ScienceDaily - June 30, 2009
A new statistical analysis technique that identifies and removes systematic bias, noise and equipment-based artifacts from experimental data could lead to more precise and reliable measurement of nanomaterials and nanostructures likely to have future industrial applications. . . . "Our statistical model will be useful when the nanomaterials industry scales up from laboratory production because industrial users cannot afford to make a detailed study of every production run," said C. F. Jeff Wu, a professor in the Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. "The significant experimental errors can be filtered out automatically, which means this could be used in a manufacturing environment." Read more>>>