Multi-ion identification device, multi-ion identification system, and method of identifying a substance

Abstract

The present disclosure relates to a multiple ion identification device, a multiple ion identification system and a method of identifying a substance. The method utilizes chemical ionization (CI) in multiple adducts formed by substances in a sampling gas of a gas sample to be analyzed in a mass spectrometer. The multiple ion identification device comprises a buffer zone to attenuate a sample flow with chemical ionization of reagents from a set of reagent ion towers (R1, R2, R3, R4, R5, R6) before the sample flow enters an ionization region (IR(A)) (IR(B)).

Description

Technical Field

[0001] Generally, this invention relates to ion identification of a medium from which samples are collected to an ion identification device. Specifically, this invention relates to a multi-ion identification device for determining the composition of gas species in a sampled medium to be analyzed, thereby identifying ions and determining the composition of the sample. This invention also relates to a program product for controlling the ion identification via a multi-ion identification device. Furthermore, this invention relates to a system for generating a database based on measurement results generated by the system. Background Technology

[0002] Over its nearly 150-year history, the composition of various gases containing organic components has been determined. An example of early compositional research relates to breath analysis, dating back to 1874 when Francis E. Anstie first observed that alcohol could be detected in exhaled breath air. This had little functional use at the time, but the first breathalyzer was invented in 1927, the first practical roadside tester was commercialized in 1931, and the first electronic version was developed in 1967.

[0003] In the current clinical setting, some diagnoses (such as asthma) can be aided by respiratory screening devices. However, the promise that many diseases can be accurately diagnosed simply by blowing air into a tube has been touted but never realized. This has led to some skepticism in the clinical community about using such devices to provide sufficient compositional information for professionals to use in their analyses.

[0004] The ability to diagnose and screen for medical conditions has long been a science fiction dream, a central theme in many stories, from the tricoder in Star Trek to the diagnostic bed. Even today, such tools seem decades away, but recent breath analysis has shown promise of a diagnostic tool based on data obtained non-invasively under certain limited conditions. One question remains: what prevents breath analysis devices from becoming truly universal diagnostic tools for professionals? On one hand, the chemical complexity of human exhaled gases exceeds the limitations of current analytical techniques such as gas chromatography (GC) and proton transfer reaction mass spectrometry (PTR-MS). While these devices and systems possess excellent analytical capabilities and have been used for decades, they appear to struggle when detecting more functionalized, less volatile compounds in gas samples—a class of molecules that could actually form the cornerstone of the breath analysis data to be used. However, the fact that these tools can only detect a limited range of compounds, and only within a limited scope, is one of the limiting factors slowing the development of breath analysis as a usable and universal diagnostic tool for professionals. More information about these system limitations comes primarily from, for example, (i) the sampling of semi-volatile to low-volatile substances, and (ii) the detection limitations due to low ionization efficiency.

[0005] Artificial intelligence, once a metaphor in science fiction, depicts how AI could influence peaceful times, predict user needs, and provide timely information and support. This kind of AI was unimaginable 20 years ago, but today AI and machine learning are becoming standard; they are self-learning and become more useful with minimal human intervention. Modern examples of AI abound, such as better traffic management, entertainment services, and enhanced fraud detection—all requiring a common element to function: data, massive amounts of data.

[0006] Ten years ago, breath analysis was a promising emerging technology, expected to become a new screening tool in the medical arsenal for detecting diseases that were difficult to diagnose or screen. While some progress has been made in recent years, this promise has yet to be fulfilled, and doctors and clinicians remain skeptical. 1 Functional breath testing is a convenient and minimally invasive method for detecting certain compounds in exhaled breath, which can be used to generate data for diagnosing certain conditions and health risks. Currently, only a few breath analysis tools have entered mainstream clinical practice.

[0007] A recent systematic review and meta-analysis of volatile organic compound (VOC)-based breath tests for cancer diagnosis revealed a lack of methodological standardization, while also highlighting the test's potential for non-invasive cancer diagnosis. 2The authors of this review propose a framework for conducting and reporting future research investigating the role of volatile organic compounds (VOCs) in cancer diagnosis. However, the study suggests that previous attempts may have methodological problems, potentially leading to an overestimation of the performance of VOC-based breath tests. 3 This criticism primarily focuses on methodological issues. Analyzing the differences in volatile organic compounds between two groups of study participants (e.g., sick and healthy) is often the main objective of such studies, while the origin and pathophysiological significance of identified labeled compounds are frequently overlooked. 4 Breath mapping offers a completely different approach, the first question being: what compounds constitute normal human respiration?

[0008] Human breath contains hundreds of different volatile compounds, the distribution of which varies from person to person. Some compounds in exhaled air are the result of environmental exposure, others are produced by normal bodily metabolism, and still others are products of bacterial or viral infections or other medical conditions.

[0009] Exhaled breath is a complex gaseous mixture containing hundreds (possibly thousands) of analytes, with biomarkers typically present at very low concentrations (on a known scale, in the parts per billion (PPB) or parts per trillion (PPT) range). To target virtually every gaseous compound, ionizing reagents need to be collected. As the degree of molecular functionalization increases, simple molecular parameters become less defined. A simple example is amino acids, characterized by both acidic and basic functions, whose acid-base behavior varies depending on the structure of the rest of the molecule.

[0010] There is a widespread need for advanced online chemical analysis of gas samples: from detecting explosives to screening food samples for pesticides, to environmental monitoring, and even diagnosing diseases from breath. A major drawback hinders chemical techniques from achieving this goal and prevents them from being merely research tools. Real-world problems often involve detecting a wide variety of compounds from very different chemical categories, ranging from highly polar and acidic compounds to poorly functional ones. Each technique, such as PTR, GC, or APCI, has its limitations in which it best distinguishes and identifies which molecules, and changing settings between them is difficult and laborious, potentially taking hours or days. This invention proposes a method to overcome this problem and provides a suite of tools for unbiased and standardized analysis of gas samples with chemical compositions. Summary of the Invention

[0011] The aim is to at least alleviate the problems described above that cannot be satisfactorily solved by known devices, and to provide a feasible multi-ion identification device for the analysis of gas composition samples, which also reveals such more functional and less volatile compounds, for the identification and analysis of data on composition and the abundance of those molecules, and simultaneously provides information on more volatile and less volatile compounds without changing settings and interrupting sampling.

[0012] Mass spectrometers are analytical instruments used to analyze the chemical composition of air with high precision. The problem is that they only measure ions, meaning the molecules need to be charged (ionized) first. Several ionization techniques have been developed, each with its own characteristics and applications.

[0013] Chemical ionization (CI) is a method that uses chemical reagents to generate reagent ions that mix with an air sample. It is a soft ionization method that uses this mechanism, meaning that molecules of interest will remain intact and aggregate with the reagent ions. This greatly aids in detection because the elemental composition of the target molecule typically does not change. Another important aspect of chemical ionization is selectivity. Some reagent ions tend to aggregate only with molecules that have different properties. Selectivity is both a good and a bad thing. When target molecules have a tendency to aggregate with selected reagent ions, it allows for very high sensitivity because most molecules in the air are not ionized, resulting in low noise levels.

[0014] However, an obvious drawback is that a certain reagent can only work on a limited number of molecules, and therefore it is not a suitable method for detecting a wide range of chemicals with different properties.

[0015] Another complicating factor in using conventional CI and SESI (secondary electrospray ionization) is the mixing of neutral reagent vapor / droplets with the sample stream, which alters the sample chemistry and complicates the use of multiple ionization schemes.

[0016] The aforementioned objectives are achieved through embodiments of a multi-ion identification device, which will be used in the systems and methods for comprehensive data analysis according to the present invention. The applicant is interested in developing a groundbreaking tool for online gas phase analysis that will not only improve the detection of known compounds in the air (such as those found in exhaled breath), but also open the possibility of studying molecules that have until now only been theoretically predicted and never measured in practice in a systematic and standardized manner, and provide researchers using the device with a gas phase chemistry knowledge base that will evolve over time.

[0017] Machine learning algorithms (such as deep learning) are used to analyze this data and compare large datasets, enabling software to identify patterns in components and suggest corresponding responses in order to analyze complex patterns in sample chemistry and create classification predictions, such as deriving the underlying conditions that lead to a particular chemical composition.

[0018] Destructive methods can be implemented by employing an online system embodied in this disclosure, providing an APCI-OT-MS (Multi-ion Atmospheric Pressure Chemical Ionization Orbital Mass Spectrometer, i.e., MION APCI-OT-MS) or any other suitable ion detection device as the detector, such as IMS utilizing multiple selective ionic chemicals simultaneously in negative and positive detection modes. This enables the system to detect a wide range of very different chemical categories with unprecedented sensitivity and selectivity. Therefore, the possibility of unbiased and comprehensive chemical analysis of gas samples is provided.

[0019] According to one embodiment, the Multi-Ion Atmospheric Pressure Chemical Ionization Orbital Mass Spectrometer (MION APCI-OT-MS) is capable of detecting virtually every gaseous molecule potentially present in human respiration with unprecedented sensitivity. Using a embodied system incorporating MION APCI-OT-MS, an example will be developed of a gas sampling method suitable for large-scale quantitative analysis of the components of respiration (considering exhalation volume, relative humidity, and other fundamental conditions affecting the spectral signal). However, it is also applicable to, for example, measurements of the ambient environment.

[0020] Simultaneously, other tools can be used to collect comprehensive auxiliary metadata into the developing database, thereby allowing for multifactorial analysis of the acquired respiration spectra and their composition. Next, further measurement data are collected. This innovative and unique method according to embodiments of this disclosure offers the possibility of detecting a variety of compounds that were previously undetectable by conventional tools. This unbiased sampling of compositional information in samples (such as respiration) reveals components for optimizing resolution and predictability in a manner similar to the need for extensive expression genomics and expression-based chemistry (e.g., cancer analysis) to enable new means of tailoring personalized treatments with the aid of analyses created by medical professionals based on embodiments of this disclosure.

[0021] In a customized system with a dedicated configuration, specific algorithms can be used to apply "big data" techniques and machine learning (MLA) algorithms to analyze data obtained from samples taken from embodiments of this disclosure, i.e., data collected through respiratory sampling and supplemental data, and to attempt to correlate specific chemicals found in the breath with different sociomedical properties associated with the composition. Embodiments may apply multivariate statistical methods to accomplish this work, which are used to identify patterns of respiratory markers in the gas composition of healthy individuals and to study the gas composition of respiratory-based disease networks (e.g., asthma, cancer, and other lung pathologies) to provide data for professionals to make diagnoses based on said data.

[0022] According to the technical solution of the present invention, one or more of the above-mentioned objectives are achieved.

[0023] According to a disclosed embodiment of the present invention, a multi-ion identification apparatus is characterized in that the apparatus comprises: a first plurality of reagent ion towers located in a first plane perpendicular to the sample inlet direction of the ionization region of the multi-ion identification apparatus; and a second plurality of reagent ion towers located in a second plane perpendicular to the sample inlet direction of the ionization region of the multi-ion identification apparatus, wherein the first and second planes are parallel by means of the reagent tower positions, thereby providing reaction time for ions emitted from the respective reagent ion towers to chemically ionize analyte molecules in the sample, wherein the chemically ionized adducts thus formed are transported from the ionization region to the mass spectrometer port to exit from the ionization region of the apparatus for adduct mass spectrometry analysis.

[0024] According to one embodiment of this disclosure, at least one of the sheath flows is made to occur in a laminar state. According to a variation of this embodiment, the sheath flows are controlled into a laminar profile shape by equalizing their velocities. According to one embodiment of this disclosure, a flow shaper (i.e., one or more consecutive grids in the flow direction) is provided to make each sheath flow laminar, to further fine-tune the shape of the sheath flows, thereby ensuring that each sheath flow has laminar characteristics in a laminar state.

[0025] According to one embodiment, a moist gas sample can be dried using a dryer as a means of drying the sample stream by diffusion drying. According to one embodiment of this disclosure, in a embodied multi-ion identification apparatus, each ionizing reagent in a corresponding reagent ion tower in the same plane (IR(A)) is configured to operate according to the same ion generation mechanism to provide the corresponding reagent ions from a dedicated reagent ion tower.

[0026] According to one embodiment of this disclosure, in a embodied multi-ion identification apparatus, the ionization mechanism of the reagent ion tower is at least one of the following: X-ray, soft X-ray, corona discharge, and electrospray-based mechanisms (one or more).

[0027] According to one embodiment of this disclosure, in a embodied multi-ion identification apparatus, the polarity of the ions generated by the reagent ion tower can be adjusted to positive or negative ions. According to a variation of one embodiment, the reagent ion tower can be controlled to be neutral, i.e., non-positive or non-negative polarity.

[0028] For example, the polarity can be changed by switching the charging mechanism, but in addition, unwanted ions can be filtered out by an electric field, keeping them away from the outlet of the reagent ion tower discussed.

[0029] According to one embodiment of this disclosure, in a embodied multi-ion identification apparatus, at least one reagent ion tower includes a filter to filter out multi-charged reagents or unwanted polarities, thereby carrying reagent ions away from the ionization region. According to one embodiment, the filter is based on an electrostatic field. According to an optional embodiment, the filter is based on an ion trap having an alternating electric field. According to one embodiment, the ion trap filter, in addition to having an alternating electric field, also has an electrostatic field arranged to trap reagent ions into the ion trap.

[0030] According to one embodiment of this disclosure, in a embodied multi-ion identification apparatus, the ionization region includes a cylindrical symmetry centered on a centerline (C). According to one embodiment, the multi-ion identification apparatus includes a buffer zone. According to one embodiment, the buffer zone has the same axis of symmetry as the ionization region. According to one embodiment, the length of the buffer zone is adapted to allow the sample flow turbulence to attenuate to a laminar state at the inlet of the ionization region. According to one embodiment, the velocity of each sheath flow at the buffer inlet entering the ionization region has been matched to accommodate the laminar state. According to one embodiment, the velocity of each sheath flow is adjusted to the sample flow velocity. According to one embodiment, this adjustment is performed by a control unit; according to another embodiment, the adjustment is performed by a user; but according to an optional embodiment, the adjustment is performed by software arranged to adjust a sheath flow valve acting as a sheath flow actuator.

[0031] According to one embodiment of the invention, in a embodied multi-ion identification apparatus, the reagent ion tower is aligned in a plane and has a deviation (α) to deviate from the direction of the center line of the ionization region along a corresponding radially pointing emission line.

[0032] A multi-ion identification system according to one embodiment of the present invention, the specific multi-ion identification system comprising:

[0033] -At least one multi-ion identification device according to one embodiment of the present invention.

[0034] - Control device, controlling the multi-ion identification system and its actuators to operate during mass spectrometry analysis of adducts formed from sample components.

[0035] - Use a mass spectrometer to perform the above-mentioned mass spectrometry analysis.

[0036] - A database used to store mass spectrometry analysis results.

[0037] The specific system is also called the MION system.

[0038] According to one embodiment of the present invention, a embodied multi-ion identification system includes a software package configured to control the operation of the multi-ion identification system. According to one embodiment, the software package includes software for a control unit to control the actuators of the system. According to one embodiment, the control unit is arranged to maintain the flow rate, voltage, and / or ambient quantities of the multi-ion identification apparatus. According to one embodiment, the control unit is arranged to operate a spectrometer as a system element. According to one embodiment, the software package is configured to form a database for measurement results obtained by the mass spectrometer during measurement under the control of the control unit. According to one embodiment, the software package is configured to provide machine learning algorithms and various statistical tools, which may have a self-learning package for data analysis to perform cluster analysis and / or find labeled substances from the compositional data of the sample and / or mass spectrometer signal.

[0039] According to one embodiment of the invention, the embodied multi-ion identification system includes a software package (SW) configured to perform group analysis from clusters to discover and infer labeled substances and / or newly discovered molecules, such as HOMs, from the results. These HOMs (highly oxidized multifunctional organic molecules) can include hundreds of different types of molecules that are rarely detected as components of secondary aerosols, if never detected.

[0040] According to one embodiment of the present invention, the software package for embodying a multi-ion identification system includes at least one of the following: machine learning algorithms, neural network solvers for optimizing cluster analysis, and artificial intelligence algorithms (such as penalized linear LARS, resilient network regression algorithms, random forests, and recursive feature elimination algorithms).

[0041] According to one embodiment, the system includes an ion detector for detecting ions, the ion detector being implemented, for example, an ion mobility spectrometer (IMS) or a mass spectrometer, such as a multi-ion ambient pressure chemical ionization orbital mass spectrometer (MION APCI-OT-MS), which is configured to simultaneously utilize multiple selective ionic chemicals in both negative and positive detection modes.

[0042] According to one embodiment of the present invention, the embodied multi-ion identification system includes a mass spectrometer as a system element, which is a multi-ion ambient pressure chemical ionization orbital mass spectrometer (MION APCI-OT-MS) configured to simultaneously utilize multiple selective ionic chemicals in both negative and positive detection modes.

[0043] According to one embodiment of the present invention, the embodied multi-ion identification system includes, in its system configuration, the detection of highly oxidized multifunctional organic molecules (HOMs) with extremely low vapor pressure from a sample.

[0044] A method for identifying substances from a gas sample using a MION system, according to one embodiment, includes:

[0045] - Sample the gas sample into the sample stream of the multi-ion identification device.

[0046] - Allows turbulence to decay to a laminar state within the buffer zone of the multi-ion identification device,

[0047] - The gas sample is protected in the buffer by at least one or two sheath flows.

[0048] - The gas sample component is charged by reagent ion molecules formed by the chemical ionization of the gas sample component to form an adduct.

[0049] - Allows adducts to form from gaseous sample components and reagent ion molecules.

[0050] - Introduce the adduct into a mass spectrometer for mass spectrometry analysis.

[0051] - Identify the components of adducts and gas samples.

[0052] - Store the identified gas sample components in a database.

[0053] According to one embodiment, the method may include: finding similarities between similar samples in the database based on identified markers from previous sample mass spectra. Furthermore, in a variation of the method, additional data associated with the sample is compared with similarly associated additional data of previous samples to find correlations between the additional data and the markers of the current and previous gas samples. According to one embodiment, the comparison is performed using software packages as system components. According to a variation of the embodiment, the comparison includes at least one of the following: an artificial intelligence algorithm for finding patterns between added data and markers, a self-learning algorithm assisting the artificial intelligence algorithm, and an optimized neural network for finding markers.

[0054] According to one embodiment, the database resides in the cloud, and the system components of the embodied system can form a system network that contributes to the database, making it more robust. Each terminal, as a system component, can access the database via the network. Edge computing (where the system is located) will identify peaks in the chemical spectrum; neural networks can be embodied as appropriate portions of the main database in the cloud; and according to one embodiment, the cloud integrates the database with other data and provides analysis, such as metadata classification and prediction, for example, basic conditions corresponding to the chemical composition of respiration.

[0055] The expression “a number of” in this article refers to any positive integer starting from one (1), such as to one, two, or three.

[0056] The expression “a plurality of” in this article refers to any positive integer starting from two (2), such as up to two, three or four.

[0057] The inclusion expression is used as an open-ended expression.

[0058] Different embodiments of the present invention are disclosed in the Detailed Description section. Attached Figure Description

[0059] The following embodiments of the present invention will be described in more detail with reference to the accompanying drawings, in which:

[0060] Figure 1 An exemplary embodiment of the multi-ion identification apparatus disclosed according to the present invention is shown, which is in a sampling state to be implemented by one or more embodiments of the present invention.

[0061] Figure 1B The idle state is shown. Figure 1 A multi-ion identification device, between the continuous sampling states of the device.

[0062] Figure 2 and Figure 3 An example of an ion implantation tower as a reagent ion tower is shown, which is located in the layer of a multi-ion identification device according to the present invention, which will be implemented by one or more embodiments.

[0063] Figure 4 The MION system is shown as an exemplary embodiment of the multi-ion identification apparatus disclosed in the present invention, which will be implemented using one or more embodiments of the present invention.

[0064] Figure 5This is a schematic diagram of an embodiment in which analytes for reagents selected based on their basic-acid properties and related functionalities are grouped into multiple groups for identification using a specific multi-ion identification device.

[0065] Figure 6 An embodiment of the present invention is illustrated, which relates to a method for identifying substances from a gas sample using a MION system, and

[0066] Figure 7 The schematic diagram illustrates the specific structure of the reagent ion tower. Detailed Implementation

[0067] As those skilled in the art will understand from the embodiments of the present invention, the same reference numerals in different figures may be used to refer to similar objects that are not necessarily exactly the same.

[0068] Figure 1 This shows the connection with a mass spectrometer (MS). Figure 4 The MION system (Sys, which is used in cooperation) Figure 4 ) Multi-ion identification device 100.

[0069] According to one embodiment, in the multi-ion identification apparatus 100, there is a buffer 100a in which the sheath flow enters the multi-ion identification apparatus and the sample enters the apparatus. According to one embodiment, the buffer may include ports for auxiliary measurements to further process the sample elsewhere and / or perform redundancy and / or diversity analysis elsewhere, i.e., in a second apparatus that may be similar but not necessarily the same.

[0070] Total flow can be measured at the port flow measurement, which is based on direct flow measurement and / or the set flow in other parts of the device set by the control unit for the flow actuator in the control system. Figure 1 The arrows in the diagram indicate the flow of dedicated reagent ions from the corresponding reagent ion towers (R1, R6) and the curved dashed paths.

[0071] Reagent ionizers (R1, R2, R3, R4, R5, R6, Rn, Rm) accelerate and filter ions based on their charge. They charge reagents according to their specific feed sources, with the feed and / or type controlled by a control unit. Reagent ionizers (also called ionizers) utilize soft X-rays, corona discharge, and / or electrospray mechanisms during reagent charging to provide reagents with the desired polarity for use in the ionization region, chemically ionizing sample molecules through the addition of reagent molecules to the sample molecules.

[0072] Sheath flows shth1 and shth2 are arranged to conform to the cylindrical geometry of the buffer zone of the device, such that both sheath flows are introduced into the buffer zone to form an annular sheath surrounding the sample flow. According to one embodiment, the geometry and flow are configured such that the sheath flows and the sample flow have equal velocities, thereby preventing unwanted vertical vortex mixing and / or turbulence formation. According to one embodiment, under the monitoring of a software routine dedicated to flow maintenance, the flow rate is set to the corresponding laminar state by controlling the flow valve as a flow actuator and as a control unit of the system element.

[0073] Figure 2 and Figure 3 Parts of the ionization regions (IR(A) and IR(B)) at levels A and B are shown respectively. Figure 2 In the figure, the uppercase C denotes the geometric center line of ionization region 100b at horizontal IR(A). The same geometric center axis is equal to the geometric symmetry axis of buffer zone 100a.

[0074] At horizontal IR(A), lines L1, L2, and L3 represent the planar linings of the corresponding reagent ion towers R1, R2, and R3, such that R1 is along the L1 lining to inject ions in the direction indicated by line L1. According to one embodiment of the invention of this disclosure, lines L1, L2, and L3 are radially offset (i.e., deflected) at an acute angle α to the geometric center direction.

[0075] According to one embodiment, the angle is less than 30°; according to another embodiment, it is less than 20°; according to yet another embodiment, it is less than 10°; according to yet another embodiment, it is less than 5°; but according to one embodiment, the angle is between 0.7° and 35°.

[0076] Similar to the geometry at horizontal IR(A), at horizontal IR(B), lines L4, L5, and L6 represent the planar linings of the corresponding reagent ion towers R4, R5, and R6, such that R4 is aligned with line L4 to inject ions in the direction indicated by line L4. According to one embodiment of the invention disclosed herein, lines L4, L5, and L6 are radially offset (i.e., deflected) at an acute angle α from the direction of the geometric center (capital C).

[0077] According to one embodiment, the angle is less than 30°; according to one embodiment, the angle is less than 20°; according to another embodiment, the angle is less than 10°; according to yet another embodiment, the angle is less than 5°; but according to one embodiment, the angle is between 0.7° and 35°.

[0078] According to one embodiment, the misalignment is selected to deflect between level A and level B, particularly in such embodiments where levels R3 and R6 are mounted opposite to each other at their respective levels. According to one embodiment, this misalignment is intentional in part to prevent the opposing reagent ionization towers (i.e., as exemplified by different levels R3 and R6) from adversely affecting each other's operation in chemical ionization. According to one embodiment, the offset is set to the same direction of rotation, thus occupying equal sectors of a certain kind for ionization probabilities with similar reaction times at that level, obtaining sample analytes charged by reagent ions at sub-regions of the ionization region with equal efficiency.

[0079] According to an optional embodiment variation, lines L1, L2, and L3 may be provided for the mounting of R1, R2, and R3, such that lines L1, L2, and L3 will define the first conical shroud. However, such an embodiment will produce different ionization relaxation times, making it easier to settle into different portions of the ionization region than in a planar configuration. Such an embodiment may be useful if such an effect is desired.

[0080] According to an optional embodiment variation, lines L4, L5, and L6 can be provided for the installation of R4, R5, and R6, such that lines L4, L5, and L6 will define the second conical shroud. However, such an embodiment will produce different ionization relaxation times, making it easier for sedimentation to occur in different portions of the ionization region than in a planar configuration. Such an embodiment may be useful if such effects are desired. However, the first and second conical shrouds defining the orientation of the reagent ionization column do not necessarily need to be collinear.

[0081] exist Figure 2 and Figure 3 In this embodiment, three injection towers, uniformly distributed at three angles, are embodied in each level IR(A) and IR(B) as examples of their number and angular positions. Those skilled in the art will recognize from these exemplary embodiments that the number of injection towers as reagent ion towers is not necessarily limited to three per level, but can be varied to a larger number, such as four, five, or six, depending on the corresponding embodiment. Offsets can be implemented according to what is discussed with respect to R1, R2, and R3 regarding their offsets. As those skilled in the art will also recognize, the members of levels (A, B) are not necessarily limited to the two shown, but can be three, four, or five according to the corresponding embodiment variations; however, sufficient crosstalk suppression is provided by the specific number of reagent ion towers and the purification time characteristics of each, taking into account the diffusion characteristics of the sheath gas material and the expected sample composition.

[0082] The indicated flow rates (Shth1, Shth2, excess, and the flow rate measured by the flow measurement device and the flow rate measured by the auxiliary flow measurement device) can be controlled by the control unit ( Figure 4 In the MION system (Sys, Figure 4 ) software package (SW, Figure 4 Controlled by commands from ), the software segment of this software package is controlled by the system's dedicated microprocessor (μP). Figure 4 The system operates by controlling the system's operation. Shth1 is materialized as sheath flow 1, and Shth2 is materialized as sheath flow 2, used to enclose the sample components traveling in the buffer to enter the ionization region 100b. The sheath flows are controlled by the control unit. Figure 4 Control is achieved by using a suitable set of actuators dedicated to each flow, such that, for example, the actuator controlling sheath flow 1 (Shth1) is dedicated to independently controlling the flow on other flows, but such that the setpoint of each flow under control collectively represents a meaningful flow value set by the dedicated actuator for each flow, thereby guiding the sample flow through the multi-ion identification device 100 toward the front port of the mass spectrometer MS. According to one embodiment, sheath flows Shth1 and Shth2 are used to protect the sample-carrying flow through the buffer zone to the ionization zone.

[0083] According to one embodiment, the sheath flow is matched to the laminar flow geometry to surround the sample flow in a ring, such that Shth1 surrounds the sample flow and Shth2 surrounds Shth1, thus also surrounding the sample flow at a certain distance. According to one embodiment, the flow velocities of the sample flow, sheath flow 1, and sheath flow 2 are set such that they pass adjacently through the ionization region. These flow rates are set by a control unit. Figure 4 ).

[0084] These actuators to be controlled, as well as other actuators in the system, Figure 4 The term Act, as shown in the diagram, refers to a set of actuators used for various purposes to maintain the operation of the system and its components.

[0085] Such actuators can also be used to control the operating environment of the device by controlling the temperature (T), pressure (P), relative humidity (RH), and / or composition (C) of the sheath gas in at least one of sheath flows 1 and 2, depending on environmental conditions, but optionally also under set conditions within the device 100. Control can be achieved through another set of valves vk and / or vl, in... Figure 4 It is shown schematically in the middle.

[0086] The accompanying diagram is also illustrative; the control unit allows the reagent chemical input terminal to... Figure 1 The corresponding arrow indicates the position of the multi-ion identification device 100. Although such polarity is not shown or selected, those skilled in the art will know from the disclosure of the embodiments that such selection can be made under the control of the control unit.

[0087] Despite Figure 1The diagram illustrates six reagent injection towers (R1, R2, R3, R4, R5, R6), also considered reagent ionization towers. Each injection tower can provide one or more reagents in ionized form to the ionization region to bind with analyte molecules from the sample, thereby forming chemically ionized adducts. However, the number of injection towers is not necessarily limited to the example shown. According to one embodiment, the polarity of each injection tower can be set individually by a control unit. According to one embodiment, the user-defined selection of injection towers can be set to a specific polarity by the control unit by using a user interface to command actuators in the system to operate accordingly for the reagent chemical feed and / or the polarity of the reagent ions.

[0088] The ionization of reagents can be based on soft X-rays, corona discharge, or other suitable ionization mechanisms to generate reagent ions for the chemical ionization of reagent molecules so that they can bind to the analyte in the ionized region.

[0089] According to a variation of one embodiment, additional ionizers Rn, Rm can also be used to provide similar ionization levels at corresponding levels in the ionization region 100b of the device 100, such as... Figure 1 The letters A and B are shown in the diagram. This type of level is represented by the expressions An(n, n+1, n+2) and Am(m, m+1, m+2). At An and Am, the letters n and m are used as arbitrary indices to refer to multiple injectors. Therefore, for Figure 5 The classification shown can be used to define the number of categories accordingly, allowing for a more refined classification of analytes and corresponding reagents.

[0090] Indication Figure 4 In the diagram, there is an actuator descriptive box marked with V and X, indicating control by the control unit. In the embodiment, Figure 4 The control unit can control the voltage used in the system via corona discharge and / or X-ray tube voltage (X), which is used by a suitable actuator dedicated to ionizing the reagent in each reagent injection port (R1, R2, R3, R4, R5, R6, Rn, Rm). However, the voltage of the mass spectrometer MS controlled by the control unit can also be set, although the mass spectrometer has independent control over its operation.

[0091] according to Figure 4 The example shown can be controlled via a dedicated microprocessor μP that runs control software, which can be implemented as a piece of software in a software package SW. The software package SW, containing routine software code, is implemented as a system element of the MION system.

[0092] According to one embodiment, the software package SW includes a database (DB) constituting measurement results obtained from a mass spectrometer MS. Figure 4The device is used to identify the substances in a sample, thereby identifying the composition and abundance in the sample. Although the database is drawn with dashed lines separating the components, it can also be a part of the system's permanent component memory M, or have a portion therein.

[0093] The method of drawing the control unit and system indicates that the control unit is controlling the system. However, the control unit is considered as a system element and is part of the system. The location can be implemented in several ways. However, according to one embodiment, the control unit can also be diversified in appropriate locations, such that some actuators are located at the multi-ion identification device, and for example at the microprocessor within the mass spectrometer, or at a network location, thereby facilitating remote control of the system element.

[0094] According to one embodiment, the software package SW may include signal processing tools to analyze the mass spectra of a mass spectrometer MS, but according to a variation of one embodiment, it may also include tools for clustering / grouping analysis and for correlation calculation to find labeled substances from the sample.

[0095] In other words, the software package, as a software suite, consists of software services related to hardware control, mass spectrometer data analysis, and the user interface. This software enables operators to easily use the system and ensures good and consistent data quality. Furthermore, the package will be used to accomplish various required levels of automation tasks in the sampling interface, MION inlet, mass spectrometer, and data processing pipeline. The output of the data processing software may include a list of peaks (multiple sets of (m / z, intensity) pairs), which, as part of a knowledge base, will be further analyzed along with auxiliary data. A simple, dedicated user interface is implemented to guide the sampling process and ensure data quality.

[0096] According to one embodiment of this disclosure, Figure 1 This demonstrates the concept of using six MION sources (reagent ion towers) for parallel switching between reagent ions. The switching occurs in less than one second, preventing neutral reagents from entering the flow stream.

[0097] Figure 5 This is a schematic diagram of an embodiment that groups analytes (i.e., target molecules having such examples) to select reagents into multiple groups based on their basic-acid properties and related functions, thereby enabling identification using a embodied multi-ion identification device.

[0098] exist Figure 5 In the example, the target molecules are divided into six groups based on their chemical composition. The multi-scheme entry developed in this paper can cover almost all of these groups in a semi-continuous manner.

[0099] To target almost every gas-phase compound, it is necessary to collect ionizing reagents. As the degree of molecular functionalization increases, simple molecular parameters become less defined. Amino acids provide a good, simple example, exhibiting typical acidic and basic functions, whose acid-base behavior varies depending on the structure of the rest of the molecule. Therefore, we adopt here an arbitrary, but in a sense more chemically meaningful, definition: that molecules are labeled based on their functional group composition, and therefore also on their ionization properties.

[0100] For this type of method variation according to the invention, target molecules are divided into six groups, ranging from acidic, highly oxidized, and highly functionalized (Group 1, best detected by adducts forming negatively ionized (aNPCI) reagent ions), to reduced naked hydrocarbons (Groups 3 and 4, to which optimal sensitivity is obtained via carefully selected hydrogen transfer reagents), and finally to highly functionalized, and therefore highly oxidized, but rather basic compounds (Group 6, best detected by adducts forming positively ionized (aPPCI) methods). The most significant difference between Groups 1 and 6 lies in the specific oxidized substituents and the nature of the hydrogen bond interactions they provide (i.e., in Group 1 hydrogen bond donors, and in Group 6 hydrogen bond acceptors). As shown, a multi-scheme entry of the MION type can cover all these groups with carefully selected combinations of reagent ions, which will be briefly described below.

[0101] Group 1 reagents operate almost entirely at atmospheric pressure in aNPCI mode. The prototype reagents used here are nitrate ions (NO3-) and halogens (I-, Br-), for which the authors of excellent literature have extensive experience. The main targets in Group 1 are the most acidic and functionalized molecules, which typically have very low gas-phase concentrations, thus requiring these aNPCI reagents to provide extreme selectivity and sensitivity. Similar characteristics were found in Group 6 target compounds (primarily low gas-phase concentrations and strong surface activity), the important difference being that they are at most slightly acidic, or even basic. Therefore, Group 6 compounds are best detected using aPPCI methods (e.g., forming adducts with certain complex amine-derived reagent ions). Groups 2 and 5 contain moderately functionalized targets, which typically maintain fairly high gas-phase concentrations, thus requiring methods with lower sensitivity (and selectivity) for their quantification. An example of aNPCI in Group 2 is a carboxylic acid-derived reagent ion, while for Group 5, simple amine-derived reagents may work well. For the remaining minimally functionalized groups 3 and 4, a set of hydrogen transfer reagents is applied, and these are formed, for example, from simple ketones and alcohols. The reagent ions of groups 1 through 6 above serve as an important example, but such grouping is not necessarily limited to the immediate example shown; it exists in various contexts. Figure 4 The process is also implemented and indicated by optional additional injection layers, as shown by the injection layers An and Am to be applied.

[0102] The reagent selection corresponding to the group can be set during the initial setup of the system and / or system updates.

[0103] According to one embodiment, a method 600 using such a embodied MION system includes:

[0104] - Step 601: Sample the gas sample 601 into the sample stream of the multi-ion identification device.

[0105] - Step 602, allowing the turbulence to decay to a laminar state within the buffer zone of the multi-ion identification device,

[0106] - Step 603: Protect the gas sample in the buffer zone by at least one or two sheath flows.

[0107] - Step 604: Charge the gas sample component with reagent ion molecules formed by the chemical ionization of the gas sample component to form an adduct.

[0108] - Step 605 allows the adduct to form from the gas sample components and reagent ion molecules.

[0109] - Step 606: Introduce the adduct into a mass spectrometer for mass spectrometry analysis.

[0110] - Step 607: Identify the adduct and gas sample components using a software package program for mass spectrometry analysis.

[0111] - Step 608: Store the identification information of the gas sample components in the database.

[0112] According to one embodiment, the method may include finding similarities between similar samples in the database based on identified markers from previous sample mass spectra. Furthermore, in a variation of the method, supplementary data associated with the sample is compared with similarly associated supplementary data of previous samples to find correlations between the supplementary data and the markers of the current and previous gas samples. According to one embodiment, the comparison is performed using software packages as system components. According to a variation of the embodiment, the comparison includes at least one of the following: an artificial intelligence algorithm for finding patterns between supplementary data and markers, a self-learning algorithm assisting the artificial intelligence algorithm, and an optimized neural network for finding markers.

[0113] Figure 7 A specific reagent ionization tower structure is shown. The reagent ionization towers discussed can be R1, R2, R3, R4, R5, R6, Rn, Rm, denoted by the expression Rn (n = 1…m). RSn represents the dedicated source of the reagent, v n(k,l) represents a dedicated valve for controlling the feed of reagent RSn, and X represents a charger, which can be implemented independently as a soft X-ray, corona discharge, electrospray, or a combination thereof. Depending on the control unit settings, the polarity can vary between negative, positive, and neutral. Acc represents a charged reagent ion accelerator, which can be achieved via an electric field. Furthermore, the reagent ion tower may include a filter F to filter out unwanted polar and / or charged ions from the reagent ion tower output. According to an optional embodiment, an electrofilter may be implemented within the accelerator Acc.

[0114] Therefore, those skilled in the art can apply the teachings provided based on this disclosure and general knowledge to realize the scope of the invention as defined by the appended claims in each particular use case by making necessary modifications, deletions, and additions.

Claims

1. A multi-ion identification device, characterized in that, The multi-ion identification device includes: The first plurality of reagent ion towers provide ionized reagent ions in a first plane perpendicular to the direction in which the sample stream enters the ionization region of the multi-ion identification device (100). The second plurality of reagent ion towers provide ionized reagent ions in a second plane perpendicular to the direction in which the sample stream enters the ionization region of the multi-ion identification device (100). The first and second planes are parallel, providing reaction time for ions emitted from the corresponding reagent ionization towers to chemically ionize analyte molecules in the sample. The resulting adducts are then transported from the ionization region to the mass spectrometer port for mass spectrometric analysis of the adduct species. The ionization region includes cylindrical symmetry with the center line (C) as the center of symmetry, and The reagent ion tower is aligned in the corresponding plane and has a deviation (α) to deviate from the center line (C) along the corresponding emission line.

2. The multi-ion identification device according to claim 1, wherein, Each ionized reagent in a corresponding reagent ion tower in the same plane is configured to operate according to the same ion generation mechanism to provide the corresponding reagent ions from a dedicated reagent ion tower.

3. The multi-ion identification device according to claim 1 or 2, wherein, The ionization mechanism of the reagent ionization tower is at least one of the following: X-rays, soft X-rays, corona discharge, electrospray, and xenon ultraviolet lamps based on ionization mechanisms.

4. The multi-ion identification device according to claim 1 or 2, wherein, The polarity of the ions generated by the reagent ionization tower can be adjusted to positive or negative ions.

5. The multi-ion identification device according to claim 1 or 2, wherein, At least one of the reagent ionization towers includes a filter to filter out multi-charged reagents and prevent them from entering the ionization region.

6. A multi-ion identification system, comprising: - At least one multi-ion identification device according to any one of claims 1 to 5, - A control device that controls the multi-ion identification system and its actuator to operate during mass spectrometry analysis of adducts formed from components of the sample. - Mass spectrometer, for performing the aforementioned mass spectrometry analysis. - Database for storing and processing mass spectrometry analysis results.

7. The multi-ion identification system according to claim 6, wherein, The multi-ion identification system includes a software package configured to control the operation of the multi-ion identification system.

8. The multi-ion identification system according to claim 6 or 7, wherein, The multi-ion identification system includes a software package configured to perform group analysis to identify and infer labeled substances from the results.

9. The multi-ion identification system according to claim 8, wherein, The software package includes at least one of the following: machine learning algorithms, neural network solvers for classifying and optimizing data clusters, and artificial intelligence algorithms for analyzing, comparing, and predicting the chemical characteristics of gas samples.

10. The multi-ion identification system according to claim 6 or 7, wherein, The multi-ion identification system includes an ion detector for detecting ions, the ion detector being configured to simultaneously utilize multiple selective ion chemicals in both negative and positive detection modes.

11. The multi-ion identification system according to claim 6 or 7, wherein, The multi-ion identification system is configured to detect highly oxidized, multifunctional organic molecules with extremely low vapor pressure from the sample.

12. The multi-ion identification system according to claim 9, wherein, The artificial intelligence algorithm is penalized linear LARS, elastic net regression algorithm, or random forest and recursive feature elimination algorithm.

13. A method for identifying substances from a gas sample using the multi-ion identification system according to any one of claims 6 to 12, the method comprising: - Sample the gas sample into the sample stream of the multi-ion identification device. - Allows turbulence to attenuate to a laminar state within the buffer zone of the multi-ion identification device, - The gas sample is protected by at least one or two sheath flows within the buffer zone. - The gas sample component is charged by reagent ion molecules formed by the chemical ionization of the gas sample component to form an adduct. - Allows the adduct to form from the gas sample components and the reagent ion molecules. - The adduct was introduced into a mass spectrometer for mass spectrometry analysis. - Identify the components of the adduct and the gas sample. - Store the identified gas sample components in a database.

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