138 results about "Chemical property" patented technology

The invention discloses a method and a system for determining the reaction activity of material molecules based on quantum computing, and relates to the technical field of material performance analysis based on quantum computing, and the method comprises the following steps: generating UCCSD (Unified Conduction Cathode Spectroscopy) simulation according to an electronic structure of molecules of a target material; obtaining at least one effective excitation operator based on parameters in the coefficient of each excitation operator in UCCSD simulation and by combining all the excitation operators; constructing a quantum circuit according to all the effective excitation operators; determining energy level distribution of molecules of the target material based on the quantum circuit; and determining the reaction activity of the molecules of the target material according to the energy level distribution of the molecules of the target material. According to the method, in the process of obtaining the effective excitation operator, an ADAPT-VQE algorithm does not need to be executed, so that the analysis cost of the physical and chemical properties of the material can be reduced, and the analysis efficiency of the physical and chemical properties of the material can also be improved.

The invention relates to the technical field of physicochemical property detection, in particular to a full-automatic smoke dust detection method and a tester, and the method comprises the following steps: acquiring the concentration, temperature and relative humidity data of the inner wall of a flue, and preprocessing; dividing the temperature sequence into a plurality of temperature subsequences, and obtaining a concentration subsequence and a relative humidity subsequence of a corresponding bit sequence; obtaining a noise content index of a single temperature subsequence; obtaining the size of a filtering window of the filter in a single temperature sub-sequence; acquiring peak values and valley values of all the concentration subsequences and the relative humidity subsequences, and acquiring in-peak elements of all the peak values; acquiring a violent index of each peak value; acquiring a humidity irrelevant coefficient of a single concentration subsequence; acquiring a concentration correction factor of a single concentration subsequence; and correcting each concentration sub-sequence. According to the method, the concentration correction factor can be adaptively adjusted according to different process parameters, so that the detection precision of the smoke concentration is improved.

The invention discloses a method for testing physical and chemical results of a steel sample blank after heat treatment. The method comprises the following steps: step 1, preparing the steel sample blank; 2, the steel sample blank is pretreated; 3, the steel sample blank is subjected to heat treatment, then the steel sample blank is tested, and a test result is recorded; step 4, optimizing process parameters of heat treatment according to a test result; according to the method, the physical and chemical property change rules of steel sample blanks with different sizes under the fixed heat treatment condition are verified, the influence of different heat treatment schemes on the properties of the steel sample blanks with the fixed sizes is evaluated, finally test data are analyzed, heat treatment process parameters are optimized, and the heat treatment efficiency is improved. A technological method capable of accurately judging the influence rule of the size of the steel sample blank on the physicochemical result after heat treatment is formed.

The embodiment of the invention provides a catalyst activity analysis method and system based on material surface physical and chemical indexes, and relates to the technical field of water treatment. According to the method, a sample data set can be obtained firstly, after the sample data set is divided into a training set and a test set, the training set is used for training a plurality of alternative models, and then a prediction model is selected from the alternative models. And inputting data of a catalyst to be detected into the prediction model to obtain a predicted degradation rate output by the prediction model. Wherein the sample data set comprises surface physical property parameters such as pore depth gray difference of the catalyst and surface chemical property parameters such as functional group peak height ratio. According to the method, alternative model training can be carried out through Bayesian optimization, a prediction model is selected by combining evaluation indexes obtained by calculation of a test set, and a machine learning process can be enhanced by utilizing multi-mode fusion data in an environment of small sample machine learning data volume, so that the prediction precision and generalization ability of catalyst activity analysis are improved.

A method of operating an analytical instrument comprises ionising a sample to produce sample ions; (i) performing a first ion separation scan by separating sample ions according to a first physico-chemical property, and analysing the separated sample ions by performing one or more MS1 mass analysis scans; and (ii) performing a second ion separation scan by separating sample ions according to the first physico-chemical property, and analysing the separated sample ions by performing a plurality of MS2 mass analysis scans. Each MS2 scan of the plurality of MS2 mass analysis scans uses one MS2 isolation window of a plurality of MS2 isolation windows. The method further comprises analysing MS1 data acquired from the one or more MS1 mass analysis scan(s), and configuring the plurality of MS2 isolation windows based on the analysis of the MS1 data.

The invention relates to the technical field of dissolvable organic matters, and discloses a method for exploring photochemical reactivity of microplastic derived dissolvable organic matters, which comprises the following steps: S1, sample preparation: selecting microplastic as a source of the dissolvable organic matters, and generating MP-DOM through a leaching experiment; different types of MP-DOM samples are subjected to illumination treatment, and the DOM samples before and after illumination are analyzed through Fourier transform ion cyclotron resonance mass spectrometry; s2, generating a molecular formula data set: calculating a plurality of molecular parameters for describing chemical characteristics of each molecular formula by using molecular formula data generated by Fourier transform ion cyclotron resonance mass spectrometry; according to the method for exploring the photochemical reactivity of the micro-plastic derived soluble organic matter, the FT-ICR-MS technology and the machine learning algorithm are combined, the RF model is superior to other models in predicting the MP-DOM photochemical reactivity, the complex DOM photochemical reactivity can be effectively analyzed, and a more accurate prediction result is provided.

Sub-millimeter scale three-dimensional (3D) structures are disclosed with customizable chemical properties and / or functionality. The 3D structures are referred to as drop-carrier particles. The drop-carrier particles allow the selective association of one solution (i.e., a dispersed phased) with an interior portion of each of the drop-carrier particles, while a second non-miscible solution (i.e., a continuous phase) associates with an exterior portion of each of the drop-carrier particles due to the specific chemical and / or physical properties of the interior and exterior regions of the drop-carrier particles. The combined drop-carrier particle with the dispersed phase contained therein is referred to as a particle-drop. The selective association results in compartmentalization of the dispersed phase solution into sub-microliter-sized volumes contained in the drop-carrier particles. The compartmentalized volumes can be used for single-molecule assays as well as single-cell, and other single-entity assays.

The invention provides a molecular property prediction method and device based on chemical bond characterization learning. The method comprises the following steps: carrying out standardization processing on simplified molecule linear input standard data of a target molecule to obtain standardized data of the target molecule; based on a predetermined key classification standard, the standardized data is converted into chemical bond characterization data, and the predetermined key classification standard is used for classifying chemical bond features; and predicting the chemical property of the target molecule based on the chemical bond characterization data to obtain a prediction result.

Disclosed herein are molecularly coated surfaces, methods of coating surfaces, and methods of using coatings on surfaces. In some embodiments, the coated surfaces are useful in applications to avoid blemishes on gemstones, confer antimicrobial activity on a surface, confer a therapeutic property to a surface, detect an analyte, change the color of a surface, and or to change the physical and / or chemical properties of a surface.

The invention relates to the technical field of ultrahigh-temperature ceramic material melting point testing, in particular to ultrahigh-temperature melting point testing equipment and method, and the ultrahigh-temperature melting point testing equipment comprises a vacuum system, a high-temperature generation system, a multi-channel high-temperature measurement system, a melting point calibration system and a control system; the vacuum system is responsible for providing a vacuum environment for the sample and avoiding the influence of the environment on a test result; the high-temperature generation system is responsible for emitting a laser beam to the surface of a sample to melt the sample, and can instantly generate a high temperature of thousands of DEG C to meet the test requirement of a high-melting-point material; the multi-channel high-temperature measuring system is responsible for recording a time-temperature curve in a sample melting process; the melting point calibration system is responsible for recording the melting state of the sample and is used for accurately calibrating the melting point of the sample in cooperation with the multi-channel high-temperature measurement system to overcome the influence of an intermediate medium on a measurement result; the problem that in the prior art, melting point testing equipment cannot accurately test the physical and chemical properties of ultra-high-temperature ceramics in a high-temperature environment exceeding 4000 K is solved.

Multivariate machine learning (ML) techniques can be applied to an XRF spectra and mitigate matrix effects and enable simultaneous quantification of composition, even when markers elements or ions of interest are imperceptible in the XRF spectra. Physical (e.g., density) and chemical (e.g., total dissolved solids and hardness) properties of the material can be also quantified using ML techniques.

An automated computer-controlled sampling system and related methods for collecting, processing, and analyzing agricultural samples for various chemical properties such as plant available nutrients. The sampling system allows multiple samples to be processed and analyzed for different analytes or chemical properties in a simultaneous concurrent or semi-concurrent manner. Advantageously, the system can process soil samples in the “as collected” condition without drying or grinding. The system generally includes a sample preparation sub-system which receives soil samples collected by a probe collection sub-system and produces a slurry (i.e. mixture of soil, vegetation, and / or manure and water), and a chemical analysis sub-system which processes the prepared slurry samples for quantifying multiple analytes and / or chemical properties of the sample. The sample preparation and chemical analysis sub-systems can be used to analyze soil, vegetation, and / or manure samples. A soil collection system is disclosed which captures and directs samples to the sampling system for processing.

The invention belongs to the technical field of analysis of harmful residues of food and medicine homologous substances, and particularly relates to a rhizoma kaempferiae standard sample containing a harmful pollutant lead and a preparation method of the rhizoma kaempferiae standard sample. According to the method, a sample preparation mode of raw material collection, raw material verification, sample pretreatment, vacuum freeze drying, coarse crushing, sieving, uniform mixing, fine crushing, re-sieving, uniform mixing and sub-packaging is adopted, so that the matrix effect and good uniformity and stability of the sample are ensured. By adopting the growth environment characteristics of the actual sample and the growth enrichment rule of the plant, the obtained raw material can have the matrix effect consistent with that of the actual sample, and the expected use purpose is met; the prepared standard sample can maintain the physical and chemical characteristics during long-term storage, so that the stability of the target element lead is ensured; a two-step crushing-sieving-uniform mixing preparation process is adopted, so that sufficient uniformity of the prepared standard sample is fully ensured, and various use requirements of a quality control sample, a proficiency testing sample, a standard sample and the like can be met.

Provided are: a learned model, with which index data relating to the kinetics of contents in a container can be evaluated with high accuracy; an estimation device; and an estimation method. This learned model is trained using, as an explanatory variable, at least one of data relating to the shape of a stirrer provided in a container, data relating to the shape of a sparger provided in the container, data relating to the shape of the container, and data relating to the physical properties, the composition, the chemical properties, the biochemical properties or the concentration of contents accommodated in the container, and also using, as an objective variable, a mass transfer capacity coefficient (kLa), a stirring power (P / V), a respiratory rate, the concentration of bacterial bodies, the concentration of a product from the bacterial bodies and cells, or a titer.

The present invention discloses a method for effectively estimating the soil nitrate nitrogen assimilation rate, which comprises the following steps: (1) obtaining the physicochemical properties of organic matter; (2) obtaining the nitrate nitrogen assimilation rate of soil nitrate nitrogen; 15 Organic nitrogen using N tracer technology 15 The N recovery method calculates the soil nitrate nitrogen assimilation rate under the input of organic materials; (3) the data of step (1) and step (2) are input into SIMCA software, and the importance of the physical and chemical properties of organic materials to the soil nitrate nitrogen assimilation rate is evaluated using projection importance analysis to obtain a VIP diagram; (4) the physical and chemical properties of organic materials that best affect the soil nitrate nitrogen assimilation rate are determined based on the VIP diagram, and a regression equation is established. The present invention uses laboratory analysis and regression model establishment methods to quickly and effectively estimate the soil nitrate nitrogen assimilation rate, which can overcome the cumbersome field operations and technical deficiencies, and no longer requires the addition of organic materials in the subsequent evaluation of the soil nitrate nitrogen assimilation capacity under the input of organic materials. 15 N markers, save costs, and thus have good promotion and practical significance.

The application provides a metal nanomaterial toxicity prediction method and device, the method comprises the following steps: collecting related data affecting the toxicity of the metal nanomaterial, wherein the related data comprises the physical and chemical properties of the metal nanomaterial, the interaction mode between the metal nanomaterial and organisms, the influence data of external environmental factors on the metal nanomaterial, and the selective reaction data of the metal nanomaterial between different organisms; screening target indexes from the related data and calculating the weights of the target indexes; inputting the target indexes and the weights corresponding to each target index into a pre-trained toxicity prediction model to obtain a metal nanomaterial toxicity prediction result. It can be seen that the application considers multiple dimensions and calculates the weights of the indexes, the indexes considered are more comprehensive, and the index weights can better reflect the influence degree of each index on the toxicity of the metal nanomaterial, thereby improving the accuracy of the model toxicity prediction.

An automated computer-controlled sampling system and related methods for collecting, processing, and analyzing agricultural samples for various chemical properties such as plant available nutrients. The sampling system allows multiple samples to be processed and analyzed for different analytes or chemical properties in a simultaneous concurrent or semi-concurrent manner. Advantageously, the system can process soil samples in the "as collected" condition without drying or grinding. The system generally includes a sample preparation sub-system which receives soil samples collected by a probe collection sub-system and produces a slurry (e.g., mixture of soil, vegetation, and / or manure and water), and a chemical analysis sub-system which processes the prepared slurry samples for quantifying multiple analytes and / or chemical properties of the sample. The preparation sub-system may comprise a slurry recirculation flow loop configured with devices to stir, measure, and adjust a water to solids ratio of the slurry.

The application discloses a comprehensive evaluation method for fire resistance of plant species, and solves the limitation of the existing evaluation method for fireproof species, and provides a method for evaluating the fire resistance of the species by comprehensively considering the physical and chemical properties and appearance characteristics of the species, which specifically comprises the following steps: 1) water content determination; 2) ignition point determination; 3) calorific value determination; 4) density determination; 5) image scanning and scoring; and 6) data conversion. The method can solve the limitation of the existing evaluation method for fireproof species, and can evaluate the fire resistance of the species by comprehensively considering the physical and chemical properties and appearance characteristics of the species.

The embodiment of the invention relates to the technical field of electrolytic production, recovery or refining of metal through a molten liquid electrolytic method, in particular to a method for designing a cutter for scraping precipitates and an electrolytic product scraping and collecting device, and the method comprises the steps that scraping force applied to the precipitates is determined; determining the corrosion effect of the precipitate on the cutter; determining the physical and chemical properties of the precipitates; the material of the cutter is determined according to the scraping force, the corrosion effect and the physical and chemical properties; determining the appearance characteristics of the precipitate and the appearance characteristics of the cathode; determining the movement modes of the cathode and the cutter; according to the appearance characteristics of the precipitate, the appearance characteristics of the cathode, the material of the cutter and the movement modes of the cathode and the cutter, the structure of the cutter is determined, and the method is beneficial for ensuring that the selected cutter can be matched with the scraping difficulty of the precipitate so as to smoothly scrape the precipitate on the cathode; and meanwhile, the cutter is prevented from being broken in the scraping process or other parts of the molten salt electrolytic refining equipment are prevented from being damaged.

The present disclosure relates to the technical field of trusted artificial intelligence for controlling and / or monitoring chemical and / or biological products. The present disclosure relates to methods and devices for determining biological and / or chemical properties related to sample data associated with the biological and / or chemical product.

In a method for providing a predictive model for spectroscopy, a response value indicating a physical and / or chemical property of a product or material is predicted from one or more spectral values indicating physical properties of the product or material. For this, spectral measurements of samples of the product are obtained, the spectral measurement including spectral values. Then the spectral values are searched in a database, resulting in data that maximizes the accuracy of the predictive model for spectroscopy of other samples of the product or material. Further a method calibrates a spectroscopic device, a spectroscopic device has installed therein a method for providing a predictive model for spectroscopy, and a computer program product includes program for a processing device including software code portions for performing a method for providing a predictive model for spectroscopy.

The invention provides an electrolyte performance prediction method and an electrolyte formula determination method and device, and relates to the technical field of electrolyte performance prediction. The electrolyte performance prediction method comprises the following steps: determining a formula proportion of an electrolyte to be tested; on the basis of a first principle calculation mode, respective microscopic chemical property information of a plurality of electrolyte molecules in the electrolyte to be detected is determined; inputting the respective microscopic chemical property information of the plurality of electrolyte molecules and the formula proportion into an electrolyte performance prediction model to obtain a performance prediction result of the to-be-tested electrolyte output by the electrolyte performance prediction model; wherein the electrolyte performance prediction model has learned to obtain the electrolyte performance prediction capability based on the formula proportion of the electrolyte and the micro chemical property information of electrolyte molecules. The electrolyte performance prediction efficiency can be improved, the experiment cost is reduced, and the performance prediction accuracy is ensured.

Embodiments of the present application relate to the field of testing liquids in boreholes or wells, and in particular to a device and method suitable for analyzing and monitoring the chemical properties of groundwater in a roadway borehole. The device and method set a sealing assembly in the water-conducting fracture of the roadway borehole, and set other components of the device outside the borehole, which facilitates the maintenance and calibration of the components outside the borehole, to ensure that the device can operate effectively for a long time; at the same time, the overall size of the device is not limited by the space of the borehole and the environment, so that the monitoring data of the device fully reflects the chemical properties of the groundwater in the water-conducting fracture, and then comprehensively evaluates the water chemical environment of the monitoring section, to assist in the selection of underground engineering site and long-term performance safety evaluation; the pipeline is used to make multiple monitoring sections and other components in fluid communication, and the pressure of multiple monitoring sections is monitored, which can make the collection and reflux of groundwater in a sealed state and under normal pressure, prevent groundwater samples from being contaminated, and ensure that the monitoring data is accurate and effective.

The invention relates to a method for evaluating the content and property of volatile components in green coke. The method comprises the following steps: S1, extracting the volatile components; sS1, mixing the to-be-detected green coke sample with a first polar solvent, and carrying out first extraction to obtain a first insoluble substance; sS2, mixing the first insoluble substance with a second polar solvent, and carrying out second extraction to obtain a second insoluble substance; sS3, determining a weight difference between the first insoluble substance and the second insoluble substance, and when the weight difference between the first insoluble substance and the second insoluble substance is less than a threshold weight, performing a step SS4; or when the weight difference is larger than the threshold weight, the step SS2 and the step SS3 are repeated till the weight difference between the insoluble substances obtained through two adjacent times of extraction is smaller than the threshold weight, and the step SS4 is carried out; sS4, carrying out solid-liquid separation on the filtrate to obtain volatile components; and S2, analyzing the relative molecular mass and the like of volatile components. The method disclosed by the invention is simple and easy to implement, economical and efficient, and not only can obtain the content of the volatile components in the green coke, but also can further obtain the chemical properties of the volatile components.

Sub-millimeter scale three-dimensional (3D) structures are disclosed with customizable chemical properties and / or functionality. The 3D structures are referred to as drop-carrier particles. The drop-carrier particles allow the selective association of one solution (i.e., a dispersed phased) with an interior portion of each of the drop-carrier particles, while a second non-miscible solution (i.e., a continuous phase) associates with an exterior portion of each of the drop-carrier particles due to the specific chemical and / or physical properties of the interior and exterior regions of the drop-carrier particles. The combined drop-carrier particle with the dispersed phase contained therein is referred to as a particle-drop. The selective association results in compartmentalization of the dispersed phase solution into sub-microliter-sized volumes contained in the drop-carrier particles. The compartmentalized volumes can be used for single-molecule assays as well as single-cell, and other single-entity assays.

The present application relates to catalytic technology, and aims to provide a method for evaluating the influence law of entropy increase on the OER performance of catalytic materials. The method comprises the following steps: selecting a plurality of physical and chemical properties of elements related to the OER performance by using existing data, obtaining corresponding values and forming a set, and then performing clustering classification; the corresponding entropy values of each attribute are calculated according to the category distribution of the sample, and the entropy values under different cluster numbers are combined as the characteristics of the sample; a new data set is constructed in this way; a regression fitting, hyperparameter tuning and testing are performed on the data set by using a machine learning algorithm to obtain a regression model; finally, SHAP analysis model is used to obtain the importance of each feature in the model and the influence of each feature on the OER overpotential predicted by the model. The present application firstly proposes to correlate the information entropy of the physical and chemical properties of elements with the OER performance of catalytic materials; the research method can save a large amount of resources and improve work efficiency; the accuracy is high and the error is small.

An example welding interface device, includes: a user interface device; a processor; and a machine readable storage device comprising machine readable instructions which, when executed by the processor, cause the processor to: determine, via the user interface device, information describing physical characteristics of a workpiece for a weld to be performed; based on the physical characteristics, determining at least one of a thermal characteristic of the workpiece, an electrical characteristic of the workpiece, or a chemical characteristic of the workpiece; determine a boundary condition associated with the workpiece based on the at least one of the thermal characteristic, the electrical characteristic, or the chemical characteristic; and output a welding process based on the boundary condition.

The invention discloses a sediment heavy metal pollution analysis and evaluation method, and belongs to the technical field of environmental statistical modeling. The method comprises the following steps: acquiring physicochemical property indexes of sediments, and calculating the effective adsorption capacity of each component by utilizing a preset saturation response relationship; inputting the physicochemical indexes into a Bayesian network constructed through hierarchical mechanism constraint, and deducing the adsorption affinity latent variable of the heavy metal; constructing a competition mapping function containing a vacancy constant term based on a competition Langmuir mechanism, and calculating a capacity occupancy rate under a multi-metal competition condition; and finally, calculating a heavy metal content predicted value according to the effective adsorption capacity and the occupancy rate. According to the method, a physical capacity upper limit and a multi-metal competition occupation mechanism are introduced into the Bayesian network, so that the problems of prediction distortion and lack of a competition mechanism of a traditional model under high load are solved, and accurate evaluation conforming to physical and chemical laws is realized.

The present application relates to a series of compounds calcium halogenated borate and calcium halogenated borate nonlinear optical crystal and preparation method and use, the molecular general formula of the series of compounds is Ca2B3O6X, wherein X=Cl, Br, molecular weight 244.04-288.50, the compound is synthesized using solid phase reaction method;The crystal is orthorhombic, space group Cmc 21, the cell parameter is a=15.360 (6)-15.406 (2) Å, b=22.115 (3)-22.175 (10) Å, c=7.3617 (11)-7.454 (4) Å, Z=16, V=2508.2 (6)-2538.7 (19) Å 3 , the crystal is grown using cosolvent method, the powder frequency doubling effect is about 1.5-2 times of KDP (KH2PO4), has wide light transmission waveband, the crystal preparation method is simple, and the cost is low, the prepared crystal is large in mechanical hardness, easy to cut, polishing processing and preservation, the series of calcium halogenated borate nonlinear optical crystal described in the application has the advantages of stable physical and chemical properties, moderate mechanical hardness, not easy to break, easy to cut, polishing processing and preservation and the like.