277results about "Chemical structure search" patented technology

The invention discloses a multi-component catalyst active site prediction system and method fused with quantum embedding, and relates to the technical field of catalysis and material informatics, and the system comprises a structure and site enumeration module which generates candidate sites; the adaptive quantum embedding calculation module obtains key reaction microcosmic parameters; the unified site fingerprint and feature engineering module constructs and fuses standard site fingerprints; the physical consistency machine learning module predicts adsorption energy and other parameters and uncertainty thereof; the active learning and sample selection module selects a high-value sample optimization model; the microdynamics evaluation module calculates index values such as activity; and the multi-objective optimization and sorting module generates an optimization sorting list. According to the method, the unification of calculation precision and efficiency is realized, the problem of non-unification of locus characterization is solved, the model interpretability and extrapolation reliability are improved, and the comprehensive evaluation and optimization sorting of multi-target performance are completed.

The invention discloses a construction method and system for volatile organic compound release behavior characterization, and belongs to the technical field of air analysis and risk assessment. According to the method, feature analysis is carried out based on multi-source information such as a molecular structure, a release carrier and environmental conditions, modeling is carried out on a release process by utilizing a mapping operator, and a three-dimensional representation vector V = [I, S, E] reflecting release intensity, environmental sensitivity and time evolution is constructed. The representation is output in a behavior vector or digital label mode, and unified quantitative benchmarking of different substances in a cross-scene mode is achieved. According to the method, depth characteristics such as molecular polarity and desorption activation energy are introduced, so that the dependence on long-period environmental chamber experiments is reduced, the generalization prediction capability on unknown pollutants is improved, the logic connection problem between a bottom-layer physical mechanism and an upper-layer intelligent management and control system is solved, and the reliability of the system is improved. And standardized and explainable behavior input is provided for prospective risk research and judgment.

The invention belongs to the technical field of traditional Chinese medicine information processing, and provides a traditional Chinese medicine disease prescription data base construction method and system.The method comprises the steps that five types of data including ancient literatures, modern medical records, prescription data, traditional Chinese medicine resources and medical record manuscript images are accessed through an extensible adapter frame; a traditional Chinese medicine term service platform is constructed by using multi-source term resources, and standardized data is generated from the analyzed data; the method comprises the following steps: extracting diseases, syndromes, prescriptions and traditional Chinese medicine entities by adopting a rule engine and a domain self-adaptive entity recognition model, on the basis of a public traditional Chinese medicine standard knowledge graph, aggregating neighbor node information through GAT, and introducing a contrast learning optimization entity relationship classifier to obtain an enhanced entity vector and classify a semantic relationship; constructing a knowledge graph based on the extracted semantic relationship; and carrying out data quality and algorithm performance monitoring and tracing on data access analysis, standardization processing, knowledge extraction and graph construction. Uniform access and standardized integration of multi-source heterogeneous traditional Chinese medicine data are realized.

The invention belongs to the technical field of high voltage and insulation, and relates to an XLPE breakdown field strength evaluation method and system based on gel content and preparation process, and the method comprises the following steps: S1, sampling, weighing, shearing and bagging; s2, extracting, weighing and calculating the gel content; s3, constructing an evaluation model; s4, predicting the breakdown field intensity; according to the technical scheme, the physical model fusing the cross-linking enhancement effect and the thermal damage effect is constructed, the breakdown field strength is predicted based on the physical model, accurate and rapid evaluation of the XLPE insulation performance under different process conditions can be achieved only through a small amount of breakdown test data calibration model, dependence on a traditional destructive electrical test is remarkably reduced, and the reliability of the XLPE insulation performance is improved. The test cost is greatly reduced, the research and development period is greatly shortened, and an effective tool is provided for cable insulation material performance analysis and production process optimization.

A method performed by at least one processor, includes receiving a query comprising at least one of a product, a reactant, a reagent, and a reaction condition; generating a query embedding vector corresponding to the query by inputting the query into a neural network model; extracting a candidate embedding vector from among a plurality of embedding vectors based on a similarity between the query embedding vector and the plurality of embedding vectors corresponding to reaction records stored in a database; and outputting a synthesis recipe corresponding to the query by retrieving a candidate reaction record corresponding to the candidate embedding vector in the database.

The invention belongs to the technical field of biology, and discloses a non-natural pathway generation method and system based on a continuous biological template, and the method comprises the following steps: obtaining an enzymatic reaction data set, and preprocessing the enzymatic reaction data set; constructing a directed reaction diagram on the basis of the preprocessed enzymatic reaction data set, performing similar compound search on a target compound by utilizing the directed reaction diagram, and obtaining a continuous group conversion template of the similar compound in the natural enzymatic pathway by taking the searched similar compound as a starting point and combining a depth-first search mode; the continuous group conversion template is applied to a target compound in a molecular linear input specification form, and an inverse synthesis process of the target compound is simulated to generate a non-natural synthesis pathway based on the continuous group conversion template. The method not only enhances the biological feasibility and construction success rate of the approach, but also has universality, expandability and engineering potential, and provides a generalizable normal form for the field of synthetic biology.

The invention discloses a multi-target joint optimized antibiotic molecule design system and method applied to the field of biological medicine, and the method comprises the steps: obtaining FabI enzyme and AcrAB-TolC efflux pump structure data, extracting double-target space and physicochemical characteristics, and constructing a joint pharmacophore model containing a FabI inhibition domain and an efflux pump blocking domain; screening candidate molecules meeting a double-domain space matching threshold, screening high-affinity double-target molecules through conformation sampling and free energy calculation, and forming a lead compound library through multi-layer filtration of metabolic stability, membrane penetrability, quantum chemical properties and synthesis feasibility; carrying out electron effect, chain length or heteroatom fine tuning on dominant molecules through in-vitro bacteriostasis and efflux inhibition experiment feedback, and carrying out iterative optimization until MIClt is met; 2 [mu] g / mL and the efflux inhibition rate is gt; according to the present invention, the antibacterial effect and the drug resistance inhibition ability are significantly improved, the molecular synthesizability and the biological safety are ensured, and the engineering design new path is provided for the Gram-negative bacterium drug resistance crisis.

The invention relates to the technical field of fluorescent probes, and provides a fluorescent probe luminescence brightness quantification method and system for coupling excitation wavelength detuning. The fluorescence probe luminescence brightness quantification method for coupling excitation wavelength detuning comprises the following steps: constructing an initial structure of a probe molecule, and optimizing a geometric structure of a ground state of the probe molecule to obtain a stable configuration of the ground state of the probe molecule; based on the stable configuration of the ground state of the probe molecule, the excitation states are calculated, and the excitation energy of the lowest n excitation states of the probe molecule and the absorption transition dipole moments of the probe molecule in the X, Y and Z directions are obtained; based on the stable configuration of the ground state of the probe molecule, optimizing the geometric structure of the lowest excited state of the probe molecule to obtain the emission energy of the lowest excited state of the probe molecule and the emission transition dipole moments of the probe molecule in the X, Y and Z directions; and calculating a luminance index in combination with the energy parameter and the transition dipole moment parameter so as to select an optimal probe. Therefore, accurate and rapid prediction of the luminescence brightness of the probe is realized.

The invention discloses an explanation method for damage threshold improvement of a fused quartz material in a femtosecond laser processing / welding process. By establishing a fused quartz electron-lattice heat transfer model under femtosecond laser irradiation, a dissociation model of environment molecules and interstitial molecules under the action of femtosecond laser and a defect-containing fused quartz molecule dynamic reaction model based on a ReaxFF reaction force field, atomic structure changes in a system before and after a reaction are analyzed; and finally, obtaining a chemical reaction mechanism of the fused quartz containing the defects under the action of the femtosecond laser, and explaining the phenomenon that the damage threshold of the fused quartz is increased after the fused quartz is irradiated by the low-flux femtosecond laser. According to the method, the research in the current fused quartz femtosecond laser processing / welding process is perfected, and meanwhile, the theoretical blank that the damage threshold lifting mechanism is not clear in the fused quartz glass femtosecond laser processing / welding process is filled up.

The invention relates to the field of computational energy chemistry and material preparation, and discloses a method for screening a chemical looping gasification oxygen carrier through machine learning. Comprising the steps of system configuration and initialization, sample database construction, model loading and training, to-be-screened oxygen carrier data set construction, data preprocessing, oxygen carrier performance prediction, multi-condition screening, result output and visualization and the like. According to the method, the screening efficiency of the chemical-looping gasification oxygen carrier is greatly improved, the screening cost of the chemical-looping gasification oxygen carrier is remarkably reduced, and the method also has the characteristics of multi-index collaborative optimization, high expansibility and result visualization.

A method for computational drug design includes defining a population of a plurality of compounds. Each compound includes one or more molecular properties. The method includes defining a training set of compounds from the population for which one or more biological properties are known. The method includes selecting, from the population, a subset of one or more compounds that are not in the training set. The method includes determining a subset score of the selected subset based on molecular properties of the one or more compounds in the selected subset, and evaluating the selected subset based on the determined subset score. The subset score is determined based on a frequency of the molecular properties in the population and on a frequency of the molecular properties in a sampled set comprising the training set and the selected subset.

The invention relates to the technical field of medical artificial intelligence, in particular to a drug discovery task processing method, device and equipment based on large model reasoning, and the method comprises the steps: obtaining a drug discovery task instruction of a user; the drug discovery task instruction is input to the target large model, the target large model outputs an execution result of a drug discovery task, and the reasoning process of the target large model comprises the steps that the drug discovery task instruction is analyzed to obtain an instruction intention and instruction parameters, a target key matched with the instruction intention is selected from a parameterized memory pool based on the instruction intention, and the target key is input to the target large model; the instruction parameter is mapped into a target key value, a target calling tool format is generated based on the target key and the target key value, and a corresponding target discovery tool is called based on the target calling tool format to execute a drug discovery task; and sending an execution result of the drug discovery task to the user. According to the method, the target large model automatically executes the reasoning process, various tools are automatically called, and intelligent drug discovery is achieved.

A system, device, method, and program for acquiring feature data for material composition information based on artificial intelligence are disclosed. The system may include a memory configured to store a first artificial intelligence (AI) model configured to output first feature data for composition information of a material and a second AI model configured to output second feature data for structure information of the material; and a processor configured to learn the first AI model and the second AI model. The processor may be configured to learn the first AI model based on the second feature data for the structure information of the material output by the second AI model, and / or to learn the second AI model based on the first feature data for the composition information of the material output by the first AI model.

This invention discloses a method for predicting the molecular structure-modulus performance relationship of glass fibers based on graph neural networks, comprising the following steps: screening composition-modulus data for multi-component glass fiber systems from a database; constructing graph data based on the screened composition data; and predicting the modulus using a graph neural network based on the graph data. This invention innovatively proposes an improved graph data construction method, introduces joint modeling of "node representation + edge features + composition vectors," introduces a triple information fusion of "local-global-composition," and introduces structural consistency regularization. This allows the model to consider both the direct contribution of local structure to the modulus and the regulatory effect of the overall composition on macroscopic performance, thereby improving prediction accuracy and generalization. This invention maintains high prediction accuracy and physical rationality, demonstrating strong generalization ability and practical application value.

To provide a computer-based method for determining an optimal sunscreen composition comprising multiple UV filter substances on the basis of constraints and objectives.SOLUTION: A computer-based method for determining a sunscreen composition comprising multiple UV filter substances comprises the steps of: selecting a constraint for a characteristic of the composition including a sunscreen performance target; selecting an optimization objective; and automatically determining the sunscreen composition as a composition of filter substances from a set of filter substances, such that the composition meets the constraint and is optimized with respect to the selected optimization objective. The automatically determining step comprises the steps of: generating multiple candidate compositions; determining sunscreen performance of the candidate compositions using a performance simulation tool; and comparing the determined sunscreen performance of the candidate compositions with the sunscreen performance target.SELECTED DRAWING: None

The invention relates to the technical field of safe conveying of oil and gas pipelines, in particular to a polypeptide type hydrate kinetic inhibitor screening method based on molecular simulation, which comprises the following steps: selecting target protein related to hydrate growth, and designing a polypeptide sequence; performing polypeptide pre-screening; evaluating the binding affinity and binding mode of the polypeptide and the target protein; performing MD simulation on the screened high-affinity polypeptide; verifying the binding affinity of the polypeptide and the target protein; and collecting all experiment and simulation data for statistical analysis, and optimizing the polypeptide sequence. The structure and function of the target protein are systematically analyzed by using a bioinformatics database and tools, it is ensured that the selected target plays an important role in hydrate formation, and meanwhile, a polypeptide sequence designed based on the target protein structure can effectively improve the binding capacity; and in the pre-screening and docking analysis process of the polypeptide, dynamic parameters are simulated and extracted by molecular dynamics, so that the interaction between the polypeptide and the target protein can be deeply understood.

The present invention relates to a method for searching for a structural gene of glass, including the following steps: determining atomic species for structure search according to the glass system; screening structure on the basis of the first principle to screen out compounds that can be formed by the interaction among each of the atoms; comparing the formation energy and the phonon spectrum of each compound to obtain stable compounds; and constructing a metastable composition diagram of a glass system according to the stable compounds, in metastable composition diagram, a micro-structural unit of a glassy compound near a target glass composition point is the structural gene of glass in the metastable glass composition diagram; designing glass properties based on the characteristics of the structural genes; and realizing the design of high-performance glasses through a hot-melt method.

The invention discloses an acidophilic protein recognition method, device and equipment. The method comprises the following steps: constructing a data set which takes acidophilic protein as a positive sample and takes thermophilic, halophilic and basophilic protein as a negative sample, and preprocessing the data set; dividing the data set into a training set and a test set according to a preset proportion; performing feature coding on the protein sequence in the data set by using a pre-trained ESM C model, extracting deep semantic features, and generating high-dimensional embedded representation; learning high-dimensional embedding representation through an adversarial network DCGAN-GP to perform data enhancement, and obtaining a pseudo-negative class sample; combining the pseudo negative sample and the data set to obtain a combined set, and inputting the combined set into a lightweight shared sparse hybrid expert model for training to obtain a trained lightweight shared sparse hybrid expert model; and inputting a to-be-identified protein sequence into the trained lightweight shared sparse hybrid expert model to obtain an acidophilic protein prediction result. According to the method, efficient prediction of the acidophilic protein can be realized.

The invention discloses a method for identifying a molecular structure and constructing a reaction network based on atomic coordinates, and belongs to the technical field of material simulation. According to the method for recognizing the molecular structure based on the atomic coordinates, by obtaining trajectory data, atoms outside a box are converted into atoms inside the box through minimum mirror agreement; grids are divided according to a space truncation radius, potential bonding atoms are accurately screened, and redundancy of distance calculation between every two atoms of the whole system is avoided; atomic clusters are quickly divided in combination with depth-first search, and molecular structure recognition is achieved. The method only depends on basic data such as atomic coordinates and does not depend on a simulation software post-processing module, and the limitation that only a single simulation system is adapted in the prior art is broken through. According to the method for constructing the reaction network, molecular structure description is compared frame by frame, and invalid reactions are offset and filtered through positive and negative reactions to obtain net reactions; counting the net reaction times to determine the reaction probability so as to quantify the tendency of the reaction; and constructing a reaction network by taking the molecular structure as a node and the reaction frequency as an edge weight.

An information processing device includes at least one memory and at least one processor. The at least one processor is configured to acquire information about a search target including at least information on a chemical element from another information processing device, repeatedly execute acquisition of a plurality of structures of a substance each containing the chemical element, update of the plurality of structures of the substance, and evaluation of the updated plurality of structures of the substance using a neural network, until a predetermined condition is satisfied, and after the repeated execution, transmit information about a searched structure of a substance and information about an evaluation value of the searched structure of the substance to the other information processing device. The at least one processor executes the acquisition based on the evaluation in the repeated execution.

This invention provides a system and program that facilitates the process of generating and / or visualizing molecular networks for library molecular structure content. [Solution] In system 500, the molecular network generation system 502 for library molecular structure content includes an evaluation component 512 that performs a comparison between a first molecular fingerprint including first molecular structure data of a first molecular structure and a second molecular fingerprint including second molecular structure data of a second molecular structure, and a visualization component 516 that generates display data that visualizes a representation of the structural similarity score obtained from the first molecular structure, the second molecular structure and the comparison. The representation by the visualization component includes edges corresponding to the structural similarity score that extend between pairs of nodes corresponding to the first molecular structure and the second molecular structure.

This material designing device is provided with: a search unit (121) that sets a generation condition (21) for generating a three-dimensional structure (23) of a material, the generation condition (21) including information indicating at least one of the characteristic and structure of the material; a cross-sectional image generation unit (123) that generates a cross-sectional image (22) of the material on the basis of the generation condition (21) set by the search unit (121); and a three-dimensional structure generation unit (124) that generates the three-dimensional structure (23) of the material on the basis of the cross-sectional image (22) generated by the cross-sectional image generation unit (123).

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for computationally docking a small molecule or ligand to a prion-protein In one aspect, a system comprises receiving data comprising a structure of a candidate drug, a structure of a prion-protein filament comprising one or more prions, and a location of a binding site in the prion-protein filament structure, generating a plurality of stacked pose configurations of the candidate drug using at least the candidate drug structure, determining a corresponding docking score for each stacked pose configuration in the plurality of stacked pose configurations in accordance with a measure of a likelihood of binding for the stacked pose configuration in the location of the binding site in the prion-protein filament, and taking an action based on the corresponding docking scores.

A foundation model for performing molecular-level tasks by learning multimodal data in the form of one-dimensional text and two-dimensional graphs, and a system therefor, according to an embodiment of the present invention, enable various molecular-unit tasks such as chemical reaction prediction, molecular attribute prediction, and natural language description generation to be effectively processed through a single foundation model. In addition, it is possible to increase prediction accuracy of the model by maximizing utilization of two-dimensional molecular graph information, and automatically generate, on the basis of statistical sparsity, high-quality descriptive text that emphasizes core and distinctive features of each molecule.

The invention discloses an acoustic topological acoustic fiber device based on a microstructure. The acoustic topological acoustic fiber device comprises a plurality of primitive cells arrayed in the Z direction. Each primitive cell is of a multi-layer honeycomb lattice structure and comprises an A-layer assembly, a middle-layer assembly, a B-layer assembly and a middle-layer assembly which are sequentially stacked from top to bottom. Pi phase difference delay exists between the A-layer assembly and the B-layer assembly. The middle layer assembly is constructed to be of an integral structure formed by connecting a plurality of coupling units. Seen from an X-Y plane, the primitive cell is constructed to be composed of a plurality of non-periodic structural units; rotation parameters are introduced into the structural units, so that the centers of the primitive cells have vortex centers, and the vortex centers are connected in the Z direction to form vortex lines. The acoustic topological acoustic fiber device disclosed by the invention can transmit in the center of the device in a defect immune manner without a magnetic field.

One embodiment of the present invention provides a structure information processing device capable of easily grasping a division result of structure information, a method for operating the structure information processing device, a user terminal device, and a server device. A structure information processing device according to one embodiment of the present invention is a structure information processing device for a compound, the structure information processing device comprising a processor and a non-transitory and tangible memory, wherein the processor: refers to the memory to acquire structure information of the compound; divides the structure information into a plurality of partial regions on the basis of designated division conditions; causes a display device to display the divided structure information; and, in the display, identifies and displays at least some of the plurality of partial regions in accordance with the result of the division.

According to a molecular comparison system and a method thereof provided by the present disclosure, after a substance analysis result is obtained, on the basis of a molecular list and matching degree values as well as related questions and corresponding weights in a knowledge management system, a correlation database is used to determine and calculate by means of an AI LLM, so as to further determine the molecular species of a compound causing damage.

A method for searching for ferroelectric materials, such as wurtzite crystal structures, that have low coercive fields and high spontaneous polarization values ​​using first-principles calculations is provided. [Solution] The method includes a first extraction step of obtaining, from a crystal structure database, ferroelectric material candidates with non-centrosymmetric symmetry as first candidates; a calculation step of calculating the band gap value, polarization reversal barrier energy value, and spontaneous polarization value of each first candidate obtained in the first extraction step using first-principles calculations; an insulating property determination step of determining whether the calculated band gap value satisfies insulating properties; a polarization reversal determination step of determining whether the calculated polarization reversal barrier energy value is within a range in which polarization reversal is possible; a spontaneous polarization determination step of determining whether the calculated spontaneous polarization value is within a range in which ferroelectric properties are exhibited; and a second extraction step of extracting, as ferroelectric materials, first candidates for which the determination results in the insulating property determination step, polarization reversal determination step, and spontaneous polarization determination step are all acceptable.

The invention discloses a multi-performance target optimization method, device and equipment for a high polymer material and a storage medium. The multi-component multi-performance target optimization method for the high polymer material comprises the following steps: obtaining substandard performance parameters which do not reach a corresponding performance threshold in determined current performance parameters; determining a corresponding recommended component content for each substandard performance parameter; judging whether the current fitness of the current performance parameter is greater than a fitness threshold value or not; if yes, according to the content of each group of recommended components corresponding to each substandard performance parameter, optimizing and adjusting the content of each to-be-optimized component according to an aggressive adjustment strategy to obtain a corrected data set; if not, according to the content of each group of recommended components, a correction data group is obtained according to a weighted balance adjustment strategy; and if the correction performance parameters in the correction data set all reach the corresponding threshold values, ending the optimization. According to the optimization method provided by the invention, a reliable optimization result can be efficiently obtained under the condition that excessive sample data is not needed.

The invention provides an ecological risk evaluation method and system based on new pollutants, and the method comprises the steps: obtaining mass spectrum data of sample data, determining a normal mass spectrum fingerprint corresponding to a geographic position and time, marking an ion peak as an unknown peak when the ion peak in the mass spectrum data deviates from a preset range of the normal mass spectrum fingerprint, and determining that the ion peak is an unknown peak; the method comprises the following steps: acquiring a fragmented spectrum of an unknown peak based on secondary mass spectrometry, inferring a possible molecular structure of the unknown peak through a graph neural network model in combination with a preset chemical database, and constructing a quantitative structure-activity relationship of possible molecular structure analogues of the unknown peak based on a preset structural similarity network. The method comprises the following steps: acquiring predicted toxicity and signal channels influenced by the predicted toxicity, performing ecological risk assessment in a preset range of a petrochemical plant based on the predicted toxicity and the signal channels influenced by the predicted toxicity, and acquiring potential ecological risks of new pollutants. And a basic basis is provided for environment management and decision making.