific molecular imprinted polymer film layer for capturing target analytes; after the measurement, the quartz crystal chip is regenerated by the online flow of regeneration solution; the regeneration time is 5-10 minutes; after regeneration, deionized water is introduced into the flow module for baseline establishment, which usually takes 5-15 minutes.

4. A novel online single-channel and multi-channel water quality and safety detection instrument combining quartz crystal resonance technology and molecular imprinting technology according to claim 2, characterized in that: Synthesis of molecular imprinting polymer: The polymerization mixture for synthesizing molecular imprinting polymer consists of 20-50 μL of free radical initiator (e.g., azobisisobutyronitrile), 200-500 μL of monomer (e.g., methacrylic acid), and 200-800 μL of crosslinker (e.g., ethylene glycol dimethacrylate); 1-5 mL of solvent (e.g., methanol or ethanol) is used as the solvent system; 10-60 μL of a certain concentration of template solution (e.g., 1% lead nitrate) is added to the above mixture as the target template; the mixture is then degassed with nitrogen for 5 to 10 minutes to remove any dissolved oxygen present; after degassing, the mixture is stirred and heated at a certain temperature (e.g., 60-80°C) for polymerization. ; a molecular imprinting polymer is synthesized by polymerization reaction; it is then immersed in a solution of a template eluent (e.g., 0.01-0.1% nitric acid) for a certain time (e.g., 3-8 hours) to remove the template (e.g., lead nitrate) used as a template from the molecular imprinting polymer; this allows the formation of complementary cavities on the molecular imprinting polymer, which are capable of selectively recognizing template ions (e.g., lead ions) or molecules used as templates during the synthesis process; the molecular imprinting polymer is then obtained by vacuum filtration or centrifugation and dried for 24-48 hours; finally, the molecular imprinting polymer is ground into fine powder using a mortar and pestle; a certain amount (e.g., 0.2-0.5 g) of light yellow molecular imprinting polymer (MIP) powder is obtained.

5. A novel online single-channel and multi-channel water quality and safety testing instrument combining quartz crystal resonance technology and molecular imprinting technology according to claim 3, characterized in that: The QCM chip is prepared as follows: first, the bare QCM chip is cleaned with Piranha solution; then, 0.1-0.5 mg of the molecular imprinting polymer powder in statement 4 is added in the form of fine powder to 1-10 mL of methanol or ethanol; the powder is dispersed by shaking the solution; then, 0.1-0.5 μL of the solution is evenly coated on the QCM chip and dried in an oven at 60-100° C. for 1-2 hours before being used for analysis.

6. A novel online single-channel and multi-channel water quality and safety testing instrument combining quartz crystal resonance technology and molecular imprinting technology according to claim 5, characterized in that: The QCM is a quartz crystal microbalance with dissipation (QCM-D), on which a 10MHz QCM quartz crystal chip can be used; together with other components and devices, programming software can be used to build an automatic real-time online single-channel sensor prototype based on a quartz crystal microbalance and molecular imprinting polymer for water quality and safety monitoring.

7. A novel online single-channel and multi-channel water quality and safety testing instrument combining quartz crystal resonance technology and molecular imprinting technology according to claim 1, characterized in that: After the online sensor prototype is built, it can be self-calibrated every day, and the standard addition method can effectively offset the matrix effect - the matrix material usually enhances or suppresses the signal. The calibration steps are carried out in order: QCM establishes the baseline with deionized water flowing into the detection cell, performs standard sample one calibration, regenerates the sensing quartz crystal MIP chip, establishes the baseline again with deionized water, performs standard sample two calibration, regenerates the MIP chip, baseline, performs standard sample three calibration and regenerates the MIP chip (calibration is completed); Typical data points of the constructed online sensor prototype are obtained by the following steps: baseline equilibration with deionized water (5-10 minutes), standard or sample measurement (5-10 minutes) and MIP chip regeneration (5-10 minutes); The online sensor prototype obtained satisfactory results on laboratory simulated samples (tap water and wastewater containing lead standards); compared with the results of ICP / MS verification, the RSD was within 5% and the accuracy was within 100±5%. Pb calibration data for tap water samples on the online sensor prototype were also obtained; 0, 1 and 2 ppm Pb(II) standards were added for calibration; The calibration curve is very linear, with R2 equal to 0.9854 close to 1; The calculated concentration of Pb(II) in the tap water sample was -2.38 ppb (reported as "not detected"); the test result was compared with the ICP / MS result (0 ppb), which was 99.76% accurate; in this example, the online sensor prototype did not report a false signal (also known as a false positive signal); The test results of the online sensor prototype on the sample spiked with 1ppm Pb(II) - 2000-fold diluted palm oil mill wastewater showed that the 2000-fold diluted palm oil mill wastewater sample spiked with 1ppm Pb(II) had a measured Pb(II) concentration of 0.98ppm and 0.98ppm (dual measurement), with an average of 0.98ppm, an accuracy of 98.0%, and an RSD of 0%; the two sets of data obtained proved that the online sensor prototype did not have a "no signal" problem in the actual sample, but could detect Pb(II) well, with an accuracy range of 95–105% and an RSD range of 0–5% in the actual sample with 1ppm Pb(II) added; the ICP-AES test result was 1.0ppm Pb.

Images