Nanostructured Biomimetic Superconductive Devices of Making and Its Multiple Applications Thereto

Abstract

A multiple functioning superconductive device was invented based on Toroidal Josephson Junction (FFTJJ) array with 3D-cage structure self-assembled organo-metallic superlattice membrane. The device not only mimics the structure and function of an activated Matrix Metalloproteinase-2 (MMP-2) protein, but also mimics the cylinder structure of the Heat Shock Protein (HSP60) protein, that works at room temperature under a normal atmosphere, and without external electromagnetic power applied. The device enabled direct rapid real-time monitoring atto-molarity concentration ATP in biological specimens and was able to define the anti-inflammatory and pro-inflammatory status revealed a transitional range of ATP concentration under antibody-free, tracer-free and label-free conditions.

Claims

1. A multiple-functioning superconductive device comprising (a) an electrode has an organo-metallic superconductive membrane having arrays of the 3D-nanocage structure by self-assembled cross-linked polymers with transition metal ions; (b) a direct electron-relay within a biomimetic matrix metalloproteinase-2 (MMP-2) membrane and a media comprising of imidazole modified cyclodextrin and ATP formed chelating coordinating bounds, forming a long range direct electron-transfer (DET) chain; (c) the superconductive organo-metallic membrane comprises of Toroidal Josephson Junction (FFTJJ) array.

2. According to claim 1, wherein the superconducting membrane has Friedel-oscillation.

3. According to claim 2, wherein the Friedel-oscillating superconductor mimics the cylinder structure of the Heat Shock Protein (HSP60) protein working at room temperature under a normal atmosphere, and without external electromagnetic power applied.

5. According to claim 1, wherein the device direct rapid real-time monitored atto-molarity concentration ATP in biological specimens having point accuracy higher than 96% with imprecision errors less than or equals to 2% at a 100 aM and 60 nM levels ATP concentration levels, compared with the controls, respectively.

4. According to claim 1, wherein the device has multiple-functioning of defining the transformational immunomodulant between the Anti-inflammatory) and the Pro-inflammatory status in extracellular ATP concentration range was demonstrated at 10 kHz.

5. According to claim 1, wherein the device has multiple-functioning of monitoring the normality of the cell reversible membrane potential (RMP) for the ATP concentration between 100 aM to 800 nM using the voltage method at 10 nA with each potential step at 0.25 Hz.

6. According to claim 1, wherein the device has multiple-functioning of monitoring the clinical normality of the ratio of the cell action potential vs. resting potential in ATP extracellular level higher than 100 aM and lower than 400 nM is normal in the ratio.

7. According to claim 1, wherein the device has multiple-functioning used for assessing milk immunological characteristics in preventing extracellular ATP hydrolyzation using biological specimens.

8. According to claim 1, wherein the biomimetic activated MMP-2 superconductive device (through heating for activation) direct quantitatively detect ATP in the range between 100 aM to 200 nM with a relative pooled standard deviation (RPSD) 0.24%, and a DOL value is 46 aM using the voltage method.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0016] FIG. 1A depicts the 2D AFM membrane image in the native state of the biomimetic MMP-2 device. FIG. 1B depicts the cross-section analysis of the AFM membrane image.

[0017] FIG. 2A depicts the 3D AFM image of the activated biomimetic MMP-2 Sensor 1 by the heating method. FIG. 2B depicts the enlarged 2D AFM image with the same z value range between 33.2 to 21.4 nm as the native state device in FIG. 1A for comparison.

[0018] FIG. 3A depicts the 2D image of the multiple-layer ring structure of the activated biomimetic MMP-2 Sensor 2 by the direct fabrication method in 0.7340.734 m.sup.2. The ring structure parameters labeled as 1 are listed. FIG. 3B depicts the cross-section analysis of the AFM membrane image. FIG. 3C depicts the 3D AFM image from the bird-view. FIG. 3D depicts the enlarged image in 0.90.9 m.sup.2 shown in the flat area in FIG. 3I. FIG. 3E depicts the alternative band deep-band flat formation of the membrane which promotes the Cooper-pair electron cloud mobility in 1.61.6 m.sup.2. FIG. 3F depicts the enlarged 2D AFM image at high sensor mode in a top view of the biomimetic Heat Shock Protein (HSP) 60 chaperone structure having 7 subunits as shown on the top. The arrow indicates the mobile zinc ions. FIG. 3G depicts the top view in an amplitude mode of the AFM image of the large single porous biomimetic HSP60 structure. FIG. 3H depicts the side view of the 3D AFM image in high sensor mode for the single porous structured in 33.6 m.sup.2. FIG. 3I depicts the 3D AFM image of the tall cylinder structure of the biomimetic HSP60 in 1010 m.sup.2.

[0019] FIG. 4 illustrates the scheme of the steps of direct detection of ATP using the 3D-nanocage structure biomimetic MMP-2 membrane sensor/superconductor approach. Step 1: the Direct Electron-relay (DER) model of the 3D-nanocage polymer network structure between the zinc ions from the activated biomimetic MMP-2, by elimination of the cysteine group from the polymer mixture of dm--DMCD/TCD/PEG/PVP/ZnCl.sub.2 before deposited on the gold chip, and the mm--DMCD (short names as MCD) in tris/HCl buffer. Step 2: Form a long range DET in the presence of Tris/MCD media with ATP being included in the cyclodextrin cavities, that not only stabilized ATP, but also invited ATP participated in the long range direct electron-relay chain between the media and the 3D-nanocage membrane electrode assembling (MEA); Step 3: the ATP interacts with the cage polymer network molecules forming enhanced DER without a need for an external power supply.

[0020] FIG. 5A depicts activated Sensor 1 by the heating method's i-V curves in different scan rate from 1 Hz to 25 kHz in pH 7.8 buffer (20 mM Tris/HCl buffer with 3 mM KCl, 130 mM NaCl and 0.5 g/mL MCD), in short, as the Tris/HCl/MCD buffer. FIG. 5B depicts Sensor 1's i-V curves under the influence of ATP concentrations over 40 fM to 60 nM compared with the control under the scan rate 60 Hz in the Tris media.

[0021] FIG. 6 depicts the scan rate impacts on the i-V curves of the activated state biomimetic MMP-2 Sensor 2, by the direct fabrication method, over scan rate from 1 Hz to 25 kHz in the tris/HCl/MCD media.

[0022] FIG. 7 depicts Sensor 2's i-V curves transformation between memristive to superconductive at zero-bias potential under the influence of ATP from 25 aM to 2 M compared with the control with a 60 Hz scan rate in the tris/HCl/MCD media. The Panel A is the i-V curves for ATP 25 aM compared with the control; the Panel B is for the i-V curve having 400 aM; the Panel C: ATP 400 fM; the Panel D: ATP 200 pM; The Panel E: ATP 200 nM; the Panel F: ATP 2 M.

[0023] FIG. 8 depicts the comparison of the superconducting i-V curves at the zero-bias potential for Sensor 2 under the influence of ATP from 200 fM to 200 M compared with the control under a 10 kHz scan rate in the tris/HCl/MCD media. The Panel A: is the control; the Panel B: ATP 200 fM; the Panel C: ATP 400 fM; the Panel D: ATP 200 pM; the Panel E: ATP 200 nM; the Panel F: ATP 400 nM; the Panel G: ATP 800 nM; the Panel H: ATP 2.0 M, and the Panel I: ATP 200 M in the media.

[0024] FIG. 9 depicts the supercurrent vs. ATP concentration curves of the DET.sub.red and DET.sub.ox peaks at the zero-bias potential with a 60 Hz scan rate for Sensor 2. The ATP concentration ranges are from 400 aM to 2 M. Data obtained according to Figures from FIG. 7B to 7F.

[0025] FIG. 10 depicts the supercurrent vs. ATP concentration curves of the DET.sub.red and DET.sub.ox peaks at the zero-bias potential at a 10 kHz scan rate for Sensor 2. The ATP concentration ranges are from 200 fM to 200 M. Data obtained according to FIGS. 8A to 8I.

[0026] FIG. 11 depicts the impact of ATP concentrations at the Josephson junction on the supercurrent and the impact on the phase change of the waves at the zero-bias potential during 10 consecutive scans at 60 Hz over the ATP concentrations from 400 fM (the Panel A), 200 pM (the Panel B), 200 nM (the Paneol C), and to 2.0 M (the Panel D) in the Tris/HCl/MCD media.

[0027] FIG. 12A depicts 25 aM low concentration ATP in consecutive 5 scan cycles of san rate 60 Hz i-V curves compared with the control of Sensor 2. There was no phase change occur, and keeping the hysteresis curves. FIG. 12B depicts 400 fM concentrations ATP in consecutive 9 scan cycles of san rate 60 Hz i-V curves compared with the control, having a phase change occur and superconducting at zero-bias potential. FIG. 12C also depicts in the presence of 200 nM ATP concentrations, Sensor 2 shows the phase change and superconducting current at 60 Hz san rate.

[0028] FIG. 13 depicts the 3D dynamic map of the relationships over 5 level ATP concentrations from 0.2 pM to 2.0 M over the potential range between 40 mV to +40 mV for illustration of the relationship among ATP concentrations, zero-bias potential and the differential quantum conductance using 10 kHz scan rate forwarding scan data.

[0029] FIG. 14 depicts Sensor 1's real-time direct monitoring of current vs. time profiles over ATP concentrations over 100 aM to 400 nM (9 levels from curve a to k) vs. controls in the buffer solution. Samples run triplicates.

[0030] FIG. 15 depicts the lower end concentration curves from a (the control) to e. Inserts are enlarged view for low end concentration compared with controls.

[0031] FIG. 16 Panel A depicts the calibration curve of current density after subtracted the background current vs. ATP over 100 aM to 170 nM. FIG. 16 Panel B depicts the calibration curve over the linear range from 400 fM to 170 nM. Each sample run triplicates.

[0032] FIG. 17 depicts Sensor 2's open circuit potential curves for monitoring the energy change over 25 aM-400 pM ATP.

[0033] FIG. 18 depicts the calibration curve of voltage vs. ATP concentrations over 25 aM-400 pM.

[0034] FIG. 19 depicts Sensor 2's open circuit potential curves at the high end ATP concentration over 0.8 nM to 2.0 M.

[0035] FIG. 20 depicts the double log plot of the calibration curve of the open circuit potential vs. ATP concentrations from 0.8 nM to 2.0 M.

[0036] FIG. 21 depicts Sensor 2's voltage vs. time curves by the Double-step Chronopotentialmetry (DSCPO) method in the presence of various ATP concentrations from 25 aM to 400 nM in the Tris/HCl/MCD buffer compared with the control. Each sample run triplicates.

[0037] FIG. 22A depicts the calibration curve of the normalized action potential divided by the mean signal vs. ATP concentrations over 100 aM to 200 nM. FIG. 22B depicts the low end ATP's calibration curve from ATP 25 aM to 400 aM in Action potential of DER peak.

[0038] FIG. 22C depicts the semi-log plot of the absolute normalized resting potential vs. ATP concentrations under the same experimental conditions as FIG. 22A.

[0039] Table 1 shows a comparison of method performance for quantitation of ATP spiked in the milk samples using the voltage method

[0040] FIG. 23 depicts the Anti-inflammatory and the Pro-inflammatory counter map related to the ATP concentration at zero-bias, and the quantum conductance for the Healthy HSP60 Sensor 2.

[0041] FIG. 24 shows the semi-log plot curve of ATP concentration ranges effect on the cell Reversed Membrane Potential (RMP) (after subtracting the control). It was shown the trace is not depending upon the ATP concentrations between the range from 100 aM to 800 nM with n=24, eight concentration levels.

[0042] FIG. 25 depicts the semi-log plot curve of ATP concentration ranges effect on the ratio of action potential vs. resting membrane potential.

[0043] FIG. 26 Left Panel depicts the organic milk CV curves for current vs. applied potential in the presence of 60 nM ATP compared with the milk control (in black color) in 6 consecutive scans at 60 Hz. FIG. 26 Right Panel depicts the CV curves of with 60 nM ATP (in red color) in buffer media and curves of the buffer control.

[0044] FIG. 27 depicts the DET peaks' current vs. scan cycles: top Panel is for the DET.sub.red peak and the bottom Panel is for the DET.sub.ox peak.

[0045] FIG. 28A depicts the first scan cycle at 60 Hz in the presence of 60 nM ATP (final concentration) in human milk sample compared with the milk control sample. FIG. 28B depicts the second scan cycle at 60 Hz in the presence of 60 nM ATP (final concentration) in human milk sample compared with the control milk sample. FIG. 28C depicts the third scan cycle. FIG. 28D depicts the fourth scan cycle.

[0046] FIG. 29 depicts the alternative trends of the superconducting current at the zero-bias vs. scan cycles for the forward scan and backward scan compared with the human milk controls, respectively.

[0047] FIG. 30 depicts the overlapping curves of the control human milk sample in 6 consecutive scans vs. the milk sample with 60 nM ATP at 60 Hz.

EXAMPLE 1

Fabrication of the Membranes

[0048] Sensor 1 has an activated biomimetic MMP-2 membrane by a heating method at 80 C. for 5 minutes using the innate biomimetic MMP-2 membrane fabricated based on a published procedure [34]. Sensor 2 was also in a state of activation of biomimetic MMP-2 by a direct deposited method with compositions of TCD, PEG, PVP, bM--DMCD and embedded zinc chloride on gold chips with appropriate proportions at 37 C. for 96 hours. The morphology of the AU/SAM was characterized using an Atomic Force Microscope (AFM) (model Dimension Edge AFM, Bruker, MA).

EXAMPLE 2

The Friedel-Oscillation in the Superlattice Membranes

[0049] Friedel-oscillation is a phenomenon of long-range indirect interactions between electrons on a superlattice surface [21]. Evaluations of the Friedel-oscillation were conducted based on the AFM images. FIG. 1A revealed the strong Friedel-oscillation with a flame-like electric cloud surrounded on the zinc atoms which the cloud moves toward the same direction in the 1.0 m.sup.2 area. This is the evidence of the Cooper pair transmission waves at the Josephson junction. The image was for the biomimetic native MMP-2 membrane, i.e., the membrane comprised of triacetyl--cyclodextrin (TCD), polyethylene glycol diglycidyl ether (PEG), poly(4-vinyl pyridine) (PVP), bis-substituted imidazole dimethyl--cyclodextrin (bM--DMCD), cysteine and embedded zinc chloride in appropriate proportions. The native MMP-2 protein has two states: an innate state with the cysteine on and an activated state with the cysteine off. FIG. 1A depicts the 2D AFM membrane image in the native state of the biomimetic MMP-2 device. FIG. 1B depicts the cross-section analysis of the AFM membrane image. FIG. 1A was with the cysteine On in its innate state, and we observed the Cooper pair electrons moving toward the same direction. FIG. 2A depicts the 3D AFM image of the activated biomimetic MMP-2 Sensor 1 by the heating method. FIG. 2B depicts the enlarged 2D AFM image with the same z value range between 33.2 to 21.4 nm as the native state device in FIG. 1A for comparison. Sensor 1 has an activated biomimetic MMP-2 membrane by a heating method to kick out the cysteine group in the network, as evidence, we did not observe moving Cooper pairs in FIG. 2A, the labeled square has the same Z range as shown in FIG. 1A. The matrix of the superlattice was shown partially damaged shown in FIG. 2B.

[0050] FIG. 3A depicts the 2D image of the multiple-layer ring structure of the activated biomimetic MMP-2 Sensor 2 by the direct fabrication method in 0.7340.734 m.sup.2. The ring structure parameters labeled as 1 are listed. The inner ring diameter is about 161 nm, and the out ring diameter is 192 nm. Sensor 2 was directly fabricated using the same polymers and other compositions such as bM--DMCD/TCD/PEG/PVP/ZnCl.sub.2, except without cysteine. The Friedel-oscillation was observed in two locations in FIG. 3A. FIG. 3B depicts the cross-section analysis of the AFM membrane image. FIG. 3C depicts the 3D AFM image from the bird-view. FIG. 3D depicts the enlarged image in 0.90.9 m.sup.2 shown in the flat area in FIG. 3I. The Friedel-oscillation observed as the moving flames surrounded the zinc atoms, while the Cooper pairs moved toward the same direction and the superlattice matrix was very orderly arranged on the surface of the FIG. 3D. FIG. 3E depicts the alternative arrangement between the valley band and the flat band on the membrane which promotes the Cooper-pair electron cloud mobility in 1.61.6 m.sup.2. FIG. 3F depicts the enlarged 2D AFM image at high sensor mode in a top view of the biomimetic Heat Shock Protein (HSP) 60 chaperone structure having 7 subunits as shown on the top. The arrow indicates the mobile zinc ions. FIG. 3G depicts the top view in an amplitude mode of the AFM image of the large single porous biomimetic HSP60 structure. FIG. 3H depicts the side view of the 3D AFM image in high sensor mode for the single porous structured in 33.6 m.sup.2. FIG. 3I depicts the 3D AFM image of the tall cylinder structure in a size of 1.3-1.5 m diameter and 491 nm in height of the biomimetic HSP60 in 1010 m.sup.2.

EXAMPLE 3

Direct Electron Relay (DER) Model Based on a Cylinder Cage-Like Structured Polymer Network

[0051] FIG. 4A illustrates the Direct Electron-relay (DER) art model made by a cage structured polymer network between the zinc ions from the activated biomimetic MMP-2, by elimination of the cysteine group from the polymer mixture of dm--DMCD/TCD/PEG/PVP/ZnCl.sub.2before deposited on the gold chip, and the mm--DMCD (short names as MCD) in tris/HCl buffer. Zinc ions coordinated with three imidazole groups (two from the bm--DMCD and one from the MCD), and either with the COO.sup. of TCD, or OH.sup. group from the cyclodextrin, or from water. Furthermore all other hydrogen bounding, hydrophobic interaction and the - interaction between the function groups inside the cavity induced the DER force evidenced as the Cooper pair electron freely moving toward a same direction shown in FIG. 3D and the cylinder cage structure was shown from FIG. 3F to FIG. 3I.

[0052] FIG. 4B depicts the art model when ATP interacts with the cylinder polymer network molecules that form an enhanced DER. This effect has enabled ATP played a role to transform a memristive/meminductive sensor to a superconductor at a san rate60 Hz with the ATP concentration higher than 400 aM at zero-bias potential.

EXAMPLE 4

The JJ Characteristics

[0053] The hallmarks of the JJ characteristics are (1) at a DC voltage=0, a supercurrent

I.sub.s=I.sub.c sin() (1)

I.sub.c is critical current, is the phase difference between the waves of two superconductors, appears at the DC Josephson junction; (2) at a finite DC voltage, the phase of the supercurrent has changed is a function of time that caused oscillating at the AC Josephson Junction, which is proportional to 2 eV.sub.DC, i.e.,

/t=(2e/h)V.sub.DC (2) [28].

Here the Planck constant=h/2 (1.05510.sup.34 Js). Scan frequency affects i-V curves shown in FIG. 5A for Sensor 1 is different from that of Sensor 2 in FIG. 6, both figures were working in the Tris/mono-substituted imidazole dimethyl--cyclodextrin (mM--DMCD), in short, MCD control media over 1 Hz to 25 kHz. Sensor 1 demonstrated a memristive behavior with a hysteresis point at zero V and zero current at 60 Hz, but it had no superconductivity through all the curves, that indicates the heating procedure damaged the superlattice structure leading to a poor Cooper pair formation. In contrast, Sensor 2 demonstrated a perfect memristive behaves at 60 Hz and also showed the superconductivity at zero-bias potential over 5 kHz to 25 kHz as shown in FIG. 6. This fact showed as long as having the Cooper pair formation, the superconductivity can be expected. The sine waves oscillated in the high scan frequency are observed.

EXAMPLE 5

Superconductivity with Super-Positioning

[0054] Because Sensor 1 lacks of Friedel-oscillation due to the heating process for eliminating the cysteine group, without any superconductivity regardless with or without ATP in the Tris media as shown in FIGS. 5A (without ATP) and 5B (with ATP) over a wide rage of scan rate. Scan frequency effects on the Shapiro step voltage in the sine waves of Sensor 2 over 5 kHz to 25 kHz, under external magnetic field=0 condition, was observed as shown in the i-V curves in FIG. 6, FIG. 7 and FIG. 8 for without and with ATP under 60 and 10 kHz scan rate, respectively. The superlattice quantum bit's superposition states were seen between state 1 at v=0, i>0; 1 state at v=0, i<0 and state 0 at v=0, i=0 at zero bias in FIG. 7 and FIG. 8.

EXAMPLE 7

Sensing ATP by Sensor 2 Using the CV Method and ATP Promotes Super Conductivity

[0055] FIG. 5B depicts the Direct Electron Transfer (DET.sub.red) peak current increased exponentially for Sensor 1 as the ATP concentration increased from 40 fM to 60 nM compared with the control having 66.5, 146, 3048.7 and 4664-fold increase in four levels, respectively at 60 Hz scan rate. FIG. 6 shows scan rate impacts on Sensor 2's i-V curves over scan rate from 1 Hz to 25 kHz in the Tris/HCl/MCD control media.

[0056] FIG. 7 shows Sensor 2's sine or cosine wave peak superconducting current intensity increased or decreased exponentially for forwarding scan and backward scan, respectively, over ATP concentrations from Panl B, 400 aM; Panel C: ATP 400 fM; Panel D: ATP 200 pM; Panel E: ATP 200 nM; Panel F: ATP 2 M. at zero-bias at the same scan rate 60 Hz compared with the controls in FIG. 6. We observed that a 25 aM ATP concentration is not enough to turn the memristive to superconductivity shown in Panel A. The superposition characteristics were shown also as an example labeled in Panel F. The exponential increase of the superconducting current vs. ATP concentrations over 400 aM to 2 M for the forward scan against the backward scan, which is in an exponential decay, were shown in FIG. 9. At high scan rate of 10 kHz, both the forward and the backward scan's supercurrent at zero-bias increased non-linearly from 200 fM till near 1 M, both current are dropped drastically as shown in FIG. 10. FIG. 10 depicts the supercurrent vs. ATP concentration curves of the DET.sub.red and DET.sub.ox peaks at the zero-bias over ATP concentration ranges from 200 fM to 200 M. Data obtained according the figures from FIGS. 8A to 8I.

EXAMPLE 9

ATP Induces Phase Change in Detail Presented in Sensor 2

[0057] Above Section we discovered ATP promoted superconductivity at an appropriate concentration and scan rate in the Tris buffer, now this Section we explain the invention of the technology on Sensor 2 discovered the ATP's another role which is for inducing a phase change as shown in FIG. 11 for 10 consecutive scans at 60 Hz. The curves from Panel A are with an ATP concentration 400 fM; Panel B with ATP 200 pM; Panel C with ATP 200 nM, and Panel D with ATP 2.0 M, respectively. The phases of the i-V curves were constantly changing at a fixed scan rate, but the ATP concentration were increased.

[0058] FIG. 12A depicts the i-V curves of a 25 aM low concentration ATP in consecutive 5 scan cycles at a scan rate 60 Hz compared with the control of Sensor 2. There was no phase change occur, and the hysteresis curves are seen through the 5 consecutive scans. FIG. 12B depicts when concentration increased to 400 fM, in the consecutive 9 scan cycles of the same scan rate, we observed the cross-point moved away from origin, and the i-V curves having degree of superconductivity at zero-bias, and companied with a phase change occurred compared with the control. FIG. 12C also depicts the similar trend when ATP concentration increased to 200 nM ATP concentrations, Sensor 2 shows the phase changes and superconducting current.

EXAMPLE 10

The 3D Quantum Conducting Map in the Multiple-Variable Study

[0059] Quantum computing is computing using quantum-mechanical phenomena, such as superposition and entanglement [28]. Superconducting flux qubit has two states that can be effectively separated from the other states is the basic building block of quantum computers. Current DC or RF superconducting SQUID were made in advance for a faster switch time; however, hundreds of MHz electromagnetic field applied onto a tank circuit coupled to the SQUID is needed for the system to work under cryogenic conditions [29-31]. The RF-SQUID consists of a superconducting ring of inductance L interrupted by a JJ, the potential energy of the SQUID and the Hamiltonian equations are given by

U()=(.sub.e).sup.2/2LE.sub.J cos(2/.sub.0) (3) [28]

H=Q.sup.2/2C+(.sub.e).sup.2/2LE.sub.J cos(2/.sub.0) (4) [28]

.sub.e is the applied magnetic flux penetrating the SQUID ring, is the total magnetic flux threading the SQUID ring, L is the inductance, E.sub.J represents the Josephson coupling energy, and .sub.0 is the superconducting magnetic flux quantum, Q is the charge on junction's shunt capacitance satisfying [, Q]=ih/2, while h is the Planck constant.

[0060] Stern's group reported the observation of Majorana bound states of Josephson vortices in topological superconductors, and the equations of three types of energy contributions to the Josephson vortices in a long circular junction in a Sine-Gordon system was published [32]. The Josephson junction energy was from the Cooper pair, the magnetic energy was from the inductivity of the circular vortex, and the charge energy was from the SIS quantum capacitor-like device [32-33]. Our group reported using a 3D dynamic map method, to elucidate the multiple-variables between the component energies contributing to the superconductivity of the vortex array system at room temperature without external magnetic field applied. Our experimental data were shown on the i-V curves and the AFM structure of the superlattice array. The modified Sine-Gordon system energy for our d-wave vortex array is:

E.sup.n.sub.JJA=(1/2)C.sup.1.sub.i(Qen.sub.1 . . . i).sup.2 (5)

E.sup.n.sub.L=(1/2).sub.0N.sup.2.sub.n=1..i.Math.A.Math.L.sup.1.sub.n=1..i.Math.I.sup.2.sub.n=1..i (6)

where E.sup.n.sub.jjA is the charge energy of Josephson Junction arrays at n=1..i; Q is the charge, C is the total capacitance at n=1..i, en is the n quantum particles at 1..i data point with an energy periodic in h/e for Josephson effect for d-wave [34]; E.sup.n.sub.L is the Inductive energy induced by the circular toroidal array. N is the turning number around the toroidal porous at n=1..i, A is the cross-sectional area of the porous, L is the length of the wending, .sub.0 is the magnetic permeability constant in free space; I is current. The toroidal arrays are in series connected. Recent publication regarding our FFTJJ multiple-variable study results in 3D dynamic maps was presented in the literature [34]. In this invention, the multiple variables, such as the ATP concentration, the applied potential affect on the quantum conductance were studied through the 3D mapping method without decomposed the superconducting energy into several components.

[0061] FIG. 13 depicts the 3D dynamic map of the relationships over 5 level ATP concentrations from 0.2 pM to 2.0 M over the potential range between 40 mV to +40 mV to illustrate the relationship among ATP concentrations, zero-bias potential and the differential quantum conductance using 10 kHz scan rate forwarding scan data. From the map, the quantum conductance values are correlating with the ATP concentrations at zero-bias, except at higher concentration near 1.0 M, it was dropped.

EXAMPLE 11

Quantitation of ATP in Biological Specimens

The Chronoamperometric Method (CA) Measured by Sensor 1.

[0062] FIG. 14 depicts Sensor 1's current vs. time over ATP concentrations over 100 aM to 400 nM compared with the control in pH 7.8 Tris/HCl/MCD solution. FIG. 15 depicts the lower end concentration curves. Inserts are enlarged view for lower end concentration compared with controls. Inserts are the enlarged view of the curves at the lower concentration compared with the control. FIG. 16 in Panel A depicts the regression calibration curve of current density vs. ATP concentrations in a logarithm scale for the x-axe and the y-axe (9 levels, n=27 over 100 aM to 400 nM) with the regression equation (y log scale)Y=1.9+0.57*(log scale), r=0.996, S.sub.Y/=0.16, p<0.0001. In inversion of the equation, 0.57 is the power of the , and 1.9 is the intercept from the log-log plot. Hence the inversed equation is F(x)=79x.sup.0.57. FIG. 16 Panel B depicts Sensor 1's calibration curve over a linear range 400 fM to 170 nM (7 levels, n=21) with the regression equation y=65.4+13.4x, r=0.997, Sy/x=65, p<0.0001. The Detection of Limits (DOL) of 0.56 fM over the analytical range 100 aM-400 nM with a relative Pooled Standard Deviation (RPSD) value 0.9% (n=30).

EXAMPLE 12

The Open Circuit Potential Method (OPO)

[0063] Sensor 2's strong superconductivity has enabled the device to direct real-time monitor energy change under open circuit potential, under a reagent-free, antibody-free condition. FIG. 17 depicts the voltage curves exponentially increase as the ATP concentration increase compared with the control in the buffer media. FIG. 18 depicts the non-linear calibration curve of voltage vs. concentrations over the range of 25 aM to 400 pM. FIG. 19 shows a plot for high-end ATP concentration with spontaneous voltage curves as the time (600 s) over 0.8 nM (a) to 2 M (d). FIG. 20 shows the calibration curve over the higher ATP concentration range from 0.8 nM to 2 M.

EXAMPLE 13

The Double Step Chronopotentialmetry Method (DSCPO) by Sensor 2

[0064] The ATP concentrations also can be detected in several seconds using the DSCPO method and setting the fixed current as 10 nA, and each step 4 s with a data rate 1 kHz. FIG. 21 depicts Sensor 2's voltage vs. time (each step 4 s) curves by the Double-step Chronopotentialmetry (DSCPO) method in the presence of various ATP concentrations from 25 aM to 400 nM in the Tris/HCl/MCD buffer compared with the control. Each sample run triplicates. The curves show a positive correlation between the voltage intensity and the ATP concentrations in 7 levels compared with the lowest voltage from the control. FIG. 22A depicts the calibration curve of the normalized action potential divided by the mean signal vs. ATP concentrations over 100 aM to 200 nM. The relative pooled standard deviation (RPSD) is 0.24%. The linear semi-log plot gave an equation of yscale(Y)=A+B*xscale(X) with A=0.37 and B=0.06, r=0.992, n=18, S.sub.y/logx=0.027, p<0.0001. The DOL was found from this plot is 46 aM. FIG. 22B depicts the low end ATP's calibration curve from ATP 25 aM to 400 aM in the Action potential results of the DER peaks after subtracted the background signals with a RPSD error 1.3% with the signal increase rate of 0.016V/aM. The DOL result is 2 aM.

EXAMPLE 14

Accuracy and Imprecision

[0065] The USDA certified organic milk for infants was compared with human milk (Lee Biosolutions, MO) without prior sample preparation. Human milk was collected from normal subjects who breastfeed 1 month-old newborn, each sample run triplicates.

[0066] Methods validations were studied through the recovery experiments using fresh human milk and USDA certified organic milk for infants as controls compared with spiked 100 aM and 60 nM ATP and with or without low and high-level LPS challenges by the OPO method against each one's standards and the controls. The accuracy recoveries were 940.14% and 910.16% at 100 aM and 60 nM ATP for the human milk samples compared with organic milk samples of 850.2% and 79%0.2%, respectively using the OPO method in traced back to the Tris standard control. The human mike control and the organic milk control samples have an agreement related to the Tris/HCl/MCD buffer sample controls (each type samples run triplicates) are 94.00.14% and 95.50.2%, respectively. The 5% difference is believed due to the artificial chaperone cage effect on the proteins of the milk, which is to lead the landscape free energy down to the lowest for a right folding [29-30]. After corrected this effect, human milk's recovery in the two levels' ATP challenges is 980.14% and 950.16%; the organic milk recoveries are 90.50.2% and 84.50.2%, respectively. The data implies the chaperoning effect has more impact on organic milk than that of the human milk. In the two levels' LPS challenges (100 ag/mL, 60 ng/mL), the recovery results are 960.16% and 1050.14% vs. 105.50.28% and 950.19% for human milk and organic milk, respectively.

[0067] Point accuracy and imprecision was studied through the recovery experiments using spiked human milk and the USDA certified organic milk samples against the control samples with 2 levels of ATP concentrations at 100 aM and 60 nM, respectively. We compared the measured results with the calibration curve after subtraction of the voltage values from control samples using sensor 2 as shown in Table 1. We also studied the LPS effects on the recovery at 10 fg/mL and 90 fg/mL, respectively under a fixed ATP concentration of 60 nM. The results shown the recoveries using human milk and organic milk samples with the voltage method are higher than 96% with an imprecision error less than or equals to 2% at the 100 aM and 60 nM levels ATP compared with the controls, respectively without LPS challenge. Using two levels of LPS challenges with the fixed ATP 60 nM, the recoveries are 1030.8%, 1030.7% for human milk samples compared with the spiked controls at the same level in the buffer; using organic milk samples, the recoveries are 971%, 18.80.3% at 10 fg/mL LPS and 90 fg/mL LPS, respectively traced back to the spiked controls at the same level in the buffer. These results showed organic cow milk samples are vulnerable to the LPS attack in higher-level 90 fg/mL, which caused an unacceptable result in recovery, but the human milk samples demonstrated immunological advantage with 100% recovery with two levels LPS challenges even under 60 nM ATP concentration.

[0068] The CA method was also used to access the accuracy and imprecision. Human milk control samples against the standard control samples in the Tris/HCl/MCD buffer found no specimen interference having 1016% traceable to the standards; In the presence of 30 fM ATP spiked in the human milk samples, i.e., the final ATP concentration is 30 fM in the sample, the recovery results are 100.07%; However, when 60 nM ATP presents in the human milk samples, due to the immunological property, human milk samples eliminated all the ATP's effect, led to no signals were measureable; In the presence of 30 fM ATP, under a 10 fg/mL LPS challenge of the human milk samples, the recovery results are 10010%; Under 30 fM ATP, using a 90 fg/mL LPS challenge, the human milk samples produce 3-fold high signal intensity,

[0069] For a comparison, the organic milk control samples were found having a 21% of HSP 60-like chaperone interference for trace back to the standard control samples with 792.6%; in the Tris/HCl/MCD buffer; After corrected the interference, in the presence of 30 fM ATP spiked in the organic milk samples, the recovery results are 100.04.4%; when 60 nM ATP presents in the organic milk samples, the recovery results are 102.30.02%; In the presence of 30 fM ATP, under a 10 fg/mL LPS challenge of the organic samples, the recovery results are 490.2%; Using a 90 fg/mL LPS challenge to the organic milk samples, the recovery results are 1303.6%.

EXAMPLE 15

Applications for Defining of the Transformational Immunomodulant Between the Anti-inflammatory and the Pro-inflammatory Status

[0070] We primarily suggest the turning point of the ATP concentration from anti-inflammatory to pro-inflammatory for a healthy Biomimetic MMP-2/HSP60 sensor 2 in the extracellular environment is higher than 800 nM. FIG. 23 further shows a contour map relationship between the ATP concentration (as the y-axis), and the applied potential (as the x-axis) and the quantum conductance (as Z-axis). It was observed that the range between the highest quantum conductance values at zero-bias is associated with the ATP concentration between 200 fM to 800 nM, so we define this range having the Physiological High-Frequency Oscillation (Phy-HFO) as the Anti-inflammatory range; when concentration higher than 800 nM, the quantum conductance values are reduced, and this range was defined as the Pro-inflammatory in the extracellular ATP concentration range at 10 kHz. Because Sensor 1 can be viewed as a Mutated or Stressful Biomimetic MMP-2/HSP60 model as far as the capability to promoting the Cooper-pair electrons' concerns, was greatly diminished as shown in the AFM image FIG. 2B, hence it was shown Sensor 1 neither have superconducting peaks in the presence of ATP in the buffer media in 60 Hz and 10 kHz scan rate, respectively.

EXAMPLE 16

Applications in Defining of ATP Concentration Ranges Effecting on Cell Reversible Membrane Potential (RMP) and Its Ratio Between Action Potential and Resting Potential

[0071] It is a well-recognized phenomenon that cancer cells have abnormal cell membrane potential [35-38]. Biologists measure cell membrane action and resting potentials with burdensome instrumentation and time-consuming procedures. A recent report shows breast cancer cell division caused a membrane potential increase [38] due to variations in ion channel expression. Because the normal cell membrane action potential is 58 mV, and 70 mV is for the resting potential [39], the small signals are very easily buried in the background noises [40] that can cause problems to pediatric neurologist and intensive care unit doctors who need strong signals to monitor and diagnose the neonatal neurological diseases [40]. The consequences of human cancers, trauma brain injury (TBI) and other diseases are not be able to maintain mitochondrial cell's reversible membrane potential (RMP) and unable to maintain the normal membrane's potential ratio between the action potential and the resting potentials [35-44]. Our group first used the biological marker of the action/resting potential ratio to monitor the treatment of triple-negative breast cancer and the brain cancer prognosis in a 3D heat release map [41-44]. There is very few, if any, uses the ratio of action/resting potential as a biomarker to monitor and define the ATP concentration ranges, that transforms from anti-inflammation to pro-inflammation in the presence of bacterial toxins under a well-controlled system without any sample processing, no labeling and no tracers were used. FIG. 24 shows the cell RMP voltage (after subtracting the control) is not depending upon the ATP concentrations between the range from 100 aM to 800 nM with a power of 0.013, that means the cell voltage increase rate is only 1.3% of the ATP concentration increase rate, hence this range is the safe zone confirmed by FIG. 10 using the 3D map method based on the CV data. However, we found concentrations lower than 100 aM and higher than 800 nM the cell RMP can not keep constant, either lower than the normal average cell voltage, or 10, 20-fold higher than the normal average cell voltage, therefore, we define this range as the pro-inflammatory toxin range, for contrast, the safe zone range was defined as the anti-inflammatory toxin range.

[0072] FIG. 25 further shows the extracellular ATP concentration range effects on the ratio of the cell action potential vs. resting potential. The results showed the concentration lower than 100 aM or higher than 400 nM will lead to a ratio of action vs. resting potential either significantly lower or significantly higher than the normal ratio range, which is between 0.7 to around 1.0 [45-50]. Our prior works revealed the living cancer cells can lead to an abnormal ratio up to 3, 10 to 100-fold higher than this range according to the nature of cancer and the stage of the cancers are in. Even FIG. 24 reveals the total cell voltage at 800 nM is in the safe zone is respected to the energy concerns, but clinically, the ratio value in FIG. 25 further revealed the 800 nM ATP concentration led to a 10-fold higher than the normal ratio range, hence in FIG. 25 we excluded the 800 nM points. The ratio vs. concentration curve has a power 0.08 that means the ratio increase rate is 8% of the concentration rate increase having a CV value4.5% error in the normal range was demonstrated.

EXAMPLE 17

Applications in Assessing Human Milk Immunological Advantage in Preventing Extracellular ATP Hydrolyzation

[0073] Assessing human milk immunological advantage in preventing extracellular ATP hydrolyzation is important. Our study was conducted through the CV method using the Sensor 1 because we knew Sensor 1 lacks Copper-pair electrons, and we used the human milk samples compared with the certified organic milk samples for infants under the same experimental conditions. FIG. 26, Left Panel shows the extracellular hydrolysis DETox curves (as also called the memristive peak) happened in the presence of spiked 60 nM ATP (final concentration), which caused a 9-fold increase of the peak current at 700 mV compared with the organic milk negative control. There is an unknown peak observed in the organic control milk sample located at 20 mV, and the peak was the 2.8-fold increase of the amplitude when ATP presences. In contrast, FIG. 26 in the Right Panel shows the buffer control sample of the CV curve has no such unknown peak at 20 mV. There is a current increase for the DET.sub.ox peak at 700 mV for more than 173-fold in the presence of 60 nM ATP compared with the control, and the DET.sub.red peak intensity also increased 150-fold in the presence of ATP compared with the control buffer sample. The DET.sub.ox has a first-order ATP hydrolysis rate of 5.9210.sup.3/s by plotting the peak currents vs. scan cycles (each cycle is 53.33 s) as shown in FIG. 27. The top Panel curve is for the DET.sub.red peak current vs. scan cycles; the bottom Panel curve is for the DET.sub.ox peak current vs. scan cycles.

[0074] Human milk samples communicated with the mutated HSP60 membrane on the same Sensor 1 having a different manner compared with the organic cow milk samples. FIG. 28A, FIG. 28B, FIG. 28C and FIG. 28D depict the human milk samples under the impact of 60 nM ATP concentration in 4 scan cycles (2 more cycles curves did not show) compared with the human milk controls using Sensor 1 at 60 Hz. The nodes, the super-positioning and the phase change at the zero-bias were observed, and there was no ATP hydrolysis signature peak observed, and there was no unknown DET reduction peak noticed. FIG. 29 shows an alternative up and down peak superconducting current vs. scan cycles for the forward and backward scan, respectively. The human milk samples have eyes that can see the danger and purposely avoiding communicate with the ATP molecules because in the human milk contains living microbiota, which the HSP60 and ZnT chaperonin proteins in the extracellular plays a role of the guardian's protection. FIG. 30 shows the overlapping curves of the control human milk sample in 6 consecutive scans vs. the milk sample with 60 nM ATP. The peak magnitude kept the same, but the phase change is constantly happening for with or without ATP, that indicates the human milk promoting an orderly electromagnetic energy stored in the cell for enhancing the brain development and memory caused by the meminductivity through the Josephson junctions, in which is advantages compared with the chaos electromagnetic energy acquired from Alzheimer's -amyloidal accumulation [51-54].

EXAMPLE 18

Experimental

[0075] Sensor 1 has an activated biomimetic MMP-2 membrane by a heating method at 80 C. for 5 minutes using the innate biomimetic MMP-2 membrane fabricated based on a published procedure [34]. Sensor 2 was also in a state of activation of biomimetic MMP-2 by a direct deposited method with compositions of TCD, PEG, PVP, bM--DMCD and embedded zinc chloride on gold chips with appropriate proportions at 37 C. for 96 hours. The USDA certified organic milk for infants was compared with human milk (Lee Biosolutions, MO) without prior sample preparation. Human milk was collected from normal subjects who breastfeed 1-month-old newborns, each sample run triplicates.

[0076] The morphology of the AU/SAM was characterized using an Atomic Force Microscope (AFM) (model Dimension Edge AFM, Bruker, MA). Data collected in TappingMode using silicon probes with a 5-10 nm tip radius and 300 kHz resonance frequency (Probe mode TESPA-V2, Bruker, MA).

EXAMPLE 19

Conclusions and Discussions

[0077] A multiple functioning superconductive device was invented based on Toroidal Josephson Junction (FFTJJ) array with 3D-cage structure self-assembled organo-metallic superlattice membrane. The device not only mimics the structure and function of an activated Matrix Metalloproteinase-2 (MMP-2) protein, but also mimics the cylinder structure of the Heat Shock Protein (HSP60) protein, that works at room temperature under a normal atmosphere, and without external electromagnetic power applied. The device enabled direct rapid real-time monitoring atto-molarity concentration ATP in biological specimens and was able to define the anti-inflammatory and pro-inflammatory status revealed a transitional range of ATP concentration under antibody-free, tracer-free and label-free conditions.

REFERENCES

[0078] 1. https://www.fda.gov/.../MedicalDevices/DeviceRegulationandGuidance/.../ucm073386 [0079] 2. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/cfrsearch.cfm?fr=1000.55 [0080] 3. https://www.cdc.gov/infectioncontrol/guidelines/.../healthcare-equipment.html [0081] 4. www.who.int/medical_devices/publications/en/MD_Regulations.pdf [0082] 5. https://www.epa.gov/dwstandardsregulations [0083] 6. G. S. Whiteley, T. O. Glasbey, P. P. Fahey, A suggested sampling algorithm for use with ATP testing in cleanliness measurement, Infection, Disease and Health, 21, 169-175, 2016. [0084] 7. L. Roady, Abundant research in support of ATP cleaning verification's applicability in healthcare, Infect Control Hosp Epidemiol 36, 1367, 2015. [0085] 8. O. K. Vang, ATP measurements for monitoring microbial drinking water quality, Ph.D. Dissertation, Technical University of Denmark, October 2013. [0086] 9. C. V. Sciortino, R. A. Giles, validation and comparison of three adenosine triphosphate luminometers for monitoring hospital surface sanitization: a Rosetta stone for adenosine triphosphate testing, Am J. Infect Control 40, e233-239, 2013. [0087] 10. H Singh, D. R Duerksen, G Schultz et al., Impact of cleaning monitoring combined with channel purge storage on the elimination of Escherichia coli and environmental bacteria from duodenoscopes, Gastrointestinal 88(2), 292-302, 2018. [0088] 11. G. S. Whiteley, M. Nolan, Mark, and P. P. Fahey, Improving the Reliability of Adenosine Triphosphate (ATP) Testing in Surveillance of Food Premises: A Pilot Study, Journal of Environmental Health, 81(1), E1-E8, 2018. [0089] 12. B-C Yin, Y-M Guan, and B-C Ye, An ultrasensitive electrochemical DNA sensor based on the ssDNA-assisted cascade of the hybridization reaction, Chem Commun 48, 4208-4210, 2012. [0090] 13. X Zhang, Y Wang, X Zhou, Ligation-Based qPCR-Amplification Assay for Radiolabel-Free Detection of ATP and NAD with High Selectivity and Sensitivity, Anal. Chem. 91(2), 1665-1670, 2018. [0091] 14. N. Nante, E. Ceriale, G. Messina, D. Lenzi, P. Manzi, Effectiveness of ATP bioluminescence to assess hospital cleaning: a review, J. Prev. Med. Hyg., 58, E177-E183, 2017. [0092] 15. https://sbir.nasa.gov/soliscitations [0093] 16. E. T. Chen, J. T. Thornton, P. T. Kissinger, S-H. Duh, Nanostructure protein toroidal array devices promoted room temperature superconductivity and direct sensing of collagen-1, Sensors and Transducers 228(12), 48-62, 2018. [0094] 17. E. T. Chen, J. T. Thornton, P. T. Kissinger, and S-H. Duh, Nanobiomimetic structured superconductive/memristive organo-metal devices at room temperature serve as amperometric sensors for sub fg/mL collagen-1 detection, TechConnect Briefs in Biotech, Biomaterials and Biomedical, 107-110, 2018. [0095] 18. S. Peotta, M. DiVentra, Superconducting memristors, arXiv:1311.2975v2, 2014. [0096] 19. J. Salmileto, F. Deppe, M. DiVentra, Quantum memristors with superconducting circuits, Scientific Reports, 7:42044, 2017. [0097] 20. C. Guarcello, P. Solinas, M. DiVentra and F. Giazotto, Solitonic Josephson-based meminductive systems, arXiv:1610.06807v1, 2016. [0098] 21. M. Ternes, M. Pivetta, F. Patthey, and W-D Schneider, Creation, electronic properties, disorder, and melting of two-dimensional surface-state-mediated adatom, Progress in Surface Science 85, 1-27, 2010. [0099] 22 X. Wang, Y-S Li, Y. Qian, et al., Extracellular ATP, as energy and phosphorylating molecule, induces different types of drug resistance in cancer cells through ATP internalization and intracellular ATP level increase, Oncotarget 2017, 8(50), pp 87860-87877. [0100] 23. J. Gu, J. S. Wiley, Rapid ATP-induced release of matrix metalloproteinase 9 by the P2X7 receptor, Blood 2006, 107, pp 4946-4963. [0101] 24. A. Manica, A. M. Da Silva, A. M. Cardoso, High levels of extracellular ATP lead to the chronic inflammatory response in melanoma patients, J. Cellular Biochemistry, 2018,119(5), pp 3980-3988. [0102] 25. A. P. S. Bertoni, R. P. De Campos, M. Tsao et al., Extracellular ATP is differentially metabolized on papillary thyroid carcinoma cells surface in comparison to normal cells, Cancer Microenviron 2018, 11(1), pp 61-70. [0103] 26. T. Zininga, L. Ramatsui, and A. Shonhai, Heat shock proteins as immunomodulators, Molecules 2018, 23, pp 2846, doi:10.3390/molecules23112846. [0104] 27. P. G. Jobin, G. S. Butler, and C. M. Overall, New intracellular activities of matrix metalloproteinase shine in the moonlight, BBA-Molecular Cell Research, 2017, 1864, pp 2043-2055. [0105] 28. Editors E. Wolf, G. Arnold, M. Gurvitch and J. Zasadzinski, Josephson Junctions, History, Devices, and Applications, Pan Stanford Publishing Pte, Ltd, 2017. [0106] 29. D. Drung and J. Beyer, Applications in superconducting quantum interference devices SQUIDs (Chapter 8, pp 245-316), Editors E. Wolf, G. Arnold, M. Gurvitch and J. Zasadzinski, Preface, Josephson Junctions, History, Devices, and Applications, Pan Stanford Publishing Pte, Ltd, 2017. [0107] 30. J. Clarke and A. I. Braginski, SQUID Handbook volume 1-2, Wiley-VCH, ISBN:3527-40229-2. [0108] 31.B. Back, W. H., Rippard, M. R. Pufall, et. al., Spin-transfer torque switch in nanopillar superconducting-magnetic hybrid Josephson Junction, Physical Review Applied 3, 011001, 2015. [0109] 32.E. Grosfeld, A. Stern, Observing Majorana bound states of Josephson vortices in topological superconductors, PNAS, Vol. 108, Issue 29, 2011, pp. 11810-11814. [0110] 33. F. Loder, A. P. Kampf, T. Kopp, et al., Magnetic flux periodicity of h/e in superconducting loops, Nature Physics, Vol. 4, 2008, pp. 112-115. [0111] 34. E. T. Chen, J. T. Thornton, P. T. Kissinger and S-H. Duh, Utilization of the Flexible Fractional Josephson Toroidal Arrays for Sensing, Memory Storage and Quantum Computing, Sensors and Transducers, 228(12), 30-47, 2018. [0112] 35 B. Weiss, G. Ganepola, H. Freeman, Y. Hsu and M. Faupel, Breast Disease, 1994, 7(2), pp 91. [0113] 36. S. V. Sree, E. Ng, G. Kaw, R. Acharya-U, and B. Chong, J. of Medical Systems, 2011, 35(1). pp79. [0114] 37. A. M. Hassan and M. Ei-Shenawee, Review of electromagnetic techniques for breast cancer detection, IEEE Transactions in magnetic, online publisher, 2011. [0115] 38. A. M. Hassan and M. Ei-Shenawee, The Diffusion-Drift Algorithm for Modeling the Biopotential Signals of Breast Tumors, #TTT-Cancer Detection and Diagnostics Technologies for Global Health Symposium at National Cancer Institute, Aug. 22-23, 2011. [0116] 39. L. Mitchell, N. A. Campbell, J. B. Reece and M. R. Taylor, Biology, 8.sup.th edition, 2007. [0117] 40. S. L. Bonifacio, H. C. Glass, D. M. Ferriero and S. Peloquin, Nature Reviews Neurology 2011, 7, pp 485. [0118] 41. E. T. Chen1, Y. Shen J. Thornton, C. Ngatchou1, S-H. Duh, and P. T. Kissinger, A Nanopore Biomimetic device quantitatively detects early-stage cancer cells; a Contour Map Multiple Variable Correlation Method assesses the heat of cancer cells released, Techconnect Briefs, Nanotech 2012, pp 198-201. [0119] 42. E. T Chen, J. Thornton, C. Ngatchou, S-H Duh and P. Kissinger, Nanostructured Biomimetic Memristor Sensors Used For Therapeutic Monitoring of The Brain Cancer, NSTi-Nanotech, 2014, 2, 200-203. [0120] 43. E. T. Chen, Book chapter of Nanobiomimetic sensors and technology, Dekker Encyclopedia of Nanoscience and Nanotechnology Mar. 8, 2013. [0121] 44. E. Chen, U.S. Pat. No. 9,534,999, Jan. 3, 2017, Nanostructured Biomimetic device for detecting a cancer cell or cancer cells. [0122] 45. J. Salmileto, F. Deppe, M. DiVentra, Quantum memristors with superconducting circuits, Scientific Reports, 7:42044, 2017. [0123] 46. C. Guarcello, P. Solinas, M. DiVentra, and F. Giazotto, Solitonic Josephson-based meminductive systems, arXiv:1610.06807v1, 2016. [0124] 47. E. T. Chen, J. T. Thornton, S-H. Duh and P. T. Kissinger, Nanobiomimetic structured organo-metallic devices direct rapid real-time monitor atto molarity ATP in biological specimens, Techconnect Briefs in Diagnostics 2019, pp 423-426. [0125] 48. M. Ternes, M. Pivetta, F. Patthey, and W-D Schneider, Creation, electronic properties, disorder, and melting of two-dimensional surface-state-mediated adatom, Progress in Surface Science 2010, 85, pp 1-27. [0126] 49. M. L. Bender and M. Komiyama, Cyclodextrin Chemistry, Springer-Verlag, Berlin, 1978. [0127] 50. J. Szejtli, Cyclodextrin, and Their Inclusion Complexes, Akademiai Kiado, Budapest, 1982. [0128] 51 E. T. Chen, J. Thornton and Jr. C. Mulchi, Nanobiomimetic Memcapacitor Memory Devices Identify Circadian Rhythm Dysfunction and Predict Early Signs of Epilepsy Using Reentrant Energy-Sensory Images, Advanced Manufacturing, Electronics, and Microsystems: TechConnect Briefs, 2015, pp 200-203. [0129] 52. J. Thornton, Jr. C. Mulchi, P. T. Kissinger and E. T. Chen, Acetylcholine Repairs the Amyloid-beta Damage on Brain Circuitry and Memory Loss From a Mutated Biomimetic Acetylcholinesterase Neuronal Memcapacitor During Slow-Wave Sleeping, Advanced Manufacturing, Electronics, and Microsystems: TechConnect Briefs, 2015, pp 226-229. [0130] 53. E. T. Chen, J. Thornton, Jr. C. Mulchi Early Forming a Hummingbird-like Hovering Neural Network Circuitry Pattern with Reentrant Spatiotemporal Energy-Sensory Orientation Privileged to Avoid Epilepsy Based on a Biomimetic Acetylcholinesterase Memcapacitor Prosthesis, Sensors and Transducers Journal, 2015, 191(8), pp 84-99. [0131] 54. J. Thornton, Jr. C. Mulchi, P. T. Kissinger and E. T. Chen, In Vitro Restoration of an Amyloid-Beta Altered Network Circuitry in a Mutated Biomimetic Acetylcholinesterase Memristor/Memcapacitor Neural Prosthesis, Sensors and Transducers Journal, 2015, 191(8), pp 100-113.