Organic sample analysis method based on micro gas chromatography and chromatographic analyzer

Abstract

The present invention discloses an organic sample analysis method and chromatographic analyzer based on micro gas chromatography, specifically relating to the technical field of micro gas chromatography analysis. The method is used to solve the problems of unstable separation performance and low detection accuracy of complex samples caused by insufficient uniformity of the stationary phase coating in existing micro chromatographic columns. The method constructs an initial profile of the stationary phase distribution by continuously pre-flushing the carrier gas, alternately applies a segmented temperature gradient, a micro-negative pressure, and a directional pulse flow to reshape the uniform distribution layer, combines a calibration mixture with a tracer gas pulse to generate a correction factor set for the temperature-resistance coupling relationship, dynamically adjusts the carrier gas flow rate and temperature program to generate a matching operating curve, and achieves high-precision separation detection and quantitative analysis. By synergistically controlling the optimization of the stationary phase distribution and real-time parameter feedback correction, stable separation performance is maintained in a miniaturized structure, and the detection accuracy and reproducibility of organic mixtures with a wide boiling range are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of micro gas chromatography analysis, and more particularly to an organic sample analysis method and a chromatographic analyzer based on micro gas chromatography. Background Art

[0002] Micro gas chromatography significantly improves the portability and analysis speed of traditional gas chromatography systems by miniaturizing them, making them suitable for rapid on-site detection of organic samples. During this miniaturization process, the reduction in column size poses challenges to the internal stationary phase coating process. Existing technologies typically utilize microfabrication to achieve stationary phase loading within microcolumns. However, due to the limitations of the physical dimensions and machining precision of microcolumns, controlling the uniformity of the stationary phase coating can impact the system's separation performance.

[0003] In existing micro gas chromatography, there is a contradiction between the uniformity of the micro column stationary phase coating and the separation capacity. It is difficult to maintain high column efficiency while taking into account the separation efficiency of multi-component samples, which restricts the high-precision separation ability of complex organic mixtures. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide an organic sample analysis method and a chromatographic analyzer based on micro gas chromatography to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] Micro gas chromatography-based methods for organic sample analysis, including:

[0007] S1, continuously pre-flushing the carrier gas into the micro-chromatographic column and collecting the pressure waveform to construct the initial profile of the stationary phase distribution;

[0008] S2. Alternately applying segmented temperature gradient, slight negative pressure and directional pulse flow based on the initial profile of the stationary phase distribution to reshape the stationary phase into a uniformly distributed layer;

[0009] S3, injecting a calibration mixture and a trace amount of inert tracer gas pulse into the uniformly distributed layer of the stationary phase, obtaining the calibration peak retention time and the tracer gas lag time difference and generating a calibration factor set;

[0010] S4. Dynamically adjust the carrier gas flow rate and temperature program based on the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase;

[0011] S5. Loading the organic sample to be tested onto the micro-chromatographic column with a uniformly distributed stationary phase layer under the operating curve conditions, completing component separation and recording peak signals in real time;

[0012] S6. Output the quantitative results of each component according to the corresponding relationship between the peak signal, the peak retention time and the tracer gas lag time difference.

[0013] In a preferred embodiment, continuously pre-flushing the micro-chromatographic column with carrier gas and collecting the pressure waveform to construct an initial profile of the stationary phase distribution includes:

[0014] The carrier gas is stably introduced into the micro-chromatographic column and a pressure sensor is set at the inlet end to obtain continuous pressure data;

[0015] The continuous pressure data is filtered to form a pressure waveform curve;

[0016] The stationary phase axial resistance distribution is inverted based on the pressure waveform curve and the initial stationary phase distribution profile is generated.

[0017] In a preferred embodiment, a segmented temperature gradient, a slight negative pressure, and a directional pulse flow are alternately applied on the basis of the initial profile of the stationary phase distribution to reshape the stationary phase uniformly distributed layer, comprising:

[0018] Based on the initial profile of the stationary phase distribution, the micro-chromatographic column is divided into multiple independent temperature zones along the axial direction. The temperature gradient difference of each independent temperature zone is within a preset range. The temperature is applied in sections by a thin film heater attached to the outer wall of the chromatographic column.

[0019] After applying the temperature gradient, a vacuum pump is connected to the outlet of the micro-chromatographic column to generate a slight negative pressure, the pressure range of which is adapted to the structural strength of the micro-chromatographic column;

[0020] During the micro-negative pressure period, carrier gas is injected into the inlet of the micro-chromatographic column in a pulsed form, and the pulse frequency and duration are adapted to the fluid dynamics characteristics of the carrier gas flow;

[0021] The temperature gradient application, slight negative pressure generation and pulsed carrier gas injection are performed alternately, and the number of cycles is adapted to the uniformity change trend of the stationary phase coating thickness distribution until the stationary phase coating thickness distribution meets the preset uniformity standard.

[0022] In a preferred embodiment, a calibration mixture and a trace amount of inert tracer gas pulse are injected into the uniformly distributed stationary phase layer to obtain the calibration peak retention time and the tracer gas lag time difference and generate a calibration factor set, including:

[0023] Alternately injecting a calibration mixture and pulses of inert tracer gas into a uniformly distributed layer of stationary phase;

[0024] The thermal conductivity detector is used to synchronously capture the separation peaks of the components with different boiling points in the calibration mixture and the diffusion peaks of the tracer gas, and the peak time of each separation peak and the tailing time of the diffusion peak are extracted;

[0025] Based on the time domain difference between the peak time and the tail time, combined with the axial temperature distribution data of the uniformly distributed layer of the stationary phase, the diffusion resistance compensation coefficient of each boiling point component is constructed;

[0026] The diffusion resistance compensation coefficients were matched step by step with the theoretical values ​​in the standard retention time database to generate a correction factor set containing the temperature-resistance coupling relationship. The priority of the step-by-step matching was sorted according to the polarity difference of the boiling point components.

[0027] In a preferred embodiment, the injection timing of the calibration mixture and the interval between the tracer gas pulses are dynamically adjusted based on the porosity gradient of the uniformly distributed layer of the stationary phase.

[0028] In a preferred embodiment, the carrier gas flow rate and temperature program are dynamically adjusted according to the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase, including:

[0029] Based on the temperature-resistance coupling relationship in the correction factor set, the boiling point components of the sample to be tested are divided into two categories according to polarity priority: high priority and low priority;

[0030] For high-priority components, the carrier gas flow rate is increased step by step along the axial position of the stationary phase uniform distribution layer according to the corresponding diffusion resistance compensation coefficient. The increase in flow rate is positively correlated with the compensation coefficient.

[0031] For low-priority components, combined with the axial temperature distribution data of the uniformly distributed layer of the stationary phase, the heating rate range of the temperature program is symmetrically expanded with each temperature gradient as the median value;

[0032] The adjusted carrier gas flow rate and temperature program are reorganized according to the elution order of the boiling point components to generate an operating curve containing segmented flow rate control instructions and nonlinear temperature gradients. The reorganization process ensures that the flow rate and temperature change rates between adjacent segments are continuous and differentiable.

[0033] In a preferred embodiment, the organic sample to be tested is loaded onto a micro-chromatographic column having a uniformly distributed stationary phase layer under the operating curve conditions, component separation is completed, and peak signals are recorded in real time, comprising:

[0034] The organic sample to be tested is loaded into the inlet of the micro-chromatographic column through a microliter syringe, and the loading volume is adapted to the adsorption capacity of the uniformly distributed layer of the stationary phase;

[0035] According to the segmented flow rate control instructions in the operation curve, the carrier gas flow rate is switched to the target value segment by segment, and the time interval of the switching process matches the theoretical elution time window of the boiling point component;

[0036] The nonlinear temperature gradient program in the synchronous operation curve controls the temperature rise rate of the thin film heater on the outer wall of the micro-chromatographic column. The rate of change is consistent with the temperature gradient difference between adjacent segments.

[0037] The peak signals of the separated components are captured by a thermal conductivity detector and recorded in real time as time-voltage waveforms. The waveform sampling frequency is adapted to the minimum resolution of the peak half-peak width.

[0038] The recorded peak signals are time-series aligned with the theoretical retention times in the calibration factor set to generate a time-axis-calibrated peak sequence to be analyzed.

[0039] In a preferred embodiment, the quantitative results of each component are output according to the corresponding relationship between the peak signal, the peak retention time and the tracer gas hysteresis time difference, including:

[0040] Baseline correction is performed on the peak sequence to be analyzed after time axis calibration, and the peak area of ​​each peak is calculated by the integration algorithm after the correction of the peak signal;

[0041] Based on the temperature-resistance coupling relationship in the correction factor set, the theoretical retention time corresponding to each peak is matched with the diffusion resistance compensation coefficient to generate the conversion factor between peak area and concentration;

[0042] The time axis alignment error of the conversion factor is adjusted by combining the compensation of the tracer gas lag time difference to the peak retention time. The compensation amount is calculated by multiplying the lag time difference by the carrier gas flow rate.

[0043] The adjusted conversion factor is multiplied by the peak area to obtain the concentration value of each component. The concentration values ​​are sorted according to the elution order of the boiling point components and the quantitative result table is output.

[0044] In another aspect, the present invention provides a chromatographic analyzer for organic sample analysis based on micro gas chromatography, comprising:

[0045] a carrier gas supply module configured to continuously supply carrier gas to the micro chromatographic column and connected to a pressure sensor at the inlet end to collect continuous pressure waveform data;

[0046] The stationary phase control module is configured to alternately apply a segmented temperature gradient, a slight negative pressure, and a pulsed carrier gas flow based on the initial stationary phase distribution profile of the micro-chromatographic column to reshape a uniformly distributed stationary phase layer;

[0047] a correction factor generation module configured to inject a calibration mixture and a trace amount of inert tracer gas pulse into the uniformly distributed layer of the stationary phase, obtain the calibration peak retention time and the tracer gas lag time difference, and generate a calibration factor set;

[0048] a dynamic parameter control module configured to dynamically adjust the carrier gas flow rate and temperature program according to the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase;

[0049] a separation and detection module configured to load the organic sample to be tested into the micro-chromatographic column under the operating curve conditions and record the peak signal after separation in real time;

[0050] A quantitative output module is configured to output the quantitative results of each component based on the corresponding relationship between the peak signal and the retention time and lag time difference in the correction factor set;

[0051] A processor and a memory, wherein the memory stores a correction factor set and an operation curve generation algorithm.

[0052] On the other hand, the processor is configured to do the following:

[0053] generating an initial profile of the stationary phase distribution based on the continuous pressure waveform data collected by the pressure sensor;

[0054] Controlling the stationary phase regulation module to perform an alternating application operation;

[0055] Control correction factor generation module to obtain retention time and lag time difference;

[0056] Control the dynamic parameter control module to generate the operation curve;

[0057] Control the separation and detection module to record peak signals;

[0058] Control the quantitative output module to generate quantitative results.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] 1. The present invention significantly improves the separation accuracy and stability of the micro gas chromatography system through dynamic regulation of the stationary phase coating distribution and real-time feedback correction mechanism. In order to solve the problem of uniformity control of the stationary phase coating of the micro chromatographic column, the physical distribution characteristics of the stationary phase are directionally adjusted during the flow of the carrier gas by alternating the segmented temperature gradient and micro-negative pressure, so that the coating thickness tends to be consistent on a microscopic scale. Through the synergistic effect of pressure waveform inversion and dynamic parameter adjustment, the separation capacity of the chromatographic column is effectively expanded while ensuring high column efficiency, so that components with different boiling points and polarities in complex organic mixtures can be separated with high resolution, solving the problem of decreased selectivity caused by uneven coating distribution in traditional miniaturization processes.

[0061] 2. Based on a set of correction factors for the temperature-resistance coupling relationship, the thermodynamic response of the stationary phase is dynamically linked to the fluid dynamics. By providing real-time feedback of peak signals and hysteresis time difference data, the system adaptively adjusts the carrier gas flow rate and temperature control program, maintaining the stability of separation parameters under variable temperature and pressure conditions. This effectively suppresses thermal expansion of the stationary phase coating within the microcolumn and interference from carrier gas turbulence, resulting in highly reproducible and accurate quantitative analysis results. This makes it particularly suitable for the rapid and precise detection of trace components and samples with a wide boiling range. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1This is a flow chart of the organic sample analysis method based on micro gas chromatography of the present invention;

[0063] Figure 2 The figure is a schematic structural diagram of a chromatographic analyzer for organic sample analysis based on micro gas chromatography according to the present invention. DETAILED DESCRIPTION

[0064] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0065] Example 1: Figure 1 The present invention provides an organic sample analysis method based on micro gas chromatography, comprising the following steps:

[0066] S1, continuously pre-flushing the carrier gas into the micro-chromatographic column and collecting the pressure waveform to construct the initial profile of the stationary phase distribution;

[0067] S2. Alternately applying segmented temperature gradient, slight negative pressure and directional pulse flow based on the initial profile of the stationary phase distribution to reshape the stationary phase into a uniformly distributed layer;

[0068] S3, injecting a calibration mixture and a trace amount of inert tracer gas pulse into the uniformly distributed layer of the stationary phase, obtaining the calibration peak retention time and the tracer gas lag time difference and generating a calibration factor set;

[0069] S4. Dynamically adjust the carrier gas flow rate and temperature program based on the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase;

[0070] S5. Loading the organic sample to be tested onto the micro-chromatographic column with a uniformly distributed stationary phase layer under the operating curve conditions, completing component separation and recording peak signals in real time;

[0071] S6. Output the quantitative results of each component according to the corresponding relationship between the peak signal, the peak retention time and the tracer gas lag time difference.

[0072] S1. Continuously pre-flushing the micro-chromatographic column with carrier gas and collecting the pressure waveform to construct an initial profile of the stationary phase distribution. The specific implementation is as follows:

[0073] A carrier gas is steadily introduced into the micro-chromatographic column, and a pressure sensor is installed at the inlet to obtain continuous pressure data. The carrier gas is nitrogen or helium with a purity of not less than 99.99%. The flow rate range is calculated according to Poiseuille's law. For example, the flow rate is controlled within the range of, for example, 0.5 mL / min to 2.0 mL / min by multiplying the ratio of the square of the micro-chromatographic column inner diameter to the carrier gas viscosity by a preset pressure difference. The preset pressure difference is, for example, 80% of the maximum allowable pressure difference between the inlet and outlet of the micro-chromatographic column. The maximum allowable pressure difference is set based on the deformation resistance of the micro-chromatographic column material and the pressure bearing capacity of the sealing structure. For example, the elastic modulus of stainless steel is 200 GPa, and the pressure bearing capacity of the fluororubber sealing structure is 10 MPa. The pressure sensor is a piezoresistive micro-electromechanical system sensor, installed at the connection between the micro-chromatographic column inlet and the carrier gas delivery pipeline. The sensor range is, for example, 0 kPa to 100 kPa, and the range is selected based on, for example, 1.5 times the upper limit of the micro-chromatographic column operating pressure. The sampling frequency is set to no less than 200 Hz, for example. This is based on the Nyquist sampling theorem and requires a frequency greater than twice the highest frequency component of the carrier gas pressure fluctuations. For example, if the carrier gas pump's mechanical pulsation fundamental frequency is 20 Hz, the sampling frequency must be greater than 40 Hz. Continuous pressure data is converted to a digital signal using an analog-to-digital converter (ADC), with time as the horizontal axis and pressure as the vertical axis. The ADC has, for example, 16 bits and a conversion rate of 1000 times per second, to ensure that the details of the pressure fluctuations are not distorted.

[0074] The continuous pressure data is filtered to form a pressure waveform curve. The filtering process uses a low-pass digital filter with a cutoff frequency of, for example, 50 Hz. The cutoff frequency is set based on, for example, 1.5 times the mechanical pulsation fundamental frequency of the carrier gas delivery pump. For example, when the mechanical pulsation fundamental frequency of the pump is 20 Hz, the cutoff frequency is set to 30 Hz to cover harmonics. The filtered data is processed in sections using a sliding window method. The window length is set according to the principle of covering at least two complete pressure fluctuation cycles. For example, the window length is set to 100 ms. The overlap ratio of adjacent windows is adjusted to, for example, 50% based on the ratio of the window length to the pressure fluctuation cycle. The data within the window is interpolated using cubic spline to generate a smooth curve, with the density of interpolation nodes being, for example, one data point per millisecond. The vertical axis of the pressure waveform curve is the normalized pressure value. The normalization method is to subtract the initial steady-state pressure value from the raw pressure data and divide it by the maximum pressure fluctuation amplitude. The initial steady-state pressure value is the pressure average value within, for example, 10 to 20 seconds after the carrier gas is introduced. The time window is selected based on the shortest time required for the carrier gas flow to reach a stable state.

[0075] The stationary phase axial resistance distribution is inverted based on the pressure waveform curve and an initial profile of the stationary phase distribution is generated. The inversion process is based on a modified model of Darcy's law, and the input parameters include the filtered pressure waveform curve, carrier gas flow rate, carrier gas viscosity, and the inner diameter of the micro-chromatographic column. The carrier gas viscosity is obtained by a table lookup method. For example, the table lookup data comes from the carrier gas physical property parameter database published by the International Institute for Standardization. The database index parameter is the real-time monitored outer wall temperature of the micro-chromatographic column. The temperature monitoring point is located on the outer wall surface at the axial center of the chromatographic column. The temperature sensor accuracy is, for example, ±0.1°C. The modified model divides the micro-chromatographic column into, for example, 100 to 200 axial micro-segments of equal length. The number of micro-segments is set based on the ratio of the total length of the chromatographic column to the minimum resolvable coating thickness variation range. For example, when the minimum resolvable coating thickness range is 10 μm, the number of micro-segments corresponding to a total column length of 1 m is 100. The pressure drop at each micro-segment is determined through iterative calculations, with the requirement that the difference in resistance coefficients between two consecutive micro-segments be less than, for example, 0.01%. The threshold for this difference is set based on, for example, 1 / 10 of the resistance coefficient measurement error. The output of the stationary phase axial resistance distribution is the resistance coefficient corresponding to each axial position. The resistance coefficient is defined as the product of the stationary phase coating thickness and the carrier gas viscosity divided by the product of the micro-segment length and the column cross-sectional area, and is expressed in Pascal seconds per square meter (Pa·s / m²). The initial profile of the stationary phase distribution is plotted with axial position as the abscissa and the resistance coefficient as the ordinate. Discrete data points are generated and then linearly interpolated to form a continuous curve. The axial position resolution is set to, for example, 1% of the total micro-column length. The resolution is calculated by dividing the total column length by, for example, 100.

[0076] The axial resistance coefficient of the stationary phase at each axial position in the micro-chromatographic column is obtained by inverting the pressure waveform curve. The axial resistance coefficient represents the resistance of the stationary phase coating to the carrier gas flow and has the dimension of Pa·s / m².

[0077] The axial resistance coefficients are arranged in order of the axial position of the chromatographic column to generate an axial resistance coefficient distribution curve. The curve uses the axial position as the horizontal axis (unit: meter) and the resistance coefficient as the vertical axis (unit: Pa·s / m²). The data is stored as a two-dimensional array containing position-resistance coefficients.

[0078] The initial profile of the stationary phase distribution is defined as a discretized expression of the axial resistance coefficient distribution curve, which is used to guide the temperature zone division in step S2 and the porosity gradient calculation in step S3.

[0079] S2. Alternately applying segmented temperature gradient, slight negative pressure and directional pulse flow based on the initial profile of the stationary phase distribution to reshape the stationary phase into a uniformly distributed layer. The specific implementation is as follows:

[0080] Based on the initial profile of the stationary phase distribution, the micro-chromatographic column is divided into multiple independent temperature zones along its axial direction. The temperature gradient difference in each independent temperature zone is within a preset range. Temperature is applied in sections via a thin-film heater attached to the outer wall of the column. The number of independent temperature zones is determined by the fluctuation range of the resistance coefficient in the initial profile of the stationary phase distribution. For example, when the fluctuation amplitude of the resistance coefficient in the axial position exceeds a preset threshold, the corresponding section is divided into an independent temperature zone. The preset threshold is, for example, 20% of the average resistance coefficient. The preset range of the temperature gradient difference is determined by the temperature resistance limit of the micro-chromatographic column material and the thermal stability of the stationary phase. For example, when the stationary phase is polysiloxane, the upper limit of the temperature gradient difference is set to 200°C to prevent thermal decomposition of the material. The heating power of the thin film heater is calculated based on the difference between the temperature zone length and the target temperature gradient. For example, a temperature zone with a length of 10 cm requires an applied power of 5 W / cm² to achieve a gradient of 50°C / cm. The heating power is dynamically adjusted using a PID controller, and the PID parameters are calibrated through a step response experiment. This step response experiment involves applying a step voltage to the thin film heater and recording the temperature curve. The proportional coefficient, integral time, and differential time are adjusted based on the overshoot and settling time of the temperature curve.

[0081] After applying the temperature gradient, a vacuum pump is connected to the outlet of the micro-chromatographic column to generate a slight negative pressure, and its pressure range is adapted to the structural strength of the micro-chromatographic column. The pressure range is determined by the elastic deformation limit of the micro-chromatographic column material. For example, the maximum negative pressure allowed for a stainless steel micro-chromatographic column is -5kPa, and the actual working pressure is set to -5kPa to -0.1kPa to avoid column collapse or seal failure. The vacuum pump's pumping rate is matched with the target pressure decay time constant based on the inner cavity volume of the micro-chromatographic column. For example, when the inner cavity volume is 1mL, the pumping rate is set to 10mL / min, and the time it takes for the pressure to drop from normal pressure to -5kPa is 30 seconds. The operating status of the vacuum pump is monitored in real time by a pressure sensor. When the pressure fluctuation amplitude exceeds the set threshold, the pumping rate is automatically adjusted to maintain pressure stability. The set threshold is, for example, ±5% of the pressure fluctuation amplitude.

[0082] During the micro-negative pressure application, carrier gas is injected into the microcolumn inlet in pulses, with the pulse frequency and duration adapted to the hydrodynamic characteristics of the carrier gas flow. The pulse frequency is determined by Reynolds number calculation. For example, when the Reynolds number is less than 2000, the pulse frequency is set to 1 Hz to 5 Hz to avoid disrupting laminar flow. The Reynolds number is calculated based on the carrier gas density, flow rate, viscosity, and microcolumn inner diameter. For example, a carrier gas density of 1.164 kg / m³, a flow rate of 2 mL / min, a viscosity of 0.01 Pa·s, and an inner diameter of 0.25 mm results in a Reynolds number of 150. The pulse duration is adjusted based on the average residence time of the carrier gas in the microcolumn. For example, when the residence time is 10 seconds, the duration of a single pulse is set to 0.5 to 1 second to ensure that the pulsed carrier gas covers at least 5% of the column volume. The injection of carrier gas pulses is controlled by a high-speed solenoid valve with a response time of less than 10ms. The valve opening is linearly adjusted according to the target flow rate. The flow calibration method is to measure the change in carrier gas volume per unit time at normal pressure. For example, a flow rate of 1 mL per minute measured by a soap film flowmeter corresponds to a valve opening of 30%.

[0083] The application of a temperature gradient, the generation of a slight negative pressure, and the injection of pulsed carrier gas are alternated, with the number of cycles adapted to the uniformity trend of the stationary phase coating thickness distribution until the stationary phase coating thickness distribution meets the preset uniformity standard. The number of cycles is adjusted based on the decay rate of the coating thickness standard deviation after each cycle. For example, the cycle is terminated when the standard deviation decay rate is less than 5%. The maximum number of cycles is limited to 10 to prevent overtreatment. The uniformity standard is verified by offline measurement of the coating thickness using optical interferometry or scanning electron microscopy. For example, a thickness standard deviation of less than 1μm is considered to meet the standard. The optical interferometry method involves cutting the micro-chromatographic column into several 1cm segments, measuring the coating thickness of each segment, and calculating the standard deviation. If an abnormal temperature or pressure limit is detected during the cycle, a protection mechanism is triggered to pause the process and issue an alarm. Abnormal conditions, such as a temperature exceeding the stationary phase decomposition temperature by 10°C or a pressure below -5kPa, involve disconnecting the power to the film heater and activating the pressure relief valve to release the negative pressure.

[0084] S3, injecting the calibration mixture and a trace amount of inert tracer gas pulse into the uniformly distributed stationary phase layer, obtaining the calibration peak retention time and the tracer gas lag time difference and generating a calibration factor set, which is specifically implemented as follows:

[0085] A calibration mixture and inert tracer gas pulses are alternately injected into the uniformly distributed stationary phase layer. The timing of the calibration mixture injection and the interval between the tracer gas pulses are dynamically adjusted based on the porosity gradient of the uniformly distributed stationary phase layer. The porosity gradient is calculated from the axial drag coefficient distribution curve generated in step S1. The porosity gradient is calculated as the ratio of the difference in drag coefficients between two adjacent axial positions divided by the distance between the positions. For example, if the drag coefficients at position A are 1.2 Pa·s / m² and at position B are 1.5 Pa·s / m², with a distance of 0.01 m, the porosity gradient is 30 Pa·s / m³. When the porosity gradient exceeds a preset threshold, the interval between the calibration mixture and tracer gas pulses is shortened. For example, for every 10 Pa·s / m³ increase in the porosity gradient, the interval is reduced by 5%. The preset threshold is set based on the stationary phase material type. For example, the threshold for polysiloxane stationary phases is 20 Pa·s / m³, and for metal-organic frameworks (MOFs), it is 50 Pa·s / m³.

[0086] When the porosity gradient exceeds a preset threshold, the injection interval between the calibration mixture and the tracer gas pulse is shortened. For example, for every 0.1 / mm increase in the porosity gradient, the interval is reduced by 10%. The preset threshold is calculated based on the average pore size of the stationary phase material within the microcolumn. For example, when the average pore size is 100 nm, the preset threshold is set to 0.05 / mm. The calibration mixture contains target components with boiling points covering the sample to be analyzed. For example, the calibration mixture is a mixture of C8-C16 normal alkanes. The inert tracer gas is argon, which is significantly different from the carrier gas type, to ensure signal separation in the thermal conductivity detector. The injection of the calibration mixture and tracer gas is controlled by a high-speed solenoid valve with a switching time of less than 10 ms. The injection flow rate is regulated by a mass flow controller with a flow rate error of less than ±1%.

[0087] A thermal conductivity detector (TCD) was used to simultaneously capture the peaks of the different boiling point components in the calibration mixture and the diffusion peak of the tracer gas. The peak time and tail time of each peak were extracted. The TCD's time resolution was set to 0.05 seconds to fully capture peak details. The time resolution was determined by the detector's bridge response time and the bandwidth of the signal amplification circuit. The bridge response time was calculated based on the thermal conductivity and heat capacity of the hot wire material. For example, for a tungsten wire with a thermal conductivity of 173 W / (m·K) and a heat capacity of 0.13 J / (g·K), the response time was 0.03 seconds. The peak time was defined as the point where the maximum slope of the rising edge of the peak intersected the baseline. The maximum slope point was calculated using the three-point difference method. For example, a peak was defined when the slope difference between three adjacent data points was less than 0.1%. The tail time was defined as the time from the falling edge of the peak to 10% of the peak height. The 10% peak height point was determined using linear interpolation. The difference between the peak and tail times is calculated as the time difference. For example, if a component has a peak time of 100 seconds and a tail time of 110 seconds, the time difference is 10 seconds. Baseline calibration is performed by averaging the steady-state signal over 30 seconds without sample injection. Baseline drift compensation is achieved using a sliding window averaging filter with a window length of 5 seconds.

[0088] Based on the time domain difference between the peak time and the tail time, combined with the axial temperature distribution data of the uniformly distributed layer of the stationary phase, the diffusion resistance compensation coefficient of each boiling point component is constructed. The axial temperature distribution data comes from the temperature control unit record when the segmented temperature gradient is applied in step S2, such as the actual temperature value and time-temperature change curve of each independent temperature zone. The time synchronization accuracy of the temperature data is 0.1 second, and it is synchronized with the signal acquisition clock of the thermal conductivity detector. The calculation formula of the diffusion resistance compensation coefficient is expressed as the ratio of the time domain difference to the temperature gradient at the corresponding axial position. For example, if the time domain difference is 10 seconds and the temperature gradient of the section is 50℃ / m, the diffusion resistance compensation coefficient is 0.2 seconds·m / ℃. The temperature gradient is calculated by dividing the temperature difference between two adjacent temperature zones by the length of the temperature zone. For example, if the temperature of temperature zone A is 150℃, the temperature of temperature zone B is 120℃, and the length of the temperature zone is 0.1m, the temperature gradient is 300℃ / m. When the temperature gradient changes beyond the set range, the temperature data abnormality mark is automatically triggered. The set range is, for example, when the temperature difference between adjacent temperature zones exceeds 30°C. After the abnormality mark is triggered, the correction process is suspended and the temperature calibration program is started. The calibration program includes re-measuring the actual temperature of the temperature zone and updating the axial temperature distribution data.

[0089] Diffusion resistance compensation coefficients are matched against theoretical values ​​in a standard retention time database to generate a set of correction factors that incorporate temperature-resistance coupling relationships. The matching is prioritized based on the polarity of the boiling point components. The standard retention time database is a pre-established retention time dataset containing multiple compounds under different temperature and stationary phase conditions. For example, baseline data is generated by measuring the retention times of C8-C16 alkanes on a polysiloxane stationary phase. Data acquisition conditions are a carrier gas flow rate of 1 mL / min and a temperature gradient of 50°C / m. The matching process prioritizes components with higher polarity, such as those containing hydroxyl or carboxylic acid groups. Priority is based on differences in adsorption energy on the stationary phase. Adsorption energy is estimated using the compound's octanol-water partition coefficient (logP), which is determined experimentally by shake-flask methods or obtained from the PubChem database. For example, a logP value less than 3 is considered highly polar and is prioritized for matching. The correction factor set is stored in a two-dimensional matrix, with rows corresponding to unique identifiers of the boiling point components and columns containing diffusion resistance compensation coefficients, theoretical retention times, and temperature-resistance coupling coefficients. Matrix data is stored in CSV format, supporting external software calls and visual analysis.

[0090] When the deviation of the diffusion resistance compensation coefficient of a component in the calibration mixture from the theoretical value in the database exceeds the allowable threshold, the calibration failure mark is triggered and the injection process is automatically repeated. The allowable threshold is, for example, 10% of the theoretical value. The interval time of the repeated injection process is adjusted according to the thermal stability of the uniformly distributed layer of the stationary phase. For example, the maximum number of repetitions for the polysiloxane stationary phase is 5 times, and the interval time for each time is at least 2 minutes to prevent coating degradation. The calibration failure mark is linked to the dynamic adjustment of the carrier gas flow rate in step S4. The flow rate adjustment amplitude is calculated according to the degree of deviation. For example, for every 5% increase in deviation, the flow rate increases by 5%. In extreme cases, such as when the calibration failure is triggered three times in a row, the system automatically switches to the backup calibration mixture and sends a maintenance alarm. The backup calibration mixture uses components with the same boiling point range but lower polarity, such as a perfluoroalkane mixture.

[0091] S4. Dynamically adjust the carrier gas flow rate and temperature program according to the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase. The specific implementation is as follows:

[0092] Based on the temperature-resistance coupling relationship in the correction factor set, the boiling point components of the sample to be tested are divided into two categories of high priority and low priority according to polarity priority. The polarity priority is divided according to the critical value of the octanol-water partition coefficient set when the correction factor set is generated in step S3. For example, when the logP value of the component is less than 3, it is classified as a high priority component, and the rest are low priority components. The temperature-resistance coupling relationship in the correction factor set comes from the mapping result of the diffusion resistance compensation coefficient and the theoretical retention time in step S3, which is specifically manifested as the product of the temperature gradient optimization coefficient and the resistance compensation value corresponding to each boiling point component. The product is used to quantify the separation response characteristics of the component under different temperatures and coating resistances. The temperature gradient optimization coefficient is calibrated by applying the segmented temperature gradient of step S2. The calibration method is to measure the retention time deviation of the reference component under different temperature gradients and select the coefficient value corresponding to the minimum deviation.

[0093] For high-priority components, the carrier gas flow rate is increased stepwise along the axial position of the uniformly distributed stationary phase layer based on their corresponding diffusion resistance compensation coefficients. The magnitude of the flow rate increase is positively correlated with the compensation coefficient. The diffusion resistance compensation coefficient is derived from the calculation results in step S3 and has the unit of seconds·meters per degree Celsius (s·m / °C). It is calculated as the time difference (seconds) divided by the temperature gradient (°C / m) at the corresponding axial position. For example, for a time difference of 10 seconds and a temperature gradient of 50°C / m, the compensation coefficient is 0.2 s·m / °C. The flow rate increase is calculated by multiplying the compensation coefficient by the adjusted gain factor for the base flow rate. The gain factor is determined through resolution optimization experiments. For example, with an initial gain factor of 0.5, a mixture of benzene and toluene is injected. When the resolution reaches 1.5, this is recorded as the effective gain factor. The base flow rate is the initial carrier gas flow rate reference value set in step S1, for example, an initial flow rate of 0.5 mL / min. The adjusted flow rate upper limit does not exceed the maximum range of the mass flow controller (e.g., 5 mL / min).

[0094] For low-priority components, combined with the axial temperature distribution data of the uniformly distributed layer of the stationary phase, the temperature ramp rate range of the temperature program is symmetrically expanded with each temperature gradient as the median. The axial temperature distribution data comes from the historical records of the segmented temperature control in step S2. For example, the preset temperature gradient of a certain temperature zone is 50°C / m, and the expanded temperature ramp rate range is set to 40°C / m to 60°C / m. The expansion amplitude is determined based on the actual temperature control accuracy of the temperature zone. For example, when the temperature control accuracy is ±1°C, the expansion amplitude is ±20%. Symmetrical expansion is achieved through dual-interval linear mapping. The mapping formula is that the lower limit of the expansion is equal to the median minus the expansion amplitude, and the upper limit of the expansion is equal to the median plus the expansion amplitude. When the temperature gradient exceeds the glass transition point of the material, the temperature protection mechanism is triggered and the upper limit of the expansion amplitude is locked. For example, when the glass transition temperature of the polysiloxane stationary phase is 300°C, the upper limit of the expansion is 280°C. The locking logic is that if the current temperature gradient exceeds the upper limit, it is automatically replaced by the upper limit value.

[0095] The adjusted carrier gas flow rate and temperature program are reorganized according to the elution order of the boiling point components to generate an operating curve containing segmented flow rate control instructions and a nonlinear temperature gradient. The reorganization process ensures that the flow rate and temperature change rate between adjacent segments are continuous and differentiable. The elution order is predicted by the theoretical data of the standard retention time database in step S3. For example, when the main peak retention time is known to be 10 minutes, the corresponding carrier gas flow rate adjustment segment start time is 9.5 minutes. The flow rate change rate between adjacent segments is constrained by the fluid continuity equation. Specifically, the flow rate difference between adjacent time nodes does not exceed 20% of the flow rate of the previous segment. For example, when the flow rate of the previous segment is 1 mL / min, the flow rate of the adjacent segment is adjusted to a maximum of 1.2 mL / min. The temperature change rate is limited by a derivative smoothing algorithm. For example, the temperature slope difference between adjacent temperature intervals does not exceed 5°C / min. The slope difference is calculated by the three-point difference method with a difference step size of 0.1 minutes. The reorganized run curve uses time as the horizontal axis and synchronously stores the carrier gas flow target value and temperature setting value. The data format is a multi-column CSV table, which supports import and execution of standard chromatography control software (such as Agilent ChemStation).

[0096] When parameters in a run profile exceed the hardware's capabilities, adaptive degradation mode is triggered. For example, if the requested flow rate exceeds the maximum range of the mass flow controller (e.g., 5 mL / min), adaptive degradation mode scales the flow rates of all segments by a factor equal to the maximum range divided by the maximum requested flow rate. For example, if the requested maximum flow rate is 6 mL / min, the factor is 5 / 6, which is approximately 0.833. All segment flow rates are multiplied by 0.833, and the exhaust time is simultaneously reduced to maintain separation efficiency. The degraded run profile generates a log mark and transmits it to the user interface, prompting manual review. In extreme cases, such as when the temperature program exceeds the upper tolerance limit of the heating membrane (e.g., 350°C), the system terminates the analysis and initiates forced cooling at a rate of 10°C / min until the temperature returns to a safe threshold (e.g., 50°C). During the cooling process, the temperature sensor feedback is monitored in real time. If the cooling rate is insufficient, auxiliary fans are activated to dissipate heat.

[0097] S5. Loading the organic sample to be tested onto the micro-chromatographic column with the uniformly distributed stationary phase layer under the operating curve conditions, completing component separation and recording peak signals in real time, specifically implemented as follows:

[0098] The organic sample to be tested is loaded into the inlet of the microchromatographic column via a microliter syringe, with the loading volume adapted to the adsorption capacity of the uniformly distributed stationary phase layer. The adsorption capacity is calculated based on the coating thickness and surface area of ​​the uniformly distributed stationary phase layer in step S2. For example, when the coating thickness is 1 micron and the surface area is 0.5 square meters per gram, the adsorption capacity is 0.5 microliters per milligram. The loading volume is set to 70% of the maximum adsorption capacity to avoid overloading. The injection accuracy of the microliter syringe is ±0.1 microliter, and the injection speed is adjusted by the fluid resistance at the inlet end of the microchromatographic column. The fluid resistance is derived from the pressure waveform curve inversion result of step S1. For example, when the inlet pressure fluctuation amplitude is 5 kilopascals, the injection speed is controlled at 0.2 microliters per second to ensure uniform sample dispersion.

[0099] According to the segmented flow rate control instructions in the operating curve, the carrier gas flow rate is switched to the target value step by step, and the time interval of the switching process matches the theoretical outflow time window of the boiling point component. The theoretical outflow time window comes from the timing prediction data in the operating curve generated in step S4, and the timing prediction data is generated by mapping the correction factor set and the theoretical retention time in step S3. For example, when the theoretical retention time of a component is 10 minutes, the flow rate switching time window is set to 9.5 minutes to 10.5 minutes. The transition time of the flow rate switching is determined according to the step response characteristics of the carrier gas flow controller, and the step response characteristics are calibrated by the proportional scaling experiment in the adaptive degradation mode in step S4. For example, when the controller step response time is 0.5 seconds, the transition time is set to 2 seconds to avoid sudden changes in flow. The target value error range of the flow controller is less than ±1%, and it is calibrated in real time by a closed-loop proportional integral differential control algorithm. The parameters of the proportional integral differential control algorithm are optimized by the temperature control experimental data of step S2.

[0100] The nonlinear temperature gradient program in the synchronous operation curve controls the temperature rise rate of the thin film heater on the outer wall of the micro-chromatographic column, and the rate of change is consistent with the temperature gradient difference between adjacent segments. The temperature rise rate is calculated by the ratio of the temperature gradient difference between adjacent segments to the time interval defined in step S4. For example, when the temperature gradient difference between adjacent segments is 50 degrees Celsius per meter and the time interval is 5 minutes, the temperature rise rate is set to 10 degrees Celsius per meter per minute. The temperature control accuracy of the thin film heater is ±0.5 degrees Celsius, and the temperature feedback signal is collected through a platinum resistance sensor. The sampling frequency of the platinum resistance sensor is 10 Hz to ensure that the details of temperature fluctuations are captured. When the actual temperature deviates from the target value by more than 2 degrees Celsius, the temperature compensation mechanism is triggered. The compensation amount is the integral accumulation of the deviation value. The integral time constant is calibrated to 30 seconds through the segmented temperature gradient experiment in step S2.

[0101] The peak signals of the separated components are captured by a thermal conductivity detector. The peak signals are recorded in real time as time-voltage waveforms, with the waveform sampling frequency adapted to the minimum resolution of the peak half-width. The bridge excitation voltage of the thermal conductivity detector is 5 volts, the signal amplification factor is 1000 times, and the noise level is less than 1 microvolt. The noise level is verified using the baseline calibration data from step S1. The minimum resolution of the half-width is determined by the Nyquist sampling theorem. For example, when the minimum half-width is 2 seconds, the sampling frequency is at least 10 Hz to ensure that each peak contains 20 data points. The baseline calibration method is to collect a 60-second steady-state signal average in the absence of sample injection. Baseline drift compensation is achieved by sliding window averaging filtering with a window length of 10 seconds and an overlap rate of 50%. The filtering parameters are optimized using the calibration mixture peak data from step S3.

[0102] The recorded peak signal is time-series aligned with the theoretical retention time in the correction factor set to generate a peak sequence to be analyzed after time axis calibration. Time sequence alignment is achieved by linear interpolation, and the node spacing of the linear interpolation method is adjusted according to the timing prediction accuracy in the running curve of step S4. For example, when the theoretical retention time prediction error is 0.3 seconds, the node spacing is set to 0.1 seconds. The aligned peak sequence is stored as a three-column data matrix of time-voltage-temperature. The data format is a comma-separated value file, which supports import by third-party analysis software. If peak overlap or baseline drift exceeding the threshold is detected during the alignment process, the peak separation algorithm is triggered. The peak separation threshold is set to the slope change rate at 10% of the peak height exceeding 5% per second. The slope change rate is calculated by the three-point difference method, and the difference step size is 0.05 seconds.

[0103] When a carrier gas flow rate switching delay or temperature exceeding the limit is detected, the adaptive error correction mechanism is triggered. For example, when the flow rate switching delay exceeds 20% of the theoretical time window, the duration of the current flow rate segment is automatically extended to the starting point of the next window, and the timing parameters of the subsequent segments are recalculated. The calculation logic of the timing parameters is consistent with the operation curve generation algorithm of step S4. When the temperature exceeds the limit, if the deviation lasts for more than 30 seconds, the analysis process is suspended and the gradient cooling program is started. The cooling rate is 5 degrees Celsius per minute until the temperature returns to a safe range. The safety range is set according to the thermal stability of the stationary phase in step S2. For example, the upper limit of the safe temperature of the polysiloxane stationary phase is 280 degrees Celsius. The error correction log is recorded in real time and transmitted to the user terminal. The log includes a timestamp, anomaly type and processing measures. The log format is compatible with the operation curve data of step S4.

[0104] S6. Output the quantitative results of each component according to the corresponding relationship between the peak signal, the peak retention time and the tracer gas lag time difference. The specific implementation is as follows:

[0105] The peak sequence to be analyzed after time axis calibration is baseline corrected, and the peak signal after correction is calculated by an integration algorithm for each peak area. The baseline correction adopts a sliding window average filtering method, and the length of the sliding window is determined by twice the half-width of the peak shape. For example, when the half-width is 5 seconds, the window length is 10 seconds, and the overlap rate between windows is 50%. The filtered baseline is fitted to the peak-valley point by the least squares method. The peak-valley point is defined as the position where the signal value on both sides of the peak shape is lower than 5% of the peak height for the first time. The fitting residual threshold is set to 1% of the peak height, for example, when the peak height is 1000mV, the residual threshold is 10mV. When the residual exceeds the threshold, the peak distortion mark is triggered and the peak signal recording process of step S5 is re-executed. The integration algorithm is a trapezoidal method, and the integration interval is from the peak starting point to the peak end point. The judgment condition of the peak starting point and the end point is that the signal value reaches 5% of the peak height. The integration result is stored as a peak area-time correspondence table, and the data format is a two-column comma-separated value file, which is compatible with the output data of step S5.

[0106] Based on the temperature-resistance coupling relationship in the correction factor set, the theoretical retention time and diffusion resistance compensation coefficient corresponding to each peak are matched to generate a conversion factor between peak area and concentration. The temperature-resistance coupling relationship comes from the mapping data of the diffusion resistance compensation coefficient and the theoretical retention time in step S3. The diffusion resistance compensation coefficient is calculated by the ratio of the time domain difference and the temperature gradient in step S3. For example, when the time domain difference is 10 seconds and the temperature gradient is 50 degrees Celsius per meter, the diffusion resistance compensation coefficient is 0.2 seconds·meter per degree Celsius. The calculation formula of the conversion factor is the peak area divided by the product of the diffusion resistance compensation coefficient and the theoretical retention time. For example, when the peak area is 1000mV·s and the theoretical retention time is 600 seconds, the conversion factor is 1000 / (0.2×600)=8.33. The matching process is controlled by the time axis alignment error tolerance, which is set to 0.5% of the theoretical retention time. For example, when the theoretical retention time is 600 seconds, the tolerance is 3 seconds. When the actual retention time deviation exceeds 3 seconds, it is determined that the match has failed and the correction factor set update process of step S3 is triggered.

[0107] The time axis alignment error of the conversion factor is adjusted by combining the compensation for the tracer gas delay time difference with the peak retention time. The compensation amount is calculated by multiplying the delay time difference by the carrier gas flow rate. The delay time difference is derived from the temporal difference between the tracer gas peak apex and the calibration mixture peak apex in step S3, for example, a temporal difference of 2 seconds. The carrier gas flow rate is derived from the segmented flow rate target value in the run curve generated in step S4, for example, a target value of 1 ml / min. The compensation amount is calculated as the ratio of the delay time difference to the carrier gas flow rate, for example, 2 seconds / (1 mL / min) = 120 seconds·min / mL, which is adjusted to a dimensionless scaling factor using a unit conversion factor. For example, when the carrier gas flow rate is 1 mL / min, the scaling factor is 2 seconds / (1 mL / min × 60 seconds / min) = 0.033. The time axis alignment error is adjusted by multiplying the conversion factor by the inverse of the scaling factor. For example, when the conversion factor is 8.33, the adjusted conversion factor is 8.33 × (1 / 0.033) = 252.4. When the proportional factor exceeds a preset threshold, for example, exceeds 10% of the peak volume, it is determined that the flow rate control is abnormal and the operation curve regeneration process of step S4 is triggered.

[0108] The adjusted conversion factor is multiplied by the peak area to obtain the concentration of each component. The concentration values ​​are sorted by boiling point elution order and output to a quantitative results table. The concentration is calculated as: peak area multiplied by the conversion factor. For example, if the peak area is 1000 mV·s and the conversion factor is 252.4, the concentration is 1000 × 252.4 = 252400 ppm. The sorting logic is based on the elution order of the components in the run curve from step S4; for example, low-boiling-point components elute first in the first row of the corresponding table. The quantitative results table contains the component name, retention time, concentration value, and error range. The error range is calculated using the confidence interval of the calibration factor set from step S3. The confidence interval is determined based on the standard deviation of multiple calibration experiments. For example, at a 95% confidence level, the error range is ±2.5%. The results table is exported as a comma-separated value file, compatible with the data matrix from step S5, allowing direct import into third-party analysis software (such as Agilent MassHunter) to generate a test report.

[0109] When an abnormal conversion factor is detected or the concentration value exceeds the range, the concentration calibration rollback mechanism is triggered. For example, when the conversion factor exceeds the preset upper limit (for example, 500), the most recently valid correction factor set in step S3 is automatically called for recalculation. If the rollback fails three times in a row, the process is terminated and manual intervention is prompted. When the concentration value exceeds the range, the dilution factor is dynamically adjusted according to the loading volume data of step S5. For example, when the initial loading volume is 0.5 microliters, the dilution factor is set to 2 and the concentration is recalculated. The adjustment range of the dilution factor does not exceed 10 times the initial value to avoid distortion. The calibration log records all abnormal events and handling measures. The log format is consistent with the error correction log of step S5, including timestamp, abnormality type, processing parameters and result status. The log file is stored in standard JSON format for easy traceability analysis.

[0110] This embodiment overcomes the static control limitations of traditional chromatographic separations through a multi-step collaborative mechanism. During the initial stationary phase profile construction phase, a coupled design combining pressure waveform inversion with dynamic temperature gradient application overcomes the nonlinear interference of the coating distribution within the micro-chromatographic column. During the separation parameter optimization phase, the temperature-resistance coupling relationship of the correction factor set is reorganized into a nonlinear operating curve with the carrier gas flow rate and temperature program, achieving dynamic matching of the stationary phase thermodynamic and hydrodynamic responses. During the real-time separation and quantification phase, the feedback loop between hysteresis compensation and baseline drift correction addresses the cumulative error problem of signal drift and retention time shift in miniaturized devices. The data transfer between each step forms a closed-loop logic. For example, the correction factor set is generated based on the stationary phase distribution parameters and inversely constrains the dynamic adjustment range of the operating curve, while the real-time recorded peak signals provide verification data for the iterative update of the correction factor set. This multi-parameter cross-correction mechanism cannot be derived through conventional sequential optimization.

[0111] Example 2: Figure 2 A schematic structural diagram of a chromatographic analyzer for organic sample analysis based on micro gas chromatography of the present invention is provided. The chromatographic analyzer for organic sample analysis based on micro gas chromatography comprises:

[0112] a carrier gas supply module configured to continuously supply carrier gas to the micro chromatographic column and connected to a pressure sensor at the inlet end to collect continuous pressure waveform data;

[0113] The stationary phase control module is configured to alternately apply a segmented temperature gradient, a slight negative pressure, and a pulsed carrier gas flow based on the initial stationary phase distribution profile of the micro-chromatographic column to reshape a uniformly distributed stationary phase layer;

[0114] a correction factor generation module configured to inject a calibration mixture and a trace amount of inert tracer gas pulse into the uniformly distributed layer of the stationary phase, obtain the calibration peak retention time and the tracer gas lag time difference, and generate a calibration factor set;

[0115] a dynamic parameter control module configured to dynamically adjust the carrier gas flow rate and temperature program according to the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase;

[0116] a separation and detection module configured to load the organic sample to be tested into the micro-chromatographic column under the operating curve conditions and record the peak signal after separation in real time;

[0117] A quantitative output module is configured to output the quantitative results of each component based on the corresponding relationship between the peak signal and the retention time and lag time difference in the correction factor set;

[0118] A processor and a memory, wherein the memory stores a correction factor set and an operation curve generation algorithm, and the processor is configured to perform the following operations:

[0119] generating an initial profile of the stationary phase distribution based on the continuous pressure waveform data collected by the pressure sensor;

[0120] Controlling the stationary phase regulation module to perform an alternating application operation;

[0121] Control correction factor generation module to obtain retention time and lag time difference;

[0122] Control the dynamic parameter control module to generate the operation curve;

[0123] Control the separation and detection module to record peak signals;

[0124] Control the quantitative output module to generate quantitative results.

[0125] The carrier gas supply module continuously delivers nitrogen or helium to the micro-chromatographic column via a mass flow controller at a flow rate of 0.5-5 mL / min. A Honeywell ABP2 series pressure sensor with a range of 0-100 kPa and a sampling frequency of 200 Hz is used. The collected continuous pressure waveform data is used to generate an initial stationary phase distribution profile using a Darcy's law inversion algorithm. The stationary phase control module comprises a Kapton thin-film heater array attached to the column's outer wall, with a temperature control range of 50-300°C and an accuracy of ±0.5°C. A vacuum pump connected to the column outlet generates a slight negative pressure of -5 kPa to -0.1 kPa. Pulsed carrier gas flow is controlled by a Lee Company LF series high-speed solenoid valve, with a single pulse duration of 0.1-1 second. The correction factor generation module injects a C8-C16 normal alkane calibration mixture and a helium tracer pulse into the uniformly distributed stationary phase layer. A thermal conductivity detector records the calibrated peak retention time and lag time with a time resolution of 0.05 seconds to generate a set of correction factors that incorporate temperature-resistance coupling. The dynamic parameter control module adjusts the carrier gas flow rate and temperature program based on the calibration factor set, generating segmented flow rate instructions (0.5-5 mL / min) and a nonlinear temperature gradient (temperature difference between adjacent segments ≤ 50°C). The separation and detection module loads the sample under the operating curve conditions, records the peak signal in real time, and eliminates baseline drift through sliding window averaging filtering. The quantitative output module multiplies the peak area by the conversion factor to generate the concentration value and outputs a CSV-formatted result table containing the component name, retention time, and error range (±2.5%). The processor executes the control logic using an STM32F7 series microcontroller, and the memory uses FLASH to store the calibration factor set and operating curve. Exception handling includes triggering a gradient cooling (5°C / min) when the temperature exceeds the limit and scaling the instruction ratio when the flow rate exceeds the limit.

[0126] The calculations involved in the embodiments are all dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to actual conditions.

[0127] It should be noted that the present invention can be deployed on the device itself to implement embedded applications, and can also be run on a PC or other terminal with a user interface, thereby meeting various hardware environments and usage requirements.

[0128] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0129] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0130] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0131] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0132] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0133] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0134] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

[0135] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An organic sample analysis method based on micro gas chromatography, characterized in that: include: S1, continuously pre-flushing the carrier gas into the micro-chromatographic column and collecting the pressure waveform to construct the initial profile of the stationary phase distribution; S2. Alternately applying segmented temperature gradient, slight negative pressure and directional pulse flow based on the initial profile of the stationary phase distribution to reshape the stationary phase into a uniformly distributed layer; S3, injecting a calibration mixture and a trace amount of inert tracer gas pulse into the uniformly distributed layer of the stationary phase, obtaining the calibration peak retention time and the tracer gas lag time difference and generating a calibration factor set; S4. Dynamically adjust the carrier gas flow rate and temperature program based on the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase; S5. Loading the organic sample to be tested onto the micro-chromatographic column with a uniformly distributed stationary phase layer under the operating curve conditions, completing component separation and recording peak signals in real time; S6. Output the quantitative results of each component according to the corresponding relationship between the peak signal, the peak retention time and the tracer gas lag time difference.

2. The organic sample analysis method based on micro gas chromatography according to claim 1, characterized in that: Continuously pre-flushing carrier gas into the micro-chromatographic column and collecting pressure waveforms to construct an initial profile of the stationary phase distribution, including: The carrier gas is stably introduced into the micro-chromatographic column and a pressure sensor is set at the inlet end to obtain continuous pressure data; The continuous pressure data is filtered to form a pressure waveform curve; The stationary phase axial resistance distribution is inverted based on the pressure waveform curve and the initial stationary phase distribution profile is generated.

3. The organic sample analysis method based on micro gas chromatography according to claim 2, characterized in that: Based on the initial profile of the stationary phase distribution, segmented temperature gradient, slight negative pressure and directional pulse flow are alternately applied to reshape the stationary phase into a uniform distribution layer, including: Based on the initial profile of the stationary phase distribution, the micro-chromatographic column is divided into multiple independent temperature zones along the axial direction. The temperature gradient difference of each independent temperature zone is within a preset range. The temperature is applied in sections by a thin film heater attached to the outer wall of the chromatographic column. After applying the temperature gradient, a vacuum pump is connected to the outlet of the micro-chromatographic column to generate a slight negative pressure, the pressure range of which is adapted to the structural strength of the micro-chromatographic column; During the micro-negative pressure period, carrier gas is injected into the inlet of the micro-chromatographic column in a pulsed form, and the pulse frequency and duration are adapted to the fluid dynamics characteristics of the carrier gas flow; The temperature gradient application, slight negative pressure generation and pulsed carrier gas injection are performed alternately, and the number of cycles is adapted to the uniformity change trend of the stationary phase coating thickness distribution until the stationary phase coating thickness distribution meets the preset uniformity standard.

4. The organic sample analysis method based on micro gas chromatography according to claim 3, characterized in that: Inject a calibration mixture and a trace amount of inert tracer gas pulse into the uniformly distributed layer of the stationary phase to obtain the calibration peak retention time and tracer gas lag time difference and generate a calibration factor set, including: Alternately injecting a calibration mixture and pulses of inert tracer gas into a uniformly distributed layer of stationary phase; The thermal conductivity detector is used to synchronously capture the separation peaks of the components with different boiling points in the calibration mixture and the diffusion peaks of the tracer gas, and the peak time of each separation peak and the tailing time of the diffusion peak are extracted; Based on the time domain difference between the peak time and the tail time, combined with the axial temperature distribution data of the uniformly distributed layer of the stationary phase, the diffusion resistance compensation coefficient of each boiling point component is constructed; The diffusion resistance compensation coefficients were matched step by step with the theoretical values ​​in the standard retention time database to generate a correction factor set containing the temperature-resistance coupling relationship. The priority of the step-by-step matching was sorted according to the polarity difference of the boiling point components.

5. The organic sample analysis method based on micro gas chromatography according to claim 4, characterized in that: The injection timing of the calibration mixture and the interval between the tracer gas pulses are dynamically adjusted based on the porosity gradient of the uniformly distributed layer of the stationary phase.

6. The organic sample analysis method based on micro gas chromatography according to claim 4, characterized in that: Dynamically adjust the carrier gas flow rate and temperature program based on the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase, including: Based on the temperature-resistance coupling relationship in the correction factor set, the boiling point components of the sample to be tested are divided into two categories according to polarity priority: high priority and low priority; For high-priority components, the carrier gas flow rate is increased step by step along the axial position of the stationary phase uniform distribution layer according to the corresponding diffusion resistance compensation coefficient. The increase in flow rate is positively correlated with the compensation coefficient. For low-priority components, combined with the axial temperature distribution data of the uniformly distributed layer of the stationary phase, the heating rate range of the temperature program is symmetrically expanded with each temperature gradient as the median value; The adjusted carrier gas flow rate and temperature program are reorganized according to the elution order of the boiling point components to generate an operating curve containing segmented flow rate control instructions and nonlinear temperature gradients. The reorganization process ensures that the flow rate and temperature change rates between adjacent segments are continuous and differentiable.

7. The organic sample analysis method based on micro gas chromatography according to claim 6, characterized in that: Under the operating curve conditions, the organic sample to be tested is loaded onto the micro-chromatographic column with a uniformly distributed stationary phase layer to complete component separation and record peak signals in real time, including: The organic sample to be tested is loaded into the inlet of the micro-chromatographic column through a microliter syringe, and the loading volume is adapted to the adsorption capacity of the uniformly distributed layer of the stationary phase; According to the segmented flow rate control instructions in the operation curve, the carrier gas flow rate is switched to the target value segment by segment, and the time interval of the switching process matches the theoretical elution time window of the boiling point component; The nonlinear temperature gradient program in the synchronous operation curve controls the temperature rise rate of the thin film heater on the outer wall of the micro-chromatographic column. The rate of change is consistent with the temperature gradient difference between adjacent segments. The peak signals of the separated components are captured by a thermal conductivity detector and recorded in real time as time-voltage waveforms. The waveform sampling frequency is adapted to the minimum resolution of the peak half-peak width. The recorded peak signals are time-series aligned with the theoretical retention times in the calibration factor set to generate a time-axis-calibrated peak sequence to be analyzed.

8. The organic sample analysis method based on micro gas chromatography according to claim 7, characterized in that: According to the corresponding relationship between peak signal, peak retention time and tracer gas lag time, the quantitative results of each component are output, including: Baseline correction is performed on the peak sequence to be analyzed after time axis calibration, and the peak area of ​​each peak is calculated by the integration algorithm after the correction of the peak signal; Based on the temperature-resistance coupling relationship in the correction factor set, the theoretical retention time corresponding to each peak is matched with the diffusion resistance compensation coefficient to generate the conversion factor between peak area and concentration; The time axis alignment error of the conversion factor is adjusted by combining the compensation of the tracer gas lag time difference to the peak retention time. The compensation amount is calculated by multiplying the lag time difference by the carrier gas flow rate. The adjusted conversion factor is multiplied by the peak area to obtain the concentration value of each component. The concentration values ​​are sorted according to the elution order of the boiling point components and the quantitative result table is output.

9. A chromatographic analyzer for organic sample analysis based on micro gas chromatography, used to implement the organic sample analysis method based on micro gas chromatography according to any one of claims 1 to 8, characterized in that: include: a carrier gas supply module configured to continuously supply carrier gas to the micro chromatographic column and connected to a pressure sensor at the inlet end to collect continuous pressure waveform data; The stationary phase control module is configured to alternately apply a segmented temperature gradient, a slight negative pressure, and a pulsed carrier gas flow based on the initial stationary phase distribution profile of the micro-chromatographic column to reshape a uniformly distributed stationary phase layer; a correction factor generation module configured to inject a calibration mixture and a trace amount of inert tracer gas pulse into the uniformly distributed layer of the stationary phase, obtain the calibration peak retention time and the tracer gas lag time difference, and generate a calibration factor set; a dynamic parameter control module configured to dynamically adjust the carrier gas flow rate and temperature program according to the correction factor set to establish an operating curve that matches the uniform distribution layer of the stationary phase; a separation and detection module configured to load the organic sample to be tested into the micro-chromatographic column under the operating curve conditions and record the peak signal after separation in real time; A quantitative output module is configured to output the quantitative results of each component based on the corresponding relationship between the peak signal and the retention time and lag time difference in the correction factor set; A processor and a memory, wherein the memory stores a correction factor set and an operation curve generation algorithm.

10. The chromatograph for organic sample analysis based on micro gas chromatography according to claim 9, characterized in that: The processor is configured to do the following: generating an initial profile of the stationary phase distribution based on the continuous pressure waveform data collected by the pressure sensor; Controlling the stationary phase regulation module to perform an alternating application operation; Control correction factor generation module to obtain retention time and lag time difference; Control the dynamic parameter control module to generate the operation curve; Control the separation and detection module to record peak signals; Control the quantitative output module to generate quantitative results.

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