| 摘要 |
<p>A method of investigating a sample using Scanning Electron Microscopy (SEM), comprising the following steps:
- Irradiating a surface (S) of the sample using a probing electron beam in a plurality (N) of measurement sessions, each measurement session having an associated beam parameter (P) value that is chosen from a range of such values and that differs between measurement sessions;
- Detecting stimulated radiation emitted by the sample during each measurement session, associating a measurand (M) therewith and noting the value of this measurand for each measurement session, thus allowing compilation of a data set (D) of data pairs (P i , M i ), where 1 ‰¤ i ‰¤ N,
wherein:
- A statistical Blind Source Separation (BSS) technique is employed to automatically process the data set (D) and spatially resolve it into a result set (R) of imaging pairs (Q k , L k ), in which an imaging quantity (Q) having value Q k is associated with a discrete depth level L k referenced to the surface S.
A suitable example of such a BSS technique is Principal Component Analysis (PCA), e.g. employing a Karhunen-Loeve transform operation.
This technique allows high-resolution 3D volume reconstruction from a sequence of backscattered images acquired by a SEM. The method differs from known techniques in that it can be used on complex samples with unknown structure. With this method, one can compute compensation factors between high- and low-energy images using second-order (or higher-order) multivariate statistics, which allows for the effective separation of different depth layers in a sample without using a priori knowledge of sample structure. The method has a wide range of applications in life-science and material science imaging.</p> |
