WO2020013811A1

WO2020013811A1 - Assessment of water quality using rainbow patterns

Info

Publication number: WO2020013811A1
Application number: PCT/US2018/041481
Authority: WO
Inventors: Harm Stefan CRONIE
Original assignee: Xinova, LLC
Priority date: 2018-07-10
Filing date: 2018-07-10
Publication date: 2020-01-16

Abstract

Technologies are described for a system and method for analyzing a liquid sample. An example system may include a controller and an apparatus comprising a dispensing unit, a light source, and a sensor, where the system may be cost-effective and implemented in an inline or mobile environment allowing real-time analysis. For example, droplets of a liquid sample may be dispensed from the dispensing unit, and a light may be directed from the light source toward the droplets. The emitted light may encounter and interact with a droplet resulting in a light being returned from the droplet. The returned light may be captured by the sensor, and a spectral profile of the liquid sample may be generated by the controller based on factors associated with the captured light. The spectral profile of the liquid sample may be analyzed, by the controller to detect substances in and/or properties of the liquid sample.

Description

ASSESSMENT OF WATER QUALITY USING RAINBOW PATTERNS

BACKGROUND

[0001] Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.

[0002] While water purification techniques have continued to develop and become more cost effective, assessment of potable water is still a prevalent concern even in developed countries. In some cities, contaminants have gone unnoticed for long periods of time, which may have lasting health effects on citizens. Traditional assessments of water quality may require someone to retrieve samples and perform a series of experiments to determine properties of interest, such as a test for heavy metals, a test for bacterial contamination, a test for viral contamination, a test for parasitical contamination, or a test to determine a particular property of the water, such as the pH. More sophisticated means to assess water quality, such as

hyperspectral imaging, may also be implemented. Hyperspectral imaging directs light of a broad wavelength range toward a sample, captures an image of the sample, determines a spectrum for each pixel in a captured image, and may determine properties of the liquid sample based on the spectrum. Hyperspectral systems may be used to analyze relatively small volumes of a water supply and may typically be implemented in permanent facilities.

SUMMARY

10063] The present disclosure generally describes techniques to analyze a liquid sample.

[00041 According to some exan¾>ies, a method to analyze a liquid sample may include receiving the liquid sample, dispensing droplets of the liquid sample, directing light toward the droplets, capturing a returned light from the droplets, generating a spectral profile of the liquid sample based on the captured light, and analyzing the generated spectral profile to detect one or more substances in the liquid sample.

[0005] According to other examples, an apparatus to analyze a liquid sample may include a dispensing unh configured to receive the liquid sample and dispense droplets of the liquid sample. The apparatus may also include a light source configured to emit light towards the droplets. Additionally, the apparatus may include a sensor configured to capture a returned light from the droplets and transmit information associated with the captured light to a controller for generation of a spectral profile of the liquid sample based on the captured light and analysis of the generated spectral profile to detect one or more substances in the liquid sample.

[0006] According to further examples, a system to analyze a liquid sample may include a dispensing unit configured to receive the liquid sample and dispense droplets of the liquid sample. The system may also include a light source configured to emit light towards the droplets and a sensor configured to capture a returned light from die droplets. The system may further include a controller. The controller may include a memory configured to store instructions and one or more processors coupled to the memory. The processors may be configured to, in conjunction with the instructions stored on the memory, receive the captured light from die sensor, generate a spectral profile of the liquid sample based on the captured light, and analyze the generated spectral profile to detect one or more substances in the liquid sample.

10007] ^"The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The foregoing and other features of this disclosure will become more fully apparent from the following description and appended claims, taken in conjunction with the

accompanying drawings. Understanding that these drawings depict only several embodiments in accordance with die disclosure and are, therefore, not to be considered limiting of its scope, the disclosure will be described with additional specificity and detail through use of the

accompanying drawings, in which:

FIG. 1 includes a conceptual illustration of an apparatus to analyze a liquid sample;

FIG. 2 includes a conceptual illustration of another apparatus to analyze a liquid sample;

FIGs. 3 A and 3B include a conceptual illustration of reflection and refraction of light emitted toward droplets of a liquid sample; FIG. 4 illustrates major components of an example system configured to analyze a liquid sample;

FIG. 5 includes a flow diagram illustrating an example method to analyze a liquid sample and the components configured to execute the actions;

FIG. 6 illustrates a computing device, which may be communicatively coupled to an apparatus to analyze a liquid sample;

FIG. 7 is a flow diagram illustrating an example method to analyze a liquid sample that may be performed by a computing device such as the computing device in FIG. 6; and

FIG. 8 illustrates a block diagram of an example computer program product.

DETAILED DESCRIPTION

[0009] In the following detailed description, reference is made to the accompanying drawings, which form a part hereof, fa the drawings, similar symbols typically identify similar components, unless context dictates otherwise. The illustrative embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be utilized, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. The aspects of the present disclosure, as generally described herein, and illustrated in the Figures, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.

[0010] This disclosure is generally drawn, infer alia, to methods, apparatus, systems, devices, and/or computer program products related to analyzing a liquid sample.

[0011] Briefly stated, technologies are generally described to analyze a liquid sample. A liquid sample may be received by a dispensing unit of an apparatus. The dispensing unit may also dispense droplets of the liquid sample. The apparatus may also include a light source that is configured to emit a light toward die droplets. The emitted light may encounter and interact with a droplet resulting in a light being returned from the droplet. The apparatus may further include a sensor configured to capture the returned light. The sensor or the apparatus may transmit information associated with the captured light to a controller. The controller may generate a spectral profile of the liquid sample and analyze die spectral profile to detect one or more substances in the liquid sample. [0012] FIG. I includes a conceptual illustration of an apparatus to analyze a liquid sample, arranged in accordance with at least some embodiments described herein.

[0013] As shown in diagram 100, an apparatus may include a dispensing unit 102. The dispensing unit 102 may be configured to receive the liquid sample and may do so in a variety of ways. The liquid sample may be one of potable water, a beverage, liquid medicine, an industrial solution, or the like. For example, impurities or contaminants in gasoline or similar liquid fuels may be detected. In medical implementations, purity of liquid medications, as well as, bodily fluids may be analyzed using the principles described herein. Blood or urine may be tested for chemical or biological markers corresponding to phenotype or genotype that may need constant monitoring in some examples. Further, the tested fluids may include particles such as cells, molecules (e.g., DNA). Molecular taggants or dyes may also be used to enhance the signal of detection. An example apparatus may be used for diagnostic or monitoring purposes. The example apparatus may be implemented as a portable device or stationary device for home, field, and point-of-care use. Additional numbers and types of sensors may also be employed to detect / analyze various characteristics of liquid samples such as viscosity* density, etc.

[0014] In some examples, the liquid sample may be manually pouted or inserted into tire dispensing unit 102 or siphoned from an external source, such as a pipe or external storage container. Additionally, the dispensing unit 102 may include a storage unit of any size to store the liquid sample or a second liquid sample for analysis, such as a control sample or a sample that may be used during a calibration process. The storage unit may be integrated with the dispensing unit 102 or may be externally coupled to the dispensing unit 102. The dispensing unit 102 may include means to receive an input such as, a button, a switch, a touch screen, or the like. The received input may indicate that the liquid sample is being received and provide instructions for die dispensing unit 102 to prevent the liquid sample from being dispensed during a time period in which the liquid sample is received. The dispensing unit 102 may also receive instructions to control receiving a liquid sample and dispensing wirelessly according to at least some embodiments. The dispensing unit 102 may also be configured to receive an input indicating that the liquid sample has been received and that the liquid sample may be dispensed. In other embodiments, the dispensing unit 102 may be configured to detect a reception of the liquid sample and may automatically cease dispensing of die liquid sample upon the detection of the reception of the liquid sample. Additionally, die dispensing unit 102 may be configured to measure a volume of the received liquid sample. For example, in the case that die dispensing unit 102 was siphoning a liquid sample from a storage unit, the dispensing unit 102 may be configured to siphon a particular volume from the storage unit and may do so by measuring the volume of the liquid sample received.

[0015] After receiving the liquid sample, the dispensing unit 102 may be configured to dispense droplets 106 of the liquid sample. The dispensing unit 102 may include an array of micro-dispensers 104, as shown in diagram 100, or a single micro-dispenser. Each micro- dispenser in the array of micro-dispensers 104 may be a Joule-heating dispenser, for example. A Joule-heating dispenser may contain a fraction of the liquid sample in a conical reservoir, according to at least some embodiments. The Joule-heating dispenser may apply energy to the reservoir in the form of hea t, which may cause parts of the liquid sample in contact with the reservoir to evaporate, forming one or more vapor bubbles. The formation and collapse of the vapor bubbles may create a unidirectional dispensing action. In such embodiments, the amount of the liquid sample dispensed may be dictated by the amount of energy applied to the reservoir of the micro-dispenser or by the amount of time the energy is applied to the reservoir. In other embodiments, each micro-dispenser in the array of micro-dispensers 104 may be a piezo-electric dispenser. A piezo-electric dispenser may contain a fraction of the liquid sample in a reservoir. An electrical potential may be applied to the dispenser resulting m a mechanical force proportional to the electrical potential to be applied to the liquid sample in the reservoir. As a result, the liquid sample may be extruded or dispensed through an orifice in the reservoir.

[0016] The array of micro-dispensers 104 may dispense the liquid sample at a specified rate, as shown by arrow 108. The rate may be a predetermined rate or the dispensing unit 102 may determine the rate based on an input. A stogie drop dispensed may be about 5-100 pL. In example implementations, up to 10,000 drops par second may be dispensed by each dispenser. Supposing 1 to 1000 microdispensers per dispenser unit, liquid sample amounts may range from 5 pL (single drop of 5 pL once a second with one microdispenser) up to 1,000,000,000 pL (10,000 drops a second of iOOpL times 1000 microdispensers). As more drops implies more reflections and higher intensity of the recorded image and thus higher dynamic range, having as many drops as possible in flight at any time may be desirable for light to reflect For example,

1000 to 10000 drops to be illuminated at any time may be targeted, and system parameters (e g. number of microdispensers) may be designed to reach that target. The number of drops in flight may be limited by limitations of the microdispensers, size of microdispensers, evacuation capability after dispensed drops are collected, amount of liquid available vs. capture time of detection sensors, etc.

[0017] For example, as discussed above, the dispensing unit 102 may further include a touch screen, and a rate may be entered using the manual inputs. Alternatively, the dispensing unit 102 may be configured to receive a rate from a communicatively coupled computing device. The dispensing unit 102 may be physically connected to the computing device or may communicate with the computing device via a network. For example, die apparatus may be connected to a server via a network, and the server may provide a rate to the apparatus and dispensing unit 102 via the network based on a machine learning algorithm. The array of micro- dispensers 104 may also dispense droplets 106 of the liquid sample that are a particular diameter 1 10, which may range from about 0.1 mm to about 0.3 mm. For drop volumes in a range of 5 to 100 pL corresponding diameters may in the range of 0.1-0.3 mm. The resulting light pattern that is recorded may depend on the drop size. Larger drop sizes may be generally preferred because larger drops may separate the eolors better in the rainbow pattern resulting in increased precision. A system according to embodiments may be calibrated for an optimal size. Recording light patterns from different drop sizes may also provide additional information. The diameter 110 of the droplets 106 may be a predetermined diameter or the dispensing unit may receive the diameter from an external source.

[00181 After the dispensing unit 102 has dispensed the droplets 106, a light source 112 may emit light 114 toward the droplets 106. The light source 112 may be one of a light emitting diode (LED), a halogen lamp, a fluorescent lamp, an incandescent lamp, a laser source^ or die like. The light 114 emitted by the light source 112 may be monochromatic or polychromatic and may have a wavelength between about 200 nm and about 2000 nm. The emitted light 114 may be a constant beam, one or more pulses of light, or a pattern of light Pulses of light may be of a predetermined number or timing. Patterns of light may contain light of two or more specific wavelengths at once or in sequence. For example, a pattern of light may contain a first light with a wavelength of 700 nm, a second light with a wavelength of 520 nm, and a third light with a wavelength of 470 nm. In some embodiments, the three wavelengths (or more) may be included together in a single polychromatic beam, and in other embodiments, the three lights may be emitted in sequence. The light source 112 may be configured to receive parameters associated with the emitted light 114, such as the wavelength, the number of pubes, or the pattern of light via an input. For example, the apparatus may include manual inputs that allow a user to select the parameters associated with the emitted light 114. In other embodiments, the light source 112 or the apparatus may receive parameters associated with the emitted light 114 from an external source, such as from a computing device or controller via a network. The emitted light 114 may encounter a droplet of die liquid sample and may be reflected or refracted by the surface of the droplet, as discussed in greater detail below in conjunction with FIGs, 3A and3B. The emitted light 114 may be refracted within die droplet or reflected from the surface of the droplet. The light refracted within the droplet may be reflected off of a surface of the droplet opposite from the location on the surface where the emitted light 114 was initially refracted. The reflected light may then be refracted a second time, exit the droplet, and return 116 from the droplet. The returned light 116 may be a particular pattern generated by the first refraction, reflection, and second refraction of the emitted light 114. The pattern may include light of different wavelengths and intensities.

10019] The returned light 116 may then be captured by a sensor 118. The sensor 118 may be one of a complimentary metal-oxide-semiconductor (CMOS) sensor, a charge-coupled device (CCD) sensor a photodiode, an active-pixel sensor (APS), a cadmium zinc telluride radiation detector, a mercury cadmium telluride detector, a reverse-biased light emitting diode (LED), a photoresistor, a phototransistor, a quantum dot photoconductor, or the like. The sensor 118 may be positioned such that the returned light 116 is captured at a specific angle. For example, the sensor 118 may be positioned such that the returned light is captured at an angle of 42.5 degrees. An angle of 42.5 degrees may minimize the effect different angles of incidence of the emitted light 114 interacting with the droplets 106. The angle between the incoming light and the outgoing light may be highly dependent on the angle of incidence of die light on die drop surface. However, at approximately 42.5 degrees between the incoming light rays and outgoing light rays, die variation may be minimal. This is also referred to as the rainbow angle because a rainbow pattern may be observed at or around this angle. At the rainbow angle, small variations in the angle of incidence of light onto the drop surface may only have a small effect on the outgoing angle. In other examples, the sensor 118 may be positioned at another angle based on a type of analysis that is being conducted. The sensor 118 may capture the returned light 116 and transmit information associated with the captured light to a controller to be processed. Information associated with the captured light may include the pattern of the returned light and an intensity or brightness of the light. For example, a captured light may contain a pattern with a blue component, a red component, and an infrared component, each with a respective intensity.

[0020] According to other embodiments, additional sensors may be deployed in the collection unit, for example, to determine acidity, alkalinity, conductivity, and comparable characteristics of the liquid. Additionally, sound based (or similar) sensors may be used to measure speed of the droplets, for example.

[0021] The controller may be a computing device (e.g., a server, a desktop computer, a mobile computer, a special purpose computing device, or a component level processor) and may receive the information associated with captured light from the sensor 118 or the apparatus. The controller may then generate a spectral profile of the liquid sample based on the information received from the sensor 118, which includes a pattern of the captured light. The generated spectral profile may quantify properties of the captured light, such as die spectrum of the captured light and the intensities of the wavelengths of light in the spectrum of the captured light. The controller may compare the pattern of the captured light in the generated spectral profile with die patterns of spectral profiles of other l iquid samples stored in a database or with known patterns corresponding to particular properties of the liquid sample. Through the comparison, the controller may detect substances, such as dissolved or suspended substances, in the liquid sample. In some examples, a targe dataset of samples with known contaminations and samples with no contaminations may be built This labeled dataset may be used to train a machine learning algorithm such as a classifier, a neural network, or similar. When the algorithm is trained, if may be used to classify a recorded pattern into several classes. These classes may include“no contamination”,“lead contamination”, etc. While training such an algorithm, the decision boundaries (e.g. intensity threshold) may set automatically to suitable levels.

[0022] Various properties of the sample, such as the pH of the sample, the turbidity of the sample, the total organic carbon of content of the sample, and the electrical conductivity of the sample, among other examples, may also be determined. The controller may then store the generated spectral profile along with any detected dissolved substances, any detected suspended substances, and any properties of the liquid sample in the database. For example, a pH of a solution may be determined by H+ and OH- tons in the solution. H+ mid OH- have specific absorption peaks that can be detected in a hyperspectral image. From the relative depth of absorption peaks, for example, the pH may be determined. In a practical setting, a calibration may be performed once to find a relation between observed pattern and pH that may be applicable to a family of solutions being used. Turbidity may be determined by many types of particles presort that have a particular chemical makeup. Hence, spectral images may be used to detect these individual molecules. In the case of turbidity, overall intensity may also be used as a measure. A calibration may be performed to determine the turbidity index according to ISO 7027, for example. Total organic carbon content may also be determined using a similar approach as with turbidity. A change in refractive index or infrared (IR) absorption of CCb generated by acidification and/or oxidation may also be used to determine total organic carbon content. Conductivity may be determined by the ions present in the sample liquid. Different ions have different spectral absorption characteristics and by detecting, for example, a spectral absorption peak at a certain wavelength, the actual ion presence may be determined.

Concentration may be determined by the depth of the absorption peak, which may then provide sufficient information to determine the concentration. Once all ions are detected, the pH may be determined by computation. It should be noted, that in the potable water analysis example, there may be only a few common salts that constitute all ions present in the solution. Additionally, a calibration may be performed.

[0023] Because the sizes of foe dispensed droplets are known together with the physics of rainbow formation, a transfer function from light source to recorded rainbow pattern may also be determined. The transfer function may then be used to estimate a hyperspectral image of the sample that gives the absorption / transmission as a function of wavelength. From foe hyperspectral data, the properties of the sample liquid may be determined such as pH, conductivity, and total organic carbon. For specific solutions such as drinking water, an initial calibration may be performed where many variants of drinking water may he dispensed and rainbow patterns recorded. The variants may be analyzed during the calibration. Then a machine learning algorithm (regression, neural net, decision tree, etc.) may be used to model foe underlying physics implicitly, and the model may then be used as an estimator that maps a rainbow pattern to a set of water quality parameters.

[0024] In an example scenario, the dispensing unit 102 may receive a sample of water from a city’s water supply. The dispensing unit 102 may dispense droplets of the sample at a predetermined rate and a pie-determined diameter. The light source 112 may emit light toward foe droplets of the sample, and the sensor 118 may capture a returned light from the droplets. The sensor 118 may transmit information associated with the captured light to the controller. The controller may generate a spectral profile of the sample and analyze the sample to determine any substances suspended in the sample, substances dissolved in the sample, as well as the pH of the sample, the turbidity of the sample, the total organic carbon of content of the sample, and the electrical conductivity of the sample, among other examples. In the example scenario, the controller may analyze the generated spectral profile to determine if the city’s water contains substances, such as bacteria, viruses, parasites, other contaminants, such as heavy metals or if any of the properties of the liquid sample are outside of a safety range. The safety ranges may be pre-determined by laws, health organizations, a user of the system, or by the controller.

[0025] As discussed above, traditional assessments of a liquid sample may require retrieving samples and performing a series of experiments to determine properties of interest, such as a test for heavy metals, a test for bacterial contamination, a test for viral contamination, a test for parasitical contamination, or a test to determine a particular property of the water, such as file pH. These assessments are often time consuming, emstiy, and subject to human error.

Hyperspectral imaging, a more sophisticated method of analyzing a liquid sample, involves directing light of a broad wavelength range toward a sample, capturing an image of the sample, determining a spectrum for each pixel in a captured image, and determining properties of the liquid sample based on the spectmms. However, means of performing hyperspectral imaging are relatively expensive for inline and mobile testing systems as well as time consuming when compared to systems that provide real-time analysis of large volumes of a liquid sample. The embodiments described herein provide a more effective and efficient method for determining a large number of properties of a liquid sample that allows for real-time inline or mobile testing of a liquid sample. Such embodiments may be a more cost-effective and accessible solution than the prior art as described above. For example, it may be less expensive and more efficient to install a number of the apparatuses similar to the apparatus described above in conjunction with FIG.l throughout a city’s water supply system. The apparatuses may continually provide realtime assessment of water quality throughout the system without wasting or contaminating any of the water supply themselves.

[0026] FIG. 2 includes a conceptual illustration of another apparatus to analyze a liquid sample arranged in accordance with at least some embodiments described herein. [0027] As shown in diagram 200, an apparatus 202 may comprise a dispensing unit 204, The dispensing unit 204 may be configured to receive a liquid sample in a variety of ways as discussed above in conjunction with FIG. 1. The dispensing unit 204 may include an array of micro-dispensers 206 which are configured to dispense droplets 208 of the liquid sample. The array of micro-dispensers 206 may be Joule-heating dispensers, piezo-electric dispensers, or a combination thereof. In other embodiments, the dispensing unit 204 may include a single microdispenser configured to dispense droplets of tire liquid sample. The array of micro-dispensers 206 may dispense droplets of the liquid sample at a rate ranging from 1 to 10,000. The array of micro-dispensers 206 may also disperse droplets of the liquid sample with a speci fic diameter ranging from 0.1 mm to 0.3 mm. The specific rate and the specific diameter may be

predetermined or the apparatus 202 may be configured to determine a rate or a diameter based on an input or an external source. For example, the apparatus 202 may be configured to receive a manual input that indicates a specific rate or a specific diameter. In other embodiments, the apparatus 202 may be configured to receive a specific rate or a specific diameter via a wireless connection, such as over a network.

[0028] The apparatus 202 may further comprise a first light source 210 and a second light source 212. The first light source 210 and the second light source 212 may be a light emitting diode (LED), a halogen lamp, a fluorescent lamp, an incandescent lamp, a laser source, or the like. The first light source 210 and the second light source 212 may emit light that is

monochromatic or polychromatic with a wavelength between 200 nm and 2000 nm. The first light source 210 may emit a first light 214, and the first light 214 may encounter a droplet of the liquid sample and may be reflected or refracted by tile surface of the droplet, as discussed in greater detail below in conjunction with FIGs.3 A arid 3B. The first light 214 may be one of a constant beam, one or more pulses of light, or a pattern of light. The interaction of the first light 214 with tihe droplets may generate a first returned light 216.

[0029] The apparatus 202 may further comprise a first sensor 218 and a second sensor 220 configured to capture light returned from the droplets 208. The first sensor 218 and the second sensor 220 may be a complimentary metal -oxide-semiconductor (CMOS) sensor, a charge- coupled device (CCD) sensor a photodiode, an active-pixel sensor (APS), a cadmium zinc telluride radiation detector, a mercury cadmium felluride detector, a reverse-biased light emitting diode (LED), a photoreststor, a phototransistor, a quantum dot photoconductot, or the like. The first sensor 218 may capture the first returned light 216 and may be positioned to capture the first returned light 216 at a specific angle, such as 42.5 degrees. The apparatus 202 may be configured to transmit information associated with the first returned light 216 to a controller 222. In some embodiments, the controller 222 and the apparatus 202 may be integrated.

[0030] The controller 222 may receive the information associated with die first returned light 216 from the apparatus 202. information associated with the first returned light 216 may include the pattern of the returned light and an intensity of the light. The controller 222 may then generate a first spectral profile of the liquid sample based on the information received from foe apparatus 202 by quantifying properties of foe captured light, such as the spectrum of foe captured light and the intensities of foe wavelengths of light in the spectrum of foe captured light. The controller 222 may compare foe pa ttern of the captured light in foe generated spectral profile with foe patterns of spectral profiles of other liquid samples stored in a database or with known patterns corresponding to particular properties of the liquid sample. If foe controller 222 is unable to identify a known pattern or spectral profiles of other liquid samples stored in foe database^ foe controller 222 may transmit instructions to foe apparatus 202 to perform a calibration process. The calibration process may include analyzing one or more liquid samples with and without known contaminants and performing analysis of a control liquid sample using variable analysis parameters. The analysis parameters may include a wavelength of the emitted light, a pattern of the emitted light, the diameter of foe droplets, and foe rate foe droplets are dispensed. In other embodiments, the apparatus 202 may initiate the calibration process powering on the apparatus 202 or foe controller 222, in response to a component being added to the apparatus 202 or replaced within foe apparatus 202 (i.e. foe first light source 210 or foe first sensor 218), or in response to an input, such as a manual input or a received signal.

[0631] As discussed above foe controller 222 may compare foe pattern of foe first returned light 216 in the generated spectral profile with foe patterns of spectral profiles of other liquid samples stored in a database or with known patterns corresponding to particular properties of the liquid sample. Based on foe comparison, foe controller 222 may detect substances in the liquid sample and to determine various properties of foe sample, such as the pH of foe sample, foe turbidity of the sample, foe total organic carbon of content of foe sample, foe electrical conductivity of foe sample, among other examples. Based on the analysis, the controller 222 may identify a property of the liquid sample to be further analyzed and determine one or more analysis parameters to analyze the identified property. As discussed above, the analysis parameters may include: a control liquid sample with and without contaminants, wavelength of the emitted light, the pattern of the emitted light, the diameter of the droplets, or the rate at which the droplets are dispensed. In an example scenario, the controller 222 may analyze the first spectral profile and detect lead suspended in the liquid sample. The controller 222 may then identify a specific concentration of lead in the liquid sample and determine a range of wavelengths of light to quantify the concentration of lead in the liquid sample. For example, the controller 222 may determine to analyze die liquid sample using wavelengths of 205 nanometers (nm), 210 nm, 215 nm, 220 nm, and 225 nm to accurately determine the concentration of lead in the liquid sample. The controller 222 may then transmit instructions to the apparatus 202 to analyze the liquid sample using the identified analysis parameter's).

{0032) The apparatus 202 may receive the identified analysis parameters and analyze the liquid sample using the received parameters. In tire example scenario described above, the apparatus 202 may receive the identified wavelengths to determine the concentration of lead in die liquid sample. The dispensing unit 204 may dispense droplets 208 of the liquid Sample and the second light source 212 may emit a second light 224 with a wavelength of 205 run, the first wavelength among die identified wavelengths. The second light 224 may encounter and interact with one or more droplets 208 of the liquid sample, and the interaction may produce a second returned light 226. The second sensor 220 may capture the second returned light 226, and the apparatus 202 may transmit information associated with the second returned light 226 to the controller 222. The apparatus 202 may repeat this process using the other identified wavelengths and transmit the information associated with captured light corresponding to each tested wavelength to die controller 222. The controller 222 may receive die information associated with each captured light and analyze the captured light to quantify die concentration of lead in die liquid sample. In other embodiments, the controller 222 may identify another dissolved substance, another suspended substance, or another property of the liquid sample to quantify.

[00331 The apparatus 202 may further comprise a collection unit 228. The collection unit 228 may be configured to collect the droplets 208 of the liquid sample. The collection unit 228 may dispose of the collected droplets, may return the collected droplets to an external source, such as an external storage container or pipe, or may return die collected droplets to die dispensing unit 204. [0634] FIGs. 3A and 3B include a conceptual illustration of reflection and refraction of light emitted toward droplets of a liquid sample.

[0035] As shown in diagrams 300A and 300B, an emitted fight 302 originating from a light source may encounter a droplet 304. The emitted light 302 may travel parallel along an axis toward the droplet 304. Diagram 300A provides a first view that depicts the emitted light 302 and the droplet 304 perpendicular to the x-axis and y-axis and parallel to the z-axis. Upon encountering the droplet 304 of the liquid sample, die emitted light may be reflected 30$ from the surface of the droplet 304. The emitted light 302 may also be refracted, designated by the first circle 308, into at least a first refracted beam 310 and a second refracted beam 312 when the emitted light 302 passes into die droplet 304. The properties of the liquid sample may determine how many beams are generated and the wavelengths of the beams generated by the refraction of the emitted light 302. The first refracted beam 310 and the second refracted beam 312 may travel through the droplet 304 and encounter the opposite surface of the droplet 304. Upon

encountering die opposite surface of the droplet 304, the first refracted beam 310 and the second refracted beam 312 may be reflected within the droplet 304, as shown in the second circle 314. The first refracted beam 310 and the second refracted beam 312 may then interact with another surface of the droplet 304 and be refracted once again as a result of exiting the droplet, designated by a third circle 316.

[0036] Diagram 300B, provides a second view that depicts the emitted light 302 and the droplet 304 perpendicular to the z-axis and y-axis and parallel to the x-axis. The emitted light 302 may then encounter the droplet 304 and may be refracted upon encountering the surface of the droplet 304, as shown in the first circle 308 into at least a first refracted beam 312 and a second refracted beam 310, ais described above m diagram 300A. The first refracted beam 310 and die second refracted beam 312 may then be reflected within the droplet 304 by an opposite surface of the droplet 304, as shown in the second circle 314, and refracted once again by another surface of the droplet 304, as shown in the third circle 316. These interactions may result in at least three distinct beams of light being returned from the droplet 304 that create a pattern 318. The pattern 318 may include the light reflected from the surface of the droplet 306, the first refracted beam 310, and the second refracted beam 312. The wavelengths and intensities of each of the components of the pattern 318 may vary depending on the properties of the liquid sample as well as any substances dissolved or suspended in the liquid sample. The pattern 318 of the returned light may be captured by a sensor of an apparatus and properties of the pattern 318, such as the spectrum of the captured light and the intensities of the wavelengths of light in the spectrum of the captured light, to generate a spectral profile of the liquid sample.

[0037] FIG. 4 includes a flow diagram illustrating components configured to analyze a liquid sample according to at least some embodiments described herein.

[0038] As shown in diagram 400, a system 402 may include a dispensing unit 410 configured to receive a liquid sample (41? j in a variety of ways. For example, the liquid sample may be manually poured or inserted into the dispensing unit 410 or siphoned from an external source, such as a pipe or external storage container. The dispensing unit 410 may also be configured to dispense droplets of the liquid sample (414). The dispensing unit 410 may dispense droplets with a specific diameter and at a specific rate. The specific diameter and the specific rate may be predetermined or the dispensing unit 410 may receive the values for the specific diameter or the specific rate, such as from a manual input or via a network.

[0039] The system 402 may also include a light source 420 configured to emit light toward die droplets of the liquid sample (422). The light emitted toward the droplets may be

monochromatic or polychromatic and may have a wavelength tanging from 200 nm to 2000 nm. The light may be a constant beam, one or more pulses of light, or a pattern of light Pulses of light may be of a pre-determined number or timing. Patterns of light may contain light of two or more specific wavelengths at once or in sequence. The directed light may encounter a droplet of the liquid sample and may be reflected or refracted by the surface of the droplet. The light refracted within the droplet may be reflected off of a surface of the droplet opposite from the location on the surface where the directed light was initially refracted. The light may then be refracted a second time exiting the droplet and returned. The returned light may be a particular pattern generated by the first refraction, reflection, and second refraction of the directed light.

The pattern may include light of different wavelengths and intensities.

[0040] The system 402 may also include a sensor 430 configured to capture the returned light from the droplets (432). The sensor 430 may capture the returned light at a specific angle based on the type of analysis being performed. For example, the sensor 430 may capture the returned light at an angle of 42.5 degrees. The sensor 430 may then transmit information associated with the captured light to die controller 440. Information associated with the captured light may include the pattern of the returned light and an intensity or brightness of the light. [0041] The system 402 may further include the controller 440 configured to receive die information associated with the captured light from the sensor 430. The controller 440 may then generate a spectral profile of the liquid sample (442) based on the information received from the sensor 430. The generated spectral profile may quantify properties of the captured light, such as the spectrum of the captured light and the intensities of the wavelengths of light in the spectrum of the captured light The controller 440 may compare the pattern of the captured light in the generated spectral profile with die patterns of spectral profiles of other liquid samples stored in a database car with known patterns corresponding to particular properties of the liquid sample (444). Through the comparison, the controller 440 may detect substances, such as dissolved or suspended substances, in the liquid sample and determine various properties of the sample, such as the pH of the sample, the turbidity of the sample, the total organic carbon of content of the sample, and the electrical conductivity of the sample, among other examples. The controller 440 may then store the spectral profile along with any detected dissolved substances, any detected suspended substances, and any properties of the liquid sample in the database.

[0042] FIG. 5 illustrates major components of an example system configured to analyze a liquid sample according to at least some embodiments described herein.

[0043] As shown in diagram 500, an apparatus 522 and a processor 530 may be governed by a system controller 520. The processor 530 may be a controller, such as the controller 222 as described in conjunction with FIG. 2, for example. The system controller 520 may be managed manually through a variety of inputs, may operate automatically after receiving one or more instructions, or may be operated independently by software. The system controller 520 may also be partially or entirely managed by a remote controller 440, for example, via network 510. The remote controller 540 may be managed manually through a variety of inputs, may operate automatically after receiving one or more instructions, or may be operated independently by software. Data associated with controlling the different processes of analyzing a liquid sample may be stored at and/or received from data stores 560.

[0044] The apparatus 522 may include a dispensing unit 524, a light source 526, and a sensor 528 in accordance with other embodiments described herein. The dispensing unit 524 may be configured to receive a liquid sample and dispense droplets of the liquid sample at a specific rate and a specific diameter. The light source 426 may be configured to emit a monochromatic light or polychromatic light toward the droplets of the liquid sample. The emitted light may encounter and interact with the droplets as described above in conjunction with FIGs. 3 A and 3B. A returned light may be generated and may be captured by the sensor 528. The apparatus 522 may then transmit information associated with the captured light to the processor 530.

According to some embodiments, the sensor 528 may also transmit information associated with the captured light to the processor 530.

[0045] The processor 530 may be a computing device (e.g., a server, a desktop computer, a mobile computer, a special purpose computing device, or even a component level processor) and may receive the information associated with captured light from the apparatus 522. Information associated with the captured light may include the pattern of the returned light and an intensity of the light. The processor 530 may then generate a spectral profile of the liquid sample based on the information received from the sensor, which includes a pattern of the captured light. The generated spectral profile may quantify properties of die captured light, such as the spectrum of the captured light and the intensities of the wavelengths of light in the spectrum of the captured light. The processor 530 may compare die pattern of the captured light in the generated spectral profile with the patterns of spectral profiles of other liquid samples stored in a database or with known patterns corresponding to particular properties of the liquid sample. Based on the comparison, the processor 530 may detect substances, such as dissolved or suspended

substances, in the liquid sample and determine various properties of the sample, such as the pH of the sample, the turbidity of the sample, the total organic carbon of content of the sample, and the electrical conductivity of die sample, among other examples. The processor 530 may also identify a property of the liquid sample to further analyze or further quantify, such as the concentration of a substance in die liquid sample. The processor 530 may determine one or more analysis parameters to analyze the identified property and may instruct die apparatus 522 to analyze the liquid sample using the determined analysis parameters. The apparatus 522 may transmit information associated with the light captured during the further analysis of die liquid sample to die processor 530, and the processor 530 may analyze the information associated with the captured light to quantify die identified property. The processor 532 may include, in son» examples, a signal processor 532 to perform some or all of the tasks performed by the processor

530.

[0046] The examples provided in FIGs, l through 5 are illustrated with specific systems, devices, and processes. Embodiments are not limited to environments according to these examples. Situationally tailored control and optimization of liquid analysis may be implemented in environments employing fewer or additional systems, devices, and processes. Furthermore, the example systems, devices, and processes shown in FIGs. I through 5 may be implemented in a similar manna: with other values using the principles described herein.

{0047] FIG. 6 illustrates a computing device, which may be communicatively coupled to an apparatus to analyze a liquid sample, arranged in accordance with at least some embodiments described herein.

[0048] ln an example basic configuration 602, die computing device 600 may include one or more processors 604 and a system memory 606. A memory bus 608 may be used to

communicate between the processor 604 and the system memory 606. The basic configuration 602 is illustrated in FIG. 6 by those components within the inner dashed line.

[0049] Depending on the desired configuration, the processor 604 may be of any type, including but not limited to a microprocessor (mR), a microcontroller (pC), a digital signal processor (DSP), or any combination thereof. The processor 604 may include one or more levels of caching, such as a cache memory 612, a processor core 614, and registers 616. The example processor core 614 may include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP Core), or any combination thereof. An example memory controller 618 may also be used with the processor 604, or in some implementations, the memory controller 618 may be an internal part of the processor 604.

[0050] Depending on the desired configuration, the system memory 606 may be of any type including but not limited to volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.) or any combination thereof. The system memory 606 may include an operating system 620, a controller 622, and program data 624. The controller 622 may receive the information associated with the captured light from a sensor or from an apparatus. The controller 622 may then generate a spectral profile of the liquid sample based on the received information. The controller 622 may analyze the generated spectral profile of the liquid sample to detect substances in the liquid sample and to determine various properties of the sample. The controller 622 may then store the spectral profile along with any detected dissolved substances, any detected suspended substances, and any properties of the liquid sample with the other stored spectral profiles 628. [0051] Program data 624 may include stored spectral profiles 628. The stored spectral profiles 628 may include one or more spectral profiles of other liquid samples as well as substances dissolved in the other liquid sample, substances suspended in the other liquid samples, and properties of the other liquid samples.

[0052] The computing device 600 may have additional features or functionality, and additional interfeces to facilitate communications between the basic configuration 602 and any desired devices and interfeces. For example, a bus/interface controller 630 may be used to facilitate communications between fee basic configuration 602 and one or more data storage devices 632 via a storage interface bus 634. The data storage devices 632 may be one or more removable storage devices 636, one or more non-removable storage devices 638, or a combination thereof. Examples of fee removable storage and fee non-removable storage devices include magnetic disk devices such as flexible disk drives and hard-disk drives (HDDs), optical disk drives such as compact disc (CD) drives or digital versatile disk (DVD) drives, solid state drives (SSDs), and tape drives to name a few. Example computer storage media may include volatile and nonvolatile, removable and non-removable media irnpleinented in any method or technology ibr storage of information, such as computer readable instructions, data structures, program modules, or other data.

[0053] The system memory 606, fee removable storage devices 636 and the non-removable storage devices 638 are examples of computer storage media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD- ROM, digital versatile disks (DVDs), solid state drives, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which may be used to store fee desired information and which may be accessed by fee computing device 600. Any such computer storage media may be part of the computing device

600.

[0054]The computing device 600 may also include an interface bus 640 for facilitating communication from various interface devices (e.g., one or more output devices 642, one or more peripheral interfaces 650, and one or more communication devices 660) to the basic configuration 602 via the bus/interface controller 630. Some of the example output devices 642 include a graphics processing unit 644 and an audio processing unit 646, which may be configured to communicate to various external devices such as a display or speakers via one or more A/V ports 648. One or more example peripheral interfaces 6S0 may include a serial interface controller 654 or a parallel interface controller 656, which may be configured to communicate with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, touch input device, etc.) or other peripheral devices (e.g., printer, scanner, etc.) via one or more I/O ports 658. An example communication device 660 includes a network controller 662, which may be arranged to facilitate communications with one or more other computing devices 666 over a network communication link via one or more communication ports 664. The one or more other computing devices 666 may include servers at a datacenter, customer equipment, and comparable devices.

[0055] The network communication link may be one example of a communication media. Communication media may be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and may include any information delivery media. A“modulated data signal” may be a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), microwave, infrared (IR) and other wireless media. The term computer readable media as used herein may include both storage media and communication media.

[0056] The computing device 600 may be implemented as a part of a specialized server, mainframe, or similar computer that includes any of the above functions. The computing device 600 may also be implemented as a personal computer including both laptop computer and non- laptop computer configurations,

[0057] FIG. 7 is a flow diagram illustrating an example method to analyze a liquid sample that may be performed by a computing device such as the computing device in FIG. 6.

[0058] Example methods may include one or more operations, functions or actions as illustrated by one or more of blocks 722, 724, 726, 728, 730, and 732, and may in some embodiments be performed by a computing device such as die computing device 600 in FIG. 6. The operations described in the blocks 722, 724, 726, 728, 730, and 732 may also be stored as computer-executable instructions in a computer-readable medium such as a c omputer-r eadable medium 720 of a computing device 710, [0059] An example process to analyze a liquid sample may begin with block 722, “RECEIVE A LIQUID SAMPLE”, where a dispensing unit may receive the liquid sample in a variety of ways. For example, the liquid sample may be manually poured or inserted into the dispensing unit or siphoned from an external source, such as a pipe or external storage container. The storage unit may be integrated with the dispensing unit or may be externally coupled to the dispensing unit. The dispensing unit may also include controls for receiving the liquid sample. For example, the dispensing unit may include a manual input, such as a button, a switch, a touch screen, or the like, to indicate the liquid sample is being received or has been received.

[0060] Block 722 may be followed by block 724,“DISPENSE DROPLETS OF THE LIQUID SAMPLE”, where the dispensing unit may dispense droplets of the liquid sample with a specific diameter, at a specific rate, or a combination thereof. The specific diameter and the specific rate may be predetermined or the dispensing unit may receive the values for the specific diameter or the specific rate from an external source, such as a manual input or via a network.

[0061] Block 724 may be followed by block 726,“DIRECT LIGHT TOWARD THE DROPLETS”, where a light source may emit a light toward the droplets of the liquid sample.

The light may be monochromatic or polychromatic and may have a wavelength ranging from 200 nm to 2000 nm. The light may be one of a constant beam, one or more pulses of light, or a pattern of light. Pulses of light may be of a pre-determined number or timing. Patterns of light may contain light of two or more specific wavelengths at once or in sequence. The directed light may encounter a droplet of the liquid sample and may be reflected or refracted by the surface of the droplet. The light refracted within die droplet may be reflected off of a surface of the droplet opposite from the location on the surface where the directed light was initially refiacted. The light may then be refracted a second time exiting the droplet arid returned from the droplet toward a sensor. The returned light may be a particular pattern generated by the first refraction, reflection, and second refraction of the directed light The pattern may include light of different wavelengths and intensities.

[0062] Block 726 may be followed by block 728,“CAPTURE A RETURNED LIGHT FROM THE DROPLETS”, where the sensor may capture the light returned from the droplets. The sensor may capture the returned light at a particular angle based on the type of analysis being performed. The sensor may then transmit information associated with die captured light to a controller. Information associated with toe captured light may include toe pattern of the returned light and an intensity or brightness of the light.

[0063] Block 728 may be followed by block 730,“GENERATE A SPECTRAL PROFILE OF THE LIQUID SAMPLE BASED ON THE CAPTURED LIGHT’, where a controller may receive the information associated with the captured light from the sensor or, according to other embodiments, from an apparatus. The controller may then generate a spectral profile of the liquid sample based on the information received from toe sensor. The spectral profile may quantify properties of toe returned light such as the wavelengtos and their respective intensities in a pattern of the returned light. The controller may generate toe spectral profile based on a comparison of the pattern of the captured light with spectral profiles of other liquid samples stored in a database or with known patterns corresponding to particular properties of toe liquid sample.

[0064] Block 730 may be followed by block 732,“ANALYZE THE GENERATED SPECTRAL PROFILE TO DETECT ONE OR MORE SUBSTANCES IN THE LIQUID SAMPLE", where the controller may analyze the generated spectral profile of the liquid sample to detect substances in the liquid sample and to determine various properties of toe sample. The controller may detect substances dissolved in toe liquid sample, substances suspended in the liquid sample, or one or more properties of the liquid sample. The controller may then store toe spectral profile along with any detected dissolved substances, any detected suspended

substances, and any properties of the liquid sample in the database.

[0065] FIG. 8 illustrates a block diagram of an example computer program product, arranged in accordance with at least some embodiments described herein.

[0066] In some examples, as shown in FIG. 8, a computer program product 800 may include a signal-bearing medium 802 that may also include one or more machine readable instructions 804 that, when executed by, for example, a processor may provide the functionality described herein. Thus, for example, referring to toe processor 604 in FIG. 6, the controller 622 may undertake one or more of toe tasks shown in FIG. 8 in response to toe instructions 804 conveyed to the processor 604 by toe signal-bearing medium 802 to perform actions associated with analyzing a liquid sample as described herein. Some of those instructions 804 may include, tor example, instructions to receive a liquid sample* dispense droplets of the liquid sample, direct light toward the droplets, capture a returned light from the droplets, generate a spectral profile of the liquid sample based on the captured light, and analyze the generated spectral profile to detect one or more substances in the liquid sample, according to some embodiments described herein.

[0067] In some implementations, the signal-bearing medium 802 depicted in FIG. 8 may encompass computer-readable medium 806, such as, but not limited to, a hard disk drive, a solid state drive, a Compact Disc (CD), a Digital Versatile Disk (DVD), a digital tape, memory, etc. In some implementations, the signal-bearing medium 802 may encompass recordable medium 808, such as, but not limited to, memory, read/write (R/W) CDs, R/W DVDs, etc. In some implementations, the signal-bearing medium 802 may encompass communications medium 810, such as, but not limited to, a digital and/or an analog communication medium (for example, a fiber optic cable, a waveguide, a wired communications link, a wireless communication Knk, etc.). Thus, for example, the computer program product 800 may be conveyed to one or more modules of the processor 604 by an RF signal bearing medium, where the signal-bearing medium 802 is conveyed by a communications medium 810 (for example, a wireless

communications medium conforming with the IEEE 802.11 standard).

[0068] According to some examples, a method to analyze a liquid sample may comprise: receiving the liquid sample, dispensing droplets of the liquid sample, directing light toward the droplets, capturing a returned light from the droplets, generating a spectral profile of the liquid sample based on the captured light, and analyzing die generated spectral profile to detect one or more substances in the liquid sample.

[0069] in other examples, the analyzing the generated spectral profile to detect one or more substances in the liquid sample may include comparing a pattern of the captured light of the generated spectral profile with one or more patterns of spectral profiles of other liquid sanples stored in a database or one or more known patterns corresponding to particular properties of the liquid sample and determining one or more of a substance suspended in die liquid sample and a substance dissolved in the liquid sample based on the comparison. In further examples, the method analyzing the generated spectral profile further may also include analyzing the generated spectral profile to determine one or more quality parameters of the liquid sample. In some examples, the one or more quality parameters may include: a pH of the liquid sample, a turbidity of the liquid sample, a total organic carbon content of the liquid sample, or an electrical conductivity of die liquid sample [0070] According to further examples, the method may further include storing the spectral profile of the liquid sample and storing the determined substances suspended in the liquid sample, the determined substances dissolved in the liquid sample, and one or more determined one or more quality parameters of the liquid sample in a database. In other examples, generating the spectral profile of the liquid sample may include determining a spectrum of a pattern of the captured light, determining an intensity of each of the one or more wavelengths in the spectrum, and generating the spectral profile of die liquid sample based on the comparison. The spectrum of the pattern of light may contain light of one or more wavelengths. In some examples, die method may also include in response to generating the spectral profile of the liquid sample based on the comparison, identifying a property of the liquid sample to be further analyzed, determining an analysis parameter to analyze the identified property of the liquid sample, setting the analysis parameter, performing the analysis of the liquid sample using the set analysts parameter, and analyzing the captured light from the droplets to quantify the identified property of the liquid sample. The analysis parameter may be one of a wavelength of the directed light, a pattern of the directed light, a diameter of the droplets, and a rate the droplets are dispensed-

[0071] In other examples, the method may also include performing a calibration process, which may be performed in response to a failure to identify a known pattern or a spectral profile of another liquid sample at a database of spectral profiles. In some examples, performing the calibration process may include analyzing one or more liquid samples with and without known contaminants or selecting an analysis parameter, setting the analysis parameter, and performing the analysis of the liquid sample using the set analysis parameter. The analysis parameter may be one of a wavelength of the directed light, a pattern of die directed light, a diameter of die droplets, and a rate the droplets are dispensed.

[0072] According to further examples, dispensing the droplets of the liquid sample may include dispensing droplets from a single microdispenser or dispensing droplets from an array of microdispensers. In some examples, dispensing droplets of the liquid sample may include setting a parameter of a dispenser such that die droplets have a diameter in a range from about 0.1 mm to about 0.3 mm or setting a parameter of a dispenser such that the droplets are dispensed at a rate in a range from about 1 to about 10,000. In other examples, directing the light toward the droplets may include directing a monochromatic light or a polychromatic light toward die droplets. According to further examples, capturing die returned light from die droplets may include capturing the returned tight at an angle of 42.5 degrees, ha some examples, the renamed tight may include: tight reflected from an external surface of the droplets, tight refracted within the droplets that is reflected from an internal surface of the droplets. In other examples, directing the tight may include emitting the tight from one or more light sources. According to further examples, capturing the returned light may include capturing the returned light through one or more sensors. In some examples, the liquid sample may be one of: potable water, a beverage, liquid medicine, a liquid fuel, or an industrial solution.

[0073] According to other embodiments, an apparatus to analyze a liquid sample may comprise a dispensing unit configured to receive the liquid sample and dispense droplets of the liquid sample. The apparatus may also comprise a light source configured to emit light towards the droplets. Additionally, the apparatus may comprise a sensor configured to capture a returned tight from the droplets and transmit information associated with the captured light to a controller for generation of a spectral profile of the liquid sample based on the captured tight and analysis of the generated spectral profile to detect one or more substances in the liquid sample.

[0074] In some embodiments, die dispensing unit may include a single dispenser or an array of dispensers and may be one of a piezo-electric dispenser or a Joule heating dispenser. According to further embodiments, the dispensing unit may be configured to dispense die droplets with a diameter in a range from about 0.1 mm to about 0.3 mm or dispense droplets at a rate in a range from about 1 to about 10,000. In further embodiments, the tight source may be one of: a light emitting diode (LED), a halogen lamp, a fluorescent lamp, an incandescent lamp, or a laser source and may be configured to emit a monochromatic light or a polychromatic tight toward the droplets. In other examples, the tight source may also be configured to emit one of: a constant beam, one or more pulses of tight, or a pattern of light toward the droplets or produce light for emission with a wavelength in a range from about 200 nm to about 2000 nm. According to some embodiments, the apparatus may include two or more light sources. In some

embodiments, the apparatus may also include one or more of a lens, a filter, a condenser, a mirror, a grating, or a combination thereof.

[0675] According to further embodiments, the sensor may be one of a Complimentary Metal-Oxide-Semiconductor (CMOS) sensor, a Charge-Coupled Device (CCD) sensor a photodiode, an active-pixel sensor (APS), a Cadmium Zinc TeUuride radiation detector, a Mercury Cadmium Telluride detector, a reverse-biased light emitting diode (LED), a photoresistor, a phototransistor, or a quantum dot photoconductor. In other embodiments, the sensor may be positioned such that the returned light is captured at an angle of 42.5 degrees in reference to an external surface of the droplets

[0076] According to further examples, a system to analyze a liquid sample may comprise a dispensing unit configured to receive die liquid sample and dispense droplets of the liquid sample. The system may also comprise a light source configured to emit light towards the droplets and a sensor configured to capture a returned light from the droplets. The system may further comprise s controller. The controller may comprise a memory configured to store instructions and one or more processors coupled to the memory. The one or more processors may be configured to, in conjunction with the instructions stored on the memory, receive the captured light from the sensor, generate a spectral profile of the liquid sample based on the captured light, and analyze the generated spectral profile to detect one or more substances in the liquid sample.

[0077] In some examples, the one or more processors may be further configured to compare a pattern of the captured light of Ae generated spectral profile wiA one or more patterns of spectral profiles of oAer liquid samples stored in a database or one or more known patterns corresponding to particular properties of Ae liquid sample and determine a substance suspended in Ae liquid sample and a substance dissolved in Ae liquid sample based on the comparison. In further examples, Ae one or more processors may be configured to analyze the spectral profile to determine one or more quality parameters of Ae liquid sample from Ae generated spectral profile. The one or more quality parameters may include: a pH of the liquid sample, a turbidity of Ae liquid sample, a total organic carbon content of Ae liquid sample, or an electrical conductivity of the liquid sample. According to some examples, the one or more processors may be further configured to store the spectral profile of Ae liquid sample or store Ae determined substances suspended in Ae liquid sample, Ae determined substances dissolved in Ae liquid sample, and one or more determined quality parameter of the liquid sample in a database.

[0078] According to oAer examples, Ae one or more processors may be further configured to determine a spectrum of a pattern of Ae captured light, wherein Ae spectrum contains light of one or more wavelengths, determine an intensity of each of the one or more wavelengths in Ae spectrum, and generate the spectral profile of Ae liquid sample based on the comparison. In some examples, Ae one or more processors may be further configured to: in response to generating Ae spectral profile of Ae liquid sample, identify a property of Ae liquid sample to be further analyzed, determine an analysis parameter to analyze the identified property of die liquid sample, set the analysis parameter, perform the analysis of the liquid sample using the set analysis parameter, and analyze the captured light to quantify the identified property of the liquid sample. The analysis parameter may be one of a wavelength of the emitted light, a pattern of the emitted light, a diameter of the droplets, a rate the droplets are dispensed.

[0079] In further examples, the one or more processors may be farther configured to execute a calibration process and may do so in response to a failure to identify a known pattern or a spectral profile of another liquid sample at a database of spectral profiles. According to some examples, in order to perform the calibration process, the one or more processors may be configured to receive an analysis parameter, receive a value for the analysis parameter, and perform the analysis of the liquid sample using the value for analysis parameter. The analysis parameter may be one of a wavelength of the emitted light, a pattern of the emitted light, a diameter of the droplets, a rate the droplets are dispensed.

[0080] According to some examples, the dispenser, the light source, and the sensor may be integrated in an apparatus, and the controller may be communicatively coupled to the apparatus. In other examples, the dispensing unit may include a single dispenser or an array of dispensers and may be one of a piezo-electric dispenser or a Joule heating dispenser. In further examples, the dispensing unit may be configured to dispense the droplets with a diameter in a range from about 0.1 mm to about 0.3 mm or dispense droplets at a rate in a range from about 1 to about 10,000. According to other examples, the light source may be one of: a light emitting diode (LED), a halogen lamp, a fluorescent lamp, an incandescent lamp, or a laser source. In some examples, the light source may be configured to emit a monochromatic light or a polychromatic light toward the droplets, emit one of: a constant beam, one or more pulses of light, or a pattern of light toward the droplets, or produce light for emission with a wavelength in a range from about 200 nm to about 2000 nm. According to further examples, the system may include two or more light sources and may also include a lens, a filter, a condenser, a mirror, a grating, or a combination thereof. In some examples, the sensor may be one of a Complimentary Metal- Oxide-Semiconductor (CMOS) sensor, a Charge-Coupled Device (CCD) sensor a photodiode, an active-pixel sensor (APS), a Cadmium Zinc Teliuride radiation detector, a Mercury Cadmium Telluride detector, a reverse-biased light emitting diode (LED), a photoresistor, a phototransistor, or a quantum dot photoconductor. [0081] The foregoing detailed description has set forth various embodiments of foe devices and/or processes via the use of block diagrams, flowcharts, and/or examples. Insofar as such block diagrams, flowcharts, and/or examples contain one or more functions and/or operations, each function and/or operation within such block diagrams, flowcharts, or examples may be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. In one embodiment, several portions of foe subject matter described herein may be implemented via application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), or other integrated formats. However, some aspects of foe embodiments disclosed herein, in whole or in part, may be equivalently implemented in integrated circuits, as one or more computer programs executing on one or more computers (e.g., as one or more programs executing on one or more computer systems), as one or more programs executing on one or more processors (e.g., as one or more programs executing on one or more microprocessors), as firmware, or as virtually any combination thereof, and designing foe circuitry and/or writing foe code for the software and/or firmware would be possible in light of this disclosure.

[0082] The present disclosure is not to be limited in terms of foe particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations can be made without departing from its spirit and scope.

Functionally equivalent methods and apparatuses within foe scope of foe disclosure, in addition to those enumerated herein, are possible from foe foregoing descriptions. Such modifications and variations are intended to fell within foe scope of the appended claims. The present disclosure is to be limited only by the terms of foe appended claims, along with foe full scope of equivalents to which such claims are entitled. The terminology used herein is for foe purpose of describing particular embodiments only, and is not intended to be limiting.

[0083] in addition, the mechanisms of foe subject matter described herein are capable of being distributed as a program product in a variety of forms, and an illustrative embodiment of the subject ma tter described herein applies regardless of the particular type of signal bearing medium used to actually carry out the distribution. Examples of a signal bearing medium include, but are not limited to, the following: a recordable type medium such as a floppy disk, a hard disk drive (HDD), a compact disc (CD), a digital versatile disk (DVD), a digital tape, a computer memory, a solid state drive (SSD), etc.; and a transmission type medium such as a digital and/or an analog communication medium fe.g., a fiber optic cable, a waveguide, a wired communication link, a wireless communication link, etc.).

[0084] 'Chose skilled in the art will recognize that it is common within the art to describe devices and/or processes in the fashion set forth herein, and thereafter use engineering practices to integrate such described devices and/or processes into data processing systems. That is, at least a portion of the devices and/or processes described herein may be integrated into a data processing system via a reasonable amount of experimentation. A data processing system may include one or more of a system unit housing, a video display device, a memory such as volatile and non-volatile memory, processors such as microprocessors and digital signal processors, computational entities such as operating systems, drivers, graphical user interfeces, and applications programs, one or more interaction devices, such as a touch pad or screen, and/or control systems including feedback loops and control motors.

[0085] A data processing system may be implemented utilizing any suitable commercially available components, such as those found in data computing/communication and/or network eomputing/cpmmunication systems. The herein described subject matter sometimes illustrates different components contained within, or connected with, different other components. Such depicted architectures are merely exemplary, and in fact, many other architectures may be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively "associated” such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality may be seen as "associated with” each other such that the desired functionality is achieved, irrespective of architectures or intermediate components. Likewise, any two components so associated may also be viewed as being "operably connected”, or "operably coupled", to each other to achieve the desired functionality, and any two components capable of being so associated may also be viewed as being "operably couplable”, to each other to achieve the desired functionality. Specific examples of operably couplable include but are not limited to physically connectable and/or physically interacting components and/or wirelessly interactabie and/or wirelessly interacting components and/or logically interacting and/or logically interactabie components.

[0086] With respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from foe plural to the singular and/or from foe singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.

10087) In general, terms used herein, and especially in the appended claims (e.g, bodies of the appended claims) are generally intended as“open” terms (eg., the term“including” should be interpreted as“including but not limited to,” die term“having” should be interpreted as “having at least,” the term“includes” should be interpreted as“includes but is not limited to,” etc. ). If a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no, such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases "at least one" and "one or more" to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles "a" or "an" limits any particular claim containing such introduced claim recitation to embodiments containing only one such recitation, even when the same claim includes the introductory phrases "one or more" or "at least one" and indefinite articles such as "a" or "an" (e.g.,“a” and/or“an” should be interpreted to mean“at least one” or “one or mote"); the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize (hat such recitation should be interpreted to mean at least the recited number (e.g., the bare recitation of "two recitations," without other modifiers, means at least two recitations, or two or more recitations).

[0088] Furthermore, in those instances where a convention analogous to“at least one of A, B, and C, etc.” is used, in general, such a construction is intended in the sense one having skill in the art would understand the convention {e.g. ,“a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in foe description, claims, or drawings, should be understood to contemplate foe possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase“A or B" will be understood to include foe possibilities of “A” or“B” or“A and B." [0689] For any and all purposes, such as in terms of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof. Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, etc. As a non-limiting example, each targe discussed herein can be readily broken down into a lower third, middle third and upper third, etc. As will also be understood by one skilled in the art all language such as“up to,”“at least,”“greater than,”“less titan,” and the like include the number recited and refer to ranges which can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member. Thus, for example, a group having 1-3 cells refers to groups having 1 , 2, or 3 cells. Similarly, a group having 1 -5 cells refers to groups having 1 , 2, 3, 4, or 5 cells, and so forth.

[0090] While various aspects and embodiments ha ve been disclosed herein, other aspects and embodiments are possible. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

Claims

CLAIMS WHAT IS CLAIMED IS:

1. A method to analyze a liquid sample, the method comprising:

receiving the liquid sample;

dispensing dtqpletsof the liquid sample;

directing light toward the droplets;

capturing a returned light from the droplets;

generating a spectral profile of the liquid sample based on the captured light; and analyzing the generated spectral profile to detea one or more substances in the liquid sample.

2. The method of claim 1 , wherein analyzing the generated spectral profile to detect one or more substances in die liquid sample comprises:

comparing a pattern of the captured light of the generated spectral profile with one or more patterns of spectral profiles of other liquid samples stored in a database or one or more known patterns corresponding to particular properties of the liquid sample; and

determining one or more of a Substance suspended in the liquid sample and a substance dissolved in the liquid sample based on the comparison.

3. The method of claim 1 , wherein analyzing the generated spectral profile further comprises:

analyzing die generated spectral profile to determine one or more quality parameters of the liquid sample.

4. The method of claim 3, wherein the one or more quality parameters include: a pH of the liquid sample, a turbidity of the liquid sample, a total organic carbon content of the liquid sample, or an electrical conductivity of the liquid sample.

5. The method of claim 1, further comprising:

storing the spectral profile of the liquid sample.

6. The method of claim 2, further comprising:

storing the determined substances suspended in the liquid sample, the determined substances dissolved in the liquid sample, and one or more determined one or more quality parameters of the liquid sample in a database.

7. The method of claim 1 , wherein generating the spectral profile of the liquid sample

Comprises:

determining a spectrum of a pattern of the captured light, wherein the spectrum contains light of one or more wavelengths;

determining an intensity of each of the one or more wavelengths in the spectrum; and generating the spectral profile of the liquid sample based on the comparison.

8. The method of claim 7, wherein, in response to generating die spectral profile of tile liquid sample based on the comparison, further comprising:

identifying a property of the liquid sample to be further analyzed; determining an analysis parameter to analyze the identified property of die liquid sample, wherein the analysis parameter is one of a wavelength of the directed light, a pattern of the directed light, a diameter of the droplets, and a rate the droplets are dispensed;

setting the analysis parameter;

performing the analysis of die liquid sample using the set analysis parameter, and analyzing the captured light from die droplets to quantify the identified property of the liquid sample.

9. The method of claim 1, further comprising:

performing a calibration process.

10. The method Of claim 9, further comprising:

performing the calibration process in response to a failure to identify a known pattern or a spectral profile of another liquid sample at a database of spectral profiles.

11. The method of claim 9, wherein performing die calibration process comprises:

analyzing one or more liquid samples with and without known contaminants.

12. The method of claim 9, wherein the calibration process comprises :

selecting an analysis parameter;

setting the analysis parameter; and

performing the analysis of the liquid sample using the set analysis parameter.

13. The method of claim 12, wherein the analysis parameter is one of a wavelength of the directed light, a pattern of the directed light, a diameter of the droplets, or a rate the droplets are dispensed.

14. The method of claim I , wherein dispensing die droplets of die liquid sample comprises: dispensing droplets from a stogie microdispenser.

15. The method of claim I _v wherein dispensing the droplets of the liquid sample comprises: dispensing droplets from an array ofmicrodispensers.

16. The method of claim I , wherein dispensing the droplets of the liquid sample comprises: setting a parameter of a dispenser such that the droplets have a diameter in a range from about 0.1 mm to about 0.3 mm.

17. The method df claim 1, wherein dispensing the droplets of the liquid sample comprises: setting a parameter of a dispenser such that the droplets are dispensed at a rate in a range from about 1 to about 10,000.

18. The method of claim 1 , wherein directing the light toward the droplets comprises:

directing a monochromatic light or a polychromatic light toward the droplets.

19. The method of claim 1 , «hereto capturing the returned light from the droplets comprises; capturing the returned light at an angle of 42.5 degrees.

20. The method of claim I , wherein the returned light comprises: light reflected from an external surface of the droplets, light refracted within the droplets that is reflected from an internal surface of the droplets.

21. The method of claim 1 , «herein directing the light comprises:

emitting die light from one or more light sources.

22. The method of claim 1, wherein capturing die returned light comprises:

capturing the returned_: light through one or more sensors.

23. The method Of claim 1 , wherein the liquid sample is one of: potable water, a beverage, liquid medicine, a liquid fuel, or an industrial solution.

24. An apparatus to analyze a liquid sample, the apparatus comprising:

a dispensing unit configured to:

receive die liquid sample; and

dispense droplets of the liquid sample;

a light source configured to:

emit light towards the droplets; and

a sensor configured to:

capture a returned light from the droplets; and transmit information associated with the captured light to a controller for generation of a spectral profile of die liquid sample based on the captured light and analysis of the generated spectral profile to detect one or more substances in the liquid sample.

25. The apparatus of claim 24, wherein the dispensing unit comprises a single dispenser or an array of dispensers.

26. The apparatus of claim 24, wherein die dispensing unit is one of a piezo-electric dispenser or a Joule heating dispenser.

27. The apparatus of claim 24, wherein the dispensing unit is configured to:

dispense the droplets with a diameter in a range from about 0.1 mm to about 0.3 mm.

28. The apparatus of claim 24, wherein the dispensing unit is configured to:

dispense droplets at a rate in a range from about I to about 10,000.

29. The apparatus of claim 24, wherein die light source is one of a light emitting diode (LED), a halogen lamp, a fluorescent lamp, an incandescent lamp, or a laser source.

30. The apparatus of claim 24, wherein the apparatus comprises two or more light sources.

31. The apparatus of claim 24, wherein the light source is configured to:

emit a monochromatic light or a polychromatic light toward die droplets.

32. The apparatus of claim 24, wherein the apparatus further comprises one or more of a lens, a filter, a condenser, a mirror, a grating, or a combination thereof.

33. The apparatus of claim 24, wherein the light source is configured to:

emit one of: a constant beam, one or mote pulses of light, or a pattern of light toward the droplets.

34. The apparatus of claim 24, wherein die light source is configured to:

produce light for emission with a wavelength in a range from about 200 nm to about 2000 nm.

35. The apparatus of claim 24, wherein the sensor is one of a Complimentary Metal-Oxide-

Semiconductor (CMOS) sensor, a Charge-Coupled Device (CCD) sensor a photodiode, an active-pixel sensor (APS), a Cadmium Zinc Te!luride radiation detector, a Mercury Cadmium Telluride detector, a reverse-biased light emitting diode (LED), a photoresistor, a phototransistor, or a quantum dot photoconductor.

36. The apparatus of claim 24, wherein the sensor is positioned such that the returned light is captured at an angle of 42.5 degrees in reference to an external surface of the droplets.

37. A system to analyze a liquid sample, the system comprising:

a dispensing unit configured to: receive die liquid sample; and

dispense droplets of the liquid sample;

a light source configured to:

emit Tight towards the droplets; and

a sensor configured to:

capture a returned light from the droplets; and

a controller comprising:

a memory configured to store instructions; and

one or more processors coupled to the memory, wherein the one or more processors in conjunction with the instructions are configured to:

receive the captured light from the sensor;

generate a spectral profile of the liquid sample based on the captured light; and

analyze the generated spectral profile to detect one or more substances in the liquid sample.

38. The system of claim 37, wherein the one or more processors are further configured to:

compare a pattern of the captured light of the generated spectral profile with one or more patterns of spectral profiles of other liquid samples stored in a database or one or more known patterns corresponding to particular properties of the liquid sample; and

determine a substance suspended in the liquid sample and a substance dissolved in the liquid sample based on the comparison.

39. The system of claim 37, wherein the one or more processors are further configured to: analyze the spectral profile to determine one or more quality parameters of the liquid sample from the generated spectral profile.

40. The system of claim 39, wherein the one or more quality parameters include: a pH of the liquid sample, a turbidity of the liquid sample, a total organic carbon content of the liquid sample, or an electrical conductivity of die liquid sample.

41. The system of claim 37, wherein the one or more processors are further configured to: store the spectral profile of the liquid sample.

42. The system of claim 38, wherein the One or mom processors are further configured to: store the determined substances suspended in the liquid sample, the determined substances dissolved in the liquid sample, and one or more determined quality parameter of the liquid sample in a database.

43. The system of claim 37, wherein the one or more processors are further configured to: determine a spectrum of a pattern of the captured light, wherein the spectrum contains light of one or more wavelengths;

determine an intensity of each of the one or more wavelengths in the spectrum; and generate the spectral profile of die liquid sample based on die comparison.

44. The system of claim 43, wherein in response to generating the spectral profile of the liquid sample, the one or more processors are configured to:

identify a property of die liquid sample to be further analyzed;

determine an analysis parameter to analyze die identified property of the liquid sample, wherein the analysis parameter is one of a wavelength of die emitted light, a pattern of the emitted light, a diameter of the droplets, a rate the droplets are dispensed;

set the analysis parameter;

perform the analysis of die liquid sample using the set analysis parameter; and analyze die captured light to quantify die identified property of the liquid sample.

45. The system of claim 37, wherein the one or more processors are further configured to: execute a calibration process.

46. The system of claim 45, wherein the one or more processors are further configured to: execute the calibration process in response to a failure to identify a known pattern or a spectral profile of another liquid sample at a database of spectral profiles.

47. The system of claim 45, wherein to perform (he calibration process, the one or more processors are configured to:

receive an analysis parameter;

receive a value for die analysis parameter; and

perform the analysis of the liquid sample using the value for analysis parameter.

48. The system of claim 47, wherein the analysis parameter is one of a wavelength of the emitted light, a pattern of the emitted light, a diameter of the droplets, or a rate the droplets are dispensed.

49. The system of claim 37, wherein the dispenser, the light source, and die sensor are integrated in an apparatus and the controller is communicatively coupled to the apparatus.

50. The system of claim 37, wherein the dispensing unit comprises a single dispenser or an array of dispensers.

51. The system of claim 37, wherein the dispensing unit is one of a piezo-electric dispenser or a

Joule heating dispenser.

52. The system of claim 37, wherein the dispensing unit is configured to:

dispense the droplets with a diameter in a range from about 0.1 nun to about 0.3 mm.

53. The system of claim 37, wherein the dispensing unit is configured to:

dispense droplets at a rate in a range from about 1 to about 10,000.

54. The system of claim 37, wherein die light source is one of: a light emitting diode (LED), a halogen lamp, a fluorescent lamp, an incandescent lamp, or a laser source.

55. The system of claim 37, wherein the system comprises two or more light sources.

56. The system of claim 37, wherein the light source is configured to:

emit a monochromatic light or a polychromatic light toward the droplets.

57. The system of claim 37, wherein the system further comprises one or more of a lens, a filter, a condenser, a mirror, a grating, or a combination thereof.

58. The system of claim 37, wherein the light source is configured to:

«nit one of: a constant beam, one or more pulses of light, or a pattern of light toward the droplets.

59. The system of claim 37, wherein the light source is configured to:

60. The system of claim 37, wherein the sensor is one of a Complimentary Metal-Oxide-

Semiconductor (CMOS) sensor, a Charge-Coupled Device (CCD) sensor a photodiode, an active-pixel sensor (APS), a Cadmium Zinc Telluride radiation detector, a Mercury Cadmium

Telluride detector, a reverse-biased light emitting diode (LED), a photoresistor, a phototransistor, or a quantum dot photoconductor.