A Liquid Cosmetic Ingredient Analysis System and Method Based on the Triboelectric Effect

Abstract

The present invention discloses a liquid cosmetic ingredient analysis system based on the triboelectric effect. The system includes a microfluidic channel and a self-powered liquid sensor respectively used for manipulating trace liquid samples and analyzing trace element components. A driving component for driving the liquid to flow is connected to the microfluidic channel, and a voltage acquisition component is connected to the self-powered liquid sensor. The self-powered liquid sensor is a multi-layer thin film sensing structure prepared based on the triboelectric effect and the electrostatic induction effect. The multi-layer thin film sensing structure includes a glass substrate (1), a bottom electrode (2), a dielectric layer (3), and a top electrode (4) sequentially arranged from bottom to top. The microfluidic channel (5) is bonded to the upper surface of the top electrode (4). The present invention can determine the components in liquid cosmetics based on different voltage signals generated by the triboelectric effect, can miniaturize the cosmetic detection equipment, and the detection is more simple and fast.

Description

Technical Field

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

[0002] With the continuous improvement of people's health awareness, the attention to cosmetic ingredients has also increased day by day, especially the concern about potential harmful substances and allergens. Cosmetic ingredient analysis plays an important role in evaluating the safety of products, 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 formulations and the stability of products.

[0003] Facing fierce market competition and the continuous introduction of new products, ingredient analysis can help develop better formulations, improve product performance, and meet the 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, promoting more sustainable product design and production. In a strict regulatory environment, ingredient analysis is an important means to ensure product compliance with regulations, helping to prevent the use of restricted or prohibited ingredients. Therefore, cosmetic ingredient analysis not only involves consumer health, safety, and quality control but also includes research and development innovation, environmental sustainability, and regulatory compliance, which has far-reaching significance for the sustainable development of the cosmetic 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 analysis methods include gas chromatography (for volatile ingredient analysis), liquid chromatography, mass spectrometry coupling technology, Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, high-resolution nuclear magnetic resonance, elemental analysis, and thermogravimetric analysis. In addition, microscopy techniques can be used to observe the microstructure and ingredient distribution of cosmetics, while surface analysis techniques are used to study the ingredients and morphology on the surface of cosmetics, and fluorescence spectroscopy techniques are specifically used to detect fluorescent active ingredients. However, these technologies are often too complex for the detection of liquid cosmetics. For example, some cosmetic detection devices need to use a variety of color-developing agents that can react with different substances to achieve substance detection, and for ingredients that cannot react with the color-developing agent, they cannot be identified, which limits the use scenarios of the detection device. Therefore, this detection technology is mainly used in a laboratory environment, which limits its feasibility in portable, on-site, or real-time applications. Summary of the Invention

[0005] The object of the present invention is to provide a liquid cosmetic ingredient analysis system and method based on the triboelectric effect. It can determine the ingredients in liquid cosmetics based on different voltage signals generated by the triboelectric effect, enabling miniaturization of cosmetic detection equipment and making detection more convenient and rapid.

[0006] The technical solution of the present invention: A liquid cosmetic ingredient analysis system based on the triboelectric effect, characterized in that it includes: a microchannel and a self-powered liquid sensor respectively for micro liquid sample manipulation and trace element component analysis. A driving component for driving the liquid to flow is connected to the microchannel, and a voltage acquisition component is connected to the self-powered liquid sensor; the self-powered liquid sensor is a multi-layer thin film sensing structure prepared based on the triboelectric effect and the electrostatic induction effect; the multi-layer thin film sensing structure includes a glass substrate, a bottom electrode, a dielectric layer, and a top electrode arranged in sequence from bottom to top; the microchannel is bonded to the upper surface of the top electrode.

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

[0008] In the aforementioned liquid cosmetic ingredient analysis system based on the triboelectric effect, the microchannel is constructed by a wall material and includes multiple microchambers respectively covering each electrode group of the top electrode. One end of the microchamber is provided with a sealable sample outlet, 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 the 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 2 cm in length, 0.3 cm in width, and 50 μm in height; the sample inlet and the sample 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 the triboelectric effect, the glass substrate is in the shape of rectangular silica, 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, with 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 the triboelectric effect, the top electrode material is one of gold, platinum, and aluminum, with a thickness of 100 - 300 μm.

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

[0016] ① Connect the microfluidic pump to the self-powered liquid sensor through a 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 until the end of the flow channel;

[0017] ② Set the microfluidic pump to circulate forward and reverse to drive the cosmetic liquid sample to construct a reciprocating friction motion with the top electrode, and the number of cycles is not less than 100 times;

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

[0019] Compared with the prior art, the present invention can use the constructed multi-layer thin film sensing structure as a self-powered liquid sensor. When the liquid cosmetic sample flows through the electrode on the self-powered liquid sensor in a microfluidic manner, a triboelectric effect occurs. According to the characteristic that the potential difference of the triboelectric effect is different for different components in the cosmetic, the difference in the potential difference of different components can be analyzed by using a machine learning algorithm to generate a basis for analyzing the components in the cosmetic. The device of the present invention is based on a microfluidic channel, which can realize the miniaturization of the device, and at the same time has the advantages of high sensitivity, high efficiency, and high biocompatibility. In addition, the same analysis environment required for cosmetic ingredient analysis can be created in the microfluidic channel of the present invention, and the design of multiple microchambers can implement high-throughput operations, providing a new simple and fast method for cosmetic ingredient analysis and measurement. Description of the Drawings

[0020] Figure 1 It is a schematic structural diagram of the whole device in Embodiment 1 of the present invention;

[0021] Figure 2 It is the structural decomposition diagram of the whole device in Embodiment 1 of the present invention;

[0022] Figure 3 It is the device manufacturing flow chart in Embodiment 1 of the present invention;

[0023] Figure 4 It is the working principle diagram of the device in Embodiment 1 of the present invention;

[0024] Figure 5 It is the system connection schematic diagram of Embodiment 1 of the present invention;

[0025] Figure 6 It is the flow chart of the method for detecting the components of cosmetics in Embodiment 1 of the present invention;

[0026] Figure 7 It is the detection of the concentration of active ingredients in the cosmetic liquid and the artificial intelligence classification result in Embodiment 2 of the present invention;

[0027] Figure 8 It is the detection of microorganisms in the cosmetic liquid and the artificial intelligence recognition result in Embodiment 3 of the present invention;

[0028] Figure 9 It is the detection of heavy metals and harmful substances in the cosmetic liquid and the artificial intelligence recognition result in Embodiment 4 of the present invention; Detailed implementation mode

[0029] The present invention will be further described below in conjunction with embodiments, but it shall not be used as the basis for limiting the present invention.

[0030] Embodiment 1: A liquid cosmetic component analysis system (six channels) based on the triboelectric effect, the structure is as Figure 1 and Figure 2 shown. The triboelectric effect is completed by a self-powered liquid sensor. The self-powered liquid sensor 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 parallel electrode groups, each electrode group includes a plurality of rectangular electrodes 201 with 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 the cosmetic sample to be measured, 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 a self-powered liquid sensor and a microchannel (hereinafter referred to as the device) is as follows Figure 3 As shown, the material of the glass substrate 1 is silicon dioxide, and the thickness is 1-3 mm; the material of the bottom electrode 2 is one of gold, platinum or aluminum, and the thickness is 500-1000 μm; the material of the dielectric layer 3 is polydimethylsiloxane, and the thickness is 20-50 μm; the material of the top electrode 4 is one of gold, platinum or aluminum, and the thickness is 100-300 μm; the material of the microchannel 5 is polydimethylsiloxane, and the thickness is 2-3 mm.

[0032] The bottom electrode 2 can grow the electrode material on the glass substrate 1 by electron beam evaporation or magnetron sputtering, and then perform patterning of 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 cleaner.

[0034] The top electrode 4 can grow the electrode material on the dielectric layer 3 by electron beam evaporation or magnetron sputtering, and then perform patterning of 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 microchannel 5 includes a wavy microchamber 503, a sample inlet 501, a sample outlet 504, and the connecting microchannel 502 between the two. The length of the microchannel 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 microchannel mold is obtained by photolithography, and the microchannel 5 is obtained through steps such as glue mixing, mixing, degassing, curing, cutting, and punching. The microchannel 5 is subjected to surface plasma treatment, bonded above the top electrode 4, and a microfluidic needle and a catheter are connected at the sample inlet 501 of the microchannel, and the other end of the catheter is connected to a syringe on the microfluidic pump. The specific system connection is as Figure 5 shown, and the six channels respectively correspond to 6 electrode combinations.

[0036] In this embodiment, the working principle of the device is as Figure 4 shown. Before the liquid to be measured contacts the top electrode, no output voltage is observed. When the liquid to be measured flows through the contact electrode 401 of the top electrode 4, the electrons on the top electrode flow to the bottom electrode 2, and at this time, a potential difference will be generated between the two electrodes. When the liquid to be measured is separated from the contact electrode 401, the electrons of the bottom electrode 2 flow to the top electrode 4, generating an opposite potential difference.

[0037] Example 2: The active efficacy components 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 antioxidant, niacinamide is used to improve pigmentation, and hyaluronic acid is a substance with good moisturizing properties. A concentration of 0.02 - 0.05 is required to ensure the moisturizing effect. Therefore, it is particularly important to verify whether the active ingredients in cosmetics meet the standards. As Figure 7 shown, the self-powered liquid sensor of the present invention is used to detect and analyze the concentration of hyaluronic acid in the cosmetic liquid sample by outputting voltage. When the concentration of hyaluronic acid is 0, the measured voltage peak is approximately 1.9V. When the concentration of hyaluronic acid is 0.01%, the measured voltage peak is approximately 7.2V. When the concentration of hyaluronic acid is 0.02%, the measured voltage peak is approximately 13.1V. When the concentration of hyaluronic acid is 0.03%, the measured voltage peak is approximately 19.4V. When the concentration of hyaluronic acid is 0.04%, the measured voltage peak is approximately 24.5V. When the concentration of hyaluronic acid is 0.05%, the measured voltage peak is approximately 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 approximately 4 - 6V. By using the CNN algorithm in machine learning to process different signals. The specific operation is as follows: all samples are divided into several subsets. Each time, some subsets are selected as the test set, 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 data of different concentrations of hyaluronic acid 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 rate, reaching 97.50%. The accuracy rate of the sample with a concentration of 0.03% reaches 97.44%. The accuracy rate of the sample with a concentration of 0.02% reaches 95.12%. The accuracy rates of the samples with concentrations of 0.01% and 0.05% also reach over 93%. The average classification accuracy rate reaches 95.52%.

[0038] Example 3: Liquid cosmetics are prone to microbial contamination during preparation, storage, and use, seriously threatening the quality and safety of cosmetics. Detecting substances such as bacteria, molds, and yeasts in cosmetics to determine whether the product meets the hygiene standards. Microorganisms may cause problems such as skin infections and allergies.

[0039] In this example, the test system of Example 1 is adopted. In this example, the microchannel and the self-powered liquid sensor need to be cleaned. First, after sterilizing the microchannel and the self-powered liquid sensor with 70% ethanol, then rinsing with deionized water and drying, the cosmetic sample to be tested containing different kinds of microorganisms can be injected into the microchannel.

[0040] In this embodiment, the output voltage of the self-powered liquid sensor through which the cosmetic sample to be tested containing different microorganisms flows 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 Escherichia coli that can withstand heat, 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. When the microorganism in the sample is yeast, the output voltage is about 30V. After processing this result using the same machine learning algorithm as in Embodiment 1, the result is as follows Figure 8 In the confusion matrix, the sample accuracy rates of Escherichia coli that can withstand heat, Staphylococcus aureus, and mold all reach 100%. The sample accuracy rate of Pseudomonas aeruginosa reaches 97.50%. The sample accuracy rate of yeast reaches 95.24%. The average sample accuracy rate reaches 98.55%.

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

[0042] In this embodiment, the test system of Embodiment 1 is adopted. First, after sterilizing the microchannel and the self-powered liquid sensor with 70% ethanol, then rinsing with deionized water and drying, the cosmetic sample to be tested containing different heavy metals can be injected into the microchannel.

[0043] In this embodiment, the output voltage of the self-powered liquid sensor through which the cosmetic sample to be tested containing different heavy metals flows is analyzed. When there are no heavy metals 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 there are obvious differences in the output voltages of cosmetic samples containing different heavy metal elements flowing through the self-powered liquid sensor. After processing this result using the same machine learning algorithm as in Embodiment 1, the result is as follows Figure 9 In the confusion matrix, the sample accuracy rate of lead element is the highest, reaching 96.43%. The sample accuracy rate of cadmium element reaches 95.00%. The sample accuracy rate of arsenic element reaches 91.23%. The sample accuracy rate of mercury element reaches 89.36%. The average sample accuracy rate reaches 93.01%.

[0044] It can be seen that according to the specific embodiments, the method and system for analyzing liquid cosmetic ingredients based on the triboelectrification effect of the present invention have 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 microchambers can achieve high-throughput measurement; it provides a brand-new simple and rapid method for the detection of liquid cosmetic ingredients.

Claims

1. A liquid cosmetic ingredient analysis system based on the triboelectrification effect, characterized in that, Comprising: A microchannel and a self-powered liquid sensor respectively for microfluidic liquid sample manipulation and trace element composition analysis. A driving component for driving liquid flow is connected to the microchannel, and a voltage acquisition component is connected to the self-powered liquid sensor; the self-powered liquid sensor is a multi-layer thin film sensing structure prepared based on the triboelectric effect and electrostatic induction effect; the multi-layer thin film sensing structure includes 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 microchannel (5) is bonded to the upper surface of the top electrode (4); the bottom electrode (2) includes a plurality of electrode groups arranged in parallel, each electrode group includes a plurality of rectangular electrodes (201) with 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 the cosmetic sample to be measured, the contact electrode (401) is rectangular, corresponding in position 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); the material of the dielectric layer (3) is a polydimethylsiloxane thin film, with a length of 8 cm, a width of 6 cm, and a thickness of 20 - 50 μm.

2. The liquid cosmetic ingredient analysis system based on the triboelectric effect according to claim 1, characterized in that: The microchannel (5) is constructed by a wall material and includes a plurality of microchambers (503) respectively covering each electrode group of the top electrode (4). One end of the microchamber (503) is provided with a sealable sample outlet (504), and the other end is connected to a common sample inlet (501) through a microchannel (502).

3. The liquid cosmetic ingredient analysis system based on the triboelectric effect according to claim 2, characterized in that: The wall material is polydimethylsiloxane.

4. The liquid cosmetic ingredient analysis system based on the triboelectric effect according to claim 2, 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 2 cm in length, 0.3 cm in width, and 50 μm in height; both the sample inlet and the sample outlet are through holes with a diameter of 0.8 cm and a diameter of 0.6 cm.

5. The liquid cosmetic ingredient analysis system based on the triboelectrification effect according to claim 1, wherein: The shape of the glass substrate (1) is rectangular silica, with a length of 10 cm, a width of 8 cm, and a thickness of 1 - 3 mm.

6. The liquid cosmetic ingredient analysis system based on the triboelectrification effect according to claim 1, wherein: The material of the bottom electrode (2) is one of gold, platinum, and aluminum, with a thickness of 500 - 1000 μm.

7. The liquid cosmetic ingredient analysis system based on the triboelectrification effect according to claim 1, wherein: The material of the top electrode (4) is one of gold, platinum, and aluminum, with a thickness of 100 - 300 μm.

8. An analysis method based on the system according to any one of claims 1-7, characterized in that, Including the following steps: ① Connect a microfluidic pump to the self-powered liquid sensor through a 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 measured into the microchamber (503) so that the cosmetic sample to be measured flows through the top electrode (4) until the end of the flow channel; ② Set the microfluidic pump to cycle forward and reverse to drive the cosmetic liquid sample to reciprocally rub against the top electrode, and the number of cycles is not less than 100 times; ③ Measure the change in the output voltage of the self-powered liquid sensor using an oscilloscope, and process the output results with a machine learning algorithm to obtain a classification result.

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