195 results about "Quantum chemistry" patented technology

The invention provides a gradient crosslinking process of photosensitive resin for photocuring 3D printing, and relates to the technical field of photocuring 3D printing materials. The gradient crosslinking process of the photosensitive resin for photocuring 3D printing comprises the following steps: S1, based on double-initiator system design, adopting molecular dynamics simulation screening, respectively adding a 405nm sensitive type TPO-L initiator and a 365nm sensitive type I TX initiator into an epoxy acrylate prepolymer, and verifying initiation energy barrier matching through quantum chemistry calculation, and generating a pre-initiation gradient resin formula. Through molecular dynamics simulation, initiator combinations are screened, energy barrier matching is verified, the ratio of dual-wavelength sensitive initiators is optimized, and accurate triggering of surface layer and deep layer cross-linking reaction is ensured. And a three-roller grinding and dispersing process is combined with ultrasonic oscillation to eliminate nanoparticle aggregation, so that the mechanical uniformity and light scattering effect of a resin system are improved.

The invention provides a method and a system for evaluating the luminescence performance of a near-infrared two-region molecular fluorescent probe, and relates to the technical field of fluorescent probes, the method comprises the following steps: obtaining the initial configuration of the near-infrared two-region molecular fluorescent probe in an aqueous solution, and carrying out molecular dynamics simulation on the initial configuration to obtain a plurality of representative conformations of the probe in the aqueous solution; performing quantum chemical calculation on each representative conformation to obtain first system energy of each representative conformation in a stable state and second system energy and intensity parameters of each representative conformation in a lowest singlet excitation state; generating a comprehensive evaluation factor based on the first system energy, the second system energy and the intensity parameter; and sorting the luminescence properties of the probes based on the comprehensive evaluation factor, and screening out the probe with the optimal performance. According to the method provided by the invention, quantitative evaluation on the luminescence property of the near-infrared two-region molecular fluorescent probe is realized, and technical support is provided for optimal design and clinical application of the probe.

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.

Provided are an information processing method and the like in which it is possible to efficiently obtain a compound capable of having a good property. In the information processing method, includes acquiring a spectral indicator obtained by quantum chemical calculation in a plurality of compounds to be candidates, classifying, on the basis of the acquired spectral indicator, each of the compounds into a group in which the spectral indicator satisfies a predetermined condition and extracting a group in which the spectral indicator does not satisfy the predetermined condition, and a light emitting compound classified into the group in which the spectral indicator satisfies the predetermined condition.

The invention discloses an asphaltene molecule nano-scale characteristic analysis method based on quantum chemistry calculation, which comprises the following steps: acquiring composition information of asphaltene components, and constructing a representative asphaltene molecule three-dimensional model containing a fused aromatic ring skeleton and an alkyl side chain; performing geometric configuration optimization on the representative asphaltene molecule three-dimensional model by adopting a quantum chemistry density functional theory method to obtain a stable configuration of the asphaltene molecule; determining key nano parameters of the asphaltene molecules according to the stable configuration of the asphaltene molecules; and associating the key nano-scale parameters of the asphaltene molecules with the macro-performance of the asphalt material, and establishing an asphalt performance association model. According to the method, the key parameters capable of representing the asphaltene microstructure and property are obtained, so that the understanding of the relationship between the asphaltene composition and the performance of the asphalt material is deepened, the performance of the asphalt material is evaluated from the molecular scale, and a new thought is provided for performance prediction and modification of the asphalt material.

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 provides a method for detecting furfural in insulating oil based on terahertz time-domain spectroscopy, and relates to the technical field of aging detection of insulating oil of electrical equipment, and the method comprises the following steps: determining the content of furfural in insulating oil in different aging states through a chromatographic analysis method, and preparing samples with corresponding concentrations; the method comprises the following steps: scanning a sample by using a transmission-type terahertz time-domain spectroscopy system according to liquid characteristics and terahertz spectral characteristics of the insulating oil to obtain time-domain spectral data of the sample; adopting a quantum chemistry simulation method to simulate absorption and reflection characteristics of furfural molecules in a terahertz frequency band, and matching a vibration mode, a rotation energy level and terahertz wave band absorption characteristics in a real spectral signal; and the content of furfural in the insulating oil is quantitatively detected by reconstructing the terahertz time-domain signal. According to the method, rapid and non-contact detection of trace furfural in the insulating oil is realized by analyzing the terahertz spectrum characteristics, and an effective evaluation means is provided for the insulation aging degree of the transformer.

The invention relates to a quantum chemistry Hamiltonian rapid generation method and device based on a stability sub-table, and the method comprises the steps: obtaining a single electron integral item, a double electron integral item and a nuclear energy item of a target Fermi Hamiltonian, and storing the nuclear energy item; dividing the equal double-electron integrals into the same calculation object class, and deleting double-electron integral items corresponding to the double-electron integrals of which the absolute values are smaller than a threshold value; converting the single-electron integral item and the double-electron integral item into a Bose Hamiltonian expression form; filling the stable sub-form table based on all Fouli items to obtain a Fouli check matrix, and recording a coefficient vector; the same row vectors in the Follicle check matrix are merged, the Follicle coefficients corresponding to the merged row vectors are added, and the row vectors with the Follicle coefficients being 0 are deleted; and storing the Follicle check matrix and the coefficient vector. According to the technical scheme, the efficiency of converting the Fermi Hamiltonian into the Bose Hamiltonian can be improved.

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.

This application relates to quantum chemistry. The method includes: obtaining training data for a molecular generative model; predicting, if a labeled property value in molecular property label data of a sample molecule in the training data for at least one of M properties is missing, a property value of the sample molecule for at least one property, to obtain molecular property prediction data of the sample molecule; obtaining molecular property tag data of the sample molecule based on the molecular property label data and the molecular property prediction data of the sample molecule; and training the molecular generative model based on the molecular property tag data of the sample molecule, to obtain a trained molecular generative model. This application supports training of the molecular generative model by using the training data without the labeled property value, molecular properties are more abundant and diversity of molecular data is improved.

Technologies and techniques for estimating the ground state energy of a quantum chemical system. The method includes classically computing states close to the ground state of the quantum chemical system, assessing the quality of the classically computed states based on their energy distribution, selecting a state based on the assessment result, implementing the selected state on a quantum computer, and estimating the ground state energy of the quantum chemical system on the quantum computer based on the implemented state. The disclosure also encompasses various technologies and techniques for preparing a quantum state for quantum energy estimation on a quantum chemical system and a system for performing these methods.

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 invention discloses a combustible gas / steam mixture multi-target burning and explosion characteristic prediction method and prediction system based on a matrix descriptor, and the method comprises the following steps: collecting burning and explosion characteristic data of a combustible gas / steam mixture, forming a burning and explosion characteristic data set, and dividing the burning and explosion characteristic data set; carrying out molecular structure optimization and frequency analysis, characterizing the molecular structure by adopting quantum chemical descriptors, and screening the quantum chemical descriptors to obtain a plurality of groups of quantum chemical descriptors with linear correlation meeting a threshold requirement; a mixture matrix descriptor of the multi-element combustible mixture is constructed according to the proportion of the components in the multi-element combustible mixture and the pure substance descriptors of the components of the multi-element combustible mixture; constructing a mixture multi-target combustion and explosion characteristic prediction model, testing and evaluating the mixture multi-target combustion and explosion characteristic prediction model by adopting the test set, and verifying the prediction capability of the model; and predicting the combustion and explosion characteristics of the multi-element combustible mixture through the constructed mixture multi-target combustion and explosion characteristic prediction model.

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.

According to the parameterized quantum circuit construction method and device, the storage medium and the computer equipment provided by the invention, the depth of the variational circuit and the number of required quantum bits are reduced by using the unitary matrix linear combination, so that any target quantum state is effectively constructed, the training parameter quantity is reduced, the efficiency and accuracy of the variational sub-algorithm are optimized, and the application prospect is wide. The practicability of the algorithm under limited quantum resources is improved; moreover, the method is especially suitable for medium-scale quantum (NISQ) equipment with noise, and can solve the problem that the application of the prior art on the NISQ equipment is limited by proposing a circuit design with lower depth and quantum bit number, for example, the method can efficiently solve VQA problems such as quantum state learning and Hamiltonian ground state solution on the quantum equipment, and can improve the efficiency of the NISQ equipment. And a new way is opened up for practical application in the fields of quantum chemistry and the like.

The invention discloses a machine learning-based isowurtzitane cage compound reaction substrate prediction method, which comprises the following steps: establishing a database containing condensation reactions of glyoxal and primary amine reaction substrates, marking the condensation reaction of which the product is an isowurtzitane cage compound as 1, and marking the condensation reaction of which the product is other types of compounds as 0; the method comprises the following steps: performing quantum chemistry calculation on primary amine reaction substrates, collecting descriptors describing chemical information, screening feature descriptors, and performing normalization processing; taking the feature descriptor as an input variable, taking a condensation reaction product marking result as an output variable, and selecting a random forest and a factorization machine to carry out weight distribution to construct an optimal fusion model; and performing prediction by using the optimal fusion model. According to the method, the reactivity of the primary amine reaction substrate can be quickly and accurately predicted, the research efficiency is improved, the experiment cost is reduced, and effective guidance is provided for synthesis of the isowurtzitane cage compound.

The invention relates to a method for estimating a ground state energy (10) of a quantum chemical system, the method comprising: classically computing states (4) close to the ground state of the quantum chemical system, assessing the quality of the classically computed states (4) based on the energy distribution of each state (4), selecting a state (4) based on the assessment result, implementing the selected state (5) on a quantum computer (3), and estimating the ground state energy (10) of the quantum chemical system on the quantum computer based on the implemented state (5). Further, the invention relates various methods for preparing a quantum state (4,5) for quantum energy estimation on a quantum chemical system and to a system (1).

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 a method for researching the protection effect of an antioxidant on vegetable oil with different water contents based on quantum chemistry and reaction molecular dynamics. The method comprises the following steps: firstly, constructing basic models by adopting MS software according to chemical structures of triglyceride, water and an antioxidant respectively, then combining the basic models into vegetable oil models containing different proportions of components, and optimizing the models by utilizing a Forcite module in the MS; single-point energy calculation is carried out on molecular structures of the three antioxidants through Gaussian 16, and key molecular characteristic parameters such as molecular surface electrostatic potential distribution and oil-water distribution coefficients are analyzed. Then, LAMMPS software is adopted for molecular dynamics simulation at high temperature, and product information is analyzed. And finally, comparing molecular characteristic parameters obtained by quantum chemistry calculation of different antioxidants under different water contents with reaction process information simulated by reaction molecular dynamics, and comprehensively judging the difference of the protection effects of the antioxidants. According to the method, deep analysis is carried out from a micro level, and a reliable basis is provided for reasonable selection of antioxidants in vegetable oil application.

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 aims to provide a method and equipment for constructing a machine learning force field for a biological system, a medium and a program product, and the method comprises the steps: carrying out the molecular dynamics simulation based on a first biological system, and obtaining a plurality of pieces of corresponding frame information; determining a plurality of pieces of structure information corresponding to each piece of frame information by using a molecular cutting algorithm; calculating system property information corresponding to each piece of structural information by using a quantum chemistry method; based on the system property information corresponding to each piece of structure information, determining a corresponding first sample data set; and training and obtaining a first machine learning force field by using the first sample data set. The research simulation of the biological system is carried out through the first machine learning force field, and the calculation efficiency can be improved while the calculation precision is guaranteed. Moreover, a molecular cutting algorithm is adopted to obtain a large amount of structural information for each frame of information to form training data, so that the generalization ability and prediction precision of a machine learning force field are further 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 combustible gas / steam multi-target burning and explosion characteristic prediction method and system, and the method comprises the following steps: collecting burning and explosion characteristic data of combustible gas / steam, forming a burning and explosion characteristic data set, and dividing the burning and explosion characteristic data set into a training set and a test set; carrying out optimization and frequency analysis on the molecular structure of the combustible gas / steam, characterizing the molecular structure of the combustible gas / steam by adopting quantum chemical descriptors, and screening the quantum chemical descriptors to obtain descriptors with linear correlation meeting a threshold requirement; on the basis of the training set, calculating corresponding screened quantum chemistry descriptor parameter values, and training and constructing a multi-target QSPR model of the combustion and explosion characteristics; testing and evaluating the model by adopting a test set, and verifying the prediction capability of the model; and through the constructed model, predicting the burning and explosion characteristics of the combustible gas / steam and analyzing the micromechanism influencing the burning and explosion characteristics. The method can accurately and quickly predict various burning and explosion characteristics of the combustible gas / steam.

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.