Crystal random nucleation analysis method and system
A nucleation and crystallization technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as unsuitability, difficulty in fitting results with sample volume, inaccurate analysis results, etc.
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Embodiment 1
[0137] A kind of methane-propane natural gas hydrate in pure water system and 50ppm polyacetone system crystal stochastic nucleation data analysis method, comprises the following steps:
[0138] (1) Acquisition of crystal nucleation data: according to the isothermal method, a set of nucleation induction times to be analyzed, including m being 12 to 15 repeated experiments, was measured.
[0139] For each experiment, the nucleation induction time data acquisition steps are as follows:
[0140] (1-1) By controlling the reaction conditions such as temperature and pressure, it can be specifically: inject the reaction fluid into the crystal growth reactor or container. If high pressure conditions are required, the reaction system will be gradually cooled to the required temperature by controlling the experimental module. temperature and pressure conditions. If it involves the dissolution of high-pressure gas, such as the nucleation and growth of natural gas hydrate, it is necessar...
Embodiment 2
[0177] A crystal random nucleation data analysis system, comprising: a crystal nucleation data acquisition module, a nucleation model acquisition module, and an analysis result acquisition module;
[0178] The data acquisition module is used to acquire a group of nucleation induction times to be analyzed including m=12 to 15 repeated experiments determined by the experimental constant temperature method, and mark the abnormal breakpoint data;
[0179] The nucleation model acquisition module is connected with the data acquisition module, and is used to establish the stochastic nucleation maximum likelihood equation for m repeated experiments to obtain fitting nucleation lag time:
[0180]
[0181] Among them, t 1:m is the shortest nucleation induction time observed in m repeated experiments; (t 1:m -τ 0 ) is a penalty term to ensure that the maximum likelihood equation does not become the nucleation lag time τ 0 monotone function; t i is the induced nucleation time obser...
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