A SIMS Primer - Quantification
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Once equilibrium is reached, the ion and sputter yields stabilise and accurate quantification can be made.
The depth scale is generally applied by measuring the depth of the crater using either a surface profilometer or interference microscope and assuming a constant erosion rate. Alternatively, if the erosion rate is known from a previous calibration or analysis of a layer of known thickness, than this can be used, assuming similar bombardment conditions. It must be remembered that different materials sputter at different rates; hence, in a multilayer system an erosion rate should be determined for each layer. Once this is done the relative erosion rate between layers can be applied in future similar analyses.
To calibrate the concentration requires a material of similar, and known, composition. For example, if one is required to calibrate for boron in silicon then a reference material is required having a known amount of boron in silicon. This calibration will only apply to the B in Si system and could not, for example, be used to determine the amount of boron in stainless steel, or even another semiconductor.
The most widely applied quantification scheme is the relative sensitivity factor, RSF, where the signal arising from an impurity in a matrix is related directly to a signal of the matrix. The use of the RSF is defined by -
Impurity concentration (atoms cm-3) = RSF (Impurity signal / Matrix signal)
Note that the RSF is highly dependent on the instrument conditions and for accuracy should be determined at the same time as the unknown sample is run.
The fact that the ion yield varies for each matrix - impurity combination brings with it the implicit requirement for known reference materials. Where bulk references are not readily available, ion implantation is generally the preferred route to making reference samples.
It should be noted that the RSF method implies a dilute impurity in a homogeneous matrix. When the impurity levels rises above a few percent the ion yield may begin to vary and the accuracy of the quantification will fall.