109 results about "Quantum chemistry" patented technology

The invention discloses a reaction site prediction method and device based on chemical and physical prior driving, and the method comprises the steps: extracting set features through the multi-modal input of a fusion molecular map, an SMILES sequence and a three-dimensional conformation; generating atomic embedding by using a message passing neural network, and calculating a mixed feature fusing a topological path and a three-dimensional distance; combining the key type weight to construct a graph position code of chemical environment correction; injecting the mixed distance and the charge difference into a Transform attention mechanism, and explicitly modeling an inter-atomic long-range electron effect; a model is jointly trained through double tasks of comparative learning and mask prediction, the comparative learning adopts a directional negative sample to enhance generalization, and mask prediction synchronously recovers an atom type and a charge transfer matrix; and finally, injecting quantum chemistry priori constraint attention weights such as a Fuzzy well function, outputting an atomic-scale reaction activity probability, generating a thermodynamic diagram, and realizing high-precision and interpretable active site labeling. According to the method, the drug design and reaction mechanism analysis efficiency can be remarkably improved.

The invention discloses a molecular simulation method and device, a nonvolatile storage medium and electronic equipment. The method comprises the following steps: acquiring molecular system information of a current molecular configuration; calculating the first energy and the first gradient of the key atom region by adopting a variable component sub-feature solicitation solver algorithm, and calculating the second energy and the second gradient of the non-key atom region; wherein the first gradient is used for expressing the stress condition of each atom in the key atom area; the second gradient is used for expressing the stress condition of each atom in the non-key atom area; and updating the current molecular configuration according to the first energy, the first gradient, the second energy and the second gradient to obtain a target molecular configuration. According to the method and the device, the technical problem that the accuracy of the simulation result cannot be ensured under the condition that the computing resources are limited due to excessive computing resources consumed by the quantum chemical computing mode when the molecules are simulated by adopting the quantum chemical computing mode in the related technology is solved.

Aspects of the present disclosure relate generally to systems and methods for optimizing an implementation of a quantum chemistry task in a quantum circuit. The method includes obtaining a chemistry task presented as a Hamilton to implement in a Variational Quantum Eigensolver (VQE) circuit. The method also includes mapping the chemistry task to a qubit space of the VQE circuit with Unitary Coupled Cluster with Single and Double excitations (UCCSD) ansatz. The method also includes decomposing the fermionic excitations to Givens rotations and controlled-Z (CZ) gates by passing exponentiated Pauli forms in the VQE circuit to a cloud compiler. The method further includes after commuting the CZ gates through Givens rotations, cancelling the commuted CZ gates. The method further includes dropping CZ gates at the beginning and the end of the quantum circuit.

The invention provides a semiconductor material precise modeling method based on structured defect information, and relates to the technical field of ultra-wide forbidden band semiconductors, and the method comprises the steps: obtaining material structured defect information, and obtaining the lattice structure, forbidden band width, Raman spectrum, defect energy level, defect atomic percentage and the like of an experiment; normalizing the defect atom percentage to obtain the calculated defect atom molar concentration and the like; establishing an initial density functional theoretical model, and performing structural relaxation optimization processing to obtain a stable model; using a defect fitting algorithm of a hybrid hybridization functional and a defect quantum chemical correction factor to calculate the electron structure properties around atoms corresponding to the stable model, and when the electron structure properties are consistent with experimental structured defect information fitting, determining the model as an accurate ultra-wide forbidden band semiconductor material model at the moment. By means of the method, accurate digital modeling, material optimization growth and device optimization design reference of semiconductor materials adopted for actual device preparation can be achieved.

The invention discloses an interactive catalysis method and platform based on molecular simulation and artificial intelligence. According to the method, intelligent design of a catalyst is achieved through data classification, condition optimization, structure modeling and mechanism analysis. Catalytic data uploaded by a user is subjected to standardization processing and then is divided into two types: a data set A is used for recommending an optimal reaction condition by a multi-objective optimization algorithm; a three-dimensional model is constructed after a catalyst structure of the data set B is optimized through quantum chemistry software, a plurality of intermediates and transition state structures are optimized, and geometric / electronic descriptors are calculated. And constructing a dual-model collaborative prediction system of the model E and the model F through a feature screening and dimension reduction technology, and finally screening the high-performance catalyst by utilizing a model F driven molecule generation algorithm. According to the method, flexible adaptation to specific application scenes can be achieved, the urgent requirements of the industry for efficient and accurate catalyst performance prediction and intelligent design are met, cost reduction and efficiency improvement of the industry are effectively assisted, and the research and development process of the catalyst is accelerated.

The invention relates to an efficient energy-saving control method for industrial furnace complete equipment, in particular to the field of industrial furnace complete equipment, and successfully realizes remarkable improvement of the energy efficiency of an industrial furnace through coupling four key technologies of high-frequency laser spectrum entropy weighting, quantum chemical combustion mechanism modeling, reinforcement learning dynamic optimization and digital twin closed-loop correction. According to the scheme, the traditional thermodynamic limit is broken through, the feeding transient response speed is increased, CO emission is effectively reduced, and in actual measurement of the aluminum smelting furnace, the problems of gas waste and temperature fluctuation caused by imbalance of the air-fuel ratio are successfully solved, so that an energy-saving closed loop from a microreaction mechanism to macroscopic system control is formed, and the energy-saving effect is achieved. And the combustion efficiency and the system stability are greatly improved.

The invention relates to a chemical reaction path prediction method and system. The method comprises the following steps: defining a reaction pair containing reactants and potential products; performing combined optimization treatment on the reactants and the potential products by adopting a molecular dynamics method and a quantum chemistry method to generate an initial reactant configuration and an initial product configuration; based on the aligned initial reactant configuration and initial product configuration, determining initial reaction path information connecting the initial reactant configuration and the initial product configuration by adopting a quantum chemistry method; the invention provides a chemical reaction path prediction method and a chemical reaction path prediction system using the method, which are used for positioning and verifying accurate transition states of reactants and potential products based on initial reaction path information by adopting a quantum chemistry method, and can improve the initial guess quality for high-precision calculation and improve the accuracy of the chemical reaction path prediction. Therefore, the convergence success rate and accuracy of the transition state search are greatly improved, and the overall calculation cost is further reduced on the premise of ensuring the prediction precision.

The application discloses a kind of method, device and medium for calculating the energy of target system using quantum chemistry, method includes: first determining target system information, target system information includes the Hamiltonian of target system, electronic information and electronic spin-orbit information, based on electronic information and electronic spin-orbit information, obtain the Hartree Fock state of fermion form of target system, by pre-setting coding mode, the Hartree Fock state of fermion form is encoded to qubit, and the quantum state of Pauli operator form is obtained, finally, according to the Hamiltonian of target system, and based on the quantum state of Pauli operator form and evolution wave function, the energy of target system is calculated, it can support the realization of quantum chemistry simulation to calculate the energy of target system, improve the calculation speed and calculation accuracy, promote the further development of quantum chemistry simulation application.

This invention provides a method and system for intelligent directional aging of baijiu (Chinese liquor) based on quantum sensing and multi-physics field synergistic regulation. The method includes: S1, using quantum sensors to detect dynamic information at the molecular scale of the liquor; S2, intelligent decision-making and flavor path planning reaction pathways based on artificial intelligence and quantum chemical simulation; S3, applying a preset energy excitation to the liquor through multi-physics field synergistic regulation to guide the aging process. This invention transforms "passive aging" into "active brewing": from an uncontrollable natural process to a designable, programmable, intelligent production process. By precisely lowering the target reaction energy barrier, the formation cycle of core flavor substances is shortened from "years" to "months" or even "weeks," achieving an order-of-magnitude efficiency improvement and breaking down the "time barrier." Based on market demand, products with different flavor emphases can be produced by adjusting the "target flavor fingerprint" and corresponding field regulation "prescription."

The application discloses a kind of based on machine learning prediction amide bond molecular synthesis conversion rate method, belong to chemical technical field.The application is based on high-throughput experiment collection reaction conversion rate data, establishes data set, and utilizes quantum chemistry calculation means to extract the feature descriptor of reaction related molecule, and the model after training finds that random forest model only needs a small amount of data to reach good prediction accuracy.Through the prediction of unknown aromatic amine molecular conversion rate in amidation reaction, it is found that a small amount of relevant reaction data can be added in the training set of random forest model to significantly improve the prediction performance of unfamiliar data.This has important guiding significance for exploring the synthesis of amide bond and the future application of machine learning to the field of chemical synthesis.

The invention discloses a quantum chemical screening method for extracting arbutin, and relates to the technical field of natural product extraction, and the quantum chemical screening method comprises the following steps: constructing an arbutin single-molecule model and a hydrogen bond donor and hydrogen bond receptor single-molecule model by using GaussView software, firstly performing conformation search through MOPAC and molplus programs to obtain a most stable molecular structure, and then extracting the arbutin from the molecular structure; carrying out geometric optimization and single-point energy calculation by utilizing Gaussian; the optimized hydrogen bond donor and hydrogen bond acceptor establish random clusters according to different molar ratios, the random clusters with target molecules are established, a cluster model with an optimal structure is selected for geometric optimization and single-point energy calculation, meanwhile, the binding energy between the eutectic solvent and arbutin is calculated, and IGMH analysis, ESP analysis and AIM analysis are carried out. The invention provides a universal method for green and efficient extraction of active ingredients of natural products.

The invention relates to the technical field of electrical data processing, and provides an anthocyanin stabilizer screening method and system based on fusion of quantum chemistry calculation and machine learning. The method comprises the following steps: constructing a molecular structure data set; performing geometric structure optimization on the anthocyanin molecules and the candidate polyphenol molecules to obtain a ground state optimization structure; performing multi-dimensional molecule descriptor calculation on the candidate polyphenol molecules to obtain a polyphenol molecule descriptor matrix; performing structure optimization, single-point energy calculation and free energy calculation on the anthocyanin polyphenol compound system to obtain a combined free energy value set; integrating the polyphenol molecule descriptor matrix and the combination free energy value set, constructing a training data set, and performing feature screening; performing model training through a machine learning algorithm to obtain a combined free energy prediction model; and predicting the binding free energy of the anthocyanin polyphenol compound through the binding free energy prediction model to obtain candidate molecules of the anthocyanin stabilizer. The screening efficiency of the anthocyanin stabilizer is improved.

The application discloses a kind of multi-element doped system simulation methods for improving the performance of 2:17 type samarium-cobalt permanent magnet, comprising: step one, using the Visualizer module of material calculation software to establish the theoretical model of 2:17 type rare earth cobalt permanent magnet material;Step two, based on the GO module of quantum chemistry calculation software, the theoretical model of different doped systems is analyzed, and then the system with stronger magnetism is found;Based on the quantum chemistry calculation software, the doped model and virtual crystal approximation model of different doped ratios are established to obtain the better doped ratio by comparison.The application discloses a kind of multi-element doped system simulation methods for improving the performance of 2:17 type samarium-cobalt permanent magnet, the theoretical research of the characteristics of rare earth cobalt permanent magnet material itself and doping characteristics is carried out through the first principle, through the implementation of the project, the theoretical analysis of rare earth cobalt permanent magnet material is formed, which provides design idea for developing rare earth cobalt permanent magnet material with better system performance.

The invention belongs to the technical field of computational chemistry and artificial intelligence crossing, and provides a molecular potential energy surface prediction method based on deep learning. The method comprises the following steps: inputting a structure file of an unoptimized molecule, and reading and predicting energy and force of a current molecular structure by utilizing a machine learning potential model; and then, judging whether the structure is converged or not according to a prediction result by adopting a GeomeTRIC algorithm, and if not, adjusting coordinates to generate a new structure and performing circular prediction until the structure is converged. According to the method, the quantum chemistry and the deep learning technology are combined, the calculation efficiency can be greatly improved, complex inter-atomic interaction in molecules can be fully captured, and the prediction accuracy is ensured; and meanwhile, batch processing and automatic generation of a quantum chemistry software interface are supported, and the method is particularly suitable for high-throughput molecular structure optimization in the fields of drug discovery, material science and chemical product design.

The parameterized quantum circuit construction method, device, storage medium and computer device provided by the application utilize unitary matrix linear combination to reduce the depth and required quantum bit number of a variational circuit, thereby effectively constructing an arbitrary target quantum state, reducing the amount of training parameters, and optimizing the efficiency and accuracy of the variational quantum algorithm and improving the practicability of the algorithm under limited quantum resources; and the application is particularly suitable for a noisy intermediate-scale quantum (NISQ) device, and by proposing a circuit design with low depth and quantum bit number, the problem that the application of the prior art on the NISQ device is limited can be solved, for example, the application can efficiently solve VQA problems such as quantum state learning and Hamiltonian ground state solving on a quantum device, thereby opening up a new way for practical applications in the field of quantum chemistry.

The invention discloses a method for evaluating photoelectric conversion efficiency of an organic solar cell material. The method comprises the following steps: firstly, acquiring the stacking morphology of a material by utilizing molecular dynamics simulation and performing molecular slicing; then, constructing a multi-dimensional geometric feature matrix containing internal deformation and external relative positions of characterization fragments and angle features based on a centroid fitting plane; performing dimension reduction processing on the feature matrix by adopting principal component analysis, extracting principal component features reflecting deformation and spatial distance, and performing morphological clustering according to the principal component features to screen effective clustering morphologies; and finally, in combination with the electron coupling value calculated by quantum chemistry and the corrected equivalent distance based on the principal component, establishing a mapping relationship to evaluate the material efficiency. According to the method, by introducing the centroid weight and the deformation parameters, geometric representation errors existing when non-planar and flexible organic molecules are processed through a traditional method are effectively solved, and the prediction precision and robustness of novel organic photovoltaic material screening are remarkably improved.

The invention provides a quantum storage structure optimization method for a plane wave basis group Hamiltonian, relates to the field of quantum calculation and quantum chemical simulation, and aims to solve storage and calculation challenges caused by huge scale of a Hamiltonian matrix in quantum calculation. Through structural analysis, double-layer index coding and structured QROM module construction, efficient loading and dynamic calling are achieved. The quantum random access memory routing module supports sub-channel loading, path compression reduces the number of control gates, and resource efficiency and flexibility are improved. The method is suitable for large-scale periodic material simulation, such as crystal structure optimization and electronic state analysis, is in seamless connection with a mainstream quantum algorithm, and remarkably reduces the circuit depth and auxiliary bit requirements.

The present application belongs to the field of chemical thermodynamics, and particularly relates to a thermodynamic model for predicting the thermodynamic properties of a salt-solvent system. The model first obtains the coordination number n of cations and anions in the salt-solvent system through molecular dynamics simulation, then obtains the initial configuration of the cation-n solvent molecule-anion through configuration optimization, and obtains the most stable structure through quantum chemistry calculation program optimization, and finally obtains the VLE (vapor-liquid equilibrium) data prediction value of the salt-solvent system based on the COSMO-RS theory. The model can obtain the prediction value with high accuracy without experiment, thereby saving a large amount of manpower, material resources and financial resources. Meanwhile, the present application also discloses the phenomenon that the salt in the salt-solvent system is volatile.

A method and apparatus for measuring energy of a quantum chemistry system. In one aspect, a method includes: for a Hamiltonian that describes a chemical system and includes a sum of multiple terms; wherein each term includes i) a respective operator that affects a respective single particle-based rotation and ii) one or more particle density operators, for each group including terms having the same operator that affects the respective single particle-based rotation, repeatedly measuring expected values for terms included in the group, including: calculating, by quantum computing, the desired values of terms included in the group; performing a corresponding single particle based rotation on a qubit system encoding a state of the chemical system; measuring a Jordan-Wigner transform of one or more particle density operators in the set under a calculation basis to obtain respective measurements of the set; calculating a total number of particles or a spin component using the obtained measurements; determining whether the calculated total particle number or spin component is equal to a corresponding target value; and in response to determining that the calculated total population or spin component is equal to the corresponding target value, retaining the measurement for determining the energy of the chemical system by a classical calculation; and determining the energy of the chemical system by classical calculations using the obtained measurements.

To enable provision of active space information that contribute to quantum chemistry computation.SOLUTION: An information output program disclosed herein causes a computer to perform processes of: acquiring occupancy data including a time series of occupancy of each of multiple molecular orbits, performing principal component analysis of the occupancy data, and outputting information on an active space corresponding to a subset of the multiple molecular orbits used for quantum chemistry computation on the basis of a result of the principal component analysis.SELECTED DRAWING: Figure 1

The application discloses a kind of target system energy calculation method, device and storage medium, method includes: first according to the electronic integration in the target system to be simulated and initial density matrix determines Fock matrix, then according to Fock matrix, iteration operation to initial density matrix is executed, until the difference of density matrix obtained in front and back two times meets preset accuracy when iteration process appears, current density matrix obtained in back is as target density matrix, finally based on the energy of the target system to be simulated is calculated based on the target density matrix obtained, it is determined by target density matrix, and the target system energy is calculated, so that the calculation accuracy of target system energy is improved, applicable to the quantum calculation simulation of complex system, further promote the development of quantum chemistry simulation application.

The invention belongs to the field of Po-210 aerosol characteristic calculation, and particularly relates to a Po-210 aerosol particle characteristic and decay kinetics calculation method. The method comprises the following steps: S1, determining an optimal theoretical method; s2, constructing an initial molecular structure of one or more candidate Po species to be researched, and completing construction of the initial molecular structure; s3, geometric structure optimization and frequency calculation are carried out; s4, a Lennard-JonesLJ potential parameter is calculated, and the Lennard-JonesLJ potential parameter is calculated; s5, determining thermodynamic properties of the candidate chemical species based on the LJ potential parameters obtained in the step 4; and S6, calculating to obtain the characteristics of the Po-210 aerosol. Based on quantum chemistry, molecular dynamics and a Monte Carlo method, particle nucleation, collision and combination mechanisms and decay dynamics of Po-210 in a gas space are disclosed, key mechanism support is provided for predicting environment evolution behaviors and designing source foot control strategies, and a feasible calculation normal form is provided for predicting cross-scale behaviors of highly toxic radioactive substances.

The application discloses an interactive catalytic method and platform based on molecular simulation and artificial intelligence, and realizes intelligent design of a catalyst through data classification, condition optimization, structure modeling and mechanism analysis. After being standardized, the catalytic data uploaded by a user is divided into two categories: data set A is used for recommending optimal reaction conditions by a multi-objective optimization algorithm; and the catalyst structure of data set B is optimized by quantum chemistry software to construct a three-dimensional model, and multiple intermediate, transition state structures and geometric / electronic descriptors are optimized. Through feature screening and dimension reduction technology, a double-model collaborative prediction system of model E and model F is constructed, and finally, model F is used to drive a molecular generation algorithm to screen high-performance catalysts. The application can realize flexible adaptation to specific application scenarios, meet the urgent needs of the industry for efficient and accurate catalyst performance prediction and intelligent design, and effectively help the industry to reduce costs and increase efficiency, and accelerate the catalyst research and development process.

To attain efficient calculation of VQE.SOLUTION: An information processing device 10 repeats update processing of a value of a coefficient in a third expression and exploration processing of a ground state of a multi-electron system. The third expression is an expression obtained by adding a term obtained by multiplying a coefficient to a second expression related to the number of electrons in the multi-electron system, to a first expression which calculates physical quantity of the multi-electron system. The exploration processing is the exploration processing in a variational quantum characteristic value solver method which explores the ground state of the multi-electron system by changing a quantum state of the multi-electron system so that an expectation value of the third expression according to the quantum state of the multi-electron system lowers. The information processing device 10, in k+1-th exploration processing, sets an end state of the multi-electron system in any of first to k-th exploration processing, as an initial state of the multi-electron system in the k+1-th exploration processing, and changes the quantum state of the multi-electron system so that the expectation value of the third expression lowers, from the initial state.SELECTED DRAWING: Figure 1

An apparatus and method are provided for optimizing the use of gas hydrate inhibitors by combining real-time "dew point" measurement with quantum-chemical phase-change analysis. A gas hydrate inhibitor reduces gas moisture; by measuring gas humidity and identifying the "dew type" using two chilled-mirror sensors each equipped with an imaging camera, a "dew coefficient" (0–1) is calculated via quantum chemistry analysis of inhibitor solvation. This mesoscale coefficient is used to monitor fluid phase changes. A general relationship for the water / hydrocarbon "dew coefficient" is derived as a function of changes in Gibbs free energy of dew evaporation (inhibitor solvation), gas temperature and pressure, and gas / liquid density. By combining measured "dew point" and "dew type" with quantum chemistry data of phase transformations "dew coefficient", the optimal inhibitor injection rate is determined, minimizing inhibitor consumption while preventing hydrate formation.

The present application relates to the technical field of electric data processing, and provides a screening method and system for anthocyanin stabilizer based on quantum chemistry calculation and machine learning fusion. The method comprises the following steps: constructing a molecular structure dataset; performing geometric structure optimization on anthocyanin molecules and candidate polyphenol molecules to obtain ground state optimized structures; performing multidimensional molecular descriptor calculation on the candidate polyphenol molecules to obtain a polyphenol molecule descriptor matrix; performing structure optimization, single-point energy calculation and free energy calculation on the anthocyanin polyphenol complex system to obtain a binding free energy numerical set; integrating the polyphenol molecule descriptor matrix and the binding free energy numerical set, constructing a training dataset and performing feature screening; performing model training through a machine learning algorithm to obtain a binding free energy prediction model; and predicting the binding free energy of the anthocyanin polyphenol complex through the binding free energy prediction model to obtain candidate molecules for anthocyanin stabilizer. The present application improves the screening efficiency of anthocyanin stabilizer.

Predict the retention time of the target substance obtained by high-performance liquid chromatography. [Solution] In the retention time prediction method, a parametric function is created using a linear combination of the partition coefficients between the mobile phase and multiple stationary phase models. For multiple standard substances, the partition coefficients between the mobile phase and multiple stationary phase models are calculated by quantum chemical calculations using molecular structure information. Using the retention times and partition coefficients of the multiple standard substances, the parameters of the partition coefficients in the linear combination of the parametric function are determined by linear regression. A specific function is created by substituting the parameters into the parametric function. For the target substance, the partition coefficients between the mobile phase and multiple stationary phase models are calculated by quantum chemical calculations using molecular structure information. Using the specific function, the retention time is calculated from the partition coefficients for the target substance.

The present application belongs to the field of computational chemistry and molecular simulation technology, and relates to a kind of aromatic eutectic solvent multiscale molecular simulation screening method and system based on multi-objective collaborative scoring model.Establish target molecule model library and eutectic solvent candidate component library;Quantum chemistry calculation is carried out on target molecules and eutectic solvent candidate system, and quantum chemistry descriptors are extracted;Molecular dynamics simulation system is constructed, and molecular dynamics descriptors such as aromatic space enrichment coefficient Kπ, glycosidic bond interaction index Ggly and lignin bond type affinity index Lβ are extracted;Multi-scale feature vectors are obtained by normalization processing, input into multi-objective collaborative scoring model, calculate and extract score SE, grading score SF, and judge and output active ingredient extraction priority, lignocellulose grading priority or segmented collaborative processing mode.The present application is suitable for eutectic solvent calculation screening and application mode discrimination when there is a target conflict between plant aromatic active ingredient extraction and lignocellulose grading treatment.

The application discloses a kind of optimization method and device for identifying Cu-Zn alloy cluster structure potential energy surface, comprising: randomly generating several Cu-Zn alloy clusters, constitute population structure library n pop ; develop shell script that can efficiently call Gaussian16 quantum chemistry software, carry out first local structure optimization to n pop ; innovative surface atom self-adapting reorganization strategy is proposed, iteratively move cluster surface atoms to self-adapting generated empty space sites, execute second stage structure optimization;Through crossover, variation operation, in combination with similarity detection and potential energy comparison, extract the optimal structure of binary Cu x Zn y Cluster.Using the technical scheme of the application, the local and global spatial search capability of genetic algorithm is optimized and improved, and the stability and electronic structure of Cu-Zn alloy cluster can be efficiently analyzed by calling quantum chemistry software.