Articles you may be interested inUltralow energy boron implants in silicon characterization by nonoxidizing secondary ion mass spectrometry analysis and soft x-ray grazing incidence x-ray fluorescence techniques High precision measurements of arsenic implantation dose in silicon by secondary ion mass spectrometry AIP Conf.The need to measure depth profiles of ultralow energy ͑ULE͒ ion implants in silicon, required for р180 nm IC device technology, has placed unprecedented requirements of high depth resolution and depth accuracy for the technique of secondary ion mass spectrometry ͑SIMS͒. The classic SIMS approaches to depth profiling ion implants employed in у250 nm device technologies are not valid for characterizing ULE implants. One reason is that the SIMS artifacts, typically observed at р30 nm, now occur in the depth range of the ULE implant. Two approaches have been proposed to overcome this. They are ͑i͒ oblique incidence bombardment, at less than 60°to the surface normal, with oxygen flooding, and ͑ii͒ normal incidence bombardment without oxygen flooding. The principle of both these approaches is the same, and requires the analytical surface to be modified to promote consistent secondary ion yields. Studies show the need to reduce the bombarding angle to Ͻ60°when using oxygen flooding. Depth profiling with this analytical condition is 3ϫ faster than by normal incidence bombardment. When using normal incidence bombardment, a greater shift towards the surface is observed due to a differential sputtering rate in the very near-surface region. With either approach, the depth resolution is the same after this initial sputtering rate increase.Oblique incidence bombardment appears to be the best approach to characterize both ''as-implanted'' and annealed ULE ion implants under ONE instrumental condition.

Techniques and applications of secondary ion mass spectrometry and spreading resistance profiling to measure ultrashallow junction implants down to 0.5 keV B and BF 2 Ultrashallow profiles challenge the capabilities of all characterization techniques. In this article, three diagnostic techniques are tested, secondary ion mass spectrometry ͑SIMS͒, capacitancevoltage (C -V) profiling and spreading resistance analysis ͑SRA͒. SIMS is used to measure the impurity concentration profiles, C -V is used to measure carrier concentration profiles directly and SRA is used to measure resistivity profiles, from which carrier concentrations can be derived. Both SIMS and SRA are calibrated techniques that relate the measured parameter to concentration or resistivity via calibration standards. C -V derives the carrier concentration directly through a mathematical model and calculation. Some of the assumptions, procedures, and limitations of these three techniques for ultrashallow profiles are reviewed and discussed. For this article these diagnostic techniques were used to examine six wafers that had been plasma doped followed by a rapid thermal anneal and three wafers that had been beamline implemented followed by a soak anneal.

Depth profiling of ultrashallow B implants in silicon using a magnetic-sector secondary ion mass spectrometry instrument J.As implant energies get lower and lower, significant errors can be present in junction depth measurements in secondary ion mass spectrometry ͑SIMS͒ ultrashallow depth profiling. Primary beam ion mixing is one of the main sources of errors leading to overestimation of junction depths in SIMS measurements. In this article, we systematically study the correlations between the implant profile trailing edge, junction depth and primary ion beam energy for low energy boron and arsenic implants. Using a mathematical deconvolution model proposed by Yang and Odom ͓Mater. Res. Soc. Symp. Proc. 669, J4.16.1 ͑2001͔͒, we are able to estimate the error of the junction depth and consistently improve the accuracy of junction depth measurements using SIMS.

Scaling metal oxide semiconductor (MOS) technology to the sub-0.1 micrometer regime faces many challenges. Shrinking MOS transistor dimensions requires the junction depth of source/drain extensions (SDEs) to be scaled by the same factor to maintain transistor immunity to short channel effects. The performance requirements, on the other hand, limit the parasitic resistance that can be tolerated in SDEs. Sheet resistance of the SDE profiles, as well as the lateral abruptness of these profiles determine the parasitic resistance. 1-3 Consequently, shrinking transistors requires more abrupt profiles and lower sheet resistances while decreasing junction depths at the same time. 4 Ion implantation has been and is projected to be the dominant technology to introduce dopants in silicon. The scaling of shallow junctions has been performed by reducing the implant energy and increasing the dose to achieve a shallower, more abrupt profile with lower sheet resistance. Secondary-ion mass spectrometry (SIMS) has been the main characterization technique to profile the implants and to measure the junction depth and total dose. However, SIMS profiling of very shallow implants can be challenging because a major fraction of the profile can fall within the surface transient of SIMS. Moreover, shallow implants can be more abrupt than the resolution of SIMS. As a result, that abrupt profiles all appear to have the same slope, is characteristic of the SIMS conditions.Arsenic was implanted in bare <100> silicon wafers at an energy of 1 keV and a dose of 1 x 10 15 /cm 2 . Silicon wafers were cleaned with a dilute HF oxide removal as the final step. Implantation was performed immediately after the clean to minimize native oxide growth. We then used a PHI ADEPT-1010 quadropole SIMS machine to do the profiling. This instrument can provide a stable, low energy primary ion beam. The crater depths were measured with a Tencor P-10 stylus profilometer. Standard grown arsenic samples were used to measure the relative sensitivity factors (RSFs) to convert the secondary-ion count to concentration. These samples are bulk doped with a known concentration of arsenic. We repeated profiling the implanted and standard samples to measure the overall repeatability of the profiling, and to monitor the drift of the machine. Figure 1 shows the SIMS profiles of the 1 keV, 1 x 10 15 /cm 2 sample using different SIMS conditions. We used a Cs primary with energies of 2 keV and 750 eV, as shown in Fig. 1a. A significant por-* Electrochemical Society Active Member. z Secondary-ion mass spectrometry (SIMS) with an ultralow energy primary ion beam was used to profile ultrashallow arsenic implants in silicon. Such shallow profiles are necessary for the formation of shallow junctions in future generations of transistors. A 750 eV Cs primary provides the best resolution in both dosimetry and depth profiling. However, even under these optimal conditions SIMS has limited resolution. We used high resolution X-ray photoelectron spectroscopy and monolayer chemical oxidation an...

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CuInxGa(1-x)Se2 (CIGS) is one of the most promising thin film PV materials due to its high efficiency, variety of growth methods available, and compatibility with flexible substrates enabling roll-to-roll manufacturing. The goal for all PV is low cost per watt, the solar industry's key metric.CIGS offers similar manufacturing costs compared with other thin film PV but with the promise of higher efficiency. Significant effort has gone into reducing materials costs, manufacturing costs, and into improving efficiency. But what makes one cell efficient and the next cell less efficient when made using the same process? In this work we compare two CIGS structures, both grown using the same process. One was measured at 6% efficiency and the other was over 12% efficient. Why the difference? We used surface analytical techniques to examine the two cells. We compared layer structure, interfaces, composition, and contaminants looking for differences that might explain the efficiency difference. Can we determine with physical analysis why one solar cell is efficient, while another seemingly identical cell is less efficient? Some measurements showed no difference, some small differences, and some large differences. Identification of differences between high and low efficiency devices could help identify important process control variables. EXPERIMENTALWe examined two CIGS solar cell structures, both grown on steel substrates using the NREL 3 stage PVD process [1]. One cell demonstrated 6% conversion efficiency (low) while the other was over 12% efficient (high). High resolution TEM was used to examine grain structures, layer structures, thickness, uniformity, and interfacial structures. Crystal structure was investigated using XRD looking at phase identification and grain orientation. Composition measurements were done using STEM/EDS, and dynamic SIMS. Dynamic SIMS was also used to measure and compare Na content. XRF survey analysis was used to identify elemental contaminant differences between the samples. Both samples were also examined with TOF-SIMS survey analysis depth profiling looking for differences in trace elemental content. Identified trace elements were then profiled using dynamic SIMS for quantification and improved detection limits.Efficiency measurements were done on complete cells. Surface analytical measurements were done on incomplete CdS/CuInGaSe/Mo/steel cells.made in parallel with the complete cells. RESULTS AND OBSERVATIONS StructureA TEM cross-section of the CdS/CIGS/Mo/steel layer structure is shown in Figure 1. TEM provides a level of image contrast and high resolution that is not available from any other imaging method. Crystal structure and defects are readily observable. Figure 1 shows the low efficiency cell structure. CIGS layer grain size is over 1µm, showed good interface integrity, good layer uniformity and few obvious defects. All these characteristics have been defined as desirable [2]. Figure 2 shows the high efficiency cell structure with essentially the same CIGS layer.A closer view of th...

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Conversion efficiency for Cu(Inx,Ga1-x)Se2 is dependent on a number of factors including band-gap and defect structures. Material composition affects band gap and it affects the formation of defect structures. A fundamental understanding of the relationship between material composition, band gap and defect structures requires that the composition measurement be accurate. Accuracy is required for really explaining how and why the cells function. Why certain defect levels form as a function of concentration, and how the influence of defects is mitigated by compensation from other defects, also dependent on the composition. [1] In this work we will look at the accuracy of a number of analytical techniques. We evaluate strengths and limitations of each for reporting useful information on thin film CIGS materials and evaluate them for accuracy in reporting CIGS composition.. EXPERIMENTALAnalytical techniques explored in this work for accuracy and general 'usefulness' include ICP-MS, XRF XRD, Raman, Auger, SIMS, STEM-EDS and RBS. Thin film CIGS materials were examined, some with composition gradients and some without. RESULTS AND OBSERVATIONS ICP-MS: Inductively Coupled Plasma Mass Spectrometry.ICP-OES measures composition with good accuracy while ICP-MS has high sensitivity for trace elements. Both are traceable to NIST standards using readily available solutions. In this work we quantify CIGS composition so ICP-OES should be the preferred choice. However, thin film samples do not provide much material and OES sensitivity to Se is low. Therefore ICP-MS is needed.The availability of NIST traceable solutions makes the ICP methods very attractive for accurate quantification. However, solid materials need to be dissolved before analysis presenting some challenges for CIGS. It is not possible to dissolve the CIGS film only without including some of the substrate. Thus the substrate cannot include Cu, In, Ga or Se. Glass substrates are usually not an issue but steel substrates can be problematic. Dissolution is often done at elevated temperature but this can cause some of the Se to be lost to vapor phase. Lower temperatures are required.ICP-MS can be very accurate provided a representative solution can be made from the CIGS thin film. Accuracy can be +/-1% absolute using NIST traceable reference solutions.Sample size is several cm of surface area and through the film thickness. No depth information is obtained. Table 1: ICP-MS measurement of composition for CIGS thin film material. Element %at +/-Cu 21.5 1 In 6.0 1 Ga 23.5 1 Se 49.0 1 XRF: X-Ray Fluorescence.XRF is a long proven technique for measuring metal alloy compositions. Quantification for bulk materials and thick films can be done using pure element standards. However, quantification for thin films cannot be done using pure element standards. XRF penetrates and collects information from up to 10µm into the surface. Thus much of the X-ray interaction occurs under rather than in the surface film of interest. Quantification for thin film XRF then requires a thin film s...