Nanogenerator device for measuring electrical conductivity of blood and other materials

Abstract

A device for measuring electrical conductivity of target ("Target") comprising blood, a body fluid, a body tissue, a biological substance, a liquid or a solid material, comprising a hollow body having a closed end and an open end; a triboelectric nanogenerator (TENG) disposed within the hollow body; the TENG comprising first and second discs disposed within the hollow body, wherein the first disc is disposed adjacent to the closed end of the hollow body and the second disc is spaced apart from the first disc to define a target chamber within the hollow body; a third disc spaced apart from the second disc towards the open end to define a gap between the second and third discs; a first electrode comprising an electrically conductive material disposed on a side of the third disc opposite the gap; and a second electrode comprising a Target in the target chamber.

Description

NANOGENERATOR DEVICE FOR MEASURING ELECTRICAL CONDUCTIVITY OF BLOOD AND OTHER MATERIALS RELATED APPLICATION

[0001] This application claims priority benefit under 35 U. S. C. § 119(e) of U. S. Provisional Application No.63 / 714,123 filed October 30, 2024, the contents of which are herein incorporated by reference.STATEMENT OF GOVERNMENT SUPPORT

[0002] This invention was made with government support under grant # 2235494 awarded by the National Science Foundation. The government has certain rights in the invention.FIELD OF THE DISCLOSURETechnical field

[0003] The present disclosure generally relates to the field of devices for measuring electrical conductivity of a target substance such as blood, a body fluid, a body tissue, a biological substance, a liquid or a solid material and, more specifically, to triboelectric nanogenerator (TENG) devices for measuring electrical conductivity of such a target where the target comprises an electrode of the TENG device.Background

[0004] Blood electrical conductivity is a valuable metric for assessing various health parameters and detecting medical conditions. The blood conductivity is predominantly governed by the concentration of essential electrolytes, notably sodium and chloride ions, along with other blood substances including metabolites (e.g. urea), plasma proteins, and nutrients (e.g. glucose). These electrolytes and other substances are integral to a multitude of physiological processes. Monitoring tools for blood conductivity can facilitate assessment of vital biological parameters such as haematocrit (Hct),[l] erythrocyte sedimentation rate (ESR),[2] cardiac output, [3] and even conditions like Alzheimer’s disease and diabetes. [4] Additionally, aberrations in blood conductivity can signal a range of medical conditions, from de-hydration and electrolyte imbalances to more complex disorders. Thus, precise and efficient techniques for blood conductivity measurement hold paramount importance in both clinical and research domains. The existing literatureabounds with studies emphasizing the adaptability of blood conductivity as a versatile tool replete with significant medical potential. For instance, Abdalla et al. [5] explored the utility of blood conductivity as an indicator to monitor physiological changes in human organism properties. Altaf et al. [6] studied the dielectric proper-ties of human blood, unveiling their utility in estimating conditions like renal failure in patients. Moreover, Istuk et al. [7] studied the correlation between blood conductivity and blood counts, accentuating the potential for employing blood conductivity investigations in medical contexts. These findings collectively highlight the multifaceted applications of blood conductivity in the realm of medical research.

[0005] However, the knowledge of human blood conductivity remains constrained due to measurement challenges, including electrode polarization, limited access to human blood samples, and the complexities associated with blood temperature maintenance. Measuring conductivity at frequencies below 100 Hz is particularly important for gaining a deeper understanding of the blood electrical properties and fundamental biological processes. [10,11] Many of the conventional techniques for measuring blood conductivity predominantly hinge on bulky laboratory or microprocessor-based equipment, constraining their suitability for point-of-care (POC) and remote monitoring applications. Conventional methods also involve labor-intensive processes, including invasive blood extraction, often uncomfortable for patients. In addition, these approaches tend to be time-consuming, making real-time monitoring unfeasible. The constraints inherent to the conventional techniques underscore the urgent necessity for innovative, portable, and minimally invasive methodologies for blood conductivity evaluation. As the fields of nanotechnology and microfluidics continue to advance, there is a growing opportunity to develop lab-on-a-chip devices capable of surmounting these constraints, thereby facilitating efficient, POC blood conductivity assessments. These technologies could potentially contribute to transforming healthcare by offering quick and convenient diagnostics, ultimately improving patient outcomes and the effectiveness of medical services.

[0006] The present disclosure presents a portable nanogenerator device for measuring the electrical conductivity of blood, body fluids, tissue, biological substances, liquids and solid materials. The biologic substances can be human or non-human. The proposed device employs blood, tissue, biological substances,liquids and solid materials as conductive substances within its built-in triboelectric nanogenerator system. The voltage generated by this nanogenerator device is used to determine the electrical conductivity of the samples. The self-powering functionality of the device eliminates the need for complex embedded electronics and external electrodes. The device is efficient in detecting variations in electrical conductivity of substances. The 3D-printed, disposable design of the device enhances portability and usability, providing a point-of-care solution for rapid electrical conductivity assessment.BRIEF SUMMARY OF THE DISCLOSURE

[0007] In a preferred aspect, the present disclosure comprises a device for measuring electrical conductivity of target (“Target”) comprising blood, a body fluid, a body tissue, a biological substance, a liquid or a solid material, comprising a hollow body having a closed end and an open end; a triboelectric nanogenerator (TENG) disposed within the hollow body; the TENG comprising first and second discs disposed within the hollow body, wherein the first disc is disposed adjacent to the closed end of the hollow body and the second disc is spaced apart from the first disc to define a target chamber within the hollow body; a third disc spaced apart from the second disc towards the open end to define a gap between the second and third discs; a first electrode comprising an electrically conductive material disposed on a side of the third disc opposite the gap; and a second electrode comprising a Target in the target chamber.

[0008] In another preferred aspect, a device for measuring electrical conductivity of a Target of the present disclosure further comprises a push trigger cap disposed on the open end of the hollow body, wherein the push trigger cap has a shaft connected between the push trigger cap and the first electrode.

[0009] In another preferred aspect, a device for measuring electrical conductivity of a Target of the present disclosure further comprises a transfer tube for transferring the Target from outside the hollow body into the target chamber.

[0010] In another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, each of the first and second discs comprises polymethyl methacrylate (PMMA).

[0011] In yet another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, the push trigger cap is spring-loaded.

[0012] In another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, the third disc comprises a polytetrafluoroethylene (PTFE).

[0013] In yet another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, the electrically conductive material of the first electrode comprises an electrically conductive metal or is selected from a group of copper, silver, gold, platinum, aluminum, iron and steel.

[0014] In another preferred aspect, a device for measuring electrical conductivity of a Target of the present disclosure further comprises a voltmeter in communication wirelessly or by wire to the target chamber.

[0015] In yet another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, the TENG provides electronic-free wireless transmission of data sensed by the device.

[0016] In another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, at an initial stage, the third disc and the second disc have no contact, and there is no charge on their surfaces; wherein pressing a spring-loaded push trigger cap causes a shaft to move down, bringing the second and third discs into contact and facilitating surface charge transfer therebetween where electrons are transferred from one or more surfaces of the second disc to one or more surfaces of the third disc whilst there being no potential difference between the first and second electrodes; wherein as the shaft moves up, the second and third discs separate, creating a potential difference with an open-circuit voltage increasing until it reaches a maximum value corresponding to a time it takes for the shaft to return to an original position; wherein when the shaft moves down, voltage decreases, reaching zero when the third disc and the second disc are in contact and wherein in each loading and unloading cycle, the spring in the push trigger maintains a consistent force and a sole variable within the TENG device is electrical conductivity of the Target in the target chamber.

[0017] In another preferred aspect, the present disclosure comprises a device for measuring electrical conductivity of target (“Target”) comprising blood, a body fluid, a body tissue, a biological substance, a liquid or a solid material, comprising a triboelectric nanogenerator (TENG) comprising first and second discs, wherein the first disc is spaced apart from the second disc to define a target channel; a third disc spaced apart from the second disc to define a gap between the second and third discs; a first electrodecomprising an electrically conductive material disposed on a side of the third disc opposite the gap; and a second electrode comprising a Target in the target chamber.

[0018] In another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, each of the first and second discs comprises polymethyl methacrylate (PMMA).

[0019] In yet another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, the third disc comprises a polytetrafluoroethylene (PTFE).

[0020] In another preferred aspect of a device for measuring electrical conductivity of a Target of the present disclosure, the electrically conductive material of the first electrode comprises an electrically conductive metal or is selected from a group of copper, silver, gold, platinum, aluminum, iron and steel.

[0021] In another preferred aspect, the present disclosure comprises a triboelectric nanogenerator (TENG) wherein a target comprising blood, a body fluid, a body tissue, a biological substance, a liquid or a solid material comprises an electrode or a component of the TENG.BRIEF DESCRIPTION OF THE DRAWINGS

[0022] For the present disclosure to be easily understood and readily practiced, the present disclosure will now be described for purposes of illustration and not limitation in connection with the following figures, wherein:

[0023] FIG. 1(a) is a schematic drawing a preferred self-powered lab-on-a-chip TENG device to determine the electrical conductivity of blood, body fluids, tissue, biological substances, liquids and solid materials of the present disclosure. The blood / tissue / biological substance / liquid / solid material layer, copper electrodes, PTFE disc, and PMMA elements form a contact-separation mode TENG system. The blood sample is sandwiched between two PMMA layers and serves as one of the conductive layers. Any change in its electrical conductivity would theoretically change the voltage signal generated by the device;

[0024] FIG. 1(b) shows a preferred operating principle in Stages I-V of the blood-based TENG device of FIG. 1(a);

[0025] FIG. 1(c) shows a 3D printing of the device of FIG. 1(a) and the type of voltage signal generated by it;

[0026] FIG. 2(a) shows experimental results showing 3D printed device of the present disclosure and test setup wherein the device is tested using 1 mL of SBF and human blood plasma samples under consistent loading;

[0027] FIG. 2(b) is a chart showing variations in the generated voltage of a preferred device of the present disclosure with increasing NaCl in c-SBF samples, while maintaining the Glc level at zero. The normal fasting NaCl levels in human blood lie between 135 and 146 mmol L-1.

[0028] FIG. 2(c) is a chart showing valuations in the generated current of a preferred device of the present disclosure with increasing NaCl in c-SBF samples, while maintaining the Glc level at zero;

[0029] FIG. 2(d) is a chart showing variations in the generated voltage of a preferred device of the present disclosure with increasing Glc in c-SBF samples with the NaCl level fixed at 147.8 mmol L-1(standard c-SBF level);

[0030] FIG. 2(e) is a chart showing variations in the generated current of a preferred device of the present disclosure with increasing Glc in c-SBF samples with the NaCl level fixed at 147.8 mmol L-1

[0031] FIG. 2(f) is a chart showing variations in the generated voltage of a preferred device of the present disclosure with increasing NaCl in c-SBF samples with the Glc level fixed at 5.6 mmol L-1(normal fasting blood Glc level);

[0032] FIG. 2(g) is a chart showing variations in the generated current of a preferred device of the present disclosure with increasing NaCl in c-SBF samples with the Glc level fixed at 5.6 mmol L-!;

[0033] FIG. 2(h) is a chart showing variations in the voltage generated by a preferred device of the present disclosure using human blood plasma samples with known NaCl and Glc levels;

[0034] FIG. 2(i) is a chart showing variations in the current generated by a preferred device of the present disclosure using human blood plasma samples with known NaCl and Glc levels;

[0035] FIG. 3(a) shows experimental and Al simulation results showing variations in the measured voltage and 5 values generated by a preferred device of the present disclosure across all samples;

[0036] FIG. 3(b) shows an Al evolutionary process proposed to formulate the voltage of a preferred device of the present disclosure in terms of NaCl and Glc concentrations, and to express Sin terms of the device voltage. The algorithm uses genetic operators (e.g., crossover and mutation) to optimize an initial population of randomly generated models for voltage and S;

[0037] FIG. 3(c) shows a comparison between the measured and predicted voltage values in Model 1 of a preferred device of the present disclosure for the training (blue circles) and testing (red circles) data;

[0038] FIG. 3(d) shows a comparison between the measured and predicted S' values in Model 2 of a preferred device of the present disclosure for the training (blue circles) and testing (red circles) data;

[0039] FIG. 3(e) shows a parametric analysis showing the variations in the voltage of a preferred device of the present disclosure by changing the NaCl and Glc concentrations;

[0040] FIG. 3(f) shows a parametric analysis showing the S variations of a preferred device of the present disclosure by changing the device voltage;

[0041] FIG. 3(g) shows variations in the generated voltage values of a preferred device of the present disclosure as temperature increases from 10 °C to 40 °C, utilizing the blood specimen with normal baseline fasting levels of NaCl at 135 mmol L-1and Glc at 5.61 mmol L-1;

[0042] FIG. 3(h) shows chart showing the correlation between the device voltage of a preferred device of the present disclosure, S and temperature variations where the device voltage and S values show a linear increase as the temperature rises;

[0043] FIG. 4 shows chart comparing conductivity measurement methods based on their operation frequency and sensing features. In terms of sensitivity, the performance of electrical conductivity measurement devices can vary based on factors such as the design and material composition of the electrodes, the quality of the measurement circuitry, and the signal processing capabilities of the instrument. Sensitivity levels (high, moderate, or low) indicate the degree to which the device’s performance relies on these factors. The power autonomy levels - high, moderate, and low - indicate whether the device is self-powered, battery-powered, or requires external power, respectively. In terms of versatility, these levels signify the device’s capability to handle various liquids and materials. In the context of POC diagnostics,these levels specify whether the device is portable and self-powered, portable but requires external power, or constitutes bulky equipment, respectively;

[0044] FIG. 5 shows is an exploded view of another a preferred embodiment of a self-powered lab-on-a-chip TENG device to determine the electrical conductivity of blood, body fluids, tissue, biological substances, liquids and solid materials of the present disclosure;

[0045] FIG. 6 shows a perspective view of the device of FIG. 5.DETAILED DESCRIPTION

[0046] In the following detailed description, reference is made to the accompanying examples and figures that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the inventive subject matter may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice them, and it is to be understood that other embodiments may be utilized and that structural or logical changes may be made without departing from the scope of the inventive subject matter. Such embodiments of the inventive subject matter may be referred to, individually and / or collectively, herein by the term "disclosure" merely for convenience and without intending to voluntarily limit the scope of this application to any single inventive concept if more than one is in fact disclosed.

[0047] The following description is, therefore, not to be taken in a limited sense, and the scope of the inventive subject matter is defined by the appended claims and their equivalents.

[0048] Blood includes significant information about the functioning of the entire body. A lab-on-a-chip device capable of accurately, rapidly, and affordably analyzing blood components presents opportunities for various medical applications. Lab-on-a-chip often refers to technologies that integrate microfluidics and biosensing to facilitate the performance of tasks typically carried out in a laboratory on a miniaturized scale within a portable or handheld device. [13, 14] Although conventional lab-on-a-chip devices are proficient in handling small fluid volumes ranging from picoliters (pL) to microliters (pL), there are new millifluidic lab-on-a-chip designs emerging that explore the manipulation of fluids in the milliliter (mL) range.

[0015] The present disclosure is directed to a 3D-printed, disposable, and portable millifluidic lab-on-a-chip device 10 to determine the conductivity of blood 14. DevicelO is essentially the first-of-its-kind TENG 22 which usesblood 14 as one of its constituent conductive elements. The electrical conductivity of blood 14 (or a body fluid, a body tissue, a biological substance, a liquid or a solid material) can be assessed via monitoring the voltage generated by device 10. A notable characteristic of device 10 is its ability to function with a few drops of blood 14, allowing for the assessment of electrical conductivity at the Point of Care (POC), without the need for additional equipment or microprocessor device.

[0049] FIG. 1(a) illustrates the schematic of device 10. Device 10 comprises a hollow body 16 having a closed end 18 and an open end 20; a triboelectric nanogenerator (TENG) 22 disposed within hollow body 16.TENG 22 comprises a first disc 24 and a second disc 26 disposed within hollow body 16. First disc 24, having a first surface 23 and a second surface 25, is disposed adjacent to closed end 18 hollow body 16. Second disc 26, having a first surface 27 and a second surface 29, is preferably disposed spaced apart from first disc 24 to define a target chamber 28 within the hollow body 16. A third disc 30, having a first surface 38 and a second surface 39, preferably is spaced apart from second disc 26 towards open end 20 to define a gap 32 between second disc 26 and third 30. A first electrode 34 comprising an electrically conductive material 36 disposed on surface 38 of third disc 30 opposite the gap 32. A second electrode 40 comprising target 12, (such as blood 14 or a body fluid, a body tissue, a biological substance, a liquid or a solid material) in target chamber 28. First disc 24, second disc 26 and / or third disc 30 preferably may comprise polymethyl methacrylate (PMMA). Also, third disc 30 preferably may comprise a polytetrafluoroethylene (PTFE). Preferably, electrically conductive material 36 first electrode 34 comprises an electrically conductive metal such as copper, silver, gold, platinum, aluminum, iron and / or steel. Device 10 may preferably also comprise a push trigger cap 42 disposed in or on open end 20 of hollow body 16. Push trigger cap 42 preferably may be spring-loaded. Additionally, device 10 may preferably voltmeter 48 connected by wire or wirelessly to target chamber 28.

[0050] Device 10 preferably comprises a hollow chamber 28 for blood containment, a polytetrafluoroethylene (PTFE) disc 30, a copper first electrode 34, first and second polymethyl methacrylate (PMMA) disc elements 24, 26, respectively, a spring-loaded push trigger cap 42, and a cap shaft 44. Device 10 is designed for blood samples taken by any type of fingerstick lancing device (preferably 24 gaugelancets) with the blooding being directly transferred to the sealed hollow channel through the transfer tube 46 via the capillary action. The blood infilling the hollow channel creates a conductive layer or electrode 40 sandwiched between two PMMA disc elements 24, 26. The entire blood infilled channel 40, copper electrode 34, PTFE disc 30, and PMMA elements 24, 26 form a TENG 22. [12, 16] FIG. 1(b) shows the operating principle of this blood-based TENG device 10. The vertical contact-separation mode of the device 10 can be described by the coupling of contact electrification and electrostatic induction.[12,16] In device 10, blood will serve as one of the conductive (electrode) layers 40. A copper layer 34 attached to the top of the PTFE disc 30 serves as the other electrode. At the initial stage Stage I 60, the PTFE disc 30 and PMMA disc 26 have no contact, and there is no charge on their surfaces. During Stage II 62, pressing the spring-loaded push trigger cap 42 causes the shaft 42 to move down, bringing the polymeric discs 24, 26 into contact and facilitating surface charge transfer. Electrons are transferred from the PMMA surfaces 25, 27 form to one or more of PTFE surfaces 38, 39. At this point, there is no potential difference between the two electrodes 34, 40. As the shaft 44 moves up in Stage III 64, the polymers separate, creating a potential difference. The open-circuit voltage increases until it reaches a maximum value during Stage IV 66, corresponding to the time it takes for the shaft 44 to return to its original position. If the shaft 44 moves down, the voltage decreases, reaching zero when the polymers discs 24, 26 are fully in contact (Stages IV and II). In each loading and unloading scenario, the spring in the push trigger cap 42 maintains a consistent force. The sole variable in this measurement probe is the blood electrical conductivity. Any change in blood electrical conductivity due to pathological conditions would theoretically alter the baseline voltage signal. The voltage can be measured using any miniaturized voltmeter or data acquisition system wired to the hollow target chamber 28.

[0051] FIG. 1(c) illustrates device 10, 3D printed using PMMA filaments, featuring a dedicated chamber 28 for holding blood samples and displaying the type of voltage signal generated by the device. The conductivity of blood is influenced by the composition and concentrations of electrolytes including salts (sodium chloride (NaCl)) and proteins. While the concentrations of electrolytes in human blood remain somewhat consistent, their complicated impact on the blood conductivity is also recognized. [8,9] Forexample, despite chloride (C1-) having a lower concentration compared to sodium (Na+), its 50% higher mobility positions it as the primary factor contributing significantly to blood conductivity. [9] Glucose (Glc) is an uncharged molecular compound and is not expected to alter blood conductivity. However, it does modify the properties of the medium, thereby influencing the TENG mechanism 22. Other ions, including divalent ions like calcium (Ca) and magnesium (Mg), are minor contributors to blood conductivity.

[0023] The typical levels of Ca in blood are ~2.5 mmol, while Mg levels are lower, ~1 mmol. Both Ca and Mg levels vary within a narrow range (less than twofold). The efficacy of device 10 in detecting blood conductivity was tested in two stages using: 1) simulated body fluid (SBF), and 2) human blood plasma. The electrical conductance of the samples was measured in Siemens unit to explore its correlation with the generated signals. SBF represents a solution with ion concentration comparable to that found in human blood plasma. Corrected SBF (c-SBF) was used for the experiment. The composition of the c-SBF was changed via adding various percentages of NaCl and Glc in order to understand their effect on the solution conductivity. The objective was to observe the impact of variations in the concentrations of NaCl and Glc components, as well as their combined effect on the conductivity of c-SBF. The normal range for blood NaCl levels lies between 135 and 146 mmol L— 1.

[0018] Based on established blood Glc levels for diagnosing diabetes (e.g., [19-21]), we chose Glc concentrations of 5.6 mmol L-l (considered normal), 8.3 mmol L-l (at the upper range for a glucose challenge), and higher levels (up to 16.7 mmol L-l) indicative of diabetic conditions. The objective was to measure the device voltage across a broad spectrum of Glc levels, encompassing those associated with diabetic states.

[0052] A total of twenty-seven devices 10 were manufactured to assess all possible scenarios for both c-SBF and human blood samples. After each test, the samples were discarded. To ensure that the devices consistently produced uniform readings under the same loading conditions, they were tested with five cyclic loadings at a constant amplitude of 25 N applied at a frequency of 1 Hz. This specific loading amplitude was chosen to maintain consistent readings corresponding to a fully compressed state across all devices and solutions. A frequency of 1 Hz was selected due to its promising utility for conductivity measurements, presenting advantages such as mitigating electrode polarization [10,22,23] and potentially falling within amaterial’s frequency-independent range. Moreover, for POC diagnostics, measuring conductivity at low frequencies (e.g., 1 Hz) is arguably more user-friendly and convenient, facilitating quick assessments of blood properties by both patients and clinicians. The solution channel or target chamber 28 was filled with 1 mL of c-SBF and blood for each test. The cyclic loading was then applied to the stationary c-SBF and blood samples stored inside the channel 28. All measurements were conducted at room temperature (25 °C or 77 °F).

[0053] FIG. 2(a) shows the experimental setup. FIGS. 2(b)-(i) presents the voltage and current signals generated by the devices 10 tested using c-SBF and human blood plasma. The percentage difference between the voltage signal peaks throughout the loading cycles was, on average, less than 1% for all twenty-seven tested specimens, indicating an acceptable level of consistency in the measurements. Specifically, the average percentage difference between the voltage signal peaks was 1.03% for the c-SBF specimens and 0.84% for the blood specimens. The slight variation in readings can be attributed to the expected uncertainties inherent in these measurements. FIGS. 2(b) and 2(c) illustrate the variations in the generated voltage and current values with increasing NaCl concentration in c-SBF, while maintaining the Glc level at zero, respectively. FIGS. 2(d) and 2(e) depict the variations of the voltage and current signals with increasing Glc con-centration in c-SBF, with the NaCl level fixed at 147.8 mmol L-l (standard c-SBF level), respectively. FIGS. 2(f) and 2(g) shows the variations of the voltage and current signals with increasing NaCl concentration in c-SBF, while keeping the Glc level fixed at 5.6 mmol L-l (normal fasting blood Glc level), respectively. An important observation from FIG. 2(b) is an increase in voltage as the NaCl concentration is individually raised from 70 mmol L-l to 160 mmol L-l, with Glc held constant at 0 mmol L-l. The averages of the peaks observed in the voltage measurements over five loading cycles in FIG. 2(b) are 17.8 V, 18.39 V, 18.74 V, 19.18 V, 19.83 V, and 19.5 V for the tested NaCl levels of 70 mmol L-l, 120 mmol L-l, 130 mmol L-l, 140 mmol L-l, 150 mmol L-l, and 160 mmol L-l, respectively. The voltage exhibits a nonlinear pattern as the concentration of Glc increases from 1.7 to 16.7 mmol L-l, with a constant NaCl level of 147.8 mmol L-l (Figure 2d). When comparing FIGS. 2(b) and 2(f), it is evident that as the average Glc level increases from 0 to a constant value of 5.6 mmol L-l, the voltage variation exhibitsa nonlinear patern. These observations imply that Glc introduces a nonlinear effect on the solution conductivity. Referring to FIGS. 2(c) and 2(e), the generated current exhibits no discernible patern as the NaCl concentration is individually raised from 70 mmol L-l to 160 mmol L-l with Glc held constant at 0 mmol L-l, and with Glc levels increasing from 1.7 to 16.7 mmol L-l with a constant NaCl level of 147.8 mmol L-l. However, the current exhibits a decreasing trend with simultaneous increases in NaCl from 70 mmol L-l to 160 mmol L-l and Glc levels up to 5.6 mmol L-l (Figure 2g).

[0054] In the second stage of the experiments, 9 human blood samples were tested these were plasma samples obtained as de-identified excess pathologic clinical specimens that had under-gone basic metabolic panel (BMP) testing at the University of Pittsburgh Medical Center (UPMC) Clinical Laboratory and thus with known NaCl and Glc levels. FIGS. 2(h) and 2(i) present the voltage and current generated by the tested devices using the human blood plasma samples, respectively. Under a constant Glc level of 5.6 mmol L-l, a distinct rise in voltage is observed as the NaCl concentration increases from 133 to 137 mmol L-l (FIG. 2(h)). However, at clinically-relevant NaCl levels of 137 and 141 mmol L-l (normal range for blood sodium levels), the voltage shows a decrease as Glc levels increase from 5.6 to 12.8 mmol L-l and from 5.9 to 13.1 mmol L-l. Referring to FIG. 2(i), it is observed that the generated current increases when NaCl is fixed at 135 mmol L-l or 137 mmol L-l, while the Glc levels are increased from 5.6 mmol L-l to 9.0 mmol L-l, or from 5.6 mmol L-l to 12.8 mmol L-l. Overall, altering Glc levels results in a nonlinear correlation between voltage, current, and NaCl. The combined influence of NaCl and Glc on voltage and electrical conductivity reveals a nonlinear relationship, aligning with expectations as reported in. [7-10]

[0055] As voltage yielded more meaningful and less noisy trends compared to current, we assessed the electrical conductivity (S) in Siemens (mS / cm) using a high-precision benchtop conductivity meter to establish the correlation between the device voltage and the conductivity of c-SBF and blood samples. FIG.3(a) illustrates the variations in the measured voltage and S values across all samples. The results indicate that there is a direct, yet nonlinear, correlation between the generated voltage and the conductivity of the samples measured by the conductivity meter. To comprehensively capture this nonlinearity, we developed advanced Al models. Instead of utilizing conventional black-box models like artificial neural networks, weadopted an evolutionary computation method capable of generating functional representations that unveil patterns within the data through predictive equations.

[0024] This approach categorizes the proposed models as gray-box Al models, [24-26] as they provide explicit relationships among data points. FIG. 3(b) presents the proposed Al evolutionary process. In order to investigate the intricate relationship between NaCl, Glc, voltage, and S, two different Al models were created. The initial Al model (Model 1) employed NaCl and Glc as the predictor variables for the generated voltage for different c-SBF and blood samples. The voltage values used for creating the database were the average of the peaks observed in the voltage measurements over five loading cycles depicted in FIGS 2(b), 2(d), 2(f), 2(g). The second model (Model 2) was designed to predict S using only the device voltage as the predictor variable. This is particularly significant in practical scenarios as the device exclusively generates voltage. Thus, the voltage can be directly utilized to estimate the conductivity of the solution without requiring knowledge of NaCl and Glc values. Model 2 was trained using precise measurements of S obtained using the benchtop conductivity meter. For the Al analysis, the available c-SBF and human blood plasma data were randomly divided into training (13 c-SBF and six blood samples) and testing (6 c-SBF and two blood samples) subsets.

[0056] The Al prediction model (Model 1) for the device voltage utilizing NaCl and Glc as the predictor variables is shown in Equation (1):Voltage(V) = exp [sin ((4.74022NaCl - 15.118) (4.9443 NaCl + 1))]- sin (22.095Glc + NaCl x Glc + 4.9443)+ 5.20117sin ((NaCl -4.9443) (NaCl + 110.258)) (1)+ sin (NaCl - NaCl x Glc + 2.788) + 12.382

[0057] FIG 3(c) illustrates a comparison between the measured and predicted voltage values for the training and testing data. The performance indexes used to evaluate the accuracy of the models are correlation coefficient R and mean absolute error (MAE). The acceptable accuracy in predictions suggests that the generated voltage inherently captures the combined effects of NaCl and Glc, making it directly applicable for predicting S. The Al prediction model (Model 2), expressed in Equation (2), correlates S with the device voltage as the sole predictor variable:S (mS / cm) = Voltage / 2 + sin (2Voltage) + sin ( Voltage3)- sin (Voltage + sin (Voltage) + Voltage2)- sin (Voltage) + sin (Voltage (Voltage - 2)) + 1 (2)

[0058] FIG 3(d) displays the predicted S values compared to those measured using the commercial benchtop conductivity meter. The model shows acceptable accuracy in estimating S, with an R value equal to 0.95 and an average error of =0.7 mS cm-1 on the testing / unseen data. The high prediction accuracy implies that the device voltage can be reliably used for conductivity measurements. To further understand the effect of each parameter in the developed models, parametric analyses were conducted. FIG 3(e) shows the parametric analysis carried out using Model 1 by varying the NaCl and Glc concentrations. The results reveal a highly nonlinear relationship among voltage, NaCl, and Glc. The voltage value increases with rising NaCl levels up to a certain range, typically between 130 and 140 mmol L-l, de-pending on Glc concentration, and subsequently begins to de-crease. In contrast to NaCl, Glc variations do not significantly affect voltage and exhibit a nonlinear pattern (Figure 3e). For NaCl concentrations lower than —140 mmol L~l, voltage initially increases as Glc concentration increases from 0 to 5 mmol L-l, and then decreases as Glc concentration further increases from 5 to 15 mmol L-l. In this case, the voltage remains relatively constant even as Glc concentration increases from 10 to 15 mmol L-l. Conversely, for NaCl concentrations higher than —140 mmol L-l, voltage decreases initially as Glc concentration increases from 0 to 10 mmol L-l, and then increases as Glc concentration rises from 10 to 15 mmol L-l. FIG 3(f) shows the parametric analysis for Model 2. As expected, S remarkably increases with increasing the voltage in the model.

[0059] However, the developed Al models are valid for the temperature at which the measurements are taken, i.e., the room temperature (25 °C). Temperature fluctuations are known to influence blood properties and increase its conductivity. [7,27,28] Consequently, variations in testing temperature can impact the voltage generated by the proposed device. While blood samples are typically transported to the laboratory at body temperature (=35- 37 °C), they are often tested at room temperature as part of routine clinical practice. However, in field conditions, blood samples may be exposed to a wide range of temperatures. Therefore, we conducted a series of tests to evaluate the effect of temperatures ranging from 10 °C to 40 °C on the devicevoltage and blood conductivity. The tests were performed using a blood sample with normal baseline fasting NaCl and Glc levels of 135 mmol L-l and 5.61 mmol L-l, respectively, at seven temperatures: 10, 20, 25, 30, 35, and 40 °C. Figure 3g shows the variation of the device voltage for different temperatures. FIG 3(h) shows the averages of the voltage peaks observed over five loading cycles in Figure 3g along with the corresponding S values. Referring to FIGS 3(g), (h), the device voltage and S are influenced by temperature variations. As seen in FIG 3(h), the device voltage and S exhibit a nearly linear increase with increasing temperature, fitted with a linear regression yielding a determination coefficient (R2) of 0.89. Below room temperature, the increase in the conductivity and device voltage values is not significant, but it becomes more pronounced thereafter. Particularly, there is a notable increase in the S values from 25 °C to 30 °C, which then stabilizes slightly at higher temperatures. The enhanced voltage and S at higher temperatures can be attributed to increased ion mobility in the blood, which improves the capacity to carry electrical current, coupled with decreased viscosity that facilitates the movement of charged ions. The voltage and S values at 10 °C are 3.3% and 3.6% lower compared to those measured at room temperature, respectively. At 40 °C, the voltage and S values are 11.5% and 11.3% higher than those at room temperature, respectively. These insights highlight the need to carefully consider temperature effects when deploying tire proposed device in practical field applications. Plots and equations similar to those shown in FIG 3(h) can serve as valuable tools for calibrating measurements acquired by the device at temperatures divergent from the initial testing temperature, thus facilitating the optimization of associated Al models.

[0060] Electrical conductivity is a fundamental property of fluids, offering crucial insights into their composition, ionic strength, and other parameters. Measuring blood conductivity carries essential diagnostic implications. For example, it reveals electrolyte imbalances, dehydration, and potential underlying medical conditions. I’-3! Traditional methods for blood conductivity measurement, such as conductivity meters, impedance plethysmography, bioimpedance analysis (BIA), electrical impedance tomography (E1T), four-electrode conductivity measurement, electrochemical sensors, microwave-based techniques, dielectric spectroscopy, and capacitance sensors provide reliable conductivity measurement. Nevertheless, certain significant concerns associated with these methods include their dependence on external power sources,intricate calibration procedures and setups, and the incorporation of complex embedded electronic components. The majority of these methods require precise electrode placement which can affect measurement accuracy, especially in dynamic settings like blood flow or changes in body position.Additionally, these methods often rely on assumptions about tissue types; therefore, the presence of varying tissue compositions (e.g., fat, muscle, bone) can introduce measurement errors. Standard conductivity meters utilize external electrodes immersed in a solution requiring careful calibration and potential interference from ambient electrical signals. Impedance plethysmography is sensitive to electrode placement and pressure variations. The BIA and EIT techniques use electrodes on the body’s surface and require complex algorithms to interpret conductivity changes within tissues. Their performance is affected by hydration status, temperature, and body composition. The widely used four-electrode conductivity measurement method reduces errors from contact resistance, but still necessitates external electronics and power. In addition, electrode polarization can affect its accuracy over time.'10'22’23' Electrochemical sensors, microwave-based techniques, dielectric spectroscopy, and capacitance sensor methods often rely on specialized sensor configurations and instrumentation.[29-35]

[0061] FIG 4 presents a comparison of standard conductivity measurement methods with the proposed millifluidic lab-on-a-chip device, based on sensitivity, power autonomy levels, versatility, and POC diagnostics features. The high, moderate, and low levels depicted in this figure represent qualitative measures. Besides comparing the operating frequency of the devices, there are no other definitive quantitative indices available to directly evaluate these methods against our approach. For instance, sensitivity generally refers to the ability of devices to detect changes in electrical conductivity. This attribute strongly relies on the instrument’s electrode design and material, circuitry, and signal processing capabilities. Based on these considerations, the sensitivity classification of the proposed device is moderate, as its performance is influenced by factors such as the selection of materials for designing the TENG components and the specific printing techniques employed. However, the proposed device, with its self-powered nanogenerator, offers a level of simplicity and portability. By eliminating the need for embedded electronics and external electrodes, the device streamlines the measurement process, making it user-friendly and suitablefor POC applications. It potentially reduces the risk of contamination as it indirectly measures conductivity in the fluid of interest. Moreover, the self-powering feature of the device facilitates its miniaturization, making it suitable for exploring intricate fluid dynamics and solution properties. This feature also makes the device not only sustainable, but also highly adaptable to resource-limited settings.

[0062] While traditional methods may be specialized for conductivity measurements in specific liquids, the proposed device stands out in its adaptability. The self-powered nanogenerator can be calibrated to measure electrical conductivity in a wide range of materials beyond blood including tissues, biological substances, liquids and solid materials. This versatility extends the device’s utility to various applications, including environmental monitoring, industrial quality control, and scientific research.

[0063] Measuring blood conductivity at low frequencies is crucial not only for specific medical applications, but also for a better understanding of the body’s electrical properties and fundamental biological processes.11-31FIG 4 also summarizes the minimum operation frequency of methods used for measuring the conductivity of liquids including blood. The maximum operation frequencies are also shown in this figure. The presented minimum and maximum frequency levels are derived from an analysis of studies utilizing a range of measurement techniques such as conductivity meters[31,32]impedance plethysmography[33,34]BIA, [35-37] EIT[38,39]four-electrode conductivity measurement

[10] electrochemical sensors[39,40]microwave-based techniques[41,42]and dielectric spectroscopy.[43-45]These studies encompass a diverse array of liquids, extending beyond the scope of blood. Currently, there is a lack of data on the electrical conductivity of human blood at frequencies lower than 100 Hz. The challenge in measuring blood conductivity at frequencies lower than 100 Hz arises from electrode polarization, which can distort accuracy during the measurement process. Despite the capability of conductivity meters and electrochemical sensors to function at frequency levels ~1 Hz, they are commonly utilized within the kHz range [31,46]Micro wave-based techniques commonly operate in the GHz range, while dielectric spectroscopy is typically employed in the MHz range.[5,41,42]Microwave techniques rely on the interaction of microwaves with the material to determine its electrical properties. At these higher frequencies, the interaction with the material’s conductivity becomes more prominent compared to other factors

[47] Nevertheless, none of these methods hasbeen utilized to assess blood conductivity at frequencies below 100 Hz. The four-electrode conductivity method stands as the sole technique recently employed for measuring the conductivity of human blood samples across frequencies ranging from 100 Hz to 100 kHz.

[10] Unlike these traditional methods, the proposed lab-on-a-chip device tackles this challenge through two key features. First, external electrode polarization concerns are eliminated as the blood itself functions as the electrode within the system.Additionally, there is no direct contact with the blood sample during the conductivity measurement. Second, the device operates as a TENG system, known for its efficiency at low frequencies (<1 — 20 Hz)[48,49]This makes it an ideal choice for applications requiring low-frequency measurements. Exploring blood conductivity at such low frequencies can contribute to the comprehension of the electrical behavior of blood at the cellular and molecular levels. This knowledge can offer insights into diverse physiological processes within the body.[4]

[0064] Direct measurement of Het from blood electrical conductivity has been fully validated (e.g. [1,7,50]), representing a practical and safe application for the proposed millifluidic device. Low frequency blood electrical conductivity measurements, in particular, can also be a potentially useful marker for fields like electrocardiography (ECG), which utilizes electrical signals for monitoring heart activity, and functional electrical stimulation (FES), employing electrical currents to stimulate muscles for therapeutic purposes. In the context of treatment development, studying changes in blood electrical conductivity resulting from electrical fields can be seen as a valuable tool complementing innovative medical treatments that utilize electrical fields. This includes procedures like pulsed field ablation, where low frequency electric fields are employed to eliminate abnormal tissue

[51] or tumor electric field therapy, where low and intermediate frequency electric fields are employed to slow tumor growth for certain types of brain tumors.

[0052] It should be noted that cancerous cells have different properties than healthy cells, including their size, shape, and membrane composition. Tumors can cause changes in blood composition, such as increased levels of electrolytes or proteins[53-55]These variances can hypothetically affect the overall electrical conductivity of the blood.

[0065] A preferred device of the present disclosure 10 could be clinically relevant for diagnosing conditions associated with changes in NaCl levels in the blood. Diseases disrupting electrolyte balance, such as kidney disease, heart failure, and liver cirrhosis, often result in low NaCl levels J37’38! Conversely, conditions associated with high NaCl levels (hypernatremia) are also clinically important.[’9]For example, severe dehydration, where fluid loss exceeds intake, can lead to elevated sodium levels due to increased blood concentration, [59,60]Advanced kidney diseases can result in an inability to excrete excess sodium, causing its accumulation in the blood[61,62]Future research could also explore how other ions with minor contributions to blood conductivity, such as Ca and Mg, might be utilized for diagnosing diseases such as hypoparathyroidism, chronic kidney disease, and Paget’s disease of bone, which are closely linked to changes in Ca and Mg levels in blood [63,64]The concept of using blood conductivity for the diagnosis of diabetes presents another intriguing research avenue. Among the limited research studies focused on diagnosing diabetes using blood conductivity, there are conflicting findings and lack of consensus. Although the proposed millifluidic device itself cannot be directly used for diagnosing diabetes, one notable feature of its associated Al-based blood conductivity prediction model (Equation (2)) is the ability to operate effectively across a wide range of Glc levels. Such models could prove to be valuable tools for analyzing the conductivity of diabetic samples on a larger scale in future research, with the goal of uncovering potential correlations between conductivity and diabetes.

[0066] The present disclosure preferably presents a new technology for measuring electrical conductivity of blood, body fluids, tissue, biological substances, liquids and solid materials through the development of a self-powered millifluidic lab-on-a-chip device equipped with a nano generator. The device 10 is the first ever TENG system using blood as a part of its contact-electrification mechanism. The blood electrical conductivity can be determined via monitoring the voltage generated by the proposed blood-based TENG system. Operating as a TENG system, the device proves optimal for applications requiring low-frequency measurements (<1-20 Hz). A preferred device 10 of the present disclosure can be miniaturized to serve as a nanofluidic and microfluidic lab-on-a-chip device.

[0067] FIG. 5 and FIG. 6 show another preferred embodiment of a device 70 of the present disclosure comprises a first layer 73 that functions as an upper structural enclosure comprising a thermoplastic polymer, photopolymer resin, thermoset composite, or metal housing. Second layer 74 is an elastic dome element of device 70 that preferably may comprise a metal dome, a spring-loaded conductive membrane, or conductive elastomer film. Third layer 75 is an intermediate mechanical support frame preferably comprising a polymer frame, an insulating composite spacer, or rigid dielectric plate. Fourth layer 76 is an upper conductive electrode layer preferably comprising metallic foil, conductive polymer coating, carbon-based electrode, or printed conductive ink. Fifth layer 77 is a dielectric interface layer preferably comprising a fluoropolymer, elastomer, ceramic thin film, or dielectric composite sheet. Sixth layer 78 is a lower conductive electrode layer preferably comprising a metallic foil, conductive carbon sheet, conductive ink film, or nanocomposite electrode. Seventh layer 79 is a lower structural substrate preferably comprising a rigid polymer base, metal support plate, or composite substrate. Reaction chamber 71 preferably comprises a micro fluidic reaction module, disposable microchamber, cartridge, or chip made of polymeric or glass materials. Test medium 80 such as blood 14 preferably comprises an analyte-containing or conductive test medium such as biofluids (blood, plasma, serum), electrolyte solutions, chemical reagents, or conductive media.Functional Description with Layer Identification

[0068] The device 70 comprises a multilayer triboelectric-based sensing assembly mechanically integrated with a micro fluidic reaction chamber 71. Layer 1 73 functions as the upper structural enclosure, providing mechanical protection and confinement for the actuator. Layer 274 is an elastic conductive dome element that deforms under applied pressure to generate relative motion within the stack. Layer 3 75 serves as an intermediate support frame that maintains spacing and alignment of the upper and lower components.

[0069] Beneath this frame, Layer 476, Layer 5 77, and Layer 678 form a conductive-dielectric-conductive sandwich structure. Layer 476 acts as the upper conductive electrode, Layer 5 77 is the dielectric interface layer responsible for charge accumulation and separation, and Layer 678 functions as the lower conductive electrode electrically coupled to the external circuitry. Layer 779 forms the lower structural substrate, which supports the electrode assembly and interfaces with the underlying reaction chamber.

[0070] The reaction chamber 71 holds a test medium 80, which may include biological fluids, blood 14, chemical reagents, or synthetic conductive substances. During operation, deformation of the dome element 74 initiates contact-separation cycles across the dielectric interface 77, inducing triboelectric and electrostatic charge transfer. The electrical response varies according to the conductivity or permittivity of the test medium 80, enabling label-free detection and quantitative analysis of analytes. The device 70 operates without an external power source, using mechanical actuation to generate measurable voltage signals correlated with the characteristics of the test medium 80.

[0071] In the foregoing Detailed Description, various features are grouped together in a single embodiment to streamline the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments of the disclosure require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.References

[0001] R. H. Okada, H. P. Schwan, IRE Trans. Med. Electron. 1960, ME-7, 188.[2] T.-X. Zhao, Med. Eng. Technol. 1996, 20, 115.[3] W. G. Kubicek, J. N. Karnegis, R. P. Patterson, D. A. Witsoe, R. H. Mattson, Aerosp. Med. 1966, 37, 1208.Hi E. Dalle, M. V. Mabandla, W. M. Daniels, Oxidative Medicine and CeUular Longevity. 2020, 2020.[5] S. Abdalla, S. S. Al-Ameer, S. H. Al~Magaishi, Biomicrofluidics. 2010, 4, 034101.[6] M. I. Altaf, M. Reddy, A. Ahmad, Dielectric properties of human blood of patients suffering from renal failure, in AIP Conference Proceedings (Vol. 2200, No. 1). AIP Publishing, 2019, December. p] N. Istuk, A. La Gioia, H. Benchakroun, A. Lowery, B. McDermott, M. O’Halloran, IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology. 2022, 6, 184.[8] F. G. Hirsch, E. C. Texter, L. A. Wood, W. C. Ballard, F. E. Horan, I. S. Wright, Blood. 1950, 5, 1017.[9] A. F. Kadjo, B. N. Stamos, C. P. Shelor, J. M. Berg, B. C. Blount, P. K. Dasgupta, Anal. Chem. 2016, 88, 6531.[io] N. Istuk, A. La Gioia, H. Benchakroun, D. O’Loughlin, A. Lowery, E. Porter, M. O’Halloran, in 2021 XXXIVth General Assembly and Sci-entific Symp. of the Int. Union of Radio Science (URSI GASS) 1-4. IEEE, 2021

[0011] C. Gabriel, A. Peyman, E. H. Grant, Phys. Med. Biol. 2009, 54, 4863.

[0012] F.-R. Fan, Z.-Q. Tian, Z. L. Wang, Nano Energy. 2012, 1, 328.

[0013] M. I. Mohammed, S. Haswell, I. Gibson, Proc. Technol. 2015, 20, 54.

[0014] V. C. Romao, S. A. Martins, J. Germano, F. A. Cardoso, S. Cardoso, P. P. Freitas, ACS Nano. 2017, 11, 10659.

[0015] R. Cartlidge, D. Nugegoda, D. Wlodkowic, Sens. Actuators, B. 2017, 239, 660.

[0016] Z. L. Wang, L. Lin, J. Chen, S. Niu, Y. Zi, Triboelectric nanogenerators, Springer, Switzerland 2016, pp. 23—47.

[0017] E. D. Trutman, R. S. Newbower, IEEE Trans. Biomed. Eng. 1983, BME-30, 141.

[0018] N. I. Dmitrieva, D. Liu, C. O. Wu, M. Boehm, Eur. Heart J. 2022, 43, 3335.

[0019] M. B. Davidson, D. L. Schriger, A. L. Peters, B. Lorber, JAMA. 1999, 281, 1203.

[0020] K. Rave, L. Nosek, J. Posner, T. Heise, K. Roggen, E. J. van Hoogdalem, Nephrol., Dial., Transplant.2006, 21, 2166.

[0021] L. Liu, X. Wan, J. Liu, Z. Huang, X. Cao, Y. Li, Diabetes technology therapeutics. 2012, 14, 756.

[0022] H. P. Schwan, Ann. N. Y. Acad. Sci. 1968, 148, 191.

[0023] M. Gal,azka, N. Osiecka-Drewniak, Crystals. 2022, 12, 1797.

[0024] Q. Zhang, K. Barri, P. Jiao, H. Salehi, A. H. Alavi, Artif. Intell. Rev. 2021, 54, 1863.

[0025] O. Giustolisi, A. Doglioni, D. A. Savic, B. W. Webb, Environ. Model. Softw. 2007, 22, 674.

[0026] C. Ferreira, Complex Syst. 2001, 13, 87.

[0027] W. Wang, W. Li, B. Liu, L. Wang, K. Li, Y.u Wang, Z. Ji, C. Xu, X. Shi, Front. Physiol. 2022, 13, 1053233.

[0028] C. Rossmann, D. Haemmerich, Critical ReviewsTM in Biomedical Engineering. 2014, 42.

[0029] P. A. Sullivan, C. D. Still, S. T. Jamieson, C. B. Dixon, B. A. Irving, J. L. Andreacci, Obes. Sci. Pract. 2018, 5, 141.

[0030] Y. Shi, Z. Yang, F. Xie, S. Ren, S. Xu, Front. Bioeng. Biotechnol. 2021, 9, 726652.

[0031] O. Velychko, S. Shevkun, M. Dobroliubova, Sens. Transducers. 2019, 237, 171.

[0032] G. C. Wakde, V. R. Raghorte, G. B. Pethe, A. S. Kakde, C. M. Dudhe, U. A. Palikundwar, Ferroelectrics. 2022, 587, 18.

[0033] J. Nyboer, M. M. Kreider, L. Hannapel, Circulation. 1950, 2, 811.

[0034] J. A. Kaufman, M. J. Lee, 2013. Vascular and interventional radiology: the requisites e-book, Elsevier Health Sciences.

[0035] D. H. Diaz, O. Casas, R. Pallas-Areny, in 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, IEEE, 2010, August, pp. 6489-6492.

[0036] M. Y. Jaffrin, Current Opinion in Clinical Nutrition Metabolic Care.2009, 12, 482.

[0037] Y. Yu, G. Anand, A. Lowe, H. Zhang, A. Kalra, Sensors. 2022, 22, 4736.

[0038] J. Padilha Leitzke, H. Zangl, Sensors. 2020, 20, 5160.

[0039] H. S. Magar, R. Y. Hassan, A. Mulchandani, Sensors. 2021, 21, 6578.

[0040] A. Zhbanov, S. Yang, Anal. Methods. 2017, 9, 3302.

[0041] S. Biju-Kumar, K. T. Mathew, U. Raveendranath, P. Augustine, J. Mi-crow. Power Electromagn. Energy. 2001, 36, 67.

[0042] J. Ma, Z. Wu, Q. Xia, S. Wang, J. Tang, K. Wang, L. Guo, H. Jiang, B. Zeng, Y. Gong, Electronics.2020, 9, 1200.

[0043] M. Wolf, R. Gulich, P. Lunkenheimer, A. Loidl, Biochim. Biophys. Acta Gen. Subj. 2011, 1810, 727.

[0044] K. F. Dobiszewski, Dissertations. 2013. 387.

[0045] K. Deshmukh, S. Sankaran, B. Ahamed, K. K. Sadasivuni, K. S. Pasha, D. Ponnamma, P. S. Rama Sreekanth, K. Chidambaram, 2017. in Spectroscopic Methods for Nanomaterials Characterization, 237- 299. Elsevier.

[0046] S. Kerai, Y. Hamoudi, Metrologies. 2023, 22.

[0047] J. M. Alison, R. J. Sheppard, Phys. Med. Biol. 1993, 38, 971.

[0048] K. Barri, Q. Zhang, I. Swink, Y. Aucie, K. Holmberg, R. Sauber, D. T. Altman, B. C. Cheng, Z. L. Wang, A. H. Alavi, Adv. Funct. Mater. 2022, 32, 2203533,

[0049] C. Liu, N. Zhang, J. Li, L. Dong, T. Wang, Z. Wang, G. Wang, X. Zhou, J. Zhang, Nano Energy. 2019, 65, 104011.

[0050] K. Cha, R. G. Faris, E. F. Brown, D. W. Wilmore, Physiol. Meas. 1994, 15, 129.

[0051] H. Wu, C. Wang, J. Liu, D. Zhou, D. Chen, Z. Liu, A. Wu, L. Yang, J. Chang, C. Luo, W. Cheng, S. Shen, Y. Bai, X. Mu, C. Li, Z. Wang, L. Chen, CNS Neuroscience Therapeutics. 2020, 26, 1168.

[0052] Y. Wang, T. A. Jiang, L. Xie, H. Wang, J. Zhao, L. Xu, C. Fang, Front. Oncol. 2022, 12, 899722.

[0053] D. Bennet, Y. Khorsandian, J. Pelusi, A. Mirabella, P. Pirrotte, F. Zenhausern, Clin. Transl. Med. 2021, 11, e461.

[0054] C. D. Duong, J. Y. Loh, J. Oncol. Pharm. Pract. 2006, 12, 223.

[0055] B. M. Syed, S. M. Memon, F. Shah, S. Mughal, J. Naeem, Advances in Cancer Research Clinical Imaging. 2020, 3.

[0056] M. J. Flanigan, Kidney Int. 2000, 58, S72.

[0057] M. A. Gibbs, V. S. Tayal, Rosen’s emergency medicine: concepts and clinmcal practice. 2006, 1724.

[0058] T. Dhondup, Q. Qian, Blood Purif. 2017, 43, 179.

[0059] S. A. Muhsin, D. B. Mount, Best Pract. Res. Clin. Endocrinol. Metab. 2016, 30, 189.

[0060] D. R. Thomas, T. R. Cote, L. Lawhorne, S. A. Levenson, L. Z. Rubenstein, D. A. Smith, R. G.Stefanacci, E. G. Tangalos, J. E. Morley, JAMDA. 2008, 9, 292.

[0061] V. Soi, J. Yee, AKDH. 2017, 24, 325.

[0062] D. Malta, K. S. Petersen, C. Johnson, K. Trieu, S. Rae, K. Jefferson, J. A. Santos, M. M. Y. Wong, T. S. Raj, J. Webster, N. R. C. Campbell, J. Arcand, J. Clin. Hypertens. 2018, 20, 1654.

[0063] H. Al-Azem, A. A. Khan, Best Pract. Res. Clin. Endocrinol. Metab. 2012, 26, 517.

[0064] N. J. Y. Woodhouse, Clin. Endocrinol. Metab. 1972, 1, 125.

[0065] M. Kanbay, D. Goldsmith, M. E. Uyar, F. Turgut, A. Covic, Blood Purif. 2010, 29, 280.

[0066] M. A. Elblbesy, Med. Devices: Evidence Res. 2019, 12, 435.

Claims

What is claimed is:

1. A device for measuring electrical conductivity of target (“Target”) comprising blood, a body fluid, a body tissue, a biological substance, a liquid or a solid material, comprising:a hollow body having a closed end and an open end;a triboelectric nanogenerator (TENG) disposed within the hollow body; the TENG comprising first and second discs disposed within the hollow body, wherein the first disc is disposed adjacent to the closed end of the hollow body and the second disc is spaced apart from the first disc to define a target chamber within the hollow body;a third disc spaced apart from the second disc towards the open end to define a gap between the second and third discs;a first electrode comprising an electrically conductive material disposed on a side of the third disc opposite the gap; anda second electrode comprising a Target in the target chamber.2 The device for measuring electrical conductivity' of a Target of claim 1, further comprising a push trigger cap disposed on the open end of the hollow body, wherein the push trigger cap has a shaft connected between the push trigger cap and the first electrode.3 The device for measuring electrical conductivity of a Target of claim 1, further comprising a transfer tube for transferring the Target from outside the hollow body into the target chamber.4 The device for measuring electrical conductivity of a Target of claim 1, wherein each of the first and second discs comprises polymethyl methacrylate (PMMA).5 The device for measuring electrical conductivity of a Target of claim 2, wherein the push trigger cap is spring-loaded.6 The device for measuring electrical conductivity of a Target of claim 1, wherein the third disc comprises a polytetrafluoroethylene (PTFE).7 The device for measuring electrical conductivity of a Target of claim 1, wherein the electrically conductive material of the first electrode comprises an electrically conductive metal or is selected from a group of copper, silver, gold, platinum, aluminum, iron and steel.

8. The device for measuring electrical conductivity of a Target of claim 1, further comprising a voltmeter in communication wirelessly or by wire to the target chamber.

9. The device for measuring electrical conductivity of a Target of claim 1, wherein the TENG provides electronic-free wireless transmission of data sensed by the device.

10. The device for measuring electrical conductivity of a Target of claim 1, wherein at an initial stage, the third disc and the second disc have no contact, and there is no charge on their surfaces; wherein pressing a spring-loaded push trigger cap causes a shaft to move down, bringing the second and third discs into contact and facilitating surface charge transfer therebetween where electrons are transferred from one or more surfaces of the second disc to one or more surfaces of the third disc whilst there being no potential difference between the first and second electrodes; wherein as the shaft moves up, the second and third discs separate, creating a potential difference with an open-circuit voltage increasing until it reaches a maximum value corresponding to a time it takes for the shaft to return to an original position; wherein when the shaft moves down, voltage decreases, reaching zero when the third disc and the second disc are in contact and wherein in each loading and unloading cycle, the spring in the push trigger maintains a consistent force and a sole variable within the TENG device is electrical conductivity of the Target in the target chamber.

11. A device for measuring electrical conductivity of target (“Target”) comprising blood, a body fluid, a body tissue, a biological substance, a liquid or a solid material, comprising:a triboelectric nanogenerator (TENG) comprising first and second discs, wherein the first disc is spaced apart from the second disc to define a target channel;a third disc spaced apart from the second disc to define a gap between the second and third discs; a first electrode comprising an electrically conductive material disposed on a side of the third disc opposite the gap; anda second electrode comprising a Target in the target chamber.

12. The device for measuring electrical conductivity of a Target of claim 11, wherein each of the first and second discs comprises polymethyl methacrylate (PMMA).

13. The device for measuring electrical conductivity of a Target of claim 11, wherein the third disc comprises a polytetrafluoroethylene (PTFE).

14. The device for measuring electrical conductivity of claim 11, wherein the electrically conductive material of the first electrode comprises an electrically conductive metal or is selected from a group of copper, silver, gold, platinum, aluminum, iron and steel.

15. A triboelectric nano generator (TENG) wherein a target comprising blood, a body fluid, a body tissue, a biological substance, a liquid or a solid material comprises an electrode or a component of the TENG.

Images