文摘
This paper demonstrates the potential of a two-dimensional (2D) gradient mapping technique that utilized theeigenvalue manipulating transformation (EMT) of the spectral data set. The EMT technique, by lowering thepower of a set of eigenvalues associated with the original data, enhances the contributions of minor principlecomponents (PCs). The operation converts the original spectral data set to the one with subtle differencesamong the responses of the system being exaggerated. Small shoulders and obscure minor features may becomemuch more visible, because such small differentiating features are often captured only by the minor PCsenlarged by the EMT treatment. This improvement for 2D mapping is potentially very important to determinethe transition temperatures, which are not readily detected in convention spectral analysis.