51 results about "Quantum chemical computations" patented technology

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.

The invention discloses a gold mine exploration method based on geological data analysis, and relates to the technical field of mineral geological exploration, and the method comprises the following specific steps: collecting rock samples of different stratums in a region, determining the content of gold element and associated elements thereof, observing the occurrence state of the elements, and establishing an element occurrence state database; by introducing quantum chemical calculation and a particle swarm optimization algorithm, refined simulation of migration behaviors of the gold element and associated elements thereof in a geologic body is realized, and chemical reaction characteristics and microscopic parameters of diffusion coefficients of the elements under different conditions can be described more accurately; in addition, a mathematical model reflecting actual conditions can be constructed according to the parameters, reliability and accuracy of a tracking result are ensured, the process enables the possibility of gold mineralization to be predicted in a larger range, the risk of blind drilling is reduced, and therefore the efficiency of exploration work is remarkably improved.

The invention discloses a biomass pyrolytic reaction network prediction method based on a graph theory and quantum chemistry, which comprises the following steps: analyzing the molecular structure of a biomass initial reactant, abstracting the molecular structure into a directed graph molecular model, marking a potential conversion path after molecular mechanics optimization, generating a unique identifier by using an atom numbering rule and a Hash algorithm, and predicting the biomass pyrolytic reaction network. Functional groups are extracted and packaged into sub-graph modules, chemical bond parameters are obtained in combination with quantum chemistry calculation and are converted into fracture probabilities, basic reaction building blocks are predefined to traverse and mark breakable bonds, fragments are recombined and then de-weighted through Hash, and then reaction activation energy weights are given to side chemical bond fracture reactions; an energy optimal path is screened by means of a priority queue search algorithm, accurate analysis of a chemical bond fracture path and intermediate product conversion in the biomass pyrolysis reaction network is finally achieved, reaction path and product distribution are efficiently predicted, and the calculation efficiency and precision of a complex system are balanced.

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.

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 invention belongs to the technical field of material information, and particularly relates to a quantum chemistry calculation result intelligent analysis and error correction system and method. The calculation result analysis module is in communication connection with the data preprocessing module and is used for analyzing the standardized data based on a preset rule; the machine learning analysis module is in communication connection with the calculation result analysis module, receives an analysis result sent by the calculation result analysis module, and performs deep analysis on the analysis result based on a machine learning algorithm; and the error correction module is in communication connection with the calculation result analysis module and the machine learning analysis module and is used for performing error correction on the quantum chemistry calculation result based on the analysis result and the analysis result, so that the overall analysis efficiency is improved, the analysis result is continuously optimized, and the practical value is remarkable.

The present invention discloses a method and system suitable for data mining of energetic compounds, belonging to the technical field of structure-activity relationship of energetic compounds in chemical informatics calculation, comprising the steps of: S1, data preprocessing; S2, extracting molecular topological structure features and features of quantum chemical calculation to generate fingerprint features; S3, calculating Pearson correlation and information entropy, screening out linearly correlated and non-correlated features, performing feature dimensionality reduction, and deleting redundant features whose linear correlation between features is higher than a set value; S4, knowledge mining and model verification, exploring the correlation and knowledge association between feature libraries. The present invention can classify data of energetic materials according to skeletons and groups, mine multi-dimensional linear features and non-linear features, embed more features based on chemical expertise into the graph structure model training process, and utilize the data mining engine of the present invention to screen out strongly correlated molecular features, which can make up for the shortcomings of existing models.

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.

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

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

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.

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.

An information output program for causing a computer to execute a process includes acquiring occupancy number data that includes a time series of occupancy numbers for each of a plurality of molecular orbitals, executing principal component analysis on the occupancy number data, and outputting information on an active space that corresponds to a subset used for a quantum chemical calculation, among the plurality of molecular orbitals, based on a result of the principal component analysis.

This invention discloses a linear scaling quantum chemistry calculation method, its applications, and related products based on pre-constrained energy. Belonging to the field of quantum chemistry calculation technology, it solves the core technical pain points of existing technologies, such as the irreconcilable trade-off between computational complexity and accuracy, lack of underlying physical consistency guarantees, and poor adaptability to complex systems. This invention uses the inherent kinetic-potential coupling relationship derived from the generalized virial theorem as a pre-priority hard constraint. Through a core process involving pre-determining inherent constraint parameters, pre-locking physical orbits, effective particle pair screening calculations, and direct calculation of total energy, it completely abandons self-consistent field iteration and Hamiltonian matrix diagonalization operations, achieving a fundamentally rigorous O(N) linear scaling. The calculation results of this invention naturally conform to the basic rules of quantum mechanics, have no approximate truncation error, and are universally applicable to all systems and quantum states. It can perform high-throughput quantum chemistry calculations for large-scale industrial systems on ordinary consumer-grade hardware, and can be widely applied in fields such as drug development, new material design, semiconductor simulation, and superconducting material screening.

The invention belongs to the field of quantum chemistry calculation, and discloses a gas molecule collision cross section prediction method based on operator learning, comprising the following steps: constructing an encoder network and a decoder network, the encoder network taking structural information of gas molecules as input and outputting feature vectors after the structural information is encoded; the decoder network takes the feature vector output by the encoder network as input, and outputs a predicted value of any physical and chemical attribute of the gas molecules; acquiring a first training set comprising gas molecule samples and corresponding structure information and materialization attribute data, and pre-training the encoder network and the decoder network by using the first training set; the correlation between the structural information of the gas molecules and the distribution space parameters is fully utilized, the generalization prediction capability of the collision section prediction network on unknown gas molecules is remarkably improved, and the problems of weak generalization performance and poor prediction precision caused by insufficient utilization of molecular structure information in the prior art are effectively solved.

To reduce processing time required in performing VQE calculation.SOLUTION: An information processing apparatus 100 specifies two or more patterns 120 representing combinations of values of a plurality of parameters 111 that defines a predetermined variational quantum circuit 110. The information processing apparatus 100 evaluates degrees of contribution to VQE calculation, for each of the parameters 111, based on calculation results of a predetermined cost function for use in quantum chemistry calculation, on each of the patterns 120. The information processing apparatus 100 selects, based on the result of the evaluation, one or more first parameters 112 determined to be relatively high in the degree of contribution to VQE calculation, out of the parameters 111. The information processing apparatus 100 controls an arithmetic unit 101 so as to set the selected one or more first parameters 112 to target parameters 113 for which values are to be updated, and execute at least one iteration of the VQE calculation.SELECTED DRAWING: Figure 1

The invention provides a task scheduling simulation method and system based on a multi-layer hardware architecture, and the method comprises the steps: a top-layer control node decouples a quantum chemistry calculation task into a lightweight index sequence, and distributes the lightweight index sequence to a middle-layer control node after sorting and batch division; the intermediate layer control node converts the received index into an electronic integral task unit, and dynamically recombines the electronic integral task unit into a task package capable of being scheduled in parallel according to simulated underlying hardware constraint so as to send the task package to an execution layer control node; and the execution layer control node responds to a task request event of the computing node and distributes a task packet based on the simulated real-time load state so as to control the computing node to process the received task packet. According to the method, the problem of load unbalance caused by the fact that time-consuming modeling is rough and the actual time-consuming huge difference cannot be reflected in existing electronic integration task simulation is solved, and high-precision and high-fidelity scheduling simulation of large-batch electronic integration tasks is achieved on the premise that real hardware is not consumed.

A non-transitory computer-readable recording medium stores an algorithm selection program for causing a computer to execute a process including: in a case where a solution for structure optimization of a molecule is calculated using a quantum chemical calculation algorithm that repeatedly executes calculation for a plurality of cycles, executing a first quantum chemical calculation algorithm for a target molecule and calculating a nuclear gradient norm for each cycle; executing the first quantum chemical calculation algorithm for a cycle in which the nuclear gradient norm is equal to or more than a first threshold; and executing a second quantum chemical calculation algorithm of which execution time is longer than the first quantum chemical calculation algorithm for a cycle in which the nuclear gradient norm is less than the first threshold.

A non-transitory computer-readable recording medium storing an information output program for causing a computer to execute a process includes acquiring occupancy number data that includes a time series of occupancy numbers for each of a plurality of molecular orbitals, executing principal component analysis on the occupancy number data, and outputting information on an active space that corresponds to a subset used for a quantum chemical calculation, among the plurality of molecular orbitals, based on a result of the principal component analysis.

The goal is to automate the determination of the active space, which is useful for quantum chemical calculations. [Solution] The active space determination program obtains occupancy data, which includes data showing the time-series changes in the number of electrons occupied in each of multiple molecular orbitals. Using the occupancy data as input, the program calculates the solution to a mathematical optimization model formulated with constraints that keep the sum of the number of electrons occupied in multiple molecular orbitals constant, and an objective function that gives a relatively higher evaluation to combinations of molecular orbitals whose time-series changes in the number of electrons occupied are negatively correlated with combinations whose time-series changes in the number of electrons occupied when selecting a subset from multiple molecular orbitals to be used in quantum chemical calculations, compared to combinations whose time-series changes in the number of electrons occupied are positively correlated. The program then has the computer execute the calculation and output the result.

The application discloses a kind of quantum chemistry-based energetic material electrostatic spark sensitivity prediction method and system, it is related to energetic material performance prediction field, the method includes: new energetic material sample carries out quantum chemistry calculation, obtains the multidimensional influence parameter data set corresponding to the new energetic material sample, and multidimensional influence parameter data set is input into energetic material electrostatic spark sensitivity value prediction model, obtains the electrostatic spark sensitivity value corresponding to new energetic material sample.The present application can solve the technical problems that the existing energetic material electrostatic spark sensitivity linear prediction model is narrow in scope of application, low in prediction efficiency, and it is difficult to realize high-precision prior prediction of electrostatic spark sensitivity of new unsynthesized energetic material.

The application provides a method for evaluating the response speed and reaction strength of a resin material microwave curing process, so as to select a resin base element material suitable for microwave curing. The method combines molecular dynamics simulation and quantum chemical calculation, and studies the dynamic change process of the resin under the microwave field by introducing an alternating electric field. Specifically, the reaction energy barrier under the microwave field is simulated from the transition state theory; the influence of the microwave on the chemical reaction rate is clarified from the effective collision theory; and the promotion effect of the microwave on the curing activity of the resin base element material is analyzed from different dimensions. Based on the above steps, a selection method is established with temperature, reaction energy barrier and effective collision probability as criteria. The application overcomes the limitation that traditional instruments and equipment cannot accurately in-situ characterize the microwave reaction, can pre-evaluate the design and synthesis of the microwave curing resin base element material, and thus improves the microwave curing efficiency of the resin base composite material and reduces the production cost.

The invention relates to an insulating oil molecule lightning impulse performance evaluation and optimization method based on a first principle, and belongs to the technical field of insulating material performance evaluation. The method comprises the following steps: S1, finely constructing a molecular model based on quantum chemistry calculation; s2, performing dispersion correction and geometric optimization on the insulating oil molecular model; s3, calculating numerical values of the performance evaluation index parameters under the action of different electric fields; and S4, comparing and analyzing the lightning impulse performance of different types of insulating oil molecules by adopting a parallel coordinate graph. The invention creatively provides a micro-scale evaluation and structure optimization method aiming at the lightning impulse performance of the insulating oil, and is expected to break through the limitation of experimental period and cost.

The invention provides a reaction kinetic model set library construction method taking a CPD base as a core layer mechanism. The method comprises the steps of experimental data collection and preprocessing, core layer mechanism standardization, expansion layer fuel specificity mechanism and model integration and verification. According to the method, based on a hierarchical architecture of a core layer (CPD mechanism) and an extension layer (target fuel sub-mechanism), high precision and universality of the model are realized by integrating a pyrolysis oxidation experiment and quantum chemistry calculation. The method can predict the pyrolysis behavior of the fuel under multiple working conditions, clarify the generation mechanism of polycyclic aromatic hydrocarbons (PAHs), and provide a high-precision and extensible digital tool basis for aviation fuel design, pollutant control and combustion optimization.

The invention provides a wide-temperature-range electrolyte development method and system based on deep learning, and relates to the technical field of electrolyte development, the system comprises an ionic liquid molecular library construction module, the ionic liquid molecular library construction module constructs a molecular library containing cations and anions, and the ionic liquid molecule library construction module screens the positive ions and the negative ions through high-throughput screening to form a candidate ion pair set. According to the wide-temperature-range electrolyte development method and system based on deep learning, an ionic liquid molecular library containing cations and anions is constructed, a high-throughput screening and graph neural network prediction model is adopted for screening and performance prediction of candidate ion pairs, and optimization is performed in combination with quantum chemistry calculation, so that the development efficiency of the wide-temperature-range electrolyte is improved. And finally, synthesizing an electrolyte formula through a micro-fluidic robot platform. Efficient development of the wide-temperature-range electrolyte is realized, and efficient electrochemical performance testing can be carried out in multiple temperature ranges.

The invention provides a molecular design method and a molecular design system based on a genetic algorithm. The molecular design method comprises the following steps: collecting related molecular structure data; simulating molecular properties through quantum chemical calculation to obtain quantum chemical calculation data; constructing a structure-activity relationship model; setting a molecular structure encoding mode to encode the collected molecules, and constructing an initial population; designing a fitness function, and calculating fitness function values of different individuals; selecting part of individuals as parent generations according to the fitness function value, and generating offspring molecules through crossover variation; predicting progeny molecule properties, calculating a fitness function value, and selecting part of progeny molecules to combine with parent molecules to form a new population; and repeating the steps until a stop condition is met, and outputting the optimal fitness molecule. The molecular design method can shorten the cycle of molecular design and development, improve the success rate of finding new molecules and reduce the research and development cost.

The embodiment of the present invention relates to a workflow task processing system for assisting high-voltage electrolyte experiments, the system comprising: a workflow task scheduling module, a workflow task pool, a workflow task database, a task execution module, a molecular dynamics simulation interface library, a quantum chemical calculation interface library, and an AI model interface library; wherein the molecular dynamics simulation interface library is connected to the functional interface of the molecular dynamics simulation software, the quantum chemical calculation interface library is connected to the functional interface of the quantum chemical calculation software, and the AI ​​model interface library is connected to the functional interface of the AI ​​model. The workflow task scheduling module completes three types of auxiliary task processing by calling the task execution module: high-throughput screening tasks, mechanism prediction tasks, and performance prediction tasks. Using this system as an auxiliary means for high-voltage electrolyte experiments can achieve the purpose of reducing the number of experimental trial and error, improving experimental accuracy, shortening the experimental cycle, and reducing experimental costs.

The invention provides an organic molecule property prediction method based on multistage line graph interaction, relates to the technical field of organic molecule property prediction, and aims to solve the problems of high calculation cost and low efficiency in a traditional method. Constructing graph structure data capable of describing an atom adjacency relationship in a molecule; data preprocessing and feature generation: preprocessing the graph structure data to generate node features and edge features; constructing a graph attention network and feature aggregation based on a multi-level line graph; by using a deep learning method, the time for predicting the property of a single molecule is greatly shortened, the prediction efficiency is improved, compared with a traditional quantum chemistry calculation method, higher accuracy can be achieved, different scale features of the single molecule can be learned by using a multi-level line graph method, the robustness of a model is improved, and the prediction efficiency is improved. A better prediction effect can be achieved while the same data volume is used.

An information processing apparatus iteratively calculates, using a self-consistent field method, an electron density at each of a plurality of points in a space where a substance exists. The information processing apparatus determines, for each of the plurality of points, each time the electron density is calculated, whether a plurality of indicator values based on the calculated electron density satisfies respective convergence criteria respectively associated with the plurality of indicator values. Then, the information processing apparatus terminates, for each of the plurality of points, the iteratively calculating of the electron density upon at least one of the plurality of indicator values satisfying the associated convergence criterion.

Reducing the amount of calculations in quantum chemical calculations. The quantum chemical calculation device combines two molecular orbitals included in a plurality of molecular orbitals of a molecule as an object of quantum chemical calculation to generate a plurality of molecular orbital pairs. Next, the quantum chemical calculation device calculates the overlap integral values ​​between the included molecular orbitals for each of the plurality of molecular orbital pairs. Then, the quantum chemical calculation device determines the first molecular orbital to be included in the active space orbital group of the quantum chemical calculation based on the overlap integral values ​​of each of the plurality of molecular orbital pairs.