Research On Fast Determination Of Specific Surface Area Of Carbon Nanomaterials Based On Low Field NMR Technology

The specific surface area is a very important parameter to measure the material properties.Traditional method of measuring specific surface area has the problems of complicated testing processes and time consuming.In recent years,low-field NMR technology which has made remarkable achievements has provided a theoretical and technical basis for the rapid detection of specific surface area because of its non-destructive and fast features.Since the 20 th century,carbon nanomaterials have become a research hot topic due to its unique physicochemical properties,which are widely used in catalysis,energy storage,and hydrogen storageand biology.Thus,it is particularly important to evaluate its specific surface area accurately and rapidly.A new theory and experimental method is proposed in this research to study the relationship between the relaxation signals of low-field NMR technology and the specific surface area of carbon nanomaterials.A nonlinear mathematical model was established in order to achieve rapid detection of specific surface area.Firstly,by investigating the synthesis and characterization of four different structures of carbon nanomaterials(sheets,tubes,ribbons and shells),the parameters for predicting specific surface areawere obtained.The improved Hummers method was used to synthesize graphene oxide sheets;the graphene oxidenanoribbons were synthesized by the longitudinal unzipping method;the grapheneoxide solution was mixed with silica solutionto form a core-shell composite;HF was ultilized to remove the silica and the graphene oxide hollow spheres can be obtained.Scanning electron microscope(SEM),transmission electron microscopy(TEM),and Raman spectroscopy were ultilized to investigate four different structures of carbon nanomaterials,including the shape,size,material order and structural defects of carbon nanomaterials.Besides,the specific surface area of carbon nanomaterials was measured with the BET method.Then,the different parameters were correlated with the nuclear magnetic resonance relaxation signal for the establishment of nonlinear mathematical model.The low-field NMR technology was applied to operate its inversion calculation with the appropriate pulse sequence.Ultimately,the transverse relaxation time was chosen as a parameter for this model.According to the experimental data,the model that describe the logarithmic relationship between transverse relaxation time and concentration of different structure carbon nanomaterials was established,which can be also applied in a multivariable non-linear mathematical model related to the specific surface area of carbon nanomaterials,transverse relaxation time and concentration.The analysis shows that the data deviation is less than 8% between the results of model and the measured values;it proves that the model can achieve the good prediction and evaluation results.Finally,the established models that describe the carbon nanotubes and the graphene oxide hollow spheres are verified in the feasibility of application.Due to the geometric features of graphene oxide nanoribbons and graphene oxide hollow spheres,by measuring the inner and outer radius with the transmission electron microscopy(TEM),a function which is related to the specific surface area could be created.Then by comparing the results of functional calculation with the results obtained by model prediction,there is a good relevance between them,thus,the nonlinear mathematical modelof carbon nanomaterials which based on low-field NMR technology is effectively proved.