The use of a scanning probe microscope (SPM), such as a conductive atomic force microscope (C-AFM) has been widely reported as a method of failure analysis in nanometer scale science and technology [1-6]. A beam bounce technique is usually used to enable the probe head to measure extremely small movements of the cantilever as it is moved across the surface of the sample. However, the laser beam used for a beam bounce also gives rise to the photoelectric effect while we are measuring the electrical characteristics of a device, such as a pn junction. In this paper, the photocurrent for a device caused by photon illumination was quantitatively evaluated. In addition, this paper also presents an example of an application of the C-AFM as a tool for the failure analysis of trap defects by taking advantage of the photoelectric effect.

SRAM memory is an ideal vehicle for defect monitoring and yield improvement during process development because of its highly structured architecture. However, the success rate of defect detection, especially for soft single-column failures, is decreasing when traditional physical failure analysis (PFA) with only the bitmap is available for guidance. This is due to a variety of invisible or undetectable defects that cause leakage in the device. In order to understand the leakage behavior in advanced high voltage (HV) processes, a Conductive Atomic Force Microscope (C-AFM) [1-4] is introduced to perform junction-level fault isolation prior to attempting PFA. According to J. P. Morniroli [5], crystalline defects affect convergent-beam electron diffraction (CBED) and large angle convergent-beam electron diffraction (LACBED) patterns, so CBED and LACBED techniques were also applied to the specimens containing dislocations to allow further characterization of these defects. In this study quantified data extracted using the C-AFM is also used to establish a connection between the failure mechanism discovered and the soft single column failure mode.

The importance of understanding mismatched behavior in SRAM devices has increased as the technology node has shrunk below 100nm. Using the nanoprobe technique [1-3], the MOS characteristics of failure bits in actual SRAM cells have been directly measured. After transistors that are failing were identified, the best approach for identifying nanoscale defects was determined. In this study, several types of nanoscale defects, such as offset spacer residue, salicide missing from the active area, doping missing from the channel, gate oxide defects, contact barrier layer residue, and severed poly-gate silicide were successfully discovered.

The difficulties in identifying the precise defect location and real leakage path is increasing as the integrated circuit design and process have become more and more complicated in nano scale technology node. Most of the defects causing chip leakage are detectable with only one of the FA (Failure Analysis) tools such as LCD (Liquid Crystal Detection) or PEM (Photon Emission Microscope). However, due to marginality of process-design interaction some defects are often not detectable with only one FA tool [1][2]. This paper present an example of an abnormal power consumption process-design interaction related defect which could only be detected with more advanced FA tools.

Single column failure [1], one of the complex failure modes in SRAM is possibly induced by multiform defect types at diverse locations. Especially, soft single column failure is of great complexity. As physical failure analysis (PFA) is expensive and time-consuming, thorough electrical failure analysis (EFA) is needed to precisely localize the failing area to greater precision before PFA. The methodology involves testing for failure mode validation, understanding the circuit and using EFA tools such as IR-OBIRCH (InfraRed-Optical Beam Induced Resistance CHange) and MCT (MerCad Telluride, HgCdTe) for analysis. However, the electrical failure signature for soft single column failure is usually marginal, so additional techniques are needed to obtain accurate isolation and electrical characterization instead of blindly looking around. Thus in this discussion, we will also present the use of internal probing techniques like C-AFM [2] (Conductive Atomic Force Microscopy) and a nanoprobing technique [3] for characterizing electrical properties and understanding the root cause.