A method for controlling a cluster of nanorobots based on an induced star chain

Abstract

The present application relates to the field of nanomaterials, and provides a kind of based on the manipulation method of star chain induction nanorobot cluster, comprising: step S1: pre-configure the composite induction field of nanorobot cluster control;Wherein, composite induction field is driven nanorobot cluster assembly into star chain structure by coarse-grained model and active particle environment;Step S2: according to star chain structure, determine the kinetic parameter of nanorobot cluster;Step S3: according to kinetic parameter, when receiving control instruction, generate the control parameter of active particle in composite induction field;Step S4: according to control parameter, control star chain structure executes the target operation corresponding to operation instruction, and after completing target operation, revoke composite induction field.

Description

Technical Field

[0001] This invention relates to the field of nanomaterials technology, and in particular to a method for manipulating a cluster of nanorobots based on induced star chains. Background Technology

[0002] In existing technologies, nanorobots are primarily driven directly by external physical fields (such as magnetic or optical fields), guiding their movement by applying uniform control signals. However, while this method can perform basic motion control in simple environments, it has many limitations in complex biological organisms.

[0003] First, a single driving mode faces difficulties in migration in a dynamically changing biological environment, and is prone to trajectory deviation and severe energy dissipation, such as in intravascular shear force gradients and tissue viscosity heterogeneity.

[0004] Secondly, in the collaborative mechanism of multi-robot clusters, the interaction modes between units cannot be adjusted based on real-time environmental changes, which can easily lead to instability in the group's movement due to local disturbances.

[0005] In existing nanorobot swarm control, conformational regulation relies on passive response to external stimuli and cannot be achieved through topological engineering-based directional deformation. In active particle baths, they exhibit limited dynamic adaptability; when the activity force increases, traditional linear chains only undergo disordered extension, failing to form stable hyperdiffusion motion modes. For example, CN202211164823.9, "Multimodal Behavior Regulation Method and System for Micro / Nanorobot Swarms Based on Magnetic Fields," uses a single magnetic field-driven approach, generating linear chains. Summary of the Invention

[0006] This application proposes a method for manipulating nanorobot swarms based on induced star chains. By synergistically combining the non-equilibrium driving force of active particles with the topological dependence of the star chains, the manipulation accuracy and environmental adaptability of nanorobot swarms are significantly improved. The directional energy gradient design of the composite induced field overcomes the randomness limitations of Brownian motion in traditional thermal bath environments, enabling nanorobots to achieve rapid self-assembly with low energy consumption. Based on dynamic scheduling and dynamic parameter control, the system can respond to external commands in real time and adaptively switch motion modes, between super-diffused and normal diffused states, making it suitable for multi-task requirements in complex biological environments. Furthermore, the phase transition mechanism driven by active particles endows the system with reversible reconfiguration capabilities. Through precise control of critical active forces, it can flexibly switch between disrupting phase separation and promoting self-assembly, providing a highly robust solution for targeted drug delivery or dynamic repair of micro / nano devices.

[0007] Firstly, this application proposes a method for manipulating nanorobot swarms based on induced star chains, comprising:

[0008] Step S1: Pre-configure a composite induction field controlled by a cluster of nanorobots; wherein, the composite induction field drives the nanorobot cluster to assemble into a star-shaped chain structure through a coarse-grained model and an active particle environment;

[0009] Step S2: Determine the dynamic parameters of the nanorobot cluster based on the star-shaped chain structure;

[0010] Step S3: Based on the dynamic parameters, upon receiving the control command, generate the control parameters for the active particles in the composite induced field;

[0011] Step S4: According to the control parameters, control the star chain structure to execute the target operation corresponding to the operation command, and after the target operation is completed, cancel the composite induction field.

[0012] This application constructs a composite induction field exhibiting induced manipulation behavior through a coarse-grained model and an active particle environment. Then, the composite induction field controls the connection of nanorobot clusters, forming a star-shaped chain structure. Based on the dynamic parameters of the star-shaped chain nanorobot clusters within the composite induction field, by controlling changes in the environment within the composite induction field, the corresponding nanorobot clusters will move in multiple directions and perform tasks simultaneously through the star-shaped chain structure, driven by changes in driving force and path under environmental changes. During movement, the stability of the overall cluster is maintained, and the application addresses the issues of energy dissipation and decreased biocompatibility of nanorobots under long-term, identical field conditions. The coarse-grained model determines the dynamic model of the nanorobot cluster, and the combination of the active particle environment and the dynamic model enhances energy dissipation. Because of the dynamic model, some of the decreased biocompatibility can be compensated for through structural control, and this reduction in biocompatibility further reduces energy dissipation through structural control.

[0013] In conjunction with the first aspect, the composite induced field is configured with active particle bath environment parameters of active particles and star chain structure parameters based on a coarse-grained model;

[0014] Among them, the environmental parameters of the active particle bath include active particle intensity parameters and particle density parameters;

[0015] The star chain structure parameters based on the coarse-grained model include: the number of branches, the range of branch bond length fluctuations, and the branch bond angles. Each branch is connected to a unique centroid node.

[0016] The spatial gradient distribution of the magnetic field component and the optical field component in the composite induced field, as well as the ratio of the distance between the branch ends and the gyroscope radius, are within the stability threshold of the star-shaped chain structure.

[0017] The composite induction field of this application is set by coordinating the environmental parameters of the active particle bath and the parameters of the star chain structure to solve the stability of the star chain structure and ensure sufficient assembly driving force, thereby preventing the random assembly of nanorobots. By correlating the spatial gradient of the magnetic field / light field with the stability threshold of the structural size, the deformation of the star chain is prevented.

[0018] In conjunction with the first aspect, step S2 also includes:

[0019] Based on the star-shaped chain structure, the periodic oscillations of the mean square displacement of the branches on the star-shaped chain relative to the centroid node are detected, and the first mapping relationship between the oscillation phase and the active particles is constructed; among them, the oscillation parameters of the periodic oscillations of the mean square displacement include the oscillation frequency and the oscillation amplitude.

[0020] Based on the first mapping relationship, the low-activity region and the high-activity region of the active particles are determined; among them, under the synchronous enhancement of the oscillating phase, the spatial gradient distribution values ​​of the magnetic field component and the optical field component change synchronously in the low-activity region and the high-activity region.

[0021] This application utilizes the low-activity and high-activity regions of active particles to control the phase-synchronous dynamic adjustment of the magnetic / optical field of the composite induced field in spatial gradient distribution, enabling multi-directional movement of star-shaped chain-structured nanorobot clusters.

[0022] In conjunction with the first aspect, the dynamic parameters include gyration radius, center of mass mobility, and branch extension.

[0023] This application utilizes dynamic parameters to control the composite induced field, enabling the overall motion and local structure to be matched.

[0024] In conjunction with the first aspect, the operation instructions include branch addition / deletion instructions, centroid node and branch bonding distance adjustment instructions, and star chain migration rate instructions.

[0025] In terms of operation instructions, this application uses three types of instructions to form multiple operation sets, thereby achieving multi-dimensional collaborative control.

[0026] In conjunction with the first aspect, when the star chain migration rate instruction is received in step S3, it includes:

[0027] Based on phase separation dynamics, the activity intensity threshold of active particles in the composite induced field is configured;

[0028] The critical optical power and critical magnetic field power density are determined based on the activity intensity threshold.

[0029] The migration path offset rate is determined by dynamically adjusting the long parameters of the critical optical power and critical magnetic field power density under the Granger causality test.

[0030] This application improves accuracy by using phase separation dynamics during the control of nanorobot cluster migration, and achieves critical setting by dynamically adjusting long parameters under Granger causality test for critical optical power and critical magnetic field power density, thereby preventing path deviation.

[0031] In conjunction with the first aspect, when the star chain migration rate instruction is received in step S3, the following further steps are also included:

[0032] Based on the star chain structure, a first driving mode and a second driving mode are configured for each branch in the star chain; wherein, the first driving mode is used to control the real-time update migration direction of active particles, and the second driving mode is used to configure the migration direction of active particles to be along the local tangent direction of the branch.

[0033] The real-time driving mode is dynamically determined by the proportion of the symmetry parameters of the first and second driving modes in the branches and centroid nodes.

[0034] This application employs two different driving modes and utilizes the symmetry parameters between the branches and the centroid node to automatically adjust the branches during overall direction control, thereby preventing conflicts between the overall star chain structure and the branch paths.

[0035] In conjunction with the first aspect, when the bonding distance adjustment command for the centroid node and the branch is received in step S3, it includes:

[0036] A pre-set threshold for the rotational diffusion coefficient of active particles is used to determine the activation of the shear-induced stretching mode and the activation of the collision-induced melting mode.

[0037] When the shear-induced stretching mode is activated, the composite induced field is configured with a hysteresis control region to alternately increase or decrease the optical field components. The rotational diffusion coefficient threshold is matched with the active particle density, and the bonding distance is controlled to be the target distance in the bonding distance adjustment command.

[0038] When the collision-induced melting mode is activated, the active particles linearly compensate for the diffusion pressure of the composite induced field.

[0039] This application distinguishes between shear-induced stretching mode and collision-induced melting mode by using a rotational diffusion coefficient threshold. These two bonding distance adjustment modes prevent nanorobot clusters from being stretched too much and breaking during migration, as well as from being stuck due to insufficient melting.

[0040] In conjunction with the first aspect, the control parameters include magnetic field control parameters, optical field control parameters, thermodynamic parameters of the active particle bath, bonding kinetics parameters of the nanorobot cluster, and synergistic control parameters;

[0041] Among them, the magnetic field control parameters include the magnetic field strength range, magnetic field gradient distribution, and magnetic field frequency range;

[0042] Optical field control parameters: optical field wavelength range, optical field power density, and optical spot positioning accuracy;

[0043] The thermodynamic parameters of the active particle bath are based on the active force intensity, particle density, and rotational diffusion coefficient of the active particles.

[0044] The bonding dynamics parameters of nanorobot clusters include the bonding temperature threshold and the hydrophilic-hydrophobic switching threshold.

[0045] The parameters for coordinated control include the magneto-optical coupling factor and the phase separation critical ratio.

[0046] This application controls the coupling relationship of multiple parameters, such as magnetic field control parameters, light field control parameters, thermodynamic parameters of active particle bath, bonding dynamics parameters of nanorobot clusters, and synergistic control parameters, to prevent drive mismatch, structural instability, and multi-field interference.

[0047] In conjunction with the first aspect, the target operation corresponding to the operation instruction in step S4 includes:

[0048] Based on the control parameters, a flexible boundary ratchet array is deployed in the star-shaped chain structure;

[0049] Based on the flexible boundary ratchet array, a pressure gradient and torque conversion model is constructed.

[0050] Based on the pressure gradient and torque conversion model, the nanorobot cluster is manipulated to generate laminar flow drive through the synchronous rotation of a flexible boundary ratchet array, enabling directional movement.

[0051] This application converts the synchronous motion of a nanorobot cluster into laminar flow drive by setting a flexible boundary ratchet array, which can adapt to the current environment and perform directional movement.

[0052] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0053] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0054] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0055] In the attached diagram:

[0056] Figure 1This is a flowchart of a method for manipulating a cluster of nanorobots based on an induced star-shaped chain, as described in an embodiment of the present invention.

[0057] Figure 2 This is a configuration diagram of the composite induced field in an embodiment of the present invention;

[0058] Figure 3 This is a mapping diagram of the star-shaped chain structure in an embodiment of the present invention;

[0059] Figure 4 This is a diagram showing the composition of dynamic parameters in an embodiment of the present invention;

[0060] Figure 5 This is a diagram showing the types of operation instructions in an embodiment of the present invention;

[0061] Figure 6 This is a diagram illustrating the calculation process of the chain migration rate in an embodiment of the present invention;

[0062] Figure 7 This is a diagram showing the driving mode settings in an embodiment of the present invention;

[0063] Figure 8 This is an embodiment diagram of the bonding distance adjustment command in this invention.

[0064] Figure 9 This is a scatter plot of the control parameters in an embodiment of the present invention. Detailed Implementation

[0065] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0066] Nanorobot manipulation technology is primarily used in the medical field, such as in targeted drug delivery and microsurgery. This application presents a high-precision nanorobot swarm manipulation method that combines chemical-driven and external field-driven approaches.

[0067] Traditional methods of manipulating nanorobot swarms involve controlling the magnetic field strength and polarity of the matrix-arranged magnetic field units during external field actuation. This alters the driving force, primarily the magnetic field force, to guide the nanorobots towards the target region. Another approach utilizes photocell reactions to propel nanorobots. In this method, the direction and wavelength of light, along with the cell itself, are adjusted to achieve multi-dimensional control of the nanorobots, enabling them to incorporate responses across different wavelength bands.

[0068] Example 1:

[0069] See Figure 1 This application proposes a method for manipulating nanorobot swarms based on induced star chains. The specific implementation process is as follows:

[0070] In step S1: A composite induction field for controlling the nanorobot cluster is pre-configured. This field drives the nanorobot cluster to assemble into a star-shaped chain structure using a coarse-grained model and an active particle environment. The coarse-grained model simplifies the molecular dynamics of the nanorobots and environmental particles, ignoring atomic-level details while retaining the particle's center of mass. Based on the nanorobot size, it defines the repulsive and attractive potential functions between particles, generating the coarse-grained model and reducing the computational complexity during nanorobot cluster assembly. The active particle environment combines the self-driving capability of the nanorobots with external driving capabilities, using light particles, magnetic particles, and chemically driven particles to achieve dynamic driving and guidance control. Its main function is to control the nanorobots to achieve automatic assembly. The resulting star-shaped chain structure contains multiple branch chains with adjustable branch chain lengths. In practical implementation, the central node of the star-shaped chain structure integrates a nanoscale microcontroller, and the branch nodes are constructed using carbon nanotubes, connecting molecular motors and drug delivery chambers, enabling its application in drug delivery in medical settings. The coarse-grained model uses a server terminal device to simulate a multimodal generator of an active particle environment. The multimodal generator has a magnetic field module and an optical drive module, which together form an alternating magnetic field that drives the nanorobot cluster.

[0071] In step S2, the dynamic parameters of the nanorobot cluster are determined based on the star-shaped chain structure. These dynamic parameters are parameters of the star-shaped chain's motion characteristics, including parameters of the central node and branch nodes, such as relative velocity, inter-node interaction forces, and the overall inertia and response delay of the cluster.

[0072] Step S3: Based on the dynamic parameters, upon receiving a manipulation command, the control parameters for the active particles in the composite induced field are generated. The mechanism for generating these control parameters in Step S3 utilizes the spatial asymmetry of the driving force of the active particles. Upon receiving a manipulation command, the direction mode of the active force is dynamically adjusted by analyzing in real time the expansion, contraction, or rotation of the conformational transition path required for the target operation, either along the contour tangent or randomly distributed, and the intensity gradient is adjusted. For example, when rapid directional motion is required, a tangential driving mode is used to enhance the cooperative propulsion force of the branches; while when structural stability is required, random directional driving is used to suppress local stress concentration. The control parameters are field control parameters used by the active particles themselves to control the magnetic field strength within the composite induced field in real time, driving the directional frequency changes of the nanorobot cluster to achieve precise manipulation.

[0073] Step S4: Based on the control parameters, control the star-shaped chain structure to execute the target operation corresponding to the operation command, and after completing the target operation, remove the composite induced field. The execution control of Step S4 relies on the phase transition coupling effect between active particles and the star-shaped chain. By adjusting the density of active particles and the driving force threshold, the rigid-to-flexible transition of the branches is triggered, causing the star-shaped chain to undergo controllable conformational reconstruction. For example, increasing the active force to a critical value can disrupt the equilibrium phase separation of the multi-chain system, and the local pressure gradient induced by active particles can drive the nanorobot cluster to complete the grasping or releasing operation. After the operation is completed, the composite induced field is removed to return the system to thermal equilibrium, and the initial configuration is restored through the relaxation process, realizing the reversibility of the operation. In the final removal process, a magnetic field detector can be used to monitor the residual field strength after the removal of the composite induced field to prevent the nanorobot cluster from moving automatically without control.

[0074] Because nanorobots lack dynamic parameters without a structure, this application first assembles a cluster of nanorobots into a star-shaped chain structure; obtains the dynamic parameters, and then uses the star-shaped chain structure to provide a potential function for optimizing the coarse-grained model of the composite induced field, determining the control parameters corresponding to the manipulation commands. In actual implementation, the control effect can also verify the accuracy of the dynamic parameters, i.e., the degree of completion of the manipulation commands.

[0075] Example 2:

[0076] See Figure 2 The composite induction field of this application is configured with active particle bath environment parameters and star chain structure parameters based on a coarse-grained model. In this application, there is a dynamic balance mechanism between the active particle bath and the star chain structure. By quantifying the key parameters in the composite induction field, the key parameters are adjusted and controlled, that is, by changing the particle density or intensity in the active particle bath environment, and combining the number of branches, bond length fluctuations, bond angles and centroid of the star chain structure, the composite induction field is controlled to drive the star chain structure to move according to the control command.

[0077] Among the environmental parameters of the active particle bath, the intensity of the active force controls the strength of the non-equilibrium driving force:

[0078] At low intensity, the active particles generate a thermal noise-like effect through random collisions, driving the nanorobots to fluctuate slightly.

[0079] At high strength, the directional driving force dominates, and the resulting shear stress field can overcome the spatial steric hindrance of the branches.

[0080] The particle density parameter can control the collision frequency of active particles and adjust the assembly efficiency. At low density, insufficient particle capture leads to loose star chain arms. At high density, the aggregation of active particles causes local pressure gradients, which control the contraction of the branches to maintain the topological stability of the centroid nodes.

[0081] Among them, the environmental parameters of the active particle bath include active particle intensity parameters and particle density parameters;

[0082] The star-shaped chain structure parameters based on the coarse-grained model include: the number of branches, the range of branch bond length fluctuations, and the branch bond angles. Each branch is connected to a unique centroid node. In this model, branches suppress thermal fluctuations through multi-arm synergy: the more branches there are, the greater the steric hindrance between arms, requiring higher reactive forces to trigger conformational transitions. The range of branch bond length fluctuations limits the stretching elasticity of the arms through bond potential energy functions, preventing bond breakage due to reactive particle impacts. The branch bond angles, combined with angular potential, regulate the chain's rigidity, resulting in semi-rigid branches. The competition between bending energy and reactive forces determines the cooperative motion mode of the arms. The centroid node, as the unique connection point of the branches, maintains the dynamic symmetry of the star topology through a concentrated energy dissipation path.

[0083] In this application, the spatial gradient distribution of the magnetic field component and the optical field component in the composite induced field, as well as the ratio of the branch end distance and the gyro radius, are within the stability threshold of the star-shaped chain structure.

[0084] By designing the magnetic and optical components of the composite induced field using spatial gradients, the ratio of the distance between the branch ends to the gyroradius is constrained, ensuring structural stability. The magnetic field gradient can regulate the motion direction of active particles, thereby aligning them along the tangential direction of the branches and improving the efficiency of driving force transmission. The optical field gradient regulates the density distribution of active particles through local thermal effects, thus suppressing disordered fluctuations at the branch ends. When a threshold is exceeded, the magnetic field gradient is automatically enhanced to compress the branch extension, or the optical field intensity is reduced to decrease particle aggregation pressure, maintaining the dynamic equilibrium of the star-shaped chain in a non-equilibrium state.

[0085] In this application, the active particle intensity parameter provides the basic driving force for star-shaped chain assembly, and combined with the number of branches, reduces the repulsive force between branches.

[0086] Example 3:

[0087] See Figure 3 Step S2 further includes:

[0088] Based on a star-shaped chain structure, this application detects the periodic oscillations of the mean square displacement of the branches on the star-shaped chain relative to the centroid node, and constructs a first mapping relationship between the oscillation phase and the active particles. The oscillation parameters of the periodic oscillations of the mean square displacement include the oscillation frequency and the oscillation amplitude. That is, by using the periodic characteristics of the mean square displacement oscillations, the frequency and amplitude parameters characterize the motion law of the star-shaped chain branches. The first mapping relationship is used to characterize the relationship between the oscillation phase and the distribution / driving ability of the active particles. When controlling the movement of the nanorobot cluster, it is possible to determine when to enhance or weaken the particle activity.

[0089] In detecting the periodic oscillation of mean square displacement between the branch and the centroid node, the oscillation frequency and amplitude are based on the non-equilibrium fluctuations caused by the collision of active particles: if the driving direction of the active particles can match the phase of the branch motion, the collision energy will be converted into periodic deformation through the elastic potential energy between the arms; if the driving direction and phase are misaligned, the energy dissipation will cause the amplitude to decay.

[0090] Based on the first mapping relationship, this application determines the low-activity region and the high-activity region of active particles; wherein, under the synchronous enhancement of the oscillating phase, the spatial gradient distribution values ​​of the magnetic field component and the optical field component of the low-activity region and the high-activity region change synchronously.

[0091] The division between low-activity and high-activity regions in this application relies on the energy transfer efficiency of the oscillation phase: if the oscillation phase is synchronously enhanced, the magnetic field gradient in the high-activity region will be enhanced, causing the active particles to align along the branch tangent direction, increasing the light field intensity to increase the local particle density and generate directional propulsion.

[0092] In the low-activity region, it is necessary to reduce the magnetic field gradient and light field intensity to suppress disordered fluctuations at the branch ends. The synchronous changes of the magnetic field and light field components will adjust the spatial gradient distribution value in real time, locking the extension-contraction period of the branches with the driving frequency of active particles, thus keeping the star-shaped chain structure in a dynamically stable state.

[0093] This application addresses the problems of poor structural stability caused by the asynchronous motion of active particles and star chain structure, as well as the static setting of field gradients, in traditional methods by considering three sequential aspects: sensing the dynamics of the star chain, matching drive, and optimizing field distribution.

[0094] Example 4:

[0095] See Figure 4 The dynamic parameters include gyroradius, centroid mobility, and branch extension.

[0096] The cyclotron radius in this application is determined based on the conformational fluctuation phenomenon caused by the collision of active particles.

[0097] If the activity force is enhanced, the branches will increase due to shear stretching. The corresponding centroid mobility is calculated by the time evolution slope of the centroid mean square displacement, and the overall translational diffusion ability of the star chain structure is enhanced.

[0098] The specific translational diffusion capability is influenced by both the density of active particles and the number of branches. The branch extension can regulate the bending stiffness through angular potential, and can be dynamically adjusted to maintain the coordinated movement of branches if it deviates from the target range.

[0099] The main purpose of this application is to quantify the dynamic characteristics through three dimensions: rotation, translation, and local structure, so as to prevent mismatch between the overall motion and the local structure.

[0100] Example 5:

[0101] See Figure 5 The operation instructions include instructions for adding or deleting branches, instructions for adjusting the bonding distance between centroid nodes and branches, and instructions for the migration rate of star chains.

[0102] When this application needs to add branches, it increases the density of active particles in the target area based on light field focusing, and drives nanorobots to self-assemble into new branches around the center of mass node by forming spatial steric hindrance through the repulsive force between particles.

[0103] If branch removal is required, a high-frequency pulsed magnetic field is applied to disrupt the bonding potential between the branch and the centroid node, reducing the local light intensity to induce the escape of active particles, resulting in the dissociation of the corresponding branch. Branch addition and deletion commands can adjust the drug loading to prevent drug blockage.

[0104] This application increases the magnetic field gradient when increasing the bonding distance, and then the active particles align along the branch axis to generate tensile force to constrain the bond length; when shortening the bonding distance, it enhances the photothermal effect and enhances the Brownian motion of the nanorobots. The nanorobots relax towards the center of mass node, control the bonding distance adjustment, and when the corresponding branch extends to release the drug, no structural breakage occurs.

[0105] In this application, the migration rate command relies on the intensity and density of active particles for nonlinear regulation, thereby controlling the migration rate. During accelerated migration, the hydrodynamic thrust generated by the collective motion of active particles enhances the centroid migration rate; if the migration is decelerated, the reverse optical field gradient can be reduced and introduced to counteract the active driving force, which is partially offset in actual implementation. The adjustment of the migration rate corresponds to the change in drug delivery speed, which can prevent collisions.

[0106] In general, adjusting chain length and bonding distance is mainly used in clinical drug delivery processes to ensure precise drug release and passage through different types of blood vessels.

[0107] Example 6:

[0108] See Figure 6 When the star chain migration rate command is received in step S3, it includes:

[0109] This application, based on phase separation kinetics, configures an activity intensity threshold for active particles in a composite induced field. This operation aims to prevent excessive concentration of active particles, either under driving force or under driving force dispersion, thereby improving the uniformity of the driving force and ensuring the overall structural stability of the star-shaped chain. Phase separation kinetics involves the phase separation of active particles and nanorobot clusters under repulsive and attractive interactions. This application maintains phase separation equilibrium by using active particles in a composite induced field with different concentration gradients around the nanorobot cluster. The activity intensity threshold represents the minimum driving force of the active particles.

[0110] In other words, when receiving a migration rate command, the activity intensity threshold is first set based on the phase separation critical condition of a multi-chain system like a star-chain structure. Based on the activity intensity threshold, the driving force relationship between the active particle driving energy and the phase separation free energy barrier is calculated, which is mainly a competitive relationship: thus, phase separation is suppressed, the activity intensity is reduced, and structural disintegration is prevented; conversely, the activity force needs to be enhanced to accelerate migration.

[0111] Based on the activity intensity threshold, the critical optical field power and critical magnetic field power density are determined. In this application, the critical optical field power (the minimum light intensity to maintain stable migration of the star-shaped chain) and critical magnetic field power density (the minimum magnetic field energy density to maintain stable migration) are used to optimize energy transfer efficiency. When setting the critical optical field power, the dynamic balance between the local heating rate of active particles and the heat dissipation rate of the system is satisfied to prevent thermal damage. When setting the critical magnetic field power density, the deviation angle between the particle motion direction and the migration path is small through the vector superposition of the Lorentz force and the activity force.

[0112] The migration path deviation rate is determined by dynamically adjusting long parameters based on the critical optical power and critical magnetic field power density under Granger causality testing. Time series analysis is used to extract the hysteresis coefficients of optical field intensity fluctuations and magnetic field gradient changes on the path deviation. During dynamic parameter adjustment, field components with higher causal weights are prioritized to stabilize the path deviation rate within the target range. In this application, the Granger causality test is used to determine whether the field parameters are Granger causes of the path deviation rate. The Granger causality test, also known as Granger causality monitoring, is a statistical method used to determine whether a causal relationship exists between two time series variables. In this application, the migration path deviation rate is determined by analyzing the path influence of critical optical power and critical magnetic field power density on a star-shaped chain structure of nanorobot clusters under time series analysis.

[0113] The above embodiments focus on monitoring the deviation of branch structures in complex structures such as star-shaped nanorobot clusters under the concentration gradient of active particles. This allows for the calculation of deviations from branch structures to the overall star-shaped structure, followed by path optimization. Traditional simple phase separation, however, is only applicable to linear structures. This embodiment primarily addresses the coupling conditions of optical and magnetic fields, rather than a single scenario. In the specific implementation, the critical field parameters are mainly determined through a blood flow shear force balancing experiment, comprehensively assessing the critical optical power and critical magnetic field power density corresponding to the driving force that counteracts the shear force.

[0114] Example 7:

[0115] See Figure 7 When the star chain migration rate instruction is received in step S3 of this application, the following is also included:

[0116] Based on a star-shaped chain structure, this application configures a first driving mode and a second driving mode for each branch in the star-shaped chain. The first driving mode is used to control the real-time update migration direction of active particles, and the second driving mode is used to configure the migration direction of active particles along the local tangent direction of the branch. In the first driving mode, the driving direction of active particles is updated synchronously with the global migration direction of the star-shaped chain to prevent the migration path of the star-shaped chain structure from deviating, and migration can be in a straight line or along a fixed route. In the second driving mode, the driving direction of active particles is along the tangent direction of the end of the branch to prevent collision with the blood vessel wall, and the branch can curl up and shrink.

[0117] In actual implementation, upon receiving the migration rate command, the weights of the first and second driving modes are dynamically allocated based on the symmetry parameters of the branches and the centroid node. The first driving mode achieves real-time matching between the direction of motion of the active particles and the external environmental resistance field through rapid redirection of the light / magnetic field.

[0118] The real-time driving mode is dynamically determined based on the proportion of symmetry parameters of the first and second driving modes in the branches and centroid nodes. The symmetry parameter represents the angular symmetry between the branch and the centroid. When the two modes are combined, the global mode is prioritized when the symmetry is high, and the local mode is prioritized when the symmetry is low. This prevents asymmetrical branch offsets in the global mode and uncontrolled offsets of the overall star-shaped chain structure in the local mode.

[0119] Example 8:

[0120] See Figure 8 When the bonding distance adjustment command for the centroid node and the branch is received in step S3, it includes:

[0121] A pre-set threshold for the rotational diffusion coefficient of active particles is used to determine the activation of shear-induced stretching mode and the activation of collision-induced melting mode. Upon receiving a bonding distance adjustment command, this application sets a threshold based on the matching relationship between the active particle density and the rotational diffusion coefficient: the threshold is calculated by subtracting the rotational motion intensity corresponding to the diffusion rate of the active particles rotating around their center of mass, defining when stretching and melting are required. The shear-induced stretching mode is characterized by generating shear force through alternating increases and decreases in the light field, uniformly stretching the bonding distance and preventing bond breakage. During precise control, uneven stretching caused by different operating methods is avoided.

[0122] This application activates the shear-induced stretching mode at a low rotational diffusion coefficient, where the orientation persistence of active particles is high. Then, based on the alternating increase and decrease of the optical field components in the composite induced field, a hysteresis control region is formed around the centroid node.

[0123] Within this region, alternating light fields induce periodic collisions of varying intensity among active particles, generating a shear stress gradient that drives the branches to gradually extend along the stretching direction until the bonding distance reaches the target value. Overall, this avoids the breakage of the star-shaped chain structure during precise control.

[0124] When the shear-induced stretching mode is activated, the hysteresis control region configured by the composite induced field is used to alternately increase or decrease the optical field components, thereby matching the rotational diffusion coefficient threshold with the active particle density and controlling the bonding distance to the target distance in the bonding distance adjustment command.

[0125] When the collision-induced melting mode is activated, the active particles linearly compensate for the diffusion pressure of the composite induced field.

[0126] Due to the characteristics of active particles, disordered collision energy accumulates under rapid random turning. The collision-induced melting mode of this application counteracts the local melting effect by linearly compensating for diffusion pressure: if the potential energy fluctuation of the branched bond exceeds the threshold, the magnetic field constraint force is enhanced, so that the disordered collision energy is converted into directional thermal diffusion flow, suppressing the risk of bond breakage.

[0127] Meanwhile, the light field power is adjusted in the opposite direction according to the density of active particles to prevent structural collapse caused by local overheating. In the drug delivery environment, it can solve the technical problem that the branches cannot pass through the capillaries due to adhesion when the branches are shortened.

[0128] Example 9:

[0129] See Figure 9 The control parameters include magnetic field control parameters, optical field control parameters, thermodynamic parameters of active particle bath, bonding kinetics parameters of nanorobot clusters, and synergistic control parameters.

[0130] Among them, the magnetic field control parameters include the magnetic field strength range, magnetic field gradient distribution, and magnetic field frequency range;

[0131] Optical field control parameters: optical field wavelength range, optical field power density, and optical spot positioning accuracy;

[0132] The thermodynamic parameters of the active particle bath are based on the active force intensity, particle density, and rotational diffusion coefficient of the active particles.

[0133] The bonding dynamics parameters of nanorobot clusters include the bonding temperature threshold and the hydrophilic-hydrophobic switching threshold.

[0134] The parameters for coordinated control include the magneto-optical coupling factor and the phase separation critical ratio.

[0135] In this application, the control parameters are primarily aimed at achieving precise controlled migration, such as drug delivery, through the synergy of magnetic field, optical field, thermodynamics, bonding kinetics, and the integrated star-shaped chain structure of nanorobots. Therefore, in the magnetic field control parameters, the magnetic field strength range in this application constrains the motion direction of active particles through Lorentz force, while the gradient distribution dynamically matches the end-to-end distance of the star-shaped chain branches, generating directional tensile force.

[0136] The magnetic field frequency range set in this application controls the inertia of active particles and suppresses the instability of the star-shaped chain structure under high-frequency oscillations through the relaxation effect of the alternating magnetic field. The optical field modulation parameters in this application, with a wavelength range matched to the absorption spectrum of the photothermal conversion material of the nanorobot, enable local energy focusing.

[0137] The optical power density of this application is mainly controlled by the photophoretic force and photothermal expansion effect to control the propulsion intensity of active particles, while the spot positioning accuracy is achieved by using spatial light modulation technology to control the selective activation of the branch ends of the star-shaped chain structure.

[0138] The thermodynamic parameters of the active particle bath in this application are based on the dynamic balance between the activity intensity and the rotational diffusion coefficient, controlling the star-shaped chain structure to execute a non-equilibrium driving mode:

[0139] At low Dr, the orientation of active particles is enhanced, resulting in shear-induced stretching;

[0140] At high Dr, a collision melting effect is triggered.

[0141] Particle density, through the synergy of spatial distribution entropy and activity force, determines the critical conditions for phase separation.

[0142] In the bonding kinetic parameters of this application, the bonding temperature threshold is based on photothermal triggering of hydrophilicity / hydrophobicity switching, which induces selective adhesion or dissociation of different nanorobots in the nanorobot cluster in the target region.

[0143] In the synergistic control parameters of this application, the magneto-optical coupling factor quantifies the interaction effect between the magnetic field gradient and the optical field power, and controls the vector superposition effect of tensile force and thermal expansion stress.

[0144] The phase separation critical ratio, controlled by the ratio of the Flory-Huggins parameter to the activity force, regulates the assembly stability threshold of the multi-chain system. The Flory-Huggins parameter is a key parameter in polymer solution theory used to quantify the interaction between polymers and solvents. In this application, it is a key parameter characterizing the interaction between nanorobot clusters and the composite induced field, representing the strength of the interaction force.

[0145] This application addresses the issue of drug delivery failure caused by adhesion by combining various parameters in the control parameters, thereby enabling the precise migration of star-shaped chain structures in the blood.

[0146] Example 10:

[0147] Step S4 involves executing the target operation corresponding to the operation instruction, including:

[0148] Based on the control parameters, a flexible boundary ratchet array is deployed in the star-shaped chain structure;

[0149] Based on the flexible boundary ratchet array, a pressure gradient and torque conversion model is constructed.

[0150] Based on the pressure gradient and torque conversion model, the nanorobot cluster is manipulated to generate laminar flow drive through the synchronous rotation of a flexible boundary ratchet array, enabling directional movement.

[0151] In this application, the flexible boundary ratchet array is an array composed of deformable micropillars. The tips of the micropillars are serrated and can deform with fluid pressure. In this application, its deployment is based on the non-uniform pressure distribution of the active particle bath. By adjusting the magnetic field gradient and optical power density in the parameters, this application constructs an asymmetric geometric flexible boundary ratchet array based on a periodic curvature distribution at the end of the star-shaped chain branches. The flexible boundary ratchet array includes multiple ratchet units. The flexible boundary curvature of each ratchet unit matches the rotational diffusion coefficient of the active particles.

[0152] In this application, the pressure gradient and torque conversion model is based on the spatiotemporal correlation of active particle collisions. The pressure gradient is the rate of change of pressure of active particles in the fluid, i.e., the composite induced field of this application, with respect to spatial position. The torque conversion model is a microscopic calculation model of the rotational torque of the star-shaped chain: this application calculates the net pressure gradient and maps it to the equivalent torque by statistically analyzing the spatiotemporal distribution of collision events on the ratchet surface. If multiple ratchet units are arranged at equal intervals along the circumference of the star-shaped chain, their synchronous rotation generates a laminar shear field through hydrodynamic coupling, producing an overall propulsive force. The directional movement of the star-shaped chain structure is controlled by adjusting the magneto-optical coupling factor to execute the movement. By enhancing the constraint of the magnetic field on the ratchet arrangement and guiding the laminar flow direction through the optical field gradient, the nanorobot cluster moves along a preset path. Through the above steps, the problem of rigid structure jamming caused by irregular blood vessel walls can be solved during drug delivery. The laminar flow-driven approach addresses the nanorobot misalignment phenomenon caused by blood flow interference.

[0153] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for manipulating a cluster of nanorobots based on an induced star-shaped chain, characterized in that, include: Step S1: Pre-configure a composite induction field controlled by a cluster of nanorobots; wherein, the composite induction field drives the nanorobot cluster to assemble into a star-shaped chain structure through a coarse-grained model and an active particle environment; Step S2: Determine the dynamic parameters of the nanorobot cluster based on the star-shaped chain structure; Step S3: Based on the dynamic parameters, upon receiving the control command, generate the control parameters for the active particles in the composite induced field; Step S4: According to the control parameters, control the star chain structure to execute the target operation corresponding to the operation command, and after the target operation is completed, cancel the composite induction field; The composite induction field is configured with active particle bath environment parameters for active particles and star chain structure parameters based on a coarse-grained model. Among them, the environmental parameters of the active particle bath include active particle intensity parameters and particle density parameters; The star chain structure parameters based on the coarse-grained model include: the number of branches, the range of branch bond length fluctuations, and the branch bond angles. Each branch is connected to a unique centroid node. The spatial gradient distribution of the magnetic field component and the optical field component in the composite induced field is within the stability threshold of the star-shaped chain structure, as are the ratios of the branch end distance and the gyro radius. The kinetic parameters include gyration radius, center of mass mobility, and branch extension. The control parameters include magnetic field control parameters, optical field control parameters, active particle bath thermodynamic parameters, nanorobot cluster bonding kinetics parameters, and synergistic control parameters. Among them, the magnetic field control parameters include the magnetic field strength range, magnetic field gradient distribution, and magnetic field frequency range; Optical field control parameters: optical field wavelength range, optical field power density, and optical spot positioning accuracy; The thermodynamic parameters of the active particle bath are based on the active force intensity, particle density, and rotational diffusion coefficient of the active particles. The bonding dynamics parameters of nanorobot clusters include the bonding temperature threshold and the hydrophilic-hydrophobic switching threshold. The parameters for coordinated control include the magneto-optical coupling factor and the phase separation critical ratio.

2. The method for manipulating a cluster of nanorobots based on an induced star-shaped chain as described in claim 1, characterized in that, Step S2 further includes: Based on the star-shaped chain structure, the periodic oscillations of the mean square displacement of the branches on the star-shaped chain relative to the centroid node are detected, and the first mapping relationship between the oscillation phase and the active particles is constructed; among them, the oscillation parameters of the periodic oscillations of the mean square displacement include the oscillation frequency and the oscillation amplitude. Based on the first mapping relationship, the low-activity region and the high-activity region of the active particles are determined; among them, under the synchronous enhancement of the oscillating phase, the spatial gradient distribution values ​​of the magnetic field component and the optical field component change synchronously in the low-activity region and the high-activity region.

3. The method for manipulating a cluster of nanorobots based on an induced star-shaped chain as described in claim 1, characterized in that, The operation instructions include instructions for adding or deleting branches, instructions for adjusting the bonding distance between centroid nodes and branches, and instructions for the migration rate of star chains.

4. The method for manipulating a cluster of nanorobots based on an induced star-shaped chain as described in claim 3, characterized in that, When the star chain migration rate command is received in step S3, it includes: Based on phase separation dynamics, the activity intensity threshold of active particles in the composite induced field is configured; The critical optical power and critical magnetic field power density are determined based on the activity intensity threshold. The migration path offset rate is determined by dynamically adjusting the long parameters of the critical optical power and critical magnetic field power density under the Granger causality test.

5. The method for manipulating a cluster of nanorobots based on an induced star-shaped chain as described in claim 3, characterized in that, When the star chain migration rate command is received in step S3, the method further includes: Based on the star chain structure, a first driving mode and a second driving mode are configured for each branch in the star chain; wherein, the first driving mode is used to control the real-time update migration direction of active particles, and the second driving mode is used to configure the migration direction of active particles to be along the local tangent direction of the branch. The real-time driving mode is dynamically determined based on the proportion of the symmetry parameters of the first and second driving modes in the branches and centroid nodes.

6. The method for manipulating a cluster of nanorobots based on an induced star-shaped chain as described in claim 3, characterized in that, When the bonding distance adjustment command for the centroid node and the branch is received in step S3, it includes: A pre-set threshold for the rotational diffusion coefficient of active particles is used to determine the activation of the shear-induced stretching mode and the activation of the collision-induced melting mode. When the shear-induced stretching mode is activated, the composite induced field is configured with a hysteresis control region to alternately increase or decrease the optical field components. The rotational diffusion coefficient threshold is matched with the active particle density, and the bonding distance is controlled to be the target distance in the bonding distance adjustment command. When the collision-induced melting mode is activated, the active particles linearly compensate for the diffusion pressure of the composite induced field.

7. The method for manipulating a cluster of nanorobots based on an induced star-shaped chain as described in claim 1, characterized in that, The target operation corresponding to the operation instruction in step S4 includes: Based on the control parameters, a flexible boundary ratchet array is deployed in the star-shaped chain structure; Based on the flexible boundary ratchet array, a pressure gradient and torque conversion model is constructed. Based on the pressure gradient and torque conversion model, the nanorobot cluster is manipulated to generate laminar flow drive through the synchronous rotation of a flexible boundary ratchet array, enabling directional movement.

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