Measuring Electrical Characteristics of Semiconductor Devices

Semiconductor devices form the foundation of modern electronics and play a key role in the function of electrical circuitry with components such as integrated circuits, diodes, and transistors. They have also become ubiquitous in many different applications.

The most common applications are the manufacture and design of (i) digital circuits for use in computer hardware and (ii) general analog appliances, such as radios [1]. Carrier type, dopant concentration level, and defect densities are key electrical parameters that influence the performance of semiconductor devices.

In order to evaluate device reliability, a technique that can determine these characteristics and analyze samples with nanoscale features should be used. Several techniques are available for the characterization of semiconductors, including transmission electron microscopy (TEM), scanning electron microscopy (SEM), secondary ion mass spectroscopy (SIMS), one-dimensional capacitance voltage (C-V), electron beam induced current (EBIC), etc. [2].

However, some of these techniques are destructive, require laborious sample preparation, and others still cannot effectively measure two- dimensional (2D) quantities of sub-device scale.

The need for next generation characterization tools was driven by these shortcomings as well as the realization that ever-smaller device geometry and high reliability requirements were beginning to trend within the industry. To satisfy this new degree of difficulty in the metrology of semiconductor device processes, various types of scanning probe microscopy (SPM) have been deployed to meet the challenge.

Scanning Capacitance Microscopy (SCM) and Scanning Kelvin Probe Microscopy (SKPM) combined with Atomic Force Microscopy (AFM) are the most powerful methods for characterization of semiconductor devices because of their non-destructive scanning ability, accuracy in measurements of samples with nanoscale features, and the lack of any sample preparation.

Furthermore, the integration of these methods with AFM helps to achieve both electrical property and topography data simultaneously, without modifying the tip or sample. Both SCM and SKPM were used to study an SRAM device, and the resulting data demonstrates that these methods can effectively characterize the electrical properties of semiconductor devices.


An SRAM sample [3] was studied with a Park NX20 AFM system [4]. Two different techniques – SCM and SKPM – were used to characterize the sample’s electrical properties under ambient air conditions. A cantilever with a metal-coated tip was used in both methods.

In the SCM technique [5], contact mode AFM and capacitance imaging was used to simultaneously collect sample electrical property and topography data all in a single scan. Due to capacitance changes between the sample and the tip, the sample’s electrical properties were measured from the difference in radio frequency (RF) amplitude signal.

The hardware configuration of this mode consists of several modules including the cavity resonator, frame module, SCM probehand, SCM sample holder, and an SCM cantilever chip with a connected probe wire. The SCM probehand was linked to an RF sensor to detect the capacitance change between the sample and the probe tip during scanning.

The RF sensor contains the cavity resonator and the frame module.  The frame module generates and amplifies the driving signal which oscillates the resonator during SCM measurements.

The cavity resonator converts the change in capacitance between the sample and the probe tip into an RF signal. The resonator’s resonant frequency is proportional to 1/√ LC, where ‘C’ is the capacitance and ‘L’ is inductance of the resonator. A resonance RF curve with a peak of 697.8 MHz was used for this analysis (Figure 1).

This curve was steepest at 705.4 MHz operating resonant frequency. This is the point on the curve where variations in amplitude due to frequency shifts can be easily visualized. These frequency shifts were caused by capacitance changes between the tip and the sample.

Resonance RF curve displaying the SCM detector signal (V) versus frequency (MHz). The optimal frequency to oscillate the resonator to achieve the highest detection sensitivity in SCM imaging is 705.4MHz.

Figure 1. Resonance RF curve displaying the SCM detector signal (V) versus frequency (MHz). The optimal frequency to oscillate the resonator to achieve the highest detection sensitivity in SCM imaging is 705.4MHz.

In order to obtain the final capacitance map reported here, the output signal from the resonator was observed and combined with a lock-in technique.

After optimizing the scan parameters to collect topography data, a lock-in amplifier internally embedded in the NX electronics with an AC voltage frequency of 17 kHz was utilized. SCM imaging parameters were also optimized by closely observing the SCM signal.

1 V was selected as the AC bias amplitude, while a 0° reference phase was selected for AC bias. To monitor the output signals, a second order filter with a 1 ms time constant was also chosen. Unwanted noise in the signals was removed by setting a sensitivity value of 1 V.

In SKPM mode, there are two interaction forces between the AC biased tip and the sample: the electrostatic force and Van der Waals force. The electrostatic force between the sample and the tip creates data for the sample's electrical properties, and the Van der Waals force is harnessed to generate the surface topography of the sample.

The cantilever deflection signal obtained includes both sets of data, so successful imaging requires a method that fully separates these signals. In order to accomplish this several techniques were developed, one of which was the two-pass scanning technique. However in this method, two separate scans have to be performed, making it two times slower than standard AFM imaging.

In the Park NX20, signals were separated using lock-in amplifiers integrated in electronics. This enables the acquisition of both SKPM data and topography in a single-pass scan.

The system uses two amplifiers - lock-in 1 and lock-in 2. Lock-in 1 acquires the topography data by inspecting the tip motion induced by the Van der Waals interaction, whereas lock-in 2 acquires electrical property data by studying the frequency of the AC voltage signal applied to the tip, which consecutively creates an electrostatic force interaction with the sample.

The frequency of the applied AC voltage signal is chosen to be smaller (~17 kHz) than that of the cantilever oscillation frequency (70 - 330 kHz), so that the two signals do not interfere each other [6]. In this analysis, scan parameters for topography data acquisition were optimized before selecting the lock-in 2 with an AC voltage frequency of 17 kHz.

In addition, the cantilever was applied with a separate DC bias, which was controlled to produce a feedback loop that would zero out the tip-sample electrical oscillation induced by the application of an AC bias to the cantilever. The value of this offsetting DC bias, which zeroes out the AC bias-induced electrical oscillation between the tip and the sample, is taken as a measure of surface potential [6, 7].

Results and Discussions

The sample's NMOS region is the region of interest in this analysis. Park Systems’ XEI software was used to analyze the acquired images from each method and map the acquired signals to a color table.

In both techniques, the topography data acquired show the NMOS region, but do not reveal any major data related to the level and type of dopant concentration. This data is in complete contrast with the electrical property data acquired in each mode, showing the NMOS structure as well as the level and type of doping concentrations across the sample.

Figure 2 shows the SCM measurement and topography of the SRAM sample with regions of varied doping levels from 2 x 1016 cm-3 to 2 x 1020 cm-3. In the SCM image, different regions doped with different types of dopants and at varying concentration levels can be clearly seen.

The numerous steps involved in the color gradient help to observe the concentration levels, as a number of regions on the device show different shades of dark (n dopant presence) and bright (p dopant presence) color mapping. The shading intensity correlates to the extent with which those regions are doped with very dark and bright areas with the highest and lowest levels of dopant concentration.

For instance, the SCM image clearly shows the device's p-channel with a doping level of 1 x 1017 cm-3. The narrow regions of the p-channel measuring roughly 100 nm wide reveal the separation of regions with alternating dopant types in the configuration of a standard NPN transistor.

In addition, the SCM resolution is high enough to show several darker spots present in what device fabricators proposed to be a continuously solid bright line of positively doped material on the device’s left side. Using this level of detail to characterize the sample's electrical properties can help to understand the functions of a semiconductor device.

Topography (top-left) and SCM (top-right) data acquired from the sample device. Topography line profile (red line, y-axis on left) and SCM line profile (green, y-axis on right): Doping level: p-epi (2 x 1016 cm- 3), n well (2 x 1017cm-3), p channel (1 x 1017 cm-3) , n+ contacts (2 x 1020 cm-3).

Topography (top-left) and SCM (top-right) data acquired from the sample device. Topography line profile (red line, y-axis on left) and SCM line profile (green, y-axis on right): Doping level: p-epi (2 x 1016 cm- 3), n well (2 x 1017cm-3), p channel (1 x 1017 cm-3) , n+ contacts (2 x 1020 cm-3).

Figure 2. Topography (top-left) and SCM (top-right) data acquired from the sample device. Topography line profile (red line, y-axis on left) and SCM line profile (green, y-axis on right): Doping level: p-epi (2 x 1016 cm- 3), n well (2 x 1017cm-3), p channel (1 x 1017 cm-3) , n+ contacts (2 x 1020 cm-3).

As with the topography and SCM images, the matching line profiles created after scanning can also provide a better understanding about the device’s design. In this experiment, the line profile for the topography data, indicated in red on Figure 2, was initially considered.

When compared to the SCM image with the labeled device features, each NPN transistor device is separated from the next by boundaries that are almost 1 µm in depth with high levels of positive dopant concentration. A slightly raised area of 0.1 µm borders the edges of each boundary.

If this topography data is overlaid onto the SCM image, the edges of each boundary are shown to have lower dopant concentration (darker color) than the n+ contacts that make up the NPN transistors.

This aspect is further reinforced by the line profile of the SCM data, indicated as green line in Figure 2, where the regions directly before and after the boundaries are determined at slightly more negative µV levels (-30 µV) compared to the rest of the negatively doped portions (-10 µV) of the device displayed in the SCM image.

Further observations can be made in the central part of the target area, where p-channels of an increased height around 0.1 µm can be identified perpendicular to the device’s p-epi region. A relatively lower concentration of positive dopant (approaching 80 - 90 µV) is present in these central p-channels, where they can be viewed clearly in the image as a whole as well as along the green line in the SCM image.

Although SCM offers exceptional electrical property and topography data with high spatial resolution, this method is enabled by acquiring supplementary hardware from various microscopy vendors. SCM must also be carried out using contact mode AFM, which leads to the consumption of probes at an accelerated pace compared to non-contact mode AFM.

When there are limited fiscal considerations or hardware availability, electrical characterization of semiconductor devices can still be carried out at a reduced yet viable manner using the surface potential measurement technique - SKPM. Although it is not as effectively detailed, SKPM can still provide data and images that are similar to that acquired with SCM.

Both methods can characterize the device structure and expose the concentrations of dopants in different regions across the target area. Areas with positive dopant concentrations are presented as brighter areas, while those with negative dopant concentrations are shown to be darker.

The main differences between these two methods are that of dopant detection sensitivity and lateral resolution. Comparison between the SKPM image and the SCM image shows that the device’s p-channels are much wider when seen in SKPM.

One possible explanation of this difference is that SCM is able to make a direct contact with the surface of the sample to detect capacitance responses, while SKPM is designed to see potential over a whole sample surface. Another explanation is that SKPM is likely to be affected by charges in moisture adhered to the sample as well as in the ambient air around the tip, both of which are potential sources of alterations in charge distribution.

Conversely, SCM tip makes direct contact with the sample surface by penetrating through any moisture layer, producing a point of direct contact, which is less likely to be influenced by parasitic charges from the scanning environment. Figure 3 shows the topography (left) and SKPM (right) data acquired in SKPM mode.

Topography (left) and SKPM (right) data acquired in SKPM mode. p-epi (2x1016 cm-3), n well (2x1017 cm-3), p-channel (1x1017 cm-3), n+ contacts (2x1020 cm-3).

Figure 3. Topography (left) and SKPM (right) data acquired in SKPM mode. p-epi (2x1016 cm-3), n well (2x1017 cm-3), p-channel (1x1017 cm-3), n+ contacts (2x1020 cm-3).


This article has shown the characterization of the electrical and topography properties of an SRAM sample using SKPM and SCM with a Park NX20 AFM system. The data obtained in this analysis shows that both methods can provide quantitative and qualitative data for electrical characterization of semiconductor devices.

The results show that when compared to SKPM, SCM offers higher contrast mapping and greater lateral resolution of electrical properties, including the type and level of dopant concentration. However, SKPM continues to be an effective source of data that can be leveraged to draw similar conclusions regarding a sample being analyzed as SCM.

On the whole, the techniques described in this study will effectively provide key electrical parameters data to both researchers and device engineers to monitor semiconductor device processes and better assess the device reliability at nanoscale level.

References and Further Reading

  1. M. Deen, et al., Electrical Characterization of Semiconductor Materials and Devices. Springer Handbook of Electronic and Photonic Materials, pp 409-438
  2. D. Schroder, Semiconductor Material and Device Characterization. 3rd Edition, Wiley Interscience, Chemical and Physical Characterization, pp 627-659
  3. SCMSAMPLE. (n.d.). Retrieved June 20, 2016, from
  4. Park NX20 Atomic Force Microscope. (n.d.). Retrieved June 13, 2016, from
  5. Park SCM Technique:
  6. Park AFM Modes and Techniques. (n.d.). Retrieved June 13, 2016, from
  7. W. Melitz, et al., Kelvin probe force microscopy and its application, Surface Science Reports 66 (2011) 1–27, pp 2-¬4


This information has been sourced, reviewed and adapted from materials provided by Park Systems Inc.

For more information on this source, please visit Park Systems Inc.


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