31 results about "Sample composition" patented technology

A sensor device includes a sensor, which may include an acoustic wave resonator structure, having a surface to which analyte capture ligand is bound. The device also includes a crowding agent to reduce the ratio of binding of an analyte in a sample composition to the analyte capture ligand when the sample composition is flowed across the surface of the sensor.

The temperature field prediction method of a hypersonic wind tunnel, an electronic device and a storage medium belong to the technical field of wind tunnel measurement and control. In order to solve the problem that the temperature field control effect of the hypersonic wind tunnel is poor, the working condition data of the hypersonic wind tunnel is collected, the input samples in the original data sample set are reconstructed in phase space, the input samples and the output samples used for model training are obtained, the sample training data set and the sample test data set are composed, the Bayesian regression method, the support vector regression method and the BP neural network method are used to establish the outlet temperature prediction model of the temperature field of the hypersonic wind tunnel, the sample training data set is used to train the three outlet temperature prediction models of the temperature field of the hypersonic wind tunnel, the sample test data set is used to test the three outlet temperature prediction models of the temperature field of the hypersonic wind tunnel, and the optimal outlet temperature prediction model of the temperature field of the hypersonic wind tunnel is obtained. The present application is accurate in prediction.

The invention provides a layered ferroelectric material piezoelectric response measurement method and device capable of eliminating static artifacts, and relates to the technical field of advanced functional material characterization and testing. According to the specific implementation scheme, a CuxInyP2S6 single crystal is synthesized by adopting a chemical vapor transport method; a Raman spectrum and an energy dispersive spectrometer are used for testing, and whether a sample composition is a CuInP2S6-In4 / 3P2S6 bulk heterostructure or not is verified; if the verification result is yes, the influence of the CuInP2S6-In4 / 3P2S6 ferroelectric domain characterization result under the action of the static artifact is obtained through a PFM test; using a static blind spot method to counteract static artifacts, and performing comparative analysis to obtain a real amplitude value of a CuInP2S6-In4 / 3P2S6 surface ferroelectric domain; and corresponding data are extracted for calculation, so that the piezoelectric coefficient of CuInP2S6-In4 / 3P2S6 is obtained. By optimizing a bias voltage and laser positioning strategy, the interference of electrostatic interaction on a measurement signal is effectively eliminated.

A method and a system for self-regulating control of an internal chamber pressure of a mass spectrometer are provided. The method specifically includes: associating a first test mass spectrum set, a sample composition, a compositional ratio, and a chamber pressure regulation parameter to obtain a test data set; performing characteristic factor identification on a first real-time mass spectrum generated in real time to obtain a plurality of first real-time characteristic factors when a mass spectrometer is used for sample detection; matching the first real-time characteristic factors with different test data sets; and regulating an internal chamber pressure of the mass spectrometer according to the chamber pressure regulation parameter in the test data set when there exists a test data set with a matching degree greater than or equal to a preset value.

This invention provides a method for predicting the Tm value of a melting curve, relating to the field of biodetection technology. The method includes the following steps: constructing a Tm value labeling model and a Tm value prediction model; acquiring data information of the sample to be tested and inputting the data information into the Tm value labeling model; preprocessing the data information by the Tm value labeling model and labeling the sample to be tested with or without a Tm value; samples with Tm values ​​constitute a valid sample set; extracting several peaks from the original melting curve to obtain an original Tm value set; encoding the original Tm value set according to temperature intervals; wherein the temperature bits in the original binary vector are arranged according to temperature intervals; inputting the original melting curve from the valid sample set into the Tm value prediction model to obtain the predicted Tm value. Arranging the temperature bits according to temperature intervals allows the model to learn the correlation between adjacent temperatures, thereby more accurately capturing the influence of temperature changes on the Tm value, and thus improving the accuracy of Tm value prediction.

The invention relates to the technical field of separation and extraction of precious metals, in particular to a method and a system for analyzing and optimizing selected silver based on a fire assaying method. The method comprises the following steps: collecting sample component data in real time by using a sensor, and obtaining standardized sample component data through denoising and standardization treatment; classifying the samples by adopting a support vector machine, and dividing the samples into a high difference group and a low difference group based on component difference; for high-difference group samples, performing iterative search of a preliminary optimization parameter set by adopting a genetic algorithm; the influence of smelting atmosphere parameters on the separation efficiency is evaluated through a simulation method, the smelting atmosphere parameters are adjusted, and the stability of the smelting atmosphere parameters is verified; predicting a separation efficiency trend according to process feedback data, and updating an optimization parameter set based on the separation efficiency trend; and finally, the control system generates an equipment control instruction according to the updated parameter set to ensure that the production equipment executes the separation process according to the optimization condition. The efficient and stable separation process is achieved for precious metal gold and silver.

This invention belongs to the field of spectroscopic technology for sample composition and content analysis, specifically relating to a device and method for measuring the concentration of specific elements based on fiber Bragg gratings and LIBS. A solid-state Q-switched laser emits pulsed light that interacts with the substance through an optical path. The resulting plasma is transmitted to corresponding single-mode fibers, circulators, and corresponding gratings, then returns to the circulator and is fed into the corresponding detector. A timing controller controls the light intensity collected by the detector for integration calculation, and the result is returned to a computer. The wavelengths selected by the first and second fiber Bragg gratings correspond to the internal standard element and the analyte element in the sample, respectively. Using the ratio of the corresponding light intensities and the mathematical relationship established with the standard sample, the concentration of the analyte element in the unknown sample can be calculated. This invention eliminates the need for a complex spectrometer structure, resulting in a simple device structure, high resolution for single-element concentration measurement, and allows for control of the fiber Bragg grating wavelength within 100 pm using a temperature-controlled water bath, or the measurement of different element concentrations by replacing the fiber Bragg grating with different wavelengths.

The application discloses a kind of field geological sample intelligence airing equipment, it is related to soil sampling technical field, including: rack, airing platform, shed top, the airing platform is by several groups of sample clamps for fixing sample composition;The shed top includes several groups of support frame, the top of the support frame is detachably installed with guide rod, the lower side of any one end of the guide rod is equipped with cloth reel, the side of the rack away from cloth reel is detachably installed and is equipped with the winding mechanism for pulling rain cloth to cover the rack.The design scheme of the present application is designed by installing the airing platform that can be turned over on the rack, when airing soil sample, soil sample is fixed by sample clamp, according to the airing cycle, sample clamp will periodically automatically turn over 180 degrees, so that the front and back of soil sample can be evenly aired, to prevent soil sample from not being dried, while improving the airing efficiency, the work burden of researcher is reduced.

The present application belongs to the technical field of metallurgical quality detection, and relates to a method for tracking steel sample detection time, comprising the following steps: S1, recording sample information in the sample detection process, including sample type, sample code, order arrival time, sample sending time and sample arrival time; S2, printing a sample label through a label printer and sticking the label on the sample; S3, sending the sample to a preparation station for sample preparation; S4, scanning a two-dimensional code at the sample code column of a direct-reading spectrometer to input the sample code; and S5, displaying sample composition data and sample analysis time. According to the present application, the detection time of each sample is dynamically and real-timely displayed in the detection and analysis system of the steel sample, so that the problem that the operation personnel cannot intuitively understand the detection time and cannot timely and accurately fill in the reason for exceeding the detection time is solved, thereby avoiding the situation that the detection result is affected by untimely information transmission and it is difficult to trace the failure reason.

To provide a method and system for determining sample composition from spectral data acquired by a charged particle microscopy system.SOLUTION: Chemical elements in a sample are identified by processing spectral data with a trained neural network (NN). If the identified chemical elements do not match a known elemental composition of the sample, the trained NN is retrained with the spectral data and the known elemental composition of the sample. The retrained NN can then be used to identify chemical elements within other samples.SELECTED DRAWING: Figure 1

This invention provides a method and system for determining sample composition based on spectral data. [Solution] A scientific instrument for performing spectral analysis comprises a memory for storing computer executable instructions and a processor for executing computer executable instructions, wherein the computer executable instructions perform a first operation using an encoder to compress one or more unknown spectra into one or more compressed unknown spectra in latent space, and a second operation to match one or more compressed unknown spectra with one or more compressed known spectra in order to obtain one or more candidate matches of a sample.

The application discloses a drilling leakage prediction model establishment method, a drilling leakage prediction method and a device. The drilling leakage prediction model establishment method comprises the following steps: for a drilled well with leakage mark data, extracting a seismic attribute value corresponding to each depth value of the leakage mark from each set seismic attribute body according to a synthetic record of the well, so as to obtain a sample containing the leakage mark corresponding to the depth value and each seismic attribute value; the leakage mark data comprises a plurality of depth values of the well and the leakage mark corresponding to each depth value; a plurality of samples are combined into a sample set, the sample set is used for training a set classification model, so as to obtain a classification model used for predicting drilling leakage, and the classification model comprises at least one sub-classification model. The drilling leakage can be reasonably predicted before drilling.

The embodiment of the invention discloses a sample component analysis method, electronic equipment, a storage medium and a program product, and relates to the technical field of sample component analysis. The method comprises the following steps: acquiring a target sample, determining a target test condition, and analyzing the target sample based on the target test condition to obtain a first analysis result of the target sample; based on the first analysis result, determining at least two reference samples associated with the target sample and a blank sample; measuring the reference samples and the blank samples to obtain measurement data, and determining a quantitative analysis model based on the measurement data; and in response to a component analysis instruction of a to-be-detected sample, determining target components of the to-be-detected sample based on the quantitative analysis model. According to the scheme provided by the embodiment of the invention, the components of the sample and the content of each component can be quickly and accurately determined.

The application discloses a kind of geological sample component identification and abnormal detection system based on machine learning, it is related to geological sample component identification and detection technical field, first by the ratio of Compton and Rayleigh scattering intensity calculated by ray fluorescence energy spectrum, obtain effective atomic number and its uncertainty;Again, the continuum of short-wave infrared spectrum is removed, the depth of aluminum hydroxyl absorption band and band shape asymmetry are extracted, and the slope is used to represent the granularity, and the monotone spline is trained to obtain the clay proportion estimation;According to the end member set and atomic number table, the theoretical atomic number and uncertainty are obtained, and the measurement side is integrated into a unified scale to obtain the cross-modal inconsistency index.The state variable and the index are used as the target to adaptively optimize the collection and retest, and the consistency constraint is executed to solve the mixture and abnormality determination.The application can carry out high-precision identification and abnormality determination under complex working conditions.

This disclosure relates to a method for near-infrared spectral conversion of gasoline. Hydrocarbon compounds are used as standard samples, and their spectra are acquired on two spectrometers. A fitting algorithm is then used to obtain a fitting coefficient vector between the standard spectral matrix obtained from the first spectrometer and the spectrum of a typical gasoline sample. This fitting coefficient vector is then multiplied by the standard spectral matrices obtained from both spectrometers to obtain the gasoline fitted spectral matrix. A mathematical transformation is then performed on this resulting matrix to obtain the gasoline near-infrared spectral conversion coefficients between the first and second spectrometers. This method eliminates minor spectral differences between near-infrared spectra of gasoline samples measured by different spectrometers. In practical applications, it eliminates the need to collect gasoline standard samples, saving manpower and resources, while improving the accuracy of spectral conversion. It is suitable for rapid analysis of gasoline sample composition and properties.

This application discloses an elemental composition analysis method, apparatus, storage medium, and product, relating to the field of laser technology. It controls a galvanometer scanning optical path to guide a pulsed laser into an array of fiber optic bundles to excite plasmas at multiple spatial points on the sample surface. The compositional spectral signals generated by each plasma are collected, and spatial distribution information of the sample's elemental composition is generated based on these signals. The array of fiber optic bundles improves collection efficiency by collecting the emitted plasma light, and the combination of the fiber optic bundles and fiber optic probes enables spatial scanning of the sample surface, obtaining the elemental composition distribution of the sample within a spatial range, thus improving the accuracy of sample composition analysis.

The present application relates to the technical field of gas sampling, in particular to a field sampling method for multi-point sampling in a large area in the wild, comprising the following steps: step 1, dividing the sampling area, and dividing the sampling area into a first area and a second area according to the distribution of roads in each sampling area, the first area is defined as within a predetermined distance from the road, and the second area is defined as outside the predetermined distance from the road. The field sampling method provided by the present application first classifies different sampling points in the wild, divides the sampling points into three types based on the distance from the road and whether it is a well gas sample, each type is sampled by a different container, and each type of gas sample is subjected to constant pressure and constant flow treatment before being input into a gas analysis system, so that the gas samples of various sampling points in the wild can be analyzed on site, restoring the current sampling point gas sample composition, especially suitable for multi-point sampling in a large area in the wild.

The utility model relates to the technical field of soil samples, in particular to a soil sample transfer device with a protection function, which comprises a box body, a base is mounted on the surface of the bottom of the box body, a first protection cover is mounted on the surface of the top of the box body, and buckles are mounted on four sides of the first protection cover. A heater is installed on the right side surface of the box body, a heating piece is installed on the surface of one side of the heater, and a radiator is installed on the left side surface of the box body. According to the improved transfer device, the double-sealing design is adopted, the sealing performance of the device is effectively improved, soil samples are prevented from being affected by external pollutants in the transfer process, the samples are prevented from being affected, the design convenient for temperature adjustment is adopted, the internal temperature of the device can be monitored according to a temperature sensor, and the device is convenient to use. The internal temperature of the device is maintained in a proper range, so that the situation that the soil sample is influenced by over-high or over-low temperature, so that the composition of the sample is changed or the analysis result is inaccurate is avoided.

The invention relates to the technical field of food safety comprehensive detectors, in particular to a food safety comprehensive detector based on the Internet of Things and a detection method thereof.The food safety comprehensive detector comprises an equipment body, a detection groove is formed in the equipment body, a cover plate is connected to one side of the detection groove, and the food safety comprehensive detector further comprises a containing disc and a plurality of installation grooves located in the detection groove and formed in the periphery of the containing disc at equal intervals; one end of each independent bin is provided with an opening and connected into the corresponding mounting groove, one side of the opening end of each independent bin is connected with a sealing cover, and the number of the independent bins is consistent with that of the mounting grooves. By arranging a combined structure of the independent cabins and the sealing covers, each sample is arranged in the independent cabin, and the sealing covers can tightly cover the ports of the independent cabins, so that the problems that volatile medicaments of a plurality of samples in a traditional detector are mutually mixed, surrounding samples are polluted and a detection module is interfered are solved; the detection environment of each sample is independent and pure, and the sample components are prevented from being changed and the detection environment is prevented from being damaged.

This utility model discloses a system for fabricating a chemical composition test specimen for welding wire, including a sample preparation container. The sample preparation container includes an electrically insulated container body, and the interior of the container body forms a sample preparation cavity with an opening at the top. The sample preparation container also includes a cover detachably assembled to the opening, and the cover has a gas channel for communicating with the sample preparation cavity. The fabrication system also includes a medium-frequency induction heating device, including a medium-frequency induction power supply and an induction coil spirally wrapped around the outer periphery of the container body. The induction coil and the medium-frequency induction power supply form a closed circuit for heating the welding wire in the sample preparation cavity. The beneficial effects of this utility model are: using inert gas to protect the molten metal reduces sample oxidation and some element burn-off, effectively prevents the escape of volatile elements in the sample, ensures that the sample composition is consistent with the actual composition, and achieves rapid and low-cost sample preparation.

Methods are provided for conducting a dual-probe assay on a set of nucleic acid targets, including: combining a set of dual probes with a sample composition potentially comprising a set of nucleic acid targets to form a set of cleavable ternary nucleic acid complexes; releasing from the cleavable ternary nucleic acid complex a set of recognition element fragments; hybridizing each of the set of released recognition element fragments to a coded oligonucleotide probe and using resulting hybridized released recognition elements as primers for copying the coded oligonucleotide probe to produce a sect of target-associated codes, wherein each of the coded oligonucleotide probes comprises a code from a set of codes, each code comprises at least one segment encoding one or more symbols that correspond to a sequence of one or more nucleotides; and performing a detection event to identify a set of detected codes of the target-associated codes.

The application discloses an element distribution map-based sample component analysis method and device and a product, and relates to the field of component analysis. First, element distribution map data corresponding to each element in a sample obtained by performing energy spectrum analysis or mass spectrum analysis on the sample and corresponding image data are acquired; non-sample region data in all element distribution map data is filtered according to the image data, and filtered element distribution map data corresponding to each element is obtained; a plurality of data points in the filtered element distribution map data corresponding to each element are subjected to local summation assignment processing, and a local summation result corresponding to each element is obtained; the local summation result corresponding to each element is subjected to division processing according to a molecular formula of sample material, and stoichiometric ratio spatial distribution characteristic data is obtained; and sample component analysis is performed according to the stoichiometric ratio spatial distribution characteristic data, so that the sample component analysis efficiency and accuracy can be improved.

The embodiment of the invention discloses a user behavior information prediction model training method, a prediction method, equipment and a medium. A specific embodiment of the method comprises the following steps: acquiring a historical user information set; for each user feature, performing binning processing on the sample set according to each user feature value of the corresponding user feature included in the sample set to generate a binning value of each box of samples; selecting a preset number of samples to form a sample group; according to the sample group and each binning value of each sample in the sample group corresponding to each user feature, training a user behavior information prediction pre-model; and training to obtain a user behavior information prediction model according to the sample set and each binning value of each sample in the sample set corresponding to each screened user feature. The implementation mode is related to big data, the universality of filling the missing value is improved, the influence of filling the missing value on the model effect is reduced, the consumption of computing resources and storage resources is reduced, the model learning difficulty is reduced, and the convergence time is shortened.

Compositions, systems and methods for multiplex detection of target biomarkers in a simple are provide, offering highly sensitive and multiplexed detection. The compositions and methods are preferably isothermal, label-free, and enzyme-free. The compositions include (i) a DNA carrier molecule comprising (decorated along its length – in a sequence-specific manner) with sequences complementary to sequences in the PNA based anchor and (ii) bifunctional PNA-based anchors which are complementary on the one end to the sequences the analytes of interest and complementary on the other end to sequences on the DNA carrier, the complementarity being provided by a first and a second PNA molecule. The disclosed systems and method include a nanopore sensor.

The utility model discloses an agricultural product detecting and sampling device which comprises a sampling device body, a machine cover is fixedly connected to the left side face of the sampling device body, a motor is fixedly connected to the inner wall of the machine cover, a mounting plate is fixedly connected to the bottom face of the sampling device body, and a battery pack is clamped to the inner wall of the mounting plate. The back surface of the sampling device body is fixedly connected with a driving seat, and the output end of the driving seat is fixedly connected with a sealing end cover. According to the device, the master control switch is matched with the touch display panel, so that starting, device control and sampling position adjustment become easy and simple, the working difficulty and intensity of operators are reduced, the driving seat drives the sealing end cover to rotate, the sampling device body can be effectively sealed and opened before and after sampling, and the sampling efficiency is improved. External impurities, dust and the like are prevented from polluting the sample, and the sampling barrel is sealed by the sealing plug after sampling, so that the component stability of the sample is further ensured, and the accuracy of a detection result is greatly improved.

The invention relates to a simulation material capable of simultaneously simulating electric heating characteristics of biological tissues and a configuration method thereof, and the configuration method comprises the following steps: calculating component concentration of the simulation material according to electric characteristics, thermal characteristics and temperature conditions of target tissues and a fitting model, and preparing a target simulation material; the fitting model is the relationship between the electrothermal performance parameters of the simulation material and the concentrations of ethylene glycol, aluminum oxide and sodium chloride forming the simulation material at different temperatures; the construction of the fitting model comprises the steps of preparing a plurality of simulation materials as samples, performing electric heating performance measurement on the prepared samples, and constructing the fitting model based on the component concentration of the simulation materials and the material characteristics according to the samples and the electric heating performance parameters of the samples. The component concentration can be accurately calculated according to the target tissue characteristics and temperature conditions, and a customized simulation material is prepared.

A method of quantifying microplastic mass in a sample composition, including the steps of pre-treating the sample composition to remove non-microplastic organic matter and extract microplastics thereby providing a pre-treated sample composition, measuring the organic carbon content of a microplastic polymer in the pre-treated sample composition using total organic carbon (TOC) analysis, and quantifying the microplastic mass in the sample composition according to the organic carbon content of the microplastic polymer.