Automatic tuning of acoustic droplet ejection equipment

Abstract

Calculate an optimal value for at least one parameter of an ADE device, OPI, or ion source device. For each of multiple parameter values ​​for at least one parameter of the ADE device, OPI, or ion source device, a processor performs three steps. First, the at least one parameter is set to that value. Second, the ADE device, OPI, ion source device, and mass spectrometer are instructed to produce one or more intensity-time mass peaks for the sample. Third, eigenvalues ​​are calculated for at least one characteristic of the one or more intensity-time mass peaks. Multiple eigenvalues ​​corresponding to the multiple parameter values ​​are generated. An optimal value is calculated for the at least one parameter from the multiple eigenvalues.

Description

[0001] Related US applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 029,247, filed May 22, 2020, the entire contents of which are incorporated herein by reference.

[0003] introduce

[0004] This paper teaches how to operate an acoustic jet mass spectrometry (AEMS) system to automatically tune its parameters. Specifically, the operating parameters of the acoustic droplet jet (ADE), open port interface (OPI), or ion source device of the AEMS system are automatically calculated from a series of mass spectrometry (MS) experiments. In these experiments, the values ​​of one or more operating parameters of the ADE, OPI, or ion source device are varied. One or more mass peaks are detected for each value of one or more operating parameters. Based on this data, the optimal values ​​of one or more operating parameters are calculated.

[0005] ADE and OPI tuning problems

[0006] High-throughput sample analysis is crucial for drug discovery. Mass spectrometry (MS)-based methods enable label-free, universal quality detection of a wide variety of analytes with excellent sensitivity, selectivity, and specificity. Therefore, there is significant interest in improving the throughput of MS-based drug discovery analyses. In particular, several sample introduction systems for MS-based analyses have been improved to deliver even higher throughput.

[0007] As described below, ADE has recently been combined with OPI to provide a sample introduction system for high-throughput mass spectrometry analysis. When the ADE device and OPI are coupled to a mass spectrometer, the system can be referred to as an AEMS system.

[0008] The analytical performance (sensitivity, reproducibility, throughput, etc.) of an AEMS system depends on the performance of the ADE (Analytical Processing) equipment and the OPI (Optimal Operating Environment). The performance of the ADE equipment and the OPI depends on selecting the optimal operating conditions or parameters for these equipment.

[0009] Two types of operating parameters need to be set for the ADE device and the OPE. The first type of parameter is the parameter set for the device used in all experiments or measurements. These parameters include, but are not limited to, the alignment of the OPI with the ADE, the position of the inner tube of the OPI relative to the outer tube of the OPI, the amount of the OPI electrode protruding from the electrospray ionization (ESI) nozzle, and the flow rate of sample solvent dilution in the OPI.

[0010] The second type of parameter is set for a specific experiment or for a specific analyte and solution or matrix. These parameters include, but are not limited to, the ejection volume of the sample generated by the ADE device and the delay time from when the sample is ejected by the ADE device to when the mass spectrometer detects the peak of the sample.

[0011] Unfortunately, currently, both types of parameters are manually set by the user of the AEMS system and may not be properly optimized. Therefore, additional systems and methods are needed to optimize the operating parameters of the ADE device or the OPI of the AEMS system before experimentation.

[0012] ADE and OPI background

[0013] The accurate determination of the presence, identity, concentration, and / or quantity of analytes in a sample is crucial in many fields. Many techniques used in such analyses involve ionizing substances in a fluid sample before introducing them into the analytical equipment used. The choice of ionization method will depend on the nature of the sample and the analytical technique employed, and many ionization methods are available, such as electrospray ionization (ESI), matrix-assisted laser desorption / ionization (MALDI), desorption-electrospray ionization (DESI), etc. ESI is generally preferred. Mass spectrometry is a well-established analytical technique in which sample molecules are ionized and then the resulting ions are classified according to their mass-to-charge ratio.

[0014] The ability to combine mass spectrometry, particularly electrospray ionization mass spectrometry, with separation techniques such as liquid chromatography (LC), including high-performance liquid chromatography (HPLC), capillary electrophoresis, or capillary electrochromatography, means that complex mixtures can be separated and characterized in a single process. Improvements in HPLC system design, such as reduced dead volume and increased pump pressure, have enabled smaller columns containing smaller particles, improved separation, and faster run times. Despite these improvements, the time required for sample separation remains approximately one minute. Even without requiring true separation, the mechanism of loading samples into the mass spectrometer using a conventional autosampler with some degree of purge between injections still limits sample loading time to approximately ten seconds per sample.

[0015] Some success has been achieved in improving throughput performance. By using solid-phase extraction instead of traditional chromatography to remove salts, simplified sample processing can reduce the pre-injection time per sample from several minutes per sample required by HPLC to less than ten seconds per sample. However, this increase in sampling speed comes at the cost of selectivity or sensitivity. Furthermore, the time savings achieved through increased sampling speed are offset by the need for cleanup between samples.

[0016] Another limitation of current mass spectrometer loading procedures is the issue of sample residues, which requires a cleaning step after loading each sample to prevent subsequent samples from being contaminated by residual analytes from previous samples. This takes time and adds a step to the process, making analysis with conventional autosampler systems more complex than simpler.

[0017] Another limitation of current mass spectrometers when used to process complex samples (such as biological fluids) is the unwanted “matrix effect,” which is due to the presence of matrix components (e.g., natural matrix components, such as cellular matrix components, or contaminants inherent in some materials (such as plastics)) and adversely affects the detection capability, precision, and / or accuracy of the target analyte.

[0018] A system combining an ADE (Automatic Dependency Analysis) with an Open Port Interface (OPI) sampling interface has been developed for high-throughput mass spectrometry. This system is described in U.S. Patent Application No. 16 / 198,667 (hereinafter referred to as the "'667 application"), which is incorporated herein by reference in its entirety.

[0019] Figure 1A This is an exemplary system that combines ADE with OPI, as described in application '667. Figure 1A In the diagram, the ADE device is generally shown as 11, which sprays droplets 49 toward the continuous flow OPI generally indicated as 51 and into its sampling tip 53.

[0020] ADE device 11 includes at least one reservoir, with a first reservoir shown as 13 and optionally a second reservoir 31. In some embodiments, multiple additional reservoirs may be provided. Each reservoir is configured to contain a fluid sample having a fluid surface, for example, a first fluid sample 14 and a second fluid sample 16 having fluid surfaces indicated as 17 and 19, respectively. Fluid samples 14 and 16 may be the same or different, but are generally different, provided they typically contain two different analytes intended to be transported to and detected in an analytical instrument (not shown). The analytes may be biomolecules or macromolecules other than biomolecules, or may be small organic molecules, inorganic compounds, ionized atoms, or any part of any size, shape, or molecular structure, as explained earlier in this section. Furthermore, the analytes may be dissolved, suspended, or dispersed in the liquid component of the fluid sample.

[0021] When using more than one memory, such as Figure 1AAs shown, the reservoirs are preferably substantially identical and acoustically indistinguishable, but identical construction is not required. As explained earlier in this section, the reservoirs can be trays, shelves, or other individual removable components of such a structure, but they can also be fixed within a plate (e.g., a perforated plate or another substrate). As shown, each reservoir is preferably substantially axisymmetric, having vertical walls 21 and 23 extending upward from circular reservoir bases 25 and 27 and terminating at openings 29 and 31, respectively, but other reservoir shapes and reservoir base shapes can be used. For example, some openings can be tapered, such that the opening has a larger cross-sectional area at the top compared to the bottom. The material and thickness of each reservoir base should allow acoustic radiation to be transmitted through it and into the fluid sample contained within each reservoir.

[0022] The ADE device 11 includes an acoustic jet 33, which includes an acoustic radiation generator 35 and a focusing element 37 for focusing acoustic radiation generated at a focal point 47 within the fluid sample, near the fluid surface. Figure 1A As shown, the focusing element 37 may comprise a single solid piece having a concave surface 39 for focusing acoustic radiation, but the focusing element may be constructed in other ways as discussed below. Thus, the acoustic ejector 33 is adapted to generate and focus acoustic radiation so as to eject fluid droplets from each of the fluid surfaces 17 and 19 when acoustically coupled to the reservoirs 13 and 15 and thus to the fluids 14 and 16, respectively. The acoustic radiation generator 35 and the focusing element 37 may be used as a single unit controlled by a single controller, or they may be controlled independently, depending on the desired performance of the device.

[0023] Ideally, acoustic coupling is achieved between the injector and each reservoir via indirect contact, such as... Figure 1A As shown in the figure, an acoustic coupling medium 41 is placed between the base 25 of the ejector 33 and the reservoir 13, which are spaced a predetermined distance apart. The acoustic coupling medium can be an acoustic coupling fluid, preferably an acoustically homogeneous material that conformally contacts the acoustic focusing element 37 and the underside of the reservoir. Furthermore, it is important to ensure that the fluid medium is substantially free of materials having acoustic properties different from those of the fluid medium itself. As shown, the first reservoir 13 is acoustically coupled to the acoustic focusing element 37, such that sound waves generated by the acoustic radiation generator are directed by the focusing element 37 into the acoustic coupling medium 41, which then transmits the acoustic radiation into the reservoir 13. The system may comprise a single acoustic ejector, such as... Figure 1A As shown in the diagram, or as previously stated, it can contain multiple injectors.

[0024] During operation, the device's reservoir 13 and optional reservoir 15 are filled with first and second fluid samples 14 and 16, respectively, as... Figure 1A As shown in the diagram, the acoustic ejector 33 is positioned directly below the reservoir 13, and acoustic coupling between the ejector and the reservoir is provided by means of an acoustic coupling medium 41. Initially, the acoustic ejector is positioned directly below the sampling tip 53 of the OPI 51, such that the sampling tip faces the surface 17 of the fluid sample 14 in the reservoir 13. Once the ejector 33 and the reservoir 13 are properly aligned below the sampling tip 53, the acoustic radiation generator 35 is activated to generate acoustic radiation directed by the focusing element 37 to a focal point 47 near the fluid surface 17 of the first reservoir. Thus, the droplet 49 is ejected from the fluid surface 17 toward the liquid boundary 50 at the sampling tip 53 of the OPI 51 and enters the liquid boundary 50, where it combines with the solvent in the flow probe 53.

[0025] The profile of the liquid boundary 50 at the sampling tip 53 can vary from extending beyond the sampling tip 53 to protruding inward into the OPI 51. In a multi-reservoir system, the reservoir unit (not shown) (e.g., a multi-well plate or tube rack) can then be repositioned relative to the acoustic ejector such that another reservoir is aligned with the ejector and a droplet of the next fluid sample can be ejected. The solvent in the flow probe continuously circulates through the probe, thereby minimizing or even eliminating “residue” between droplet ejection events. The multi-well plate can be, but is not limited to, a 24-well, 384-well, or 1536-well plate.

[0026] Fluid samples 14 and 16 are samples of any fluid intended to be transferred to the analytical instrument. Therefore, fluid samples may contain minimal, partially or completely solvated, dispersed, or suspended solids in a liquid, which may be aqueous or non-aqueous. The structure of the OPI 51 is also... Figure 1A As shown in the diagram. Any number of commercially available continuous-flow OPIs can be used as is or in modified form, as is well known in the art, all of which operate on essentially the same principles. Figure 1A As can be seen, the sampling tip 53 of OPI51 is spaced apart from the fluid surface 17 in the reservoir 13 by a gap 55. The gap 55 may be an air gap, an inert gas gap, or it may include some other gaseous material; there is no liquid bridge connecting the sampling tip 53 to the fluid 14 in the reservoir 13.

[0027] OPI 51 includes a solvent inlet 57 for receiving solvent from a solvent source and a solvent transport capillary 59 for transporting a solvent flow from the solvent inlet 57 to a sampling tip 53, wherein a jet of droplets 49 containing the analyte sample 14 combines with the solvent to form an analyte-solvent dilution. A solvent pump (not shown) is operatively connected to and in fluid communication with the solvent inlet 57 to control the rate at which solvent flows into the solvent transport capillary, thereby also controlling the solvent flow rate within the solvent transport capillary 59.

[0028] The fluid flow within probe 53 carries the analyte-solvent diluent toward sample outlet 63 through sample transport capillary 61 provided by inner capillary 73 for subsequent transfer to the analytical instrument. A sampling pump (not shown) may be provided, operatively connected to and in fluid communication with sample transport capillary 61, to control the output rate from outlet 63.

[0029] In one embodiment, a positive displacement pump is used as a solvent pump, such as a peristaltic pump, and instead of a sampling pump, an aspirating nebulization system is used to draw analyte-solvent diluent (in the sample outlet 63) from the sample outlet 63 via the Venturi effect caused by the flow of nebulized gas introduced from the nebulizing gas source 65 through the gas inlet 67. Figure 1A (The diagram is shown in a simplified form because the characteristics of inhalation nebulizers are well known in the art). The analyte-solvent dilution stream is then drawn upward through the sample transport capillary 61 by a pressure drop generated by the nebulizing gas passing through the sample outlet 63 and combining with the fluid leaving the sample transport capillary 61. A gas pressure regulator is used to control the gas flow rate entering the system via the gas inlet 67.

[0030] In a preferred manner, the nebulizing gas flows in a sheath flow pattern over the outside of the sample transport capillary 61 at or near the sample outlet 63. This sheath flow pattern occurs when the analyte-solvent diluent flows through the sample outlet 63, drawing it down from the sample transport capillary 61. This creates a suction effect at the sample outlet after mixing with the nebulizer gas. In various embodiments, the sample outlet 63 is a straight tube protruding from the gas nozzle.

[0031] Solvent transport capillary 59 and sample transport capillary 61 are provided by an outer capillary tube 71 and an inner capillary tube 73, which are substantially coaxially deployed therein. The inner capillary tube 73 defines the sample transport capillary, and the annular space between the inner capillary tube 73 and the outer capillary tube 71 defines the solvent transport capillary 59. The dimensions of the inner capillary tube 73 can range from 1 micrometer to 1 millimeter, for example, 200 micrometers. The typical dimensions of the outer diameter of the inner capillary tube 73 can range from 100 micrometers to 3 or 4 centimeters, for example, 360 micrometers. The typical dimensions of the inner diameter of the outer capillary tube 71 can range from 100 micrometers to 3 or 4 centimeters, for example, 450 micrometers. The typical dimensions of the outer diameter of the outer capillary tube 71 can range from 150 micrometers to 3 or 4 centimeters, for example, 950 micrometers. The cross-sectional area of ​​the inner capillary tube 73 and / or the outer capillary tube 71 can be circular, elliptical, superelliptical (i.e., shaped like a superellipse), or even polygonal. Although Figure 1A The system shown indicates that the solvent flow direction is downward from the solvent inlet 57 to the sampling tip 53 in the solvent transport capillary 59, while the analyte-solvent diluent flow direction is upward from the sampling tip 53 through the sample transport capillary 61 towards the outlet 63. However, the directions can be reversed, and the OPI 51 does not need to be perfectly vertical. Figure 1A Various modifications to the structure shown will be obvious to those skilled in the art, or can be derived by those skilled in the art during use of the system.

[0032] The system may also include an adjuster 75 coupled to the outer capillary tube 71 and the inner capillary tube 73. The adjuster 75 may be adapted to move the outer capillary tube tip 77 and the inner capillary tube tip 79 longitudinally relative to each other. The adjuster 75 may be any device capable of moving the outer capillary tube 71 relative to the inner capillary tube 73. An exemplary adjuster 75 may be a motor, including but not limited to electric motors (e.g., AC motors, DC motors, electrostatic motors, servo motors, etc.), hydraulic motors, pneumatic motors, translation stages, and combinations thereof. As used herein, “longitudinal” means an axis extending along the length of OPI 51, and the inner and outer capillary tubes 73, 71 may be arranged coaxially about the longitudinal axis of OPI 51, as shown in FIG1.

[0033] Optionally, prior to use, the adjuster 75 is used to pull the inner capillary tube 73 longitudinally inward, causing the outer capillary tube 71 to protrude beyond the end of the inner capillary tube 73, thereby promoting optimal fluid communication between the solvent flow in the solvent transport capillary 59 and the sample transported as the analyte-solvent dilution flow 61 in the sample transport capillary 61. Furthermore, as... Figure 1A As shown, OPI 51 is generally fixed within a roughly cylindrical retainer 81 to maintain stability and ease of handling.

[0034] Figure 1B illustrates an exemplary system 110 for ionization and mass analysis of analytes received at the open end of a sampling OPI, as described in application '667'. System 110 includes an acoustic droplet injection device 11 configured to inject droplets 49 from a reservoir into the open end of a sampling OPI 51. As shown in Figure 1B, the exemplary system 110 generally includes a sampling OPI 51 in fluid communication with a nebulizer-assisted ion source 160 for discharging liquid containing one or more sample analytes (e.g., via an electrospray electrode 164) into an ionization chamber 112, and a mass analyzer 170 in fluid communication with the ionization chamber 112 for downstream processing and / or detection of ions generated by the ion source 160. A fluid handling system 140 (e.g., including one or more pumps 143 and one or more conduits) provides liquid flow from a solvent reservoir 150 to the sampling OPI 51 and from the sampling OPI 51 to the ion source 160. For example, as shown in Figure 1B, a solvent reservoir 150 (e.g., containing liquid, desorption solvent) can be fluidly coupled to the sampling OPI 51 via a supply conduit through which the liquid can be delivered at a selected volumetric rate by a pump 143 (e.g., a reciprocating pump, a positive displacement pump (such as a rotary, gear, plunger, piston, peristaltic, diaphragm pump), or other pumps (such as a gravity, pulse, pneumatic, electric, and centrifugal pump)), all of which are non-limiting examples. As discussed in detail below, the flow of liquid into and out of the sampling OPI 51 occurs within the sample space accessible at the open end, such that one or more droplets 49 can be introduced into the liquid boundary 50 at the sample tip and subsequently delivered to the ion source 160.

[0035] As shown in the figure, system 110 includes an acoustic droplet ejection device 11 configured to generate acoustic energy, which is applied to a reservoir (e.g., Figure 1A The liquid within (as depicted in the diagram) is injected, causing one or more droplets 49 to be ejected from the reservoir onto the open end of the sampling OPI 51. The controller 180 may be operatively coupled to the acoustic droplet injection device 11 and may be configured to operate any aspect of the acoustic droplet injection device 11 (e.g., focusing components, acoustic radiation generator, automated components for positioning one or more reservoirs in alignment with the acoustic radiation generator, etc.) to inject droplets into the sampling OPI 51 or otherwise be used substantially continuously or by way of non-limiting example in selected portions of the experimental protocol discussed herein. The controller 180 may be, but is not limited to, a microcontroller, computer, microprocessor, the computer system of FIG. 1, or any device capable of sending and receiving control signals and data.

[0036] As shown in Figure 1B, the exemplary ion source 160 may include a source 65 of pressurized gas (e.g., nitrogen, air, or a rare gas) supplying a high-speed atomized gas stream that surrounds the outlet end of the electrospray electrode 164 and interacts with the fluid exiting therefrom to enhance the formation of the sample plume and the release of ions within the plume for sampling at 114b and 116b, for example, via the interaction of the high-speed atomized stream and the jet of the liquid sample (e.g., an analyte-solvent diluent). The nebulizer gas may be supplied at various flow rates, for example, in the range from approximately 0.1 L / min to approximately 20 L / min, which may also be controlled by the controller 180 (e.g., via opening and / or closing valve 16).

[0037] It will be appreciated that the flow rate of the atomizer gas can be adjusted (e.g., under the influence of the controller 180) so that the liquid flow rate within the sampling OPI 51 can be adjusted based on the suction / suction force generated by the interaction of the atomizer gas and the analyte-solvent diluent when the atomizer gas is discharged from the electrospray electrode 164 (e.g., due to the Venturi effect).

[0038] As shown in Figure 1B, the ionization chamber 112 can be maintained at atmospheric pressure, but in some embodiments, the ionization chamber 112 can be evacuated to a pressure below atmospheric pressure. The ionization chamber 112 is separated from the curtain chamber 114 by a plate 114a having curtain apertures 114b. The analyte is ionized within the ionization chamber 112 when the analyte-solvent diluent is discharged from the electrospray electrode 164. As shown, the vacuum chamber 116 housing the mass analyzer 170 is separated from the curtain chamber 114 by a plate 116a having a vacuum chamber sampling port 116b. The curtain chamber 114 and the vacuum chamber 116 can be maintained at a selected pressure(s) (e.g., the same or different sub-atmospheric pressures, below the ionization chamber pressure) by evacuation through one or more vacuum pump ports 118.

[0039] Those skilled in the art will also recognize, and in accordance with the teachings herein, that the mass analyzer 170 may have a variety of configurations. Generally, the mass analyzer 170 is configured to process (e.g., filter, sort, dissociate, detect, etc.) sample ions generated by the ion source 160. As a non-limiting example, the mass analyzer 170 may be a triple quadrupole mass spectrometer, or any other mass analyzer known in the art and modified in accordance with the teachings herein. Other non-limiting exemplary mass spectrometer systems that can be modified according to various aspects of the systems, apparatus, and methods disclosed herein can be found, for example, in U.S. Patent Nos. 7,923,681, authored by James W. Hager and J.C.Y. Le Blanc and published in Rapid Communications in Mass Spectrometry (2003; 17:1056-1064) entitled “Product ion scanning using a QqQ linear ion trap (QTRAP) mass spectrometer” and “Collision Cell for Mass Spectrometer,” both of which are incorporated herein by reference in their entirety.

[0040] Other configurations, including but not limited to those described herein and others known to those skilled in the art, may also be used in conjunction with the systems, apparatus, and methods disclosed herein. For example, other suitable mass spectrometers include single quadrupole, triple quadrupole, ToF, trap, and mixed analyzers. It should also be appreciated that system 110 may include any number of additional elements, including, for example, an ion mobility spectrometer (e.g., a differential mobility spectrometer) deployed between ionization chamber 112 and mass analyzer 170, and said ion mobility spectrometer is configured to separate ions based on their mobility through drift gas in high and low fields rather than their mass-to-charge ratio. Furthermore, it should be appreciated that mass analyzer 170 may include a detector capable of detecting ions passing through analyzer 170 and may, for example, supply a signal indicating the number of ions detected per second.

[0041] Mass spectrometry background

[0042] Mass spectrometers are often coupled with chromatographic or other sample introduction systems, such as ADE devices and OPI, to identify and characterize compounds of interest from samples or to analyze multiple samples. In such coupled systems, the eluting or injected solvent is ionized, and a series of mass spectra are obtained from the eluting solvent at specific time intervals called retention times. These retention times range from, for example, 1 second to 100 minutes or longer. The sequence of mass spectra forms traces, chromatograms, or extracted ion chromatograms (XIC).

[0043] For example, peaks detected in XIC are used to identify or characterize known peptides or compounds in a sample. More specifically, peak retention time and / or peak area are used to identify or characterize (quantify) known peptides or compounds in a sample. In cases where the sample introduction device delivers multiple samples over time, peak retention time is used to align the peak with the correct sample.

[0044] In traditional separation-coupled mass spectrometry systems, fragments or product ions of known compounds are selected for analysis. Then, at each separation interval, a mass range including the product ions is scanned by tandem mass spectrometry or mass spectrometry / mass spectrometry (MS / MS). For example, the intensities of product ions detected in each MS / MS scan are collected over time and analyzed as a ensemble of spectra or XIC.

[0045] Generally speaking, tandem mass spectrometry, or MS / MS, is a well-known technique for analyzing compounds. Tandem mass spectrometry involves the ionization of one or more compounds from a sample, the selection of one or more precursor ions of one or more compounds, the fragmentation of one or more precursor ions into fragments or product ions, and the mass analysis of the product ions.

[0046] Tandem mass spectrometry can provide qualitative and quantitative information. Product ion spectra can be used to identify molecules of interest. The intensities of one or more product ions can be used to quantify the amount of compounds present in a sample.

[0047] A wide variety of experimental methods or workflows can be performed using tandem mass spectrometers. These workflows fall into three main categories: targeted acquisition, information-related acquisition (IDA) or data-related acquisition (DDA), and data-independent acquisition (DIA).

[0048] In targeted acquisition methods, one or more transitions from precursor ions to product ions are predefined for the compound of interest. When a sample is introduced into a tandem mass spectrometer, one or more transitions are interrogated or monitored during each of multiple time periods or cycles. In other words, the mass spectrometer selects and breaks down the precursor ions of each transition and performs targeted mass analysis only on the product ions of the transitions. Therefore, an intensity (product ion intensity) is generated for each transition. Targeted acquisition methods include, but are not limited to, multiple reaction monitoring (MRM) and selected reaction monitoring (SRM).

[0049] In targeted fetching methods, a list of transitions is typically queried during each cycle period. To reduce the number of transitions queried at any given time, some targeted fetching methods have been modified to include a retention time or retention time range for each transition. A specific transition is only queried during that retention time or within that retention time range. A targeted fetching method that allows specifying retention times for transitions is called a scheduled MRM.

[0050] In the IDA method, users can specify criteria for performing non-targeted mass analysis of product ions while introducing the sample into the tandem mass spectrometer. For example, in the IDA method, a precursor ion or mass spectrometry (MS) survey scan is performed to generate a precursor ion peak list. Users can select criteria to filter the peak list for a subset of precursor ions. MS / MS is then performed on each precursor ion in the subset. A product ion spectrum is generated for each precursor ion. MS / MS is repeated on the subset of precursor ions as the sample is introduced into the tandem mass spectrometer.

[0051] However, in proteomics and many other sample types, the complexity and dynamic range of compounds are extremely large. This poses a challenge to traditional targeted and IDA methods, requiring very high-speed MS / MS acquisition to deeply interrogate samples in order to identify and quantify a wide range of analytes.

[0052] Therefore, a third major class of tandem mass spectrometry, the DIA method, was developed. These DIA methods have been used to improve the reproducibility and comprehensiveness of data collected from complex samples. The DIA method can also be called a non-specific fragmentation method. In traditional DIA methods, the effect of the tandem mass spectrometer does not change between MS / MS scans based on data acquired in previous precursor or product ion scans. Instead, a precursor ion mass range is selected. Then, a precursor ion mass selection window is stepped within the precursor ion mass range. All precursor ions in the precursor ion mass selection window are fragmented, and all product ions of all precursor ions in the precursor ion mass selection window are mass-analyzed.

[0053] The precursor ion mass selection window used to scan the mass range can be very narrow, making it unlikely that multiple precursors will be present within the window. This type of DIA method is known, for example, as MS / MS. ALL In MS / MS ALL In this method, a precursor ion mass selection window of approximately 1 amu is scanned and stepped across the entire mass range. Product ion spectra are generated for each 1 amu precursor mass window. The time taken for a single analysis or scan of the entire mass range is called a scan cycle. However, scanning a narrow precursor ion mass selection window across a wide precursor ion mass range during each cycle is not practical for some instruments and experiments.

[0054] Therefore, a larger precursor ion quality selection window, or a selection window with a large width, steps across the entire precursor quality range. This type of DIA method is called, for example, SWATH acquisition. In SWATH acquisition, the precursor ion quality selection window across the precursor quality range in each cycle can have a width of 5-25 amu or even greater. Similar to MS / MS... ALL The method is the same: all precursor ions in each precursor ion mass selection window are fragmented, and all product ions of all precursor ions in each mass selection window are subjected to mass analysis. Summary of the Invention

[0055] A system, method, and computer program product are disclosed for automatically calculating the optimal value of at least one operating parameter for an ADE device, OPI, or ion source device using a mass spectrometer. The system includes an ADE device, an OPI, an ion source device, a mass spectrometer, and a processor.

[0056] An ADE (Aspect-Definition) device is suitable for performing one or more jets of a sample over time. An OPI (Optical Probe Injection) device is suitable for receiving one or more jets over time at the inlet of the inner tube, mixing the received jets with solvent to form a series of sample-solvent diluents, and transferring the series of diluents to the outlet of the inner tube. An ion source device is suitable for receiving and ionizing the series of diluents to generate an ion beam. A mass spectrometer is suitable for receiving the ion beam over time and performing mass analysis on the ion beam to generate time-dependent mass peaks corresponding to one or more jets.

[0057] The processor communicates with the ADE device, OPI, ion source device, and mass spectrometer. For each of multiple parameter values ​​for at least one parameter used by the ADE device, OPI, or ion source device, the processor performs three steps. These parameters include flow rates such as pump flow rate and nebulizer gas flow rate. First, the processor sets at least one parameter to each value. Second, the processor instructs the ADE device, OPI, ion source device, and mass spectrometer to generate one or more intensity-time mass peaks for the sample. Third, the processor calculates characteristic values ​​for at least one feature of the one or more intensity-time mass peaks. Multiple characteristic values ​​are generated corresponding to the multiple parameter values.

[0058] Then, the processor calculates the optimal value of at least one parameter from multiple eigenvalues ​​corresponding to multiple parameter values.

[0059] A system, method, and computer program product for automatically calculating the optimal protrusion length of electrodes in an ion source device using an overflow sensor are disclosed. The system includes an ADE device, an OPI, an ion source device, an overflow sensor, and a processor.

[0060] The ADE device is suitable for performing one or more jets of a sample over time. The OPI is suitable for receiving one or more jets over time at the inlet of the inner tube, mixing the received jets with solvent to form a series of sample-solvent diluents, and transferring the series of diluents to the outlet of the inner tube. The ion source device is suitable for receiving the series of diluents and ionizing the series of diluents to generate an ion beam. The overflow sensor is suitable for measuring the flow rate of the series of diluents and triggering a notification when the flow rate exceeds a threshold. The overflow sensor can be an integrated component or associated with the OPI.

[0061] The processor communicates with the ADE device, OPI, ion source device, and overflow sensor. For each of multiple length values ​​of the electrode protruding from the nozzle of the ion source device at the outlet of the OPI's inner tube, the processor performs three steps. First, the processor sets the length for each value. Second, the processor instructs the ADE device, OPI, and ion source device to generate an ion beam for the sample at each of multiple flow rate values ​​until the overflow sensor triggers a notification. Multiple flow rates are generated for each value. Third, the processor calculates the highest flow rate value for each of the multiple flow rates. Multiple highest flow rate values ​​are generated corresponding to the multiple length values.

[0062] The processor then calculates the optimal length by computing the length value that produces the highest overflow flow rate from among multiple highest flow rate values ​​corresponding to multiple length values.

[0063] This article describes these and other characteristics of the applicant's teaching. Attached Figure Description

[0064] Those skilled in the art will understand that the accompanying drawings described below are for illustrative purposes only. The drawings are not intended to limit the scope of this teaching in any way.

[0065] Figure 1A An exemplary system that combines acoustic droplet ejection (ADE) with an open port interface (OPI) sampling interface, as described in application '667.

[0066] Figure 1B is an exemplary system for ionization and mass analysis of analytes received within the open end of the sampling OPP, as described in application '667'.

[0067] Figure 2 This is a block diagram illustrating an embodiment of the teachings of a computer system on which the computer system may be implemented.

[0068] Figure 3 This is an exemplary graph showing the clustering of intensity relative to time quality peaks detected by standard samples at different x-axis and y-axis positions of OPI relative to an ADE device, according to various embodiments.

[0069] Figure 4 This illustrates the representation according to various embodiments. Figure 3 An exemplary plot of the average peak intensity calculated for clusters of OPI at six different locations along the x-axis and plotted relative to the six different locations along the x-axis.

[0070] Figure 5 This is an exemplary diagram showing the clustering of intensity relative to time-dependent quality peaks detected in a standard sample at different positions of the inner tube relative to the outer tube of the OPI according to various embodiments.

[0071] Figure 6 This illustrates the representation according to various embodiments. Figure 5 An exemplary plot of the average peak intensity of five different indentation locations of the inner tube of the OPI is calculated and plotted relative to these five different indentation locations.

[0072] Figure 7 This illustrates the representation according to various embodiments. Figure 5 An exemplary plot of the average peak widths of five different indentation locations within the inner tube of the OPI is calculated and plotted relative to these five different indentation locations.

[0073] Figure 8 This is an exemplary plot of the intensity of the cluster of time-dependent mass peaks detected in a standard sample at different flow rates for an OPI with an electrode protrusion length of 300 μm, according to various embodiments.

[0074] Figure 9 This illustrates the representation according to various embodiments. Figure 8 An exemplary plot of ten average peak widths and nine average delay times relative to the flow rate of the clusters of OPI is calculated.

[0075] Figure 10 This is an exemplary plot of the intensity of the cluster of time-dependent mass peaks detected in a standard sample at different flow rates for an OPI with an electrode protrusion length of 750 μm, according to various embodiments.

[0076] Figure 11 The illustrations are based on various embodiments and are shown from the representation. Figure 10 An exemplary plot of cluster calculations for ten different flow rates of OPI and nine average peak widths and seven average delay times plotted relative to the flow rates.

[0077] Figure 12 This is an exemplary graph showing a series of intensity-time mass peaks detected for a standard sample from three different types of solutions according to various embodiments, illustrating how the intensity of the mass peaks varies with the type of solution used as the jet volume increases.

[0078] Figure 13This is an exemplary plot of a series of intensity relative to time mass peaks detected from a standard sample ejected from the same orifice, according to various embodiments, illustrating that the distance between peaks can be optimized when the samples have similar concentrations.

[0079] Figure 14 These are exemplary series of intensity versus time quality peak plots from three different experiments according to various embodiments, wherein samples are ejected from a series of different orifices using different ejection delay times.

[0080] Figure 15 This is an exemplary matrix chart illustrating one or more mass peak characteristics according to various embodiments, which can be used to calculate optimal values ​​for different operating parameters of an ADE device, OPI, or ion source device.

[0081] Figure 16 This is a schematic diagram of a system according to various embodiments for automatically calculating the optimal value of at least one operating parameter for an ADE device, OPI or ion source device using a mass spectrometer.

[0082] Figure 17 This is a flowchart illustrating a method, according to various embodiments, for automatically calculating the optimal value of at least one operating parameter of an ADE device, OPI, or ion source device using a mass spectrometer.

[0083] Figure 18 This is a schematic diagram of a system according to various embodiments, comprising one or more different software modules that perform a method for automatically calculating the optimal value of at least one operating parameter of an ADE device, OPI, or ion source device using a mass spectrometer.

[0084] Figure 19 This is a schematic diagram of a system for automatically calculating the optimal protrusion length of the electrodes of an ion source device using an overflow sensor, according to various embodiments.

[0085] Figure 20 This is a flowchart illustrating a method for automatically calculating the optimal protrusion length of the electrodes of an ion source device using an overflow sensor, according to various embodiments.

[0086] Before describing one or more embodiments of this teaching in detail, those skilled in the art will recognize that the application of this teaching is not limited to the details of the construction, arrangement, and steps of the components described in the following detailed description or illustrated in the accompanying drawings. Furthermore, it should be understood that the wording and terminology used herein are for descriptive purposes and should not be considered limiting. Detailed Implementation

[0087] Figure 2This is a block diagram illustrating a computer system 200 on which embodiments of the present teachings may be implemented. The computer system 200 includes a bus 202 or other communication mechanism for transmitting information, and a processor 204 coupled to the bus 202 for processing information. The computer system 200 also includes a memory 206 coupled to the bus 202, which may be random access memory (RAM) or other dynamic storage device, for storing instructions to be executed by the processor 204. The memory 206 may also be used to store temporary variables or other intermediate information during the execution of instructions to be executed by the processor 204. The computer system 200 also includes a read-only memory (ROM) 208 or other static storage device coupled to the bus 202 for storing static information and instructions for the processor 204. A storage device 210, such as a magnetic disk or optical disk, is provided and coupled to the bus 102 to store information and instructions.

[0088] Computer system 200 can be coupled to display 212, such as a cathode ray tube (CRT) or liquid crystal display (LCD), via bus 202 to display information to the computer user. Input device 214, including alphanumeric keys and other keys, is coupled to bus 202 to transmit information and command selections to processor 204. Another type of user input device is cursor control 216, such as a mouse, trackball, or arrow keys, used to transmit directional information and command selections to processor 204 and to control cursor movement on display 212. Such input devices typically have two degrees of freedom on two axes (i.e., the first axis (x) and the second axis (y)), allowing the device to specify a position in a plane.

[0089] Computer system 200 can execute this teaching. Consistent with certain embodiments of this teaching, computer system 200 provides results in response to processor 204 executing one or more sequences of one or more instructions contained in memory 206. Such instructions may be read into memory 206 from another computer-readable medium, such as storage device 210. Execution of the sequence of instructions contained in memory 206 causes processor 204 to perform the processes described herein. Alternatively, hardwired circuitry may be used in place of or in combination with software instructions to implement this teaching. Therefore, embodiments of this teaching are not limited to any particular combination of hardware circuitry and software.

[0090] In various embodiments, computer system 200 can be connected across a network to one or more other computer systems (such as computer system 200) to form a networked system. The network can include a private network or a public network such as the Internet. In a networked system, one or more computer systems can store data and provide data to other computer systems. In a cloud computing scenario, the one or more computer systems that store and provide data can be referred to as servers or the cloud. For example, one or more computer systems can include one or more web servers. For example, other computer systems that send data to or receive data from servers or the cloud can be referred to as clients or cloud devices.

[0091] As used herein, the term "computer-readable medium" means any medium that participates in providing instructions to processor 204 for execution. Such media can take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical discs or magnetic disks, such as storage device 210. Volatile media include dynamic memory, such as memory 206. Transmission media include coaxial cables, copper wires, and optical fibers, including wires constituting bus 202.

[0092] Common forms of computer-readable media or computer program products include, for example, floppy disks, flexible disks, hard disks, magnetic tapes or any other magnetic media, CD-ROMs, digital video discs (DVDs), Blu-ray discs, any other optical media, thumb drives, memory cards, RAM, PROMs and EPROMs, FLASH-EPROMs, any other memory chips or cassettes, or any other tangible media from which a computer can read.

[0093] Various forms of computer-readable media may involve carrying one or more sequences of one or more instructions to processor 204 for execution. For example, the instructions may initially be carried on a disk of a remote computer. The remote computer may load the instructions into its dynamic memory and transmit the instructions over a telephone line using a modem. A modem local to computer system 200 may receive data over a telephone line and convert the data into an infrared signal using an infrared transmitter. An infrared detector coupled to bus 202 may receive the data carried in the infrared signal and place the data on bus 202. Bus 202 carries the data to memory 206, from which processor 204 retrieves and executes the instructions. The instructions received by memory 206 may optionally be stored on storage device 210 before or after execution by processor 204.

[0094] According to various embodiments, instructions configured to be executed by a processor to perform a method are stored on a computer-readable medium. The computer-readable medium may be a device for storing digital information. For example, a computer-readable medium includes an optical disc read-only memory (CD-ROM) for storing software, as known in the art. The computer-readable medium is accessed by a processor adapted to execute the instructions configured to be executed.

[0095] For illustrative and descriptive purposes, the following descriptions of various implementations of this teaching have been given. It is not exhaustive and does not limit this teaching to the precise forms disclosed. Modifications and variations are possible in light of the above teachings, or may be derived from practice of this teaching. Furthermore, the described implementations include software, but this teaching can be implemented as a combination of hardware and software or solely as hardware. This teaching can be implemented using both object-oriented and non-object-oriented programming systems.

[0096] Calculate the optimal parameters for the AEMS system

[0097] As mentioned above, the analytical performance (sensitivity, reproducibility, throughput, etc.) of an acoustic jet mass spectrometry (AEMS) system depends on the performance of the acoustic droplet jet (ADE) device and the open port interface (OPI). The performance of the ADE device and the OPI depends on selecting the optimal operating conditions or parameters for these devices.

[0098] Two types of operating parameters need to be set for both ADE and OPE devices. The first type of parameter is for devices used for all experiments or determinations. The second type of parameter is for specific experiments or specific analytes and solutions or matrices.

[0099] Unfortunately, currently, both types of parameters are manually set by the user of the AEMS system and may not be properly optimized. Therefore, additional systems and methods are needed to optimally set the operating parameters of the AEMS system's ADE device or OPI before experiments.

[0100] In one embodiment, the operating parameters of the ADE device, OPI, or ion source device of the AEMS system are automatically calculated by a series of sample mass spectrometry (MS) experiments. In these experiments, the values ​​of one or more operating parameters of the ADE device, OPI, or ion source device are varied and may include pump flow rate and gas pressure / flow rate. One or more mass peaks are detected for each value of one or more operating parameters. Optimal values ​​for one or more operating parameters are calculated based on this data.

[0101] In another embodiment, the operating parameters of the ADE device, OPI, or ion source device of the AEMS system are automatically calculated based on a series of samples introduced into the ion source, and may include gas and solvent flow rates. Again, the values ​​of one or more operating parameters of the ADE device, OPI, or ion source device vary between sample introductions. However, in these experiments, the AEMS sensors are used to determine the condition of the ADE device, OPI, or ion source device. Therefore, conditions are detected for each value of one or more operating parameters. Based on this data, the optimal value for one or more operating parameters is calculated.

[0102] In various embodiments, once the optimal value for one or more operating parameters is calculated, it can be used to set the operating parameters for the ADE device, OPI, or ion source device. As mentioned above, two types of operating parameter values ​​need to be set. A first type of value is set for the parameters of the device used for all experiments or determinations, and a second type of value is set for the device parameters used for a specific experiment or a specific analyte and solution.

[0103] In various embodiments, the second type of value may alternatively be stored in a memory device. Each time a specific analyte and solution for a specific assay are analyzed, the second type of value is then retrieved from the memory device and used to set the parameters of the device for that specific analyte and solution.

[0104] alignment

[0105] Reproducible AEMS system performance depends on proper alignment of the ADE device, the sample aperture, and the OPI. Typically, the first step in this alignment process is aligning the acoustic transducer in the ADE device with the sample aperture. In addition to generating acoustic signals, the ADE device can also receive acoustic signals. Therefore, the ADE device can be used to align itself with the sample aperture.

[0106] For example, an ADE device can use the received acoustic signal to distinguish the edge of a sample aperture from the rest of the aperture. Therefore, to determine the center of the sample aperture, it can be moved until the ADE device identifies all aperture edges. The center is then determined based on the average distance between the edges. An alternative method involves monitoring the intensity of the reflected signal while moving along the x and / or y axes without reaching the edge. The center of the surface meniscus is identified as the point with the lowest liquid level, resulting in the highest intensity of the reflected signal.

[0107] Furthermore, alignment, which can involve vertical alignment, is also used to determine the optimal positioning of the acoustic transducer relative to the sample aperture. Ideally, the open port interface should be as close as possible to the top surface of the sample plate to ensure that most of the dispensed droplets are captured during plate movement without the plate coming into contact with the OPI head. Therefore, there will be a small gap, such as an air gap of approximately 0.3 mm. If an optimal xy alignment exists, this vertical gap can be several millimeters. The smaller the vertical gap, the greater the tolerance for potential xy misalignment.

[0108] Although the gap can be kept the same across different board types, the absolute level needs to be adjusted for different board types due to the different board heights.

[0109] Once the sample aperture is aligned with the acoustic transducer of the ADE device, the OPI can be aligned with the ADE device. In various embodiments, the OPI is automatically aligned by moving the OPI relative to the ADE device on two axes and measuring one or more mass peaks at each movement. The optimal position of the OPI is determined based on the intensity of the mass peaks detected at each position of the OPI.

[0110] Typically, alignment of the OPI with the ADE device is performed to find the optimal relative positions of these devices. These optimal positions are then set for the devices used in all experiments or determinations. Standard analytes and standard solutions are typically, but not necessarily, used to find these optimal positions. For example, a standard analyte and standard solution could be, but is not limited to, a single drop (low nL) of 100 nM dextromethorphan in water. The delay time between sample sprays is, for example, two seconds.

[0111] Figure 3 Figure 300 is an exemplary diagram of clusters of intensity-time mass peaks detected from standard samples at different x- and y-axis positions of the OPI relative to an ADE device, according to various embodiments. In Figure 300, cluster 310 represents different positions along the x-axis and cluster 320 represents different positions along the y-axis, with optimized x-axis positions generated by the process shown in 310. Each cluster comprises 20 mass peaks detected from 20 sequential sprays of a single drop of a standard sample.

[0112] Cluster 311 shows the intensity detected by the mass spectrometer when the OPI is at an initial position along the x-axis. The OPI is then moved along the x-axis in 200 μm steps. Cluster 312 shows the intensity detected by the mass spectrometer when the OPI is 200 μm from the initial position along the x-axis. Cluster 313 shows the intensity detected by the mass spectrometer when the OPI is 400 μm from the initial position along the x-axis.

[0113] The peak of each cluster is compared with the previous cluster. If the peak differs from the previous cluster by a certain intensity threshold, then the outer boundary of the alignment is reached. For example, it is found that the intensity of the peak of cluster 313 differs from the intensity of the peak of cluster 312 by more than a certain intensity threshold. Therefore, cluster 313 uses a step size of 200 μm to define the x-axis boundary of the alignment, starting from the initial position.

[0114] Therefore, the x-axis is then interrogated in the other direction. The OPI is moved back to its initial position and then decreased from the initial position in steps of 200 μm. For example, cluster 314 shows the intensity detected by the mass spectrometer when the OPI is located along the x-axis at a distance of -200 μm from the initial position. Cluster 315 shows the intensity detected by the mass spectrometer when the OPI is located along the x-axis at a distance of -400 μm from the initial position. Cluster 316 shows the intensity detected by the mass spectrometer when the OPI is located along the x-axis at a distance of -600 μm from the initial position.

[0115] Next, the peaks of each cluster are compared with the previous cluster to determine whether the outer boundary of the alignment has been reached. In Figure 300, it is found that the intensity of the peak of cluster 316 differs from that of the peak of cluster 315 by more than a certain intensity threshold. Therefore, cluster 316 is found to define another x-axis boundary of the alignment.

[0116] In various embodiments, the average intensity of each of clusters 311-316 is calculated. Therefore, each of the six different locations of the OPI relative to the ADE device has a corresponding average intensity, resulting in six average intensities corresponding to the six different locations along the x-axis. The optimized x-position can then be determined by curve fitting of the location point with the highest MS intensity.

[0117] Cluster 320 was similarly measured at six different locations along the y-axis of the OPI. Six average intensities corresponding to the six different locations along the y-axis were also calculated.

[0118] The alignment position of the OPI relative to the ADE device is calculated from the average intensity along the x and y axes. For example, the optimal x-axis position of the OPI can be found by plotting a curve or creating a function based on six average intensities corresponding to six different positions along the x-axis. The optimal x-axis position is then calculated as the position with the highest average intensity based on the curve or function. Similarly, the optimal y-axis position of the OPI is found.

[0119] Figure 4 This illustrates the representation according to various embodiments. Figure 3 The six average peak intensities are calculated for the clusters of OPI at six different locations along the x-axis, and these six average peak intensities are plotted relative to the six different locations of (Versus) along the x-axis in an exemplary figure 400. Figure 4The average strengths of 411, 412, 413, 414, 415, and 416 are respectively Figure 3 The average peak intensity was calculated for clusters 311, 312, 313, 314, 315, and 316. The curve can be fitted to... Figure 4 The points in Figure 400, or functions derived from these points, can be used to determine the position of the OPI along the x-axis. From the curve or function, point 430 is found to be the center point with the highest intensity. Point 430 corresponds to an x-axis position of -100 μm from the initial position of the OPI.

[0120] Figure 4 This demonstrates how to calculate the optimal value of the OPI parameter (x-position) by calculating the value of the parameter that maximizes the average peak height or the intensity of the mass peak. Figure 4 It is also shown that the optimal value of the parameter does not necessarily have to be one of the measured values. A similar plot to Figure 400 can be created for y-axis measurements, and the optimal value for the y-axis position of the OPI can be found similarly. These parameters are preferably set before other parameters, as the other parameters generally depend on the correct alignment of the OPI relative to the ADE device. If the initial point is far apart, the initial spray may not generate any signal. If this occurs, a coarse alignment can be used in both directions and on both axes with a larger gap (e.g., 1 mm) to quickly find the initial point with a signal. This coarse alignment step may potentially cause some droplets to be sprayed to the edges, resulting in residue. This can be mitigated by including some washing steps to remove the residue.

[0121] OPI inner tube location

[0122] Figure 1A The OPI 51 is shown to include an inner capillary 73 and an outer capillary 71. The inner capillary 73 is recessed relative to the outer capillary 71 to minimize overflow and allow solvent to flow into the inner capillary 73. This position of the inner capillary 73 relative to the outer capillary 71 is adjustable.

[0123] In various embodiments, the optimal position of the inner tube 73 relative to the outer tube 71 in OPI 51 is automatically found by moving the inner tube 73 relative to the outer tube 71 and measuring one or more mass peaks at each movement. The optimal position of the inner tube 73 is determined based on the peak intensity or peak width of the mass peaks detected at each position of the inner tube 73 relative to the outer tube 71.

[0124] The optimal position of inner tube 73 is typically the OPI 51 setting used for all experiments or determinations. These optimal values ​​are usually found using standard analytes and standard solutions. The delay time between sample injections is, for example, two seconds.

[0125] Figure 5Figure 500 is an exemplary diagram of clusters of intensity-time mass peaks detected in a standard sample at different positions of the inner tube of the OPI relative to the outer tube of the OPI, according to various embodiments. In Figure 500, pairs or repetitions of clusters 510-550 represent different recessed positions of the inner tube of the OPI. Cluster 561 represents a position returning to pair 510 of the cluster. Each cluster comprises 20 mass peaks detected from 20 sequential jets of a droplet against a standard sample.

[0126] Clusters 510, 520, 530, 540, and 550 correspond to recessed positions of 160 μm, 320 μm, 480 μm, 630 μm, and 790 μm in the inner tube of the OPI, respectively. Cluster 561 corresponds to the OPI inner tube returning to a recessed position of 320 μm. The cluster pairs indicate that the amount of recess of the OPI inner tube relative to the OPI outer tube increases progressively. For example, the range of inner tube recess is the entire operating range of the inner tube's movement relative to the outer tube.

[0127] In various embodiments, average peak height or intensity and average peak width are calculated for each cluster pair 510-550. For example, the calculated peak width is half-peak full width (FWHM). Since peak height and peak width are related, both can be used for determination. Therefore, the inner tube of the OPI has a corresponding average intensity and a corresponding average peak width at each of the five different positions relative to the outer tube of the OPI. Thus, five average peak intensities and five average peak widths corresponding to the five different inner tube positions of the OPI are generated.

[0128] The optimal position of the OPI inner tube is calculated based on either the average peak intensity, the average peak width, or both. For example, the optimal position of the OPI inner tube can be found by plotting curves or creating functions for the five average intensities and five average widths corresponding to the five inner tube positions. The optimal inner tube position is then calculated based on the curves or functions as a location with a high average peak intensity and a narrow average peak width. For example, for the OPI inner tube, the optimal inner tube position is a recessed position of 320 μm. The OPI inner tube is then set to this optimal position, as shown by cluster 561.

[0129] Figure 6 This illustrates the representation according to various embodiments. Figure 5 An exemplary figure 600 shows the cluster pairs of five different recessed locations of the inner tube of the OPI calculated and the five average peak intensities plotted relative to these five different recessed locations. Figure 6 The average strengths of 610, 620, 630, 640, and 650 are respectively Figure 5 The cluster of values ​​for 510, 520, 530, 540, and 550 is used to calculate the average peak intensity. The curve can be fitted to... Figure 6 The points in Figure 600, or functions derived from these points, can be used to determine, for example, the optimal recess position of the inner tube of the OPI. Alternatively, the curve or function can be used in conjunction with another curve or function for another characteristic of the detected quality peak, such as the peak width.

[0130] Figure 7 This illustrates the representation according to various embodiments. Figure 5 An exemplary figure 700 shows the cluster pairs of five different recessed positions of the inner tube of the OPI, and the five average peak widths plotted relative to these five different recessed positions. Figure 7 The average widths of 710, 720, 730, 740, and 750 are respectively Figure 5 The average peak width (FWHM) of the cluster was calculated for 510, 520, 530, 540, and 550. The curve can be fitted to... Figure 7 The points in Figure 700, or functions derived from these points, can be used to determine, for example, the optimal recess position of the inner tube of the OPI. Alternatively, the curve or function can be used in conjunction with another curve or function of another characteristic of the detected quality peak, such as peak intensity.

[0131] In various embodiments, the comparison fit to Figure 6 and 7 The curve of points or comparison from Figure 6 and 7 The function is calculated from the points to find the optimal value for the inner tube position of OPI. For example, an average strength of 620 is... Figure 6 The highest average peak intensity in. Figure 6 Average strength 620 and Figure 7 The average peak width corresponds to 720. Figure 7 The average peak width of 720 is close to or at the minimum measured peak width.

[0132] The goal of adjusting the inner tube of the OPP is to both increase the intensity of the mass peaks and decrease their width. Therefore, with Figure 6 Average strength 620 and Figure 7 The optimal position for the inner tube, corresponding to an average peak width of 720 μm, is 320 μm. Therefore, Figure 6 and 7 This illustrates how to use two characteristics (intensity and width) of the measured mass peak to find the optimal values ​​for the OPI parameters. In various alternative embodiments, only one characteristic of the measured mass peak can be used to find the optimal value for the inner tube position of the OPI. In one example, if a wide range exists for parameter settings that achieve a similar level of optimized performance, then an intermediate value of that range can be used.

[0133] ESI nozzle electrode protrusion

[0134] Figure 1B shows an electrode 164 protruding from the ion source 160, fed by the OPI 51. The length of the electrode 164 protruding from the nozzle of the ion source 160 is an adjustable parameter of the ion source device. The ion source 160 can be, for example, an electrospray ionization (ESI) device.

[0135] The optimal length for electrode 164 to protrude from the nozzle of ion source 160 is automatically found using at least two different methods. In a first method, according to various embodiments, the optimal length for electrode 164 to protrude from the nozzle of ion source 160 is automatically found by moving electrode 164 relative to the nozzle of ion source 160 and monitoring the flow rate of the sample-solvent diluent of OPI 51 using an overflow sensor. For example, the length for electrode 164 to protrude from the nozzle of ion source 160 varies at several different lengths.

[0136] For each length, the flow rate of the OPI 51 sample-solvent diluent varies across several different flow rates until the overflow sensor is triggered. The optimal overflow length is found by determining the length that produces the highest overflow rate, but other parameters can also be monitored. The overflow sensor may also include monitoring of the meniscus.

[0137] In the second method, according to various embodiments, the optimal protrusion length of electrode 164 from the nozzle of ion source 160 is automatically found by moving electrode 164 relative to the nozzle of ion source 160 and measuring one or more mass peaks. Generally, the optimal protrusion length is found by determining the length with the highest flow rate to achieve a peak width less than a certain threshold peak width. For example, the length of electrode 164 protruding from the nozzle of ion source 160 varies at many different lengths. For each length, the flow rate of the sample-solvent diluent of OPI 51 also varies at many different flow rates, and the peak width of the mass peak measured at each flow rate is measured.

[0138] For each length, calculate or determine the highest flow rate that produces a peak width less than a threshold peak width. The threshold peak width is, for example, 0.4 seconds of FWHM. The optimal salient length is then found by determining the length that produces the highest flow rate.

[0139] Two methods for determining the optimal protrusion length of electrode 164 from the nozzle of ion source 160 include varying the flow rate in addition to the protrusion length. An optimal protrusion length can be set for the ion source device used in all experiments or measurements, or it can be varied based on other parameters such as nebulizer flow rate. These optimal values ​​are typically found using standard analytes and standard solutions. For example, an initial protrusion length of 0.3 mm is used. The delay time between sample jets is, for example, two seconds.

[0140] Flow rate

[0141] Once the optimal length of electrode 164 protruding from the nozzle of ion source 160 is found, the optimal flow rate is preferably determined automatically. In various embodiments, the optimal flow rate of the sample-solvent diluent for OPI 51 is automatically found by varying the flow rate and measuring one or more mass peaks for each different flow rate. The optimal flow rate is determined based on the peak intensity of the detected mass peak, the peak width of the detected mass peak, the delay time measured between sample injection and the detected mass peak, or any combination of these measurements.

[0142] An optimal flow rate is typically set for the OPI used in all experiments or measurements. These optimal values ​​are usually found using standard analytes and standard solutions. The delay time between sample injections is, for example, two seconds. For instance, the initial flow rate is 150 μL / min lower than the overflow condition.

[0143] Figure 8 Figure 800 is an exemplary diagram of clusters of intensity relative to time mass peaks detected for a standard sample at different flow rates using an electrode protrusion length of 300 μm according to various embodiments. In Figure 800, clusters 801-810 represent different flow rates of the OPI. Each cluster comprises 20 mass peaks detected from 20 sequential jets of a droplet for a standard sample.

[0144] Clusters 801, 802, 803, 804, 805, 806, 807, 808, 809, and 810 correspond to flow rates of 410, 380, 350, 320, 290, 260, 230, 200, 170, and 140 μL / min, respectively. The clusters show that the OPI flow rate decreases in steps of 30 μL / min.

[0145] In various embodiments, for each cluster 801-810, one or more of the following are calculated: average peak height or intensity, average peak width or average delay time between sample jets, and detected mass peaks. For example, the calculated peak width is FWHM. Thus, each of the ten different flow rates of OPI has one or more of the following: average peak intensity, average peak width or average delay time between sample jets, and detected mass peaks.

[0146] The optimal flow rate is calculated based on one or more of the following: average peak intensity, average peak width or average delay time between sample jets, and the CV of the detected mass peak or peak height (or peak width). For example, the optimal flow rate can be found by plotting a curve or creating a function for ten average peak widths corresponding to ten flow rates and ten delay times corresponding to ten flow rates. The optimal flow rate is then calculated from the curve or function as a flow rate with a narrow average peak width and a long delay time.

[0147] Figure 9 This illustrates the representation according to various embodiments. Figure 8 An exemplary figure 900 shows the calculation of clusters with ten different flow rates of OPI and the plotting of ten average peak widths and nine average delay times relative to the flow rates. Figure 9 The average peak widths of 901, 902, 903, 904, 905, 906, 907, 908, 909, and 910 are respectively... Figure 8 The average peak widths of clusters 801, 802, 803, 804, 805, 806, 807, 808, 809, and 810 are calculated. Curve 930 can be fitted to... Figure 9 The average peak width points of Figure 900, or functions that can be derived from these points, for example, to determine the optimal flow rate.

[0148] Figure 9 The average delay times 911, 912, 913, 914, 915, 916, 917, 918, and 919 are respectively... Figure 8 The average latency was calculated for clusters 801, 802, 803, 804, 805, 806, 807, 808, and 809. Curve 940 can be fitted to... Figure 9 The delay time points in Figure 900, or functions that can be derived from these points, for example, to determine the optimal flow rate.

[0149] In various embodiments, both the average peak width and the average delay time can be used to determine the optimal flow rate. For example, square 950 highlights a range of flow rates where the measurements provide a narrow average peak width and a longer delay time. The optimal flow rate can be selected from the range provided by square 950.

[0150] Figure 10 Figure 1000 is an exemplary diagram of clusters of intensity relative to time mass peaks detected for a standard sample at different flow rates using an electrode protrusion length of 750 μm according to various embodiments. In Figure 1000, clusters 1001-1010 represent different flow rates of the OPI. Each cluster comprises 20 mass peaks detected from 20 successive jets of a droplet for a standard sample.

[0151] Clusters 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, and 1010 correspond to flow rates of 350, 320, 290, 260, 230, 200, 170, 140, 110, and 80 μL / min, respectively. The clusters show that the OPI flow rate decreases in steps of 30 μL / min.

[0152] In various embodiments, for each cluster 1001-1010, one or more of the following are calculated: average peak height or intensity, average peak width or average delay time between sample jets, and detected mass peaks. For example, the calculated peak width is FWHM. Thus, each of the ten different flow rates of OPI has one or more of the following: average peak intensity, average peak width or average delay time between sample jets, and detected mass peaks.

[0153] The optimal flow rate is calculated from one or more of the following: average peak intensity, average peak width or average delay time between sample jets, and detected mass peaks. For example, the optimal flow rate can be found by plotting a curve or creating a function for ten average peak widths corresponding to ten flow rates and ten delay times corresponding to ten flow rates. The optimal flow rate is then calculated from the curve or function as a flow rate with a narrow average peak width and a long delay time.

[0154] Figure 11 The illustrations are based on various embodiments and are shown from the representation. Figure 10 An exemplary figure 1100 shows the cluster calculation of ten different flow rates of OPI and the nine average peak widths and seven average delay times plotted relative to the flow rates. Figure 11 The average widths 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, and 1110 are respectively Figure 10 The average peak widths were calculated for clusters 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, and 1010. Curve 1130 can be fitted to... Figure 11 The average peak width points in Figure 1100, or functions that can be derived from these points, for example, to determine the optimal flow rate.

[0155] Figure 11 The average latency times 1113, 1114, 1115, 1116, 1117, 1118, and 1119 are respectively... Figure 10 The average latency was calculated for clusters 1003, 1004, 1005, 1006, 1007, 1008, and 1009. Curve 1140 can be fitted to... Figure 11 The delay time points in Figure 1100, or functions that can be derived from these points, for example, to determine the optimal flow rate.

[0156] In various embodiments, both the average peak width and the average delay time can be used to determine the optimal flow rate. For example, square 1150 highlights a range of flow rates where the measurements provide a narrow average peak width and a longer delay time. The optimal flow rate can be selected from the range provided by square 1150.

[0157] Figure 8-11This illustrates how two characteristics of the measured mass peak (width and delay time) can be used to find the optimal values ​​for the parameters of the OPI. In various alternative embodiments, only one characteristic of the measured mass peak can be used to find the optimal value for the OPI flow rate.

[0158] Figure 8-11 It also shows how the length of the electrode protrusion affects the optimal flow rate. Figure 9 The results show that for an electrode protrusion length of 300 μm defined by a square of 950, the optimal flow rate ranges between 280 and 390 μL / min. In contrast, Figure 11 The results show that for an electrode protrusion length of 750 μm defined by square 1150, the optimal flow rate ranges between 170 μL / min and 270 μL / min. This comparison shows that increasing the electrode protrusion length reduces the optimal flow rate.

[0159] injection volume

[0160] The optimal jet sample volume provided by the ADE device provides optimal sensitivity for AEMS experiments. For example, for a “clean” matrix or solution, sensitivity can be easily improved by increasing the sample loading within a certain range (e.g., <200 nL, preferably <20 nL). However, when the matrix is ​​complex, increasing the jet volume does not always help improve sensitivity due to ionization suppression. In various embodiments, the jet volume is optimized to obtain optimal sensitivity by monitoring the intensity of the detected mass peak while varying the jet volume.

[0161] To adjust the sample volume, ADE devices can vary the volume of fluid ejected in each droplet or increase the number of droplets ejected to produce a single sample jet. In the latter case, the droplets are ejected at a high frequency, causing them to merge and form a single jet with a volume larger than any individual droplet. These methods can be combined. For some ADE devices, the range of different volumes that can be ejected in each droplet is limited. For example, for some ADE devices, the droplet volume range can be between 1 and 10 nL. Therefore, such devices, for example, cannot eject droplets of 50 nL.

[0162] Therefore, in various embodiments, varying the number of droplets sprayed to produce a single sample jet is a preferred method for increasing volume. For example, spraying multiple droplets at a high jet rate causes the multiple droplets to merge at the OPI and become a single jet with a higher jet volume. A high jet rate can be, but is not limited to, five droplets per second.

[0163] In various embodiments, the optimal jet volume for the ADE device is automatically found by varying the jet volume and measuring one or more mass peaks for each jet volume. The optimal jet volume is determined from the peak intensity of the mass peaks detected for various jet volumes.

[0164] The optimal jet volume is typically set for a specific analyte and analyte solution or matrix, or at a given flow rate, or stored in a memory device. If the optimal jet volume for a specific analyte and analyte solution is stored in a memory device, it can be retrieved from the memory device, and the ADE device can be set to the optimal jet volume each time the analyte in that analyte solution is analyzed.

[0165] Figure 12 Figure 1200 is an exemplary graph showing a series of intensity-time mass peaks detected for a standard sample from three different types of solutions according to various embodiments, illustrating how the intensity of the mass peaks varies with the type of solution used as the jet volume increases. Figure 1200 shows three different series of intensity-time mass peaks 1210, 1220, and 1230.

[0166] In each series of peaks, the same standard compound was analyzed. Furthermore, 10 different sample jet volumes were used in each series of peaks. These different sample jet volumes were created using different numbers of drops for each sample jet. The initial number of drops was one. This was increased in increments of one drop up to a maximum of 10 drops. Each different sample jet volume was performed twice. Therefore, in each series of peaks, there is a pair of mass peaks for each different jet volume. This results in a total of 20 peaks in each series.

[0167] A series of peaks 1210 represents the intensity measured for the standard compound in water. The series 1210 shows that the measured peak intensity steadily increases with increasing spray volume. Therefore, for this “clean” solution or matrix, the optimal spray volume is the highest spray volume.

[0168] A series of peaks 1220 represents the intensity measured for the standard compound in broken NIST plasma. A series of peaks 1230 represents the intensity measured for the standard compound in broken high-lipid plasma. Series 1220 and 1230 show that after a spray volume of approximately four or five drops, the intensity of the measured peaks stops increasing with increasing spray volume. Therefore, for these solutions or matrices, the optimal spray volume is approximately four or five drops per sample.

[0169] A series of peaks, 1210, 1220, and 1230, show that the intensity of the mass peaks produced varies with increasing injection volume, depending on the solution or matrix used. Therefore, it is possible to... Figure 12The tuning type shown automatically finds the optimal injection volume for a specific substrate or measurement.

[0170] Finding the optimal jet volume will be determined by the requirements of the measurement. Typically, a jet volume reaching the upper limit of the linear peak height increase will be used. In some cases, this is not preferred, such as when, for example, the maximum volume for the linear peak height increase range is still insufficient to meet the required measurement sensitivity, the jet volume can be further increased until the desired sensitivity is achieved. Alternatively, in some complex matrices, as long as the measurement sensitivity requirements are met, it may be desirable to limit the jet volume to the lowest possible level to avoid potential system contamination and improve electrode lifespan.

[0171] Injection delay time

[0172] The analytical throughput of an AEMS system can be adjusted by changing the delay time between injections from the ADE device. The shortest delay time (for optimal analytical throughput) should satisfy the requirement for accurate quantification of all injections. Faster throughput is possible when absolute quantification is not required. However, this required delay time depends on the desired concentration dynamic range between adjacent injections.

[0173] In various embodiments, throughput is optimized by varying the latency of the ADE device and determining whether the peak area of ​​a jet following a jet that produces a larger peak is similar to the peak area of ​​a jet that does not follow a jet that produces a larger peak. In other words, throughput is optimized by varying the latency and monitoring the peak area to determine when a peak following a larger peak no longer convolves with that larger peak.

[0174] In various embodiments, the optimal injection delay time for the ADE device is automatically found by varying the injection delay time and measuring one or more mass peaks for each injection delay time. The optimal injection delay time is determined from the peak area of ​​the mass peaks detected for various injection delay times.

[0175] The optimal jetting delay time for a specific analyte and analyte solution or matrix is ​​typically set or stored in a memory device. If the optimal jetting delay time for a specific analyte and analyte solution is stored in a memory device, it can be retrieved from the memory device, and the ADE device can be set to have the optimal jetting delay time each time the analyte in that analyte solution is analyzed.

[0176] Figure 13Figure 1300, an exemplary representation of a series of intensity-time mass peaks detected from a standard sample ejected from the same orifice according to various embodiments, illustrates how the distance between peaks can be optimized when samples have similar concentrations. In Figure 1300, all eight peaks have similar intensities. This is because they were all generated for samples from the same orifice, and therefore for samples with the same concentration. Thus, the distance between peaks is minimized by reducing the ejection delay time. The ejection delay time used to generate the peaks in Figure 1300 is 0.98 seconds.

[0177] However, the intensity of peaks can vary significantly when they are generated from different concentrations of the sample. This can happen, for example, when the sample is analyzed using different wells with different concentrations.

[0178] Figure 14 This is an exemplary series 1400 of intensity versus time mass peak plots from three different experiments according to various embodiments, wherein samples are ejected from a series of different wells using different ejection delay times. The concentration in the first well of each of the five wells in each series is three orders of magnitude higher than the concentration in the other four wells.

[0179] The results of the first experiment with a spray delay time of 1.09 seconds are shown in Figure 1410. The first peak 1411 corresponds to the first well with a sample concentration three orders of magnitude higher than the following four wells. The intensity of peak 1411 is much greater than the intensity range shown in the figure. Peak 1411 is so large or so intense that it includes peak 1412, which is the immediate following peak. In other words, peak 1411 is so intense that peak 1412 convolves with peak 1411. Peaks 1413, 1414, and 1415 follow peak 1412 and originate from wells with similar concentrations to the well that produced peak 1412.

[0180] Peak 1412 can be estimated from the convolution with peak 1411 using a peak discovery algorithm. In various embodiments, the area of ​​the estimated peak 1412 is then compared with the areas of one or more peaks 1413, 1414, and 1415 within an area threshold. However, due to the convolution with peak 1411, the estimated area of ​​peak 1412 is unlikely to match the areas of one or more peaks 1413, 1414, and 1415 within an area threshold. Therefore, the 1.09-second jet delay time used for the results in Figure 1410 is not optimal for the sample concentration used.

[0181] The results of the second experiment with a jet delay time of 1.37 seconds are shown in Figure 1420. Again, the first peak 1421 corresponds to the first well with a sample concentration three orders of magnitude higher than the following four wells. Due to the increased jet delay time, peak 1421 does not completely encompass peak 1422, which is the immediate follower. However, it still distorts the shape of peak 1422. In other words, peak 1422 is still convolved with peak 1421. Peaks 1423, 1424, and 1425 follow peak 1422 and originate from wells with similar concentrations to the well that produced peak 1422.

[0182] Furthermore, peak 1422 can be estimated from the convolution with peak 1421 using a peak discovery algorithm. In various embodiments, the estimated area of ​​peak 1422 is then compared with the areas of one or more peaks 1423, 1424, and 1425 within an area threshold. However, due to the convolution with peak 1421, the estimated area of ​​peak 1422 is still unlikely to match the areas of one or more peaks 1423, 1424, and 1425 within an area threshold. Therefore, the 1.37-second jet delay time used for the results in Figure 1420 is still not optimal for the sample concentration used.

[0183] The results of the third experiment with a spray delay time of 1.56 seconds are shown in Figure 1430. Again, the first peak 1431 corresponds to the first well with a sample concentration three orders of magnitude higher than the following four wells. Due to the increased spray delay time, peak 1431 no longer appears to influence peak 1432, which is the immediate follower. In other words, peak 1432 no longer convolves with peak 1431. Peaks 1433, 1434, and 1435 follow peak 1432 and originate from wells with similar concentrations to the well that produced peak 1432.

[0184] In various embodiments, the area of ​​peak 1432 is then compared with the areas of one or more peaks 1433, 1434, and 1435 within an area threshold. The area of ​​peak 1432 may now match the areas of one or more peaks 1423, 1424, and 1425 within an area threshold. Therefore, the 1.56-second spray delay time used for the results in Figure 1420 is optimal for the sample concentration used.

[0185] Figures 1410-1430 illustrate how the injection delay time can be automatically adjusted to find the optimal injection delay time. Again, the selected optimal delay time does not need to be the actual delay time used for measurement. Alternatively, it can be the delay time calculated from a curve or function derived from the measured data.

[0186] Parameters and features

[0187] As described above, in various embodiments, the operating parameters of the ADE device, OPI, or ion source device of the AEMS system are automatically calculated from a series of sample MS experiments. In these experiments, the values ​​of one or more operating parameters of the ADE device, OPI, or ion source device vary. One or more mass peaks are detected for each value of one or more operating parameters. Based on this data, the optimal value for one or more operating parameters is calculated.

[0188] More specifically, the optimal value for one or more operating parameters is calculated from one or more characteristics of one or more mass peaks. The characteristics of one or more mass peaks may include, but are not limited to, peak height, peak width, delay time between jetting and mass analysis, or peak area.

[0189] Furthermore, as shown above, one or more other operating parameters can be used to calculate the optimal value of the operating parameters. Therefore, there is a complex relationship between the operating parameters and the peak quality characteristics.

[0190] Figure 15 This is an exemplary matrix plot 1500 illustrating one or more mass peak characteristics according to various embodiments. These mass peak characteristics can be used to calculate optimal values ​​for different operating parameters of an ADE device, OPI, or ion source device. In the matrix plot 1500, columns represent peak characteristics and rows represent operating parameters of the ADE device, OPI, or ion source device. An "X" indicates a relationship between the characteristic and the operating parameter.

[0191] A system for calculating optimal parameters using a mass spectrometer

[0192] Figure 16 Figure 1600 is a schematic diagram of a system for automatically calculating the optimal value of at least one operating parameter for an ADE device, OPI or ion source device using a mass spectrometer, according to various embodiments. Figure 16 The system includes an ADE device 1610, an OPI device 1620, an ion source device 1630, a mass spectrometer 1640, and a processor 1650.

[0193] The ADE device 1610 is suitable for performing one or more sprays of a sample over time. The ADE device 1610 can be, for example... Figure 1A ADE device 11.

[0194] Return to Figure 16 The OPI 1620 is adapted to receive one or more jets over time at the inlet 1621 of the inner tube 1622, mix the received jets with a solvent to form a series of sample-solvent diluents, and transfer the series of diluents to the outlet 1623 of the inner tube 1622. The OPI 1620 can be, for example... Figure 1A OPI 51.

[0195] Return to Figure 16 Ion source device 1630 is adapted to receive and ionize a series of diluents, thereby generating an ion beam 1631. Ion source device 1630 can be, for example, an electrospray ionization (ESI) device. Ion source device 1630 in... Figure 16 It is shown as part of mass spectrometer 1640, but it could also be a separate device.

[0196] Mass spectrometer 1640 is adapted to receive ion beam 1631 and perform mass analysis of ion beam 1631 over time, thereby producing intensity-time mass peaks corresponding to one or more ejections. Mass spectrometer 1640 can perform MS or MS / MS. Mass spectrometer 1640 can be any type of mass spectrometer. Mass spectrometer 1640 is shown as including a four-pole time-of-flight (TOF) mass analyzer, but mass spectrometer 1640 can include any type of mass analyzer, such as a triple quadrupole mass analyzer.

[0197] Processor 1650 communicates with ADE device 1610, OPI 1620, ion source device 1630, and mass spectrometer 1640. For each of a plurality of parameter values ​​1660 for at least one parameter of ADE device 1610, OPI 1620, or ion source device 1630, processor 1650 performs three steps. For example, processor 1650 reads a plurality of parameter values ​​1660 from a memory device (not shown). First, processor 1650 sets at least one parameter to each value. Second, processor 1650 instructs ADE device 1610, OPI 1620, ion source device 1630, and mass spectrometer 1640 to generate one or more intensity-time mass peaks 1641 for the sample. The sample may be obtained from one of wells 1611 or from two or more wells. Third, processor 1650 calculates a feature value 1651 for at least one characteristic of the one or more intensity-time mass peaks 1641. A plurality of feature values ​​corresponding to the plurality of parameter values ​​are generated.

[0198] The processor 1650 calculates the optimal value 1652 of at least one parameter from a plurality of eigenvalues ​​corresponding to a plurality of parameter values ​​1660.

[0199] In various embodiments, processor 1650 may also set at least one parameter to an optimal value 1652 or processor 1650 may also store the optimal value 1652 in a memory device (not shown) for the sample.

[0200] In various embodiments, the sample is a standard sample. For example, a standard sample is a standard analyte in a standard solution.

[0201] In various embodiments, optimal parameters are calculated for the alignment of ADE device 1610 and OPI 1620. Specifically, at least one parameter of ADE device 1610, OPI 1620, or ion source device 1630 includes the x-axis position of OPI 1620 relative to the position of ADE device 1610 or the y-axis position of OPI 1620 relative to the position of ADE device 1610. At least one feature of one or more intensities relative to time-mass peak 1641 includes peak height or intensity. Processor 1650 calculates an optimal value 1652 for at least one parameter by calculating a value for at least one parameter, which generates a maximum value for peak height from a plurality of feature values ​​corresponding to a plurality of parameter values ​​1660.

[0202] In various embodiments, optimal parameters are calculated for the position of the inner tube 1622 of the OPI 1620 relative to the outer tube 1624. Specifically, at least one parameter of the ADE device 1610, the OPI 1620, or the ion source device 1630 includes the position of the inner tube 1622 of the OPI 1620 relative to the outer tube 1624 at the inlet 1621 of the inner tube 1622. At least one feature of one or more intensity-relative-time mass peaks 1641 includes peak height or peak width. The processor 1650 calculates an optimal value 1652 for at least one parameter by calculating a value for at least one parameter that produces a maximum peak height or a minimum peak width from a plurality of feature values ​​corresponding to a plurality of parameter values ​​1660.

[0203] In various embodiments, optimal parameters are calculated or determined by optimizing the protrusion length of the electrode 1632 of the ion source device 1630. Specifically, at least one parameter of the ADE device 1610, OPI 1620, or ion source device 1630 includes the length by which the electrode 1632 of the outlet 1623 of the inner tube 1622 protrudes from the nozzle 1633 of the ion source device 1630. At least one feature of one or more intensity relative to time-mass peaks 1641 includes peak width or peak height. The processor 1650 also instructs the OPI 1620 to change the flow rate of the diluent among multiple flow rate values ​​for each value of at least one parameter until the width value for the peak width of one or more intensity relative to time-mass peaks 1641 is less than a peak width threshold. A width value and a flow rate value are generated for each value of at least one parameter. The processor 1650 calculates the optimal value 1652 of at least one parameter by calculating the value of at least one parameter that produces the peak width with the highest flow rate from multiple feature values ​​corresponding to multiple parameter values ​​1660.

[0204] In various embodiments, optimal parameters are calculated for the flow rate of OPI 1620. Specifically, at least one parameter of ADE device 1610, OPI 1620, or ion source device 1630 includes the flow rate of OPI 1620. At least one characteristic of one or more intensities relative to time-mass peak 1641 includes peak height, peak width, or delay time between sample ejection and sample mass analysis. Processor 1650 calculates an optimal value 1652 for at least one parameter by calculating the value of at least one parameter, which generates a maximum peak height, a minimum peak width, or a maximum delay time from a plurality of characteristic values ​​corresponding to a plurality of parameter values ​​1660.

[0205] In various embodiments, the sample is an experimental sample. For example, an experimental sample is an experimental analyte in an experimental solution.

[0206] In various embodiments, optimal parameters are calculated for the jet volume of the ADE device 1610. Specifically, at least one parameter of the ADE device 1610, OPI 1620, or ion source device 1630 includes the droplet size of the ADE device 1610 or the droplet count per sample jet of the ADE device 1610. At least one feature of one or more intensity-relative time-mass peaks 1641 includes peak height or peak area. The processor 1650 calculates an optimal value 1652 for at least one parameter by calculating the value of at least one parameter, which yields the maximum value of the peak height or peak area from a plurality of feature values ​​corresponding to a plurality of parameter values ​​1660. In some cases, CV may need to be considered. For example, for some conditions, even if the peak may be sharper and / or higher, if the CV is poor, the conditions used to generate such peaks will not be used.

[0207] In various embodiments, an optimal parameter is calculated for the delay time between sample ejections from the ADE device 1610. Specifically, at least one parameter of the ADE device 1610, OPI 1620, or ion source device 1630 includes the delay time between sample ejections from the ADE device 1610. At least one feature of one or more intensity-relative-time mass peaks 1641 includes peak area. The processor 1650 calculates the optimal value of at least one parameter by calculating the minimum delay time between sample ejections, which still allows the peak area of ​​one or more intensity-relative-time peaks 1641 immediately following a more intense peak to have a similar peak area to one or more intensity-relative-time peaks 1641 that do not immediately follow a more intense peak.

[0208] In various embodiments, processor 1650 is used to send and receive instructions, control signals, and data to and from ADE device 1610, OPI 1620, ion source device 1630, and mass spectrometer 1640. Processor 1650 controls or provides instructions by, for example, controlling one or more voltage, current, or pressure sources (not shown). Processor 1650 may be as follows: Figure 16 The separate device shown may be a processor or controller of the ADE device 1610, OPI 1620, ion source device 1630, or mass spectrometer 1640. Processor 1650 may be, but is not limited to, a controller, computer, microprocessor, etc. Figure 2 A computer system, or any device capable of sending and receiving control signals and data and analyzing the data.

[0209] Methods for calculating optimal parameters using mass spectrometry

[0210] Figure 17 This is a flowchart illustrating a method 1700 for automatically calculating the optimal value of at least one operating parameter of an ADE device, OPI, or ion source device using a mass spectrometer, according to various embodiments.

[0211] In step 1710 of method 1700, for each of a plurality of parameter values ​​for at least one parameter of the ADE device, OPI, or ion source device, three steps are performed using a processor. First, at least one parameter is set to that value. Second, the ADE device, OPI, ion source device, and mass spectrometer are instructed to generate one or more intensity-time mass peaks for the sample. Third, characteristic values ​​are calculated for at least one characteristic of the one or more intensity-time mass peaks. A plurality of characteristic values ​​corresponding to the plurality of parameter values ​​are generated.

[0212] In step 1720, the optimal value for at least one parameter is calculated from a plurality of eigenvalues ​​corresponding to a plurality of parameter values.

[0213] An ADE (Aspect-Definition) device is suitable for performing one or more jets of a sample over time. An OPI (Optical Probe Injection) device is suitable for receiving one or more jets over time at the inlet of the inner tube, mixing the received jets with solvent to form a series of sample-solvent diluents, and transferring the series of diluents to the outlet of the inner tube. An ion source device is suitable for receiving and ionizing the series of diluents to generate an ion beam. A mass spectrometer is suitable for receiving the ion beam over time and performing mass analysis on the ion beam to generate time-dependent mass peaks corresponding to one or more jets.

[0214] Computer program products that use mass spectrometry to calculate optimal parameters

[0215] In various embodiments, the computer program product includes a tangible computer-readable storage medium containing a program having instructions executable on a processor to perform a method for automatically calculating optimal values ​​for at least one operating parameter of an ADE device, OPI, or ion source device using a mass spectrometer. This method is executed by a system comprising one or more different software modules.

[0216] Figure 18 This is a schematic diagram of a system 1800 according to various embodiments, comprising one or more different software modules for performing methods for automatically calculating optimal values ​​of at least one operating parameter of an ADE device, OPI, or ion source device using a mass spectrometer. System 1800 includes a control module 1810 and an analysis module 1820.

[0217] For each of a plurality of parameter values ​​for at least one parameter of the ADE device, OPI, or ion source device, the control module 1810 sets at least one parameter to that value. The control module 1810 then instructs the ADE device, OPI, ion source device, and mass spectrometer using the control module to generate one or more intensity-time mass peaks for the sample. Finally, the analysis module 1820 calculates characteristic values ​​for at least one feature of the one or more intensity-time mass peaks, thereby generating a plurality of characteristic values ​​corresponding to the plurality of parameter values.

[0218] Analysis module 1820 calculates the optimal value of at least one parameter from multiple feature values ​​corresponding to multiple parameter values.

[0219] An ADE (Aspect-Definition) device is suitable for performing one or more sample ejections over time. An OPI (Optical Probe Injection) device is suitable for receiving one or more ejections over time at the inlet of the inner tube, mixing the received ejections with solvent to form a series of sample-solvent diluents, and transferring the series of diluents to the outlet of the inner tube. An ion source device is suitable for receiving and ionizing the series of diluents to generate an ion beam. A mass spectrometer is suitable for receiving the ion beam over time and performing mass analysis on the ion beam to produce a time-dependent mass peak corresponding to one or more ejections.

[0220] A system that uses an overflow sensor to calculate the length of an electrode protrusion.

[0221] Figure 19 This is a schematic diagram 1900 of a system for automatically calculating the optimal protrusion length of the electrodes of an ion source device using an overflow sensor, according to various embodiments. Figure 19 The system includes an ADE device 1910, an OPI device 1920, an ion source device 1930, an overflow sensor 1940, and a processor 1950.

[0222] The ADE device 1910 is suitable for performing one or more sample sprays over time. The ADE device 1910 can be, for example... Figure 1A ADE device 11.

[0223] Return to Figure 19 The OPI 1920 is adapted to receive one or more jets over time at the inlet 1921 of the inner tube 1922, mix the received jets with a solvent that can be included in the inner tube 1922 to form a series of sample-solvent diluents, and transfer the series of diluents to the outlet 1923 of the inner tube 1922. The OPI 1920 can be, for example... Figure 1A OPI 51.

[0224] Return to Figure 19 The ion source device 1930 is adapted to receive and ionize a series of diluents, thereby generating an ion beam 1931. For example, the ion source device 1930 may be an electrospray ionization (ESI) device.

[0225] The overflow sensor 1940 is suitable for measuring the flow rate of a series of diluents and triggering a notification if the flow rate exceeds a threshold.

[0226] Processor 1950 communicates with ADE device 1910, OPI 1920, ion source device 1930, and overflow sensor 1940. For each of a plurality of length values ​​1960 for the protruding length of the electrode 1932 at the outlet 1923 of the inner tube 1922 of OPI 1920 from the nozzle 1933 of ion source device 1930, processor 1950 performs three steps. First, processor 1950 sets the length for each value. Second, processor 1950 instructs ADE device 1910, OPI 1920, and ion source device 1930 to generate an ion beam 1931 for the sample at each of a plurality of flow rate values ​​until overflow sensor 1940 triggers a notification. A plurality of flow rates are generated for each value. The sample can be obtained from one of orifices 1911 or from two or more orifices. Third, processor 1950 calculates the highest flow rate value for each value from the plurality of flow rates. A plurality of highest flow rate values ​​corresponding to the plurality of length values ​​1960 are generated.

[0227] The processor 1950 calculates the optimal value 1952 of the length by calculating the length value that produces the highest overflow flow rate from among multiple highest flow rate values ​​corresponding to multiple length values ​​1950.

[0228] In various embodiments, processor 1950 is used to send and receive instructions, control signals, and data to and from ADE device 1910, OPI 1920, ion source device 1930, and mass spectrometer 1940. Processor 1950 controls or provides instructions by, for example, controlling one or more voltage, current, or pressure sources (not shown). Processor 1950 may be as follows: Figure 19The separate device shown may be a processor or controller of ADE device 1910, OPI 1920, ion source device 1930, or mass spectrometer 1940. Processor 1950 may be, but is not limited to, a controller, computer, microprocessor, etc. Figure 2 A computer system, or any device capable of sending and receiving control signals and data and analyzing the data.

[0229] Method for calculating electrode protrusion length using an overflow sensor

[0230] Figure 20 This is a flowchart illustrating a method 2000 for automatically calculating the optimal protrusion length of an electrode in an ion source device using an overflow sensor, according to various embodiments.

[0231] In step 2010 of method 2000, three steps are performed using a processor for each of a plurality of length values ​​for the length of the electrode protruding from the nozzle of the ion source device at the outlet of the inner tube of the OPI. First, the length is set for each value. Second, the ADE device, OPI, and ion source device are instructed to generate an ion beam for the sample at each of a plurality of flow rate values ​​until an overflow sensor triggers a notification. There are multiple flow rates for each value. Third, the highest flow rate value is calculated for each value from the plurality of flow rates. Multiple highest flow rate values ​​are generated corresponding to the plurality of length values.

[0232] In step 2020, the processor calculates the optimal value of the length by calculating the length value that produces the highest overflow flow rate from multiple highest flow rate values ​​corresponding to multiple length values.

[0233] The ADE device is suitable for performing one or more sample jets over time. The OPI device is suitable for receiving one or more jets over time at the inlet of the inner tube, mixing the received jets with the solvent in the inner tube to form a series of sample-solvent diluents, and transferring the series of diluents to the outlet of the inner tube. The ion source device is suitable for receiving the series of diluents and ionizing the series of diluents to generate an ion beam. The overflow sensor is suitable for measuring the flow rate of the series of diluents and triggering a notification when the flow rate exceeds a threshold.

[0234] Computer program product that uses an overflow sensor to calculate the length of the electrode protrusion.

[0235] In various embodiments, the computer program product includes a tangible computer-readable storage medium containing a program having instructions executable on a processor for performing a method for automatically calculating the optimal protrusion length of an electrode in an ion source device using an overflow sensor. The method is executed by a system comprising one or more different software modules.

[0236] Return to Figure 18According to various embodiments, system 1800 can also be used to perform a method for automatically calculating the optimal protrusion length of the electrodes of an ion source device using an overflow sensor. System 1800 includes a control module 1810 and an analysis module 1820.

[0237] For each of a plurality of length values ​​for the length of the electrode protruding from the nozzle of the ion source device at the outlet of the inner tube of the OPI, the control module 1810 sets that length for each value. The control module 1810 then instructs the ADE device, the OPI, and the ion source device to generate an ion beam for the sample at each of a plurality of flow rate values ​​until an overflow sensor triggers a notification, thus generating multiple flow rates for each value. The analysis module 1820 calculates the highest flow rate value for each value from the plurality of flow rates, thereby generating a plurality of highest flow rate values ​​corresponding to the plurality of length values.

[0238] Analysis Model 1820 calculates the optimal length by calculating the length value that produces the highest overflow flow from multiple highest flow values ​​corresponding to multiple length values.

[0239] The ADE device is suitable for performing one or more jets of a sample over time. The OPI device is suitable for receiving one or more jets over time at the inlet of the inner tube, mixing the received jets with the solvent in the inner tube to form a series of sample-solvent diluents, and transferring the series of diluents to the outlet of the inner tube. The ion source device is suitable for receiving the series of diluents and ionizing the series of diluents to generate an ion beam. The overflow sensor is suitable for measuring the flow rate of the series of diluents and triggering a notification when the flow rate exceeds a threshold.

[0240] Furthermore, in describing various embodiments, the specification may have given methods and / or processes as a specific order of steps. However, the method or process should not be limited to the specific order of steps described herein, as long as the method or process does not depend on the specific order of steps set forth herein. Other orders of steps may be possible, as will be readily recognized by those skilled in the art. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims relating to the method and / or process should not be limited to performing the steps in the written order, and those skilled in the art will readily recognize that the order may vary and still remain within the spirit and scope of the various embodiments.

Claims

1. A system for automatically calculating the optimal value of at least one operating parameter of an acoustic droplet ejection ADE device, an open port interface (OPI) device, or an ion source device using a mass spectrometer, comprising: ADE equipment is suitable for performing one or more sprays of samples over time; OPI is adapted to receive one or more sprays over time at the inlet of the inner tube, mix the received sprays with solvent to form a series of sample-solvent diluents, and transfer the series of diluents to the outlet of the inner tube. An ion source device suitable for receiving and ionizing a series of diluents to generate an ion beam; A mass spectrometer adapted to receive an ion beam over time and perform mass analysis on the ion beam, thereby generating a time-intensity mass peak corresponding to the one or more jets. as well as The processor, which communicates with ADE devices, OPI, ion source devices, and mass spectrometers, is configured to: For each of a plurality of parameter values ​​for at least one parameter of an ADE device, OPI, or ion source device, the at least one parameter is set to each value to instruct the ADE device, OPI, ion source device, and mass spectrometer to generate one or more intensity-time mass peaks for the sample, and a characteristic value of at least one feature of the one or more intensity-time mass peaks is calculated, thereby generating a plurality of characteristic values ​​corresponding to the plurality of parameter values. The optimal value of at least one parameter is calculated from the plurality of feature values ​​corresponding to the plurality of parameter values.

2. The system of claim 1, wherein the processor further sets the at least one parameter to an optimal value, or wherein the processor further stores the optimal value in a memory device for the sample.

3. The system of claim 1 or 2, wherein the ADE device is adapted to perform the spraying of a sample comprising a standard analyte in a standard solution.

4. The system as described in claim 3, The at least one parameter of the ADE device, OPI, or ion source device includes the OPI x-axis position relative to the position of the ADE device or the OPI y-axis position relative to the position of the ADE device. The at least one characteristic of the intensity of one or more times relative to the time-mass peak includes the peak height, and The processor calculates the optimal value of the at least one parameter by calculating the value of the at least one parameter that produces the maximum peak height from a plurality of feature values ​​corresponding to the plurality of parameter values.

5. The system as described in claim 3, The at least one parameter of the ADE device, OPI, or ion source device includes the position of the inner tube of the OPI relative to the outer tube at the inlet of the inner tube. The at least one characteristic of the intensity of one or more intensity relative to the time-mass peak includes peak height or peak width, and The processor calculates the optimal value of the at least one parameter by calculating the value of the at least one parameter that produces the maximum value of the peak height or the minimum value of the peak width from a plurality of feature values ​​corresponding to the plurality of parameter values.

6. The system as described in claim 3, The at least one parameter of the ADE device, OPI, or ion source device includes the length of the electrode at the outlet of the inner tube protruding from the nozzle of the ion source device. The at least one characteristic of the intensity of one or more times relative to the time-mass peak includes peak width. in, For each value of the at least one parameter, the processor also instructs the OPI to vary the diluent flow rate among multiple flow rate values ​​until the peak width value of the one or more intensities relative to the time-mass peak is less than a peak width threshold, thereby generating a width value and a flow rate value for each value. The processor calculates the optimal value of the at least one parameter by calculating the value of the at least one parameter that produces the peak width with the highest flow rate from a plurality of feature values ​​corresponding to the plurality of parameter values.

7. The system as described in claim 3, The at least one parameter of the ADE device, OPI, or ion source device includes the flow rate of the OPI. The one or more intensities relative to the time-mass peak, comprising at least one characteristic including peak height, peak width, or the delay time between sample ejection and sample quality analysis, and The processor calculates the optimal value of the at least one parameter by calculating the value of the at least one parameter that produces the maximum value of the peak height, the minimum value of the peak width, or the maximum value of the delay time from a plurality of feature values ​​corresponding to the plurality of parameter values.

8. The system of claim 1 or 2, wherein the ADE device is adapted to perform the spraying of a sample comprising an experimental analyte in an experimental solution.

9. The system as described in claim 8, The at least one parameter of the ADE device, OPI, or ion source device includes the droplet size for the ADE device or the droplet count per sample ejection for the ADE device. The at least one characteristic of the intensity of one or more times relative to the time-mass peak includes the peak height, and The processor calculates the optimal value of the at least one parameter by calculating the value of the at least one parameter that produces the maximum peak height from a plurality of feature values ​​corresponding to the plurality of parameter values.

10. The system as described in claim 8, The at least one parameter of the ADE device, OPI, or ion source device includes the delay time between sample ejections for the ADE device. The at least one characteristic of the intensity of one or more times relative to the time-mass peak includes the peak area, and The processor calculates the optimal value of at least one parameter by calculating the minimum delay time between sample injections, which still allows the peak area of ​​the one or more intensity peaks that immediately follow the stronger peak in the time peaks to have a similar peak area to the one or more intensity peaks that do not immediately follow the stronger peak in the time peaks.

11. The system of claim 1, further comprising: An overflow sensor is used to measure the flow rate of a series of diluents and trigger a notification when the flow rate exceeds a threshold. The processor also communicates with an overflow sensor, and the processor is further configured to: For each of a plurality of length values ​​for the length of the electrode protruding from the nozzle of the ion source device at the outlet of the inner tube of the OPI, this length is set for each value, instructing the ADE device, OPI, and ion source device to generate an ion beam for the sample at each of a plurality of flow rate values ​​until an overflow sensor triggers a notification, thereby generating a plurality of flow rates for each value, and calculating the highest flow rate for each value from the plurality of flow rates, thereby generating a plurality of highest flow rate values ​​corresponding to the plurality of length values, and The optimal value of the length is calculated by calculating the length value that produces the highest overflow flow rate from among the plurality of highest flow rate values ​​corresponding to the plurality of length values.

12. A method for automatically calculating the optimal value of at least one operating parameter of an acoustic droplet ejection ADE device, an open port interface (OPI) device, or an ion source device using a mass spectrometer, comprising: For each of a plurality of parameter values ​​for at least one parameter of an ADE device, OPI, or ion source device, the at least one parameter is set to each value, instructing the ADE device, OPI, ion source device, and mass spectrometer to generate one or more intensity-time mass peaks for the sample, and using a processor to calculate feature values ​​for at least one characteristic of the one or more intensity-time mass peaks, thereby generating a plurality of feature values ​​corresponding to the plurality of parameter values, and Calculate the optimal value of at least one parameter from the plurality of feature values ​​corresponding to the plurality of parameter values. ADE devices are suitable for performing one or more sprays of samples over time. The OPI is adapted to receive one or more sprays over time at the inlet of the inner tube, mix the received sprays with the solvent in the inner tube to form a series of sample-solvent diluents, and transfer the series of diluents to the outlet of the inner tube. The ion source equipment is suitable for receiving and ionizing a series of diluents, thereby generating an ion beam. The mass spectrometer is adapted to receive the ion beam over time and perform mass analysis on the ion beam, thereby generating a time-dependent mass peak corresponding to the one or more jets.

13. The method of claim 12, further comprising: For each of a plurality of length values ​​for the length of the electrode protruding from the nozzle of the ion source device at the outlet of the inner tube of the OPI, this length is set for each value, instructing the ADE device, OPI, and ion source device to generate an ion beam for the sample at each of a plurality of flow rate values ​​until an overflow sensor triggers a notification, thereby generating a plurality of flow rates for each value, and using a processor to calculate the highest flow rate for each value from the plurality of flow rates, thereby generating a plurality of highest flow rate values ​​corresponding to the plurality of length values, and The processor calculates the optimal length value by selecting the length value that produces the highest overflow flow rate from among the plurality of highest flow rate values ​​corresponding to the plurality of length values. The overflow sensor is suitable for measuring the flow rate of a series of diluents and triggering a notification when the flow rate exceeds a threshold.

14. A computer program product comprising a non-transitory and tangible computer-readable storage medium containing instructions executable on a processor for performing a method for automatically calculating optimal values ​​of at least one operating parameter of an acoustic droplet ejection ADE device, an open port interface (OPI) device, or an ion source device using a mass spectrometer, the method comprising: A system is provided, wherein the system includes one or more different software modules, and wherein said different software modules include a control module and an analysis module; For each of a plurality of parameter values ​​for at least one parameter of an ADE device, OPI, or ion source device, the at least one parameter is set to each value, instructing the ADE device, OPI, ion source device, and mass spectrometer to generate one or more intensity-time-mass peaks for the sample, and using the analysis module to calculate a characteristic value for at least one feature of the one or more intensity-time-mass peaks, thereby generating a plurality of characteristic values ​​corresponding to the plurality of parameter values, and The analysis module is used to calculate the optimal value of at least one parameter from the plurality of feature values ​​corresponding to the plurality of parameter values. ADE devices are suitable for performing one or more sprays of samples over time. The OPI is adapted to receive one or more sprays over time at the inlet of the inner tube, mix the received sprays with the solvent in the inner tube to form a series of sample-solvent diluents, and transfer the series of diluents to the outlet of the inner tube. The ion source equipment is suitable for receiving and ionizing a series of diluents, thereby generating an ion beam. The mass spectrometer is adapted to receive the ion beam over time and perform mass analysis on the ion beam, thereby generating a time-dependent mass peak corresponding to the one or more jets.

15. The computer program product of claim 14, further comprising: For each of a plurality of length values ​​for the length of the electrode protruding from the nozzle of the ion source device at the outlet of the inner tube of the OPI, the control module sets that length for each value, instructs the ADE device, OPI, and ion source device to generate an ion beam for the sample at each of a plurality of flow rate values ​​until an overflow sensor triggers a notification, thereby generating a plurality of flow rates for each value, and uses the analysis module to calculate the highest flow rate for each value from the plurality of flow rates, thereby generating a plurality of highest flow rate values ​​corresponding to the plurality of length values, and The control module calculates the optimal length value by selecting the length value that generates the highest overflow flow rate from among the plurality of maximum flow rate values ​​corresponding to the plurality of length values. The overflow sensor is suitable for measuring the flow rate of a series of diluents and triggering a notification when the flow rate exceeds a threshold.

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