Spreading Resistance Data Research Articles

SDVSRM - a new SSRM based technique featuring dynamically adjusted, scanner synchronized sample voltages for measurement of actively operated devices

Scanning spreading resistance microscopy (SSRM) with its high spatial resolution and high dynamic signal range is a powerful tool for two-dimensional characterization of semiconductor dopant areas. However, the application of the method is limited to devices in equilibrium condition, as the investigation of actively operated devices would imply potential differences within the device, whereas SSRM relies on a constant voltage difference between sample surface and probe tip. Furthermore, the standard preparation includes short circuiting of all device components, limiting applications to devices in equilibrium condition. In this work scanning dynamic voltage spreading resistance microscopy (SDVSRM), a new SSRM based two pass atomic force microscopy (AFM) technique is introduced, overcoming these limitations. Instead of short circuiting the samples during preparation, wire bond devices are used allowing for active control of the individual device components. SDVSRM consists of two passes. In the first pass the local sample surface voltage dependent on the dc biases applied to the components of the actively driven device is measured as in scanning voltage microscopy (SVM). The local spreading resistance is measured within the second pass, in which the afore obtained local surface voltage is used to dynamically adjust the terminal voltages of the device under test. This is done in a way that the local potential difference across the nano-electrical contact matches the software set SSRM measurement voltage, and at the same time, the internal voltage differences within the device under test are maintained. In this work the proof of the concept could be demonstrated by obtaining spreading resistance data of an actively driven photodiode test device. SDVSRM adds a higher level of flexibility in general to SSRM, as occurring differences in cross section surface voltage are taken into account. These differences are immanent for actively driven devices, but can also be present at standard, short circuited samples. Therefore, SDVSRM could improve the characterization under equilibrium conditions as well.

Electrical activation and electron spin resonance measurements of arsenic implanted in silicon

The electrical activation of arsenic (As) implanted in Si is investigated with electron spin resonance (ESR), spreading resistance (SR), and secondary ion mass spectroscopy (SIMS). The As ions were implanted with a dose of 1 × 1012 cm−2 and subsequently annealed at various temperatures in the range of 500–1100 °C. The ESR measurements at 10 K show that the density of the As donor electrons for all the annealing temperatures is less than 10% of the As atom concentration measured by SIMS. The SR data indicate that the density of conduction band electrons is several times larger than that of the As donor electrons. These results strongly suggest that most of the As donor electrons are ESR inactive at low temperatures.

Modeling of ultrashallow spreading resistance probe calibration curves

Accurate determination of resistivity and carrier density from spreading resistance (SR) data depends heavily on the quality of the SR probes. This quality can be assessed by the shape of the calibration curve, which primarily depends on the properties and behavior of the point contact diodes. In this article, we demonstrate that the SR calibration curve can be simulated using an accurate representation of the SR equivalent circuit. This simulation includes physical models for the point contact diodes, the traditional geometric spreading resistance, and all parasitic resistances. Modeling of the point contact diode is emphasized based on measurements and analysis of the full current/voltage relationships for bulk p-type material.

New method based on atomic force microscopy for in-depth characterization of damage in Si irradiated with 209 MeV Kr

Si was irradiated with 209 MeV Kr ions on an (010) oriented surface. Then atomic force microscopy (AFM) was used to measure the roughness on the adjacent (100) plane (the original wafer surface). The distance on this later plane is called “depth” as measured from the (010) (100) edge. Good agreement is found in projected range values between AFM, spreading resistance (SR) data, and Monte Carlo (TRIM) simulation. Four distinct damage zones are found: zone A, dominated by electronic stopping effects; zone B, electronically assisted elastic collisions; zone C, dominant nuclear stopping; and zone D, defects created by the channeled fraction of the beam.

Improved analysis of spreading resistance measurements

In this article, a system is described for the analysis of spreading resistance data which includes carrier spilling through the solution of Poisson’s equation. The Poisson equation solution requires boundary conditions for the charge density on the beveled surface, which was modeled by considering the presence of surface states with levels within the band gap. Considering surface states allows the deviation from ideality of both n- and p-type calibration curves to be accounted for consistently without empirical contact resistance or variable radius corrections. In addition, the effects of finite probe penetration and change in energy gap due to probe pressure were considered to account for the reduction in peak resistance near junctions observed experimentally as compared to theoretical calculations. The software (SERAPES) can be used both to calculate simulated resistance profiles from doping profiles for process model characterization, as well as to calculate doping profiles directly from spreading resistance measurements.

Profiling of silicide–silicon structures using a combination of the spreading resistance and point contact current–voltage methods

Silicides are increasingly being used as diffusion sources to form the ultra-shallow, low resistance source-drain junctions, which will be needed in the next generation of ultra-large-scale integration technology. The silicide thickness and impurity profile in the silicon must be determined accurately as they are critical parameters in determining the performance of the resulting devices. In order to analyze the spreading resistance data measured on silicide structures, the interface between the silicide and silicon must be precisely located. In this article, the use of point-contact current–voltage (PC I–V) measurements for accurately determining the thickness of ultrathin cobalt silicide–monocrystalline silicon layers is demonstrated. This method is based on the potential barrier, which exists at the probe/silicon interface, but which does not exist at the probe–silicide interface. By monitoring this potential barrier, PC I–V can locate the silicide–silicon interface with a resolution of 10 Å.

Electrical characterization of shallow arsenic profiles using SRP2

The accurate measurement of shallow (<0.2 μm) electrically active profiles is complicated by the effects of carrier diffusion which in some cases causes the carrier concentration profile calculated from spreading resistance (SR) data to be different from the impurity profile. This article describes analysis of SR data collected on shallow As profiles using the new analysis program srp2. srp2 is an analysis process which compares the measured SR data with SR data calculated from an assumed impurity profile. This assumed impurity profile is adjusted until the calculated SR profile matches the measured one. The srp2‐calculated electrical profiles agree well with independently simulated electrical profiles obtained using models which were calibrated to secondary ion mass spectrometry (i.e., nonelectrical profiles) and sheet resistance data. The distribution of the calculated SR data beyond the junction is found to be strongly dependent upon the assumed tail of the impurity distribution, and therefore provides a means of characterizing the electrically active low‐concentration tail (below 1×1016). The variation of the calculated spreading resistance with the assumed shape of the tail is illustrated and compared with measured SR data.

Profiling of ultra-shallow complementary metal–oxide semiconductor junctions using spreading resistance: A comparison to secondary ion mass spectrometry

Spreading resistance profiling (SRP) and secondary ion mass spectrometry (SIMS) were used to characterize ultra-shallow (&amp;lt;100 nm deep) doping profiles. For junctions below 100 nm, the sheet resistances determined from carrier concentrations calculated from spreading resistance data in the traditional manner were considerably greater than values measured by the variable probe spacing technique. A new model which includes the effect of a damaged layer on the beveled surface is presented which accounts for the discrepancy between the measured and calculated sheet resistances. A Poisson analysis (SRP2) of the measured SRP data show that the doping profile and on-bevel carrier concentration profile differ only slightly near the junction for the shallow, heavily doped layers considered in this study.

Spreading resistance analysis with carrier spilling correction

This paper presents results obtained in extracting dopant profiles from spreading resistance (SR) data, with carrier spilling effects taken into account. The inversion process involves a one-dimensional solution of Poisson’s equation, followed by the application of a multilayer analysis to calculate the spreading resistance for a planar structure whose surface is defined by the probe position on the beveled SR sample. The dopant profiles of n/n+ epitaxial and p-well structures were recovered using the method of regularization. A detailed description is provided of the procedure employed in applying the method of regularization.

Incremental sheet resistance and spreading resistance: A comparison

Spreading resistance measurements are widely used to obtain carrier depth profiles in shallow silicon diffused layers. The transformation of the raw spreading resistance data into concentration data relies on the calibration of the system against standards of known resistivity. This procedure implies that, for a given carrier concentration, the analyzed sample and the standards have the same carrier mobility. However, this hypothesis is not verified when other carrier scattering centers, in addition to those active in a perfect silicon single crystal (lattice and ionized impurities), are present in the sample. In this case spreading resistance cannot give the correct carrier concentration and an independent measurement of carrier mobility must be performed. In addition, uniform standards are not easily available at the very high doping levels used, for instance, for the source and drain diffusion of complementary metal–oxide semiconductor devices, or for the emitter diffusion in bipolar devices. In this paper we compare the results obtained with incremental sheet resistance and sheet Hall coefficient, secondary ion mass spectrometry, and spreading resistance measurements on samples implanted with BF2 at high fluence and annealed at low temperatures, and on high fluence arsenic implanted layers. Rapid thermal annealed samples, implanted with As, As and P, and BF2 have been also studied, due to the present interest in this low thermal budget method for dopant activation.

A Poisson solver for spreading resistance analysis

It has become evident in recent years that carrier concentration profiles measured on beveled surfaces with a spreading resistance probe might not accurately reflect the associated vertical dopant profiles. Carrier spilling, even in the absence of surface states, can move an on-bevel junction 1/2 micron or more from its metallurgical depth. This article describes a Poisson solver which we have developed for use in spreading resistance data reduction. It allows the calculation of dopant profiles from measured on-bevel profiles. Examples from a variety of structures are given.

Extraction of semiconductor dopant profiles from spreading resistance data: An inverse problem

The traditional method of solving, on a layer-by-layer basis, the inverse problem of extracting resistivity values from spreading resistance measurements is found to produce wildly oscillatory, physically unacceptable resistivity profiles in the case of p-type silicon structures, where a resistivity-dependent probe contact radius is used in conjunction with the probe calibration data. These oscillations are manifestations of the fact that the inverse problem has non-unique solutions; they occur because the problem is inherently ill-posed. The well-known Tikhonov regularisation technique, which converts the present set of highly non-linear integral equations to an equivalent variational problem, is applied to stabilise the solution. Tests are performed on a variety of simulated profiles, and they reveal the existence of an optimum value for the regularisation parameter that is to be used with a second difference expression for the stabiliser of the cost function. When applied to measured spreading resistance data, the technique is found to produce results of reconstruction that are stable and physically reasonable.

Recent Developments in the Interpretation of Spreading Resistance Profiles for VLSI‐Technology

The interpretation of spreading resistance depth profiles for submicron devices is seriously affected by the fact that the spreading resistance technique measures an electrical on‐bevel carrier profile which may be quite different from the underlying atomic dopant profile. A one‐dimensional Poisson model has been implemented for simulating the carrier spilling effects responsible for these differences. The model is able to explain anomalies such as the absence of a junction peak for certain types of abrupt junctions, the observed discrepancies between implanted and measured doses for low‐dose implants, and the substantial differences in junction depth found between identical implants in same and opposite type material. The model has further led to the construction of a new correction procedure for spreading resistance measurements which corrects spreading resistance data into a dopant profile taking into account all the effects of beveling, carrier spilling, and the correct mobility values.

An efficient smoothing algorithm for spreading resistance calculations

The need for a good smoothing algorithm before applying a more elaborate correction algorithm to spreading resistance data is illustrated. The important requirements for such a scheme are formulated. A new efficient smoothing scheme has been implemented and tested. It is shown that this scheme substantially improves the generated carrier concentration profiles and makes their interpretation easier.

Electrical properties of vacuum annealed Si surfaces

We have measured dopant distribution profiles by spreading resistance and secondary ion mass spectrometry (SIMS) as well as Schottky contact properties at Si surfaces cleaned by a high-temperature anneal in vacuum. After sufficiently long anneal a p-type surface layer forms. The p-type dopant has been identified by SIMS as boron. SIMS and spreading resistance data indicate that the chemically cleaned surface contains boron impurities in the 1012/cm2 range. Metal/silicon (Ag, Al, Ni) contact measurements reveal strong influences on the electrical characteristics due to electrically active p-type accumulation in the near-surface region only after extensive anneal (1150 °C for 5 min). In comparison with nonreacting contacts, silicide formation reduces the influence of the high-temperature anneal due to interface motion into the boron-enriched surface region.

Comparison of carrier profiles from spreading resistance analysis and from model calculations for abrupt doping structures

Very abrupt doping structures grown by Si molecular beam epitaxy are investigated by spreading resistance (SR) analysis. The corresponding SR profiles reveal strong carrier spilling effects. To calculate the ‘‘on bevel’’ carrier concentrations of these structures, a formalism is developed which is based on the Poisson–Boltzmann equation. Qualitative agreement between the model calculation and the SR data is established.

Silicon sheet bicrystal growth for the study of grain boundary effects in solar cells

Abstract A modification of the edge-supported pulling (ESP) technique is described for the growth of silicon bicrystals in sheet form. Two flat silicon seeds, 20–25 mm in width, are mounted side-by-side between parallel 0.5–1.5 mm diameter graphite filaments spaced 40–50 mm apart. The assembly is placed in a silicon melt where sheet growth is initiated at the seeds. A bicrystal grain boundary forms in the newly grown sheet where the two seeds are in contact, and this boundary is propagated as the assembly is pulled upward. The grain boundaries in these bicrystals are useful for the controlled study of grain boundary effects on photovoltaic devices. A series of [110] and [112] rotation boundaries have been grown from semiconductor-grade silicon. We present here the spreading resistance and solar cell data detailing the effects of these grain boundary defects on photovoltaic devices.

MOSFET performance enhancement by improved SOS material processes

The performance of NMOS/SOS devices designed for near micron geometries is shown to be enhanced markedly by pre-process SOS material improvements. A description of the double solid phase epitaxial regrowth technique, DSPE, is presented including the results of several materials evaluation, techniques: Rutherford backscattering and channeling spectrometry, X-ray twin content, sheet resistance, spreading resistance, ultraviolet reflectivity, and Hall data vs. temperature. Post-MOS process evaluation data of materials and device properties is also presented, which includes: gated Hall data, SIMS, sheet resistance, majority and minority carrier mobility, threshold voltage, subthreshold current slope, back channel leakage current, and electrical carrier density profiles. Significantly enhanced device performance is reported, such as ≥20% improvement in all mobilities, factor of 100 reduction in twin content, factor of 5 to 10 reduction in backchannel leakage, and 15 to 25% improvement in subthreshold current slope.

Electrical characterisation of ion-implanted silicon-on-sapphire

Electrical parameters of carrier transport in SOS films were investigated by measuring gate capacitance at frequencies ranging from 1kHz to 10MHz, conductance both in the linear region and in the saturation region and Hall effect as a function of gate bias voltage. The results show that the mobility decreases almost linearly with increasing distance from the Si/SiO2 interface. Similar characteristics were obtained for the carrier concentration profile. The magnitudes drop more than 200 percent from the Si/SiO2 interface to about 0.2μm deep in the Si film. This experimental result is very different from the data predicted by SUPREM. Spreading resistance profiles measured on the same n-type SOS film. after wafer processing show increasing resistivity with increasing distance from the Si surface. The doping profile calculated from spreading resistance data by using the mobility data obtained from the gated Hall effect measurements also indicates that the n-type carrier concentration decreases toward the Si/sapphire interface. The discrepancy between experimental data and the carrier concentration profile predicted by SUPREM can be explained by the existence of deep-level acceptor traps that are evident from Hall effect measurements made on a lightly boron-implanted SOS sample. The temperature dependence of the free carrier concentration shows an activation energy close to 0.31 eV. Mobility and carrier concentration measured by different techniques is discussed.

The Relation Between the Correction Factor and the Local Slope in Spreading Resistance

Dickey had proposed a technique, known as the local slope method, for the calculation of the correction factor which is used to obtain resistivity profiles from spreading resistance data. The technique is founded upon two asymptotic models for the conduction process involved in the spreading resistance measurement for the cases of (i) a conducting layer over an insulating substrate, and (ii) a high resistivity layer over a low resistivity or conducting substrate. The results of these two extreme cases are bridged by means of an assumed functional relation between the correction factor and the local slope of the spreading resistance data. This paper examines the two asymptotic models as well as the assumed functional relation between the correction factor and the local slope. It is shown that the asymptotic models adequately describe the behavior of the correction factor for a thin uniform layer over insulating or conducting boundaries. In addition, the single‐valued relation between the correction factor and the local slope, which is assumed by the local slope method, is shown not to be an adequate representation of the multiple‐valued relation between these two quantities found from multilayer data. For the cases considered, this distinction leads to an error in the resistivities as interpreted by the local slope method by as much as 60%. Nonetheless, the local slope results qualitatively follow the multilayer results thus making the technique a usable one for the calculation of approximate correction factors. A comparison of the two correction factor vs. local slope relations provides a basis for the behavior of the interpreted resistivities when they are compared with the input resistivities.