AU2020100714A4 - Device and method for detecting a substance contained in a sample - Google Patents

Abstract

There is provided a device for detecting a substance contained in a sample. The device may comprise a substrate; and a layer of metal nanoparticles attached to the substrate. The layer of metal nanoparticles is configured to, if the sample is applied to the layer of metal nanoparticles, enhance Raman scattering caused by the substance contained in the sample in order to detect the substance contained in the sample. Fig. 1

Description

DEVICE AND METHOD FOR DETECTING A SUBSTANCE CONTAINED IN A SAMPLE

Technical Field

[1] The present invention relates to detection of a substance, and in particular, relates to a device and method for detecting a substance contained in a sample based on Raman spectroscopy.

Background

[2] It is desired to detect existence of certain substances in many industries, for example, public security, law enforcement, border control, medical treatment, laboratory analysis, environmental protection, drug detection, etc. As an example, police may need to detect a series of drugs such as heroin, ***e, fentanyl, codeine, methamphetamine, amphetamine sulfate, aspirin, and melamine when patrolling streets. Scientists may need to detect a water pollutant from a water sample collected from a water source, or an air pollutant from an air sample. In hemp growing industry, government agencies or growers may need to detect the level of cannabidiol (CBD) and tetrahydrocannabinol (THC) in the hemp being grown to make sure the levels of CBD and THC in the hemp comply with legal requirements. After the legalisation of industrial hemp cultivation, hemp products have been used to produce a variety of commercial and industrial products such as hemp food and other derivatives. There are over 420 chemicals including at least 61 cannabinoids in the hemp plant. Among these cannabinoids compounds, A9-Tetrahydrocannabinol (THC) is the most psychoactive component, other major constituent cannabidiol (CBD) has been proven to treat epilepsy and other medicinal benefits. Both CBD and THC have the same molecular structure formula, however, a slight difference in how the atoms are arranged accounts for the different effects on our body.

[3] Among various detection techniques, Raman spectroscopy has become increasingly important in substance detection. This technology uses Raman spectral information to identify (i.e., detect the existence of a substance) and quantify (i.e., determine the level of the substance) the substance in a sample. However, the intensity of Raman spectral signal obtained from most of the systems is very weak, so additional expensive equipment is required to process these weak Raman signals. As a result, the existing Raman spectral detection technologies are time-consuming and not cost-efficient. Also, detection accuracy and detection limit are problematic.

[4] Therefore, there is a need for a device and method capable of rapidly and accurately detecting the existence and/or level of one or more substances in a sample. The device and method need to be sensitive to those substances in order to provide a wide detection range.

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[5] Any discussion of the background art throughout the specification should in no way be considered as an admission that such background art is prior art nor that such background art is widely known or forms part of the common general knowledge in the field in Australia or worldwide.

Summary of the invention

[6] The present invention is described hereinafter by various embodiments. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, the embodiments are provided so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those skilled in the art.

[7] There is provided a device for detecting a substance contained in a sample, the device comprising:

a substrate; and a layer of metal nanoparticles attached to the substrate, the layer of metal nanoparticles being configured to, if the sample is applied to the layer of metal nanoparticles, enhance Raman scattering caused by the substance contained in the sample in order to detect the substance contained in the sample.

[8] The substrate may be one of a group of materials including: filter paper, low ash filter paper, aluminium film, graphene film.

[9] The layer of metal nanoparticles may include one of a group of materials including: gold nanoparticles, silver nanoparticles, and copper nanoparticles.

[10] The metal nanoparticles may have a diameter ranging from 5 nanometres (nm) to lOOnm.

[U] The diameter may be one of 5nm, 13nm, and 45nm.

[12] The sample may be a liquid sample.

[13] The liquid sample may be a solution sample, and the substance may be one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) in the solution sample, or a mixture of the cannabinoids.

[14] The liquid sample may be a juice sample extracted from one of cannabis plants including hemp and marijuana. The substance may be one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) contained in the juice sample, or a mixture of the cannabinoids.

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[15] The liquid sample may be a saliva sample, and the substance may include one of a group of drugs contained in the saliva sample, including heroin, ***e, fentanyl, codeine, methamphetamine, amphetamine sulfate, aspirin, and melamine.

[16] The liquid sample may be a water sample. The substance may include a water pollutant contained in the water sample.

[17] The sample may be an air sample, and the substance may include an air pollutant contained in the air sample.

[18] There is provided a method for detecting a substance contained in a sample, the method comprising:

applying the sample to a device as described above in order to enhance Raman scattering caused by the substance contained in the sample;

scanning the sample with a laser beam to obtain a Raman spectrum for the sample, the Raman spectrum indicating scattering intensities of the laser beam by the substance; and identifying the substance contained in the sample based on the Raman spectrum.

[19] The laser beam may have a wavelength of one of a group of wavelengths including 514nm, 633nm, 785nm, and 1064nm.

[20] The method may further comprise: determining a concentration of the substance in the sample based on the scattering intensities indicated in the Raman spectrum.

[21] The sample may be a juice sample extracted from one of cannabis plants including hemp and marijuana, or a solution sample. The substance may be one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) contained in the sample. The method may further comprise:

if there is a first peak at 1007cm’¹ in the Raman spectrum, determining a first scattering intensity of the first peak at 1007cm’¹;

if there is a second peak at 1589cm’¹ in the Raman spectrum, determining a second scattering intensity of the second peak at 1589cm’¹;

determining a ratio of the first scattering intensity to the second scattering intensity;

if the ratio is in a range from 0.62 to 1.02, identifying the substance as CBD; and if the ratio is in a range from 1.91 to 2.51, identifying the substance as THC.

[22] Determining the concentration of CBD or THC may comprise determining the concentration of CBD or THC based on the first scattering intensity at 1007cm’¹.

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[23] The sample may be a saliva sample, and the substance may include one of a group of drugs contained in the saliva sample, including heroin, ***e, fentanyl, codeine, methamphetamine, amphetamine sulfate, aspirin, and melamine. The method may further comprise:

if there is a peak between 625cm’¹ and 628cm’¹ in the Raman spectrum, identifying the substance as heroin;

if there are peaks at 1714cm’¹, 1597cm’¹, 1003 cm’¹ in the Raman spectrum, identifying the substance as ***e;

if there are peaks at 1620cm’¹, 1005cm’¹, 830cm’¹ in the Raman spectrum, identifying the substance as codeine;

if there are peaks at 1578cm’¹, 998cm’¹ in the Raman spectrum, identifying the substance as methamphetamine;

if there are peaks at 1030cm’¹,1003cm’¹, 970cm’¹ in the Raman spectrum, identifying the substance as amphetamine sulfate;

if there are peaks at 1665cm’¹,1080cm’¹, 900cm’¹, 500cm’¹ in the Raman spectrum, identifying the substance as aspirin; and if there is a peak at 695cm’¹ in the Raman spectrum, identifying the substance as melamine.

[24] Throughout this specification, unless the context requires otherwise, the words “comprise”, “comprises” and “comprising” will be understood to imply the inclusion of a stated step or element or group of steps or elements but not the exclusion of any other step or element or group of steps or elements.

[25] Any one of the terms: “including” or “which includes” or “that includes” as used herein is also an open term that also means including at least the elements/features that follow the term, but not excluding others.

Brief Description of Drawings

[26] At least one example of the present invention will be described with reference to the accompanying drawings, in which:

Fig. 1 illustrates an example device for detecting a substance contained in a sample in accordance with an embodiment of the present disclosure;

Fig. 2 illustrates a Raman spectrum by a low ash filter paper in accordance with an embodiment of the present disclosure;

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Figs. 3(A) to 3(C) illustrate Transmission Electron Microscopy (TEM) images of resulting AuNPs of different sizes in accordance with an embodiment of the present disclosure;

Fig. 4 illustrates a Raman scattering spectrum by the device in accordance with an embodiment of the present disclosure;

Fig. 5 illustrates an example method for detecting a substance contained in a sample in accordance with an embodiment of the present disclosure;

Fig. 6A illustrates an averaged Raman spectrum obtained from a sample containing CBD using the device in accordance with an embodiment of the present disclosure;

Fig. 6B illustrates an averaged Raman spectrum obtained from a sample containing THC using the device in accordance with an embodiment of the present disclosure; and

Fig. 7 illustrates calibration curves to determine concentrations of CBD and/or THC based on scattering intensities in accordance with an embodiment of the present disclosure.

[27] It should be noted in the accompanying drawings and description below that like or the same reference numerals in different drawings denote the same or similar elements.

Description of Embodiments

Structure of the device

[28] Fig. 1 illustrates an example device 100 for detecting a substance contained in a sample in accordance with an embodiment of the present disclosure.

[29] As shown in Fig. 1, the example device 100 includes a substrate 101 and a layer of metal nanoparticles 102 attached to the substrate 101. The layer of metal nanoparticles 102 is visible in a partial enlarged view 103 in Fig. 1. The substrate 101 of the example device 100 is in a round shape with a diameter of 5 millimetres (mm) (φ=5 mm). The layer of metal nanoparticles 102 is configured to enhance Raman scattering caused by the substance (not shown) contained in the sample (not shown) in order to detect the substance contained in the sample if the sample is applied to the device 100, particularly, the layer of metal nanoparticles 102.

[30] In one embodiment, the sample is a liquid sample such as a juice sample extracted from one of cannabis plants including hemp and marijuana. In this case, the substance is one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) contained in the juice sample, or a mixture of the cannabinoids.

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[31] The liquid sample can be a solution sample. For example, the solution sample contains one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) to be detected, or a mixture of the cannabinoids.

[32] The liquid sample can also be a saliva sample collected from a person under test by for example police and the substance to be detected can include one of a group of drugs contained in the saliva sample, including heroin, ***e, fentanyl, codeine, methamphetamine, amphetamine sulfate, aspirin, and melamine.

[33] The liquid sample can be a water sample collected from a water source, for example, a river, a creek, a water tank, a water tap, etc. The substance to be detected can include a water pollutant contained in the water sample.

[34] In another embodiment, the sample is an air sample collected from atmosphere. The substance to be detected can include an air pollutant contained in the air sample.

[35] The device 100 is now descried below in detail with reference to detection of CBD and THC in hemp. However, it should be noted that the device 100 can also be used to detect other substances as set out above.

[36] Fig. 1 includes a partial enlarged view 103 of the device 100. The partial enlarged view 103 shows that the substrate 101 of the device 100 is configured to carry the layer of metal nanoparticles 102 in order to provide physical support for the layer of metal nanoparticles 102. Theoretically, the substrate 101 can be made of different materials, including, but not limited to, filter paper, low ash filter paper, aluminium film, graphene film, etc., as long as the substrate 101 does not have obvious Raman effect (or Raman scattering peak) that will affect the detection result. In practice, the choice of the material for the substrate 101 needs to be cost-efficient for mass production. Further, in addition to just being physically supported by the substrate 101, the layer of metal nanoparticles 102 is attached or bonded (as shown in the partial enlarged view 103) to the substrate 101 to ensure structural integrity of the device 100.

[37] Among the multiple choices of the material for the substrate 101, a qualitative low ash filter paper is cost-efficient for mass production. It is also chemically stable when used with the substance(s) under detection. The low ash filter paper is porous, which does not only provide physical support for metal nanoparticles in the layer of metal nanoparticles 102 but also makes it easy to attach or bond the metal nanoparticles to the low ash filter paper during the manufacturing

2020100714 05 May 2020 process as described below in order to provide strong local plasmonic to enhance the Raman scattering signals.

[38] Fig. 2 illustrates a Raman spectrum 200 by the low ash filter paper (φ=5 mm) in accordance with an embodiment of the present disclosure. As shown in Fig. 2, the low ash filter paper does not have obvious Raman effects (or Raman scattering peaks) that will affect the detection result. Therefore, the substrate 101 in the present disclosure is described with reference to the low ash filter paper. It should also be noted that although Raman spectrums illustrated in Fig. 2 and other drawings throughout the present disclosure show the Raman frequency shifts between 500cm’¹ to 2000cm’¹, the present disclosure is also applicable to other frequency shifts.

[39] The layer of metal nanoparticles 102 can be made of one of a group of materials including: gold nanoparticles, silver nanoparticles, copper nanoparticles, etc., as long as the layer of metal nanoparticles 102 is able to enhance Raman scattering caused by the substance contained in the sample. However, due to better chemical stability of gold (for example, gold does not tend to be oxidised over time, which results in the consistent performance of the device 100 over a long period of time), the layer of metal nanoparticles 102 in the present disclosure is described with reference to a gold nanoparticles layer.

Manufacturing process of the device

[40] An example manufacturing process of the device 100 is described below in accordance with an embodiment of the present disclosure. In other embodiments, other manufacturing processes may be adopted to make the device 100 without departing from the scope of the present disclosure.

[41] The layer of gold nanoparticles 102 includes gold nanoparticles (AuNPs), which are small gold particles with a certain diameter, for example, 5 nanometres (nm) to lOOnm. In the present disclosure, there are different options for the size (i.e., diameter) of the gold nanoparticles, including 5nm, 13nm, and 45nm. Experiment results indicate that AuNPs with a diameter of 45nm achieves the highest detection limit and the optimal linear detection range possibly due to the curvature of the nanoparticles.

[42] AuNPs with a diameter of 5nm, 13nm or 45nm are synthesized from HAuCU by a chemical reduction method in the present disclosure. For example, in order to produce 5nm AuNPs, 1 mL of 1 wt% HAuCU -3H2O is added to 90 mL of deionized water. After 1 min of stirring, 2 mL of 38.8 mM sodium citrate is added and then stirred for one more minute. 1 mL of fresh 0.075 wt%

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NaBEL in 38.8 mM sodium citrate is slowly added and stirred for another 5 min. As for the AuNPs with a diameter of 13nm or 45nm, 1 mL of 5 mM HAuCL GHzO solution is added to 18 mL deionized water under stirring and heating until boiling. Then, 0.5% w/w sodium citrate as the reducing agent is added to reduce the Au³⁺ to Au° by heating and stirring until the colour change is evident. By varying the amount of sodium citrate (1mL or 0.365 mL), AuNPs with a diameter of 13nm or 45 nm are synthesized, respectively. The final solution is topped up to 20 mL and the final concentration of the prepared gold colloid is approximately 0.25 mM. The fresh prepared GNPs are carefully washed three times through a centrifuge for 10 mins at 5000 rpm to remove the abundant sodium citrate. Figs. 3(A), 3(B), and (3C) illustrate the Transmission Electron Microscopy (TEM) images 300 of the resulting AuNPs of different sizes in accordance with an embodiment of the present disclosure. Fig. 3(A) shows an image 300 of 5nm AuNPs (scale bar: 20nm), Fig. 3(B) shows an image 302 of 13nm AuNPs (scale bar: 20nm), and Fig. 3(C) shows an image 304 of 45nm AuNPs (scale bar: 50nm). As shown in Figs. 3(A), 3(B), and (3C), the AuNPs are approximately spherical and are well monodisperse.

[43] Attaching or binding AuNPs to the surface of the substrate 101, i.e., the low ash filter paper 101 in this embodiment, is achieved by using a centrifugal spinning method. After removing the sodium citrate with the centrifuge as described above, AuNPs are then applied on the surface of the low ash filter paper with a spinning coating machine in order to be attached or bound to the surface of the low ash filter 102, as shown in the view 103 of Fig. 1. The AuNPs are well dispersed on the surface of the low ash filter paper 102. The amount of AuNPs used in the device 100 ranges from as low as 5 microliters (ul), lOul, 20ul to as much as 50ul, lOOul, which will greatly contribute to the background noise and enhancement factor. The background noise resulting from the AuNPs increases with the increase in the amount of AuNPs applied on the low ash filter paper 102 due to the aggregation effect. However, a lower amount of AuNPs is not able to generate enough local plasmon for Raman scattering signal enhancement. A series of tests indicate that when 10 ul and 20ul AuNPs are applied, the low ash filter paper 101 demonstrates the optimal background noise and enhancement factor if used to detect CBD or THC in hemp.

[44] It is noteworthy that the Raman effect of the device 100 itself should not substantially affect the detection result when it is used with the sample containing the substance under detection. This means the Raman scattering spectrum resulting from the device 100 without the sample needs to meet a certain pattern. Fig. 4 illustrates a Raman scattering spectrum 400 by the device 100 in accordance with an embodiment of the present disclosure. As shown in Fig. 4, there are five main peaks located at 1176cm’¹, 1255cm’¹, 1305cm’¹, 1478cm’¹ and 1502cm’¹ in the Raman spectrum

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400. This indicates that the AuNPs are properly attached or bonded to the surface of the low ash filter paper 101 and the layer of the gold nanoparticles 102 is formed properly. During an actual test, the sample containing the substance is applied to the device 100, and these five peaks will also appear in the Raman scattering spectrum of the device 100 with the sample applied thereto, but these peaks are removed before further analysis, or are excluded from detecting the substance because the five peaks are caused by the device 100 itself, not by the substance.

[45] Regarding the excitation light source used with the device 100, laser sources of different wavelengths 514nm, 633nm, 785nm, and 1064nm have been compared for performance assessment purposes because the wavelength of the laser is important in acquisition of accurate spectroscopic data. The Raman effect is directly proportional to the power of the light source. However, a shorter wavelength may have much higher fluorescence that can drown out the Raman scattering signals. Having compared the scattering intensity from the device 100 without the sample containing the substance (for example, CBD or THC) and the scattering intensity from the device 100 with the sample applied, the laser source with a wavelength of 633nm and 785nm presents a wide range of detection limits and stable Raman scattering signals. The Raman scattering spectrum provided in the present disclosure is obtained with a 633nm laser source.

Detection method

[46] Fig. 5 illustrates an example method 500 for detecting a substance contained in a sample in accordance with an embodiment of the present disclosure.

[47] During the use of the device 100 or its manufacturing process, a user (for example, a researcher, an engineer, a scientist, an analyst, etc.) who conducts the detection (for example, an actual drug detection on the site or in the lab) or tests the device 100 (for example, for quality control purposes during manufacturing) applies 501 a sample containing one or more substances to the device 100, particular, the layer of metal nanoparticles 102. In this embodiment, the sample can be a liquid sample, particularly, a juice sample. The juice sample is extracted from one of cannabis plants including hemp and marijuana. The juice sample contains one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC), or a mixture of the cannabinoids, which needs to be detected with the device 100.

[48] In another embodiment, the liquid sample is a solution sample that contains one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC), or a mixture of the cannabinoids. The solution sample contains a predetermined level of CBD and/or THC. It can be ίο

2020100714 05 May 2020 used to assess the performance of the device 100. That is, if the level of CBD and/or THC detected with the device 100 is substantially identical with the predetermined level, it means the detection result by using the device 100 is accurate.

[49] A laser source is used by the user to project a laser beam with a certain wavelength (for example, 633nm in the present disclosure) to scan 503 the sample applied on the layer of gold nanoparticles 102. As described above, the layer of gold nanoparticles 102 enhances Raman scattering caused by the substance, i.e., CBD or THC, contained in the sample. The laser source may be part of a Raman spectrometer. In other embodiments, the laser beam can have a different wavelength, for example, 514nm, 785nm, or 1064nm.

[50] The laser beam provides different scan areas, for example, 1^χ1 micrometre (um), lOumxlOum, 20^x20um, and 50^x50um. The laser beam scans the sample with a preset step size, for example, O.lum, lum, lOum, 20um, to produce Raman scattering signals. The Raman spectrometer receives the Raman scattering signals from the device 100 to obtain a Raman spectrum. The Raman spectrum indicates scattering intensities of the laser beam by the substance in the sample. Based on the experimental results, in terms of detection results and acquisition time, a scan area of 50^x50um with a step size of lOum provide a better performance.

[51] The sample can be scanned by the laser beam multiple times in order to obtain an averaged Raman spectrum. In one embodiment, the sample is scanned 25 times, resulting in 25 individual Raman spectrums. The 25 Raman spectrums are averaged to determine an averaged Raman spectrum in order to detect the substance in the sample. This way, the detection accuracy is not substantially affected by any one of the individual Raman spectrums, which leads to a better performance.

[52] The method 500 then identifies 505 the substance contained in the sample based on the Raman spectrum or averaged Raman spectrum. Examples of identifying a substance contained in a sample are described in detail below with reference to Fig. 6A and Fig. 6B. In the examples, the sample can be a juice sample extracted from one of cannabis plants including hemp and marijuana. The sample can also be a solution sample. The substance can be one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) contained in the sample or a mixture of the cannabinoids.

[53] Fig. 6A illustrates an averaged Raman spectrum 600 obtained from a sample containing CBD using the device 100 in accordance with an embodiment of the present disclosure. With the

2020100714 05 May 2020 background noise removed, as shown in Fig. 6A, there are two dominating peaks located at lOOTcm’¹ and 1589cm·¹, which can be attributed to the C-C stretching and C=C stretching respectively in the CBD molecules.

[54] Fig. 6B illustrates an averaged Raman spectrum 601 obtained from a sample containing THC using the device 100 in accordance with an embodiment of the present disclosure. As shown in Fig. 6B, there are also two dominating peaks located at 1007cm’¹ and 1589cm’¹, which can be attributed to the C-C stretching and C=C stretching respectively in the THC molecules.

[55] The molecule of CBD has the same chemical formula as that of THC, but the atoms are arranged differently. Although the locations of the peaks in the Raman spectrum in Fig. 6A are substantially the same as those in the spectrum shown in Fig. 6B, the scattering intensities at these those peaks are different. This indicates different vibrational intensities of C-C stretching and C=C stretching occurring in the CBD and THC molecules. From the optimized geometries, the structure of the CBD molecule has one more C=C bond and an intermolecular hydrogen bond, while the structure of the THC molecule has an ether bond instead. The hydrogen of the phenol moiety of CBD has a great electronic repulsion with the methylcyclohexene ring due to the difference in polarity. As a result, different Raman scattering intensities are observed for CBD and THC even at the substantially same concentration (200 ppm in the example shown in Fig. 6A and Fig. 6B). Therefore, an intensity ratio (Ic-c/Ic=c) is used in the present disclosure to identify the substance in the sample, i.e., to determine if the substance in the sample is CBD (Ic-c/Ic=c = 0.82 ± 0.2) or THC (I_C-c/Ic=c= 2.21 ± 0.3).

[56] Specifically, when analysing a Raman spectrum obtained from a sample containing CBD or THC, if there is a first peak at 1007cm’¹ in the Raman spectrum, the method determines a first scattering intensity (i.e., Ic-c) of the first peak at 1007cm’¹, which is caused by the C-C stretching. Further, if there is a second peak at 1589cm’¹ in the Raman spectrum, the method determines a second scattering intensity (i.e., Ic=c) of the second peak at 1589cm’¹, which is caused by the C=C stretching. The method then determines a ratio (i.e., Ic-c/Ic=c) of the first scattering intensity Ic-c to the second scattering intensity Ic=c. If the ratio Ic-c/Ic=c is in a range 0.82 ± 0.2, i.e., from 0.62 to 1.02, then the method identifies the substance in the sample as CBD. If the ratio Ic-c/Ic=c is in a range 2.21 ± 0.3, i.e., from 1.91 to 2.51, then the method identifies the substance in the sample as THC.

[57] In other embodiments, the method 500 can detect substances other than CBD or THC. For example, the sample can be a saliva sample, and the substance includes one of a group of drugs

2020100714 05 May 2020 contained in the saliva sample. The substance includes heroin, ***e, fentanyl, codeine, methamphetamine, amphetamine sulfate, aspirin, and melamine. In the Raman spectrum obtained from the sample using the device 100, if there is a peak between 625cm’¹ and 628cm’¹ in the Raman spectrum, the method 500 identifies the substance as heroin. If there are peaks at 1714cm’¹, 1597cm’¹, 1003cm’¹ in the Raman spectrum, the method 500 identifies the substance as ***e. If there are peaks at 1620cm’¹, 1005cm’¹, 830cm’¹ in the Raman spectrum, the method 500 identifies the substance as codeine. If there are peaks at 1578cm’¹, 998cm’¹ in the Raman spectrum, the method 500 identifies the substance as methamphetamine. If there are peaks at 1030cm’¹, 1003 cm’¹, 970cm’¹ in the Raman spectrum, the method 500 identifies the substance as amphetamine sulfate. If there are peaks at 1665cm’¹, 1080cm’¹, 900cm’¹, 500cm’¹ in the Raman spectrum, the method 500 identifies the substance as aspirin. If there is a peak at 695 cm’¹ in the Raman spectrum, the method 500 identifies the substance as melamine.

[58] In other embodiments, the method 500 can detect the concentration of the substance in the sample based on the scattering intensities indicated in the Raman spectrum. Fig. 7 illustrates calibration curves 700 to determine concentrations of CBD and/or THC based on the scattering intensities in accordance with an embodiment of the present disclosure. As shown in Fig. 7, reference points for CBD concentration detection at different predetermined concentrations (particularly, lOppm, 50ppm, lOOppm, 200ppm, 500ppm and lOOOppm) are denoted by squares. These CBD reference points indicates reference scattering intensities caused by the C-C stretching in CBD molecules at the predetermined concentrations. That is, the reference scattering intensities are the scattering intensities of the first peak at 1007cm’¹, i.e., Ic-c, in the Raman spectrum. For example, the reference CBD scattering intensity (i.e., Ic-c) is about 125 at 200ppm, about 750 at lOOOppm, etc. The CBD calibration curve is generated based on the CBD reference points by for example curve fitting technologies. Although the CBD calibration curve is shown as a line (linear correlation coefficient = 0.9949) in Fig. 7, it can be other curves without departing from the scope of the invention.

[59] To determine the concentration of CBD in a sample under investigation, a Raman scattering spectrum of the sample is obtained via a Raman spectrometer, as described above. The scattering intensity of the first peak at 1007cm’¹ (i.e., Ic-c) is then determined from Raman scattering spectrum. The concentration of the CBD in the sample can be determined from the CBD calibration curve, which is the concentration corresponding to the scattering intensity on the CBD calibration curve. The linear detection range for CBD (linear correlation coefficient = 0.9949) is from 10 ppm to 1000 ppm.

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[60] Similarly, as shown in Fig. 7, reference points for THC concentration detection at different predetermined concentrations (particularly, lOppm, 50ppm, lOOppm, 200ppm, 500ppm and lOOOppm) are denoted by dots. These THC reference points indicates reference scattering intensities caused by the C-C stretching in THC molecules at the predetermined concentrations. That is, the reference scattering intensities are the scattering intensities of the first peak at 1007cm’ i.e., Ic-c, in the Raman spectrum. For example, the reference THC scattering intensity (i.e., Ic-c) is about 375 at 200ppm, about 1500 at lOOOppm, etc. The THC calibration curve is generated based on the THC reference points by for example curve fitting technologies. Although the THC calibration curve is shown as a line (linear correlation coefficient = 0.9952) in Fig. 7, it can be other curves without departing from the scope of the invention.

[61] To determine the concentration of THC in a sample under investigation, a Raman scattering spectrum of the sample is obtained via a Raman spectrometer, as described above. The scattering intensity of the first peak at 1007cm’¹ (i.e., Ic-c) is then determined from Raman scattering spectrum. The concentration of the THC in the sample can be determined from the THC calibration curve, which is the concentration corresponding to the scattering intensity on the THC calibration curve. The linear detection range for THC (linear correlation coefficient = 0.9952) is from 6ppm to lOOOppm.

[62] It should be understood that the techniques of the present disclosure might be implemented using a variety of technologies. For example, the methods described herein may be implemented by a series of computer executable instructions residing on a suitable computer readable medium. Suitable computer readable media may include volatile (e.g. RAM) and/or non-volatile (e.g. ROM, disk) memory, carrier waves and transmission media. Exemplary carrier waves may take the form of electrical, electromagnetic or optical signals conveying digital data steams along a local network or a publicly accessible network such as the Internet.

[63] It should also be understood that, unless specifically stated otherwise as apparent from the following discussion, it is appreciated that throughout the description, when the methods described herein are implemented by a series of computer executable instructions residing on a suitable computer readable medium, discussions utilizing terms such as controlling or obtaining or computing or storing or receiving or determining or the like, refer to the action and processes of a computer system, or similar electronic computing device, that processes and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display

2020100714 05 May 2020 devices. The terms and descriptions used herein are set forth by way of illustration only and are not meant as limitations. Examples and limitations disclosed herein are intended to be not limiting in any manner, and modifications may be made without departing from the spirit of the present disclosure. Those skilled in the art will recognize that many variations are possible within the spirit and scope of the disclosure, and their equivalents, in which all terms are to be understood in their broadest possible sense unless otherwise indicated.

[64] Various modifications to these embodiments are apparent to those skilled in the art from the description and the accompanying drawings. The principles associated with the various embodiments described herein may be applied to other embodiments. Therefore, the description is not intended to be limited to the embodiments shown along with the accompanying drawings but is meant to provide the broadest scope, consistent with the principles and the novel and inventive features disclosed or suggested herein. Accordingly, the disclosure is anticipated to hold on to all other such alternatives, modifications, and variations that fall within the scope of the present disclosure and appended claims.

Claims (17)

1. Claims

   1. A device for detecting a substance contained in a sample, the device comprising:

   a substrate; and a layer of metal nanoparticles attached to the substrate, the layer of metal nanoparticles being configured to, if the sample is applied to the layer of metal nanoparticles, enhance Raman scattering caused by the substance contained in the sample in order to detect the substance contained in the sample.
2. 2. The device of claim 1, wherein the substrate is one of a group of materials including: filter paper, low ash filter paper, aluminium film, graphene film.
3. 3. The device of claim 1 or 2, wherein the layer of metal nanoparticles includes one of a group of materials including: gold nanoparticles, silver nanoparticles, and copper nanoparticles.
4. 4. The device of any one of preceding claims, wherein the metal nanoparticles have a diameter ranging from 5 nanometers (nm) to lOOnm.
5. 5. The device of claim 4, wherein the diameter is one of 5nm, 13nm, and 45nm.
6. 6. The device of any one of the preceding claims, wherein the sample is a liquid sample.
7. 7. The device of claim 6, wherein the liquid sample is a solution sample, and the substance is one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) in the solution sample, or a mixture of the cannabinoids.
8. 8. The device of claim 6, wherein the liquid sample is a juice sample extracted from one of cannabis plants including hemp and marijuana, and the substance is one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) contained in the juice sample, or a mixture of the cannabinoids.
9. 9. The device of claim 6, wherein the liquid sample is a saliva sample, and the substance includes one of a group of drugs contained in the saliva sample, including heroin, ***e, fentanyl, codeine, methamphetamine, amphetamine sulfate, aspirin, and melamine.

   2020100714 05 May 2020
10. 10. The device of claim 6, wherein the liquid sample is a water sample, and the substance includes a water pollutant contained in the water sample.
11. 11. The device of any one of claims 1 to 5, wherein the sample is an air sample, and the substance includes an air pollutant contained in the air sample.
12. 12. A method for detecting a substance contained in a sample, the method comprising:

    applying the sample to a device of any one of claims 1 to 11 in order to enhance Raman scattering caused by the substance contained in the sample;

    scanning the sample with a laser beam to obtain a Raman spectrum for the sample, the Raman spectrum indicating scattering intensities of the laser beam by the substance; and identifying the substance contained in the sample based on the Raman spectrum.
13. 13. The method of claim 12, wherein the laser beam has a wavelength of one of a group of wavelengths including 514nm, 633nm, 785nm, and 1064nm.
14. 14. The method of claim 12 or 13, further comprising: determining a concentration of the substance in the sample based on the scattering intensities indicated in the Raman spectrum.
15. 15. The method of any one of claims 11 to 14, wherein the sample is a juice sample extracted from one of cannabis plants including hemp and marijuana, or a solution sample, and the substance is one of cannabinoids including cannabidiol (CBD) and tetrahydrocannabinol (THC) contained in the sample, the method further comprising:

    if there is a first peak at 1007cm¹ in the Raman spectrum, determining a first scattering intensity of the first peak at 1007cm¹;

    if there is a second peak at 1589cm¹ in the Raman spectrum, determining a second scattering intensity of the second peak at 1589cm¹;

    determining a ratio of the first scattering intensity to the second scattering intensity;

    if the ratio is in a range from 0.62 to 1.02, identifying the substance as CBD; and if the ratio is in a range from 1.91 to 2.51, identifying the substance as THC.
16. 16. The method of claim 14, wherein determining the concentration of CBD or THC comprises determining the concentration of CBD or THC based on the first scattering intensity at 1007cm¹.

    2020100714 05 May 2020
17. 17. The method of any one of claims 11 to 14, wherein the sample is a saliva sample, and the substance includes one of a group of drugs contained in the saliva sample, including heroin, ***e, fentanyl, codeine, methamphetamine, amphetamine sulfate, aspirin, and melamine, the method further comprising:

    if there is a peak between 625cm¹ and 628cm¹ in the Raman spectrum, identifying the substance as heroin;

    if there are peaks at 1714cm¹, 1597cm'¹, 1003cm'¹ in the Raman spectrum, identifying the substance as ***e;

    if there are peaks at 1620cm¹, 1005cm¹, 830cm¹ in the Raman spectrum, identifying the substance as codeine;

    if there are peaks at 1578cm¹, 998cm¹ in the Raman spectrum, identifying the substance as methamphetamine;

    if there Eire peaks at 1030cm¹,1003cm¹, 970cm¹ in the Raman spectrum, identifying the substance as amphetamine sulfate;

    if there are peaks at 1665cm¹,1080cm¹, 900cm¹, 500cm¹ in the Raman spectrum, identifying the substance as aspirin; and if there is a peak at 695cm¹ in the Raman spectrum, identifying the substance as melamine.