Cooperative regulation and control optimization method of multi-nano-channel ion permeation energy conversion device

Abstract

The invention discloses a collaborative regulation and control optimization method for a multi-nano-channel ion permeation energy conversion device. The method comprises the following steps: determining structural parameters of the ion permeation energy conversion device; constructing a geometric model comprising a high-concentration liquid storage tank, a low-concentration liquid storage tank and a plurality of nano-channels connected between the high-concentration liquid storage tank and the low-concentration liquid storage tank in parallel; calculating the surface charge density sigma of the inner surface and the outer surface of the nano-channel; calculating the conductance Gtotal and the diffusion potential Ediff of the ion permeation energy conversion device; calculating the power density Pd of the device under different numbers of the nano channels to obtain a curve of the power density Pd changing along with the number N of the nano channels; determining the corresponding NlsrMP when the power density Pd reaches the maximum value; in a parameter area corresponding to the NlsrMP value, a curve that the power density changes along with the number N of the Pd nano channels is obtained, and the maximum power density Pd and MP of the ion permeation energy conversion device and the corresponding optimal structure parameters are determined according to the curve.

Description

Technical Field

[0001] This disclosure belongs to the field of renewable energy utilization technology, specifically relating to the structural design and performance optimization methods of ion permeation energy conversion devices, and is particularly applicable to ion permeation energy conversion devices based on multiple nanochannels in parallel. Background Technology

[0002] Ion permeation energy conversion technology, as a core approach to directly convert the vast salinity gradient energy (global river estuary permeation energy reserves reach 2TW) into electricity, is a key direction for achieving efficient utilization of renewable energy. To meet the power generation demands of practical applications, the industry currently widely adopts a multi-nanochannel parallel connection technology to improve ion permeability and overall power generation. However, this approach faces a core technical contradiction: the number and length of nanochannels have an inverse regulatory effect on ion selectivity and permeability. Therefore, controlling the number and length of nanochannels becomes a core requirement for improving the device's output performance. The current mainstream design method for nanochannel structure control is based on a single-channel model, but it has significant technical limitations and is difficult to adapt to the optimization requirements of multi-channel parallel connections.

[0003] Meanwhile, accurate characterization of surface charge density is the core functional basis for the ion selectivity of nanochannels, and its accuracy directly determines the effectiveness of nanochannel number-length regulation. It has been confirmed that ion-specific adsorption directly regulates channel surface charge density and weakens the electric double-layer effect. However, traditional power generation simulations neglect the specific adsorption of cations to channel surface functional groups and their shielding effect on surface charge density. This leads to a lack of reliable physical basis for the synergistic regulation of nanochannel number-length, resulting in an inability to reflect actual power generation patterns.

[0004] Currently, the industry lacks a method for the synergistic regulation of multiple nanochannels that balances precision and efficiency. Furthermore, it lacks surface charge density models that consider ion-specific adsorption and rapid performance optimization methods, resulting in the optimization design of multi-channel ion permeation energy conversion devices remaining in a trial-and-error development phase for a long time. Therefore, it is necessary to develop a surface charge density model that considers ion-specific adsorption and further develop an efficient method for the synergistic regulation and optimization of the number and length of nanochannels.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure and may therefore contain information that does not constitute prior art known to those skilled in the art in this country. Summary of the Invention

[0006] To address the problems existing in the prior art, this disclosure proposes a synergistic regulation and optimization method for a multi-nanochannel ion permeation energy conversion device, comprising the following steps:

[0007] Step S100: Determine the structural parameters of the ion permeation energy conversion device, wherein the structural parameters include at least the length L of the storage tank. r and nanochannel radius R n And determine the radius R of the storage tank. r and nanochannel length L n The scope of regulation;

[0008] Step S200: Based on the structural parameters, construct a geometric model that includes a high-concentration storage tank, a low-concentration storage tank, and multiple nanochannels connected in parallel between the two.

[0009] Step S300: Calculate the surface charge density σ of the inner and outer surfaces of the nanochannel based on the surface charge density model of ion-specific adsorption;

[0010] Step S400: Based on the geometric model, surface charge density σ, and solution concentration distribution, calculate the conductivity G of the ion permeation energy conversion device. total With diffusion potential E diff ;

[0011] Step S500: Based on the conductivity G total With the diffusion potential E diff Calculate the device power density P under different numbers of nanochannels. d The power density P is obtained. d Curve showing the variation of the number of nanochannels N;

[0012] Step S600: Based on the power density P d The curve showing the change in the number of nanochannels N determines the power density P. d The number of nanochannels N and the length of nanochannel L corresponding to the maximum value n The dimensionless number Nlsr is denoted as Nlsr MP ;

[0013] Step S700: In the Nlsr MP Within the parameter range corresponding to the value, obtain the power density P. d The curve showing the variation of the number of nanochannels N is used to determine the maximum power density P of the ion permeation energy conversion device. d,MP And its corresponding optimal structural parameters.

[0014] Furthermore, the geometric model constructed in step S200 satisfies the following condition: the high-concentration storage tank and the low-concentration storage tank have the same storage tank length L. r and the radius R of the storage tank r .

[0015] Furthermore, the geometric model constructed in step S200 satisfies the following condition: the plurality of nanochannels have the same channel radius R. n and channel length L n ;

[0016] Furthermore, the formula for calculating the surface charge density σ in step S300 is as follows:

[0017] ,

[0018] Where F is the Faraday constant; K represents the total functional group surface density. A K is the reaction equilibrium constant for the reaction between the surface silanol hydroxyl group –SiOH hydrolysis generating a surface negative charge and hydrated hydrogen ions; B K is the reaction equilibrium constant for the protonation reaction of surface silanol-SiOH; C It is the reaction equilibrium constant for the specific adsorption reaction between surface silanol hydroxyl groups –SiOH and surface-positioned cations (non-hydrated hydrogen ions); Surface-positioned hydrated hydrogen ions H3O + concentration; The concentration of cations at the surface location.

[0019] Further, the electrical conductance G of the device described in step S400 total The calculation formula is:

[0020] ,

[0021] Among them, R n k is the radius of the nanochannel; b c is the molar conductivity. H c represents the concentration at the opening boundary of the high-concentration storage tank. L The concentration at the opening boundary of the low-concentration reservoir; Nlsr is the concentration representing the number of nanochannels N - the length of the nanochannels L. n The dimensionless number of the correlation; L r c is the length of the storage tank. ξ The concentration drop in the storage tank is β; the conductivity correction factor is R. n The radius of the nanochannel; This is the average conductivity correction factor; l Du The length of the Dukhin.

[0022] Further, the diffusion potential E of the device described in step S400 diff The calculation formula is:

[0023] ,

[0024] Among them, cH c represents the concentration at the opening boundary of the high-concentration storage tank. L The opening boundary of the low-concentration storage tank

[0025] Concentration; c ξ The concentration in the storage tank is reduced.

[0026] Further, in step S500, the power density P d The calculation formula is:

[0027] ,

[0028] Among them, E diff G is the diffusion potential; total For electrical conductance; R r Let be the radius of the liquid storage tank.

[0029] Furthermore, the Nlsr number (Nlsr) corresponding to the power density reaching its maximum value in step S600. MP The formula for calculating ) is:

[0030] ,

[0031] Among them, L r L represents the length of the storage tank. n N represents the length of the nanochannel; MP The number of nanochannels in the ion permeation energy conversion device structure corresponding to the maximum power density.

[0032] A computer storage medium including computer instructions that, when run on a computer, cause the computer to perform the method.

[0033] An electronic device, the electronic device comprising:

[0034] Memory, processor, and computer programs stored in memory and executable on the processor, wherein,

[0035] The processor implements the method when executing the program.

[0036] Compared with the prior art, the beneficial effects of this disclosure are as follows:

[0037] This disclosure addresses the inaccuracy of surface charge density characterization in traditional designs by establishing a surface charge density model for ion-specific adsorption. Simultaneously, by introducing the dimensionless number Nlsr, which correlates the number and length of nanochannels, it achieves efficient synergistic optimization of multi-channel structures. This method can rapidly determine the optimal combination of structural parameters, effectively improving the power density and conversion efficiency of the device, and providing a reliable design paradigm for the engineering application of ion permeation energy conversion technology.

[0038] The description provided is merely an overview of the technical solution disclosed herein. In order to make the technical means of this disclosure clearer and more understandable, to the point that those skilled in the art can implement it according to the contents of the specification, and in order to make the described and other objects, features and advantages of this disclosure more obvious and understandable, specific embodiments of this disclosure are illustrated below. Attached Figure Description

[0039] Various other advantages and benefits of this disclosure will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. Furthermore, the same reference numerals denote the same parts throughout the drawings.

[0040] In the attached diagram:

[0041] Figure 1 This is a schematic diagram of a synergistic regulation and optimization method for a multi-nanochannel ion permeation energy conversion device provided in this disclosure;

[0042] Figure 2 This is a schematic diagram of the calculation process for a collaborative regulation and optimization method for a multi-nanochannel ion permeation energy conversion device provided in this disclosure;

[0043] Figure 3 In one embodiment provided in this disclosure, the power density P d Curves showing the variation of the number of nanochannels N and the corresponding N-Nlsr number curves;

[0044] Figure 4 In one embodiment provided in this disclosure, Nlsr MP Power density P under the number d Line graph;

[0045] Figure 5 In one embodiment provided in this disclosure, the number of nanochannels N - the length of the nanochannels L n -Power density P d Two-dimensional cloud map. Detailed Implementation

[0046] The following will be combined with the appendix Figures 1 to 5The embodiments described herein are provided in detail and are intended to explain, rather than limit, this disclosure. While specific embodiments of this disclosure are shown in the accompanying drawings, it should be understood that this disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of this disclosure to those skilled in the art.

[0047] It should be noted that certain terms are used in the specification and claims to refer to specific components. Those skilled in the art will understand that different terms may be used to refer to the same component. This specification and claims do not distinguish components based on differences in terminology, but rather on differences in function. The terms "comprising" or "including" used throughout the specification and claims are open-ended and should be interpreted as "comprising but not limited to." The following descriptions of preferred embodiments of this disclosure are for the purpose of implementing the general principles of the specification and are not intended to limit the scope of this disclosure. The scope of protection of this disclosure is determined by the appended claims.

[0048] To facilitate understanding of the embodiments of this disclosure, the following will provide further explanation and description with reference to the accompanying drawings and several specific embodiments, and the accompanying drawings do not constitute a limitation on the embodiments of this disclosure.

[0049] A method for synergistic regulation and optimization of a multi-nanochannel ion permeation energy conversion device, see [link to relevant documentation]. Figure 1 This includes the following steps:

[0050] Step S100: Determine the structural parameters of the ion permeation energy conversion device, wherein the structural parameters include at least the length L of the storage tank. r and nanochannel radius R n And determine the radius R of the storage tank. r and nanochannel length L n The scope of regulation;

[0051] Step S200: Based on the structural parameters, construct a geometric model that includes a high-concentration storage tank, a low-concentration storage tank, and multiple nanochannels connected in parallel between the two.

[0052] Step S300: Calculate the surface charge density σ of the inner and outer surfaces of the nanochannel based on the surface charge density model of ion-specific adsorption;

[0053] Step S400: Based on the geometric model, surface charge density σ, and solution concentration distribution, calculate the conductivity G of the ion permeation energy conversion device. total With diffusion potential E diff ;

[0054] Step S500: Based on the conductivity G total With the diffusion potential E diff Calculate the device power density P under different numbers of nanochannels. d The power density P is obtained. d Curve showing the variation of the number of nanochannels N;

[0055] Step S600: Based on the power density P d The curve showing the change in the number of nanochannels N determines the power density P. d The number of nanochannels N and the length of nanochannel L corresponding to the maximum value n The dimensionless number Nlsr is denoted as Nlsr MP ;

[0056] Step S700: In the Nlsr MP Within the parameter range corresponding to the value, obtain the power density P. d The curve showing the variation of the number of nanochannels N is used to determine the maximum power density P of the ion permeation energy conversion device. d,MP And its corresponding optimal structural parameters.

[0057] In a preferred embodiment of the method, the geometric model constructed in step S200 satisfies the following condition: the high-concentration storage tank and the low-concentration storage tank have the same storage tank length L. r and the radius R of the storage tank r .

[0058] In a preferred embodiment of the method, the geometric model constructed in step S200 satisfies the following condition: the plurality of nanochannels have the same channel radius R. n and channel length L n ;

[0059] In a preferred embodiment of the method, the formula for calculating the surface charge density σ in step S300 is:

[0060] ,

[0061] Where F is the Faraday constant; K represents the total functional group surface density. A K is the reaction equilibrium constant for the reaction between the surface silanol hydroxyl group –SiOH hydrolysis generating a surface negative charge and hydrated hydrogen ions; B K is the reaction equilibrium constant for the protonation reaction of surface silanol-SiOH; C It is the reaction equilibrium constant for the specific adsorption reaction between surface silanol hydroxyl groups –SiOH and surface-positioned cations (non-hydrated hydrogen ions); Surface-positioned hydrated hydrogen ions H3O + concentration; The concentration of cations at the surface location.

[0062] In a preferred embodiment of the method, the electrical conductance G of the device in step S400 total The calculation formula is:

[0063] ,

[0064] Among them, R n k is the radius of the nanochannel; b c is the molar conductivity. H c represents the concentration at the opening boundary of the high-concentration storage tank. L The concentration at the opening boundary of the low-concentration reservoir; Nlsr is the concentration representing the number of nanochannels N - the length of the nanochannels L. n The dimensionless number of the correlation; L r c is the length of the storage tank. ξ The concentration drop in the storage tank is β; the conductivity correction factor is R. n The radius of the nanochannel; This is the average conductivity correction factor; l Du The length of the Dukhin.

[0065] In a preferred embodiment of the method, the diffusion potential E of the device in step S400 diff The calculation formula is:

[0066] ,

[0067] Among them, c H c represents the concentration at the opening boundary of the high-concentration storage tank. L The opening boundary of the low-concentration storage tank

[0068] Concentration; c ξ The concentration in the storage tank is reduced.

[0069] In a preferred embodiment of the method, in step S500, the power density P d The calculation formula is:

[0070] ,

[0071] Among them, E diff G is the diffusion potential; total For electrical conductance; R r Let be the radius of the liquid storage tank.

[0072] In a preferred embodiment of the method, the Nlsr number (Nlsr) corresponding to the power density reaching its maximum value in step S600. MP The formula for calculating ) is:

[0073] ,

[0074] Among them, L r L represents the length of the storage tank. n N represents the length of the nanochannel; MP The number of nanochannels in the ion permeation energy conversion device structure corresponding to the maximum power density.

[0075] A computer storage medium including computer instructions that, when run on a computer, cause the computer to perform the method.

[0076] An electronic device, the electronic device comprising:

[0077] Memory, processor, and computer programs stored in memory and executable on the processor, wherein,

[0078] The processor implements the method when executing the program.

[0079] In one specific embodiment, a method for synergistic regulation and optimization of a multi-nanochannel ion permeation energy conversion device includes the following steps:

[0080] Step S100: Determine the structural parameters of the ion permeation energy conversion device, wherein the structural parameters include at least the length L of the storage tank. r and nanochannel radius R n And determine the radius R of the storage tank. r and nanochannel length L n The scope of regulation;

[0081] In this embodiment, the solution ion concentration c ranges from 0.01 to 3000 mol / m³. 3 The pH value ranges from 5 to 9, the temperature T is 298 K, and the length of the storage tank is L. r The value range is 5~10 4 nm, nanochannel radius R n The value ranges from 5 to 30 nm, and the radius R of the storage tank is... r The value ranges from 8.8 to 7200 nm (greater than the channel radius), and the channel length L n The value range is 5~10 4 nm.

[0082] Step S200: Based on the structural parameters, construct a geometric model that includes a high-concentration storage tank, a low-concentration storage tank, and multiple nanochannels connected in parallel between the two.

[0083] In this embodiment, the high-concentration storage tank and the low-concentration storage tank have the same storage tank length L. r and the radius R of the storage tank r The multiple nanochannels have the same channel radius R. n and channel length L n .

[0084] It should be noted that the high-concentration storage tank and the low-concentration storage tank have the same storage tank length L. r and the radius R of the storage tank r This is a key prerequisite for simplifying and optimizing this method; the multiple nanochannels have the same channel radius R. n and channel length L n This is the core assumption that enables the establishment and implementation of the collaborative regulation and optimization method disclosed herein.

[0085] In this embodiment, the high-concentration storage tank, the low-concentration storage tank, and the nanochannels are all cylindrical. The opening boundary of the high-concentration storage tank is set to c. H The c H The value range is 1~3000 mol / m 3 The opening boundary of the low-concentration storage tank is set to c. L The c L The value range is 0.01~1000 mol / m 3 .

[0086] Step S300: Calculate the surface charge density σ of the inner and outer surfaces of the nanochannel based on the surface charge density model of ion-specific adsorption;

[0087] In this embodiment, the formula for calculating the surface charge density σ is:

[0088] ,

[0089] Where F is the Faraday constant, with a value of 96485 C / mol; The total functional group surface density is taken as 8.3 × 10⁻⁶. -6 mol / m 2 ;K A The equilibrium constant for the reaction of surface silanol hydroxyl –SiOH hydrolysis to generate surface negative charges and hydrated hydrogen ions is taken as 10. -6 mol / m 3 ;K BThe equilibrium constant for the protonation reaction of surface silanol-SiOH is 10. -1 m 3 / mol; K C The equilibrium constant for the specific adsorption reaction between surface silanol groups –SiOH and surface-positioned cations (non-hydrated hydrogen ions) is 10. -4.4 ; Surface-positioned hydrated hydrogen ions H3O + Concentration, with a value range of 2×10 -4 ~7×10 -4 mol / m 3 ; The cation concentration at the surface site ranges from 500 to 640 mol / m. 3 .

[0090] Step S400: Based on the geometric model, surface charge density σ, and solution concentration distribution, calculate the conductivity G of the ion permeation energy conversion device. total With diffusion potential E diff ;

[0091] In this embodiment, the electrical conductivity G of the device total The calculation formula is:

[0092] ,

[0093] Among them, R n The radius of the nanochannel is defined as k, which ranges from 5 to 30 nm. b The molar conductivity is 0.0142 S·m. 2 / mol; c H This refers to the concentration at the opening boundary of the high-concentration storage tank, ranging from 1 to 3000 mol / m³. 3 c L This refers to the concentration at the opening boundary of the low-concentration storage tank, ranging from 0.01 to 1000 mol / m³. 3 Nlsr represents the number of nanochannels N and the length of the nanochannels L. n The dimensionless number of the correlation; L r The length of the storage tank, ranging from 5 to 10. 4 nm; c ξ The concentration drop in the storage tank is β; β is the conductivity correction factor. This is the average conductivity correction factor; l Du The length of the Dukhin.

[0094] Furthermore, Nlsr is a denoted by N - the length L of the nanochannels, representing the number of nanochannels. nThe dimensionless number of the correlation is calculated using the following formula:

[0095]

[0096] Where N is the number of nanochannels, ranging from 1 to 256; L r The length of the storage tank, ranging from 5 to 10. 4 nm;L n The length of the nanochannel is 5 to 10. 4 nm.

[0097] Furthermore, the concentration in the storage tank decreases by c ξ The calculation formula is:

[0098]

[0099] Among them, c H This refers to the concentration at the opening boundary of the high-concentration storage tank, ranging from 1 to 3000 mol / m³. 3 c L This refers to the concentration at the opening boundary of the low-concentration storage tank, ranging from 0.01 to 1000 mol / m³. 3 .

[0100] Furthermore, the formula for calculating the conductivity correction factor β is as follows:

[0101] ,

[0102] Where, λ D * The length of the dimensionless Debye.

[0103] The dimensionless Debye length λ D * The calculation formula is:

[0104] ,

[0105] Where, λ D R is the length of Debye; n The radius of the nanochannel is 5~30nm.

[0106] The Debye length λ D The calculation formula is:

[0107] ,

[0108] Among them, R g ε is the universal gas constant, with a value of 8.314 J / (mol·K); ε is the dielectric constant, with a value of 6.95 × 10⁻⁶. -10F / m; T is the temperature, taken as 298K; F is the Faraday constant, taken as 96485 C / mol; c is the ion concentration of the solution, ranging from 0.01 to 3000 mol / m. 3 .

[0109] Furthermore, the average conductivity correction factor The calculation formula is:

[0110] ,

[0111] Among them, c H This refers to the concentration at the opening boundary of the high-concentration storage tank, ranging from 1 to 3000 mol / m³. 3 c L

[0112] This refers to the concentration at the opening boundary of the low-concentration storage tank, ranging from 0.01 to 1000 mol / m³. 3 c ξ β is the concentration drop in the storage tank; β is the conductivity correction factor.

[0113] In this embodiment, the Dukhin length l Du The calculation formula is:

[0114] ,

[0115] in, The surface charge density ranges from -0.001 to -0.1 C / m³. 2 c represents the ion concentration of the solution, ranging from 0.01 to 3000 mol / m³. 3 F is the Faraday constant, with a value of 96485 C / mol. These are dimensionless control parameters.

[0116] The formula for calculating υ is:

[0117] ,

[0118] Among them, l GC λ is the Gouy–Chapmann length; D The length of Debye.

[0119] The Gouy–Chapmann length l GC The calculation formula is:

[0120] ,

[0121] Where ε is the dielectric constant, with a value of 6.95 × 10⁻⁶. -10 F / m; R gis the universal gas constant, with a value of 8.314 J / (mol·K); T is the temperature, with a value of 298 K; The surface charge density ranges from -0.001 to -0.1 C / m³. 2 F is the Faraday constant, with a value of 96485 C / mol.

[0122] In this embodiment, the diffusion potential E of the device diff The calculation formula is:

[0123] ,

[0124] Among them, c H This refers to the concentration at the opening boundary of the high-concentration storage tank, ranging from 1 to 3000 mol / m³. 3 c L

[0125] This refers to the concentration at the opening boundary of the low-concentration storage tank, ranging from 0.01 to 1000 mol / m³. 3 c ξ The concentration in the storage tank is reduced.

[0126] Step S500: Based on the conductivity G total With the diffusion potential E diff Calculate the device power density P under different numbers of nanochannels. d The power density P is obtained. d Curve showing the variation of the number of nanochannels N;

[0127] In this embodiment, the device power density P d The calculation formula is:

[0128] ,

[0129] Among them, E diff G is the diffusion potential; total For electrical conductance; R r The radius of the liquid storage tank ranges from 8.8 to 7200 nm.

[0130] Step S600: Based on the power density P d The curve showing the change in the number of nanochannels N determines the power density P. d The number of nanochannels N and the length of nanochannel L corresponding to the maximum value n The dimensionless number Nlsr is denoted as Nlsr MP ;

[0131] In this embodiment, the number of nanochannels N - power density P dThe Nlsr number corresponding to the maximum power density on the curve (Nlsr MP The formula for calculating ) is:

[0132] ,

[0133] Where, N MP The number of nanochannels in the ion permeation energy conversion device structure corresponding to the maximum power density; L r The length of the storage tank, ranging from 5 to 10. 4 nm;L n This represents the channel length, with a value ranging from 5 to 10. 4 nm.

[0134] Step S700: In the Nlsr MP Within the parameter range corresponding to the value, obtain the power density P. d The curve showing the variation of the number of nanochannels N is used to determine the maximum power density P of the ion permeation energy conversion device. d,MP And its corresponding optimal structural parameters.

[0135] In this embodiment, based on the Nlsr MP Value, select its Nlsr MP The power density P is obtained from the parameter range corresponding to the value. d The curve showing the variation of the number of nanochannels N is used to determine the maximum power density P of the ion permeation energy conversion device. d,MP And its corresponding optimal structural parameters.

[0136] To better understand this disclosure, in a more specific embodiment, the calculation flow of the synergistic regulation optimization method for multi-nanochannel ion permeation energy conversion devices is described below. Figure 2 The input parameters include:

[0137] Length L of the storage tank r 1000 nm; nanochannel radius R n The value is 10 nm; determine the radius R of the storage tank. r The range is 17.68 nm to 282.84 nm; the nanochannel length L n The range is 80nm~2560nm; the temperature T is 298K; c H 300 mol / m 3 c L 1 mol / m 3 ;K A The value is 10 -6 mol / m 3 ;K B The value is 10 -1 m3 / mol; K C 10 -4.4 ; 4.5×10 -4 mol / m 3 Molar conductivity k b It is 0.0142 S·m 2 / mol; Universal gas constant R g The commonly used estimate is 8.314 J / (mol·K); the Faraday constant F is the commonly used estimate of 96487 C / mol.

[0138] The power density P calculated in this embodiment d See the curves showing the variation of the number of nanochannels N and the corresponding N-Nlsr number curves. Figure 3 .Depend on Figure 3 It can be seen that the power density P d It does not increase monotonically with the number of channels N, but reaches a peak of 11.33 W·m when N is approximately 3. -2 Continuing to increase N thereafter actually leads to P d A significant decrease. Furthermore, through... Figure 3 It is possible to obtain the number of channels N - power density P d The Nlsr value corresponding to the peak point of the curve is approximately 18.75.

[0139] The equivalent Nlsr calculated in this embodiment MP The power density curve under the number is as follows Figure 4 As shown in the figure. It can be seen from the figure that when the structural parameters satisfy Nlsr... MP When N is 18.75, the corresponding maximum power density P is... d,MP Stabilized at 11.33 W·m -2 nearby.

[0140] In this embodiment, the calculated number of channels N - channel length L n- Power density P d See the two-dimensional cloud map. Figure 5 . Figure 5 The two-dimensional cloud map clearly shows that the high power density region (the light-colored area in the figure) is concentrated in a narrow strip-shaped region, while the highest power density point P... d It is 11.33 W·m -2 It happens to be located in this area.

[0141] Therefore, in this embodiment, the maximum power density P of the device is... d,MP It is 11.33 W·m -2 In the corresponding optimal structural parameters, the final number of channels N MP With the final nanochannel length Ln,MP The relationship is:

[0142] ,

[0143] For example, the final number of nanochannels N MP When the value is 128, the length L of the nanochannel is... n,MP It is 427nm.

[0144] Although the embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this disclosure is not limited to the specific embodiments and application fields described above. The specific embodiments described above are merely illustrative and instructive, and not restrictive. Those skilled in the art can make many other forms based on the teachings of this specification and without departing from the scope of protection of the claims of this disclosure, and all of these are within the scope of protection of this disclosure.

Claims

1. A method for synergistic regulation and optimization of a multi-nanochannel ion permeation energy conversion device, characterized in that, Includes the following steps: Step S100: Determine the structural parameters of the ion permeation energy conversion device, wherein the structural parameters include at least the length L of the storage tank. r and nanochannel radius R n And determine the radius R of the storage tank. r and nanochannel length L n The scope of regulation; Step S200: Based on the structural parameters, construct a geometric model that includes a high-concentration storage tank, a low-concentration storage tank, and multiple nanochannels connected in parallel between the two. Step S300: Calculate the surface charge density σ of the inner and outer surfaces of the nanochannel based on the surface charge density model of ion-specific adsorption; Step S400: Based on the geometric model, surface charge density σ, and solution concentration distribution, calculate the conductivity G of the ion permeation energy conversion device. total With diffusion potential E diff ; Step S500: Based on the conductivity G total With the diffusion potential E diff Calculate the device power density P under different numbers of nanochannels. d The power density P is obtained. d Curve showing the variation of the number of nanochannels N; Step S600: Based on the power density P d The curve showing the change in the number of nanochannels N determines the power density P. d The number of nanochannels N and the length of nanochannel L corresponding to the maximum value n The dimensionless number Nlsr is denoted as Nlsr MP ; Step S700: In the Nlsr MP Within the parameter range corresponding to the value, obtain the power density P. d The curve showing the variation of the number of nanochannels N is used to determine the maximum power density P of the ion permeation energy conversion device. d,MP And its corresponding optimal structural parameters.

2. The method according to claim 1, characterized in that, Preferably, the geometric model constructed in step S200 satisfies the following condition: the high-concentration storage tank and the low-concentration storage tank have the same storage tank length L. r and the radius R of the storage tank r .

3. The method according to claim 1, characterized in that, The geometric model constructed in step S200 satisfies the following condition: the multiple nanochannels have the same channel radius R. n and channel length L n .

4. The method according to claim 1, characterized in that, The formula for calculating the surface charge density σ in step S300 is as follows: ， Where F is the Faraday constant; K represents the total functional group surface density. A K is the reaction equilibrium constant for the reaction between the surface silanol hydroxyl group –SiOH hydrolysis generating a surface negative charge and hydrated hydrogen ions; B K is the reaction equilibrium constant for the protonation reaction of surface silanol-SiOH; C It is the reaction equilibrium constant for the specific adsorption reaction between surface silanol hydroxyl groups –SiOH and surface-positioned cations (non-hydrated hydrogen ions); Surface-positioned hydrated hydrogen ions H3O + concentration; The concentration of cations at the surface location.

5. The method according to claim 1, characterized in that, The electrical conductance G of the device described in step S400 total The calculation formula is: ， Among them, R n k is the radius of the nanochannel; b c is the molar conductivity. H c represents the concentration at the opening boundary of the high-concentration storage tank. L The concentration at the opening boundary of the low-concentration reservoir; Nlsr is the concentration representing the number of nanochannels N - the length of the nanochannels L. n The dimensionless number of the correlation; L r c is the length of the storage tank. ξ The concentration drop in the storage tank is β; the conductivity correction factor is R. n The radius of the nanochannel; This is the average conductivity correction factor; l Du The length of the Dukhin.

6. The method according to claim 1, characterized in that, In step S400, the diffusion potential E of the device diff The calculation formula is: ， Among them, c H c represents the concentration at the opening boundary of the high-concentration storage tank. L The opening boundary of the low-concentration storage tank Concentration; c ξ The concentration in the storage tank is reduced.

7. The method according to claim 1, characterized in that, The power density P mentioned in step S500 d The calculation formula is: ， Among them, E diff G is the diffusion potential; total For electrical conductance; R r Let be the radius of the liquid storage tank.

8. The method according to claim 1, characterized in that, The Nlsr number corresponding to the power density reaching its maximum value in step S600 (Nlsr MP The formula for calculating ) is: ， Among them, L r L represents the length of the storage tank. n N represents the length of the nanochannel; MP The number of nanochannels in the ion permeation energy conversion device structure corresponding to the maximum power density.

9. A computer storage medium, characterized in that, The storage medium includes computer instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1-8.

10. An electronic device, characterized in that, The electronic device includes: Memory, processor, and computer programs stored in memory and executable on the processor, wherein, When the processor executes the program, it implements the method as described in any one of claims 1-8.

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