18 results about "Reaction rate constant" patented technology

The invention relates to a method for predicting the carbon residue value of heavy oil hydrogenation generated oil, and the method comprises the following steps: obtaining a heavy oil raw material, and obtaining the characterization data of the characteristic properties of the heavy oil raw material; obtaining hydrogenated generated oil to be detected, wherein the hydrogenated generated oil to be detected is obtained by carrying out hydrogenation carbon residue removal reaction on the heavy oil raw material; substituting the characterization data of the characteristic properties of the heavy oil raw material into the characteristic factor equation of the hydrogenation carbon residue removal reaction, and calculating the characteristic factor of the hydrogenation carbon residue removal reaction; substituting the characteristic factor into the characteristic factor-reaction rate constant relation equation of the hydrogenation carbon residue removal reaction, and calculating the reaction rate constant of the hydrogenation carbon residue removal reaction; and substituting the reaction rate constant into the reaction kinetic equation of the hydrogenation carbon residue removal reaction, and calculating the predicted carbon residue value of the hydrogenation generated oil to be detected. By adopting the method disclosed by the invention, the carbon residue value of the heavy oil hydrogenation generated oil can be accurately predicted.

The invention particularly relates to a method for determining a reaction rate constant of tetravalent iron and organic pollutants by using a chemiluminescence method, and belongs to the technical field of water quality detection. According to the method, on the basis of a chemiluminescence reaction between Fe (IV) and naproxen (NAP), a target organic pollutant (TrOC) is introduced, the quenching effect of the target organic pollutant on a chemiluminescence signal is measured, and a competitive kinetic model between the chemiluminescence quenching capacity (CLQC) and a secondary reaction rate constant (kFe (IV), TrOC) of Fe (IV) on the target pollutant is constructed. According to the method, the concentration of Fe (IV) does not need to be monitored in real time, and the reaction activity between Fe (IV) and various pollutants can be directly and rapidly measured only by comparing the intensity change of the chemiluminescence signals when the target pollutants exist and do not exist.

The present application relates to the technical field of pollution detection, in particular to a water body heavy metal chromium pollution detection method and system, the method comprising the following steps: obtaining the concentration of water body dissolved organic matter, hydrogen ion concentration, oxidation-reduction potential, temperature and initial hexavalent chromium concentration and normalizing, determining the reduction reaction rate constant according to the temperature and oxidation-reduction potential, predicting the reduction rate of hexavalent chromium, the theoretical reduction amount and the theoretical residual concentration, collecting the online electrochemical concentration and the unmanned aerial vehicle hyperspectral inversion concentration and performing difference verification, respectively correcting the electrochemical concentration and the hyperspectral concentration when there is data contradiction, and fusing the two types of correction results to judge the pollution state. In the present application, by establishing a hexavalent chromium natural evolution reference and combining multi-source observation consistency verification, the electrochemical underestimation caused by organic matter passivation and the hyperspectral overestimation caused by spectral background are identified, compensation correction and background stripping are completed, and the accuracy and reliability of chromium pollution detection in complex water bodies are improved.

The application discloses a preparation method of oil displacement and plugging integrated gel, and particularly relates to the technical field of oilfield chemicals, S1, reaction kinetics parameter solving; S2, dynamic topology network evolution simulation; S3, gel network crosslinking density calculation; S4, gel macroscopic mechanics parameter derivation; S5, pore throat scale plugging state determination. The application solves the reaction probability rate constant of initiation, chain growth, chain transfer and chemical crosslinking, and based on the dynamic simulation of the probability set starting time step promotion, realizes the recurrence of the growth of polymer chain and the network topology evolution process from the molecular reaction kinetics level. The microcosmic simulation mode starting from the chemical reaction mechanism replaces the traditional macroscopic mixing experiment, makes the formation process of the gel network transparent and traceable, and lays a foundation for deeply understanding the influence of the formula parameters on the network structure.

The invention relates to the technical field of water treatment, and discloses a modular intelligent mine wastewater treatment system, which comprises a data acquisition module, a data processing module and a control module, the calculation module is used for calculating a zero delay reaction rate constant by utilizing Smith estimation; the decision control module is used for determining a virtual topological structure and driving a valve matrix; the configuration module is used for mapping the physical unit to a logic position based on the chemical saturation index; and the dosing execution module is used for executing gradient collaborative dosing according to the stage number. The real-time apparent reaction rate constant with the zero-delay characteristic is solved by introducing the Smith estimation compensation algorithm, constructing the nominal model and superposing the actual observation deviation, the real working condition can be obtained at the moment of pollutant concentration fluctuation or reaction activity change, and the real-time performance of the real-time apparent reaction rate constant is improved. Therefore, the topology reconstruction decision is completed before the degradation-resistant wastewater flows through the main treatment unit, and the phenomenon that initial discharge exceeds the standard due to insufficient timeliness of traditional feedback control is avoided.

The application discloses a pecan oil shelf life prediction model and a construction method thereof. The initial peroxide value, storage temperature and terminal peroxide value of pecan oil are input into the pecan oil shelf life prediction model, so that the shelf life of cold-pressed pecan oil or hot-pressed pecan oil can be predicted. The construction method comprises the following steps: firstly, storing the oil sample at constant temperature and determining the peroxide value; secondly, substituting into a first-order reaction kinetics equation to obtain a peroxide value change rate constant; and finally, substituting into an Arrhenius equation to obtain a pecan oil peroxide value shelf life prediction model. The pecan oil shelf life prediction model provided by the application can predict the shelf life of cold-pressed or hot-pressed pecan oil stored at 20 DEG C to 60 DEG C, and the prediction accuracy can reach more than 80%, and the pecan oil shelf life prediction model has the characteristics of real-time, high efficiency and accuracy, and provides a theoretical basis for evaluating the stability and quality control of pecan oil.

The invention provides a method for obtaining reaction kinetic parameters based on in-situ infrared spectroscopy, which comprises the following steps: in a chemical reaction process, carrying out on-line detection on a reactant A by adopting an in-situ infrared spectrometer to obtain a curve of the absorbance of the reactant A along with time change, and obtaining a corrected molar absorption coefficient K'according to a formula 1-1; performing linear fitting on the changing curve of the reactant A according to a formula 1-2 to obtain a reaction series n of the reactant A and a corrected rate constant k '; the reaction series n of the reactant A at different temperatures and the corrected rate constant k'are obtained, linear fitting is conducted on lnk 'along with the change trend of 1 / T according to formulas 1-3, and the activation energy Ea and the corrected pre-exponential factor A' are obtained. According to the method provided by the invention, the influence of factors such as interval sampling and human factors is avoided, the calculation is simple, the obtained data is accurate, and the applicability is wider.

The invention provides a mass-to-charge ratio-based proton transfer reaction time-of-flight mass spectrometer calibration method, and the method comprises the steps: S1, obtaining a function relation between the sensitivity of each standard gas group and the charge ratio of a corresponding protonation product, each standard gas group independently comprises organic matter gases belonging to the same category but different specific categories; s2, respectively substituting the mass-to-charge ratios of the protonated products of different gas components in the gas to be detected into the function relationship of the respective corresponding standard gas group, and calculating to obtain the respective sensitivity of the different gas components in the gas to be detected; and S3, calculating the concentration of the gas component in the gas to be detected according to the respective peak response intensity and sensitivity of different gas components in the gas to be detected. According to the method, the reaction rate constant between the volatile organic compound and the hydrated hydrogen ions does not need to be obtained in advance, and the quantitative analysis efficiency of the proton transfer reaction time-of-flight mass spectrometer in a complex environmental sample is remarkably improved.

This invention relates to the field of computer-aided process design technology, specifically to a method and system for optimizing the formulation of biodegradable tableware materials. The method includes the following steps: generating equilibrium molecular conformations based on atomic coordinates and calculating initial formulation component parameters; converting modulus parameters to generate theoretical elastic recovery strain parameters; mapping models to calculate deformation and marking diffusion characteristic length parameters; calculating diffusion coefficients and flux parameters to update local hydrogen ion concentration indices; updating reaction rate constants and integrating them to generate finalized formulation structural parameters. In this invention, a microscopic molecular dynamics model is constructed to analyze interface voids to quantitatively assess compatibility; relaxation time spectra are used to invert elastic recovery strain to predict deformation risk; autocatalytic reaction and diffusion theories are combined to track hydrogen ion concentration evolution; a dynamic mapping between degradation and failure is established; and full life-cycle verification is completed in a virtual environment, significantly shortening the R&D cycle and reducing trial-and-error costs.

The invention relates to an electrochemical auxiliary material surface functional group regulation and control method which comprises the following steps: applying a control potential to a material in an electrochemical system, so that a non-uniform charge distribution region is formed on the surface of the material, reaction activity difference is generated on an interface, and a functional group reaction is limited to only occur in a potential stable section; the electric potential fluctuation in unit area is smaller than a set threshold value; a functional group precursor is introduced into a limited region, a directional electrochemical reaction is carried out under the condition of applying potential, and the generated functional group moves towards a region with low energy potential along a potential gradient under the action of interface charge migration, so that stable adsorption is realized in the region; determining the type of a target functional group formed by the site according to the local electrochemical parameters of the functional group generation site; when two or more than two functional group precursors exist in the system, a priority rule is established based on a reaction potential window, an interface reaction rate constant and adsorption affinity of a material to the precursors, a first preferred reaction path is selected, and other reaction channels are blocked.

The invention discloses an atmospheric reaction kinetic parameter intelligent prediction method and system fusing multilevel quantum chemical characterization. The method comprises the following steps: acquiring experimental measurement data, respectively acquiring a descriptor table data set and a plurality of quantum chemistry descriptors according to the experimental measurement data, further respectively acquiring a new feature set serving as model input and a reaction rate constant data set serving as model output, and then acquiring an optimal machine learning model according to the input and the output, and the optimal machine learning model is used for predicting the reaction rate constant of the reaction of the organic compound to be detected and the hydroxyl radical. According to the method, parallel training is carried out by integrating models of multiple decision trees, the complex nonlinear relation between molecular structure parameters and reaction kinetics is effectively analyzed, compared with a traditional regression model, the analysis capacity of high-dimensional data such as interpretable quantum chemistry descriptors is remarkably improved, and the calculation complexity is greatly reduced while the prediction precision is guaranteed.

The application discloses a method for calculating chemical reaction time under adiabatic conditions, comprising determining physical property parameters and kinetic parameters of a reaction system; calculating adiabatic temperature rise of the reaction system, and establishing a linear relationship between temperature and conversion rate; based on the Arrhenius formula, a functional relationship between the reaction rate constant and the conversion rate is established; according to the reaction order, a numerical integral expression of the reaction time is constructed; and the reaction time is solved by using a numerical integral method. The method can make the calculation result more consistent with the actual adiabatic reaction process, and has higher accuracy, and is suitable for different reaction orders, so that engineering and technical personnel can perform corresponding calculation for specific reaction systems, assist relevant personnel to more accurately judge emergency response time, and take emergency response measures corresponding to the reaction time. The application also discloses a calculation system for chemical reaction time under adiabatic conditions and a storage medium, which have the same advantages as the above method.

The invention relates to a method for predicting sulfur content of heavy oil hydrogenated oil, which comprises the following steps of: calculating characteristic factors and reaction rate constants of a heavy oil raw material for hydrodesulfurization reaction according to specific characteristic properties of the heavy oil raw material, and obtaining the predicted sulfur content of the hydrogenated oil according to a reaction kinetic equation. By adopting the method disclosed by the invention, the sulfur content of the heavy oil hydrogenation generated oil can be accurately predicted.

The invention discloses a dynamic modeling method for a carbon capture system based on intelligent estimation of reaction kinetic parameters, and belongs to the technical field of carbon capture. On the basis of a double-deep neural network structure, an Arrhenius equation and a primary reaction kinetic equation are respectively embedded into a grid result calculation and loss function, so that a physical information neural network model for realizing intelligent estimation of a reaction rate constant is formed; and in combination with an estimated value output by the physical information neural network and a carbon capture system mechanism model based on a constitutive equation, a carbon capture system'data driving + mechanism 'model considering nonlinear dynamic characteristics of reaction kinetic parameters is constructed. According to the method, the reaction dynamic characteristics of the carbon capture system in the actual operation process are fully considered, and the adaptability and precision of the carbon capture system model in the complex industrial environment can be improved.

The invention provides a chemical kinetics measurement method for an air dissociation process, which comprises the following steps: synchronously detecting an air dissociation area by using a multi-channel spectrograph and a wide-spectrum radiometer to respectively obtain a multi-band spectral signal and a wide-spectrum thermal radiation energy spectrum signal; on the basis of the multiband spectral signal, identifying characteristic spectral lines of the target component and the free electron, and determining radiation intensity corresponding to each dissociation product; according to the radiation intensity corresponding to each dissociation product, combining with a local thermodynamic equilibrium or non-equilibrium radiation transfer model to invert instantaneous concentration distribution of each dissociation product; analyzing the dynamic thermal relaxation characteristic of the wide-spectrum thermal radiation energy spectrum signal to obtain the real-time temperature field and electron density data of the reaction area; and taking the instantaneous concentration distribution, the electron density and the temperature field data of each dissociation product as boundary conditions, substituting the boundary conditions into a rate equation set containing a non-equilibrium chemical-ionization reaction path, and determining a rate constant and a dominant path of a target reaction.

This invention provides a method for predicting current-voltage characteristics of a fuel cell equipped with a catalyst composed of any material, enabling easy and highly accurate prediction of its current-voltage characteristics. [Solution] The present invention provides a method for predicting current-voltage characteristics, comprising: a first step of performing RRDE measurement to obtain the measured value of the electrode current; a second step of solving equation (1) below, which relates to the concentration distribution of oxygen molecules and hydrogen peroxide molecules on the electrode surface of the fuel cell, to obtain the theoretical value of the electrode current; a third step of mathematically optimizing the theoretical value so that the difference between the measured value and the theoretical value is small; and a fourth step of substituting the mathematically optimized theoretical value into the Butler-Volmer equation to obtain the activation voltage under conditions where the electrode reaction is in equilibrium, and thereby determining the current-voltage characteristics. The theoretical value obtained in the second step is the sum of the electrode currents for each active site. TIFF2026075784000041.tif14170 (C is the concentration distribution, D is the diffusion coefficient, and K is the reaction rate constant.)

The application belongs to the cross field of nanomaterials and coordination chemistry, and particularly relates to an Ag 19 Pd nanocluster, a preparation method and application thereof 141 H 126 Ag 19 Cl3N 18 P6Pd, which is abbreviated as Ag 19 Pd(dpa)6(dppp)3Cl3, belongs to a triclinic system; a space group is P-1, alpha=80.073(3) degrees, beta=75.948(3) degrees, gamma=88.025(3) degrees, in addition, the nanocluster has high monodispersity and stability, and contains an unsaturated mu3-Ag active site. The Ag 19 Pd nanocluster of the application has an atomic level accurate structure and an unsaturated active site, and after forming a supported catalyst with a commercially available TiO2, exhibits high catalytic activity in a p-nitrophenol reduction reaction, and a reaction rate constant is as high as 1.26 min ‑1 , and has a broad development prospect.

The embodiment of the invention provides a hydrogen production quantity prediction method, device and equipment, a medium and a product, and belongs to the technical field of geological exploration. The method comprises the following steps: constructing a geologic model of a to-be-predicted area, wherein the geologic model comprises a plurality of three-dimensional grid units; determining key parameters of each three-dimensional grid unit in the plurality of three-dimensional grid units based on geological features of the to-be-predicted region, wherein the key parameters comprise at least one of reaction rate constant, effective reaction volume, rock porosity, rock density, reaction duration, hydrogen production efficiency and hydrogen leakage flux; calculating based on the key parameters to obtain the unit hydrogen generation amount of each three-dimensional grid unit; and superposing the unit hydrogen generation amount of each three-dimensional grid unit to obtain a target hydrogen generation amount of the to-be-predicted region. The method can accurately predict the hydrogen generation amount of the target area.