95 results about "Scientific instrument" patented technology

The invention provides a scientific instrument purchase type selection method and device based on artificial intelligence, and belongs to the technical field of artificial intelligence, and the method comprises the steps: constructing a knowledge graph of all initial instruments; calculating an evaluation value of each initial instrument under each evaluation dimension; matching in the knowledge graph according to model selection demand information input by a user to obtain a candidate instrument set; extracting evaluation values of each candidate instrument in the candidate instrument set under all evaluation dimensions; performing weighted calculation on the evaluation values corresponding to all the candidate instruments according to dimension weight parameters set by a user to obtain a personalized comprehensive score; and generating a model selection scheme including an instrument recommendation result and data traceability information according to the personalized comprehensive score and associated information in the knowledge graph. According to the method, the knowledge graph fusing the multi-source data is constructed, and the scientific instrument purchase type selection scheme based on artificial intelligence is generated in combination with multi-dimensional evaluation, so that accurate recommendation of scientific instrument purchase type selection based on artificial intelligence is realized.

Disclosed herein are scientific instrument support systems, related methods, computing devices and computer-readable media. A method of mitigating distortion of an optical emission spectrum obtained from an optical emission spectrometer is provided. The method may comprise a step of obtaining a spectrum recorded with the spectrometer and a respective one or more condition parameters indicative of an operating condition at a time of recording the spectrum. The method may further comprise a step of providing a model configured to output, in response to the one or more condition parameters, one or more transform parameters of a transformation to be applied to the obtained spectrum. A transformation may be applied in accordance with the obtained one or more transform parameters to the obtained spectrum to mitigate distortion of the spectrum due to a discrepancy between the operating condition and a baseline operating condition.

Systems / techniques are provided for facilitating mass analyzer calibration via reinforcement learning. In various embodiments, a system can predict, via execution of one or more reinforcement learning neural networks on present-time state data of a mass analyzer of a scientific instrument, what adjustments to one or more operational parameters of the mass analyzer would cause the mass analyzer to approach a calibrated state, wherein the one or more operational parameters include an electrode voltage of the mass analyzer or a timing control of the mass analyzer. In various aspects, the system can modify the one or more operational parameters based on the adjustments, thereby causing the mass analyzer to approach the calibrated state.

The present disclosure provides a scientific instrument support apparatus comprising a first logic, a second logic, and a third logic. The first logic subscribes to events from a device driver, receives signature data events including a generated signature event, generates signature data with a specified signature identifier in response to the generated signature event, and transmits the signature data to the second logic. The second logic receives the signature data from the first logic, processes the signature data, writes the processed signature data to an instrument health database, and transmits the signature data to a cloud-based database. The third logic presents a graphical user interface based on the processed signature data. The apparatus enables efficient collection, processing, and presentation of scientific instrument data for improved monitoring and analysis.

The utility model relates to an in-situ torsion experiment device for X-ray CT (Computed Tomography), and belongs to the technical field of scientific instruments for in-situ torsion experiments for X-ray CT. Comprising a driving assembly, a torque sensor and a clamp assembly. Two ends of a shaft of the torque sensor are respectively connected with the driving assembly and a clamp. The driving assembly comprises a motor, an outer shell, a worm gear and a worm, the worm gear and the worm are rotationally arranged in the outer shell and meshed, the upper end of the worm gear is in key connection with the lower end of the torque sensor, and one end of the worm is connected with the output end of the motor. The driving assembly is stable in transmission during an experiment, has a self-locking function, prevents reverse rotation, improves the detection accuracy, is compact in structure, has a large transmission ratio, is suitable for speed reduction, is low in noise and small in vibration, and effectively prevents the influence on other works in a laboratory.

This invention provides a high-end scientific instrument reliability analysis and design method based on SysML, belonging to the field of instrument reliability analysis technology. The method includes: constructing a system model of the target instrument using SysML, the system model including a requirements diagram, internal block diagram, and attribute library; extracting all failure modes from all failure mode libraries and assigning them global numbers to establish a failure mode mapping matrix; performing failure mode and impact analysis (FMEA) for the target instrument based on the system model to obtain a failure mode and impact analysis table; establishing a parameterized reliability model for each functional path; calculating the reliability constraints of each functional path based on the system model and the impact analysis table; and performing reliability analysis based on the measured attributes and reliability constraints of sub-components to generate an optimization scheme. The advantages of this invention are improved accuracy, consistency, and automation of reliability analysis.

Disclosed herein are scientific instrument support systems, related methods, computing devices, and computer-readable media. For example, in some embodiments, a scientific instrument support apparatus includes sample analysis logic to cause a sample to be injected into a gas chromatograph and to obtain a mass spectrum of the sample using a mass spectrometer coupled to the output of the gas chromatograph, the mass spectrometer utilizing a mass calibration or a lock mass correction while obtaining the mass spectrum of the sample; calibration gas logic to control a supply of a calibration gas to the mass spectrometer during the void time of the gas chromatograph; and lock mass calibration logic to obtain a mass spectrum of the calibration gas using the mass spectrometer during the void time of the gas chromatograph and to calculate the mass calibration or the lock mass correction to be used by the sample analysis logic.

This invention provides a method and system for verifying and tracing file fingerprints for scientific instrument data, comprising: Step S1, acquiring user identity information and instrument identifier of the scientific instrument, identifying the original data file through file monitoring and automatically collecting basic metadata to generate labeled metadata; Step S2, calculating the file fingerprint based on the algorithm identifier using a digest algorithm and writing it into a fingerprint database; Step S3, performing fingerprint comparison on the file fingerprints; if the fingerprints are the same, reusing the existing content object identifier and adding a new version record; if they are different, creating a new content object identifier and adding a new version record; and when the same reservation identifier, upload time difference not exceeding a preset threshold, and fingerprint inconsistency are met, creating a version fork and recording the fork reason code and fork reason payload for traceability; Step S4, performing verification processing on the downloaded file. The beneficial effect is that this invention can meet the comprehensive requirements of traceability, auditability, and real-time performance for the security management of scientific instrument data.

The application is suitable for the field of computers, and provides a scientific instrument leasing analysis method and system based on big data, which comprises the following steps: acquiring position information of leasing equipment, wherein the leasing equipment comprises a first leasing equipment and a second leasing equipment; identifying a changed position relationship of the first leasing equipment and the second leasing equipment according to the position information of the leasing equipment; if it is identified that the first leasing equipment or the second leasing equipment to be used is within a mutual visual monitoring range, releasing use locking of a monitored leasing equipment; instructing at least one of the leasing equipment to monitor the monitored leasing equipment and generating monitoring information; and identifying and analyzing the monitoring information based on big data to determine whether there is a damaged use behavior in the monitoring information, wherein the application has the beneficial effects of reducing the labor intensity of operation and maintenance personnel, being capable of guaranteeing the integrity of the leasing equipment as much as possible, and reducing the risk of damage of the leasing equipment.

This application provides a hardware-software heterogeneous data processing system and method for atmospheric sounding lidar, relating to the technical field of embedded architecture for atmospheric remote sensing and scientific instruments. The system includes: a PL (Plug-in) terminal, which performs preliminary processing on lidar signal data to generate target data; a PS (Power Controller) terminal, including an internal cache and a processing core, with a virtual spatial filter configured within the processing core; the target data is stored in the internal cache via an ACP (Automatic Component Processing Filter); the processing core schedules the PL terminal to perform preliminary processing on the digital signal, reads the target data from the internal cache, and runs the virtual spatial filter to filter the target data; the virtual spatial filter performs register-level single-loop fusion of each independent algorithm node, completing the calculation of each independent algorithm within the single loop fusion, and all intermediate data resides in the register file. Relying on the ACP and single-loop fusion architecture, the bus occupancy rate and system latency of data flow are reduced, thereby achieving high throughput and zero bottlenecks at the system level.

Scientific instrument support systems and related methods, computing devices, and computer readable media are disclosed herein. For example, in some embodiments, a scientific instrument support apparatus includes a first logic element to generate a first command frame including a flag having a first value; and a second logic element to transmit the first command frame to a first device. The first value indicates that the first device should ignore an operation indicated by the first command frame. The scientific instrument supporting device comprises a third logic element which is used for determining whether a confirmation signal indicating successful operation is received or not; and a fourth logic element for generating a second command frame including a flag having a second value upon receipt of the acknowledgement signal. The second value indicates that the first device should perform an operation indicated by the second command frame.

This invention belongs to the field of precision scientific instrument manufacturing and polymer material characterization technology. Specifically, it discloses a tensile testing system and analysis method for polymer elastomers with resistance to wall slip. The method includes the following steps: S1, preparing a defect-free annular polymer elastomer sample; S2, fitting the sample onto two parallel fixed rods of the tensile testing system in a floating contact fit without mechanical clamping; S3, placing the sample in a vacuum chamber; S4, applying periodic tensile deformation to the annular polymer elastomer sample; S5, acquiring the stress response signal of the annular polymer elastomer sample and performing spectral analysis to obtain even-order harmonic signals. This invention, employing the aforementioned tensile testing system and analysis method for polymer elastomers with resistance to wall slip, eliminates measurement artifacts introduced by geometric mismatch in hardware construction and overcomes the defect of misjudging even-order harmonics, providing a new high-sensitivity detection dimension for the characterization of the microstructure of polymer materials.

1. The name of the design product: hot field emission scanning electron microscope (8200). 2. The use of the design product: precision scientific instrument for high-resolution topography observation and microstructure analysis of sample surface at nanometer scale. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

Systems and methods are provided for correction and harmonization of data from multiple devices, such as scientific instruments. Embodiments of the present disclosure provide systems and methods to automate this process to increase data throughput while standardizing that data despite differences in instrument settings and the challenges of proprietary software. For example, embodiments of the present disclosure include a functioning workflow for acquiring and digesting in very large datasets generated by scientific instruments for the oceanic microbiome proteome which can harmonize data taken from instruments of multiple make, model, and settings and detect flawed data / malfunctioning instruments.

This system / technique provides a way to facilitate the resolution of large-scale language models of disruptions in scientific instrument workflows. [Solution] In various embodiments, the system can cause scientific instruments (e.g., charged particle microscopes, chromatographs, mass spectrometers) to perform a workflow on a sample. In various embodiments, the system can retrieve runtime data logged by the scientific instrument during the workflow in response to the scientific instrument generating an error message that interrupts the workflow. In various cases, the system can synthesize a first text explaining why the workflow was interrupted by running a large-scale language model on the error message and runtime data.

Disclosed herein are scientific instrument support systems, as well as related methods, computing devices, and computer-readable media. A scientific instrument support apparatus is disclosed comprising generating logic to generate mass spectrum data during a tandem mass tag labeling experiment including a plurality of channels, determining logic to determine, in the generated mass spectrum data, a correction ratio between a first reporter ion peak intensity corresponding to a first non-deuterated tag and a second reporter ion peak intensity corresponding to a first deuterated tag, and normalizing logic to normalize reporter ion intensities corresponding to a second non-deuterated tag and a second deuterated tag based on the determined correction ratio.

This invention belongs to the field of precision scientific instruments and vacuum technology, and discloses a liquid ultrafast electron diffraction experimental station integrating a THz diagnostic structure. The station includes a vacuum chamber, a double-sided flange arranged upstream of the liquid film location along the electron beam transmission path, a position adjustment structure, a vacuum differential pipe, and a THz diagnostic structure. The double-sided flange is fixed between the vacuum pipe flange outside the vacuum chamber and the vacuum chamber itself. The position adjustment structure is axially and adjustablely fixed coaxially within the double-sided flange. The vacuum differential pipe is coaxially fixed within the position adjustment structure and passes through the sidewall of the vacuum chamber. The THz diagnostic structure is positioned between the vacuum differential pipe and the liquid film location. This invention integrates a vacuum differential system and a THz electron beam diagnostic system in situ within a single vacuum chamber, achieving synchronous compatibility between liquid-phase ultrafast electron diffraction and electron pulse time-domain diagnostics, ensuring the accuracy of time-resolved assessment of liquid-phase structure dynamics.

A method of generating computer-readable code executable by a controller of a scientific instrument is provided. The method comprises receiving instructions in a natural language. The method further c

Disclosed herein are scientific instrument support systems, as well as related methods, computing devices, and computer-readable media. For example, in some embodiments, an example method may comprise receiving, by a first device located at a premises and from a second device located external to the premises, and via a network, configuration data for a charged particle microscope located at the premises. The method may comprise updating, by the first device and based on the configuration data, one or more configuration settings associated with the charged particle microscope. The method may comprise causing, based on the updated one or more configuration settings, one or more operations associated with the charged particle microscope to be performed.

Systems and methods are provided for correction and harmonization of data from multiple devices, such as scientific instruments. Embodiments of the present disclosure provide systems and methods to automate this process to increase data throughput while standardizing that data despite differences in instrument settings and the challenges of proprietary software. For example, embodiments of the present disclosure include a functioning workflow for acquiring and digesting in very large datasets generated by scientific instruments for the oceanic microbiome proteome which can harmonize data taken from instruments of multiple make, model, and settings and detect flawed data / malfunctioning instruments.

This application relates to a computer-implemented method, computer-readable medium, and system for storing heterogeneous sequences of discrete-time data determined from processes producing chemicals, pharmaceuticals, biopharmaceuticals, and / or biological products. The method includes receiving discrete-time data, which includes first data from a first scientific instrument. The method also includes receiving second data from a second scientific instrument. The first and second scientific instruments each have different corresponding observation types, the first data having a first observation type, and the second data having a second observation type. The method further includes: storing the first data and first metadata in a first record of a database, the first data being stored according to the function of stored data mapped by the first observation type; and storing the second data and second metadata in a second record of the database, the second data being stored according to the function of stored data mapped by the second observation type.

Systems, methods, or techniques are provided for lamella lift-out based on sample plane orientation. In various embodiments, a method can comprise adjusting, by a scientific instrument, stage tilt and rotation of a sample stage of the scientific instrument based on plane orientation of a sample.

Systems / techniques are provided for facilitating large language model parsing of scientific instrument workflow interruptions. In various embodiments, the system may cause a scientific instrument (e.g., charged particle microscope, chromatograph, mass spectrometer) to perform a workflow on a sample. In various aspects, the system may retrieve runtime data recorded by the scientific instrument during the workflow in response to the scientific instrument generating an error message to interrupt the workflow. In various cases, the system may synthesize first text that interprets why the workflow is interrupted via execution of a large language model on error messages and runtime data.

Disclosed herein are scientific instrument support systems, as well as related methods, computing devices, and computer-readable media. For example, in some embodiments, a support system for a scientific instrument includes first, second, and third logic. The first logic is configured to acquire a first data file via a detector of the instrument. The second logic is configured to convert the first data file into a plurality of second data files stored in object storage. Each of the second files is named using a preferred file naming convention. The third logic is configured to process a request for a data portion of the first data file and provide the data portion by accessing one or more of the first memory cache, the second memory cache, and the object storage to retrieve a corresponding portion of a corresponding one of the second data files identified based on the file naming convention.

A scientific instrument, such as an electron microscope, is disclosed, and the scientific instrument includes a movable stage with a sample holder. A finger-shaped cryostat contacts a heat sink and includes a cooling plate configured to contact the sample holder to cool the sample holder in a rapid cooling position. A flexible heat-conducting component thermally connects the sample holder and the finger-shaped cryostat to cool the sample holder away from the rapid cooling position, where the sample can be studied, imaged, etc. In the disclosed embodiments, both the cryostat and the sample holder are movable, or only the finger-shaped cryostat moves between the rapid cooling configuration and other configurations. A corresponding method for operating the scientific instrument is also disclosed. This disclosure advantageously combines rapid cooling in the rapid cooling position with reduced restrictions on movement of the sample holder away from its parking position.

The application provides a scientific instrument procurement selection method and device based on artificial intelligence, and belongs to the technical field of artificial intelligence, and comprises the following steps: constructing a knowledge graph of all initial instruments; calculating the evaluation value of each initial instrument in each evaluation dimension; matching in the knowledge graph according to the selection requirement information input by a user to obtain a candidate instrument set; extracting the evaluation value of each candidate instrument in the candidate instrument set in all evaluation dimensions; performing weighted calculation on the evaluation values corresponding to all candidate instruments according to the dimension weight parameters set by the user to obtain a personalized comprehensive score; and generating a selection scheme containing an instrument recommendation result and data traceability information according to the personalized comprehensive score and the associated information in the knowledge graph. The application constructs a knowledge graph fusing multi-source data, and generates a scientific instrument procurement selection scheme based on artificial intelligence in combination with multi-dimensional evaluation, so that accurate recommendation of scientific instrument procurement selection based on artificial intelligence is realized.

The invention relates to the technical field of geometric quantity precision measurement, in particular to a self-evolution high-precision angle measurement method based on double-grating iteration mutual calibration, and realizes self-evolution and improvement of measurement precision based on a double-grating iteration mutual calibration principle. According to the method, through mutual calibration of the two coaxially-installed gratings and combination of an advanced nonlinear optimization algorithm, the dependence of a traditional measurement method on an ultra-high-precision standard device is broken through, and a brand new technical solution is provided for the fields of precision manufacturing, scientific instruments and the like.

Disclosed herein are scientific instrument support systems, as well as related methods, apparatus, computing devices, and computer-readable media. Some embodiments provide a scientific instrument including detectors supporting one or more spectroscopic modalities and an imaging modality and further including an electronic controller configured to process streams of measurements received from the detectors. The electronic controller operates to generate a base image of the sample based on the measurements corresponding to the imaging modality and further operates to generate an anomaly map of the sample based on the base image and further based on differences between measured and autoencoder-reconstructed spectra corresponding to different pixels of the base image. In at least some instances, the anomaly map can beneficially be used in a quality-control procedure to identify, within seconds, specific problem spots in the sample for more-detailed inspection and / or analyses.

Systems / techniques are provided to facilitate the calibration of mass analyzers using reinforcement learning. In various embodiments, a system can predict, by executing one or more neural reinforcement learning networks on current state data of a mass analyzer in a scientific instrument, which adjustments to one or more operating parameters of the mass analyzer would cause it to approach a calibrated state. These operating parameters include an electrode voltage or timing of the mass analyzer. Based on these adjustments, the system can modify the operating parameter(s) in various ways, thereby causing the mass analyzer to approach the calibrated state.

The invention provides an information recommendation method and device in the field of scientific instruments, and belongs to the technical field of data processing.The method comprises the steps that a search request is received, the search request comprises first user identity information and first search information, the first user identity information corresponds to a first user identity feature, and the first search information corresponds to a second user identity feature; the first user identity feature comprises at least one of a city where the user is located, a gender of the user, an education background of the user, a user type and a user basic portrait; obtaining a prediction probability of each browsing direction based on the first user identity information and the first search information; and outputting a preset number of browsing directions with the highest prediction probability. According to the method, the discrimination capability of the prediction model on the user intention is improved by integrating the user identity features and the search information, the recommendation accuracy is improved, and the user experience is optimized.