Liquid cosmetic component analysis system and method based on triboelectrification effect

Abstract

The invention discloses a liquid cosmetic component analysis system based on a triboelectrification effect, the system comprises a micro-channel and a self-powered liquid sensor which are respectively used for micro liquid sample control and trace element component analysis, and the micro-channel is connected with a driving assembly used for driving liquid to flow; the self-powered liquid sensor is connected with a voltage acquisition assembly; the self-powered liquid sensor is of a multi-layer film sensing structure prepared based on the triboelectrification effect and the electrostatic induction effect. The multilayer film sensing structure comprises a glass substrate (1), a bottom electrode (2), a dielectric layer (3) and a top electrode (4) which are sequentially arranged from bottom to top. And the micro-channel (5) is bonded on the upper surface of the top electrode (4). According to the invention, the components in the liquid cosmetic can be determined based on different voltage signals generated by the triboelectrification effect, the miniaturization of cosmetic detection equipment can be realized, and the detection is simpler, more convenient and quicker.

Description

Technical Field

[0001] The present invention relates to a liquid cosmetic component analysis system and method, in particular to a liquid cosmetic component analysis system and method based on triboelectric effect. Background Art

[0002] As people's health awareness continues to improve, there is an increasing focus on cosmetic ingredients, especially concerns about the possible presence of harmful substances and allergens. Cosmetic ingredient analysis plays an important role in evaluating the safety of products and ensuring that cosmetics comply with relevant regulations and standards. This analysis can not only reveal potential harmful substances, but also help maintain the health and safety of consumers. Cosmetic manufacturers need to ensure that their products meet strict quality standards, and ingredient analysis helps monitor the consistency of formulas and the stability of products.

[0003] Faced with fierce market competition and the continuous introduction of new products, ingredient analysis can help develop better formulas, improve product performance, and meet changing market demands. At the same time, some cosmetic ingredients may have a negative impact on the environment, and ingredient analysis can also evaluate these environmental impacts and promote more sustainable product design and production. Under strict regulations and regulatory environments, ingredient analysis is an important means to ensure that products comply with regulations and help prevent the use of restricted or banned ingredients. Therefore, cosmetic ingredient analysis not only involves consumer health, safety, and quality control, but also includes R&D innovation, environmental sustainability, and regulatory compliance, which has far-reaching significance for the sustainable development of the cosmetics industry and the protection of consumer rights.

[0004] The purpose of cosmetic ingredient analysis technology is to study and identify the types, concentrations and properties of various ingredients in cosmetics. Common analytical methods include gas chromatography (for volatile component analysis), liquid chromatography, mass spectrometry, Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, high-resolution nuclear magnetic resonance, elemental analysis and thermogravimetric analysis. In addition, microscopy technology can be used to observe the microstructure and component distribution of cosmetics, while surface analysis technology is used to study the composition and morphology of the cosmetic surface, and fluorescence spectroscopy technology is specifically used to detect fluorescent active ingredients. However, these technologies are often too complicated in the detection of liquid cosmetics. For example, some cosmetic detection devices require the use of a variety of color developers that can react with different substances to achieve substance detection. For ingredients that cannot react with color developers, identification cannot be made, which limits the use scenario of the detection device. Therefore, this detection technology is mainly used in laboratory environments, which limits its feasibility in portable, on-site or real-time applications. Summary of the invention

[0005] The purpose of the present invention is to provide a liquid cosmetic component analysis system and method based on the triboelectric effect. It can determine the components in the liquid cosmetic based on different voltage signals generated by the triboelectric effect, and can realize the miniaturization of cosmetic detection equipment, making the detection simpler and faster.

[0006] The technical solution of the present invention is a liquid cosmetic ingredient analysis system based on the triboelectric effect, which is characterized by comprising: a microfluidic channel and a self-powered liquid sensor respectively used for trace liquid sample manipulation and trace element ingredient analysis, the microfluidic channel is connected to a driving component for driving liquid flow, and the self-powered liquid sensor is connected to a voltage collection component; the self-powered liquid sensor is a multilayer thin film sensing structure prepared based on the triboelectric effect and the electrostatic induction effect; the multilayer thin film sensing structure comprises a glass substrate, a bottom electrode, a dielectric layer and a top electrode arranged in sequence from bottom to top; the microfluidic channel is bonded to the upper surface of the top electrode.

[0007] In the above-mentioned liquid cosmetic ingredient analysis system based on triboelectric effect, the bottom electrode includes a plurality of electrode groups arranged in parallel, each electrode group includes a plurality of rectangular electrodes of the same shape, and the rectangular electrodes of each electrode group are connected to the first signal pin electrode at the edge of the multilayer thin film sensing structure through the bottom electrode lead on the side; the top electrode includes a plurality of electrode groups whose number and position correspond to the bottom electrodes, and each electrode group includes a contact electrode for contacting the cosmetic sample to be tested, the contact electrode is rectangular, and its position corresponds to the rectangular electrode (the size of the contact electrode is smaller than the rectangular electrode), and is connected to the second signal pin electrode at the edge of the multilayer thin film sensing structure through the top electrode lead.

[0008] In the aforementioned liquid cosmetic ingredient analysis system based on triboelectric effect, the microchannel is constructed of wall materials, including a plurality of microchambers covering each electrode group of the top electrode respectively, a sealable sample outlet is arranged at one end of the microchamber, and the other end is connected to a common sample inlet through a microchannel. Its coverage area is larger than the area of ​​the contact electrode in the top electrode.

[0009] In the aforementioned liquid cosmetic ingredient analysis system based on triboelectric effect, the wall material is polydimethylsiloxane.

[0010] In the aforementioned liquid cosmetic ingredient analysis system based on the triboelectric effect, the overall length of the wall material of the microchannel is 7 cm, the width is 6.5 cm, and the thickness is 2-3 mm; the microchamber is a wavy channel with a length of 4 cm, a width of 0.5 cm, and a height of 50 μm; the connecting microchannel is a length of 2 cm, a width of 0.3 cm, and a height of 50 μm; the inlet and outlet are both through holes with a diameter of 0.8 cm and a diameter of 0.6 cm.

[0011] In the aforementioned liquid cosmetic ingredient analysis system based on triboelectric effect, the shape of the glass substrate is rectangular silicon dioxide with a length of 10 cm, a width of 8 cm and a thickness of 1-3 mm.

[0012] In the aforementioned liquid cosmetic ingredient analysis system based on the triboelectric effect, the bottom electrode material is one of gold, platinum and aluminum, and has a thickness of 500-1000 μm.

[0013] In the aforementioned liquid cosmetic ingredient analysis system based on the triboelectric effect, the dielectric layer material is a polydimethylsiloxane film with a length of 8 cm, a width of 6 cm, and a thickness of 20-50 μm.

[0014] In the aforementioned liquid cosmetic ingredient analysis system based on triboelectric effect, the top electrode material is one of gold, platinum and aluminum, and has a thickness of 100-300 μm.

[0015] The analysis method based on the former system is characterized by comprising the following steps:

[0016] ① Connect the microfluidic pump to the self-powered liquid sensor through the catheter, then set the flow rate and direction of the microfluidic pump, and then drive the microfluidic pump to inject the cosmetic sample to be tested into the microchamber, so that the cosmetic sample to be tested flows through the top electrode to the end of the flow channel;

[0017] ② Set the microfluidic pump to cycle forward and reverse to drive the cosmetic liquid sample and the top electrode to establish a reciprocating friction motion, and the number of cycles shall be no less than 100 times;

[0018] ③ Use an oscilloscope to measure the changes in the output voltage of the self-powered liquid sensor, and process the output results using a machine learning algorithm to obtain the classification results.

[0019] Compared with the prior art, the present invention can use the constructed multilayer thin film sensing structure as a self-powered liquid sensor. When the liquid cosmetic sample flows through the electrodes on the self-powered liquid sensor in a microflow manner, a triboelectric effect occurs. The potential difference of the electrification effect varies according to the different ingredients in the cosmetics. The difference in the potential difference of different ingredients can be analyzed using a machine learning algorithm to generate a basis for analyzing the ingredients in the cosmetics. The device of the present invention is based on a microfluidic channel, which can realize the miniaturization of the equipment and at the same time has the advantages of high sensitivity, high efficiency, and high biocompatibility. In addition, the same analysis environment required for the analysis of cosmetic ingredients can be created in the microchannel of the present invention, and the design of multiple microchambers can implement high-throughput operations, which can provide a new simple and fast method for the analysis and measurement of cosmetic ingredients. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the overall structure of the device in Example 1 of the present invention;

[0021] Figure 2 This is a structural exploded view of the entire device in Example 1 of the present invention;

[0022] Figure 3 This is a flow chart of device manufacturing in Example 1 of the present invention;

[0023] Figure 4 This is a working principle diagram of the device in Example 1 of the present invention;

[0024] Figure 5 This is a schematic diagram of system connection in Example 1 of the present invention;

[0025] Figure 6 This is a flow chart of the cosmetic ingredient detection method in Example 1 of the present invention;

[0026] Figure 7 The results of active ingredient concentration detection and artificial intelligence classification in the cosmetic liquid in Example 2 of the present invention;

[0027] Figure 8 The results of microbial detection and artificial intelligence recognition in cosmetic liquid in Example 3 of the present invention;

[0028] Fig. 9 The results of heavy metal and harmful substance detection and artificial intelligence recognition in cosmetic liquid in Example 4 of the present invention; DETAILED DESCRIPTION

[0029] The present invention will be further described below in conjunction with the embodiments, but they are not intended to limit the present invention.

[0030] Example 1: A liquid cosmetic ingredient analysis system (six channels) based on triboelectric effect, the structure of which is as follows: Figure 1 and Figure 2 As shown, the triboelectric effect is achieved by a self-powered liquid sensor, which includes a glass substrate 1, a bottom electrode 2, a dielectric layer 3, and a top electrode 4. The microchannel 5 is bonded to the upper surface of the top electrode 4 in the self-powered liquid sensor, and the microchamber is located above the contact electrode 401 of the top electrode 4. The bottom electrode 2 includes 6 electrode groups arranged in parallel, each electrode group includes a plurality of rectangular electrodes 201 of the same shape, and the rectangular electrodes 201 of each electrode group are connected to the first signal pin electrode 203 at the edge of the multi-layer thin film sensing structure through the bottom electrode lead 202 on the side; the top electrode 4 includes a plurality of electrode groups corresponding in number and position to the bottom electrode 2, each electrode group includes a contact electrode 401 for contacting with the cosmetic sample to be tested, the contact electrode 401 is rectangular, and the position corresponds to the rectangular electrode 201, and is connected to the second signal pin electrode 403 at the edge of the multi-layer thin film sensing structure through the top electrode lead 402.

[0031] In this embodiment, the manufacturing process of the device composed of the self-powered liquid sensor and the microfluidic channel (hereinafter referred to as the device) is as follows: Figure 3 As shown, the material of the glass substrate 1 is silicon dioxide with a thickness of 1-3 mm; the material of the bottom electrode 2 is one of gold, platinum or aluminum with a thickness of 500-1000 μm; the material of the dielectric layer 3 is polydimethylsiloxane with a thickness of 20-50 μm; the material of the top electrode 4 is one of gold, platinum or aluminum with a thickness of 100-300 μm; the material of the microchannel 5 is polydimethylsiloxane with a thickness of 2-3 mm.

[0032] The bottom electrode 2 can be formed by growing the electrode material on the glass substrate 1 by electron beam evaporation or magnetron sputtering, and then patterning the electrode. The rectangular electrode 201 of the bottom electrode 2 is connected to the first pin electrode 203 at the edge of the device through the bottom electrode lead 202.

[0033] The dielectric layer 3 is bonded to the bottom electrode 2 using a PLASMA cleaning machine.

[0034] The top electrode 4 can be formed by growing the electrode material on the dielectric layer 3 by electron beam evaporation or magnetron sputtering, and then patterning the electrode. The contact electrode 401 of the top electrode 4 is connected to the second signal pin electrode 403 at the edge of the device through the top electrode lead 402.

[0035] The microfluidic channel 5 includes a wavy microchamber 503, an injection port 501, an outlet port 504 and a microchannel 502 connecting the two. The length of the microfluidic channel 5 structure is 7 cm, the width is 6.5 cm, and the thickness is 2-3 mm. The height of the microchamber 503 is 50 μm, and its coverage area should be larger than the contact electrode area. The microfluidic channel mold is obtained by photolithography, and the microfluidic channel 5 is obtained through the steps of glue preparation, mixing, debubbling, curing, cutting, and punching. The microfluidic channel 5 is surface plasma treated, bonded above the top electrode 4 and connected to the microfluidic needle and catheter at the microfluidic channel injection port 501, and the other end of the catheter is connected to the syringe on the microfluidic pump. The specific system connection is as follows Figure 5 As shown, the six channels correspond to six electrode combinations respectively.

[0036] In this embodiment, the device works as follows: Figure 4 Before the liquid to be tested contacts the top electrode, no output voltage is observed. When the liquid to be tested flows through the contact electrode 401 of the top electrode 4, the electrons on the top electrode flow to the bottom electrode 2, and a potential difference is generated between the two electrodes. When the liquid to be tested separates from the contact electrode 401, the electrons on the bottom electrode 2 flow to the top electrode 4, generating an opposite potential difference.

[0037] Example 2: The active ingredients of cosmetics generally include moisturizing factors, antioxidants, firming agents, etc. For example, retinol is an anti-aging ingredient, vitamin C promotes collagen production, vitamin E is used for antioxidants, niacinamide is used to improve pigmentation, and hyaluronic acid is a substance with good moisturizing properties. The concentration of 0.02-0.05 can ensure the moisturizing effect. Therefore, it is particularly important to verify whether the active ingredients in cosmetics meet the standards. Figure 7 As shown, the output voltage of the self-powered liquid sensor of the present invention is used to detect and analyze the concentration of hyaluronic acid contained in the cosmetic liquid sample. When the concentration of hyaluronic acid is 0, the measured voltage peak is about 1.9V, when the concentration of hyaluronic acid is 0.01%, the measured voltage peak is about 7.2V, when the concentration of hyaluronic acid is 0.02%, the measured voltage peak is about 13.1V, when the concentration of hyaluronic acid is 0.03%, the measured voltage peak is about 19.4V, when the concentration of hyaluronic acid is 0.04%, the measured voltage peak is about 24.5V, when the concentration of hyaluronic acid is 0.05%, the measured voltage peak is about 28.6V. From the measurement results, we can see that when the concentration of hyaluronic acid increases by 0.01%, the measured peak voltage increases by about 4-6V. Different signals are processed by using the CNN algorithm in machine learning. The specific operation is as follows: all samples are divided into several subsets, and some subsets are selected as test sets each time, while other subsets are used for model training, and this process is repeated several times to finally obtain a comprehensive evaluation of the model performance. The indicators on the diagonal of the confusion matrix represent the accuracy of the hyaluronic acid data of different concentrations measured by the self-powered liquid sensor, that is, the number of samples accurately predicted. Among them, the sample with a concentration of 0.04% has the highest accuracy, reaching 97.50%, the sample with a concentration of 0.03% has an accuracy of 97.44%, the sample with a concentration of 0.02% has an accuracy of 95.12%, and the samples with a concentration of 0.01% and 0.05% have an accuracy of more than 93%, and the average classification accuracy has reached 95.52%.

[0038] Example 3: Liquid cosmetics are easily contaminated by microorganisms during preparation, storage and use, which seriously threatens the quality and safety of cosmetics. Detect bacteria, molds, yeasts and other substances in cosmetics to determine whether the products meet hygiene standards. Microorganisms may cause skin infections and allergies.

[0039] This embodiment uses the test system of embodiment 1. In this embodiment, the microfluidic channel and the self-powered liquid sensor need to be cleaned. First, the microfluidic channel and the self-powered liquid sensor are sterilized with 70% ethanol, then rinsed with deionized water, and dried. Then, the cosmetic samples containing different types of microorganisms can be injected into the microfluidic channel.

[0040] In this embodiment, the output voltage of the self-powered liquid sensor when the cosmetic samples containing different kinds of microorganisms are tested is analyzed. When there are no microorganisms in the sample, the output voltage of the self-powered liquid sensor is about 1.9V, when the microorganism in the sample is heat-resistant Escherichia coli, the output voltage is about 7.5V, when the microorganism in the sample is Staphylococcus aureus, the output voltage is about 13V, when the microorganism in the sample is Pseudomonas aeruginosa, the output voltage is about 18.5V, when the microorganism in the sample is mold, the output voltage is about 24.5V, and when the microorganism in the sample is yeast, the output voltage is about 30V. The results are processed by the same machine learning algorithm as in Example 1 to obtain the following Figure 8 As a result, in the confusion matrix, the sample accuracy rates of thermotolerant Escherichia coli, Staphylococcus aureus, and mold all reached 100%, the sample accuracy rates of Pseudomonas aeruginosa all reached 97.50%, the sample accuracy rates of yeast all reached 95.24%, and the average sample accuracy rates all reached 98.55%.

[0041] Example 4: Excessive levels of heavy metals such as lead, mercury, arsenic, and cadmium in liquid cosmetics can also cause harm to human health.

[0042] This embodiment adopts the test system of embodiment 1. First, the microfluidic channel and the self-powered liquid sensor are sterilized with 70% ethanol, and then rinsed with deionized water. After drying, the cosmetic samples containing different heavy metals to be tested can be injected into the microfluidic channel.

[0043] In this embodiment, the output voltage of the self-powered liquid sensor is analyzed when the cosmetic samples containing different heavy metals are tested. When there is no heavy metal in the sample, the output voltage of the self-powered liquid sensor is about 1.9V, when the heavy metal in the sample is lead, the output voltage is about 9.2V, when the heavy metal in the sample is mercury, the output voltage is about 18.1V, when the heavy metal in the sample is arsenic, the output voltage is about 25.6V, when the heavy metal in the sample is cadmium, the output voltage is about 33.5V. It can be seen that the output voltage of the self-powered liquid sensor is significantly different when the cosmetic samples containing different heavy metal elements flow through the self-powered liquid sensor. This result is processed using the same machine learning algorithm as in Example 1 to obtain the following: Fig. 9 The results show that in the confusion matrix, the sample accuracy of lead element is the highest, reaching 96.43%, the sample accuracy of cadmium element is 95.00%, the sample accuracy of arsenic element is 91.23%, the sample accuracy of mercury element is 89.36%, and the average sample accuracy is 93.01%.

[0044] It can be seen that according to the specific implementation, the liquid cosmetic ingredient analysis method and system based on the triboelectric effect of the present invention has the function of identifying different ingredients in liquid cosmetics. The present invention has the advantages of high sensitivity, high efficiency and high biocompatibility. The microchannel can provide a consistent environment for the test sample, reducing the interference of external factors on the test results; the design of multiple micro chambers can achieve high-throughput measurement; and it provides a new, simple and fast method for the detection of liquid cosmetic ingredients.

Claims

1. A liquid cosmetic ingredient analysis system based on triboelectric effect, characterized in that: include: A microfluidic channel and a self-powered liquid sensor are respectively used for manipulation of trace liquid samples and analysis of trace element components. The microfluidic channel is connected to a driving component for driving the flow of liquid, and the self-powered liquid sensor is connected to a voltage collection component. The self-powered liquid sensor is a multilayer thin film sensing structure prepared based on the triboelectric effect and the electrostatic induction effect. The multilayer thin film sensing structure comprises a glass substrate (1), a bottom electrode (2), a dielectric layer (3) and a top electrode (4) arranged in sequence from bottom to top. The microfluidic channel (5) is bonded to the upper surface of the top electrode (4).

2. The liquid cosmetic ingredient analysis system based on triboelectric effect according to claim 1, characterized in that: The bottom electrode (2) comprises a plurality of electrode groups arranged in parallel, each electrode group comprises a plurality of rectangular electrodes (201) of the same shape, and the rectangular electrodes (201) of each electrode group are connected to a first signal pin electrode (203) at the edge of a multilayer thin film sensing structure via a bottom electrode lead (202) on the side; the top electrode (4) comprises a plurality of electrode groups whose number and position correspond to those of the bottom electrode (2), and each electrode group comprises a contact electrode (401) for contacting a cosmetic sample to be tested, the contact electrode (401) is rectangular, and its position corresponds to that of the rectangular electrode (201), and is connected to a second signal pin electrode (403) at the edge of the multilayer thin film sensing structure via a top electrode lead (402).

3. The liquid cosmetic ingredient analysis system based on triboelectric effect according to claim 2, characterized in that: The microfluidic channel (5) is constructed of wall materials and includes a plurality of microchambers (503) that cover each electrode group of the top electrode (4) respectively. A sealable sample outlet (504) is provided at one end of the microchamber (503), and the other end is connected to a common sample inlet (501) through a microchannel (502).

4. The liquid cosmetic ingredient analysis system based on triboelectric effect according to claim 3, characterized in that: The wall material is polydimethylsiloxane.

5. The liquid cosmetic ingredient analysis system based on triboelectric effect according to claim 3, characterized in that: The overall length of the wall material of the microchannel is 7 cm, the width is 6.5 cm, and the thickness is 2-3 mm; the microchamber is a wavy channel with a length of 4 cm, a width of 0.5 cm, and a height of 50 μm; the connecting microchannel is a length of 2 cm, a width of 0.3 cm, and a height of 50 μm; the inlet and outlet are through holes with diameters of 0.8 cm and 0.6 cm respectively.

6. The liquid cosmetic ingredient analysis system based on triboelectric effect according to claim 1, characterized in that: The glass substrate (1) is in the shape of a rectangular silicon dioxide with a length of 10 cm, a width of 8 cm and a thickness of 1-3 mm.

7. The liquid cosmetic ingredient analysis system based on triboelectric effect according to claim 1, characterized in that: The bottom electrode (2) is made of one of gold, platinum and aluminum, and has a thickness of 500-1000 μm.

8. The liquid cosmetic ingredient analysis system based on triboelectric effect according to claim 1, characterized in that: The dielectric layer (3) is made of a polydimethylsiloxane film with a length of 8 cm, a width of 6 cm and a thickness of 20-50 μm.

9. The liquid cosmetic ingredient analysis system based on triboelectric effect according to claim 1, characterized in that: The material of the top electrode (4) is one of gold, platinum and aluminum, and has a thickness of 100-300 μm.

10. An analysis method based on the system according to any one of claims 1 to 9, characterized in that: The following steps are involved: ① Connecting the microfluidic pump to the self-powered liquid sensor through a catheter, then setting the flow rate and direction of the microfluidic pump, and then driving the microfluidic pump to inject the cosmetic sample to be tested into the microchamber (502), so that the cosmetic sample to be tested flows through the top electrode (4) to the end of the flow channel; ② Set the microfluidic pump to cycle forward and reverse to drive the cosmetic liquid sample and the top electrode to establish a reciprocating friction motion, and the number of cycles shall be no less than 100 times; ③ Use an oscilloscope to measure the changes in the output voltage of the self-powered liquid sensor, and process the output results using a machine learning algorithm to obtain the classification results.

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