Graphene-based sensor, measuring device using same, and method for measuring and analyzing sample

Abstract

The invention provides a graphene-based sensor, a measuring device using the same, and a method for measuring and analyzing a sample. A graphene-based sensor according to one embodiment of the present invention comprises: a substrate; a doped region formed by doping a partial region of the substrate with an impurity; an insulator layer stacked on the substrate except for a portion of the doped region; the graphene layer is stacked on the doped region; a first electrode connected to the graphene layer; and a second electrode connected to the doped region.

Description

Technical Field

[0001] The present invention relates to a graphene-based sensor, a measuring device using the same, and a method of measuring and analyzing a sample. Background Art

[0002] There are various types of sensors, such as biosensors for detecting biological materials (such as enzymes, antibodies and DNA), gas sensors for detecting gas concentrations, etc., and pressure sensors for detecting pressure. Among these sensors, biosensors are mainly classified into biosensors based on optical methods, biosensors based on electrochemical methods, and biosensors based on piezoelectric methods. The biosensor based on the optical method uses optical methods, such as color development, fluorescence, chemiluminescence, and surface plasmon resonance, and the biosensor based on the electrochemical method uses a method of measuring the interaction between the analyte and the bioreceptor by using electrochemical signals (such as potential, current, charge, conductivity, and impedance). The biosensor based on the piezoelectric method uses a method of measuring mass changes. In terms of portability and miniaturization, the biosensor based on the electrochemical method has advantages over other methods. In addition, compared to the biosensor based on the optical method, the biosensor based on the electrochemical method promotes the signal conversion process because it can be used in both labeled and unlabeled methods and uses electrical signals for detection signals. The sensor based on the electrochemical method can be implemented based on a transistor to accurately measure the changes in tiny electrical signals.

[0003] As a novel material that can replace semiconductors, graphene is being actively studied. Graphene has a two-dimensional planar crystal structure in a hexagonal honeycomb shape and is used in various fields due to its thinness, lightness, excellent durability and conductivity. Recently, a new component (i.e., a barristor) that is functionally close to a transistor but structurally close to a diode has emerged using graphene. Summary of the invention

[0004] A first aspect of the present invention provides a graphene-based sensor capable of detecting minute changes in an electrical signal exhibited by a sample.

[0005] Another aspect of the present invention provides a measuring device using a graphene-based sensor.

[0006] Another aspect of the present invention provides a method of measuring a sample by applying a voltage to a sensor.

[0007] Another aspect of the present invention provides a method for analyzing measurements of a sensor array comprising a plurality of graphene-based sensors by using an artificial neural network.

[0008] The technical problems of the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by a person skilled in the art in the art to which the present invention belongs from the following description.

[0009] A graphene-based sensor according to an embodiment of the present invention includes a substrate; a doped region formed by doping a portion of the substrate with impurities; an insulator layer stacked on the substrate except for a portion of the doped region; a graphene layer stacked on the doped region; a first electrode connected to the graphene layer; and a second electrode connected to the doped region.

[0010] In one embodiment, the doped region may include a first doped region doped to have a first concentration, and a second doped region doped to have a second concentration, wherein the first concentration is equal to or less than the second concentration, wherein the graphene layer is connected to the first doped region, and wherein the second electrode is connected to the second doped region.

[0011] In one embodiment, the first electrode may surround the periphery of the graphene layer.

[0012] In one embodiment, the second electrode may be positioned under the substrate to be opposite to the graphene layer.

[0013] In one embodiment, the graphene-based sensor may further include one or more through-hole electrodes passing through the insulator layer and the substrate from a location spaced apart from the first electrode, wherein the second electrode may be connected to the one or more through-hole electrodes.

[0014] In one embodiment, the second electrode may pass through the insulator layer to be connected to the doped region.

[0015] In an embodiment, the graphene-based sensor may further include a third electrode spaced apart from the first electrode and in contact with the graphene layer.

[0016] In one embodiment, the graphene-based sensor may further include a storage unit formed by etching a substrate to have a first depth and a first width, and a channel unit formed by etching an insulator layer to have a second depth and a second width and configured to connect the storage unit and the graphene layer to each other, wherein the second depth and the second width are respectively smaller than the first depth and the first width.

[0017] In one embodiment, a plurality of doped regions may be formed on a substrate in a manner separated from each other, and an insulator layer may be stacked to expose the plurality of doped regions.

[0018] In one embodiment, graphene layers are stacked to correspond to a plurality of doped regions, wherein the graphene-based sensor comprises a plurality of first electrodes respectively corresponding to the plurality of doped regions, and wherein the second electrodes are commonly connected to the plurality of doped regions.

[0019] In one embodiment, a graphene layer is stacked on a plurality of doped regions, wherein the graphene-based sensor comprises a plurality of second electrodes respectively connected to the plurality of doped regions, and wherein the first electrode is commonly connected to the plurality of doped regions.

[0020] In one embodiment, the graphene-based sensor may further include a multiplexer configured to output values ​​measured through the graphene layer on the plurality of doped regions.

[0021] In one embodiment, the graphene-based sensor may further include a reaction layer located on the surface of the graphene layer and including a material that induces charge in the graphene layer.

[0022] According to another embodiment of the present invention, a graphene-based sensor may include a substrate, a two-dimensional semiconductor layer stacked on the substrate, a graphene layer stacked on the two-dimensional semiconductor layer, a first electrode stacked in contact with the two-dimensional semiconductor layer, and a second electrode stacked in contact with the graphene layer.

[0023] In another embodiment, a graphene-based sensor may include a reactive layer located on a surface of a graphene layer and including a material that induces charge in the graphene layer.

[0024] In another embodiment, a plurality of two-dimensional semiconductor layers are arranged on a substrate to be separated from each other, wherein the graphene layer is stacked on the plurality of two-dimensional semiconductor layers, and wherein a plurality of first electrodes are respectively arranged on the plurality of two-dimensional semiconductor layers.

[0025] In another embodiment, the two-dimensional material constituting the plurality of two-dimensional semiconductor layers may include a portion and another portion that are different from each other.

[0026] In another embodiment, a plurality of two-dimensional semiconductor layers may be arranged in a first direction, and wherein the graphene layer may be arranged in a second direction perpendicular to the first direction.

[0027] In another embodiment, the graphene-based sensor may further include a third electrode spaced apart from the first electrode and in contact with the two-dimensional semiconductor layer stack.

[0028] In another embodiment, the graphene-based sensor may further include a fourth electrode spaced apart from the second electrode and stacked in contact with the graphene layer.

[0029] In another embodiment, the graphene-based sensor may further include a third electrode commonly connected to a plurality of two-dimensional semiconductor layers, wherein the plurality of two-dimensional semiconductor layers are radially arranged, wherein the graphene layer is arranged across the plurality of two-dimensional semiconductor layers to have a circular band shape, wherein a plurality of first electrodes are connected to the plurality of two-dimensional semiconductor layers, and wherein the plurality of first electrodes are respectively connected to the plurality of two-dimensional semiconductor layers.

[0030] A measuring device according to another embodiment of the present invention may include a graphene-based sensor, wherein a graphene layer is stacked on a doped region formed on a substrate or on a two-dimensional semiconductor layer stacked on a substrate, and an output unit configured to convert an output current of the graphene-based sensor into a voltage and output the voltage.

[0031] In another embodiment, the output unit may include: a pre-amplification unit configured to convert the output current of the graphene-based sensor into a voltage and output the voltage; and a feedback unit configured to adjust so that the output voltage of the pre-amplification unit is within a predetermined range.

[0032] In another embodiment, the measuring device may further include a display unit configured to display the output voltage of the output unit, and a communication unit configured to transmit the output voltage of the output unit to the outside.

[0033] In another embodiment, the measuring device may include a sensor array, wherein the graphene-based sensors are arranged in one or two dimensions, and a multiplexer connected to a plurality of graphene-based sensors constituting the sensor array, wherein the output unit is configured to selectively receive the output current of each graphene-based sensor through the multiplexer.

[0034] In another embodiment, the measuring device may further include an internal circuit including a set of mapping tables corresponding to an artificial neural network that receives measurement values ​​obtained by a reaction between the sample and the material of the reaction layer of the graphene-based sensor and outputs an analysis value.

[0035] In another embodiment, the measuring device may further include a voltage applying unit configured to apply a voltage within a predetermined range to the graphene-based sensor; and a measuring unit configured to detect a first measurement value of the resistance or current of the graphene-based sensor based on the voltage applied before applying the sample, and to detect and output a second measurement value of the resistance or current of the graphene-based sensor based on the voltage applied after applying the sample.

[0036] In another embodiment, the measuring unit may output a result value including a maximum difference among voltage-specific differences between the first measurement value and the second measurement value.

[0037] In another embodiment, the measuring unit may repeat the process of measuring the second measurement value at fixed time intervals, and output the second measurement value of the resistance or current of the sensor according to the voltage applied each time the repetition is performed.

[0038] In another embodiment, the measuring unit may detect and output a change in the maximum difference between the first measurement value and the second measurement value each time the repetition is performed.

[0039] According to another embodiment of the present invention, an analysis method uses a sensor array comprising a plurality of sensors, wherein a graphene layer is stacked on a two-dimensional semiconductor or on a semiconductor region doped on a substrate, and the method includes receiving a plurality of measurement values ​​from a plurality of graphene-based sensors of the sensor array; and receiving the plurality of measurement values ​​and obtaining analysis results by using an artificial neural network using arithmetic operations determined in a set of mapping tables.

[0040] In another embodiment, the material of the reaction layer applied to the graphene layer of the plurality of graphene-based sensors may include a portion and another portion that are different from each other.

[0041] In another embodiment, the material of the reaction layers of the plurality of graphene-based sensors may be at least one of the following: quantum dots, biomolecules, gas-reactive molecules, or pressure-reactive structures.

[0042] The graphene-based sensor according to the present invention has a higher reaction sensitivity than a general sensor, and thus can accurately measure changes in tiny electrical signals caused by interactions between antigens, antibodies, enzymes, DNA, and the like. In addition, the graphene-based sensor can be applied not only to the biological field, but also to various fields requiring measurement of light, gas, pressure, and the like.

[0043] According to the present invention, the sample can be accurately measured using the sensor. The accuracy of the measurement can be improved based on the difference between the sensor values ​​measured before and after applying the sample.

[0044] According to the present invention, the measurement sensitivity of a sample can be improved using a graphene-based sensor.

[0045] The effects of the technical concept according to the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by a person skilled in the art in the art to which the present invention belongs from the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figures 1A to 1D The structure of a graphene-based sensor according to a first embodiment of the present invention is shown.

[0047] Figures 2A to 2D The structure of a graphene-based sensor according to a second embodiment of the present invention is shown.

[0048] Figures 3A to 3B FIG. 1 shows the structure of a graphene-based sensor according to a third embodiment of the present invention.

[0049] Figures 4A to 4B The structure of a graphene-based sensor according to a fourth embodiment of the present invention is shown.

[0050] Figure 5 The structure of a graphene-based sensor according to a fifth embodiment of the present invention is shown.

[0051] Figures 6A to 6B The structure of a sensor array according to a first embodiment of the present invention is shown.

[0052] Figures 7A to 7D The structure of a sensor array according to a second embodiment of the present invention is shown.

[0053] Figures 8A to 8D The structure of a sensor array according to a third embodiment of the present invention is shown.

[0054] Figures 9A to 9B A structure of a sensor array according to a fourth embodiment of the present invention is shown.

[0055] Figures 10A to 10B A structure of a sensor array according to a fifth embodiment of the present invention is shown.

[0056] Figures 11A to 11B A structure of a sensor array according to a sixth embodiment of the present invention is shown.

[0057] Fig.12 A structure of a sensor array according to a seventh embodiment of the present invention is shown.

[0058] Figures 13A to 13B A structure of a sensor array according to an eighth embodiment of the present invention is shown.

[0059] Fig.14 A structure of a sensor array according to a ninth embodiment of the present invention is shown.

[0060] Fig.15 A structure of a sensor array according to a tenth embodiment of the present invention is shown.

[0061] Fig.16A and 16B An example of the change in the current of the graphene-based sensor according to the present invention is shown.

[0062] Fig.17 and 18 Various examples of measuring devices using the graphene-based sensor according to the present invention are shown.

[0063] Fig.19 An example of a detailed configuration of a feedback unit and a controller of a measuring device according to the present invention is shown.

[0064] Figures 20 to 26Various examples of measuring devices using the sensor array according to the present invention are shown.

[0065] Fig. 27 A block diagram of a measuring device according to the invention is shown.

[0066] Figures 28 to 29 An implementation example of the measuring device according to the present invention is shown.

[0067] Fig.30 A flow chart showing a method for measuring a sample according to the present invention is shown.

[0068] Fig.31 An example of a method of applying a buffer solution that may be mentioned in various embodiments of the present invention is shown.

[0069] Fig.32 An example of a method of measuring a sample according to the present invention is shown.

[0070] Fig.33 An example of measurement results that may be mentioned in various embodiments of the present invention is shown.

[0071] Fig.34 An example of using the measuring device according to the present invention is shown.

[0072] Fig.35 An example of a method according to the invention for analyzing measurement results is shown.

[0073] Fig.36 An example of an artificial neural network that may be mentioned in various embodiments of the present invention is shown. DETAILED DESCRIPTION

[0074] The various embodiments of the present invention are exemplified for the purpose of clearly explaining the technical spirit of the present invention, and are not intended to be limited to specific embodiments. The technical spirit of the present invention includes various modifications, equivalents and alternatives of the various embodiments described in the present invention, as well as embodiments selectively combined from all or part of the various embodiments. In addition, the scope of the technical concept of the present invention is not limited to the various embodiments presented below or their specific descriptions.

[0075] Unless defined otherwise, all technical or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0076] Expressions used in the present invention such as "include", "may include", "include", "may include", "have", "may have", etc. refer to the existence of any described features (e.g., functions, operations or components) without preventing the existence of other additional features. That is, it should be understood that such expressions are open terms, which include the possibility of including other embodiments.

[0077] Unless otherwise mentioned, singular expressions may include a plural meaning, and the same applies to the singular expressions described in the appended claims.

[0078] The terms “first,” “second,” etc. used herein are used to identify a plurality of components of the same kind from one another and are not intended to limit the order or importance of the related components.

[0079] As used herein, expressions such as "A, B, and C", "A, B or C", "at least one of A, B, and C", or "at least one of A, B, or C" refer to each listed item or all possible combinations of the listed items. For example, "at least one of A or B" may refer to all of (1) at least one A, (2) at least one B, and (3) at least one A and at least one B.

[0080] As used in the present invention, the expression "based on" is used to describe one or more factors that affect the action or operation of the decision and judgment described in the phrase or sentence including the expression, and the expression does not exclude other factors that may affect the action or operation of the decision and judgment.

[0081] As used in the present invention, the expression that a component (e.g., a first component) is “coupled” or “connected” to another component (e.g., a second component) may mean not only being directly coupled or connected to another component but also being coupled or connected through another new component (e.g., a third component).

[0082] As used in the present invention, the expression "configured to" may have meanings such as "configured to", "having the ability to", "modified to", "so as to be able to", and "to". This expression is not limited to the meaning of "specially designed in hardware" and, for example, a processor configured to perform a specific operation may mean a general-purpose processor capable of performing a specific operation by executing software, or a special-purpose computer that is programmed to perform the specific operation.

[0083] The term "~unit" used in the present invention means a software component or a hardware component, such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC). However, the "~unit" is not limited to hardware and software, and the "~unit" can be configured to be in an addressable storage medium or configured to reproduce one or more processors. Therefore, as an example of what can be indicated by a "~unit", the "~unit" includes components such as software components, object-oriented software components, class components and task components, processors, functions, attributes, programs, subroutines, program code segments, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays and variables. In addition, the components and functions provided in the "~unit" can be combined into fewer components and "~units" or further divided into additional components and "~units".

[0084] The term "artificial intelligence (AI)" used in the present invention may refer to a technology that simulates human learning, reasoning or perception abilities and implements them as computers. Specifically, artificial intelligence may perform judgment or prediction based on input data by analyzing the input data and generating output data based on the results of the analysis. In addition, artificial intelligence may perform technology that simulates the cognitive or judgment functions of the human brain (e.g., language understanding, visual understanding, reasoning / prediction, knowledge representation or motion control, etc.). In one embodiment, artificial intelligence may include the concepts of machine learning or symbolic logic.

[0085] The term "machine learning (ML)" used in the present invention may refer to a series of processes for training an artificial neural network model by using data processing experience. Through this machine learning, the artificial neural network model can improve its data processing capabilities.

[0086] The term "artificial neural network model" used in the present invention is constructed by modeling the correlation between data, and the correlation can be represented by a plurality of parameters. This artificial neural network model can be implemented on a computer to include a plurality of network nodes with weights and simulating the structure of the human brain, for example, neurons of a human neural network. The artificial neural network model can optimize the parameters of the artificial neural network model by repeatedly extracting features from given training data and deriving a series of operations of the correlation between data. Optimizing the parameters of the artificial neural network model in this way can be called machine learning. As a specific example, with respect to data given as input / output pairs, the artificial neural network model can learn the mapping (correlation) between input and output, and this can be called supervised learning. As another example, even when only input data is given, the artificial neural network model can still learn the relationship by deriving the regularity between the given data, which can be called unsupervised learning. The artificial neural network model in the present invention can be interchangeably referred to as "artificial neural network", "model", "neural network model", "artificial intelligence learning model" or "machine learning model".

[0087] Hereinafter, various embodiments described in the present invention will be described with reference to the attached drawings. In the attached drawings and the description of the drawings, the same or substantially the same components may be given the same reference numerals. In addition, in the following description of various embodiments, overlapping descriptions of the same or corresponding components may be omitted, but this does not mean that these components are not included in these embodiments.

[0088] Figures 1A to 1D The structure of a graphene-based sensor according to a first embodiment of the present invention is shown. Specifically, Figure 1A is a perspective view of the graphene-based sensor in the first embodiment, Figure 1B is a plan view of the graphene-based sensor in the first embodiment, Figure 1C For along Figure 1A A cross-sectional view taken along line AA' of the graphene-based sensor of the first embodiment of the present invention, and Figure 1D For along Figure 1A FIG. 1 is a cross-sectional view of the graphene-based sensor of the first embodiment taken along line BB′. Figures 1A to 1D Any one of .

[0089] 1 , the graphene-based sensor includes a substrate 100 , an insulator layer 110 , a graphene layer 120 , a first electrode 130 , a second electrode 140 , and a doping region 160 .

[0090] The doping region 160 including impurities doped therein is present in the substrate 100. In one embodiment, the substrate may be a semiconductor layer made of a general semiconductor material such as silicon, germanium, or a compound semiconductor. The doping region 160 may be doped with n-type impurities or p-type impurities. In one embodiment, the doping region 160 may include two regions 150 and 155 having different doping concentrations. For example, the doping region 160 may include a region doped to have a first concentration (e.g., 1*10 8 / cm 3 Up to 5*10 19 / cm 3 ) and doped to a first doping region 150 having a second concentration (≥ the first concentration) (eg, 10 19 / cm 3 In another embodiment, the entire doped region 160 may be doped to have the same concentration. However, for ease of description, the doped region 160 including two regions 150 and 155 doped to have different concentrations is shown in the following description. The area and depth of the doped region 160 may vary.

[0091] The insulator layer 110 is disposed on the substrate 100 except for a portion of the doped region 160. For example, the insulator layer 110 does not exist on top of a portion or all of the first doped region 150 and is disposed on the substrate 100 to be exposed. In one embodiment, the insulator layer 110 may be formed of various oxides such as silicon oxide, hafnium oxide, or aluminum oxide.

[0092] The graphene layer 120 made of graphene is stacked on the doping region 160 not covered by the insulator layer 110. For example, the graphene layer 120 may have a structure stacked on the insulator layer 110 and the doping region 160.

[0093] The first electrode 130 is connected to the graphene layer 120. The second electrode 140 is arranged under the substrate 100 and is connected to the doping region 160. In another embodiment, a through-hole electrode 170 connected to the second electrode 140 on the lower surface of the substrate 100 may be further provided on the upper surface of the substrate 100. The through-hole electrode 170 may pass through the insulator layer 110 and the substrate 100 to be connected to the second electrode 140 under the substrate 100. The connection structure of the first electrode 130 and the second electrode 140 of this embodiment is only an example to facilitate understanding of the present invention, and the scope of the present invention is not limited to this embodiment. Examples of various connection structures of the first electrode 130 and the second electrode 140 are shown in the following Figures 2 to 5.

[0094] A reaction layer 180 formed of a material that reacts with a sample or structure for sensing pressure may be further included on the surface of the graphene layer 120. The type of material constituting the reaction layer may vary according to the type of sample (e.g., light, biological material, gas, etc.). For example, the reaction layer 180 may be formed by applying a biological material (DNA, antigen, antibody, enzyme, etc.), quantum dots (e.g., lead sulfide quantum dots), a polymer film, or the like to the graphene layer 120, or the reaction layer 180 formed of a structure for measuring pressure may be stacked on the graphene layer 120. In another embodiment, the reaction layer 180 may be formed of various materials or various layers. Depending on the type of material of the reaction layer 180 located on the surface of the graphene layer 120, the graphene-based sensor of the present embodiment may be used as various types of sensors, such as an optical sensor for detecting light, a biosensor for detecting biological materials, an environmental sensor for detecting gas, temperature, humidity, or the like.

[0095] Figures 2A to 2D FIG. 2 shows the structure of a graphene-based sensor according to a second embodiment of the present invention. Specifically, Figure 2A is a perspective view of a graphene-based sensor in the second embodiment, Figure 2B is a plan view of the graphene-based sensor in the second embodiment, Figure 2C For along Figure 2A A cross-sectional view taken along line AA' of the graphene-based sensor of the second embodiment of the present invention, and Figure 2D For along Figure 2A FIG. 2 is a cross-sectional view of a graphene-based sensor according to a second embodiment of the present invention taken along line BB'. Figures 2A to 2D Any one of .

[0096] 2 , the graphene-based sensor includes a substrate 200, an insulator layer 210, a graphene layer 220, a first electrode 230, a second electrode 240, and a doping region 260. The substrate 200, the insulator layer 210, the graphene layer 220, and the first electrode 230 have the same structure as in FIG1 . The depth and area of ​​the doping region 260 may be the same as the first embodiment in FIG1 or may be partially modified.

[0097] The first electrode 230 is the same as the first embodiment in FIG1 , but the second electrode 240 is different from the first embodiment in FIG1 . The second electrode 240 is separated from the first electrode 230 and passes through the insulator layer 210 and the substrate 200 to be connected to the doping region 260 (e.g., the first doping region 250 and / or the second doping region 255).

[0098] Figures 3A to 3B The structure of a graphene-based sensor according to a third embodiment of the present invention is shown. Specifically, Figure 3A is a plan view of the graphene-based sensor in the third embodiment, and Figure 3B FIG. 3 is a cross-sectional view of a graphene-based sensor in the third embodiment. Figures 3A to 3B Any one of .

[0099] 3 , the graphene-based sensor includes a substrate 300, an insulator layer 310, a graphene layer 320, a first electrode 330, a second electrode 340, and a doping region 360. Except for the first electrode 330, the configuration of this embodiment is the same as the first embodiment in FIG1 . The graphene-based sensor may further include a reaction layer 380.

[0100] Although the first embodiment of FIG. 1 provides a structure in which the first electrode 130 is located on one side of the graphene layer 120, the first electrode 330 of this embodiment surrounds the periphery (e.g., a rectangular shape) of the graphene layer 320. In another embodiment, the first electrode 230 of the second embodiment may be formed into a shape surrounding the graphene layer 220, like the first electrode 330 of this embodiment.

[0101] Although this embodiment shows two via electrodes 370 connected to the second electrode 340, the number of via electrodes 370 may be variously modified according to the embodiment. In another embodiment, the via electrode 370 may be omitted.

[0102] Figures 4A to 4B The structure of a graphene-based sensor according to a fourth embodiment of the present invention is shown. Specifically, Figure 4A is a plan view of the graphene-based sensor of the fourth embodiment, and Figure 4B FIG4 is a cross-sectional view of the graphene-based sensor of the fourth embodiment. Figures 4A to 4BAny one of them.

[0103] 4 , the graphene-based sensor includes a substrate 400, an insulator layer 410, a graphene layer 420, a first electrode 430, a second electrode 440, and a doping region 460. Compared with the first to third embodiments, the present embodiment further includes a plurality of electrodes 432, 434, 470, and 472. In the present embodiment, for convenience of description, additional electrodes 432, 434, 470, and 472 are shown based on the structure of the first embodiment (i.e., a structure including through-hole electrodes). However, the present embodiment may be implemented based on the structure of the second or third embodiment.

[0104] The third electrode 432 and the fourth electrode 434 are formed in contact with the graphene layer 420 to be spaced apart from the first electrode 430. The third electrode 432 and the fourth electrode 434 together with the first electrode 430 may be used to identify a bonding error of the first electrode 430 (e.g., a bonding error between the first electrode 430 and the graphene layer 420, etc.), or the third electrode 432 or the fourth electrode 434 may be used in the case of a bonding error of the first electrode 430.

[0105] The fifth electrode 472 and the sixth electrode 474 pass through the insulator layer 410 and the substrate 400 and are connected to the second electrode 440 formed under the substrate 400. Therefore, when a bonding error and the like occur in the through-hole electrode 470, the fifth electrode 472 or the sixth electrode 474 may be used. In addition, the through-hole electrode 470 and the fifth electrode 472 (or the sixth electrode 474) may be used to identify whether the through-hole electrode 470 is normally bonded to the second electrode 440.

[0106] According to an embodiment, the graphene-based sensor may include only a portion of the third to sixth electrodes 432, 434, 472, and 474. For example, various modifications such as making the graphene-based sensor include only the third electrode 432, or only the third electrode 432 and the fifth electrode 472 are possible.

[0107] An embodiment of implementing a substrate using a general semiconductor material has been described with reference to FIGS. 1 to 4. Figure 5 Embodiments of implementing a substrate using two-dimensional materials are described.

[0108] Figure 5 The structure of a graphene-based sensor according to a fifth embodiment of the present invention is shown.

[0109] refer to Figure 5, the graphene-based sensor 500 includes a substrate 510, a two-dimensional semiconductor layer 520, a graphene layer 530, a first electrode 540, and a second electrode 550. According to an embodiment, the graphene-based sensor 500 may be implemented with or without a reaction layer 560. Hereinafter, for convenience of description, it is assumed that the reaction layer 560 exists in the graphene-based sensor 500. In addition, a structure surrounding the periphery of the reaction layer 560 may be formed to prevent the sample from flowing out of the reaction layer.

[0110] The two-dimensional semiconductor layer 520 is formed by laminating a two-dimensional material onto the substrate 510. For example, the two-dimensional semiconductor layer 520 may be implemented using Si, Ge, WS2, or MoS. In addition, the two-dimensional semiconductor layer 520 may be implemented using various types of two-dimensional materials.

[0111] The graphene layer 530 is formed by stacking graphene on the substrate 510 and the two-dimensional semiconductor layer 520 .

[0112] The first electrode 540 is stacked in contact with the two-dimensional semiconductor layer 520, and the second electrode 550 is stacked in contact with the graphene layer 530. That is, the first electrode 540 is connected to the two-dimensional semiconductor layer 520, and the second electrode 550 is connected to the graphene layer.

[0113] The reaction layer 560 is located on the surface of the region where the two-dimensional semiconductor layer 520 and the graphene layer 530 are stacked. The reaction layer 560 includes a material that induces charge in the graphene layer 530. The type of material constituting the reaction layer 560 may vary according to the type of sample (e.g., light, biological material, gas, etc.). For example, the reaction layer 560 may be formed by applying a biological material (e.g., DNA, antigen, antibody, or enzyme), a quantum dot (e.g., lead sulfide quantum dot), or a polymer film to the graphene layer 530, or a reaction layer 560 formed of a structure for measuring pressure may be stacked on the graphene layer 530. In another embodiment, the reaction layer 560 may include various materials or various layers. Depending on the material type of the reaction layer 560 located on the surface of the graphene layer 530, the graphene-based sensor 500 of this embodiment may be used as various types of sensors, such as an optical sensor for detecting light, a biosensor for detecting biological materials, an environmental sensor for detecting gas, temperature, humidity, or the like.

[0114] The sensor array may be made by arranging one or more of the graphene-based sensors of the first to fifth embodiments. When the sensor array includes a plurality of graphene-based sensors, the sensor array may include a graphene-based sensor having the same structure or a mixture of the graphene-based sensors of the first to fifth embodiments. However, for convenience of description, the sensor array formed by arranging a plurality of graphene-based sensors having the same structure will be described below.

[0115] Figures 6A to 6B The structure of the sensor array according to the first embodiment of the present invention is shown. Specifically, Fig. 6A is a plan view of the sensor array of the first embodiment, and Figure 6B For along Fig. 6A The term "FIG. 6" may refer to a cross-sectional view of the sensor array of the first embodiment of the present invention taken along line AA'. Figures 6A to 6B Any one of .

[0116] 6 , the sensor array has a structure in which a plurality of graphene-based sensors are arranged in one dimension. The graphene-based sensors constituting the sensor array are based on the structure of the third embodiment in FIG. 3 . That is, the graphene-based sensor includes a substrate 600, an insulator layer 610, a graphene layer 620, a first electrode 630, a second electrode 640, and a doped region 660. The sensor array may further include an output terminal 632 configured to output a measurement value (e.g., an electrical signal such as a current or a voltage) of each graphene-based sensor. The output terminal 632 may correspond to the fourth electrode 434 described with reference to FIG. 4 .

[0117] The second electrodes 640 of the plurality of graphene-based sensors constituting the sensor array are common electrodes connected to each other. In other words, the common electrode 690 vertically formed across the plurality of graphene-based sensors may be formed on the rear surface of the substrate 600. Although the through-hole electrode 670 is shown in this embodiment, the through-hole electrode 670 may be omitted according to this embodiment.

[0118] The reaction layers 680 of the plurality of graphene-based sensors constituting the sensor array may all include the same material or may include different materials (A1, A2, and A3). For example, a sensor array configured to detect the wavelength or intensity of light may be implemented by using reaction layers 680 formed of different quantum dot materials for each graphene-based sensor. Alternatively, a sensor array configured to detect the type and / or amount of biomolecules may be implemented by using reaction layers 680 formed of biomolecules having different degrees of reaction to biomolecules (e.g., at least one of DNA, RNA, antigens, antibodies, and enzymes) for each graphene-based sensor. For example, the sensor array may identify coronaviruses and avian influenza viruses, or SARS-CoV-1 and SARS-CoV-2 among the coronaviruses. Alternatively, a sensor array configured to detect the type and / or amount of gas may be implemented by using reaction layers 680 formed of biomolecules having different degrees of reaction to specific gas molecules for each graphene-based sensor. Alternatively, the reaction layer 680 of the sensor array may be formed by combining materials that react with quantum dots, biomolecules, gas molecules, and the like so that light, biomolecules, and gas molecules can be detected simultaneously through a single sensor array.

[0119] When the materials or structures of the reaction layers 680 of the graphene-based sensors constituting the sensor array are different, the thickness of the insulator layer 610 may be at a predetermined height to prevent the materials of the reaction layers 680 of the graphene-based sensors from being mixed with each other.

[0120] Figures 7A to 7D The structure of the sensor array according to the second embodiment of the present invention is shown. Specifically, Fig. 7A is a plan view of the sensor array of the second embodiment, Figure 7B For the second embodiment Fig. 7A A cross-sectional view of the sensor array along line A-A', Figure 7C For the second embodiment Fig. 7A An example of a cross-sectional view taken along line BB' of the sensor array in FIG. 1 , and Fig.7D For along Fig. 7A Another example of a cross-sectional view taken along line BB' of the sensor array of the second embodiment of the present invention. The term "FIG. 7" may refer to Figures 7A to 7D Any one of .

[0121] 7 , the sensor array includes a plurality of graphene-based sensors. Each graphene-based sensor constituting the sensor array includes a substrate 700, an insulator layer 710, a graphene layer 720, a first electrode 730, a second electrode 740, and a doping region 760. The graphene-based sensor of this embodiment is obtained by partially modifying the structure of the second embodiment of FIG. 2 .

[0122] The graphene layers 720 of the plurality of graphene-based sensors are connected to each other. In other words, the graphene layer 720 of the sensor array spans the plurality of graphene-based sensors stack. Therefore, the first electrode 730 connected to the graphene layer 720 is a shared electrode of the plurality of graphene-based sensors. The shared electrode is the second electrode 640 in the case of the sensor array in FIG. 6 , and the shared electrode is the first electrode 730 in this embodiment. The second electrode 740 is present in each graphene-based sensor. In addition, each graphene-based sensor may further include an output terminal 742 for outputting a measurement value.

[0123] As another example, the insulator layer 710 may be formed in a stepwise manner (see Figure 7C and 7D ). This embodiment provides two examples together according to the height of the insulator layer 710. For example, the region of the insulator layer 710 where the first electrode 730 exists may be formed higher than its edge region (see Figure 7C ). In this case, the sample is prevented from flowing out of the sensor array.

[0124] Figures 8A to 8D The structure of the sensor array according to the third embodiment of the present invention is shown. Specifically, Fig. 8A is a plan view of the sensor array of the third embodiment, Figure 8B For the third embodiment Fig. 8A A cross-sectional view of the sensor array along line A-A', Figure 8C For the third embodiment Fig. 8A An example of a cross-sectional view taken along line BB' of the sensor array in FIG. 1 , and Fig.8D For the third embodiment Fig. 8A Another example of a cross-sectional view taken along line BB' of a sensor array in FIG. Figures 8A to 8D Any one of .

[0125] 8 , the sensor array includes a plurality of graphene-based sensors. Each of the graphene-based sensors constituting the sensor array includes a substrate 800 , an insulator layer 810 , a graphene layer 820 , a first electrode 830 , a second electrode 840 , and a doping region 860 .

[0126] The doping region 860 is formed longitudinally in the vertical direction of the substrate 800 to span across the plurality of graphene-based sensors. For example, when the doping region 860 is formed of a plurality of regions having different concentrations, the doping region 860 includes a second doping region 855 spanning all of the plurality of graphene-based sensors, and a plurality of first doping regions 850, 851, and 852 corresponding to the graphene layer 820 of each graphene-based sensor.

[0127] The second electrode 840 passes through the insulator layer 810 to connect to the doping region 860, as in the second embodiment of FIG. 2. Although the structure including two second electrodes 840 and 842 is shown in this embodiment, the number of second electrodes 840 and 842 can be variously modified according to the embodiment. Since the second electrode 840 is connected to the doping region 860 across all the plurality of graphene-based sensors, the second electrode 840 becomes a shared electrode for the plurality of graphene-based sensors. The first electrode 830 exists in each graphene-based sensor. An output terminal 832 for outputting a measurement value by each graphene-based sensor may be further included.

[0128] In another embodiment, the insulator layer 810 can be formed in a stepwise manner (see Figure 8C and 8D ). This embodiment provides two examples together according to the height of the insulator layer 810. For example, the region of the insulator layer 810 where the second electrode 840 exists may be formed higher than its edge region, such as Figure 7C The examples shown in Figure 8C In another embodiment, separate further electrodes 892 and 894 connected to the doped region 760 may be further provided on the lower surface of the substrate 800 .

[0129] Figures 9A to 9B and Figures 10A to 10B The structure of the sensor array according to the fourth and fifth embodiments of the present invention is shown. Specifically, Fig. 9A FIG. 4 is a plan view of the sensor array according to the fourth embodiment. Fig. 9B For the fourth embodiment Fig. 9A The cross-sectional view of the sensor array line A-A' is obtained using, Fig. 10A is a plan view of the sensor array of the fifth embodiment, and Fig. 10B For the fifth embodiment Fig. 10A The term "FIG. 9" may refer to a cross-sectional view of a sensor array taken along line A-A' in FIG. Figures 9A to 9B Any of the above, and the term "Figure 10" may refer to Figures 10A to 10B Any one of .

[0130] 9 and 10 , the sensor array includes output units 950 and 1050 on substrates 900 and 1000, respectively. Each graphene-based sensor constituting the sensor array includes a substrate 900 or 1000, an insulator layer 910 or 1010, a graphene layer 920 or 1020, a first electrode 930 or 1030, a second electrode 940 or 1032, and a doping region 960 or 1060. Reaction layers 980 and 1080 may be further provided on the surfaces of the graphene layers 920 and 1020, respectively. The structure of the sensor array of FIG. 9 is a structure partially modified from the structure of FIG. 7 , and the structure of the sensor array of FIG. 10 is a structure partially modified from the structure of FIG. 8 .

[0131] The output units 950 and 1050 may be implemented as semiconductor circuits on the substrates 900 and 1000 , respectively.

[0132] The output units 950 and 1050 include terminals 972 and 1072 for receiving address signals, output terminals 974 and 1074, and the like, respectively. The output units 950 and 1050 are respectively connected to the output terminal 970 of the plurality of graphene-based components of the sensor array. When receiving the address signal, the output unit 950 or 1050 selectively outputs the signal (e.g., measurement value) received through the output terminal of the corresponding graphene-based component in the plurality of graphene-based components. For example, the output units 950 and 1050 may be implemented as a multiplexer circuit. Reference Figures 17 to 26 Various embodiments of output units 950 and 1050 are shown.

[0133] Figures 11A to 11B The structure of the sensor array according to the sixth embodiment of the present invention is shown. Specifically, Fig.11A is a plan view of the sensor array of the sixth embodiment, and Fig. 11B For the sixth embodiment Fig.11A The term "FIG. 11" may refer to a cross-sectional view of a sensor array taken along line A-A' in FIG. Figures 11A to 11B Any one of .

[0134] 11 , the sensor array has a structure in which graphene-based sensors are arranged in an n*m form (n, m are natural numbers greater than or equal to 2). Each graphene-based sensor includes a substrate 1100, an insulator layer 1110, a graphene layer 1120, a first electrode 1130, a second electrode 1140, and a doping region 1160. In addition, each graphene-based sensor of the sensor array can be implemented in the structure of the various embodiments shown in FIGS. 1 to 5 .

[0135] The graphene layer 1120 is stacked on a plurality of graphene-based sensors in columns. For example, the graphene layers of three graphene-based sensors in the first column are connected to each other. Therefore, the shared first electrode 1130 exists in each column.

[0136] The doping regions 1160 exist in a row unit on a plurality of graphene-based sensors. For example, the doping regions of three graphene-based sensors located in the first row are connected to each other, the doping regions of three graphene-based sensors located in the second row are connected to each other, and the doping regions of three graphene-based sensors located in the third row are connected to each other. Therefore, the shared second electrode 1140 exists in a row unit. For example, as shown in FIG. 8 , the second electrode 1140 passes through the insulator layer 1110 to be connected to the doping regions 1160 existing in each row.

[0137] The measurement value of the desired graphene-based sensor among the plurality of graphene-based sensors may be output through the plurality of first electrodes 1130, 1131, and 1132 and the plurality of second electrodes 1140, 1141, and 1142. For example, the B2 sensor may operate by applying a signal to the first electrode in the first column and the second electrode in the second row.

[0138] A first multiplexer 1150 and a second multiplexer 1170 may be included to selectively control the operation of each graphene-based sensor and selectively output the measured value of each graphene-based sensor. In one embodiment, the first multiplexer 1150 and the second multiplexer 1170 may be implemented as a semiconductor circuit on the substrate 1100. The first multiplexer 1150 may be connected to a plurality of second electrodes 1140, 1141 and 1142, and the second multiplexer 1170 may be connected to the output terminals (not shown) of the plurality of graphene-based sensors. For example, when receiving an address signal, the first multiplexer 1150 receives a signal corresponding to a row of the address signal in the plurality of second electrodes 1140, 1141 and 1142 and outputs the signal, and when receiving an address signal, the second multiplexer 1170 receives a signal corresponding to a column of the address signal and outputs the signal.

[0139] Fig.12 A structure of a sensor array according to a seventh embodiment of the present invention is shown.

[0140] refer to Fig.12 , the structure of the plurality of graphene-based sensors 1210 and the two multiplexers 1220 and 1230 of the sensor array is the same as that of FIG11. The present embodiment further includes an amplifier 1240. The amplifier 1240 is connected to the second multiplexer 1230 to amplify the output signal of the second multiplexer 1230. The sensor array including the amplifier 1240 of the present embodiment can be implemented in a chip form.

[0141] Figures 13A to 13B The structure of the sensor array according to the eighth embodiment of the present invention is shown. Specifically, Fig.13A is a plan view of the sensor array of the eighth embodiment, and Fig. 13B FIG. 13 is a cross-sectional view of the sensor array of the eighth embodiment. Figures 13A to 13B Any one of .

[0142] Referring to FIG. 13 , the sensor array includes a plurality of graphene-based sensors 1360. The structure of the sensor array may be any one of the structures of FIGS. 6 to 12 . In addition, the structure of the sensor array may be the structure of the sensor array described later. Figures 14 to 15 The sensor array 1360 also includes a storage unit 1340 and a channel unit 1350 .

[0143] The storage unit 1340 is formed by etching the substrate 1300 to a predetermined depth and width. The plurality of graphene-based sensors are connected to the storage unit 1340 through the channel unit 1350. The channel unit 1350 may be formed by etching a portion of the insulator layer 1310 between the plurality of graphene-based sensors 1360 and the storage unit 1340 to a predetermined depth and width.

[0144] The depth and width of the channel unit 1350 may be formed smaller than the depth and width of the storage unit 1340, so that among the samples stored in the storage unit 1340, only materials having a predetermined size or less are transferred to the plurality of graphene-based sensors 1360 through the channel unit 1350. For example, when the sample is blood, the channel unit 1350 may be formed to have a width smaller than a predetermined width (e.g., smaller than 6 μm), so that only materials other than red blood cells and white blood cells are transferred to the graphene-based sensors 1360.

[0145] Although the sensor array structure in this embodiment further includes a storage unit 1340 and a channel unit 1350 , the configuration of the storage unit 1340 and the channel unit 1350 can also be applied to the single graphene-based sensor described with reference to FIGS. 1 to 5 .

[0146] Fig.14 A structure of a sensor array according to a ninth embodiment of the present invention is shown.

[0147] refer to Fig.14 , the sensor array 1400 includes a plurality of sensing regions 1430, 1432, 1434, and 1436 in which two-dimensional semiconductor layers 1410, 1412, 1414, and 1416 and a graphene layer 1420 are stacked. The plurality of sensing regions 1430, 1432, 1434, and 1436 each serve as a reference Figure 5Graphene-based sensors described.

[0148] A plurality of two-dimensional semiconductor layers 1410, 1412, 1414, and 1416 are arranged on a substrate to be spaced apart from each other, and a graphene layer 1420 is stacked on the plurality of two-dimensional semiconductor layers 1410, 1412, 1414, and 1416. For example, the plurality of two-dimensional semiconductor layers 1410, 1412, 1414, and 1416 may be arranged to be spaced apart from each other in a first direction (e.g., a vertical direction) at predetermined intervals, and the graphene layer 1420 may be stacked in a second direction (e.g., a horizontal direction) perpendicular to the first direction across the plurality of two-dimensional semiconductor layers 1410, 1412, 1414, and 1416. The graphene layer 1420 is commonly connected to a plurality of sensing regions 1430, 1432, 1434, and 1436.

[0149] In one embodiment, the plurality of two-dimensional semiconductor layers 1410, 1412, 1414, and 1416 may be implemented using the same two-dimensional material or different two-dimensional materials. Alternatively, only some of the two-dimensional semiconductor layers (at least two of 1410, 1412, 1414, and 1416) may be implemented using different two-dimensional materials.

[0150] In another embodiment, the sensing regions 1430, 1432, 1434, and 1436 in which the plurality of two-dimensional semiconductor layers 1410, 1412, 1414, and 1416 and the graphene layer 1420 are stacked may have different sizes. For example, at least two of the two-dimensional semiconductor layers 1410, 1412, 1414, and 1416 may have different widths. Alternatively, the widths of the graphene layer 1420 corresponding to the sensing regions 1430, 1432, 1434, and 1436 may be implemented differently.

[0151] Although only the two-dimensional semiconductor layers 1410, 1412, 1414 and 1416 and the graphene layer 1420 are shown in this embodiment for the convenience of description, the structure of each sensing region 1430, 1432, 1434 or 1436 may include the same Figure 5 For example, a plurality of first electrodes (not shown) are connected to a plurality of two-dimensional semiconductor layers 1410, 1412, 1414, and 1416, and a second electrode (not shown) may be connected to the graphene layer 1420.

[0152] A reaction layer (not shown) may exist in each of the sensing regions 1430, 1432, 1434, and 1436 in which the two-dimensional semiconductor layers 1410, 1412, 1414, and 1416 and the graphene layer 1420 are stacked. Materials constituting the reaction layers of the respective sensing regions may be the same or different from each other.

[0153] Fig.15A structure of a sensor array according to a tenth embodiment of the present invention is shown.

[0154] refer to Fig.15 The sensor array 1500 includes a plurality of sensing regions 1580, 1582, 1584, 1586, 1588, and 1590 in which two-dimensional semiconductor layers 1510, 1512, 1514, 1516, 1518, and 1520 and a graphene layer 1530 are stacked. The plurality of two-dimensional semiconductor layers 1510, 1512, 1514, 1516, 1518, and 1520 may be radially arranged on a substrate spaced apart from one another, and the graphene layer 1530 may be stacked on the plurality of two-dimensional semiconductor layers 1510, 1512, 1514, 1516, 1518, and 1520 in a circular belt shape.

[0155] A plurality of first electrodes 1540 , 1542 , 1544 , 1546 , 1548 and 1550 are respectively connected to the plurality of two-dimensional semiconductor layers 1510 , 1512 , 1514 , 1516 , 1518 and 1520 , and a second electrode 1570 is connected to the graphene layer 1530 .

[0156] The sensor array 1500 may further include a third electrode 1560 commonly connected to the plurality of two-dimensional semiconductor layers 1510, 1512, 1514, 1516, 1518, and 1520. Since the plurality of two-dimensional semiconductor layers 1510, 1512, 1514, 1516, 1518, and 1520 are arranged radially, the third electrode 1560 may be disposed inside the radial arrangement thereof to be commonly connected to the plurality of two-dimensional semiconductor layers 1510, 1512, 1514, 1516, 1518, and 1520. The states (e.g., failure, etc.) of the respective two-dimensional semiconductor layers 1510, 1512, 1514, 1516, 1518, and 1520 may be inspected through the plurality of first electrodes 1540, 1542, 1544, 1546, 1548, and 1550 and the third electrode 1560.

[0157] The sensor array 1500 may further include a fourth electrode 1572 connected to the graphene layer 1530. For example, the graphene layer 1530 may have a partially open circular band shape, and the second electrode 1570 and the fourth electrode 1572 may be respectively connected to both ends of the graphene layer 1530. The state of the graphene layer 1530 (e.g., a fault state, etc.) may be checked through the second electrode 1570 and the fourth electrode 1572.

[0158] The sensing values ​​of the sensing regions 1580 , 1582 , 1584 , 1586 , 1588 , and 1590 may be measured through the second electrode 1570 and a plurality of first electrodes 1540 , 1542 , 1544 , 1546 , 1548 , and 1550 respectively connected to a plurality of two-dimensional semiconductor layers 1510 , 1512 , 1514 , 1516 , 1518 , and 1520 .

[0159] The frequency or intensity of light, biomolecules, gas molecules, or pressure can be detected using the sensor array described with reference to Figures 6 to 15. For example, the graphene layer of each graphene-based sensor or the reaction layer located on the surface of the sensing area can be formed of antibodies to various viruses or bacteria to detect the type of antigens possessed by the sample. Alternatively, the reaction layer can be formed of antigens including specific proteins of various viruses or bacteria to detect the type of antibodies possessed by the sample. Alternatively, the reaction layer can be formed of antibodies that react to various pathogens to different degrees to detect the type of pathogen. Alternatively, the reaction layer can be formed of various enzymes to detect various types of materials that react with the enzymes.

[0160] In another embodiment, the reaction layer of the graphene-based sensor constituting the sensor array may be formed of molecules that react to specific gas molecules to different degrees to detect the type and amount of the gas molecules. In another embodiment, the reaction layer may be formed of a structure that reacts to pressure to detect the intensity of the pressure.

[0161] In another embodiment, the reaction layers of a plurality of graphene-based sensors constituting the sensor array may be formed of nucleic acids to detect the sequences of the nucleic acids. For example, the material of the reaction layer may be formed of a single-stranded nucleic acid of about 20 base pairs to implement a sensor array capable of detecting even base pairs. For example, the reaction layer of a first graphene-based sensor may be formed of a nucleic acid having a complementary sequence relative to a first nucleic acid having a specific sequence, and the reaction layer of a second graphene-based sensor may be formed of a nucleic acid having a complementary sequence relative to a second nucleic acid in which a portion of the first nucleic acid is mutated. If a sample having concentrations of C1 and C2 of the first nucleic acid and the second nucleic acid, respectively, is input into the sensor array, the measurement values ​​(S1, S2) obtained by the sensor array are shown as follows,

[0162] [Equation 1]

[0163]

[0164] Among them, M nm Indicates the signal amplitude indicated by the graphene-based sensor when a nucleic acid with a sequence of n is combined with a complementary sequence with a sequence of m. nm It can be identified and defined in advance through experiments. From the above equations, the concentrations of the first nucleic acid and the second nucleic acid in the sample can be obtained as follows.

[0165] [Equation 2]

[0166]

[0167] That is, the concentrations of the first nucleic acid and the second nucleic acid of the sample can be identified by the measurement values ​​S1 and S2 identified by the sensor array. Although the above example is described using two types of nucleic acids, three or more types of nucleic acids can be detected by the same method.

[0168] In another embodiment, the concentration of various substances (e.g., calcium, sodium, blood glucose, etc.) in the blood can be measured. The reaction layer of the graphene-based sensors constituting the sensor array can be formed of various enzymes or channels to detect the concentration of ions and blood glucose in the blood. For example, the reaction layer of the first graphene-based sensor can be formed of glucose oxidase and the reaction layer of the second graphene-based sensor can be formed of potassium channels to measure the concentration of glucose and potassium in the blood. In addition, the sensor array can be configured to include various enzyme reactions and various channels to simultaneously measure the concentration of various materials in the sample.

[0169] Fig.16A and 16B An example of current variation of a graphene-based sensor according to the present invention is shown. Specifically, Fig.16A shows the current variation of the graphene-based sensor, and Fig. 16B The term "Figure 16" may refer to Figures 16A to 16B Any one of .

[0170] Referring to FIG. 16 , the output currents 1600 and 1610 of the graphene-based sensor vary according to the degree of reaction of the reaction layer. In addition, the output currents 1610 and 1610 of the graphene-based sensor may vary according to the type of material constituting the reaction layer. However, the graphene-based sensor can accurately measure small changes in electrical signals because the sensitivity of the output currents 1600 and 1610 of the graphene-based sensor of the present embodiment is greater than the output currents 1650 and 1660 of the transistor-based sensor of the related art. The wavelength or intensity of light, the type or amount of biomolecules, the type or amount of gas molecules, or the intensity of pressure can be detected using the changes in the output currents 1600 and 1610.

[0171] The output currents 1600 and 1610 of the graphene-based sensor vary in a logarithmic scale, and therefore their measurement range is very wide, making it difficult to measure them accurately. Figures 17 to 26 Methods and apparatus are presented for converting the output currents 1600 and 1610 of the graphene-based sensor into a voltage within a predetermined range (eg, 0 to 10 V, etc.) and measuring the voltage.

[0172] Fig.17 and 18 Various examples of measuring devices using the graphene-based sensor according to the present invention are shown.

[0173] refer to Fig.17 and 18 , the measuring device includes a graphene-based sensor 1710 or 1810 and an output unit 1720 or 1820. The graphene-based sensor 1710 or 1810 may be implemented in the form of a chip 1700 or 1800. The output unit 1720 or 1820 includes a pre-amplification unit 1730 or 1830 and a feedback unit 1740 or 1840. According to an embodiment, the measuring device may further include a controller 1750 or 1850.

[0174] The pre-amplifier unit 1730 or 1830 converts the output current of the graphene-based sensor 1710 or 1810 into a voltage. In other words, when receiving a current as an input, the pre-amplifier unit 1730 or 1830 outputs a voltage within a predetermined range. In one embodiment, the pre-amplifier unit 1730 or 1830 may include an amplifier and a variable resistor, and the output voltage of the amplifier is adjusted by adjusting the variable resistor so that it is within a predetermined range (e.g., 0 to 10V). The structure of the pre-amplifier unit 1730 or 1830 of the present embodiment is only an example for understanding, and various circuit structures in the related field of converting a current input into a voltage and outputting the voltage can be used in the pre-amplifier unit 1730 or 1830 of the present embodiment.

[0175] The feedback unit 1740 or 1840 performs feedback control on the output voltage of the pre-amplification unit 1730 or 1830 according to the set point of the controller 1750 or 1850 and outputs it. As shown in FIG. 16, the graphene-based sensor 1710 or 1810 displays different graphs of the output currents 1600 and 1610 according to the reaction material in the reaction layer, and therefore, the feedback unit 1740 or 1840 adjusts the output voltage of the pre-amplification unit 1730 or 1830 according to the set point. For example, when the output voltage of the pre-amplification unit 1730 or 1830 ranges from 0 to 10V and the set point is 1V, the feedback unit 1740 or 1840 adjusts the output voltage of the pre-amplification unit 1730 or 1830 to a point between 0 and 1V and outputs it. The feedback unit 1740 or 1840 configured to adjust the range of the output voltage according to the set point may be implemented as an analog circuit or as a digital signal processor (DSP). Fig.19 An example of a feedback unit implemented as a DSP is shown in FIG.

[0176] The connection between the pre-amplification unit 1730 or 1830 and the graphene-based sensor 1710 or 1810 can be implemented in various forms. Fig.17 , the (-) terminal of the amplifier may be connected to the output terminal of the graphene-based sensor 1710, and the (+) terminal of the amplifier may be connected to the output of the feedback unit 1740. Fig.18 , the (-) terminal of the amplifier may be connected to the output terminal of the graphene-based sensor 1810, and the (+) terminal of the amplifier may be connected to the ground. In this case, the remaining electrodes of the graphene-based sensor 1810 may be connected to the output of the feedback unit 1840.

[0177] Fig.19 An example of a detailed configuration of a feedback unit and a controller of a measuring device according to the present invention is shown.

[0178] refer to Fig.19 , the feedback unit 1900 is implemented as a DSP. When the feedback unit 1900 receives a voltage within a predetermined range (e.g., a first range), the feedback unit 1900 performs feedback control on the value of the output voltage of the pre-amplification unit 1730 or 1830 described above and adjusts the value to a voltage within a predetermined range (e.g., a second range < the first range) to output it. Various circuit structures in the related art configured to perform feedback control on the output voltage of the pre-amplification unit 1730 or 1830 to output a voltage within a predetermined range can be applied to the feedback unit 1900 of the present embodiment, and the feedback unit 1900 is not limited to the structure of the present embodiment. The measuring device may further include a display unit 1920, a communication unit 1930, an input unit 1940, and the like together with the control unit 1910.

[0179] Figures 20 to 26 Various examples of measuring devices using the sensor array according to the present invention are shown.

[0180] refer to Fig. 20 The measuring device includes a plurality of output units 2020, 2022, 2024 and 2026, which output the measurement values ​​of the plurality of graphene-based sensors 2010, 2012, 2014 and 2016 included in the sensor array 2000. Each of the output units 2020, 2022, 2024 and 2026 can be Fig.17 For example, when the sensor array 2000 includes four graphene-based sensors 2010, 2012, 2014, and 2016, four output units 2020, 2022, 2024, and 2026 are respectively connected to the graphene-based sensors 2010, 2012, 2014, and 2016. Since as many output units as the number of graphene-based sensors included in the sensor array 2000 are required, the size of the measuring device increases in proportion to the number of the graphene-based sensors.

[0181] refer to Fig.21 and 22 , the measuring device includes an output unit to which a multiplexer 2100 or 2200 is added. Fig. 20 In the embodiment of the present invention, the sensor array 2000 needs to include as many output units as the number of graphene-based sensors included therein, but in this embodiment, only one output unit is required. The multiplexer 2100 or 2200 selectively receives the output currents of the plurality of graphene-based sensors from the sensor array 2000 and outputs a voltage. Fig.21 To connect the multiplexer 2100 to Fig.17 The structure obtained by the components of the output unit 1720 in Fig. 22 To connect the multiplexer 2200 to Fig.18 The structure obtained by the components of the output unit 1820.

[0182] refer to Fig.23 and 24 , the sensor array and the multiplexer 2300 or 2400 are implemented as a single chip. In this case, the sensor array selectively outputs the measurement values ​​of the plurality of graphene-based sensors through the multiplexer 2300 or 2400, and thus the output unit 2310 or 2410 can be configured as a single component. Fig.23 The output unit 2310 and Fig.17 The output unit 1720 is the same as that of Fig.24 The output unit 2410 and Fig.18 The output unit 1820 is the same.

[0183] refer to Fig.25 and 26 , the sensor array, the multiplexer 2510 or 2610 and the pre-amplification unit 2520 or 2620 are implemented as a single chip 2500 or 2600. The output unit 2530 or 2630 includes a feedback unit and a control unit. Fig.25 The output unit 2530 in Fig.18 The output unit 1820 is implemented as follows, and Fig.26 The output unit 2630 in Fig.17 The structure of the output unit 1720 is implemented.

[0184] Fig. 27 A block diagram of a measuring device according to the invention is shown.

[0185] Hereinafter, the sensor measuring device 2700 will be described as an example of a measuring device. The sensor measuring device 2700 may be implemented as a computing device that performs computing functions.

[0186] refer to Fig. 27The sensor measuring device 2700 includes a voltage applying unit 2702 and a measuring unit 2704. The sensor measuring device 2700 can be implemented in various forms, and Figures 17 to 26 It can be called an example. The sensor 2710 can output different currents or resistances according to the type of sample. Various types of sensors 2710 can be used in this embodiment. In another embodiment, a graphene-based sensor can be used to increase the sensitivity of the sensor. Figures 1 to 15 and 17 to 26 can be called examples of graphene-based sensors.

[0187] The voltage applying unit 2702 applies at least one voltage within a predetermined voltage range to the sensor 2710. For example, the voltage applying unit 2702 inputs a voltage between 0 and 2V to the sensor 2710 at fixed intervals (for example, 0.1V intervals). According to embodiments, the voltage range and the voltage applying interval may be variously modified.

[0188] The measuring unit 2704 measures the resistance or current of the sensor 2710 according to the application of the voltage. The measuring unit 2704 detects the resistance or current of the sensor for each voltage. For example, the measuring unit 2704 detects the measured value of the resistance or current of the sensor 2710 according to the application of the voltage before the sample is applied, and detects the measured value of the resistance or current of the sensor 2710 according to the application of the voltage after the sample is applied. Figures 30 to 33 A measurement method using the sensor measurement device 2700 is described.

[0189] The measurement unit 2704 may display the measurement results through a screen interface, output whether the sample is recognized through voice, or transmit the measurement results to an external device through a wired or wireless communication network. The type of information displayed or transmitted by the measurement unit 2704 may be modified in various ways according to the embodiment.

[0190] Figures 28 to 29 An implementation example of the measuring device according to the present invention is shown.

[0191] refer to Fig.28 , the measuring device 2800 can be implemented in a small portable size. An insertion hole 2810 into which a diagnostic test strip can be inserted is provided in one side of the measuring device 2800. The diagnostic test strip 2810 has a long and thin rod shape, and the diagnostic test strip 2810 on which a sample is smeared can be inserted into the insertion hole 2810 of the measuring device 2800.

[0192] As an example, the measuring device 2800 can transmit the measured values ​​of the graphene-based sensor to an external device, such as a smart phone. Fig.34An example of using the measuring device will be described. In another embodiment, the measuring device 2800 may further include internal circuitry capable of analyzing the measurement values ​​provided by the graphene-based sensor. Figures 35 to 36 In addition, the measuring device 2800 may further include a display capable of displaying the analysis result or a communication unit capable of transmitting the analysis result to the outside via a wired or wireless network.

[0193] refer to Fig.29 The measuring device 2900 includes a plurality of insertion holes 2910 into which a plurality of diagnostic test strips can be inserted, and a plurality of graphene-based sensors capable of simultaneously analyzing the plurality of diagnostic test strips inserted through the insertion holes 2910. The plurality of graphene-based sensors included in the measuring device 2900 may exist individually in each insertion hole 2910 or may exist in the sensor array structure described above.

[0194] The measuring device 2900 may include internal circuitry capable of analyzing the output values ​​of a plurality of graphene-based sensors. Figures 35 to 36 The measuring device 2900 may further include a display unit configured to display the analysis result, and a communication unit capable of transmitting the analysis result to an external device.

[0195] In another embodiment, quantitative analysis of a sample may be performed using Fig.28 The measuring device 2800 or 2900 of 29 is used. Fig.28 As shown in FIG. 2 , when the measuring device 2800 includes a single insertion hole 1810, a plurality of diagnostic test strips containing a plurality of standard samples of different concentrations and a diagnostic test strip of a sample are sequentially inserted into the insertion hole 2810 of the measuring device 2800 to obtain the measurement value provided by the graphene-based sensor of each diagnostic test strip. Alternatively, when Fig.29 When the measuring device 2900 shown in FIG. 2 includes a plurality of insertion holes 2910, a plurality of diagnostic test strips containing a plurality of standard samples of different concentrations and a diagnostic test strip of a sample are simultaneously inserted into the insertion holes 2910 of the measuring device 2900 to simultaneously obtain the measurement values ​​provided by the graphene-based sensor of the plurality of diagnostic test strips. The measuring device 2800 or 2900 identifies the time-dependent change (e.g., change in current or voltage) of the measurement value of the graphene-based sensor for the standard samples having different concentrations. In addition, the measuring device 2800 or 2900 can identify the concentration or intensity of the sample by comparing the change in the measurement value of the standard sample of each concentration with the change in the measurement value of the sample.

[0196] Fig.30 A flow chart showing a method for measuring a sample according to the present invention is shown.

[0197] For convenience, refer to Figures 30 to 33 A method of measuring a sample is described by assuming that Fig. 27 The method will be described using a sensor measuring device 2700.

[0198] refer to Fig.30 Before applying the sample, the sensor measuring device 2700 applies a voltage within a predetermined range to the sensor 2710 (S3000). For example, the sensor measuring device 2700 may apply a voltage between 0 and 2V to the sensor at a fixed interval and time.

[0199] In another embodiment, after applying the buffer solution, the sensor measuring device 2700 may apply a voltage to the sensor 2710. Examples of buffer solutions include phosphate buffered saline (PBS), universal transport medium (UTM), PBST (PBS + Tween 20), ADA (C 6 H 10 N 2 O 5 )、AMP(C 4 H 11 NO)、BES(C 6 H 15 NO 5 S), dihydroxyethylglycine (C 6 H 13 NO 4 )、BIS-TRIS(C 8 H 19 NO 5 )、Bis-Tris propane (C 11 H 26 N 2 O 6 ), boric acid (H 3 BO 3 )、CAPS(C 6 H 11 NH(CH 2 ) 3 SO 3 H), CAPSO sodium salt (C 9 H 18 NO 4 SNa)、CHES(C 8 H 17 NSO 3 )、DIPSO(C 7 H 17 NO 6 S), DIPSO monosodium salt (C 7 H 16 NO 6 SNa)、EDTA、Glycine-HCl、HEPBS(C10 H 22 N 2 O 4 S), HEPES free acid (C 8 H 18 N 2 O 4 S), HEPES sodium salt (C 8 H 17 N 2 O 4 SNa)、HEPPS(C 9 H 20 N 2 O 4 S), HEPPSO free acid (C 9 H 20 N 2 O 5 S), HEPPSO sodium salt (C 9 H 19 N 2 O 5 SNa), MES free acid monohydrate (C 6 H 13 NO 4 S.H. 2 O), MES sodium salt (C 6 H 12 NNaO 4 S), MOPS free acid (C 7 H 15 NO 4 S), MOPS sodium salt (C 7 H 14 NO 4 SNa), MOPSO free acid (C 7 H 15 NO 5 S), MOPSO sodium salt (C 7 H 14 NO 5 SNa), PIPES free acid (C 8 H 18 N 2 O 6 S2), PIPES sodium salt (C 8 H 16.5 N2Na 1.5 O 6 S2), POPSO free acid (C 10 H 22 N 2 O 8 S 2 )、POPSO disodium salt (C 10 H 20N 2 O 8 S 2 Na 2 ), Satellite free Ampicillin, SDS (sodium dodecyl sulfate)-urea-Tris solution, sodium acetate, SSC, SSPE, TAE, TAPS free acid (C 7 H 17 NO 6 S), TAPS sodium salt (C 7 H 17 NO 6 SNa), TAPSO free acid (C 7 H 17 NO 7 S), TAPSO sodium salt (C 7 H 16 NO 7 SNa), TBS (TRIS buffered saline), TBST (TBS-Tween 20), TE buffer (Tris-EDTA), TES free acid (C 6 H 15 NO 6 S), TG buffer (TRIS-glycine), TG-SDS buffer (TRIS-glycine-SDS), Tris (C 4 H 11 NO 3 )、Tris-HCl、Tris hydrochloride (C 4 H 11 NO 3· HCl), Tris-(hydroxymethyl)propane (C 6 H 14 O 3 ), TT-SDS (Tris-tris(hydroxymethyl)methylglycine-SDS buffer), TTE (Tris-TAPS-EDTA buffer), and the like. According to an embodiment, the buffer solution may be omitted. Fig.31 An example of a method of applying a buffer solution 3110 to a sensor 3100 is shown in FIG.

[0200] The sensor measuring device 2700 measures the resistance or current of the sensor 2710 according to the application of the voltage (S3010). Hereinafter, the resistance or current of the sensor 2710 measured before applying the sample is referred to as a first measurement value. The sensor measuring device 2700 measures the first measurement value for each voltage within a predetermined voltage range. For example, if a voltage between 0 and 2V is applied at intervals of 0.1V, the sensor measuring device 2700 identifies a plurality of first measurement values, which indicate the resistance or current of the sensor for each voltage (such as 0.1V, 0.2V, ... 2V).

[0201] A sample is applied to the sensor 2710 (S3020). In one embodiment, if a buffer solution is applied to the sensor 2710, the sample is applied to the sensor 2710 while the buffer solution is applied. After the sample is applied, the sensor measuring device 2700 applies a voltage within a predetermined range to the sensor (S3030). The voltage applied primarily to the sensor 2710 before the sample is applied and the voltage applied secondarily to the sensor 2710 after the sample is applied may be voltages under the same conditions. For example, if the primarily applied voltage is a voltage between 0 and 2 V in units of 0.1 V, the secondarily applied voltage may also be a voltage between 0 and 2 V in units of 0.1 V.

[0202] The sensor measuring device 2700 measures the resistance or current of the sensor 2710 according to the application of the voltage (S3040). Hereinafter, the resistance or current of the sensor 2710 measured after the sample is applied is referred to as the second measurement value. The sensor measuring device 2700 identifies the difference between the first measurement value before the sample is applied and the second measurement value after the sample is applied (S3050). That is, the sensor measuring device 2700 detects the difference between the first measurement value and the second measurement value for each voltage. For example, when there are a plurality of first measurement values ​​measured by applying 0.2V and 0.5V before applying the sample and a plurality of second measurement values ​​measured by applying 0.2V and 0.5V after applying the sample, the sensor measuring device 2700 compares the first measurement value of 0.2V before applying the sample and the second measurement value of 0.2V after applying the sample, and compares the first measurement value of 0.5V before applying the sample and the second measurement value of 0.5V after applying the sample. Reference will be made later Fig.32 Describe the method for comparing the measurements before and after applying the sample.

[0203] As one embodiment, the sensor measuring device 2700 may output the first measurement value and the second measurement value on a screen or transmit them to an external device. In another embodiment, the sensor measuring device 2700 may output the difference between the first measurement value and the second measurement value on the screen or transmit the difference to the external device.

[0204] As another embodiment, the sensor measuring device 2700 may output the maximum difference between the first measurement value and the second measurement value on a screen or transmit the maximum difference to an external device. For example, if the difference between the first measurement value and the second measurement value is A for a 0.2V voltage, and B (>A) for a 0.5V voltage, the sensor measuring device 2700 may output B having a larger difference.

[0205] As another embodiment, the sensor measuring device 2700 may repeat the process of measuring the second measurement value. For example, the sensor measuring device 2700 may input a voltage between 0 and 2V to the sensor 2710 at a fixed interval at the time point t1 to obtain a plurality of second measurement values ​​at the time point t1. The sensor measuring device 2700 may again input a voltage between 0 and 2V to the sensor 2710 at a fixed interval at the time point t2 to obtain a plurality of second measurement values ​​at the time point t2. By the method described above, a plurality of second measurement values ​​at the time point tn may be obtained. The number of times the second measurement value is repeatedly measured and the interval between the repeated measurements (i.e., t2-t1) may be variously modified according to the embodiment.

[0206] The sensor measuring device 2700 may compare the plurality of second measurement values ​​measured at the time point t1 with the first measurement value measured previously to determine the maximum difference therebetween. In addition, the sensor measuring device 2700 may compare the first measurement value with the plurality of second measurement values ​​measured at the time point t2 to determine the maximum difference therebetween. By the method described above, the maximum difference may be determined by comparing the first measurement value with the plurality of second measurement values ​​measured at the time point tn. For example, at the time point t1, the difference between the first measurement value and the second measurement value measured at 0.5V is the maximum value, and at the time point t2, the difference between the first measurement value and the second measurement value measured at 0.2V is the maximum value. That is, the voltage applied when the maximum difference between the first measurement value and the second measurement value occurs may be different from each other at each measurement time point t1, t2, ... tn.

[0207] As an embodiment, the sensor measuring device 2700 may obtain the difference between the first measurement value and the second measurement value as follows.

[0208] [Equation 3]

[0209]

[0210] When the value measured by the sensor measuring device 2700 using the sensor 2710 is a current, the first measurement value and the second measurement value are the current value of the sensor. When the value measured by the sensor measuring device 2700 using the sensor 2710 is a resistance, the first measurement value and the second measurement value are the resistance value of the sensor.

[0211] In an embodiment of the present invention, the effect of a sample on a sensor can be accurately measured by identifying a first measurement value measured before applying the sample to the sensor 2710 and a second measurement value measured after applying the sample to the sensor 2710. In another embodiment, the sensor measurement device 2700 can more accurately measure the sample by using a change in the maximum difference between the first measurement value before applying the sample and the second measurement value obtained at each time point (t1, t2, ... tn) after repeatedly measuring the second measurement value at fixed time intervals.

[0212] The sensor measuring device 2700 may output the difference between the second measurement value determined at each time point and the first measurement value measured before applying the sample to the screen or transmitting the difference to the external device. In another embodiment, the sensor measuring device 2700 may output the maximum difference in the difference between the second measurement value determined at each time point and the second measurement value measured before applying the sample to the screen or transmitting the maximum difference to the external device. For example, the sensor measuring device 2700 may display the maximum difference as a number or a graph (e.g., a bar graph or a line graph). In another embodiment, the sensor measuring device 2700 may output the result of identifying the sample based on the change in the maximum difference to the screen or transmit the result to the external device. As another embodiment, the sensor measuring device 2700 may output various values, such as the voltage applied at each measurement time point when the maximum difference occurs.

[0213] Fig.32 An example of a method of measuring a sample according to the present invention is shown.

[0214] refer to Fig.32 Before applying the sample 3200, the sensor measuring device 2700 applies a voltage to the sensor to identify a first measurement value 3210 including a current or a resistance of the sensor. As one embodiment, the sensor measuring device 2700 can determine the first measurement value 3210 by applying at least one voltage to the sensor. For example, the sensor measuring device 2700 can determine the plurality of first measurement values ​​3210 by applying a voltage between 0 and 2V at fixed intervals.

[0215] After applying the sample 3220, the sensor measuring device 2700 applies a voltage to the sensor to identify a second measurement value including a current or a resistance of the sensor. The voltage input to the sensor after applying the sample is the same as the voltage input to the sensor before applying the sample. The sensor measuring device 2700 may repeat the process of measuring the second measurement value. For example, the sensor measuring device 2700 determines the (2-1)th measurement value 3230 by applying a voltage at time point t1. In addition, the sensor measuring device 2700 determines the (2-2)th measurement value 3232 to the (2-N)th measurement value 3234 at time points t2 to tn, respectively.

[0216] The sensor measuring device 2700 determines the difference between the first measurement value 3210 and the second measurement value for each voltage. For example, assume that the first measurement value 3210 and the second measurement value are both measured with respect to voltages V1, V2, and V3. The sensor measuring device 2700 compares the first measurement value 3210 and the second measurement value (i.e., the (2-1)th measurement value 3230) at time point t1 for each voltage. If the difference between the (2-1)th measurement value 3230 measured by applying V2 at time point t1 and the first measurement value 3210 is the maximum value, the sensor measuring device 2700 determines the difference between the (2-1)th measurement value 3230 and the first measurement value 3210 at V2 as the maximum difference 3240 at time point t1. By using the method described above, the maximum difference 3242 is determined by comparing the voltage-specific difference between the first measurement value 3210 and the (2-2)th measurement value 3232 at time point t2, and the maximum difference 3244 is determined by comparing the voltage-specific difference between the first measurement value 3210 and the (2-N)th measurement value 3234 at time point tn.

[0217] Fig.33 An example of measurement results that may be mentioned in various embodiments of the present invention is shown.

[0218] Fig.33 A first graph 3300 showing the result of measuring the current by applying a voltage within a predetermined range to the sensor before applying a sample, and a second graph 3310 showing the result of measuring the current by applying a voltage within a predetermined range to the sensor after applying the sample are shown. Graphs 3300 and 3310 show sensor measurement values ​​at fixed intervals according to voltage, which are connected in a curve form. In addition, the graphs of this embodiment are only an example to facilitate understanding, and the sensor measurement results can be displayed in various types of graphs or numbers.

[0219] As an example, Fig.3233 shows that the process of repeatedly determining the second measurement value can generate a plurality of second graphs 3310, i.e., the (2-1)th graph representing the (2-1)th measurement value 3230 measured by the sensor at time point t1, the (2-2)th graph representing the (2-2)th measurement value 3232 measured by the sensor at time point t2, and the (2-N)th graph representing the (2-N)th measurement value 3234 measured by the sensor at time point tn. However, in this embodiment, only one graph is shown for convenience of explanation.

[0220] The sensor measurement device 2700 can determine the difference between the sensor measurements for each voltage in the first graph and the second graph by using Equation 3. The difference between the measurements is not limited to Equation 3 and can be obtained in a variety of ways. The difference between the first graph 3300 and the second graph 3310 is shown in the third graph 3320. For example, referring to Fig.32 The third figure shows a graph 3320 showing the difference between the (2-1)th measurement value 3230 and the first measurement value 3210 and a graph 3330 showing the difference between the (2-2)th measurement value 3232 and the first measurement value 3210. The sample can be identified based on the change in the position of the maximum value points 3332 and 3342 in the two graphs 3330 and 3340.

[0221] Fig.34 An example of using the measuring device according to the present invention is shown.

[0222] refer to Fig.34 , the measuring device 3410 may include a communication unit that can be used by connecting to the smart phone 3400. For example, the measuring device 3410 can be connected to the smart phone through an earphone terminal, a charging terminal or Bluetooth. Figures 17 to 29 Various examples of measurement device 3410 are shown in FIG.

[0223] The smart phone 3400 may display the voltage value received from the measuring device 3410 on the screen or transmit the voltage value to an external device. In another embodiment, the smart phone 3400 may display the result obtained by analyzing the voltage value received from the measuring device 3410 on the screen or transmit the result to the external device. For example, the implementation described below Figures 35 to 36 The software for the analysis method may be present in the smart phone 3400 .

[0224] In another embodiment, information capable of identifying the measuring device (such as a QR code or a barcode) may be present on one side of the measuring device 3410. When the QR code is present in the measuring device 3410, the smart phone 3400 may recognize the QR code through a camera and store the value of the QR code and the voltage value (or analysis result) of the measuring device 3410 therein or send them to an external device.

[0225] Fig.35 An example of a method according to the invention for analyzing measurement results is shown.

[0226] refer to Fig.35 , the sensor array 3500 outputs a plurality of graphene-based sensor measurement values ​​3510 (e.g., current or voltage). The structure of the sensor array 3500 is shown in FIGS. 1 to 15 . As another embodiment, an output unit configured to convert the output current into a voltage may be provided at the output terminal of the sensor array 3500. However, hereinafter, for convenience of description, it is assumed that the measurement values ​​output from the sensor array 3500 are adjusted to a voltage value within a predetermined range by the output unit. That is, all ranges of the measurement values ​​are standardized to values ​​within a predetermined range.

[0227] The plurality of measurement values ​​3510 output from the sensor array 3500 is input to the artificial neural network 3520. The artificial neural network 3520 can be implemented using various deep learning models of the related art, such as a convolutional neural network (CNN). The artificial neural network 3520 is trained in advance using training data. For example, the artificial neural network 3520 can be trained using learning data by a supervised learning method, wherein the plurality of measurement values ​​3510 obtained by measuring a standard sample using the sensor array is labeled with pre-identified standard sample information (e.g., wavelength / intensity of light, type / amount of biomolecules, type / amount of gas molecules, intensity of pressure, etc.). The learning method of the regression analysis model can be mainly used as an example of the supervised learning method. When the artificial neural network 3520 that has been trained by the method described above receives the plurality of measurement values ​​3510 measured by the sensor array, the artificial neural network 3520 outputs an analysis result 3530 (e.g., wavelength / intensity of light, type / amount of biomolecules, type / amount of gas molecules, intensity of pressure, etc.). Various analysis methods are described below.

[0228] As a first embodiment of the analysis method, a method for detecting the wavelength or intensity of light by using a sensor array 3500 and an artificial neural network 3520 will first be described. The reaction layers of the plurality of graphene-based sensors of the sensor array 3500 include different quantum dot materials that sense light of different wavelengths. For example, the reaction layers of the plurality of graphene-based sensors constituting the sensor array 3500 may be formed of quantum dots that react to R, G, and B. When the artificial neural network 3520 that has been trained in advance receives the plurality of measurement values ​​3510 of the sensor array, the artificial neural network 3520 outputs a wavelength in the visible light region as an analysis result. As another example, the reaction layers of the plurality of graphene-based sensors may be formed of quantum dots that sense infrared rays of different wavelength bands to detect wavelengths in the infrared region. In this case, the amount of blood sugar can be measured through infrared sensing of the skin. As another example, the reaction layers of each graphene-based sensor of the sensor array 3500 may be formed of different quantum dots that can detect different wavelength bands in the UV-IR region to analyze the wavelength of the signal.

[0229] As a second embodiment of the analysis method, the type and amount of biomolecules can be detected using the sensor array 3500 and the artificial neural network 3520. The reaction layers of the plurality of graphene-based sensors of the sensor array 3500 may include biomolecules (e.g., DNA, RNA, antigens, antibodies, enzymes, etc.) with different reaction degrees. For example, the degree to which the first antibody of the reaction layer of the first graphene-based sensor of the sensor array 3500 reacts with various viruses (e.g., SARS-CoV-1, SARS-CoV-2, MERS-Cov, etc.) and the degree to which the second antibody of the reaction layer of the second graphene-based sensor reacts with various viruses (i.e., the signal of the measured value) may be different from each other. In other words, the degree to which the first antibody reacts with the first virus is r1, the degree to which the first antibody reacts with the second virus is r2, and the degree to which the second antibody reacts with the first virus and the second virus is r3 and r4, respectively, which may be different from each other.

[0230] When the sensor array 3500 outputs a plurality of measurement values ​​3510 of the sample, the artificial neural network 3520 outputs the type / amount of the virus as the analysis result. To this end, the artificial neural network 3520 can be pre-trained using learning data, wherein the measurement values ​​3510 obtained by the sensor array 3500 for various types of viruses are marked with the type and / or amount of the virus. The reaction layer of each graphene-based sensor can be formed by antibodies having different degrees of reaction to various viruses to detect the type and amount of the sample according to the degree of reaction of each antibody. Therefore, the sensor array 3500 can detect a greater number of viruses than the number of graphene-based sensors included therein. In addition, if the degree of reaction of each antibody in the reaction layer of the graphene-based sensor is different with respect to a new virus, the existing sensor array 3500 is used as is without having to manufacture the reaction layer again and train the artificial neural network using the learning data of the new virus to facilitate detection of the new virus.

[0231] As a third embodiment of the analysis method, a method for diagnosing a disease by using the sensor array 3500 and the artificial neural network 3520 will be described. The reaction layer is formed in the plurality of graphene-based sensors of the sensor array 3500 by using various materials such as DNA, RNA, antigens, antibodies, and enzymes. For example, the first graphene-based sensor of the sensor array 3500 may include a reaction layer of a material capable of detecting DNA, and the second graphene-based sensor may include a reaction layer of a material capable of detecting enzymes. The artificial neural network 3520 predicts and outputs a disease after receiving the plurality of measurement values ​​3510 provided by the sensor array 3500. That is, a specific disease can be diagnosed through a combination of various measurement values. To this end, the artificial neural network 3520 can be pre-trained by learning data, in which the plurality of measurement values ​​obtained by inputting samples capable of diagnosing a specific disease into the sensor array 3500 are labeled with the name of the disease.

[0232] Fig.36 An example of an artificial neural network that may be mentioned in various embodiments of the present invention is shown.

[0233] refer to Fig.36, the artificial neural network 3600 includes an input layer 3610, one or more hidden layers 3620, and an output layer 3630. The one or more hidden layers 3620 include one or more network nodes 3621. The one or more network nodes 3621 have a connection relationship with each other by simulating the synaptic activity of neurons, wherein human neurons exchange signals through synapses. For example, in the artificial neural network 3600, one or more network nodes 3621 are located in layers (e.g., hidden layers) of different depths and exchange data according to a convolutional connection relationship. In addition, network nodes having various connection relationships (e.g., recursive, etc.) are included in the artificial neural network 3600. The connection relationship between these network nodes can be defined as mapping tables 3641 and 3642 for each layer in the hidden layers. The set of mapping tables 3641 and 3642 can be simply referred to as a mapping table set 3640.

[0234] The mapping table set 3640 is determined through the learning of the artificial neural network 3600 described above. In one embodiment, the mapping table set 3640 can be implemented as various types of internal circuits. The internal circuit implemented as hardware may include Fig.28 and 29 In another embodiment, the mapping table set 3640 may be implemented as various types of computer programs. The computer program implemented as software may include Fig.28 and 29 The artificial neural network 3600 receives a plurality of measurement values ​​provided by the sensor array and outputs analysis results (e.g., wavelength / intensity of light, type / amount of biological molecules, type / amount of gas molecules, intensity of pressure, etc.) according to the operations determined in the mapping table set 3640.

[0235] In the flowcharts of the present invention, the operations of the method or algorithm are described in sequential order, but can be performed in any combinable order other than sequentially. The description of the flowcharts in the present invention does not exclude the application of changes or modifications to the method or algorithm, and does not mean that any operation is necessary or required. In one embodiment, at least some of the operations can be performed in parallel, iteratively or heuristically. In another embodiment, at least one operation can be omitted or other operations can be added.

[0236] Various embodiments of the present invention may be implemented as software in a machine-readable storage medium (MRSM) that can be read by a computing device. The software may be software for implementing various embodiments of the present invention. The software may be inferred from various embodiments of the present invention by a programmer skilled in the art. For example, the software may be a computer program containing instructions that can be read by a computing device. The computing device is a device that can operate according to instructions invoked from a storage medium and may be referred to interchangeably with, for example, an electronic device. In one embodiment, a processor of the computing device may execute an invoked command so that a component of the computing device performs a function corresponding to the command. The storage medium may refer to any type of recording medium that stores information that can be read by a device. The storage medium may include, for example, a ROM, RAM, CD-ROM, magnetic tape, floppy disk, or optical information storage device. In one embodiment, the storage medium may be distributed to computer systems connected via a network. In this case, the software may be distributed, stored, and executed in such computer systems or the like. In another embodiment, the storage medium may be a non-transient storage medium. Non-transient storage media refers to media that exist regardless of whether the information is stored semi-permanently or temporarily and does not include transient signals.

[0237] Although the technical concept according to the present invention has been described by various embodiments above, the technical concept according to the present invention includes various substitutions, modifications and changes that can be performed within the scope understood by a person skilled in the art of the present invention. In addition, it should be noted that such substitutions, modifications and changes are intended to fall within the scope of the appended claims.

Claims

1. A graphene-based sensor comprising: substrate; A doped region formed by doping a portion of the substrate with impurities; an insulator layer stacked on the substrate except for a portion of the doped region; A graphene layer stacked on the doped region; a first electrode connected to the graphene layer; as well as A second electrode is connected to the doped region.

2. The graphene-based sensor according to claim 1, wherein: The doped region comprises: doped to a first doping region having a first concentration; and doped into a second doping region having a second concentration, wherein the first concentration is equal to or less than the second concentration, wherein the graphene layer is connected to the first doping region, and Wherein, the second electrode is connected to the second doping region.

3. The graphene-based sensor according to claim 1, wherein: The first electrode surrounds a periphery of the graphene layer.

4. The graphene-based sensor according to claim 1, wherein: The second electrode is located under the substrate to face the graphene layer.

5. The graphene-based sensor according to claim 1, wherein: further comprising one or more through-hole electrodes passing through the insulator layer and the substrate from a position separated from the first electrode, Wherein, the second electrode is connected to one or more of the through-hole electrodes.

6. The graphene-based sensor according to claim 1, wherein: The second electrode passes through the insulator layer to be connected to the doping region.

7. The graphene-based sensor of claim 1, wherein: Further included is a third electrode separated from the first electrode and in contact with the graphene layer.

8. The graphene-based sensor of claim 1, wherein: Further including: A storage cell is formed by etching the substrate to have a first depth and a first width; and A channel unit configured to connect the storage unit and the graphene layer to each other is formed by etching the insulator layer to a second depth and a second width, The second depth and the second width are respectively smaller than the first depth and the first width.

9. The graphene-based sensor of claim 1, wherein: forming a plurality of doped regions separated from each other on the substrate, and The insulating layers are stacked so that the plurality of doped regions are exposed.

10. The graphene-based sensor according to claim 9, wherein: The graphene layers are stacked to correspond to the plurality of doped regions, The graphene-based sensor comprises a plurality of first electrodes respectively corresponding to the plurality of doping regions, and Wherein, the second electrodes are commonly connected to the plurality of doped regions.

11. The graphene-based sensor according to claim 9, wherein: The graphene layer is stacked on the plurality of doped regions, The graphene-based sensor comprises a plurality of second electrodes respectively connected to the plurality of doping regions, and Wherein, the first electrodes are commonly connected to the plurality of doped regions.

12. The graphene-based sensor according to claim 10 or 11, wherein: Further included is a multiplexer configured to output values ​​measured through the graphene layer on the plurality of doped regions.

13. The graphene-based sensor of claim 1, wherein: Further included is a reaction layer located on the surface of the graphene layer and including a material that induces charge in the graphene layer.

14. A graphene-based sensor, wherein: Include: substrate; A two-dimensional semiconductor layer stacked on the substrate; A graphene layer stacked on the two-dimensional semiconductor layer; A first electrode stacked in contact with the two-dimensional semiconductor layer; as well as A second electrode of the stack is in contact with the graphene layer.

15. The graphene-based sensor of claim 14, wherein: Further included is a reaction layer located on the surface of the graphene layer and including a material that induces charge in the graphene layer.

16. The graphene-based sensor of claim 14, wherein: A plurality of two-dimensional semiconductor layers are arranged on the substrate in a manner spaced apart from each other. wherein the graphene layer is stacked on the plurality of two-dimensional semiconductor layers, and Wherein, a plurality of first electrodes are respectively arranged on the plurality of two-dimensional semiconductor layers.

17. The graphene-based sensor of claim 16, wherein: The two-dimensional materials constituting the plurality of two-dimensional semiconductor layers include a portion and another portion that are different from each other.

18. The graphene-based sensor of claim 16, wherein: The plurality of two-dimensional semiconductor layers are arranged in a first direction, and Wherein, the graphene layers are arranged in a second direction perpendicular to the first direction.

19. The graphene-based sensor of claim 14, wherein: The invention further includes a third electrode which is separated from the first electrode and is in contact with the stack of the two-dimensional semiconductor layer.

20. The graphene-based sensor of claim 14, wherein: The invention further includes a fourth electrode which is separated from the second electrode and is stacked in contact with the graphene layer.

21. The graphene-based sensor of claim 14, wherein: Multiple two-dimensional semiconductor layers are arranged radially. wherein the graphene layer is arranged across the plurality of two-dimensional semiconductor layers to have a circular belt shape, The graphene-based sensor further comprises a third electrode commonly connected to the plurality of two-dimensional semiconductor layers, and Wherein, the plurality of first electrodes are respectively connected to the plurality of two-dimensional semiconductor layers.

22. A measuring device, wherein: Include: A graphene-based sensor, wherein a graphene layer is stacked on a doped region formed on a substrate or on a two-dimensional semiconductor layer stacked on the substrate; and An output unit configured to convert an output current of the graphene-based sensor into a voltage and output the voltage.

23. The measuring device according to claim 22, wherein: The output unit comprises: a pre-amplification unit configured to convert an output current of the graphene-based sensor into a voltage and output the voltage; and A feedback unit is configured to adjust so that the output voltage of the pre-amplification unit is within a predetermined range.

24. The measuring device according to claim 22, wherein: Further including: a display unit configured to display an output voltage of the output unit; and The device is configured to transmit the output voltage of the output unit to an external communication unit.

25. The measuring device according to claim 22, wherein: Further including: A sensor array, wherein the graphene-based sensors are arranged in one or two dimensions; and a multiplexer connected to a plurality of graphene-based sensors constituting the sensor array, The output unit is configured to selectively receive the output current of each graphene-based sensor through the multiplexer.

26. The measuring device according to claim 22, wherein: Further included is an internal circuit comprising a set of mapping tables corresponding to an artificial neural network configured to receive measurement values ​​obtained by a reaction between a sample and a material of the reaction layer of the graphene-based sensor and output an analysis value.

27. The measuring device according to claim 22, wherein: Further including: a voltage applying unit configured to apply a voltage within a predetermined range to the graphene-based sensor; as well as A measuring unit is configured to detect a first measurement value of the resistance or current of the graphene-based sensor according to a voltage applied before applying a sample, and to detect and output a second measurement value of the resistance or current of the graphene-based sensor according to a voltage applied after applying the sample.

28. The measuring device according to claim 27, wherein: The measurement unit outputs a result value including a maximum difference in voltage-specific differences between the first measurement value and the second measurement value.

29. The measuring device according to claim 27, wherein: The measuring unit repeats the process of measuring the second measurement value at fixed time intervals, and outputs a second measurement value of the resistance or current of the sensor according to the applied voltage each time the repetition is performed.

30. The measuring device according to claim 29, wherein: Each time the repetition is performed, the measuring unit detects and outputs a change in a maximum difference between the first measurement value and the second measurement value.

31. An analysis method using a sensor array, the sensor array comprising a plurality of sensors, wherein: The graphene layer is stacked on a two-dimensional semiconductor or on a semiconductor region doped on a substrate. The method comprises: receiving a plurality of measurements from a plurality of graphene-based sensors of the sensor array; and The plurality of measured values ​​are received and an analysis result is obtained by using an artificial neural network using arithmetic operations determined in a set of mapping tables.

32. The analytical method according to claim 31, wherein The material of the reaction layer applied to the graphene layer of the plurality of graphene-based sensors includes a portion and another portion that are different from each other.

33. The analytical method according to claim 31, wherein The material of the reaction layers of the plurality of graphene-based sensors includes at least one of the following: quantum dots, biomolecules, gas-reactive molecules, or pressure-reactive structures.

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