Research On Biodegradation Of Bio-based Lubricants By Microbial Flora

As traditional mineral-based lubricants are non-renewable and pollute the environment,the development and utilization of biodegradable lubricants has gradually become a major trend.Trimethylolpropane esters show unique advantages as a base oil and are regarded as a very promising substitute for mineral oil.In this thesis,trimethylolpropane(TMP)triester is used as the base oil,combined with the degradation of microorganisms to carry out the following research.This paper refered to the biodegradation method of CEC L-33-A-93.Activated sludge was used to degrade the trimethylolpropane ester and mineral oil,and 5 types of co-degradation bacteria were isolated from activated sludge,three of them that had best degradation rate were cultured individually and mixedly and proved the high-efficiency degradation ability of the compound flora.The response surface optimization of the degradation conditions of the complex flora was carried out.The optimal degradation conditions for the microbial degradation of TMP triester were:temperature 30.4?,substrate concentration 104 mg/mL,and pH 6.7.Under these conditions,the predicted value of co-cultured bacteria for the degradation rate of TMP triester was 90.03%.The highest degradation rate can be obtained,and the degradation efficiency of the microbial remediation process can be improved.The base oil containing different additives was degraded,and the variation range of the degradation rate was found to be 57.1%-99.4%.Four commonly used additives were selected in this paper:dialkyl dithiophosphoric acid double ester amine salt,alkenyl succinate,2,6-di-tert-butyl-paramethyl phenol and benzotriazole.They were added to the TMP triester and degraded with activated sludge.The changes in substrate composition and microbial community changes during different degradation periods were investigated.Through highthroughput sequencing,the Proteobacteria and Actinobacteria was detected as the main bacteria with relative abundance between 48.52%and 89.94%.The second is Bacteroidetes,whose content ranges from 6.42%to 38.65%.With the change of degradation time,the microbial community in the lubricating oil system containing different additives changes greatly,and the test results show that the addition of additives reduces the diversity of microorganisms.In this thesis,the neural network model was combined with genetic algorithm to optimize the proportion of lubricant additives to obtain the highest biodegradability.TMP triester was used as base oil,and alkyl succinate(T746),alkylated diphenylamine(T534),and dialkyl dithiophosphoric acid double ester amine salt(T307)were used as additives.48 kinds of lubricants were formulated according to different additive ratios,and their degradability was determined.Through the fitting of the model,the correlation coefficient R2 of the data set is 0.9052,which has good generalization ability.The optimum additive ratio was obtained by genetic algorithm:the content of T746,0.42 wt%;T534,0.10 wt%and T307,0.48 wt%,TMP triester was 99 wt%,and the optimal biodegradation rate was 93.9%.