10 results about "CHEMISTRY METHODS" patented technology

The present invention provides a novel integrated platform that enables the verification of manufacturing processes for complex natural products, as well as the standardization and evaluation of complex natural products. This platform allows for the "system-wide" characterization of complex mixtures contained in therapeutic and / or health-promoting products based on or composed of natural substances, without limiting the approach to reductionist chemical approaches targeting single markers. This is achieved through the integration of qualitative and quantitative fingerprint characterization data metabolomics and physical and biophysical activity data for the mixtures, thereby providing a product characterization that forms the basis for verifying manufacturing processes that can ensure the reproducibility of efficacy and safety across different batches of the product. The analytical platform described herein enables the assurance of a complex natural product as a whole, by considering all the characteristics of its quality and efficacy, through a multidimensional analytical approach, in order to ensure reproducibility regarding efficacy and safety.

The invention discloses a method for screening a quality difference marker of a Mongolian medicine Gaohubaone-6, and relates to the technical field of medicine detection. Comprising the following steps: S1, carrying out multi-index quantitative analysis on the Mongolian medicine Goler Figure Bione-6 by adopting an HPLC-MS / MS technology, and screening out a quality difference component group in combination with mode recognition-machine learning-weight coefficient analysis; s2, on the basis of a serum pharmaceutical chemistry method and an HPLC-Q-Exactive MS technology, comparing the difference between the in-vitro inherent chemical components and the serum migration components of the Gaichubaone-6 by adopting an analysis process of spectrum library retrieval and mass spectrum recognition, and analyzing a serum migration component group of the Gaichubaone-6; and S3, confirming a quality difference marker based on the common components of the quality difference component group and the serum migration component group. The method not only pays attention to quality difference components of the preparation, but also considers in-vivo functional components, and the quality of the preparation can be objectively, systematically and comprehensively analyzed.

This invention discloses an in-situ detection device and method for the intrinsic content of multiple components, belonging to the field of metal material detection and analysis technology. The implementation method of this invention is as follows: 1. Setting sample measurement indicators; 2. Measuring sample measurement indicators using standard chemical methods; 3. Using a robotic arm to pick up the sample to be tested, and acquiring the infrared spectrum of the sample using an infrared signal acquisition spectrometer to form raw spectral data; 4. Adaptively preprocessing the raw spectral data using a data processing module that removes abnormal spectra and eliminates baseline drift and scattering to form preprocessed spectral data; 5. Constructing a multi-indicator joint quantitative correction model using partial least squares and variable selection methods, and training the model using a correction set and sample measurement indicators; inputting the validation set into the trained model to obtain the detection accuracy of the intrinsic content of multiple components; 6. Outputting the detection results of the intrinsic content of multiple components; Compared with the prior art, this invention achieves simultaneous detection of the intrinsic content of multiple components.

This invention belongs to the field of ionic liquid property prediction, and discloses a method and system for predicting ionic liquid properties. The method includes: obtaining a global structural feature vector of the ionic liquid that does not change with environmental factors from ionic liquid data; inputting the feature vector into a dual-branch neural network for decoupled calculation, with the main branch outputting the macroscopic property prediction value of the ionic liquid; outputting thermodynamic reference constants that constrain the properties to be predicted from the auxiliary branch; determining a joint loss function by dynamically weighting and fusing the residual loss term and the thermodynamic physical constraint loss term through empirical data fitting; training the dual-branch neural network based on the joint loss function; inputting the features of the ionic liquid to be tested and environmental factors into the trained dual-branch neural network, with the main branch outputting the final property prediction result of the ionic liquid that conforms to the thermodynamic evolution law. This invention solves the problems of insufficient accuracy of thermodynamic models and low efficiency of computational chemistry methods in existing ionic liquid property prediction technologies.

The invention discloses an evaluation method for a deep-source CO2 tracer mineral formation process, and belongs to the field of petroleum and natural gas geology. According to the method, firstly, the occurrence characteristics and the formation time sequence of the deep-source CO2 tracer mineral are represented through a petrology testing system; further utilizing geochemical tests of carbon, oxygen and strontium isotopes, trace elements and the like to judge the carbon source property and cause background; on the basis, the time-space distribution rule, the time sequence relation and the cause background of the minerals are synthesized, the charging period of the CO2 fluid is divided, and the charging rule is clarified; further, determining a charging time window of the carbon source fluid in combination with a geochemical method; and finally, geochemical simulation software is utilized to construct a reservoir model based on the filling time, and the formation process of minerals under different periods of fluid filling is dynamically simulated. According to the invention, systematic and dynamic evaluation of the deep CO2 fluid migration-precipitation history is realized, and key technical support is provided for research of oil and gas accumulation, carbon sequestration and the like.

The application discloses a method and system for analyzing an enzymatic synthesis mechanism of N-nitrosourea compounds, and relates to the technical fields of artificial intelligence, computational chemistry and synthetic biology. K a The application quantitatively determines the protonation state of a substrate by predicting the p of each ionizable site of the substrate, and combining quantum chemistry methods to perform structure optimization and free energy calculation; then, molecular dynamics simulation is performed to determine the optimal reaction conformation and serve as an initial conformation, and based on the initial conformation, a plurality of potential reaction paths are acquired, and QM / MM calculation is combined, the process determines the path of hydrogen migration-attack under the optimal reaction conformation from the atomic level, thereby establishing a complete quantitative relationship from the microenvironment characteristics of the enzyme active center to the protonation state of the substrate, and then to the reaction activity, and revealing the complete mechanism of the enzymatic synthesis of the N-nitrosourea pharmacophore from the atomic level.

Targetry coupled separation refers to enhancing the production of a predetermined radiation product through the selection of a target (including selection of the target material and the material's physical structure) and separation chemistry in order to optimize the recovery of the predetermined radiation product. This disclosure describes systems and methods for creating (through irradiation) and removing one or more desired radioisotopes from a target and further describes systems and methods that allow the same target to undergo multiple irradiations and separation operations without damage to the target. In contrast with the prior art that requires complete dissolution or destruction of a target before recovery of any irradiation products, the repeated reuse of the same physical target allowed by targetry coupled separation represents a significant increase in efficiency and decrease in cost over the prior art.

The invention provides a quasi-reaction path adaptive enhanced sampling method, which is used for constructing a reaction machine learning potential database. The method comprises the following steps: firstly, generating a catalyst ligand candidate space by using a computer-aided molecular design tool based on a skeleton, and quickly generating a transition state initial conjecture through a GENiniTS-RS algorithm; the method comprises the core steps of combining an intrinsic reaction coordinate path of a semi-empirical quantum chemistry method (GFN2-xTB), and performing disturbance sampling around an IRC path by using normal modulus sampling so as to capture complex characteristics of a reaction potential energy surface. Then, a committee queries an active learning strategy to screen a high-information-entropy configuration to carry out high-precision density functional theory (DFT) marking; compared with full DFT sampling, the method has the advantages that the calculation cost is remarkably reduced, meanwhile, the success rate and precision of a machine learning model in transition state optimization are improved through enhanced sampling, and key data support is provided for high-throughput screening of efficient catalysts.

The invention discloses a method and system for analyzing an enzymatic synthesis mechanism of N-nitrosourea compounds, and relates to the technical field of artificial intelligence, computational chemistry and synthetic biology. The method comprises the steps that firstly, the pKa value of each ionizable site of a substrate is predicted, and structural optimization and free energy calculation are conducted in combination with a quantum chemistry method; the protonation state of the substrate is quantitatively determined in the process; then molecular dynamics simulation is carried out to define an optimal reaction conformation and serve as an initial conformation, a plurality of potential reaction paths are obtained based on the initial conformation, QM / MM calculation is combined, and the hydrogen migration-attack path under the optimal reaction conformation is defined from the atomic level in the process, so that an enzyme activity center microenvironment characteristic to a substance protonation state is established, and a hydrogen migration-attack path under the optimal reaction conformation is obtained. The complete quantitative relation from the reaction activity to the reaction activity is realized, and the complete mechanism of N-nitrosourea pharmacophore enzymatic synthesis is disclosed from the atomic level.