Preparation And Properties Of 3D Printing Alumina Ceramic Slurries

Ceramic materials have many important performance advantages such as high hardness,high strength,wear resistance,acid and alkali resistance,high temperature resistance and corrosion resistance.They are widely used in various industrial applications such as medical,electronics,machinery,aerospace and so on.In this paper,the gradation of aluminum oxide with different particle size distribution is used to study the effect of powder particle size on the viscosity of alumina photosensitive ceramic slurry.Tensorflow neural network architecture is used to establish an Artificial neural network model of ceramic slurry.The neural network model was used to predict the viscosity of ceramics with different particle sizes.The mechanical properties,XRD and SEM analysis were used to characterize the properties of the prepared ceramics.The results show that the dispersant PMA25 and powder 2?m(35.2wt%)+5?m(0wt%)+ 10?m(64.8wt%)can be selected as components of the alumina ceramic slurry,it can effectively reduce the viscosity of the slurry.The lowest viscosity of the alumina ceramic slurry is 1556.8m Pa.s.SEM analysis shows that the ceramic powder with smaller particle size is directly distributed between the powders of large particles,filling the gap between the large particles,so that the alumina powder is tightly bonded and firmer.The mechanical properties of alumina ceramics are greatly improved.The performance analysis results show that the performance of the grading sample is better than that of the ungraded sample.The shrinkage rate of the grading sample is reduced by 20.17%,the density is increased by 7.23%,and the bending strength is increased by 55.17%.