| Voltage contrast observed in scanning electron microscopes (SEM) is a technique used to visualize electrical potential differences in electronic devices. It is a phenomenon where regions of different electrical potentials (voltages) in a sample produce varying intensities or brightness in an SEM image. It allows for the visualization of electrical activity or faults within electronic devices, such as circuits. Linearization of voltage contrast in a SEM refers to making the contrast more directly proportional to the actual voltage differences across different regions of a sample. Several factors influence the linearization of voltage contrast, and controlling these can help improve the accuracy of voltage measurements and diagnostics:
- Beam Energy (Electron Beam Energy):
- Low Beam Energy: Higher sensitivity to surface voltages, leading to better contrast for small voltage differences but at the expense of spatial resolution.
- High Beam Energy: Deeper penetration into the sample, which may reduce surface sensitivity and voltage contrast. It can cause more complex interactions between the beam and sample, affecting linearization.
Figure 0041a, based on the approximation in Equation 0041a, shows that the voltage contrast increases non-linearly with beam energy and approaches saturation at higher energies.
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Figure 0041a. Voltage contrast versus beam energy. |
- Secondary Electron Emission (SEE) Yield:
- Local Surface Conditions: The number of secondary electrons emitted depends on the local electric field and the material properties. Higher voltages can increase the yield of secondary electrons, affecting the contrast.
- Material Properties: Different materials emit secondary electrons at different rates, making it difficult to linearize the voltage contrast without compensating for these variations.
Figure 0041b, based on the approximation in Equation 0041b, shows the voltage contrast increases linearly with SEE yield up to a maximum threshold of 1.
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Figure 0041b. Voltage contrast versus SEE yield. |
- Surface Charging:
- Charging Effects: If the sample is non-conductive or poorly grounded, surface charging can distort the electron trajectories and reduce the accuracy of voltage contrast. This leads to nonlinear behavior as charging effects dominate, especially in areas with high voltage or poor conductivity.
Figure 0041c, based on the approximation in Equation 0041c, shows a non-linear increase in contrast as charging builds up, with saturation at higher levels of charging.
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Figure 0041c. Voltage contrast versus surface charging. |
- Detector Configuration:
- Detector Placement: The position and type of detector used (e.g., Everhart-Thornley detector, in-lens detector) affect how electrons are collected. The electron collection efficiency changes with the local electric fields, which in turn impacts voltage contrast linearity.
- Electron Collection Angle: The angle at which the detector collects secondary electrons influences how variations in the electric field affect the signal, thereby impacting the linearization.
Figure 0041d, based on the approximation in Equation 0041d, shows the contrast decreases with increasing detector angle, following a cosine function.
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Figure 0041d. Voltage contrast versus detector angle. |
- Working Distance:
- Electron Beam-Sample Distance: The distance between the SEM electron gun and the sample (working distance) influences the interaction volume and the distribution of electric fields. Shorter working distances improve resolution and contrast but may introduce nonlinearities due to field distortions.
Figure 0041e, based on the approximation in Equation 0041e, shows the contrast increases exponentially with decreasing working distance, approaching 1 at the end.
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Figure 0041e. Voltage contrast versus working distance. |
- Sample Surface Topography:
- Surface Features: Non-uniform topography can affect the electron trajectories and secondary electron emission, leading to variations in contrast that are not directly related to voltage differences. This introduces nonlinearities, making it harder to achieve linear voltage contrast.
Figure 0041f, based on the approximation in Equation 0041f, shows the contrast depends on surface topography with a sigmoidal non-linear transition.
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Figure 0041f. Voltage contrast versus surface topography. |
- Environmental Factors (Local Fields):
- Magnetic and Electric Fields in the Chamber: External fields, such as those generated by other components in the SEM or residual fields from the sample, can affect the electron trajectories and the resulting contrast. These fields can introduce nonlinearities in voltage contrast.
Figure 0041g, based on the approximation in Equation 0041g, shows the contrast fluctuates sinusoidally with local environmental electric or magnetic field strength, indicating a cyclical influence.
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Figure 0041g. Voltage contrast versus environmental fields. |
- Beam-Sample Interaction Time:
- Dwell Time: The length of time the electron beam interacts with a specific point on the sample can influence the contrast. Longer dwell times may increase surface charging or lead to local thermal effects, which affect the contrast nonlinearly.
Figure 0041h, based on the approximation in Equation 0041h, shows in logarithmic function models, the effect of increasing interaction time, where the contrast grows logarithmically and eventually saturates.
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Figure 0041h. Voltage contrast versus interaction time. |
- Conductivity of the Sample:
- Electrical Conductivity: The electrical conductivity of the sample material directly affects how well it dissipates charge. Poor conductors may accumulate charge over time, introducing nonlinearities in voltage contrast due to unpredictable charge distribution.
Figure 0041i, based on the approximation in Equation 0041i, shows that as conductivity increases, the contrast rises non-linearly and saturates at higher conductivity levels.
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Figure 0041i. Voltage cContrast versus conductivity. |
- Backscattered Electrons:
- Backscattering Effects: The presence of backscattered electrons can influence the secondary electron yield and thus the voltage contrast. These backscattered electrons are affected by both the material composition and the local electric fields, leading to potential nonlinearity in the observed contrast.
Figure 0041j, based on the approximation in Equation 0041j, shows that the contrast decreases as the number of backscattered electrons increases, with a saturation effect as backscattering reaches a maximum.
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Figure 0041j. Voltage contrast versus backscattered electrons. |
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