227 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 provides the uses of chemical waste and byproducts in a chemical library to store digital information, and methods for computing with unknown waste chemicals by encoding digital data into a plurality of chemicals to obtain a dataset; translating the dataset into a chemical form; reading the data set; querying the dataset by performing an operation to obtain a perceptron; and analyzing the perceptron for identifying change in at least one of the chemicals, thereby developing a chemical computational language. The invention demonstrates a workflow for representing abstract data in synthetic metabolomes. Also presented are several demonstrations of kilobyte-scale image data sets stored in synthetic metabolomes, recovered at >99% accuracy.

The invention discloses a method for predicting the content of heavy metals in different occurrence forms in soil based on machine learning, and relates to the technical field of soil component content analysis, and the method comprises the following steps: (1) collecting soil physicochemical properties, the total amount of soil heavy metals, the types of the heavy metals in the soil and the content of the heavy metals in different occurrence forms in the soil from a literature library, constructing a sample database; (2) preprocessing the sample database to obtain a preprocessed sample database; (3) for each kind of heavy metal, extracting corresponding sample data from the preprocessing sample database, dividing the sample data into a training set and a test set, selecting a machine learning algorithm, establishing a prediction model training model of different occurrence form contents of the heavy metal in the soil, and optimizing hyper-parameters in the training process; and (4) predicting the content of heavy metals in different occurrence forms in the soil to be detected by using the optimized prediction model. The method has a good application prospect in the aspects of heavy metal pollution risk evaluation and the like.

The invention discloses an amorphous forming ability prediction method based on Transform and table data conversion. The amorphous forming ability prediction method comprises the following steps: acquiring basic attributes and amorphous forming ability attributes of amorphous alloy composition elements in a metal alloy sample; the basic attributes refer to element properties simulated based on an experiment or a density functional theory and comprise atomic basic properties, chemical properties and physical properties, and the amorphous forming ability attributes comprise a critical casting diameter Dmax; generating an amorphous alloy data set; wherein the data set comprises an independent variable and a response variable, the independent variable comprises element composition and mixing enthalpy Hmix, and the response variable is a critical casting diameter Dmax; defining a relation model, wherein the relation model is an integrated model formed by three types of models; and training the integrated model by using an amorphous alloy data set, and constructing an amorphous forming ability evaluation model. According to the technical scheme, various relation models for predicting the critical casting diameter can be trained, and the various relation models are combined to construct the optimal amorphous forming ability evaluation model.

The invention relates to a method for predicting physical and chemical properties of crude oil, and the method comprises the following steps: obtaining library sample spectrums of a plurality of crude oil samples, and obtaining respective standard data of a first physical and chemical property and a second physical and chemical property; taking the first n main factors of the first characteristic spectrum and the standard data of the first physicochemical property of the crude oil sample as a first variable, taking the standard data of the second physicochemical property of the crude oil sample as a second variable, and performing partial least square regression analysis to obtain a correction model; collecting a to-be-detected sample spectrum of a to-be-detected crude oil sample, and obtaining detection data of a first physicochemical property of the to-be-detected crude oil sample; substituting the first n main factors of the second characteristic spectrum and the detection data of the first physicochemical property of the crude oil sample to be detected into the correction model to obtain the prediction data of the second physicochemical property of the crude oil sample to be detected. The method disclosed by the invention has a relatively wide range of physicochemical property prediction capability and better prediction precision.

The invention discloses a method for screening potential efficacy raw materials of cosmetics by establishing a mathematical model based on molecular docking and physical and chemical properties of substances, and the method comprises the following steps: S1, aiming at semi-flexible molecular docking of a specific efficacy target, including pretreatment and simulated docking of a compound ligand and a target receptor; s2, querying and selecting cosmetic application related indexes in a database, wherein the specific indexes are molecular weight, the number of hydrogen bond receptors and donors, fat-water distribution coefficient, topological polar surface area and skin permeability; and S3, alternative compound screening, including data preprocessing, definition of optimal / inferior values and median values, primary screening of principal component analysis, weight coefficient determination by an entropy weight method and Topsis comprehensive evaluation. According to the method, reasonable non-experimental type indexes are found, so that the screening efficiency is effectively improved, the cost is effectively reduced, the scientific large-batch raw material screening requirement can be met, and besides the screening purpose, the potential size of alternative compounds can be predicted and quantified.

A mechanism is provided in a data processing system comprising at least one processor and a memory comprising instructions which, when executed by the at least one processor, causes the at least one processor to implement a real-time prediction engine for real-time predication of chemical properties through combining calculated, structured, and unstructured data at large scale. Offline components executing within the real-time prediction engine store a computational representation for each of a plurality of chemical structures in a unified storage. Each computational representation maps a respective chemical structure to a vector of calculated chemical structure features and properties, unstructured chemical features and properties, and structured chemical features and properties. The offline components train a computational real-time predictive model based on the computational representations. A user interface executing within the real-time prediction engine receives a request specifying one or more chemical compounds. An analytics jobs manager executing within the real-time prediction engine predicts one or more properties of the one or more chemical compounds using the computational real-time predictive model. The analytics jobs manager outputs the one or more properties of the one or more chemical compounds to the user interface.

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.

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 relates to the technical field of diaphragm detection equipment, in particular to a diaphragm physical and chemical property detection device which comprises a box body. The air pressure testing mechanism is used for testing air permeability; an aging test mechanism; the tester is used for aging test; the clamping mechanism is used for clamping the diaphragm; the infiltration mechanism is used for wettability testing; the air pressure testing mechanism is arranged at the top end of the box body, the aging testing mechanism and the infiltration mechanism are arranged at the bottom end in the box body, and the clamping mechanism is arranged between the air pressure testing mechanism and the aging testing mechanism. Through the set aging performance test, the diaphragm can be immersed in a high-temperature electrolyte to simulate the condition of the diaphragm in long-term use, and the strength of the diaphragm is tested by using air pressure after a set time interval, so that the aging performance of the diaphragm can be detected; and meanwhile, the wettability of the diaphragm can be tested by using the electrolyte before the aging test is carried out on the diaphragm, so that the test efficiency of different properties of the diaphragm is 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.

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.

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 nanomaterial preparation characterization system, and the system comprises a beam generation assembly which is suitable for generating an initial nanocluster beam; the deposition assembly is suitable for depositing the initial nanocluster beam under the action of an external field to obtain a target nanomaterial; the characterization assembly is suitable for characterizing chemical properties and physical properties of the target nano material; and the sample transfer assembly is suitable for conveying the target nano material to the characterization assembly in a vacuum environment, so that the physical or chemical properties of the target nano material are kept unchanged in the transfer process, and the characterization of the physical or chemical properties of the target nano material is completed.

A reactor and method commonly applicable for high-pressure in-situ DSC and neutron tests of a gas hydrate relates to the field of characterization of physical and chemical properties of the gas hydrate. The reactor can not only carry out a high-pressure and low-temperature in-situ DSC test of the hydrate but also be suitable for a neutron diffraction test of the hydrate. The reactor can be adapted to an existing high-pressure and low-temperature in-situ DSC device without the need to re-develop a whole set of system, thus greatly reducing the replacement cost of the device. Owing to the sectional design, the flexibility and the applicability of the reactor can be ensured. Researchers can conveniently transport the hydrate in a pressure-maintaining manner. Even at a long distance, with the assistance of a liquid nitrogen tank or a vehicle-mounted refrigerator, it can be ensured that the hydrate may not be decomposed during transportation.

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.

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.

An electron paramagnetic resonant (EPR) instrument able to determine chemical properties of a sample using paramagnetic resonance is provided. In one embodiment, the instrument is able to measure the paramagnetic concentration of a wide variety of practical substances, ranging from food and beverages to biological specimens and solid-state electronic materials. The disclosed device can be portable and perform a measurement faster than commonly used techniques to quantify this parameter, including methods that use vibrating sample magnetometers and currently available electron paramagnetic resonance spectrometers.

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.

Disclosed is a method of mass spectrometry comprising the steps of: providing a library of matrix data, said matrix data comprising one or more physico-chemical properties of one or more matrix components as a function of retention time; chromatographically separating a sample, said sample containing at least some of said matrix components and one or more analyte components; analysing said sample at a plurality of retention times to obtain sample data, said sample data comprising one or more physico-chemical properties of one or more sample components as a function of retention time; and calculating one or more error values as a function of retention time based on a comparison between said sample data and said matrix data.

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.