Surface Modification Of Nanometer Calcium Carbonate And Its Adsorption Properties For Cu 2+

Nano calcium carbonate particles are small in size,have surface effect,small size effect and macro quantum tunneling effect,so in optical,thermal,electrical,mechanical and chemical have unique performance.With the development of science and technology in recent years,heavy metal water pollution is more serious,environmentally friendly water treatment adsorbent development is imminent.Nano calcium carbonate with its superior surface properties can be applied to the adsorption of heavy metals in wastewater,but because of it is easy to reunite,high surface energy and poor dispersion in water,so it is not conducive to the adsorption process.Therefore,nano calcium carbonate can be surface modification treatment,enhance its dispersion in water and surface activity,to obtain a better adsorption performance.At the same time,the adsorption performance of modified nano-calcium carbonate can be simulated by BP neural network,and it is hoped to use computer technology to guide the experiment.The details of this thesis is as follows:?1?In this thesis,nano-calcium carbonate was prepared by liquid phase method,and the nano calcium carbonate was surface modified by sodium dodecyl sulfate,sodium stearate and cetyltrimethylammonium bromide,and the effects of modifier type,modifier dosage,modification temperature,modification time and stirring rate on the activation,oil absorption,absorbance and transmittance of nano calcium carbonate were investigated,and the morphology and particle size of modified nano-calcium carbonate were tested by SEM and XRD patterns.The results show that the dispersion and surface activity of the modified nano calcium carbonate have been improved remarkably,and the best effect of nano calcium carbonate modified by cetyltrimethylammonium bromide was obtained,and the effect of nano calcium carbonate modified by cetyltrimethylammonium bromide is the best,The optimum modification conditions were as follows:modifier dosage is 1.25g,modification temperature is 110?,modification time is 45min,stirring rate is 1000rmp,the activation rate under this condition can reach about 98%.?2?The Cu²⁺was adsorbed by sodium hexadecyltrimethylammonium bromide modified nano calcium carbonate and unmodified nano calcium carbonate under the optimum modification conditions,and the effects of nano calcium carbonate addition,initial solution pH,adsorption temperature,adsorption time and initial concentration on the adsorption performance were studied,and the adsorption process is studied by adsorption isotherm,adsorption thermodynamics and adsorption kinetics.The results show that the adsorption performance of modified calcium carbonate is better than that unmodified,and when the solution temperature is 6,addition amount of nano calcium carbonate is 0.5g,adsorption time is 15h,adsorption temperature is 30?,the adsorption effect of Cu²⁺is the best.By drawing the adsorption isotherms,and the Langmuir and Freundlich model fitting of the experimental data can be found,the adsorption of Cu²⁺meets the Langmuir model,and the theoretical maximum adsorption capacity of Cu²⁺was 2.5211 mg/g and 3.1969 mg/g before and after modification,and adsorption thermodynamics studies show that the adsorption process is spontaneous.The adsorption kinetics showed that the adsorption process was in accordance with the quasi-second order kinetic model,which was mainly related to the number of active sites on the surface of nano-calcium carbonate particles and ion exchange,precipitation reaction,electron sharing or electron transfer between nano calcium carbonate and Cu²⁺,and the control step of adsorption rate is not only related to the internal diffusion of particles,but also may be related to other forms of synergistic control,so the initial concentration of solution and the amount of nano-calcium carbonate are the main factors affecting the adsorption rate.?3?By using the modified learning rate and the additional momentum factor method to improve the BP neural network,and this BP neural network was used to simulate the experimental data on the adsorption of Cu²⁺by modified nano calcium carbonate,and forecast it.It is found that the selection of appropriate learning rate and the addition of momentum factor can reduce the occurrence of local minima,avoid the occurrence of error oscillation,improve the convergence speed and ensure the stability of the network.By comparing the experimental data and the predicted values of nano calcium carbonate on the adsorption performance of heavy metal Cu²⁺in wastewater under different experimental conditions can found,the prediction results of this BP neural network model are in good agreement with the experimental results,and the error is low?up to 4.7%?,it can reflect the trend of adsorption performance,has a certain reference value and guiding significance.