465 results about "Electronic structure" patented technology

The invention discloses a method and a system for determining the reaction activity of material molecules based on quantum computing, and relates to the technical field of material performance analysis based on quantum computing, and the method comprises the following steps: generating UCCSD (Unified Conduction Cathode Spectroscopy) simulation according to an electronic structure of molecules of a target material; obtaining at least one effective excitation operator based on parameters in the coefficient of each excitation operator in UCCSD simulation and by combining all the excitation operators; constructing a quantum circuit according to all the effective excitation operators; determining energy level distribution of molecules of the target material based on the quantum circuit; and determining the reaction activity of the molecules of the target material according to the energy level distribution of the molecules of the target material. According to the method, in the process of obtaining the effective excitation operator, an ADAPT-VQE algorithm does not need to be executed, so that the analysis cost of the physical and chemical properties of the material can be reduced, and the analysis efficiency of the physical and chemical properties of the material can also be improved.

The invention pertains to quantum computing. Specifically, the invention refers to a computer-implemented method for finding the ground state of a molecule with a quantum processor by using a quantum-classical Variational Quantum Eigensolver (VQE) method with the ground state corresponding to a Hamiltonian of the molecule, the quantum processor comprising a predetermined quantum circuit for producing trial quantum states for the Hamiltonian operator, said predetermined quantum circuit comprising at least parametric quantum gates associated with one or more parameters to be optimized, the method comprising: - providing an initial and final Hamilton operator, building up a pool of generators to construct an Ansatz of parametrized entanglers for the quantum circuit, and - applying the quantum-classical VQE method to optimize the values of the parameters for finding the ground state of the Hamiltonian.

Nanomaterials and methods of preparation and use thereof, are disclosed. The nanomaterials include a non-noble metal substrate and noble metal atoms on a surface of the non-noble metal substrate. The noble metal atoms simultaneously coordinate with a halogen and oxygen. The substrate has a large specific surface area and a large electrochemical active area, and the surface coordination environment of the noble metal affects the electronic structure and catalytic activity of a resulting catalyst. The noble metal surface coordination structure may be regulated and controlled by a synthesis temperature, an alkalinity, a reaction time, and an electrodeposition voltage range. A hydroxide ion and the halogen coordinate with the noble metal, exhibiting an unsaturated pentacoordinate state. Doping the substrate with reducing metal ions may increase the loading capacity, anchor the noble metal atoms, and improve anodic oxygen evolution and cathodic hydrogen evolution in seawater electrolysis.

The invention discloses a construction method of a TiH binary system machine learning potential. The construction method comprises the following steps: constructing a reference electronic structure data set by adopting first principle calculation software VASP; training and testing an artificial neural network potential-ANN potential model on the reference data set by using the artificial neural network model; vASP and ANN potential obtained through training are used for calculating and comparing a Dimer curve, a lattice constant, an elastic modulus and the like for performance testing; and performing targeted improvement on data with large comparison error between the ANN model and the DFT result in model test and performance test results by increasing related configuration weights until an ANN potential model conforming to the precision is obtained. The machine learning potential model constructed by the invention can better fit the interatomic interaction potential energy surface of the TiH binary system, solves the problems of small time-space scale and low precision of the traditional empirical potential in the calculation of the first principle, and provides a technical basis for the high-precision and large-size simulation and research of the TiH binary system.

Provided are computer-implemented methods and quantum computing systems for preparing computational states representing quantum states of a physical system, including performing a computational evolution of the state and then determining physical properties of the system using the time-evolved computational state. Hamiltonian dynamics of observables are computed on a quantum computer to provide information about the physical system represented by the Hamiltonian. Low energy electronic structure states of a physical system are prepared using adiabatic evolution. The energy of an equilibrium quantum state of a physical system is determined using a time-evolution operator. The energy of an eigenstate of a physical system is indirectly determined by evaluating expectation values of a time-evolution operator averaged across multiple shots for randomly-generated quantum circuits. Example methods enable calculation of the energy of an evolved computational state with chemical accuracy, due to avoiding discretization errors, with a smaller circuit depth than known alternatives.

The invention discloses a method and system for determining the reaction activity of material molecules based on quantum computing, and relates to the technical field of material performance analysis based on quantum computing, and the method comprises the following steps: generating UCCSD (Unified Conduction Cancellation Standard Description) simulation containing a plurality of excitation operators according to the electronic structure of a target material molecule; constructing a quantum circuit based on all the excitation operators; when the ground state energy is calculated by using the VQE algorithm, initially setting each parameter as zero in the first calculation, calculating the current gradient of each parameter, updating the parameter value according to the gradient, and iterating until all gradients are zero to obtain the ground state energy; and finally determining the reaction activity of the molecules according to the ground state energy. According to the method, the initial parameter is set to be zero, the gradient calculation complexity is reduced by using the excitation operator ease relation, and measurement of a large number of expected values is avoided. And the line is directly constructed based on UCCSD, and bubble-string conversion and graph coloring preprocessing are not needed, so that the calculation overhead is reduced.

The present invention relates to a method for calculating an electronic structure of a material by using quantum computing. Particularly, the method of the present invention for calculating an electronic structure of a material performed linking a quantum computer and a classical computer, may comprise the steps of: fragmenting a target molecule into fragments of a plurality of monomers having a predetermined positional relation; performing a first VQE routine for performing a Hamiltonian matrix calculation for the plurality of monomers on the basis of a calculation of electron density for the plurality of monomers, inputting modified electron density, and repeating the first VQE routine performing the Hamiltonian matrix calculation until the modified electron density according to the Hamiltonian matrix by the result of the first VQE routine converges; and performing a second VQE routine for performing a Hamiltonian matrix calculation on one or more dimers consisting of two monomer pairs of the plurality of monomers.

The invention discloses a preparation method of a negative electrode material of a sodium ion battery, a negative electrode plate containing the negative electrode material and the sodium ion battery, and the negative electrode material is prepared by taking biomass waste semen cassiae as a carbon precursor and montmorillonite as a template and combining an in-situ fluorine ion exchange and carbonization process. The preparation method comprises the following steps: mixing semen cassiae with montmorillonite, removing a template, and carrying out fluorine ion exchange to obtain the fluorine-doped three-dimensional porous carbon composite material. According to the material, micro / mesopore distribution is regulated and controlled through a confinement effect between montmorillonite layers, uniform doping of fluorine elements is realized, and an electronic structure and a pore channel system are synergistically optimized. The composite material has rich sodium storage active sites, efficient ion / electron transmission paths and stable interface characteristics, can significantly improve the specific capacity, rate capability and cycle life of the sodium-ion battery, and has important application value in the field of sodium-ion battery negative electrode materials.

The invention discloses a density matrix energy and atom stress calculation method, a local density matrix DM and an energy density matrix EDM of a target material structure are predicted through a machine learning model such as a HamGNN-DM model, the atom stress of the material structure is calculated, and the calculation amount of the whole process is in direct proportion to the number of atoms contained in the material structure. The atom stress of the obtained material structure is used for molecular dynamics simulation of the material structure, and meanwhile, the electronic structure property of the material in the molecular dynamics simulation process can be efficiently obtained. The HamGNN-DM model is based on a graph neural network, but can be based on any machine learning model, and is not limited to the graph neural network.

The invention relates to a cathode material of a medium-temperature solid oxide fuel cell as well as a preparation method and application thereof, and belongs to the technical field of fuel cells. The cathode material comprises a cathode material body and a doped coating layer, the cathode material body comprises a perovskite material, and the doped coating layer material comprises platinum; by doping and coating platinum on the surface of the cathode material body, the electronic structure of the material surface is improved, the electronic conductivity is improved, and the transmission of electrons on the surface is smoother. Platinum provides a large number of efficient oxygen reduction reaction active sites on the surface of the cathode material body, and platinum has a unique electronic structure, so that the adsorption and dissociation processes of oxygen molecules can be greatly accelerated, the activation energy of the oxygen reduction reaction is remarkably reduced, and the catalytic activity of the whole cathode material is greatly improved. And meanwhile, platinum on the surface of the cathode material body forms a stable protection layer in a medium-temperature environment, so that the problems of oxidation, corrosion and the like on the surface of the material are effectively prevented, the chemical and structural stability of the surface is maintained, and the service life of the material is prolonged.

Disclosed herein are microelectronic structures including bridges, and related assemblies and methods. In some embodiments, a microelectronic structure may include a substrate with first and second metal layers; a cavity in the substrate, where a portion of the first and second metal layers, are exposed with the portion of the first metal layer partially overlapping the portion of the second metal layer; and a bridge component in the cavity, having a first conductive contact at a first face and a second conductive contact at a second face opposing the first face, the second face towards a bottom surface of the cavity, the portion of the first metal layer is between the second face of the bridge component and the portion of the second metal layer, and the second conductive contact is electrically coupled to the portion of the second metal layer in the cavity.

The invention provides a luminescent material containing a cyclobutadiene structure, and a preparation method and application thereof, and relates to the technical field of organic electroluminescent materials. According to the cyclobutadiene-containing luminescent material provided by the invention, the anti-aromatic cyclobutadiene is fused into a binary nitrogen-containing fused heterocyclic skeleton, and excitation state vibration relaxation is inhibited by using the special electronic structure and high ring tension of the anti-aromatic cyclobutadiene, so that narrow-band luminescence is realized. By introducing the steric hindrance effect group, the aggregation fluorescence quenching phenomenon between luminescent parent nuclei is weakened, and the fluorescence quantum yield is improved. Different from a current mainstream multi-resonance mechanism, the design of the narrow-spectrum light-emitting molecule provided by the invention does not need to depend on the construction of a B / N-fused ring, and the molecular structure can be simplified to realize full-light-color ultra-narrow-band light emission. When the organic light-emitting diode is applied to an organic light-emitting device, an ultra-narrow full-width-at-half-peak electroluminescent spectrum and high device efficiency can be realized, and a better solution is provided for an ultra-high-definition organic light-emitting diode display technology.

The invention provides a computer cross-scale integrated analysis method based on a multi-physics field coupling mechanism, and the method comprises the steps: constructing a multi-level finite element model from a system level to a micro-area level, and integrating thermal-mechanical-electric coupling modeling; therefore, the technical problems that in a traditional method, multi-physics field coupling lacks, local area modeling is not fine, and electrical performance evolution is not introduced are solved, high-precision simulation of a typical device failure mechanism is achieved, and the method is suitable for device packaging reliability evaluation in special electronic systems such as military and high-reliability civil use and the like. The method can be widely popularized in microelectronic structures such as a power supply module, a processor and a memory, and can improve the evaluation precision of the high-frequency signal transmission performance of complex electronic equipment, thereby improving the precision of predicting the service life.

The invention discloses a mining intrinsic safety type steel wire rope non-contact magnetization detection integrated device, which relates to the technical field of steel wire rope magnetization sensor detection, and comprises a first detector shell, a second detector shell, a first permanent magnet, a second permanent magnet and two magnetic sensors, the first detector shells and the second detector shells are arranged in pairs, and the edges of the same sides of the first detector shells and the second detector shells are connected; according to the invention, the splitting of the two detector shells is not influenced, the steel wire rope can be easily put into any section of position of the steel wire rope, the magnetic field of the permanent magnet can still magnetize the steel wire rope when the steel wire rope is closed, and the position of the fixed wheel can be changed according to the diameter of the steel wire rope, so that the axis of the steel wire rope is located in the middle of the middle shield; the influence of the magnetic field on the steel wire rope or the electronic structure difference of the detected steel wire rope is consistent, and the accuracy of detecting the internal damage of the steel wire rope by the magnetic sensor is improved.

The invention discloses a Ce-doped CoP / NiCoP-coated NM self-supporting structure electrode and a preparation method and application thereof, the electrode takes a pretreated nickel net as a conductive substrate, a two-step method combining pulse electrodeposition and constant potential deposition is adopted, a compact NiCoP bottom layer and a Ce-doped CoP outer layer are constructed in sequence, and a CoP / NiCoP heterojunction structure with a three-dimensional coralline open morphology is formed. The method is mild in process, green, simple and convenient, and a traditional high-temperature phosphating step is abandoned. The prepared self-supporting electrode combines the charge regulation advantage of a heterojunction interface, the Ce-doped electronic structure optimization effect and the mass transfer advantage of a three-dimensional porous structure, so that the self-supporting electrode has extremely high hydrogen evolution catalytic activity, strong bonding force with a substrate and excellent long-period operation stability.

The invention discloses a spheroidal graphite cast iron wear resistance evaluation, regulation and control method based on an electronic work function, and relates to the technical field of surface engineering and performance evaluation.The method comprises the steps that electronic work function data and material characteristic data of the surface of spheroidal graphite cast iron are collected; extracting features of the electronic work function data to obtain electronic work function features; based on the electronic work function characteristics, establishing a mathematical model to analyze the correlation between the electronic work function data and the material characteristic data; and analyzing the relationship between the electronic work function characteristics and the wear resistance, and establishing a comprehensive evaluation model to evaluate the wear resistance of the nodular cast iron. The characterization technology, the complex data analysis method and the multivariate statistical model are combined at the same time, the relation between the electronic structure and the macroscopic performance of the material can be deeply understood, and a comprehensive evaluation model is established to predict the wear resistance of the nodular cast iron; the method guides the design of materials and the optimization of the production process.

The invention relates to the technical field of semiconductor materials, and discloses a Si-doped epsilon-Ga2O3 material with high conductivity and deep ultraviolet light absorption performance and a preparation method, the doping concentration of Si in the Si-doped epsilon-Ga2O3 material is 0.83 at%-2.5 at%, and Si atoms replace tetrahedral coordinated Ga (1) atoms in epsilon-Ga2O3. By accurately controlling the Si doping concentration to be 0.83-2.5 at% and enabling Si atoms to replace tetrahedral coordinated Ga (1) atoms in epsilon-Ga2O3, the electronic structure of the material is effectively improved, the Fermi level moves upwards to enter a conduction band after Si doping, and Si3s orbital electrons occupy the conduction band bottom (CBM), so that the carrier concentration is increased, the effective mass of the electrons is reduced, and the conductivity of the material is remarkably improved; tests show that compared with an intrinsic epsilon-Ga2O3 material, the conductivity of the doped material is improved by 1-3 orders of magnitude, strict requirements of high-power electronic components and the like on the conductivity of the material are met, heat loss of the electronic components due to resistance is reduced, and the working efficiency and stability of the components are improved.

The invention belongs to the technical field of batteries, and particularly relates to a doped phosphate positive electrode material and a preparation method and application thereof. The doped phosphate positive electrode material comprises a phosphate active material and a doped metal element doped in a crystal structure of the phosphate active material; according to the doped phosphate positive electrode material, under the condition that the pressure is 100-500 MPa, the maximum deformation quantity of particles is smaller than 50%, and the reversible deformation quantity is smaller than 10%. By doping the metal elements in the crystal structure of the phosphate-based active material, the structure of the doped phosphate-based positive electrode material is optimized, the structural stability of the doped phosphate-based positive electrode material is improved, the compression modulus of the positive electrode material is improved, and meanwhile, the chemical components and the electronic structure of the surface of the positive electrode material can be changed; therefore, the doped phosphate positive electrode material has the characteristics of relatively high ionic conductivity, electron conductivity, gram volume, cycling stability and the like.

Provided are computer-implemented methods and quantum computing systems for preparing computational states representing quantum states of a physical system, including performing a computational evolution of the state and then determining physical properties of the system using the time-evolved computational state. A described computer-implemented method enables computing Hamiltonian dynamics of observables on a quantum computer to provide information about the physical system represented by the Hamiltonian. A described computer-implemented method prepares low energy electronic structure states of a physical system using adiabatic evolution. The method determines the energy of an equilibrium quantum state of a physical system using a time evolution operator that enables adiabatic evolution of a prepared electronic structure state on a quantum computing system. A described method involves indirectly determining the energy of an eigenstate of a physical system by evaluating the expectation values of a time-evolution operator averaged across multiple shots for randomly-generated quantum circuits.

The invention relates to a nitrogen-containing bowl-shaped conjugated pH-responsive fluorescent probe and a preparation method and application thereof, the nitrogen-containing bowl-shaped conjugated pH-responsive fluorescent probe is characterized in that the structural formula of the nitrogen-containing bowl-shaped conjugated pH-responsive fluorescent probe is # imgabs0 #, and R is hydrogen, acetyl or p-toluenesulfonyl. Compared with the prior art, the nitrogen-containing bowl-shaped conjugated molecule provided by the invention shows a highly sensitive response characteristic in an acid-base medium. Due to the introduction of nitrogen atoms, the electronic structure of molecules is obviously changed, lone pair electrons of the nitrogen atoms can participate in the reaction, and the protonation behavior is obvious under the acidic condition. After protonation, the fluorescence intensity of the molecule is obviously enhanced, and the emission wavelength has obvious red shift, so that the probe has important application value in the aspect of developing a high-sensitivity acid-base sensor. In addition, the nitrogen-containing polycyclic aromatic hydrocarbon compound also shows application prospects in the fields of organic light-emitting diodes, information safety, biological imaging and the like.

The invention relates to the technical field of material science, and discloses a method for constructing a density functional tight constraint-neural network hybrid potential function, and the method comprises the steps: obtaining structure parameters of a target material sample in a data set through a constructed density functional theory data set; calculating energy, atomization energy and stress data of an electronic structure corresponding to the sample configuration based on a density functional theory; calculating band structure energy and stress of a target material sample in the density functional theory data set based on a density functional tight constraint theory, and obtaining corresponding density functional tight constraint atomization energy; calculating repulsion energy and repulsion stress of each sample configuration according to each atomization energy and the corresponding stress data; and constructing an atomic neural network potential function, and combining the atomic neural network potential function with a density functional tight constraint theory to generate a hybrid potential function. According to the method, the DFTB method and the machine learning technology are combined, the precision and the mobility of the potential function are greatly improved, and meanwhile, the calculation efficiency is remarkably improved.

The invention discloses a flexible substrate material doped with a two-dimensional material and a preparation method of a sensor of the flexible substrate material, and belongs to the technical field of array sensors. The electrode material comprises a two-dimensional material substrate, a composite doping atom layer and an insulation isolation layer, high-density defect sites are formed through H2 plasma processing, uniform distribution of doping atoms is achieved in combination with atomic layer deposition, and an electrode and a temperature-sensitive layer are precisely integrated through the self-alignment photoetching technology. According to the scheme, the electronic structure of the two-dimensional material is optimized through the composite doping synergistic effect, the multi-layer heterojunction design and the high-precision preparation process are combined, the response capacity of the electrode to weak pressure signals is remarkably improved, and high resolution and stability of the sensor in pressure and temperature detection are achieved. The method has a wide application prospect in the fields of wearable equipment, medical monitoring, robot tactile perception and the like.

The invention discloses a material physical property calculation and simulation method and system based on a first principle, and relates to the field of material physical property calculation and simulation, and the method comprises the following operation steps: S1, atomic-scale structure modeling and initial parameter setting; s2, structure optimization and energy minimization are carried out; s3, electronic structure calculation and intrinsic physical property extraction; s4, performing multi-scale coupling and mesostructure simulation; s5, simulating a multi-physics coupling process; s6, data-driven intelligent optimization is carried out; s7, carrying out multi-dimensional visual verification and interaction; and S8, carrying out full life cycle model iteration and knowledge base construction. According to the material physical property calculation and simulation method and system based on the first principle, full-process simulation from an atomic scale to a macroscopic material is achieved, atomic-scale structure modeling, multi-scale coupling and macroscopic process simulation are covered, physical properties and behaviors of the material under different scales can be deeply revealed, and the material physical property calculation and simulation method and system based on the first principle are provided for the purpose of improving the material physical property calculation and simulation efficiency. And more complete and accurate information can be provided for material design and process optimization.

The invention discloses an injection molding method and an injection molding device for a vehicle-mounted electronic structural member, and the method comprises the following steps: applying an excitation light source to obtain a polarization emission spectrum of engineering plastic, and forming a quantum optical fingerprint spectrum; carrying out polarization analysis on the spectral characteristic peak, and calculating a dichroic ratio to obtain molecular orientation three-dimensional distribution data; applying a laser pulse to acquire a coherent Raman scattering signal and a harmonic generation signal to obtain nonlinear optical response data; analyzing a molecular chain rearrangement characteristic and a stress relaxation characteristic based on the data to obtain kinetic parameters; and analyzing a molecular orientation evolution rule according to the kinetic parameters to obtain structure evolution prediction data. According to the technical scheme, the molecular orientation state of the engineering plastic can be monitored in real time in the injection molding process, and accurate characterization and prediction of the dynamic arrangement behavior of molecular chain segments are achieved through a method combining quantum spectrum analysis and nonlinear optical response characterization. And a scientific basis is provided for optimizing injection molding process parameters and controlling residual stress distribution in a product.

The invention relates to the technical field of new energy materials, in particular to a method for simulating hydrogen evolution performance of Co and Fe double-metal atoms on the surface of defect-state graphene, and aims to simulate the electronic structure performance and reaction mechanism of Co and Fe double-atom hydrogen evolution under modification of Co, Fe and N on the surface of the defect-state graphene by optimizing a modified material structure. A density functional theory of a first principle and a molecular dynamics analogue simulation method are adopted, and the relationship between the structure and hydrogen evolution performance of defect-state graphene metal diatoms and N-modified metal diatom modified materials is studied; the interaction rule between pi electrons in the carbon material under the defect and outer layer electrons of Co and Fe double atoms and Fe, Co and N three atoms is disclosed; therefore, a Co and Fe diatom and Co, Fe and N triatom-graphene two-dimensional material high-efficiency hydrogen evolution mechanism is disclosed, and a theoretical foundation is laid for developing a novel high-efficiency hydrogen evolution material.

The invention discloses a beta-type titanium alloy microstructure phase change prediction method and system, and the method comprises the steps: obtaining the composition proportion information of a to-be-predicted beta-type titanium alloy sample, and obtaining corresponding electronic structure parameters, lattice distortion parameters, thermodynamic parameters and other physical characteristic data based on the analysis; and inputting the physical characteristic data into a constructed phase change prediction model to obtain a phase change prediction result which is used for guiding and adjusting the composition proportion of the titanium alloy. Wherein the phase change prediction model constructs an initial prediction model through a machine learning mechanism fusing uncertainty quantization, robust mode recognition and decision boundary learning, adopts a layered five-fold cross validation strategy for training, and determines an integrated weight based on prediction accuracy and diversity indexes of each mechanism on a validation set; and finally carrying out weighted integration to obtain a high-precision prediction model. According to the method, the accuracy and reliability of phase change prediction of the beta-type titanium alloy are effectively improved.

The invention discloses a preparation method of a rare metal-doped IZO target material, and relates to the technical field of target material preparation, and the preparation method comprises the following steps: mixing an indium oxide and a zinc oxide according to a mass ratio, and adding a rare metal oxide accounting for 1-5% of the total mass of the indium oxide and the zinc oxide; carrying out wet or dry ball milling by using a ball mill to ensure that the powder is uniformly mixed; drying the mixed powder to remove excessive moisture; pressing through a cold isostatic pressing method to form a target material preform; putting the pressed target material pre-body into a high-temperature furnace, sintering in an oxygen atmosphere, controlling the sintering temperature to be 1200-1600 DEG C, and controlling the sintering time to be 4-8 hours; after sintering, the target material is subjected to annealing treatment in a low-oxygen atmosphere; and target material surface treatment. By doping the rare metal oxide, the electronic structure of the IZO target material can be effectively improved, and the conductivity and the optical performance of the IZO target material are improved; the doping of rare metals is beneficial to enhancing the stability and high temperature resistance of the material, and the material is suitable for being applied in a high-temperature environment.

The invention discloses a method for researching the corrosion resistance behavior of zinc alloy based on a first principle. The method comprises the following steps: firstly, retrieving a zinc primitive cell model from a material database and carrying out structure optimization; performing crystal face cutting, cell expansion and re-structure optimization to obtain a zinc plate model; then aluminum atom random replacement doping processing is carried out, and optimization is carried out to obtain a doping model; performing static self-consistent calculation to obtain surface energy, and screening out the most stable doping model; fixing two layers of atoms at the bottom of the most stable doping model, performing chloride ion adsorption calculation and structure optimization, and calculating adsorption energy to determine a most stable adsorption site; and finally, carrying out electronic structure calculation of state density and a work function, and representing the corrosion resistance of the zinc alloy. According to the method, a zinc alloy corrosion micromechanism is deeply analyzed, theoretical guidance is provided for component optimization and corrosion resistance improvement, and compared with a traditional experimental method, the research and development cost and time are remarkably reduced, the research efficiency is improved, and the method has important theoretical and practical application value.

The invention discloses a preparation method of a boron nitride-based multi-shell wave-absorbing anticorrosive coating, which specifically comprises the following steps: firstly preparing magnetic modified BN, then preparing a multi-shell m-BN-coated Fe-Co microsphere precursor, calcining the precursor, coating with modified nano TiO2, and finally preparing the wave-absorbing anticorrosive coating. The invention also discloses the coating prepared by the method. According to the invention, the high-density TiO2-coated wave-absorbing anticorrosive coating with a multi-layer Fe-Co doped carbon shell and a magnetic modified BN particle core can be obtained. The interaction between the BN particles and electromagnetic waves is enhanced through magnetic modification, a wave absorbing mechanism is increased through the multi-layer Fe-Co doped carbon shell, multiple scattering of the electromagnetic waves is achieved, and the wave absorbing efficiency is improved. The high-density coating of the modified nano TiO2 on the outer layer enhances the interface polarization and optimizes the wave-absorbing effect through the unique electronic structure of the modified nano TiO2. The design of the multi-shell m-BN-coated Fe-Co microspheres forms a multi-layer barrier, so that a corrosive medium is effectively blocked.

The present invention discloses a method for evaluating and regulating the wear resistance of ductile iron based on the electronic work function, which relates to the technical fields of surface engineering and performance evaluation. The method includes collecting the electronic work function data and material characteristic data on the surface of ductile iron; extracting the characteristics of the electronic work function data to obtain the electronic work function characteristics; establishing a mathematical model based on the electronic work function characteristics to analyze the correlation between the electronic work function data and the material characteristic data; analyzing the relationship between the electronic work function characteristics and the wear resistance, and establishing a comprehensive evaluation model to evaluate the wear resistance of ductile iron. The present invention combines characterization techniques, complex data analysis methods and multivariate statistical models at the same time. It can not only deeply understand the connection between the electronic structure and macroscopic properties of materials, but also establish a comprehensive evaluation model to predict the wear resistance of ductile iron; this method guides the design of materials and the optimization of the production process.