A type of nanorobot that can be selectively controlled in a region

Abstract

The present invention discloses a nanorobot capable of selective regional control, the nanorobot comprising a head and a tail; the head is formed of a polymer material, the interior of which comprises NFs and NPs, and has the function of absorbing and carrying drugs; the tail comprises a magnetocaloric material, and nano-magnetic fluid grains or crystal lines are precipitated therefrom by heat treatment to form an actuating device of the nanorobot; the present invention provides a nanorobot capable of selective regional control with the ability of autonomous energy absorption, energy storage and triggered energy release actuation.

Description

Technical Field

[0001] The present invention relates to the field of medical devices, and more specifically, to a nanorobot capable of region-selective control. Background Art

[0002] Recently, with the rapid development of robotics technology, micro-nano robots are becoming the focus of biomedical research as an innovative means of modern medicine. For example, when used in endoscopes, they can change with the size of the entrance to the human body's natural channels, which not only reduces the pain of invasion, but also, if they are made of biocompatible degradable materials, they can be decomposed and absorbed by the human body or excreted from the body by the same route after the task is completed.

[0003] With the progress of nanotechnology and the deepening of research in the field of micro-nanoscale, micro-nano robots can be roughly divided into two categories: micro-nano robots based on microorganisms and artificial micro-nano robots. Among them, the former mainly combines artificial structures with microorganisms, uses the various tendencies of microorganisms to control the movement of the robot, and its driving force is provided by microorganisms; while the latter is designed and processed by nanomaterials based on micro-nano structures, which is completely independent of microorganisms, and its power source is supplied and regulated by the external field. When the size of an object is reduced to the micron or nanometer level, the traditional volume-based energy supply method is difficult to use. Because the structural feature size suddenly decreases and the specific surface area increases rapidly, the factors related to the area dominate, so the area-based energy supply method becomes the dominant one. At present, the driving energy of this type of micro-nano robot mostly depends on the external environment, and the main methods are: chemical method, acoustic, photothermal method and electromagnetic field method. Due to the inertia of micro-nano robots and the complexity of the fluid environment, it is difficult to achieve precise control and path planning with the power usually provided by the external environment (such as magnetic control). Therefore, the design of artificial micro-nano robots and devices that can utilize the external environment to coordinate and absorb and store energy and convert it into actuating energy should attract great attention at home and abroad.

[0004] The application of nanorobots and micro-nano actuators in biomedicine deserves special attention. The current research directions are mainly focused on how to achieve micro-nano-level movement and positioning, how to make micro-nano actuators realize sensing detection and effective control, etc. Among them, how to use nano-micro displacement to achieve the macroscopic displacement of the actuator itself is also increasingly favored, but it is still in the stage of mechanism research and laboratory demonstration, involving many key scientific issues such as structural design, motion triggering, material processing, sensing and control, etc., which need to be solved urgently. Summary of the invention

[0005] The present invention overcomes the shortcomings of the prior art and provides a nanorobot that can be selectively controlled in a regional manner.

[0006] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0007] A nanorobot capable of region-selective control, the nanorobot comprising a head and a tail;

[0008] The head includes a spherical part and a conical part, and is integrally formed; the head is formed of a polymer material, and the interior thereof includes nanoparticles (NPs) and nanofibers (NFs), which have the function of absorbing and carrying drugs;

[0009] The tail portion includes a 3 / 4 circular portion and an eight-shaped portion, and is integrally formed; the tail portion contains a magnetocaloric material, and nano-magnetic fluid grains or crystal lines are precipitated therefrom through heat treatment to form an actuator of the nanorobot;

[0010] The actuator obtains the power source through the magnetic energy contribution of each cycle to the total energy obtained with temperature, that is, the nanorobot obtains the power source through different thermodynamic processes when crossing the Curie temperature Tc and the spin reorientation temperature, and the theoretical output power is predicted from this; the specific formula is as follows:

[0011] , E is the introduced field quantity H D After the whole area,

[0012] in, is the magnetic permeability, M is the magnetization intensity, N is the shape factor matrix, is the externally applied field, is the exchange energy, is the magnetocrystalline anisotropy energy;

[0013] After the actuator obtains energy from the power source, it will produce free deformation. At this time, the magnetic field is maintained, its energy is converted into deformation energy, and the current deformation is maintained; the nanorobot is then pushed into the flow field through injection or gas, and the fluid provides its initial power and transports it forward with the flow field; when it reaches the vicinity of the predetermined target point, the magnetic field and temperature field are changed to trigger it to release energy and actuate; combined with the interaction between the nanorobot and the fluid when the internal stress is released, the surface stress of the fluid on the actuator is changed at the same time, to realize the start and stop, speed and direction change of the nanorobot in the fluid, and achieve regional selective control.

[0014] Furthermore, the actuator obtains the energy contribution of magnetic energy according to the basic magnetic system theory, which is as follows: ,in, It is the whole domain. is the magnetic permeability, is the field quantity;

[0015] Then, when there are magnets and external applied fields in the initial system environment, the magnetic energy in the closed system environment is as follows: ,in, The difference in field quantity is the energy obtained inside the hypothetical nanorobot with the magnet surface as the control boundary, and the field quantity The field quantity is introduced as the magnetizing field due to the applied external field is the demagnetization field energy that reacts inside the magnet, and the specific formula is as follows:

[0016] ,

[0017] Among them, after expansion and simplification, the relationship For demagnetization energy, according to the magnetization intensity M and the demagnetization field Magnetic flux, the formula is expanded as follows:

[0018]

[0019] The first term of the formula is the volume integral of the space , and the demagnetization field This is equivalent to the negative gradient of the scalar field , then the formula is as follows:

[0020] , where V is the volume, g is the gravitational constant,

[0021] Applying the electrostatic Maxwell relation, the divergence of B is 0, and the second term of the formula is reduced to 0. Combining Gauss's law, the volume integral is converted into an area integral , S represents the area. Since the plane area is infinite, the variable formula for the field energy change of the demagnetization field is obtained: , then the volume integral of the space will approach 0, so the formula is as follows:

[0022] ,

[0023] The area integral and the relation Substituting into the above formula, we get the following formula:

[0024] ,

[0025] Applying Maxwell's relations and Gauss's law for electrostatics, tends to 0, and the magnetic field It is equivalent to the shape coefficient matrix N and the magnetization intensity M, that is, , and we get the following formula:

[0026] ,

[0027] Combined with the Hamiltonian function's description of the magnetic system, two energy terms are added, and the final formula is as follows:

[0028]

[0029] in, is the exchange energy, is the magnetocrystalline anisotropy energy.

[0030] Furthermore, when there is only non-magnetic medium in the initial system environment, all the magnetic energy in the closed system comes from the external applied field. .

[0031] Furthermore, the energy absorbed by the actuator is determined by combining the form of autonomous energy absorption of the actuator. , Input energy to it, the energy conversion efficiency is as follows:

[0032] ,

[0033] The energy absorbed by the actuator is directly related to the magnetization energy of the magnetocaloric material, the deformation energy of the device, the temperature and other energy items to be determined, which is called mixed energy. Therefore, the specific formula for its energy absorption is as follows:

[0034] ,

[0035] in, P is the generalized stress, ξ is the device deformation, ρ is the density, T is the temperature, C p is the heat energy at normal pressure, S m is the magnetic entropy of the device magnetic domain, W other is other energy terms.

[0036] Furthermore, combined with the interaction between the nanorobot and the fluid when the internal stress is released, the surface stress of the fluid on the actuator is changed at the same time. The temperature distribution of the actuator generated by the excitation magnetic field is used as the boundary condition to construct an equivalent source term, and the motion characteristics of the nanorobot are modeled and the motion morphology is described.

[0037] Furthermore, the basic conditions for describing the motion characteristics of nanorobots include kinematic conditions and dynamic conditions;

[0038] Kinematic conditions: , where d f and d s Represent the displacement of fluid and structure respectively. The actuator is a micro-nano structure with a non-smooth surface. The corresponding velocity coordination condition is , where u f Represents the fluid velocity.

[0039] Kinetic conditions: , σ f and σ sare the stresses of fluid and structure respectively, and n is a constant coefficient.

[0040] Furthermore, nanorobot control includes fluid motion control and structural dynamic solid motion control;

[0041] Fluid motion control requires consideration of mass and momentum for incompressible fluids;

[0042] The mass conservation equation is as follows: ,

[0043] Among them, since the fluid is incompressible, the velocity gradient is simplified to 0;

[0044] The momentum balance equation is as follows:

[0045]

[0046] in, is the Cauchy stress tensor, expressed as , then the momentum balance equation is as follows:

[0047] ,

[0048] Where ρ is the density in kg / m 3 ; μ is the dynamic viscosity, the unit is Ns / m 2 ; u is the speed, the unit is m / s; p is the pressure, the unit is Pa; I is the unit matrix; g is the unit volume force of the fluid; t is the time;

[0049] In micro-scale structural analysis, surface tension is crucial, so it is added to the formula as a volume force, as follows:

[0050] ,

[0051] in, is the surface tension acting on the air / water interface, in N;

[0052] Structural dynamic solid motion control, due to the size effect of the nanorobot's micro-nano structure, the surface stress of the interface between the nanorobot and the fluid should be calculated with the help of the diffusion interface representation method. The specific formula is as follows:

[0053] ,

[0054] in, is the phase field parameter; G is the chemical potential, the unit is ;

[0055] ,

[0056] In the phase field method, the mixing energy density and the interface thickness are related to the surface tension coefficient as follows: ; The interface thickness parameter is usually set to ,in is the characteristic grid size of the interface passing region, and each characteristic grid constitutes a sub-region of selective control; the dynamic formula is as follows:

[0057] ,

[0058] Where d is the displacement field of the elastic device and f is the body force vector of the elastic structure.

[0059] Furthermore, the nanorobot transport speed is set to , changing the external field to trigger the energy storage actuator to release energy and deform, and start directional movement to the vicinity of the predetermined target under the coupling control of the new physical field;

[0060] The nanorobot solves the control formula to obtain the following speed of the nanorobot to the fluid: , then the speed after superposition is , then the trajectory of a single nanorobot is Statistical analysis is used to characterize and solve the motion trajectory and regional aggregation degree of nanorobot clusters.

[0061] Furthermore, the entire flow field is divided into several sub-areas, and then the sub-areas are divided into smaller grid areas, and the grids are further subdivided into nanoscale flow field areas, namely nanodomains; a large amount of nanorobot feature data is collected in the nanodomain, and a motion trajectory model is obtained through machine learning training, which is compared with the travel trajectory of a single nanorobot, and then the target path is used as an input variable to obtain the optimal motion control model; the optimal control variable is output for each nanodomain, forming a regional selective cluster directional control of nanorobots;

[0062] Among them, the characteristic data of nanorobots include position, direction, and speed.

[0063] Furthermore, when the nanorobot cluster is regionally selectively controlled, due to the continuity and inertia in the movement of the fluid, the motion state of the micro-nano device at time t is affected by the motion state at time t-1. Therefore, the recurrent neural network RNN ​​and LTST are introduced to control and predict its motion trajectory.

[0064] Compared with the prior art, the present invention has the following advantages:

[0065] 1. The nanorobot designed by the present invention includes a head and a tail; the head includes a spherical part and a conical part, and is integrally formed; the head is formed of a polymer material, and the interior thereof includes NFs and NPs, and has the function of absorbing and carrying drugs; the tail includes a 3 / 4 circular part and an eight-shaped part, and is integrally formed; the tail contains a magnetocaloric material, and nano-magnetic fluid grains or crystal lines are precipitated from it by heat treatment to form the actuating device of the nanorobot. The obtained magnetocaloric energy-absorbing material-polymer composite nanorobot has the ability of autonomous energy absorption, energy storage, and triggering energy release actuation.

[0066] 2. Compared with micro-nano robots that rely solely on microorganisms or the external environment to provide driving energy, this invention proposes the temperature characteristics of magnetization energy absorption based on the selected thermomagnetic material, determines the optimal temperature range of energy conversion and its optimal efficiency calculation; dumps magnetic energy into deformation energy of flexible micro-nano composite devices, and realizes energy release and actuation of the actuator through external trigger conditions;

[0067] 3. Based on near-field electrospinning and fluid instability, the present invention uses near-field electrospinning to prepare energy-absorbing actuation devices with regularly arranged nanofibers and nanoparticles, and establishes the coupling control equation of energy-releasing actuation according to its micro-nano surface effect.

[0068] 4. The present invention applies artificial intelligence algorithms to the precise control strategy of micro-nano robots. The physical characteristics of the actuator and the target path are used as the input of the machine learning model to obtain the optimal control parameters and schemes. The external physical field coupling is adjusted accordingly to promote the release of the actuator's stored energy and autonomous directional movement, thereby achieving predictable regional selective control. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 is a schematic diagram of the structure of the nanorobot of the present invention;

[0070] Figure 2 It is a schematic diagram of the relative motion of the fluid and the device under the coupling effect of the present invention;

[0071] Figure 3 This is a schematic diagram of the recurrent neural network (RNN) combined with the present invention.

[0072] Description of reference numerals: head 1 and tail 2. DETAILED DESCRIPTION

[0073] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments. Parts not described herein are all implemented by conventional technical means in the art, so they will not be described in detail.

[0074] Example:

[0075] like Figures 1 to 3As shown, a nanorobot that can be selectively controlled in a certain area includes a head 1 and a tail 2.

[0076] The head 1 includes a spherical part and a conical part, and is integrally formed. The head 1 is formed of a polymer material, and includes nanoparticles (NPs) and nanofibers (NFs) inside, which have the function of absorbing and carrying drugs.

[0077] The tail 2 includes a 3 / 4 circular portion and an eight-shaped portion, and is integrally formed; the tail 2 contains magnetocaloric material, and nano-magnetic fluid grains or crystal lines are precipitated from the material through heat treatment to form the actuator of the nanorobot. That is, the magnetocaloric material is added and co-sprayed during the manufacture of the tail 2.

[0078] The whole nanorobot is processed by high-voltage electrostatic field direct spraying for the selected magnetocaloric materials and deformation absorbing composites (such as gel, etc.) through the electrospray device. The selected materials are prepared by high-concentration doping magnetocaloric materials in the sol-gel and electrostatic spraying process. In the process of preparing the nanorobot, various parameters are adjusted to make full use of the fluid instability of the jet flow to spray out nanorobots with nanocomposite structures with regular arrangement of nanofibers and nanoparticles. The obtained magnetocaloric energy absorbing material-polymer composite nanorobot has the ability to autonomously absorb energy, store energy and trigger energy release.

[0079] The actuator obtains the power source through the magnetic energy contribution of each cycle to the total energy obtained with temperature, that is, the nanorobot obtains the power source through different thermodynamic processes when crossing the Curie temperature Tc and the spin reorientation temperature, and the theoretical output power is predicted from this. The specific formula is as follows:

[0080] , E is the introduced field quantity H D After the whole area,

[0081] in, is the magnetic permeability, M is the magnetization intensity, N is the shape factor matrix, is the externally applied field, is the exchange energy, is the magnetocrystalline anisotropy energy.

[0082] Specifically, the actuator uses a low Curie point (0-20°C) magnetic material and gel composite to prepare an elastic polymer micro-nano-sized nanorobot. Under the excitation of the magnetic field, it will deform, thereby changing the interaction force between the solid device and the fluid, triggering the energy release actuation to produce displacement. As a micro-actuator driving element, as the external magnetic field changes, its magnetic field size, alternating frequency, etc. will affect the magnetothermal energy obtained by the micro-nano composite device, and the deformation of the nanorobot actuator can be accurately controlled by adjusting the external magnetic field.

[0083] When the magnet enters the nanometer scale and reaches the critical size of a single domain, its magnetic domain structure will undergo a qualitative change from multi-domain to single domain, and the anisotropy and coercive field will change. Therefore, the microstructure of the material can be changed purposefully, and the magnetic domain engineering of the magnetic material can be carried out in a controllable manner, ultimately obtaining excellent magnetic properties. In an alternating magnetic field or a stable magnetic field, the magnetocaloric material of the nanorobot, under the conditions of different magnetic crystal structures, has a forced increase in spontaneous magnetization intensity and an accompanying temperature increase. In order to obtain sufficient actuation energy, it is necessary to be able to calculate the specific energy value of the power source.

[0084] The actuator obtains the energy contribution of magnetic energy according to the basic magnetic system theory, which is as follows: ; in, It is the whole domain. is the magnetic permeability, For the field quantity.

[0085] Assuming that there is only non-magnetic medium in the initial system environment, all the magnetic energy of the closed system comes from the external applied field. When there are magnets and external applied fields in the initial system environment, the magnetic energy in the closed system environment is as follows: ,in The difference in field quantity is the energy obtained inside the hypothetical nanorobot with the magnet surface as the control boundary, and the field quantity The field quantity is introduced as the magnetizing field due to the applied external field is the demagnetization field energy that reacts inside the magnet, and the specific formula is as follows:

[0086]

[0087] After expansion and simplification, the relationship Used to calculate the demagnetization energy, based on the magnetization intensity M and the demagnetization field Magnetic flux, the formula is expanded as follows:

[0088]

[0089] The first term of the formula is the volume integral of the space , and the demagnetization field This is equivalent to the negative gradient of the scalar field , then the formula is as follows:

[0090] , where V is the volume, g is the gravitational constant,

[0091] Applying the electrostatic Maxwell relation, the divergence of B is 0, and the second term of the formula is reduced to 0. Combining Gauss's law, the volume integral is converted into an area integral , S represents the area, because the plane area is infinite, such as and , we get the variable formula of field energy change of demagnetization field , then the volume integral of the space will approach 0, so the formula can be simplified as follows: , substitute the area integral into the above formula, and then change the relationship Substituting the second term into the above formula, we get the following formula:

[0092]

[0093] Applying Maxwell's relations and Gauss's law for electrostatics, tends to 0, and the magnetic field It is equivalent to the shape coefficient matrix N and the magnetization intensity M, that is, , and we get the following formula:

[0094]

[0095] Combined with the Hamiltonian function's description of the magnetic system, two energy terms are added, and the final formula is as follows:

[0096] ,in, is the exchange energy, is the magnetocrystalline anisotropy energy.

[0097] The above thermodynamics is used to predict the theoretical power source energy value. To further optimize this model, the thermomagnetic conduction mechanism based on ordered-ordered magnets can achieve higher absolute efficiency. The above energy terms need to be derived theoretically to obtain their specific expressions, and combined with the form of autonomous energy absorption of the actuator of the research object, the absorbed energy is determined. , The input energy is the theoretical power source energy value, and the energy conversion efficiency is as follows:

[0098] , the energy absorbed by the actuator is directly related to the magnetization energy of the magnetocaloric material, the deformation energy of the device, the temperature and other energy items to be determined, which is called mixed energy. Therefore, the specific formula for energy absorption is as follows:

[0099]

[0100] in, P is the generalized stress, ξ is the device deformation, ρ is the density, T is the temperature, C p is the heat energy at normal pressure, S m is the magnetic entropy of the device magnetic domain, W other is other energy terms.

[0101] Therefore, the nanorobot has deformation stress and magnetic stress, and can freely release the power source under triggering conditions.

[0102] In order to optimize the monomer structure of the actuator and prepare for regional selective control, it is necessary to study the transport, triggering of energy release and actuation, and controllable conditions of the monomer elastic actuator under the action of multiple physical fields. Because it will absorb and store energy after being subjected to the action of the magnetic field. According to the magnetocaloric effect, the actuator will produce free deformation after absorbing energy; if the magnetic field is maintained, its energy is converted into deformation energy and can also maintain the current deformation. Then it is pushed into the flow field by injection or gas, and the fluid provides its initial power and transports it forward with the flow field; when it is near the predetermined target point, the coupling effect of changing the magnetic field and temperature field will trigger its energy release and actuation. Therefore, the deformation generated when the internal stress of the nanorobot is released will interact with the fluid. If the surface stress of the fluid on the actuator is changed at the same time, the motion characteristics of the actuator of the nanorobot in the fluid, such as start and stop, speed and direction change, can be realized, and regional selective control can be achieved. This is the coupling effect between the fluid and the actuator.

[0103] In the process of coupling between fluid and actuator, the deformation of the structure is applied to the fluid area, and the force of the fluid in turn affects the structure. In order to simplify the complexity of the coupling effect, the temperature distribution of the actuator generated by the excitation magnetic field is used as the boundary condition, and its equivalent source term is constructed to model the motion characteristics of the device and describe the motion morphology. To accurately predict the movement direction and displacement of the nanorobot and achieve controlled motion. Taking the actuator as the research object, the basic conditions applied to the coupling interface between the fluid and the actuator are kinematic conditions and dynamic conditions. That is, the basic conditions for describing the motion characteristics of the nanorobot include kinematic conditions and dynamic conditions.

[0104] Kinematic conditions: , where d f and d s represent the displacement of the fluid and the structure respectively. Since the actuator under study is a micro-nano structure with a non-smooth surface, the corresponding velocity coordination condition is , where u f Represents the fluid velocity.

[0105] Kinetic conditions: , where σ f and σ s are the stresses of fluid and structure respectively, and n is a constant coefficient.

[0106] Nanorobot control includes fluid motion control and structural dynamic solid motion control, and then a coupling control method is established.

[0107] Specifically, fluid motion control requires consideration of the mass and momentum of incompressible fluids.

[0108] The mass conservation equation is as follows:

[0109]

[0110] Among them, since the fluid is incompressible, the velocity gradient is simplified to 0;

[0111] The momentum balance equation is as follows:

[0112]

[0113] in, is the Cauchy stress tensor, expressed as , then after substituting, the momentum balance equation is as follows:

[0114]

[0115] Where ρ is the density in kg / m 3 ; μ is the dynamic viscosity, the unit is Ns / m 2 ; u is the speed, the unit is m / s; p is the pressure, the unit is Pa; I is the unit matrix; g is the fluid unit volume force; t is the time.

[0116] In microscale structural analysis, surface tension is crucial, so the surface tension is equivalent to the product of the gradient of the field variable and the chemical potential, and is added to the formula as a volume force, as follows:

[0117]

[0118] in is the surface tension acting on the air / water interface, in N.

[0119] Structural dynamic solid motion control, due to the size effect of the nanorobot's micro-nano structure, the surface stress of the interface between the nanorobot and the fluid should be calculated with the help of the diffusion interface representation method. The specific formula is as follows:

[0120]

[0121] in, is the phase field parameter; G is the chemical potential, the unit is ;

[0122]

[0123] In the phase field method, the mixing energy density and the interface thickness are related to the surface tension coefficient as follows: ; The interface thickness parameter is usually set to ,in is the characteristic grid size of the interface passing area, and each characteristic grid constitutes a sub-area of ​​selective control. The dynamic formula is as follows:

[0124]

[0125] Where d is the displacement field of the elastic device, and f is the body force vector of the elastic structure. In this way, the hybrid energy of the nanorobot and the displacement field are mutually correlated.

[0126] Under the control of the magnetic field, it absorbs energy, produces deformation and stores sufficient mechanical energy. Based on the randomness of Brownian motion and unstable flow, the distribution of nanorobot clusters in the carrier fluid tends to be uniform. Through injection or gas push, the random and uniformly distributed clusters of actuators are injected into the flow field to form initial excitation and forward transport.

[0127] Set the nanorobot transport speed to , changing the external field to trigger the energy storage actuator to release energy and deform, achieving autonomous movement under the coupling of fluid and actuator, and starting directional movement to the vicinity of the predetermined target under the coupling control of the new physical field;

[0128] The nanorobot solves the control formula to obtain the following speed of the nanorobot to the fluid: , then the speed after superposition is , then the trajectory of a single nanorobot is Statistical analysis is used to characterize and solve the motion trajectory and regional aggregation degree of nanorobot clusters.

[0129] Since the motion characteristics of the monomers are scattered, in order to achieve cluster control for a common goal, it is necessary to plan the optimal path. Therefore, the discrete idea and regional selectivity algorithm are used to divide the entire flow field into several sub-regions, and then the sub-regions are divided into smaller grid regions, and the grids are gradually subdivided into nanoscale flow field regions, namely nanodomains. A large amount of nanorobot feature data is collected in the nanodomain, and the motion trajectory model is obtained through machine learning training, which is compared with the travel trajectory of a single nanorobot. The target path is then used as the input variable to obtain the optimal motion control model; the best control variables are output for each nanodomain, so that the micro-nano devices can reach the expected target position in a timely and accurate manner, forming a regional selective cluster directional control method. That is, regional selective cluster directional control of nanorobots is formed. Among them, the nanorobot feature data includes position, direction, speed, etc.

[0130] Preferably, when the nanorobot cluster is subjected to regional selective control, due to the continuity and inertia in the movement of the fluid, the motion state of the micro-nano device at time t is affected by the motion state at time t-1. Therefore, the recurrent neural network RNN ​​and LTST are introduced to control and predict the trajectory of its movement, thereby achieving accurate planning of the target path.

[0131] In summary, compared with micro-nano robots that rely solely on microorganisms or the external environment to provide driving energy, the nanorobots designed in this scheme propose the temperature characteristics of magnetization energy absorption based on the selected thermomagnetic materials, determine the optimal temperature range of energy conversion and its optimal efficiency calculation; dump the magnetic energy into the deformation energy of the flexible micro-nano composite device, and realize the energy release actuation of the actuator through external triggering conditions. The energy-absorbing actuation device with regular arrangement of nanofibers and nanoparticles is prepared by near-field electrospraying. Based on its micro-nano surface effect, the coupling control equation of energy release actuation is established, and by adjusting the coupling effect of the external physical field, the actuator's energy storage is released and autonomous directional movement is promoted, realizing predictable regional selective control.

[0132] In the description of the present invention, it should be noted that, unless otherwise specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, which may refer to mechanical connection or electrical connection, internal communication between two components, or direct connection. "upper", "lower", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may change.

[0133] In the drawings of the embodiments disclosed in the present invention, only the structures involved in the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the case of no conflict, the same embodiment and different embodiments of the present invention can be combined with each other; the above is only a preferred implementation mode of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the concept of the present invention, and these improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A nanorobot capable of region-selective control, characterized in that: The nanorobot includes a head and a tail; the head includes a spherical part and a conical part, and is integrally formed; the head is formed of a polymer material, and includes NFs and NPs inside, which has the function of absorbing and carrying drugs; The tail portion includes a 3 / 4 circular portion and an eight-shaped portion, and is integrally formed; the tail portion contains a magnetocaloric material, and nano-magnetic fluid grains or crystal lines are precipitated therefrom through heat treatment to form an actuator of the nanorobot; The actuator obtains the power source through the magnetic energy contribution of each cycle to the total energy obtained with temperature, that is, the nanorobot obtains the power source through different thermodynamic processes when crossing the Curie temperature Tc and the spin reorientation temperature, and the theoretical output power is predicted from this; the specific formula is as follows: , E is the introduced field quantity H D After the whole area, in, is the magnetic permeability, M is the magnetization intensity, N is the shape factor matrix, is the externally applied field, is the exchange energy, is the magnetocrystalline anisotropy energy; After the actuator obtains the energy from the power source, it will produce free deformation. At this time, the magnetic field is maintained, and its energy is converted into deformation energy, and the current deformation is maintained; The nanorobot is then pushed into the flow field through injection or gas, with the fluid providing its initial power and transporting it forward along the flow field; when it is near the predetermined target point, the magnetic field and temperature field are changed to trigger its energy release and actuation; the nanorobot's internal stress release is combined with the interaction with the fluid, while the surface stress of the fluid on the actuator is changed, to achieve the start and stop, speed and direction change of the nanorobot in the fluid, and achieve regional selective control; The actuator obtains the energy contribution of magnetic energy according to the basic magnetic system theory, which is specifically as follows: , in, It is the whole domain. is the magnetic permeability, is the field quantity; Then, when there are magnets and external applied fields in the initial system environment, the magnetic energy in the closed system environment is as follows: ,in, The difference in field quantity is the energy obtained inside the hypothetical nanorobot with the magnet surface as the control boundary, and the field quantity The field quantity is introduced as the magnetizing field due to the applied external field is the demagnetization energy that reacts inside the magnet, and the specific formula is as follows: ， After expansion and simplification, the relationship For demagnetization energy, according to the magnetization intensity M and the demagnetization field Magnetic flux, the formula is expanded as follows: ， The first term of the formula is the volume integral of the space , and the demagnetization field This is equivalent to the negative gradient of the scalar field , then the formula is as follows: , where V is the volume, g is the gravitational constant, Applying the electrostatic Maxwell relation, the divergence of B is 0, and the second term of the formula is reduced to 0; combined with Gauss's law, the volume integral is converted into an area integral , S represents the area. Since the plane area is infinite, the variable formula for the field energy change of the demagnetization field is obtained: , then the volume integral of the space will approach 0, so the formula is as follows: ， The area integral and the relation Substituting into the above formula, we get the following formula: ， Applying Maxwell's relations and Gauss's law for electrostatics, tends to 0, and the magnetic field It is equivalent to the shape coefficient matrix N and the magnetization intensity M, that is, , and we can get the following formula: ， Combined with the Hamiltonian function's description of the magnetic system, two energy terms are added, and the final formula is as follows: ， in, is the exchange energy, is the magnetocrystalline anisotropy energy.

2. A region-selectively controllable nanorobot according to claim 1, characterized in that: When there is only non-magnetic medium in the initial system environment, all the magnetic energy of the closed system comes from the external applied field. .

3. A region-selectively controllable nanorobot according to claim 1 or 2, characterized in that: Combined with the form of autonomous energy absorption of the actuator, determine its absorbed energy , Input energy to it, the energy conversion efficiency is as follows: ， The energy absorbed by the actuator is directly related to the magnetization energy of the magnetocaloric material, the deformation energy of the device, the temperature and other energy items to be determined, which is called mixed energy. Therefore, the specific formula for its energy absorption is as follows: ， in, P is the generalized stress, ξ is the device deformation, ρ is the density, T is the temperature, C p is the heat energy at normal pressure, S m is the magnetic entropy of the device magnetic domain, W other is other energy terms.

4. The region-selectively controllable nanorobot according to claim 1, characterized in that: Combined with the interaction between the nanorobot and the fluid when the internal stress is released, the surface stress of the fluid on the actuator is changed at the same time. The temperature distribution of the actuator generated by the excitation magnetic field is used as the boundary condition to construct an equivalent source term, model the motion characteristics of the nanorobot and describe the motion morphology.

5. The region-selectively controllable nanorobot according to claim 4, characterized in that: The basic conditions for describing the motion characteristics of nanorobots include kinematic conditions and dynamic conditions; Kinematic conditions: d f =d s , where d f and d s They represent the displacement of the fluid and the structure respectively. The actuator is a micro-nano structure with a non-smooth surface. The corresponding velocity coordination condition is u f =d s , where u f represents the fluid velocity; Kinetic conditions: , where σ f and σ s are the stresses of fluid and structure respectively, and n is a constant coefficient.

6. The region-selectively controllable nanorobot according to claim 5, characterized in that: Nanorobot control includes fluid motion control and structural dynamic solid motion control; Fluid motion control requires consideration of mass and momentum for incompressible fluids; The mass conservation equation is as follows: , Among them, since the fluid is incompressible, the velocity gradient is simplified to 0; The momentum balance equation is as follows: , Where б is the Cauchy stress tensor, expressed as , then the momentum balance equation is as follows: ， Where ρ is the density in kg / m 3 ; μ is the dynamic viscosity, the unit is Ns / m 2 ; u is the speed, the unit is m / s; p is the pressure, the unit is Pa; I is the unit matrix; g is the unit volume force of the fluid; t is the time; In micro-scale structural analysis, surface tension is crucial, so it is added to the formula as a volume force, as follows: ， in is the surface tension acting on the air / water interface, in N; Structural dynamic solid motion control, due to the size effect of the nanorobot's micro-nano structure, the surface stress of the interface between the nanorobot and the fluid should be calculated with the help of the diffusion interface representation method. The specific formula is as follows: ， Where Φ is the phase field parameter; G is the chemical potential, the unit is J / mol, ； In the phase field method, the mixing energy density and the interface thickness are related to the surface tension coefficient as follows: ; The interface thickness parameter is usually set to ,in is the characteristic grid size of the interface passing region, and each characteristic grid constitutes a sub-region of selective control; the dynamic formula is as follows: , where d is the displacement field of the elastic device and f is the body force vector of the elastic structure.

7. The region-selectively controllable nanorobot according to claim 6, characterized in that: Set the nanorobot transport speed to , changing the external field to trigger the energy storage actuator to release and deform, and the new physical field coupling control starts the directional movement to the vicinity of the predetermined target; the nanorobot solves the control formula to obtain the following speed of the nanorobot to the fluid: Then the speed after superposition is , then the trajectory of a single nanorobot is Statistical analysis is used to characterize and solve the motion trajectory and regional aggregation degree of nanorobot clusters.

8. The region-selectively controllable nanorobot according to claim 7, characterized in that: The entire flow field is divided into several sub-areas, which are then divided into smaller grid areas. The grids are then gradually subdivided into nanoscale flow field areas, namely nanodomains. A large amount of nanorobot characteristic data is collected in the nanodomain, and a motion trajectory model is obtained through machine learning training. This is compared with the travel trajectory of a single nanorobot, and the target path is used as an input variable to obtain the optimal motion control model. The optimal control variables are output for each nanodomain to form a directional control of the nanorobot regional selective cluster. Among them, the nanorobot characteristic data include position, direction, and speed.

9. The region-selectively controllable nanorobot according to claim 8, characterized in that: When the nanorobot cluster is regionally selectively controlled, due to the continuity and inertia in the movement of the fluid, the motion state of the micro-nano device at time t is affected by the motion state at time t-1. Therefore, the recurrent neural network RNN ​​and LTST are introduced to control and predict its motion trajectory.

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