178results about "Cheminformatics programming languages" patented technology

The application discloses a kind of visualization methods for microcosmic action mechanism of steam displacement heavy oil, which comprises: obtaining the porous structure information of rock sample;According to the structure information of rock sample, design pore network structure and make microfluidic chip;Build steam displacement heavy oil visualization implementation system, and adopt steam displacement heavy oil visualization implementation system to collect the phase distribution and temperature distribution of microfluidic chip in displacement process;Boundary extraction is carried out to experimental picture, and the dynamic change process of each phase in displacement process is obtained and the interaction relationship with temperature distribution change is obtained.The application designs pore network chip according to the pore structure information of rock sample, obtains the phase distribution and temperature distribution in displacement process, and is used to study the microcosmic phase distribution characteristics and temperature distribution characteristics of fluid in heavy oil reservoir reservoir, and then the microcosmic mechanism of reservoir fluid movement is explored, so as to provide a practical visualization method for the research of steam drive oil mechanism.

The present application belongs to the technical field of oil and gas field development chemical agent design, and particularly relates to a design method and system of an ultra-low interfacial tension oil displacement agent based on AI4S. A cross-modal retrieval is used to construct a molecular structure-reservoir condition mapping database, high-dimensional embedding vectors are generated by RDKit / ChemBERTa / Mol2Vec to construct a knowledge graph, historical schemes are retrieved by a RAG mechanism and input into a DeepSeek-R1 / Qwen3 large model, an interpretable molecular design and action mechanism are generated, and the feedback closed loop optimization is verified by experiments, so that the data-AI-experiment closed loop is realized, and the research and development efficiency and design accuracy are significantly improved.

The present application relates to the field of information technology services, and discloses a record product risk early warning method and system based on a component library, comprising: extracting a full component list of a record product from product record data to construct a component database corresponding to the full component list by using a preset component matching rule; establishing a component quick search index and a risk feature set of the component database to match potential risk components corresponding to the full component list in the component database; constructing a multi-dimensional risk portrait corresponding to the record product by calculating the compliance correlation degree of each component in the full component list and the potential risk components; and outputting a risk early warning result of the record product according to a risk assessment conclusion corresponding to the record product and the multi-dimensional risk portrait. The present application can greatly improve the initiative foresight and prevention accuracy of record product risk early warning.

The present disclosure relates to a method, system and control device for regulating the performance of carbon sequestration filling slurry, using industrial solid waste as raw material, combining with glauber's salt and alkali residue composite activator, establishing a mapping relationship model of performance index and process parameters, through pre-carbonization and intensified carbonization grading process, considering the pumpability of slurry and the strength of filling body; The system integrates raw material storage metering, mixing and slurry preparation, grading carbonization, conveying and filling, CO2 gas supply and regulation and control modules, realizes full-process closed-loop control relying on online monitoring and model dynamic correction, self-adapts to raw material and working condition fluctuations, can efficiently consume large quantities of industrial solid waste, improve CO2 mineralization and carbon sequestration efficiency, and is suitable for mine goaf cementation filling, and has multiple benefits of resource recycling, carbon emission reduction and engineering stability.

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 application discloses a complex peptide traceable structure coding method, comprising the following steps: analyzing original input data, constructing an intermediate representation object irrelevant to an input format; mapping and processing the intermediate representation object based on a rule base, constructing a standardized molecular graph; serializing the standardized molecular graph, generating a standardized structure string representation, and generating a traceable structure coding result aligned with the standardized structure string representation according to a character position interval, node attributes and edge attributes of the standardized molecular graph and the intermediate representation object. By constructing an intermediate representation object irrelevant to an input format, the inconsistent problem caused by input format differences in traditional methods is solved; the obtained coding result can be directly used for artificial intelligence model input, structure screening, source audit and data archiving, and the computability, traceability and reusability of complex peptide data are improved.

This disclosure provides a nuclear magnetic resonance (NMR) analysis method for establishing the chemical composition and condensed-state structure of fluorine-containing materials and its application. The method includes: placing fluorine-containing materials under different operating conditions in a single-sided NMR spectrometer; under a single-sided inhomogeneous magnetic field environment; presetting parameters for a spin echo pulse sequence; using the spin echo pulse sequence to excite fluorine and hydrogen nuclei in the fluorine-containing material to obtain coupled NMR signals of fluorine and hydrogen nuclei; determining echo peak data from the coupled NMR signals according to the preset parameters; processing the echo peak data according to the structural characteristics of the fluorine-containing material to obtain relaxation spectrum fingerprint data; performing data transformation on the relaxation spectrum fingerprint data to obtain transverse relaxation time data; and establishing a relaxation spectrum fingerprint database and a transverse relaxation time database of the coupling of fluorine and hydrogen nuclei in the fluorine-containing material based on the relaxation spectrum fingerprint data and transverse relaxation time data under different operating conditions.

This invention discloses an adaptive control method and apparatus for the dosage of low-carbon concrete admixtures. The method involves collecting raw materials and performing performance testing to obtain activity coefficients and moisture content parameters. It then identifies moisture content fluctuation ranges to generate compensation coefficients and constructs a mix design baseline to form an initial mix proportion scheme. Based on this initial mix proportion scheme, carbon emission factors for each component are extracted. Multiple admixture combinations are designed, and carbon footprint accounting is performed to establish a relationship curve between admixture dosage and carbon emissions. Performance constraints are obtained, and candidate admixture combinations are screened through performance threshold range determination and performance-carbon emission co-evaluation. Finally, carbon emission minimization screening is performed to obtain the optimal admixture value, which is then corrected using the moisture content compensation coefficient to generate control instructions. This method combines raw material fluctuation compensation, carbon emission accounting, and performance constraint optimization to achieve intelligent control of admixture dosage and low-carbon concrete production.

The present application belongs to the technical field of pollutant control, and discloses a tannery deodorization method and system based on reaction cluster classification and polarity matching. The deodorization method comprises the following steps: step 1: constructing a tannery pollution characteristic database, and collecting characteristic pollution factor concentration data in the environment in real time; step 2: calculating the current odor polarity index and the comprehensive odor load according to the database of step 1 and the collected data; step 3: determining the category of pollutants according to the current odor polarity index calculated in step 2, obtaining the combination ratio of deodorants according to the category of pollutants, determining the odor load state according to the size of the comprehensive odor load and the preset threshold, and obtaining the deodorant spraying parameters according to the odor load state; and spraying the deodorants according to the combination ratio of the deodorants and the spraying parameters. The present application converts parameters into a single polarity control variable, determines the specific deodorant ratio and spraying parameters according to the current pollutant state.

This invention discloses a method and related equipment for processing molecular file information. The method includes: constructing and generating chemical reactions of molecules with different reaction conditions according to the categories of reaction molecules; reading molecular file data from a target folder and extracting three-dimensional and two-dimensional structural information; concatenating the three-dimensional and two-dimensional structural information to obtain two-dimensional and three-dimensional molecular data; combining and arranging the two-dimensional and three-dimensional molecular data according to a reaction plate to obtain reaction data with two-dimensional and three-dimensional molecular information; reading the actual yield of each reaction in the molecular file data, adding the actual yield to the reaction data, and cleaning the reaction data to obtain a target dataset. This invention processes molecular file information to generate a reaction dataset of conditional molecules containing two-dimensional and three-dimensional structural information, and applies these two dimensions of information to deep learning to predict reaction yields, improving the efficiency and accuracy of molecular research.

This invention relates to the field of hydrogen energy technology and discloses a multi-level sequential optimization design method for solid oxide electrolysis systems. The method includes: S1, multi-objective optimization of system-level design parameters; S2, accurate simulation of the entire system process; S3, comprehensive optimization of the heat exchanger network, constructing a comprehensive optimization model for the heat exchanger network; and S4, heat exchanger layer design optimization, including optimization of heat exchanger geometry and heat exchanger channel arrangement. The full-process simulation results and heat exchanger network optimization results are fed back to the system-level multi-objective optimization model to iteratively optimize candidate design parameters. The heat exchanger network optimization results are used as input for heat exchanger layer optimization, achieving cross-level coupling and collaborative optimization between the system layer, heat exchanger network layer, and heat exchanger layer. This method realizes multi-level sequential optimization design of solid oxide electrolysis systems from system operating parameters and heat exchanger network to heat exchanger equipment, effectively improving system energy utilization efficiency and reducing overall operating costs.

The application discloses a catalytic cracking simulation system and method, a system construction method and related devices. The construction method comprises: converting each chemical substance including raw oil and products in the catalytic cracking reaction into corresponding vector data, and storing the raw oil vector data in a pre-built database; constructing a digital twin model of the catalytic cracking reaction device; inputting the raw oil data and reaction condition data in the sample data into an initial catalytic cracking simulation system integrated by the database and the digital twin model, querying the raw oil data by using the database to obtain corresponding vector data, performing a catalytic cracking simulation reaction based on the vector data and the input reaction condition by using the digital twin model, and outputting a prediction result; verifying and optimizing the digital twin model in the initial catalytic cracking simulation system based on the prediction result and the true product result in the sample data, and obtaining a constructed catalytic cracking simulation system. The catalytic cracking simulation system can simulate the catalytic cracking reaction.

The application provides a fragrance reconstruction method, device, medium and product, relates to the technical field of perfume manufacturing, and the method comprises the following steps: obtaining target sample chemical analysis data and olfactory sensory data; determining a sensory contribution weight value according to a GC-O intensity value and a flavor dilution factor value; calculating a sensory contribution value by combining an olfactory threshold, a relative concentration and the sensory contribution weight value; converting an odor description text into a digital fragrance feature vector by using a natural language processing technology, and synthesizing a fragrance profile vector by weighting; based on a raw material database, iteratively calculating a raw material combination by using a multi-objective optimization genetic algorithm according to constraint conditions and optimization objectives of maximizing a predicted fragrance profile vector and the fragrance profile vector similarity and minimizing a cost, to obtain a Pareto optimal formula set. The scheme solves the technical problem of how to stably output a fragrance formula with optimal comprehensive indexes.

This invention discloses a high-trophic-level food chain biomagnification prediction model for organic chemicals. The model comprises the following steps: S1. Dividing the sample into six training samples and three validation samples; S2. Retaining a 1169-dimensional molecular descriptor matrix after screening; S3. Generating an extended pollutant parameter database by combining laboratory biomagnification factors; S4. Forming a position-time normalized sample dataset; S5. Obtaining a fused amplification probability result set; S6. Identifying a candidate set of pollutant amplification paths on the coupled directed graph of amplification probability-flux-stability; S7. Performing uncertainty propagation and confidence assessment on the candidate set of pollutant amplification paths, outputting a priority control list of pollutant amplification paths and their confidence information. This invention addresses the problems of insufficient model coverage and weak extrapolation ability caused by traditional methods relying solely on single molecular descriptors or experimental values.

The application provides a surfactant multi-target selection system based on data economic double driving, which comprises a data acquisition module, a database construction module, a data driving module, an economic driving module, a multi-target decision module and a man-machine interaction module, and through construction of a coal sample physicochemical parameter database, a surfactant physicochemical parameter database and a surfactant efficiency database; current working condition parameters and data in the database are screened based on a data driving mechanism to obtain a surfactant formula set, and cost data are determined based on an economic driving mechanism; according to the surfactant formula set and the cost data, a non-dominated sorting genetic algorithm II (NSGA-II) is used to obtain a Pareto optimal solution set, a target formula is determined from the Pareto optimal solution set and visualized display is performed, so that dynamic and accurate screening of surfactants is realized.

The application discloses a biomass gas coupling coal-fired boiler alkali metal slagging tendency intelligent prediction method and system, relates to the field of slagging tendency prediction, obtains flue gas temperature data of a target area of a boiler convection heating surface, obtains ash fusion characteristic temperature and alkali metal element content data of mixed fuel fed into the boiler, performs self-adaptive correlation calculation of ash temperature-liquid phase yield under physical constraints, calculates coupling adhesion force, generates particle surface equivalent adhesion strength distribution, based on the particle surface equivalent adhesion strength distribution, counts particle turbulent collision physical parameters, determines effective collision adhesion efficiency based on energy competition, calculates the agglomeration growth rate of ash particles in a flow field, outputs ash particle agglomerate spatial growth configuration, according to the ash particle agglomerate spatial growth configuration, performs macroscopic mechanical characteristic analysis and bridge stability determination on the accumulation body of the throat of a cold ash bucket, and outputs an ash bucket blockage risk level, thereby effectively solving the cold ash bucket blockage problem.

The application discloses a preparation method of oil displacement and plugging integrated gel, and particularly relates to the technical field of oilfield chemicals, S1, reaction kinetics parameter solving; S2, dynamic topology network evolution simulation; S3, gel network crosslinking density calculation; S4, gel macroscopic mechanics parameter derivation; S5, pore throat scale plugging state determination. The application solves the reaction probability rate constant of initiation, chain growth, chain transfer and chemical crosslinking, and based on the dynamic simulation of the probability set starting time step promotion, realizes the recurrence of the growth of polymer chain and the network topology evolution process from the molecular reaction kinetics level. The microcosmic simulation mode starting from the chemical reaction mechanism replaces the traditional macroscopic mixing experiment, makes the formation process of the gel network transparent and traceable, and lays a foundation for deeply understanding the influence of the formula parameters on the network structure.

The application discloses a comprehensive detection method and system for neonicotinoid compounds in an environment, and is characterized in that: the coverage of mass spectrum information is improved based on coupling of a multi-module data-dependent acquisition mode and a multi-window data-independent acquisition mode; a suspected screening analysis database is established based on a core structure of neonicotinoid compounds; compounds matched with the suspected screening compounds are detected; and the neonicotinoid compounds in the environment sample to be detected are subjected to non-target analysis based on coupling of a feature molecule network technology in the data-dependent acquisition mode and a feature fragment ion extraction technology in the data-independent acquisition mode, so as to back-propagate candidate compounds different from the target compounds and the suspected screening compounds; and the comprehensive detection of potential neonicotinoid compounds in the environment sample to be detected is realized through target analysis, suspected screening analysis and non-target analysis.

The application provides a high-performance water-based acrylic emulsion formula screening method, comprising the following steps: constructing a multi-source heterogeneous iterable database and differentiating storage; extracting key features from the database and performing cross-scale feature conversion and screening to obtain important key features; taking the important key features as input and the target performance as output, establishing a machine learning model and optimizing; using the optimized model to perform high-throughput virtual screening on virtual formula and process combinations, screening out candidate formulas with synergistic optimization of flame retardancy, hardness and adhesion, preparing water-based acrylic emulsion samples, obtaining the flame retardancy, hardness and adhesion data of the samples, completing verification and analysis; according to the verification data, further updating the database and model based on an active learning strategy, and performing explainability analysis of the machine learning model to guide subsequent experiments; repeating the above steps until the target high-performance water-based acrylic emulsion formula is obtained.

An analysis system, an analysis method, and an analysis program capable of assisting analysis that utilizes knowledge possessed by an experimenter are provided. An analysis system (1) includes a text acquisition unit (114), an extraction unit (115), and a difference evaluation unit (116). The text acquisition unit (114) acquires text data corresponding to each of a plurality of samples. The extraction unit (115) extracts extraction information about the samples from the text data. The difference evaluation unit (116) evaluates a difference between a plurality of pieces of the extraction information.

Disclosed is an apparatus for generating a chemical product passport, the apparatus comprising: one or more computing nodes; and one or more computer-readable media having thereon com puter-executable instructions that are structured such that, when executed by the one or more computing nodes, cause the apparatus to perform the following steps: receiving a request to provide a decentral identifier associated with emission data and a data owner, in response to the request, generating the chemical product passport including the decentral identifier and data related to the emission data; providing the chemical product passport for access by a data consuming service controlled by a data providing service associated with the data owner.

The present application relates to the technical field of material performance prediction, and discloses a method for predicting high-temperature oxidation film stability of an alloy based on theoretical calculation, comprising the following steps: S1: obtaining stable oxides actually formed on the surface of the alloy, corresponding molar mass, metal atom number, density of the alloy, and average atomic weight of the alloy for the alloy composition and a preset high-temperature oxidation environment; S2: obtaining the theoretical density of the oxides according to the initial crystal structure of the oxides; S3: obtaining key parameters for evaluating the protection performance of metal oxides; S4: when the key parameters are less than or equal to a first preset value, the high-temperature oxidation film stability of the alloy is poor; when the key parameters are greater than the first preset value and less than a second preset value, the high-temperature oxidation film stability of the alloy is good; and when the key parameters are greater than or equal to the second preset value, the high-temperature oxidation film stability of the alloy is poor. The present application can efficiently, at low cost, and in advance, screen high-performance oxidation-resistant alloys.

This invention discloses a molecular generation method and apparatus based on a hierarchical consistent diffusion model, belonging to the field of drug discovery. The method includes: acquiring the three-dimensional structural information of a target protein pocket and constructing a protein map; calculating normalized persistent entropy based on the protein map and performing feature mapping through a pre-trained topological proxy network to output pocket topological features; sampling initial noise coordinates from a standard normal distribution and initial discrete states from a uniform distribution to generate a noise atom map and a noise template map; iteratively executing a back-diffusion process using a pre-trained hierarchical consistent diffusion model based on the protein map, pocket topological features, noise atom map, and noise template map to output a ligand atom map and a ligand template map; and performing geometric consistency correction on the ligand atom map based on the ligand template map, and constructing a ligand molecule based on the corrected ligand atom map. Therefore, by implementing this invention, the accuracy of molecular generation can be improved.

Disclosed is a computer-implemented method for providing material identifier package usable for recycling of batteries, the method comprising the steps of: - providing at least one battery identifier and corresponding material configuration data associated with at least one component of the battery to be recycled; - determining at least one material identifier package by relating the at least one material configuration provided by the material configuration data to at least one material configuration processable by at least one plant; - providing the at least one material identifier package usable for recycling batteries including the at least one battery identifier.

This invention relates to the field of computational chemistry data processing technology, and in particular to a DMol3 electron density difference data processing system and file generation method. The system includes: an input module for acquiring electron density files in specific formats for the overall system and each component generated by DMol3 calculations; a processing module for automatically reading the files and performing numerical calculations on the electron density differences; and an output module for simultaneously generating the calculation results into a first format file and a second format file. This invention, through a multi-format parallel output architecture, solves the technical problems of cumbersome post-processing workflows, single result file formats, and incompatibility with visualization software in existing DMol3 electron density difference data, achieving automation of the data processing workflow and cross-platform compatibility for result display.

This invention proposes an ionic liquid screening method for preparing CH4 / N2 separation membranes, belonging to the field of materials technology. The method includes the following steps: determining the initial structure of the ionic liquid, determining the stable structure of the dimer, and calculating the dimer binding energy. This invention is based on density functional theory (DFT) simulations, grounded in the Schrödinger equation, which is theoretically sound and yields highly reliable calculation results. It can quickly screen ionic liquids with differential binding properties for CH4 and N2. The ionic liquid blend membranes prepared from the screened ionic liquids exhibit a promoted transport mechanism, demonstrating excellent CH4 / N2 selectivity and significantly improving the CH4 / N2 separation selectivity of the polymer membrane. It also enhances CH4 permeability to a certain extent.

This application discloses a multi-module combined aquaculture water purification method and system, relating to the field of water purification technology. The method includes: acquiring the rated aquaculture load and module distribution information of multiple aquaculture modules; determining the initial connection topology between the multiple water purification modules through a priori empirical model; collecting real-time monitoring data from the multiple aquaculture modules and calculating the real-time water quality load; optimizing water purification parameters based on simulation analysis; and controlling the aquaculture water purification in the target scenario based on the optimized water purification parameter results. This solves the technical problem of traditional aquaculture water purification methods being unable to dynamically adjust according to the actual load and distribution characteristics of different aquaculture modules, leading to low purification efficiency.

Systems or techniques are provided for spectral analysis. In various embodiments, a system can comprise a memory that stores computer executable instructions and a processor that executes the computer executable instructions. The computer executable instructions can comprise a compression component that compresses the one or more unknown spectra, using an encoder, into one or more compressed unknown spectra in a latent space; and a search component that matches the one or more compressed unknown spectra with one or more compressed known spectra to obtain one or more candidate matches of the sample.

The present invention relates to a chemical reaction prediction system, a control method thereof, and a learning method for a chemical reaction prediction system. More specifically, the present invention relates to a chemical reaction prediction system that performs forward reaction prediction based on electron flow, a control method thereof, and a learning method for a chemical reaction prediction system.