Method and system for characterizing type of organic live particles in water

Abstract

The present disclosure relates to a method (100) for characterizing the type of charged / polarizable organic living particles in water, the method comprising applying (101) a first time-dependent electrical bias on a first pair of electrodes in order to generate a first spatio-temporal dependent electric field in a water sample. Further, the method determines (102) background ion characteristics in the water sample based on the first electric field. Furthermore, the method applies (103) a second time dependent electrical bias on at least a second pair of electrodes. Further, the method comprises obtaining (104) kinetic motion data of the captured particles. In addition, the method determines (105) the presence / identity of charged / polarizable organic live particle types.

Description

Technical Field

[0001] The present disclosure relates to methods and systems for characterizing the types of organic live particles in water. Background Art

[0002] Water is essential for all life on Earth, so access to safe drinking water, and therefore rapid assessments regarding the safety of drinking water, are critical.

[0003] Conventional techniques for assessing water quality (i.e., characterizing the presence or absence of any unwanted organic live particles in the water) are typically chemical and biological, and are time consuming, expensive, or both. Systems and methods are needed to quickly and conveniently assess, for example, drinking water, recycled water for irrigation, sewage treatment plant overflows, garbage leaks into groundwater, and bathing water to ensure safe water use, and in particular, systems and methods are needed that enable characterization of organic live particle types such as Escherichia coli (E. coli) in water in a quick and convenient manner. Summary of the invention

[0004] It is therefore an object of the present disclosure to provide a method and system to mitigate, alleviate or eliminate one or more of the above-mentioned deficiencies and shortcomings in assessing water quality.

[0005] This object is achieved by providing a system and a method as defined in the appended claims.

[0006] The present disclosure relates to a method for characterizing (which may be interchangeable with "determining the presence / identity of") a type of charged / polarizable organic live particles (or organic particles or live particles) (also referred to as particles hereinafter) in water, the method comprising applying a first time-dependent electrical bias to a first pair of electrodes so as to generate a first spatiotemporally-dependent electric field in a water sample.

[0007] In order to identify and quantify specific particles in the water sample, the method also includes a step of determining background ion characteristics in the water sample based on a response to a first spatiotemporally correlated electric field applied to a first pair of electrodes. The background ion characteristics can be at least one of the mass, concentration, charge, and chemical properties of the ions / polarizable (fine) particles in the water sample. In some aspects, the background ion characteristics can be ion concentration and mass. The spatiotemporally correlated electric field can be a uniform electric field suitable for measuring ionic particles, or a spatially distributed electric field suitable for measuring polarizable particles.

[0008] It should be noted that the time-dependent electrical bias may be applied by applying a first bias voltage. However, in some aspects, the first time-dependent electrical bias may include applying a first bias voltage V1 to one electrode of the first pair of electrodes and applying a second bias voltage V2 to the other electrode of the first pair of electrodes. V1 and V2 may be applied to obtain a symmetrical response voltage Vr. One advantage of this is that it enables a more efficient determination of ion concentrations. The bias voltages V1, V2 may be alternating biases, preferably the alternating biases may be applied to V1 and V2 in a complementary manner relative to each other. An advantage of the alternating bias is that it reduces the risk of undesirable coatings on the electrodes.

[0009] In addition, the method includes applying a second time-dependent electrical bias to at least a second pair of electrodes to generate at least one particle-specific spatiotemporally dependent electric field in the water sample, thereby trapping particles between the second pair of electrodes. Furthermore, the method includes obtaining kinetic motion data of the particles trapped between the second pair of electrodes.

[0010] In addition, the method determines the presence / identity of a charged / polarizable organic live particle type by comparing the kinetic motion data and background ion signature to a predetermined data set, the predetermined data set including characteristic kinetic motion data for a specific particle type based on different background ion signatures (e.g., based on different water environments). Determining the presence of particles may also include determining the concentration of the specific particle type by quantification.

[0011] Therefore, the predetermined data set includes, for example, characteristic kinetic motion information of specific particles in a specific background ion feature (water environment). Based on the specific background ion feature, particles have different characteristic motions in water. Therefore, the method matches the characteristic kinetic motion of the specific particles in the background ion feature (water environment) (as the determined background ion feature) obtained (or recorded) with the kinetic motion in the data set. In other words, the method compares and matches the kinetic motion data with the characteristic kinetic motion data in the data set, wherein the kinetic motion data and the characteristic kinetic motion data include a common background ion feature. Therefore, when comparing / matching, the method matches the kinetic motion data with the corresponding kinetic motion data having a common background ion feature as the determined background ion feature. Therefore, the predetermined data set can segment the characteristic motion data therein based on the background ion feature.

[0012] Background ion characteristics may include ionic strength, ionic response time, temperature, and ionic charge of the background ions / polarizable (fine) particles in the water sample.

[0013] Thus, it is possible to obtain information about the background ions / polarizable particles, their concentration, the mass and charge of the ions / polarizable particles. The particles in the water attract these background ions / polarizable particles (now called counterions accompanying the particles), which will affect the kinetic motion of the particles in the water.

[0014] A benefit of the method herein is that the spatiotemporally correlated electric field E(r, t) between the second pair of electrodes will exert a force F(t) = ∫q(r)E(r, t)dr on a particle having a charge / polarization distribution q(r). By Newton's second law, F = ma, where "m" is mass and "a" is acceleration, the spatiotemporally correlated electric field E(r, t) exerts a net force on the particle toward the spatial region between the second pair of electrodes, thereby trapping the particle. In addition, the mass m and charge q(r) of the particle can be determined from the kinetic motion data. Specifically, the time series of the kinetic motion enables the calculation of a(t), after which the acceleration can be used to obtain m and q(r).

[0015] In some aspects, the method can determine the presence of a specific particle, provided that the specific particle (intended to be characterized) is charged and / or electrically polarizable. Such a particle undergoes a characteristic motion in a spatiotemporally correlated field, so that the method can characterize such a particle.

[0016] In general, the methods herein enable characterization of particle types in water in a time-efficient manner.

[0017] In some aspects, the method may (preferably but not necessarily, if the at least one particle type is determined to be present) further comprise the steps of:

[0018] - obtaining fluorescence data of particles in the water sample;

[0019] - comparing the fluorescence data with characteristic fluorescence data for the particle type (eg an individual protein fingerprint).

[0020] Therefore, the fluorescence data enables the method to determine the identity of the particles with unequivocal certainty, thereby increasing the accuracy of the method.

[0021] Characteristic fluorescence data may also be stored in the predetermined data set. Thus, the predetermined data set may also include characteristic fluorescence data of the determined particle type.

[0022] The particle specific electric field may be an electric field that captures the E. coli particle type. Thus, the time dependent electrical bias and the electrodes (eg, the geometrical dimensions / spatial configuration / distance of the electrodes) may be adapted to capture the E. coli within the time dependent electric field.

[0023] The method may further comprise the step of applying a third time-dependent bias on a third pair of electrodes having a different spatial configuration than the second pair of electrodes to generate different electric fields for different particle types. Thus, the method may involve determining the presence / identity of multiple particle types based on a method / system. Thus, the method may utilize multiple electrode pairs, each electrode pair being configured (by specifically adapted biasing and spatial configuration) for a specific type of particle, such that multiple particle types may be determined to be present.

[0024] The electric field parameters from the particle-specific spatiotemporally correlated electric field are current and voltage parameters measured as a function of time. Thus, the electric field parameters may be a time-resolved response of the measured current and voltage. Thus, the time-resolved response may indicate the presence / identity of a particle type.

[0025] The time-dependent electric field can have a dynamic duration, ranging from a few microseconds to a few milliseconds, depending on the type of background ions / polarizable particles and the specific type of particles.

[0026] The benefit of using a time-space dependent electric field with dynamic duration is that the mass and charge distribution of the particle can be measured separately, while a uniform space electric field can only measure the ratio between charge and mass. According to Newton's second law, F = ma, where F is the force, m is the mass and a is the acceleration. In a uniform space electric field E, F = ∫q(r)Edr = E∫q(r)dr = Eq, where q is the total charge; combining these two equations, we obtain qE = ma, which shows That is, it is possible to obtain only the ratio between charge and mass, which can be the same for different particles. This method therefore enables the particles to be identified with a greatly increased certainty.

[0027] Also provided is a system for determining the presence / identity of types of organic live particles in water, the system comprising:

[0028] - at least a first pair of electrodes and a second pair of electrodes

[0029] -Control circuit system

[0030] - a measuring chamber, the measuring chamber being arranged to contain water

[0031] The control circuitry is configured to perform a method according to any aspect herein.

[0032] The system may also include a mass spectrometer for performing fluorescence readout, and an optical readout device (eg, a fast CMOS camera) for identifying the kinetic motion of the particles.

[0033] Also provided is a computer-readable storage medium storing one or more programs configured to be executed by one or more control circuit systems of a system, the one or more programs including instructions for executing a method according to any aspect of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In the following, the present disclosure will be described in a non-limiting manner and in more detail with reference to exemplary embodiments shown in the accompanying drawings, in which:

[0035] Figure 1 The method according to various aspects of the present invention is schematically shown in the form of a flow chart;

[0036] Figure 2 A system according to aspects of the present disclosure is shown from an objective view;

[0037] Figure 3 Schematically illustrates a measurement device according to aspects of the present disclosure;

[0038] Figure 4 shows a portion of the system herein according to aspects of the present disclosure, and schematically shows in enlarged portions A and B the attraction of background ions / polarizable particles to electrode 2, and exemplarily shows a graph of the time resolved response; and

[0039] Figure 5 A portion of the system herein is schematically illustrated showing circuitry having a first bias source and a second bias source, each bias source connected to a respective electrode of an electrode pair, in accordance with aspects of the present disclosure. DETAILED DESCRIPTION

[0040] In the following detailed description, some embodiments of the present disclosure will be described. However, it should be understood that the features of different embodiments are interchangeable between embodiments and can be combined in different ways, unless any other content is specifically pointed out. Although in the following description, many specific details are set forth to provide a more thorough understanding of the disclosure provided, it is obvious to those skilled in the art that the embodiments in the present disclosure can be implemented without these details. In other cases, well-known structures or functions are not described in detail to avoid making the present disclosure unclear.

[0041] In the following description of example embodiments, the same reference numerals refer to the same or similar components.

[0042] As used herein, the term "characterization" may refer to determining the presence, concentration, and identity of a particular particle type.

[0043] Figure 1 A method 100 for characterizing the type of organic live particles in water is shown in the form of a flow chart, and includes the following steps:

[0044] - applying 101 a first time-dependent electrical bias to the first pair of electrodes so as to generate a first time- and space-dependent electric field in the water sample;

[0045] - determining 102 background ion characteristics in the water sample based on the first electric field;

[0046] - applying 103 a second time-dependent electrical bias to at least a second pair of electrodes to generate at least one particle-specific and spatiotemporally-dependent electric field in said water sample, thereby trapping particles between said second pair of electrodes;

[0047] - obtaining 104 kinetic motion data of the captured particles;

[0048] - determining 105 the presence / identity of a charged / polarizable organic live particle type by comparing said kinetic motion data and background ion signature to a predetermined data set comprising characteristic kinetic motion data for a specific particle type based on different background ion signatures.

[0049] Method steps 102, 104 and 105 can be computer-implemented steps performed by the control circuit system of the electronic device. The device can also send a control signal for performing method steps 101 and 103. The step of determining 102 background ion characteristics enables the method to infer the type of environment to which the water sample belongs / lives. According to the water environment, there are significant differences in the response time of positive ions and negative ions. For example, even if a very small amount of salt, such as 10 salt particles, is added to 50mL of tap water (that is, about 0.0007g of salt is present in 50mL, and in seawater, there is usually close to 0.2g of dissolved salt in 50mL), significant differences can also be clearly detected in the kinetic motion of particles and concise conclusions. Therefore, by first determining the background ion characteristics, it will be more reliable to subsequently determine the presence / identity of specific particles. It should be noted that the bias voltage applied can vary within the scope of the present disclosure, for example, the amplitude of the bias voltage can be 2V to 25V. The phrase "particle-specific electric field" means that the electric field is adapted to capture a specific particle type, and thus the electrical bias and / or spatial configuration of the electrodes can be adjusted to capture specific particles between the electrode pair.

[0050] In addition, the step of applying 103 a second time-dependent electrical bias to generate a spatiotemporal-dependent electric field enables the particles to be captured, i.e., concentrated in the space between the paired electrodes. Inanimate particles undergo typical Brownian motion in water, and charged / polarizable / living particles undergo characteristic kinetic motion in a spatiotemporal-dependent electric field. In addition, the kinetic motion under the influence of the electric field is related to the mass and charge distribution of the particles. Therefore, by applying a spatiotemporal-dependent electric field specific to the particles, specific particle types, such as E. coli types, can be targeted and captured. Data for the corresponding bias that should be applied to each particle-specific electric field can be predetermined. In some aspects, the particles are organic, inorganic, dead or alive. It should be noted that for method step 103, it is preferred to apply a time-dependent bias directly to the electrode pair, the geometry of which can be specifically designed for a specific particle (i.e., specifically designed for the charge distribution and mass of the particle being studied), and a spatiotemporal-dependent electric field in which the particles will be attracted to the central region between the electrode pair or associated with the region between the electrode pair can be generated.

[0051] The time-dependent electrical bias may be a time-dependent bias comprising a series of different waveforms having different durations. The predetermined data set may be, for example, a data set in the form of a lookup table. However, the method may employ / utilize a trained machine learning algorithm by comparing the electric field parameters to the predetermined data set and thereby determining the presence of a particle type based on the comparison. Thus, method step 105 may not only determine the presence of a specific particle type, but may also characterize / identify the specific particle type.

[0052] It should be noted that the electric field in the space around the electrode can be spatially dependent based on the shape of the electrode (forming a tubular / finger-like shape), while the electrical bias is time dependent. Figure 1 As further shown in FIG. 1 , method 100 may further include the following steps (preferably but not necessarily, if the particle type is at least determined to be present):

[0053] - obtaining fluorescence data of particles in the water sample 106;

[0054] - Comparing 107 the fluorescence data with characteristic fluorescence data of the determined particle type.

[0055] Steps 106 and 107 may also be performed by a trained machine learning algorithm. Step 107 may be used to validate the method herein.

[0056] Fluorescence data can be obtained by emitting in an excitation beam at a short wavelength (eg, 405 nm) and then detecting fluorescence at a longer wavelength. Living organisms contain fluorescent proteins, which are a hallmark of life and thus can be used herein as a means of verifying that the identification performed in step 105 is complete.

[0057] Kinetic motion data can be obtained by using an imaging device / optical device configured to capture image data. The imaging device can be a microscope configured to record kinetic motion (e.g., with a 100x objective and a fast CMOS camera). In addition, the imaging device can include an image processing device to determine the kinetic motion data. For example, the kinetic motion data can show that the particles exist with a certain reliability, but by also using fluorescence on the recorded image, it can be verified by checking the presence of fluorescent proteins, thereby increasing the reliability of the assessment of the existence / identity of the particles. Preferably, the images are recorded sequentially over a period of time so that the final increase and quantification of the particles around the electrode pair 2, 3 can be followed. Kinetic motion data can be obtained by bright field images captured by a microscope (optical device / imaging device), which are reflections or transmissions of a transmitted light beam. This method can not only determine the type of particles present, but also characterize / identify and quantify / count the particle types.

[0058] The predetermined data set may also include characteristic motion data of at least one determined particle type and characteristic fluorescence data of the determined particle type. Thus, for example, data showing that a specific particle type has a specific characteristic motion in the specific environment (which is determined by the background ion characteristics) is included, and additionally includes data of the kinetic motion and fluorescence of the specific particles. The predetermined data set may also include data of the particle-specific spatiotemporal correlation electric field for capturing a specific particle type, which is the electrode geometry and input bias parameters. Thus, a user utilizing the method may input a specific particle type and obtain the electrode geometry and input bias parameters required to capture the particle as output.

[0059] Background ion characteristics may include ionic strength, ionic response time, temperature, and ionic charge of the background ions / polarizable particles in the water sample. Intensity, response time, and charge may be obtained by applying a spatiotemporally correlated electric field, wherein the time-resolved response of the measured voltage and current from the electric field enables determination of the ionic strength, response time, and charge of the background ions / polarizable particles.

[0060] Particle-specific electric fields can be electric field capture particles, such as E. coli particle types.

[0061] Figure 1 It is also shown that the method 100 includes the step of applying 103' a third time-dependent bias voltage on a third pair of electrodes having a different spatial configuration than the second pair of electrodes to generate a different type of particle-specific electric field than the particle-specific electric field generated by the second pair of electrodes. Thus, the method 100 may include a plurality of electrode pairs, each electrode pair being used to determine a specific type of particle (live / organic particle type) or E. coli type.

[0062] Figure 2 A system 1 for determining the presence / identity of a particle type in water is schematically shown, the system 1 comprising at least a first pair of electrodes 2 and a second pair of electrodes 3, a control circuit system 4, a measurement chamber 5 configured to contain water. The control circuit system 4 is configured to perform a method 100 according to any aspect of the present invention. Thus, the first pair 2 can be directed to determine background ion characteristics, wherein the second pair 3 can be used to capture a specific particle type to determine its presence.

[0063] like Figure 2 As further shown in FIG. 1 , the system may include an inlet 6 arranged to receive the water to be examined. Thus, the inlet 6 leads to the measuring chamber 5 and ultimately to the outlet 7. Thus, the method 100 may be performed sequentially as the water passes through the electrode pair 2, 3. Figure 2 As shown, water can be introduced into the inlet 6 so as to pass through the space between each electrode pair 2 , 3 towards the outlet 7 .

[0064] Figure 2 It is also shown that system 1 can include a measuring device 8, which is configured to capture the kinetic motion data of the particles in the water sample and optionally the fluorescence data. The measuring device 8 can include a spectrometer device and an optical readout device (e.g., a microscope). System 1 can also include a temperature sensor to obtain the temperature of the background ions / polarizable particles in the water. In some aspects, a pH meter device can also be used in the system 1 of this article.

[0065] The control circuit system 4 may include one or more memory devices (not shown). The memory device may include any form of volatile or non-volatile computer-readable memory, including but not limited to permanent memory, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (e.g., hard disk), removable storage media (e.g., flash drive, compact disk (CD) or digital video disk (DVD)) and / or any other volatile or non-volatile, non-transitory device readable and / or computer executable memory device, which stores information, data and / or instructions that can be used by each associated control circuit system 4. Each memory device may store any appropriate instructions, data or information, including computer programs, software, applications including one or more of logic, rules, codes, tables, etc. and / or other instructions that can be executed and utilized by the control circuit system 4. The memory device 4 may be used to store any calculations performed by the control circuit system and / or any data received via the output and input interfaces. Thus, the memory device may store a predetermined data set including correlations, as well as any records from the measurement device. In some embodiments, each control circuit system 4 and each memory device may be considered integrated. In some embodiments, the memory devices and associated data are stored in a cloud server accessible by the control circuit system 4 .

[0066] Each memory device may also store data that may be retrieved, manipulated, created, or stored by the control circuit system 4. The data may include, for example, local updates, parameters, training data, a trained learning algorithm (and / or a model, component, data utilized in the trained learning algorithm, such as the data set herein). In some aspects, the control circuit system 4 includes a machine learning component that can implement a trained machine learning algorithm based on data from the memory device, and thus, the machine learning algorithm may utilize method steps 104 to 106. The data may be stored in one or more databases. One or more databases may be connected to the optimization device 2 via a high-bandwidth field area network (FAN) or a wide area network (WAN) or any wireless network. Thus, the control circuit system 4 may include data for capturing a particle-specific spatiotemporally correlated electric field of a particular particle type, so that a user may obtain the data for the desired particle type to be identified, and proceed accordingly to method step 101.

[0067] Circuit system 4 may include, for example, one or more central processing units (CPUs), graphics processing units (GPUs) dedicated to performing calculations, and / or other processing devices.

[0068] Figure 2Also shown is a calibration inlet 9 arranged to receive a cleaning fluid (eg water) to reset the system for additional measurements.

[0069] Figure 3 A more detailed view of the measuring device and in particular the spectrometer device is schematically shown, showing that the device may include a laser device 20 arranged to excite a laser beam 20', a reflection device 21, a chopper 22, a mirror 23, an objective lens 24, wherein the laser beam 20' from the laser device 20 is arranged to penetrate the objective lens 24 and reflect back at the water in the chamber 5 to penetrate the objective lens 24 a second time, thereby reflecting at the mirror 23 through a second lens 24' into a SPEX spectrometer including a detector 31 and a photomultiplier tube 32. In addition, the signal can reach the control circuit system 4 through the spectrometer 30, and the control circuit system 4 is configured to obtain fluorescence data, thereby comparing the fluorescence data with characteristic fluorescence data of a specific particle type. It should be noted that Figure 3 The measuring devices are disclosed for disclosure purposes only and may vary within the knowledge of a person skilled in the art.

[0070] Figure 4 A schematic diagram of the steps of determining 102 background ion characteristics according to aspects of the present disclosure is shown. Part A shows in an enlarged manner that at t0 when one electron in pair 2 is positively biased and the other is negatively biased, negative background ions 41 are attracted to the positively biased electrode, and positive background ions 42 are attracted to the negatively biased electrode, so that the bias V on the series-connected resistor R R Part A may show the spatial region between the pair of electrodes in an exemplary manner. R The change over time is the so-called time-resolved response, from which the intensity, response time, concentration, charge and mass of the background ions / polarizable particles are obtained. The time-resolved response is also shown as Figure 4 Thus, each electrode pair 2, 3 can be coupled to a bias voltage supply V and a series coupling resistor R, wherein the bias voltage V across the resistor can be R The derived time-resolved response can be used to derive background ion characteristics. The term "trapped particles" can refer to particles trapped between the electrode pair 2 (or in an area associated with the electrode pair 2), and thus kinetic motion data can refer to data captured from the area between the electrode pair 2.

[0071] Figure 5 A schematic diagram of the steps of determining 102 background ion characteristics according to aspects of the present disclosure is shown. Figure 5 In the embodiment, each electrode in the electrode pair is biased by a corresponding bias source so that each electrode is biased independently. Figure 5It is shown that at t0, when one electron in pair 2 is positively biased by a separate bias source and the other is negatively biased by a separate bias source, negative background ions 41 are attracted to the positive bias electrode and positive background ions 42 are attracted to the negative bias electrode, resulting in a bias voltage V on resistor R R decline. Figure 5 Each electrode is shown to be biased individually, where the bias voltages can be applied to a common time period and amplitude, but are complementary, so that when a positive bias is applied to one electrode of the pair, the other electrode of the pair is negatively biased. The time resolved response is also shown as a graph showing that the response is symmetrical. This enables the use of equation (1): V R =ae -bt The background ion characteristics can be conveniently obtained by correlating the response curve with equation (1) by using the equation (1) where t is the time of applying the electrical bias, a is proportional to the ion concentration, 1 / b is proportional to the ion mass, and c is the device-related noise that depends on the hardware, so c can be known / predetermined in advance. Therefore, the background ion characteristics can be obtained by correlating the response curve with equation (1). Figure 5 Also shown is a circuit system including a respective resistor coupled between a bias source providing a detection bias voltage V1 , V2 and each electrode. Figure 5 The period T shown in can be adjusted based on the amount of mass desired to be measured, e.g., a larger period T can enable measurement of a larger mass than a shorter period T. In other words, each bias voltage can be applied to a defined T based on a specific mass (desired to be measured).

Claims

1. A method (100) for characterizing the type of charged / polarizable organic live particles in water, comprising: - applying (101) a first time-dependent electrical bias to the first pair of electrodes so as to generate a first time- and space-dependent electric field in the water sample; - determining (102) background ion characteristics in the water sample based on the first electric field; - applying (103) a second time-dependent electrical bias to at least a second pair of electrodes to generate at least one particle-specific and time-dependent electric field in said water sample, thereby trapping particles between said second pair of electrodes; - obtaining (104) kinetic motion data of the captured particles; - Determining (105) the presence / identity of a charged / polarizable organic live particle type by comparing the kinetic motion data and background ion signature with a predetermined data set, the predetermined data set comprising characteristic kinetic motion data for a particular particle type based on different background ion signatures.

2. The method (100) according to claim 1, wherein: The predetermined data set also includes characteristic fluorescence data of the determined particle type, wherein the method further includes: - obtaining (106) fluorescence data of said capture particles in said water sample; - comparing said fluorescence data with said characteristic fluorescence data of said determined particle type (107).

3. The method (100) according to claim 1 or 2, wherein: The predetermined data set also includes data for capturing particle-specific spatiotemporally correlated electric fields of a specific particle type, which data are electrode geometry and input bias parameters.

4. The method (100) according to any one of claims 1 to 3, wherein: The background ion characteristics include ionic strength, ionic response time, temperature, and ionic charge of the background ions / polarizable particles in the water sample.

5. The method (100) according to any one of claims 1 to 4, wherein: The particle specific electric field is an electric field that captures the particle type, preferably E. coli.

6. The method (100) according to any one of claims 1 to 5, further comprising the following steps: A third time-dependent bias is applied (103') to a third pair of electrodes having a different spatial configuration than the second pair of electrodes to generate another particle-specific electric field of a different type than the particle-specific electric field generated by the second pair of electrodes.

7. The method (100) according to any one of claims 1 to 6, wherein: Electric field parameters from the particle-specific, spatiotemporally correlated electric field are current and voltage parameters measured as a function of time and space.

8. The method (100) according to any one of claims 1 to 7, wherein: The spatiotemporally dependent electric field is generated by a first time-dependent electrical bias and a second time-dependent electrical bias, which are particle-specific waveforms with dynamic durations.

9. The method (100) according to any one of claims 1 to 8, wherein: The step of applying (101) a first time-dependent electrical bias on a first pair of electrodes is performed by applying a first bias to a first electrode of the pair of electrodes and applying a second bias to a second electrode of the pair of electrodes, wherein the first bias and the second bias are alternating biases, wherein the alternating biases are applied to the pair of electrodes that are complementary to each other.

10. A system (1) for determining the presence / identity of a particle type in water, the system (1) comprising: - at least a first pair of electrodes and a second pair of electrodes (2, 3) -Control circuit system (4) - a measuring chamber (5) configured to receive a water sample; The control circuitry (4) is arranged to perform a method (100) according to any one of claims 1 to 9.

11. A computer-readable storage medium storing one or more programs, wherein the one or more programs are configured to be executed by one or more control circuit systems (4) of a system (1), and the one or more programs include instructions for executing the method (100) according to any one of claims 1 to 9.

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