Status and review of two-dimensional carrier and dopant profiling ...

Status and review of two-dimensional carrier and dopant profiling using scanning probe microscopy P. De Wolf,a) R. Stephenson, T. Trenkler, T. Clarysse, and T. Hantschel IMEC, Kapeldreef 75, B-3001 Leuven, Belgium

W. Vandervorst IMEC, Kapeldreef 75, B-3001 Leuven, Belgium and KU Leuven, INSYS, Kard. Mercierlaan 92, B-3001 Leuven, Belgium

共Received 28 March 1999; accepted 21 September 1999兲 An overview of the existing two-dimensional carrier profiling tools using scanning probe microscopy includes several scanning tunneling microscopy modes, scanning capacitance microscopy, Kelvin probe microscopy, scanning spreading resistance microscopy, and dopant selective etching. The techniques are discussed and compared in terms of the sensitivity or concentration range which can be covered, the quantification possibility, and the final resolution, which is influenced by the intrinsic imaging resolution as well as by the response of the investigated property to concentration gradients and the sampling volume. From this comparison it is clear that, at present, none of the techniques fulfills all the requirements formulated by the 1997 Semiconductor Industry Association roadmap for semiconductors 关National Technology Roadmap for Semiconductors 共Semiconductor Industry Association, San Jose, CA, 1997兲兴. Most methods are limited to pn-junction delineation or provide a semiquantitative image of the differently doped regions. However, recent comparisons have shown that the techniques can provide useful information, which is not accessible with any other method. © 2000 American Vacuum Society. 关S0734-211X共00兲01201-4兴 I. INTRODUCTION The 1997 U.S. Roadmap for Semiconductors from the Semiconductor Industry Association 共SIA兲 defined the needs for nanometer-scale measurement of carrier concentration profiles for the next decade.1 These needs are summarized in Table I for a 0.25, 0.18, and 0.13 ␮m technology. Clearly, there is a demand for sub-10-nm resolution, combined with sufficient sensitivity 共down to the 1e15 atoms/cm3 level兲 and high-quantification accuracy over a dynamic range of 1e15– 1e20 atoms/cm3. The need for such an extreme spatial resolution as well as the applicability towards standard devices has spurred the development of numerous twodimensional 共2D兲 carrier profiling tools. Until today, more than 20 different methods have been developed for this purpose. These techniques can roughly be divided into four categories: 共i兲 2D techniques which are based on a widely used one-dimensional 共1D兲 technique such as secondary ion mass spectrometry 共SIMS兲 共Ref. 2兲 关imaging SIMS,3 2D SIMS,4,5 tomography SIMS,6 and lateral SIMS 共Ref. 7兲兴 or spreading resistance profiling 共SRP兲.8 共ii兲 Electron microscopy-based techniques including field-effect scanning electron microscopy 共FE-SEM兲 共Refs. 9 and 10兲 and electron holography.11 共iii兲 Inverse modeling techniques.12 共iv兲 Scanning probe microscopy 共SPM兲 -based techniques. This article is limited to SPM-based techniques. All SPMs are based on the ability to position various types of probes in very close proximity with extremely high precision to the sample under investigation. These probes can detect electrical current, atomic and molecular forces, electrostatic forces, or other types of interaca兲

Present address: Digital Instruments, 112 Robin Hill Road, Santa Barbara, CA 93117; electronic mail: [email protected]

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tions with the sample. By scanning the probe laterally over the sample surface and performing measurements at different locations, detailed maps of surface topography, electronic properties, magnetic or electrostatic forces, optical characteristics, thermal properties, or other properties can be obtained. The spatial resolution which can be obtained is only limited by the sharpness of the probe tip, the accuracy with which the probe can be positioned, the condition of the surface under study, and the nature of the force being detected. The resolution can vary from a few angstroms to tens or hundreds of nanometers. This extremely high spatial resolution makes SPM the ideal candidate for a general applicable 2D carrier profiling tool. SPM-based 2D dopant profiling methods include various scanning tunneling microscopy techniques 共STM兲, dopant selective etching, scanning capacitance microscopy 共SCM兲, Kelvin probe force microscopy 共KPM兲, scanning spreading resistance microscopy 共SSRM兲, and scanning surface harmonic microscopy 共SSHM兲. In general, all SPM-based 2D profiling techniques are being applied on the cross section of the semiconductor structure under investigation. Earlier reviews of this topic have been given by Subrahmanyan in 1992,13 Vandervorst et al.14 and Dagata and Kopanski in 1995,15 Yu in 1996,16 and Vandervorst and co-workers in 1997 共Ref. 17兲 and 1998.18 The basic characteristics of the methods described in this article are summarized in Table II. Table II displays the type of probe used and the measured physical quantity. II. PRINCIPLES OF THE DIFFERENT TECHNIQUES A. Scanning tunneling microscopy „STM…

The scanning tunneling microscope is a very surfacesensitive SPM technique which requires, however, a conduc-

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TABLE I. Most important requirements for 2D carrier profiling as given in the SIA Roadmap for Semiconductors 共Ref. 1兲. Design rule

0.25 ␮m

0.18 ␮m

0.13 ␮m

Accuracy of carrier concentration

5%

5%

4%

Measurement repeatability

5%

5%

4%

Spatial resolution

5 nm

3 nm

2 nm

Carrier concentration range 共atoms/cm3兲

1e15– 1e20

1e15– 1e21

1e15– 1e21

tive surface, such that STM measurements on Si can normally not be operated in air due to the presence of the native oxide. It is clear that if the native oxide is removed through sample heating to relative high temperatures 共⬎1000 °C兲, the dopant distribution is disturbed. Therefore, one has to use in situ cleavage to generate a fresh sample cross section, which is, however, only possible along certain crystal directions.19 The structure of interest must thus be oriented exactly in that direction, limiting the flexibility of the technique. Additionally, it is not always possible to determine the carrier profile with respect to the mask edge and mask shape since the STM cannot image the oxide position 共due to the requirement of a conductive surface兲. Despite these basic limitations, crosssectional STM offers several methods for high-resolution dopant profiling.

1. Dopant atom counting

The most direct STM-based dopant profiling method is to simply count the number of dopant atoms appearing in 共or near兲 the surface atomic plane. Examples are given by Johnson and co-workers,20–23 who clearly resolved individual Be 共and Zn兲 dopant atoms in a cleaved 共110兲 surface of Ga. In this work, the negatively charged dopant atoms are attractive to holes and appear in the STM image as protrusions. From the size and shape of the features, dopants at the surface and one atomic layer below the surface could be distinguished from each other and from dopants further below the surface. So far, dopant atom counting has not been reported for Si substrates. In this context it is worth noting that the capability of imaging individual dopant atoms is

TABLE II. Summary of the different scanning probe microscopy techniques which can be used for 2D carrier profiling of semiconductor devices. The ‘‘mode’’ reflects the scanning mode which is being used to control the movement of the probe (NC⫽noncontact; C⫽contact).

Technique

Mode

Scanning tunneling microscopy/ spectroscopy 共STM/STS兲

STM

Selective etching⫹atomic force microscopy

Probe

Measured quantity

Metallic needle

No. doping atoms I – V spectra

NC-AFM

Ultrasharp Si

Topography after chemical etch

Scanning capacitance microscopy/ spectroscopy 共SCM/STS兲

C-AFM

Metal-coated Si or metallic

Depletion capacitance C – V spectra

Scanning spreading resistance microscopy 共SSRM兲

C-AFM

Diamondcoated Si or diamond

Electrical resistance I – V spectra

Kelvin probe force microscopy 共KPM兲

NC-AFM

Metal-coated Si or metallic

Electrostatic potential 共electric field兲

STM

Metallic needle with microwave cavity

Depletion capacitance

Scanning surface harmonic microscopy 共SSHM兲

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associated with the special properties of cleaved GaAs共110兲 surfaces where the intrinsic surface states are outside the bulk band gap.23 Although this method provides the ultimate resolution, its sensitivity is rather poor. Since only the atoms in the top two atomic layers are revealed, a high dopant concentration is required to be able to determine the dopant concentration adequately. 2. Scanning tunneling spectroscopy (STS) and current imaging tunneling spectroscopy (CITS)

The work using STM as a dopant profiler has primarily been focused on pn-junction delineation by detecting differences in tunneling current characteristics for n- and p-type material. Feenstra and co-workers carried out the first detailed imaging and spectroscopic studies of GaAs pn junctions, observing electronically induced topography.24–26 Current–voltage spectroscopy allowed the n-type, p-type, and depleted regions to be identified unambiguously. The STM current dependence on dopant type and concentration within semiconductors is due to tip-induced bandbending at the surface.27 Kordic and co-workers performed the first cross-sectional STM studies of Si pn junctions exposed by cleaving in air and UHV.28–30 The location of the junctions could be resolved to within 30 nm using a potentiometric technique in UHV 关scanning tunneling potentiometry 共STP兲兴: A forward or reverse bias was applied across the pn junction, and differences in tunneling current measured in p-type, depleted, and n-type regions for various bias voltages applied to the pn junctions then revealed the electronic structure of the biased junctions. Yu and co-workers31,32 used current imaging tunneling spectroscopy 共CITS兲. In this technique a constant-current topographic scan with the current stabilized at a fixed value I 0 for a specific voltage V 0 is performed over the sample surface and, at each point, a current–voltage spectrum is measured. Variations in electronic structure across the sample surface produce corresponding variations in the current– voltage spectra; these spatial variations can be revealed by plotting the current measured at specific bias voltages other than V 0 —so-called current images. CITS under UHV conditions on cleaved, hydrogen-passivated cross-sectioned Si metal–oxide–semiconductor 共MOS兲 structures made it possible to image the source and drain junction profiles with a spatial resolution on the order of 10 nm.32 Because the current–voltage spectra differed significantly for the p-type, n-type, and depleted regions, current images generated from the spatially resolved tunneling spectra were able to reveal the profiles of the pn junctions. A problem to extend this work further to quantitative dopant profile information, is the dependence of the tunneling current on the Fermi level and bandbending rather than on the carrier concentration directly. In addition, the surface disorder problems form a significant limitation for the STM approach. In conclusion, the different STM-based cross-sectional carrier 共or doping兲 profiling methods have low performance on Si. This difficulty can be ascribed to the difficult crossJVST B - Microelectronics and Nanometer Structures

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section preparation, combined with the fact that the STM is a very surface-sensitive technique. First, Si 共001兲 wafers are more difficult to cleave than III–V wafers; and second, the as-cleaved 共110兲 cross-sectional surface is atomically disordered with its electronic structure dominated by danglingbond states. Despite these complications, 2D junction delineation and qualitative 2D nanometer-scale carrier profiling of cross-sectioned Si-based structures have been achieved by several research groups. The applicability of STM 关or scanning tunneling spectroscopy 共STS兲兴 as a quantitative carrier profiling tool is complicated and, therefore, limited. B. Dopant selective etching or staining

The method of chemical staining or etching of doped Si layers has been known since the early days of semiconductor processing. Staining techniques use selective deposition of a metal such as Cu, Au, Ag, or Pt on one side of the junction by an electrochemical displacement reaction from a metalion-based solution. Etching techniques use mixtures of HF and an oxidizing agent to preferentially etch regions with a high carrier concentration. The impurity-sensitive etching solutions typically consist of a mixture of HF, HNO3, and either H2O or CH3COOH. The sample topography after the staining or etching step is a measure for the 2D carrier profile and can be imaged using transmission electron microscopy 共TEM兲,32–34 SEM,35 STM,36,37 or atomic force microscopy 共AFM兲.38 In a final step, the measured topography profiles have to be converted to electrical carrier distributions. Among the advantages of using AFM compared with STM in performing topographic measurements on selectively etched cross sections is that AFM makes it possible to measure the surrounding structures 共oxides, metals, etc.兲 since this is not possible with the STM, which requires a conducting sample surface. Also, AFM is less sensitive to the detailed electronic structure of the etched surface and to possible contamination of the sample or tip surfaces. Both the STM and AFM method can suffer from tip–sample convolution leading to an incorrect image of the etched region. The regions with a high carrier concentration gradient are particularly sensitive to this effect. Independently of the technique which is used to measure the sample topography, the accuracy of etching and staining techniques is always limited by the reproducibility of factors such as surface preparation, the concentration of the staining or etching solution, etching time, the volume and the agitation of the solution on the sample, temperature, and light illumination. The effects of these factors can be minimized by careful sample preparation and precise control of the etching factors. In this context, different approaches have been used by several groups. A promising method to obtain longer etching times and a better general control of the etching makes use of an electrochemical etching procedure with potentiostatic control.39 An important drawback of the etching techniques until now is that analysis suffers from a poor understanding of the etching process and the correlation between carrier concentration and the observed topography. Two approaches have

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been employed so far for this calibration. The first calibration method uses a 1D doping profile adjacent to the 2D area of interest. The 1D doping profile may be measured by SIMS or SRP or be numerically simulated. After etching, the 1D etched profile is characterized and related to the known 1D carrier 共or doping兲 distribution. A 2D doping map is obtained by assuming that the dependence of the etching rate on carrier concentration obtained for the 1D region is also correct for the complete 2D area. The second calibration method includes direct measurement of the etching rate as a function of carrier concentration using homogeneously doped bulk or epitaxially grown Si samples. Again, it is assumed that under similar etching conditions 共temperature, concentrations, light, time, etc.兲 the etching rate for a particular spot depends exclusively on the carrier concentration at this point. However, it has been found that the etching also depends on the carrier concentration gradient.40 In summary, the applicability of the selective etching method to 2D carrier profiling is limited because of 共i兲 poor understanding of the etching process, 共ii兲 poor control of the etching conditions, and 共iii兲 lack of a good general quantification procedure. Despite these limitations, the method remains valuable for fast qualitative analysis. C. Scanning capacitance microscopy „SCM…

In the scanning capacitance microscope, the sample 共or the metallic AFM tip兲 is covered with a thin dielectric layer, such that the tip–sample contact forms a metal–insulator– semiconductor 共MIS兲 capacitor, whose capacitance–voltage (C – V) behavior is determined by the local carrier concentration of the semiconductor sample. If no dielectric layer is used, the tip–sample contact forms a metal–semiconductor 共MS兲 structure and one has a so-called Schottky contact SCM.41,42 By monitoring the capacitance variations as the probe scans across the sample surface, one can measure a 2D carrier concentration profile. Since the total tip–sample capacitance is large compared to the capacitance variations due to different carrier concentrations, one usually measures the capacitance variations and not the absolute capacitance values. Note that no signal is measured if the probe is positioned over a dielectric or metallic region since these regions can not be depleted. Most SCMs are based on contact-mode AFM with a conducting tip, and an essentially independent capacitance measurement in parallel.43 The capacitance between the tip and sample is measured by using a highfrequency capacitance sensor, based on a 915 MHz oscillator driving a resonance circuit which is tuned in part by the external capacitance to be measured. The capacitance detection limit is as small as 1e-19 F in a 1 kHz bandwidth 共translating into a noise level of 3e-21 F/ 冑Hz). An extensive review of SCM for 2D dopant profiling is given by Williams.44 The SCM is usually operated in one of the following two modes. 1. Differential-capacitance (open-loop) mode

In the open-loop mode, an ac bias 共typically, 0.2–2 V, 10–100 kHz兲 is superimposed on a dc sample bias 共⫺2–2 J. Vac. Sci. Technol. B, Vol. 18, No. 1, JanÕFeb 2000

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V兲, while the tip is at dc ground. The ac bias can alternately deplete and accumulate the semiconductor surface region. The modulated surface capacitance changes ⌬C under the probe tip are registered using a lock-in technique, simultaneously with the topographical data, while the probe is scanned across the surface. When using large ac voltages 共several volts兲, this setup measures ⌬C across the entire C – V curve, and is almost independent on shifts in the flatband voltage caused by oxide or surface charges. When smaller ac bias voltages are used, the differential capacitance dC/dV is measured. 2. Closed-loop mode

In the closed-loop mode, the magnitude of the ac bias voltage applied to the sample is adjusted by a feedback loop to maintain a constant capacitance change as the tip is scanned across the sample at constant force.45,46 The feedback-controlled magnitude of the ac bias voltage is recorded. The main advantage of the closed-loop mode is the fact that the capacitance and, consequently, the depletion width is kept constant, whereas the depletion width might become very large 共⬎1 ␮m兲 for lowly doped regions in the differential capacitance mode, leading to a loss in spatial resolution. Since in SCM the measured capacitance signal is proportional to the tip interaction area, shrinkage of the tip size will improve the spatial resolution, but also reduce the sensitivity of the capacitance measurement. A dynamic range of 1e14– 1e20 has been demonstrated on a special calibration structure.47 The sensitivity is a function of the carrier concentration and can be increased by reducing the thickness of the oxide layer. The response of SCM is not necessarily monotonic with concentration but does depends on the applied experimental conditions as well.48 Several groups have published qualitative 1D and 2D 共Refs. 49–51兲 open- or closed-loop SCM images, which were compared with TCAD simulations and conventional 1D carrier profiling results. The resolution of these images is on the order of 10–20 nm.52 Much of the recent work related to SCM is focused on the theoretical interpretation and quantitative conversion of the measured signals into carrier profiles. In an ideal 共flat兲 MOS capacitor, the dopant concentration is easily extracted from the variation of capacitance with voltage. The situation is more complex for SCM since there are stray fields between the probe shaft and the sample surface, the sample has a nonconstant carrier concentration, and the quality of the surface is largely unknown 共surface charges, contaminants, oxide quality, etc.兲. Several models were presented to set up a quantification procedure. In the simplest model, the quantification of the SCM images is achieved using SIMS or SRP data in conjunction with contour mapping software. Hereby, it is assumed that the dependence of the SCM signal on carrier concentration obtained for the 1D line is also correct for the complete 2D area. In a quasi-1D analytical model, the tip is modeled as a metallic sphere placed in an insulating dielectric medium

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near a Si surface with a sphere–Si gap just equal to the experimental measured oxide thickness.49 The Si surface is divided into annular regions. The insulator capacitance between the sphere and each annular region, and the Si depletion capacitance for each annular region are calculated and summed to give the total tip–sample capacitance. This approximate analytical model provides a means to rapidly calculate the C – V relation as a function of tip radius, dielectric constant, gap distance, and carrier density. Note that a constant carrier density is assumed in these calculations, the effect of a carrier gradient 共in the lateral direction兲 is not yet included. In an alternative model the C – V relation is calculated using the solution of the three-dimensional 共3D兲 Poisson equations for various tip–sample bias voltages, tip–sample gap distances, carrier concentrations, and oxide thickness.49,53,54 The probe is modeled as a cone with a hemispherical tip end to include stray-field effects. The quality of the sample surface, although known to be an important parameter, was not included in the calculations. Algorithms based on interpolation within the results of this database have then been developed, to convert a measured SCM profile into a quantitative carrier profile. Kopanski and co-workers49,53 treat each measured capacitance point independently and thus ignore the effect of carrier gradients, whereas Yu, Griffin, and Plummer54 include the effect of the dopant gradient in their simulations. It needs to be pointed out that the behavior of the SCM signal 共in the open- or closed-loop mode兲 at pn junctions is not well understood and is not yet included in the calculations, although pronounced effects have been observed.49 Calculations and experiments have shown that the tip– sample bias 共ac and dc兲 has a pronounced effect on the presence, position, and extent of extra contour lines in the vicinity of the junction, complicating precise junction delineation and data quantification at pn junctions.55,56 Several groups have proposed and implemented promising approaches to overcome this problem. Timp et al. use heavily doped Si tips rather than metal-coated tips.57 In this case, not only the sample, but also the tip itself, is being depleted and accumulated. The resulting SCM images persist over a wide tip– sample bias range. The delineation of the highly doped regions 共such as the poly-Si gate兲 and the metal regions becomes now clearer and junction positions appear less influenced by the bias voltage used. However, now the exact concentration of the tip material enters as an extra parameter in the quantification 共in particular, in those cases where carrier concentration in the sample and tip are equivalent, interpretation becomes less transparent兲. Edwards et al. present another approach:58 scanning capacitance spectroscopy 共SCS兲. In SCS the C – V curve is measured for every position of the probe in the 2D profile. The shape of the C – V curve allows one to distinguish between n-type, p-type, and depletion regions and facilitates data quantification. Both approaches—Si tips, and SCS—result in easier data interpretation, in particular, at pn junctions. However, quantification of the data into carrier concentration values still requires 3D JVST B - Microelectronics and Nanometer Structures

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simulations in order to determine the exact impact of carrier concentration gradients and pn junctions on the observed SCM images. In conclusion, the SCM is a promising tool for quantitative 2D carrier profiling with nanometer resolution. The spatial resolution 共10–20 nm兲 and dynamic range (1e15– 1e20 atoms/cm3) are good. The major challenges in SCM include: surface preparation including the formation of a good dielectric oxide,59 and the quantification and calibration methodologies. At present, the technique is widely used in a qualitative manner and only limited by a lack of a generally applicable quantification routine. D. Scanning surface harmonic microscopy „SSHM…

The SSHM consists of a STM with a microwave cavity, in which a microwave signal is applied across the tip–sample tunneling gap.60 The nonlinear tip–sample MIS capacitance C results in higher-order harmonics in the tunneling current. The second- and third-harmonic signals are proportional to the first and second derivatives of C. The driving frequency is chosen such that the second- or third-harmonic frequency corresponds to the resonance frequency of the cavity 共typically, 2.7 GHz兲, making it detectable.61,62 The capacitance C is a measure for the local active carrier concentration in the semiconductor and the insulator quality in the same way as in the SCM technique. Bourgoin, Johnson, and Michel have applied the SSHM technique to delineate the qualitative carrier profile of Si pn junctions with 5 nm resolution.61 In general, the signal-to-noise ratio is lower compared to the SCM method and quantification of the data is faced with similar problems as the SCM technique. E. Kelvin probe force microscopy „KPM…

Kelvin probe force microscopy and the related scanning Maxwell-stress microscopy, are high-resolution and highly sensitive potential imaging methods.63 A conductive tip is scanned in the noncontact AFM mode while an ac voltage 共frequency f兲 is applied to it. This voltage results in an electrostatic field which causes an oscillation of the cantilever at the same frequency. This force disappears when the dc potential difference between tip and sample is zero. Thus, by observing the amplitude of the cantilever oscillation at frequency f by a lock-in technique, and nulling it by changing the dc bias voltage on the tip, the sample’s surface potential can be measured. The maximum sensitivity is obtained when f corresponds to one of the resonance frequencies of the cantilever. In order to separate the height-control signal and the voltage signal, the first cantilever resonance peak is usually employed for the tip height control while f is taken equal to the second resonance peak on a dual resonant probe.63 This mode was used to measure the 2D potential distribution inside Si device structures.64–66 The measured electrochemical potential difference between the probe tip and sample surface is dependent on the carrier concentration-related workfunction difference, and can thus be used as a measure for the local carrier concentration, although the sensitivity is limited. This mode of KPM has been applied successfully for qualitative 2D carrier profiling of Si structures.66,67 The tech-

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TABLE III. Intercomparison of two-dimensional doping 共D兲 and carrier 共C兲 profiling methods (NA⫽not available).

Ref.

Resol. 共nm兲

Range 共cm⫺3兲

SCM

共43–59兲

10

1e15– 1e20

SSHM

共60–62兲

5

NA

STM-atom counting

共20–23兲

Atomic

STM-STS/ CITS

共24–26兲 共31,32兲

STM-STP

D/ C

Quantifiable

C

Limited

Power

C

No

No quantification procedure

1e18– 1e20

Linear

D

Yes

Only on GaAs, not on Si

10

NA

Log.

C

Limited

Only junction delineation and type 共n or p兲 identification

共27–30兲

10

NA

Limited

C

Limited

Only junction delineation

KPM

共66,67兲

100

1e15– 1e20

Limited

C

Limited

Poor quantification procedure, strayfields limit the resolution

SSRM

共68–73兲

20

1e15– 1e20

Linear

C

Yes

Chemical etch ⫹AFM/STM

共37–39兲

10–20

1e17– 1e20

Limited

C

Limited

Imaging SIMS

共3兲

100

NA

共4,5兲

30–50

1e16– 1e21

Linear

2D-tomography SIMS

共6兲

50

NA

Lateral SIMS

共7兲

5–10

2D-SRP

共8兲

Method

Conc. resol. SPM techniques Power

1D-based techniques Linear D

Comments and problems Uncertainties at junctions, poor quantification procedure

Availability diamond probes Difficult to quantify, poor reproducibility

Yes

Sensitivity limited by target volume

D

Yes

Special structures required

Linear

D

Yes

Special structures required, complex sample preparation

Dose

Linear

D

Yes

Only the lateral dose distribution is measured

100

1e15– 1e21

Linear

C

Yes

Special structures required

共32–35兲

20

1e17– 1e21

EM techniques Limited

C

Limited

Only qualitative

共9,10兲

10–20

4e16– 1e21

Limited

Limited

Robust model for quantification is not available

E-holography

共11兲

1–10

1e17– 1e20

Limited

Inv. modeling with C – V

共12兲

NA

NA

2D-SIMS

Chemical etch ⫹SEM/TEM FE-SEM

Inverse modeling techniques C

nique is sensitive to changes in carrier concentration from 1e15 to 1e20 atoms/cm3 with a spatial resolution of about 100 nm. However, the sensitivity to small concentration changes and the application towards quantitative profiling are limited by surface charges on the sample and calibration of the KPM technique against absolute doping concentration standards remains to be demonstrated. F. Scanning spreading resistance microscopy „SSRM…

In SSRM the electrical resistance is measured between the conductive probe tip and a large current-collecting back contact while the probe is scanned in the contact mode across the cross section of the Si device. When the applied force exceeds a certain threshold force, the measured resistance is dominated by the spreading resistance.68 As for the convenJ. Vac. Sci. Technol. B, Vol. 18, No. 1, JanÕFeb 2000

C

Limited Yes

Resolution and accuracy are unknown, long calculation times

tional 共1D兲 spreading resistance profiling method, the spreading resistance depends inverse proportionally on the local carrier concentration underneath the probe–silicon contact. If one uses small bias voltages 共about 100 mV兲, the displacements as observed in SCM imaging are minimized. Contact potential differences between tip and surface can possibly alter this situation. Junction positions can be assigned to a single point as their positions show up as a peak in the resistance profile. On Si structures, high forces 共typically, a few ␮N兲 are required in order to penetrate the native oxide and to establish a stable electrical contact. As standard AFM probes deform at these high forces, one needs to use doped diamond or diamond-coated Si probes. If lower forces are being used, the measured resistance is no longer dominated by the spreading resistance but by the contact resistance of the tip–sample contact. In this case, qualitative car-

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rier profiling remains possible, although the sensitivity to small changes in the carrier concentration is lost.69 The quantification of the SSRM resistance data into carrier concentration values is possible using an n- and p-type calibration curve in combination with an algorithm which corrects for the effect of nearby layers with different carrier concentrations.70 This quantification method is simple and fast and does not require one to measure the 1D in-depth profile by SIMS or SRP. The SSRM method has been applied on various InP 共Ref. 71兲 and Si 共Refs. 68, 72, and 73兲 device structures. These measurements include fully quantitative 2D profiles of both nMOSFETs and pMOSFETs 共metal–oxide–semiconductor field-effect transistors兲 and allow extraction of values for effective channel lengths and two-dimensional diffusion effects depending on gate lengths.73 Reasonable agreement is also obtained when compared to data extracted from device characteristics.74 The data indicate a dynamic range of 1e15– 1e20 atoms/cm3, a spatial resolution of about 25 nm, and also show that SSRM can be applied on arbitrary device structures. At present, the SSRM method is mainly limited by the availability of conductive diamond or diamond-coated probes.71 III. INTERCOMPARISON Various features of the methods described above are summarized in Table III. The SPM-based 2D carrier profiling are compared with alternative methods based on 1D techniques, electron microscopy, or inverse modeling. The most important features are spatial resolution 共in nanometers兲, dynamic range 共in atoms/cm3兲, sensitivity 共defined here as the ratio of the change in the instrument response to a corresponding change in carrier concentration兲, quantification ability, and applicability to real devices 共without needing special test structures兲. The listed resolution and dynamic range correspond to the best specifications found in the literature. Note that different definitions for spatial resolution and sensitivity 共or dynamic range兲 are used by different groups, complicating this intercomparison. If no value is found in the literature, the specification is labeled as ‘‘not available’’ 共NA兲. The ability to transform the measured raw data values into a fully quantitative 2D doping or carrier profile is labeled as ‘‘yes,’’ ‘‘no,’’ or ‘‘limited.’’ The concentration resolution is labeled as ‘‘linear’’ if the instrument response is proportional to the carrier concentration, ‘‘logarithmic’’ if the instrument response is proportional to the logarithm of the carrier concentration, and ‘‘power’’ if there is a power-law relation between the carrier concentration and the instrument response, or ‘‘limited.’’ Based on this intercomparison, it is clear that none of the available techniques fulfills all the requirements formulated in Table I and can at the same time be applied on any arbitrary semiconductor structure. Most techniques are limited to pn-junction delineation or provide a qualitative image of the differently doped regions. Whereas all SPM-based methods can be applied on arbitrary devices, all 1D-based techniques require a special test structure, making them less flexible as compared to the SPM-based methods. JVST B - Microelectronics and Nanometer Structures

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The authors believe that although the SSRM and the SCM techniques are still in a development or optimization stage, they are the leading candidates to become a general applicable 2D carrier profiling tool. Both techniques have a resolution close to the values asked for, can be applied on arbitrary structures, and have the required dynamic range. Quantification accuracy and reproducibility are still issues which need to be determined with much more detail. IV. CONCLUSIONS At present there are numerous SPM-based methods for 2D carrier profiling of Si 共and other兲 device structures. These include several scanning tunneling microscopy modes, scanning capacitance microscopy, Kelvin probe microscopy, scanning spreading resistance microscopy, and dopant selective etching. All of these methods can be directly applied on the cross section of an arbitrary device and do not require special test structures. The methods differ in the range of carrier concentrations which can be mapped, the spatial resolution, and the quantification possibility. The features of the different methods can be summarized as follows: 共i兲 The different STM-based methods have a rather low performance on Si due to the difficult cross-section preparation, combined with the fact that the STM is a very surfacesensitive technique. STM-based carrier profiling is, therefore, limited to 2D junction delineation and qualitative 2D imaging. At present, the applicability of STM as a quantitative carrier profiling tool is not possible. 共ii兲 The applicability of the selective etching method 共followed by AFM imaging兲 is limited because of a poor understanding of the etching process, a poor control of the etching conditions, and a lack of a general quantification procedure. However, the etching method is a very valuable tool for fast qualitative analysis of the 2D carrier profile. 共iii兲 Both the SCM and SSRM are promising tools for quantitative 2D carrier profiling with nanometer resolution. The spatial resolution 共10–20 nm兲 and dynamic range (1e15– 1e20 atoms/cm3) are good. Some further research and development is required such that these methods fulfill the requirements set by the 1997 SIA roadmap for semiconductors. This future work includes the development and fabrication of reliable probes for SSRM, and the development of routines to interprete and convert the SCM images into quantitative carrier concentration values. National Technology Roadmap for Semiconductors 共Semiconductor Industry Association, San Jose, CA, 1997兲. 2 M. G. Dowsett, Proceedings of the SIMS XI Conference, edited by G. Gillen, R. Larea, J. Bennet, and F. Stevie 共Wiley, Chichester, 1997兲, p. 157. 3 S. R. Bryan, W. S. Woodward, R. W. Linton, and D. P. Griffis, J. Vac. Sci. Technol. A 3, 2102 共1985兲. 4 M. G. Dowsett and G. A. Cooke, J. Vac. Sci. Technol. B 10, 353 共1992兲. 5 V. A. Ukraintsev, P. J. Chen, J. T. Gray, C. F. Machala, L. K. Magel, and M.-C. Chang, J. Vac. Sci. Technol. B, these proceedings. 6 S. H. Goodwin-Johansson, M. Ray, Y. Kim, and H. Z. Massoud, J. Vac. Sci. Technol. B 10, 369 共1992兲. 7 R. Van Criegern, F. Jahnel, R. Lange-Gieseler, P. Pearson, G. Hobler, and A. Simionescu, J. Vac. Sci. Technol. B 16, 386 共1998兲. 8 V. Privitera, W. Vandervorst, and T. Clarysse, J. Electrochem. Soc. 140, 262 共1993兲. 1

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De Wolf et al.: Status and review of 2D carrier profiling

9

R. Turan, D. D. Perovic, and D. C. Houghton, Appl. Phys. Lett. 69, 1593 共1996兲. 10 D. Venables, H. Jain, and D. C. Collins, J. Vac. Sci. Technol. B 16, 362 共1998兲. 11 W. D. Rau, F. H. Baumann, H. H. Vuong, B. Heinemann, W. Hoppner, C. S. Rafferty, H. Rucker, P. Schwander, and A. Ourmazd, Tech. Dig. Int. Electron Devices Meet., 713 共1998兲. 12 N. Khalil, J. Faricelli, C. L. Huang, and S. Selberherr, J. Vac. Sci. Technol. B 14, 224 共1996兲. 13 R. Subrahmanyan, J. Vac. Sci. Technol. B 10, 358 共1992兲. 14 W. Vandervorst, T. Clarysse, P. De Wolf, L. Hellemans, J. Snauwaert, V. Privitera, and V. Raineri, Nucl. Instrum. Methods Phys. Res. B 96, 123 共1995兲. 15 J. A. Dagata and J. J. Kopanski, Solid State Technol. 38, 91 共1995兲. 16 E. T. Yu, Mater. Sci. Eng. 17, 147 共1996兲. 17 W. Vandervorst, T. Clarysse, P. De Wolf, T. Trenkler, T. Hantschel, and R. Stephenson, Future Fab. Int. 4, 287 共1997兲. 18 W. Vandervorst, T. Clarysse, P. De Wolf, T. Trenkler, T. Hantschel, R. Stephenson, and T. Janssens, in Proceedings of the International Workshop on Semiconductor Characterization: Present Status and Future Needs, edited by D. Seiler 共AIP, New York, 1998兲. 19 Y.-C. Kim, M. J. Nowakowaski, and D. N. Seidman, Rev. Sci. Instrum. 67, 1922 共1996兲. 20 M. B. Johnson, O. Albrektsen, R. M. Feenstra, and H. W. M. Salemink, Appl. Phys. Lett. 63, 2923 共1993兲. 21 M. B. Johnson, H. P. Meier, and H. W. M. Salemink, Appl. Phys. Lett. 63, 3636 共1993兲. 22 H. W. M. Salemink, M. B. Johnson, O. Albrektsen, and P. Koenraad, Solid-State Electron. 37, 1053 共1994兲. 23 K.-J. Chao, A. R. Smith, A. J. McDonald, D.-L. Kwong, B. G. Streetman, and C.-K. Shih, J. Vac. Sci. Technol. B 16, 453 共1998兲. 24 R. M. Feenstra, E. T. Yu, M. Woodall, P. D. Kirchner, C. L. Lin, and G. D. Pettit, Appl. Phys. Lett. 61, 795 共1992兲. 25 S. Gwo, A. R. Smith, K.-J. Chao, C. K. Shih, K. Sadra, and B. G. Streetman, J. Vac. Sci. Technol. A 12, 2005 共1994兲. 26 R. M. Silver, J. A. Dagata, and W. Tseng, J. Vac. Sci. Technol. A 13, 1705 共1995兲. 27 R. M. Feenstra and J. A. Stroscio, J. Vac. Sci. Technol. B 5, 923 共1987兲. 28 S. Kordic, E. J. Van Loenen, D. Dijkkamp, A. J. Hoeven, and H. K. Moraal, J. Vac. Sci. Technol. A 8, 549 共1990兲. 29 S. Kordic, E. J. Van Loenen, and A. J. Walker, IEEE Electron Device Lett. 12, 422 共1991兲. 30 M. B. Johnson and J.-M. Halbout, J. Vac. Sci. Technol. B 10, 508 共1992兲. 31 E. T. Yu, M. B. Johnson, and J.-M. Halbout, Appl. Phys. Lett. 61, 201 共1992兲. 32 E. T. Yu, K. Barmak, P. Ronsheim, M. B. Johnson, P. McFarland, and J.-M. Halbout, J. Appl. Phys. 79, 2115 共1996兲. 33 R. Alvis, B. Mantiply, and M. Young, J. Vac. Sci. Technol. B 14, 452 共1996兲. 34 S. S. Neogi, D. Venables, Z. Ma, and D. M. Maher, J. Vac. Sci. Technol. B 16, 471 共1998兲. 35 L. Gong, S. Petersen, L. Frey, and H. Ryssel, Nucl. Instrum. Methods Phys. Res. B 96, 133 共1995兲. 36 T. Takigami and M. Tanimoto, Appl. Phys. Lett. 58, 2288 共1991兲. 37 M. Tanimoto and T. Takigami, Ultramicroscopy 42–44, 1381 共1992兲. 38 G. Neubauer, M. Lawrence, A. Dass, and T. J. Johnson, Mater. Res. Soc. Symp. Proc. 286, 283 共1992兲. 39 T. Trenkler, W. Vandervorst, and L. Hellemans, J. Vac. Sci. Technol. B 16, 349 共1998兲. 40 V. A. Ukraintsev, R. McGlothin, M. A. Gribelyuk, and H. Edwards, J. Vac. Sci. Technol. B 16, 476 共1998兲. 41 M. Morooka and S. Fukasako, Jpn. J. Appl. Phys., Part 1 35, 3686 共1996兲. 42 Y. Li, J. N. Nxumalo, and D. J. Thomson, in Proceedings of the 4th International Workshop on Ultra Shallow Junctions, Raleigh, NC, edited by M. Current, M. Kump, and G. McGuire 共1997兲, p. 63.1. 43 Y. Huang and C. C. Williams, J. Vac. Sci. Technol. B 12, 369 共1994兲. 44 C. C. Williams, Annu. Rev. Mater. Sci. 29, 471 共1999兲.

J. Vac. Sci. Technol. B, Vol. 18, No. 1, JanÕFeb 2000

368 45

Y. Huang, C. C. Williams, and J. Slinkman, Appl. Phys. Lett. 66, 344 共1995兲. 46 Y. Huang, C. C. Williams, and M. A. Wendman, J. Vac. Sci. Technol. A 14, 1168 共1996兲. 47 T. Clarysse, M. Caymax, P. De Wolf, T. Trenkler, W. Vandervorst, J. S. McMurray, J. Kim, C. C. Williams, J. G. Clark, and G. Neubauer, J. Vac. Sci. Technol. B 16, 394 共1998兲. 48 R. Stephenson, A. Verhulst, P. De Wolf, M. Caymax, and W. Vandervorst, Appl. Phys. Lett. 73, 2597 共1998兲. 49 J. J. Kopanski, J. F. Marchiando, D. W. Berning, R. Alvis, and H. E. Smith, J. Vac. Sci. Technol. B 16, 339 共1998兲. 50 J. S. McMurray, J. Kim, C. C. Williams, and J. Slinkman, J. Vac. Sci. Technol. B 16, 344 共1998兲. 51 W. Timp, M. L. O’Malley, R. N. Kleiman, and J. P. Garno, Tech. Dig. Int. Electron Devices Meet., 555 共1998兲. 52 Y. Huang, C. C. Williams, and H. Smith, J. Vac. Sci. Technol. B 14, 433 共1996兲. 53 J. F. Marchiando, J. J. Kopanski, and J. R. Lowney, J. Vac. Sci. Technol. B 16, 463 共1998兲. 54 G. Yu, P. Griffin, and J. Plummer, Tech. Dig. Int. Electron Devices Meet., 717 共1998兲. 55 R. N. Kleiman, M. L. O’Malley, F. H. Baumann, J. P. Garno, and G. L. Timp, Tech. Dig. Int. Electron Devices Meet., 671 共1997兲. 56 C. J. Kang, C. K. Kim, J. D. Lera, Y. Kuk, K. M. Mang, J. G. Lee, K. S. Suh, and C. C. Williams, Appl. Phys. Lett. 71, 1546 共1997兲. 57 W. Timp, M. L. O’Malley, R. N. Kleiman, and J. P. Garno, Tech. Dig. Int. Electron Devices Meet., 555 共1998兲. 58 H. Edwards, R. Mahaffy, C. K. Shih, R. McGlothlin, R. San Martin, M. Gribelyuk, R. S. List, and V. A. Ukraintsev, Appl. Phys. Lett. 72, 698 共1998兲. 59 V. A. Ukraintsev, F. R. Potts, R. M. Wallace, L. K. Magel, H. Edwards, and M.-C. Chang, Proceedings of the International Conference on Characteristics and Metrology for ULSI Technology 共1998兲. 60 B. Michel, W. Mitzutani, R. Schierle, A. Jarosh, W. Knop, H. Benedickter, W. Bachtold, and H. Rohrer, Rev. Sci. Instrum. 63, 4080 共1992兲. 61 J.-P. Bourgoin, M. B. Johnson, and B. Michel, Appl. Phys. Lett. 65, 2045 共1994兲. 62 F. Bordoni, L. Yinghua, B. Spataro, F. Feliciangeli, F. Vasarelli, G. Cardarilli, B. Antonini, and R. Scrimaglio, Meas. Sci. Technol. 6, 1208 共1995兲. 63 M. Nonnenmacher, M. P. O’Boyle, and H. K. Wickramasinghe, Appl. Phys. Lett. 58, 2921 共1991兲. 64 A. Kikukawa, S. Hosaka, and R. Imura, Appl. Phys. Lett. 66, 3510 共1995兲. 65 A. Kikukawa, S. Hosaka, and R. Imura, Rev. Sci. Instrum. 67, 1463 共1996兲. 66 M. Tanimoto and O. Vatel, J. Vac. Sci. Technol. B 14, 1547 共1996兲. 67 A. K. Henning, T. Hochwitz, J. Slinkman, J. Never, S. Hoffmann, P. Kaszuba, and C. Daghlian, J. Appl. Phys. 77, 1888 共1995兲. 68 P. De Wolf, T. Clarysse, W. Vandervorst, L. Hellemans, Ph. Niedermann, and W. Ha¨nni, J. Vac. Sci. Technol. B 16, 401 共1998兲. 69 J. N. Nxumalo, D. T. Shimizu, and D. J. Thomson, J. Vac. Sci. Technol. B 14, 386 共1996兲. 70 P. De Wolf, T. Clarysse, and W. Vandervorst, J. Vac. Sci. Technol. B 16, 320 共1998兲. 71 P. De Wolf, M. Geva, T. Hantschel, W. Vandervorst, and R. B. Bylsma, Appl. Phys. Lett. 73, 2155 共1998兲. 72 P. De Wolf, R. Stephenson, S. Biesemans, Ph. Jansen, G. Badenes, K. De Meyer, and W. Vandervorst, Tech. Dig. Int. Electron Devices Meet., 559 共1998兲. 73 P. De Wolf, W. Vandervorst, H. Smith, and N. Khalil, J. Vac. Sci. Technol. B, these proceedings. 74 T. Trenkler, T. Hantschel, R. Stephenson, P. De Wolf, W. Vandervorst, L. Hellemans, A. Malave´, D. Bu¨chel, E. Oesterschulze, W. Kulisch, P. Niedermann, T. Sulzbach, and O. Ohlsson, J. Vac. Sci. Technol. B, these proceedings.