Presentation slides for the ISTFA 2024 Tutorial session “Basics and Current Aspects of Scanning Electron Microscopy.”

Presentation slides for the ISTFA 2024 Tutorial session “AI-Driven Advancements in Image Processing, Analysis and 3D Modeling for Fault Isolation and Failure Analysis.”

Image segmentation is a valuable tool for visual image data inspection of semiconductor device structures. For the large amounts of data provided by recent advancements in automated scanning electron microscope (SEM) and focused ion beam-scanning electron microscope (FIB-SEM) data acquisition, automatic segmentation becomes indispensable to fully exploit the information contained in the data in automated characterization workflows. Using two exemplary FIB-SEM tomography datasets, we explored artificial intelligence based image segmentation using only a minimum amount of training images annotated by a human user.

In semiconductor manufacturing, the process of laser dicing can result in a loss of yield due to defects associated to the laser interaction with the sample. These defects can be difficult to identify, especially before a proper tuning of the process. Traditional investigation methods, like infrared (IR) inspection and focused-ion beam scanning electron microscopy (FIB-SEM) analysis, are labor-intensive and lack comprehensive insights. Here, we propose a robust correlative microscopy (CM) workflow integrating IR, X-ray Microscopy (XRM), and FIB-SEM tomography analyses, leveraging artificial intelligence (AI) driven algorithm for time- and quality-improved dataset reconstruction, automatic segmentation and defect site identification. Our approach streamlines defect identification, preparation, and characterization. Through AI-enhanced methodologies, as well as femtosecond (fs) laser, we optimize investigation efficiency and extract crucial information about defects properties and evolution. Our research aims to advance semiconductor failure analysis by integrating AI for enhanced defect localization and high-quality 3D dataset acquisition in the realm of laser dicing processes.

The effects of sample prep with a Ga + -ion Focused Ion Beam (Ga-FIB) on measurements of electron beam induced current (EBIC) were studied. Concerns have been occasionally raised about amorphization from the beam, or even Ga + implantation ruining the ability to make useful measurements for purposes of either failure analysis or device tailoring. To understand the magnitude of any deleterious effects, two different lamellae from a 5 nm SRAM sample were prepared with different areas of increasingly improved polish, as indicated by decreasing, cumulative, FIB beam energy, followed by EBIC measurements at 1 or 2 kV beam landing energy. A first experiment looked at the ability to generate EBIC measurements from depletion zones and found no difference across the various beam polish cells. A second experiment considered leakage and/or shorts and found little problematic currents, within standard deviations.

Power MOSFETs are electronic devices that are commonly used as switches or amplifiers in power electronics applications such as motor control, audio amplifiers, power supplies and illumination systems. During the fabrication process, impurities such as copper can become incorporated into the device structure, giving rise to defects in crystal lattice and creating localized areas of high resistance or conductivity. In this work we present a multiscale and multimodal correlative microscopy workflow for the characterization of copper inclusions found in the epitaxial layer in power MOSFETs combining Light Microscopy (LM), non-destructive 3D X-ray Microscopy (XRM), Focused-Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography coupled with Energy Dispersive X-ray Spectroscopy (EDX), and Transmission Electron Microscopy (TEM) coupled with Electron Energy Loss Spectroscopy (EELS). Thanks to this approach of correlating 2D and 3D morphological insights with chemical information, a comprehensive and multiscale understanding of copper segregations distribution and effects at the structural level of the power MOSFETs can be achieved.

Focused-Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography is a high resolution three-dimensional (3D) imaging method with applications in failure analysis and metrology of semiconductor devices. For the smallest logic and memory structures currently in use, it requires single-digit nanometer 3D resolution. In this resolution range, avoiding distortion artifacts in the data becomes crucial. We present examples and discuss ways to reduce the likelihood of such artifacts during the data acquisition, as well as how to mitigate them in post-processing, and therefore increase the data quality.

Insulated Gate Bipolar Transistors (IGBT) and silicon carbide (SiC) based MOSFETs have become the predominantly used power semiconductors in particular in automotive applications. For failure analysis of such devices, site-specific access to subsurface fault sites is required, as is understanding their construction and junction profiles, and how the device turns on. We have applied focused ion beam-scanning electron microscopy (FIB-SEM) tomography to visualize inner structure and dopant distributions of an IGBT and of a SiC MOSFET in three dimensions (3D). Such 3D data can be used to complement 2D electron beam induced current (EBIC) measurements obtained at site-specific FIB cross-sections in these devices.

A commercially available 4H-SiC power device and a GaN on SiC HEMT were examined with Ga-FIB sectioning and various junction analysis techniques. The impact of Ga-FIB on the electronic properties of such power devices is observed to be less significant than anticipated. A field of view was FIB-milled into the structure, exposing a row of devices. In this window, p/n junctions were evaluated by Passive Voltage Contrast (PVC), Electron Beam Induced Current (EBIC), and Kelvin Force Probe Microscopy (KFPM). Results showed excellent fidelity to expectations and each technique brought out new insights. In further work, the gate voltage was varied and the changing of depletion zones upon device turn-on was observed. This work: 1) Demonstrates complete sufficiency of Ga-FIB cross sections for regular cross-sectional work. 2) Demonstrates a novel method for investigating junction properties from Ga-FIB sections of power devices which largely leaves the rest of the device intact. 3) Provides some assurance that the Ga-FIB does not severely impact the evaluation of junction properties in some power semiconductors. 4) Points to alternative mechanism for device turn-on.

Presentation slides for the ISTFA 2023 Tutorial session “Basics and Current Aspects of Scanning Electron Microscopy (2023 Update).”

Presentation slides for the ISTFA 2023 Tutorial session “Power Semiconductor Failure Analysis Tutorial.”

This presentation addresses topics of relevance to scanning electron microscopy, including SEM basics, electron guns, electron optics, beam-specimen interactions, signal detection, sample prep and cleanliness, low-voltage imaging, nonconductive imaging, voltage contrast, stage biasing, electron channeling contrast imaging, magnetic contrast imaging, STEM-in-SEM, 3D imaging and analytics, image post-processing, and automation.

In this work we present a new approach in physical failure analysis. Fault isolation can be done using volume diagnosis techniques. But when studying the identified defect sites by Focused Ion Beam (FIB) cross-sectioning, correct interpretation of the cross-sectional views strongly relies on choosing an appropriate cutting strategy. However, volume diagnosis techniques do not provide any information on which cutting directions and settings to choose to avoid misinterpretation of the spatial evolution of the defects. The proposed approach is to acquire FIB-SEM tomographic datasets at the defect sites to unequivocally characterize the defects in three-dimensional visualizations, independent of particular cross-sectioning strategies. In this specific case we have applied the methodology at a microcontroller for automotive applications on which a couple of floating VIAS were found. Thanks to the complete information obtained with the tomography, the defect could be assigned to a specific class of etching tools, and the root cause thus be solved.

Secondary ion mass spectrometry (SIMS) is a well-established method in semiconductor manufacturing process control and development for trace metal and organic contaminant detection, as well as for depth profiling of ultra-thin film stacks and total dopant concentrations. Using a focused ion beam (FIB) as the primary ion beam provides a versatile and highly sensitive analytical technique with lateral resolution down to a few tens of nanometers, an appropriate technique for targeted failure analysis on functional device structures. This paper presents an example to show the potential of FIB-SIMS to support failure analysis, concentrating on practical aspects of the technique.

In prior work, it was demonstrated that information about device turn-on can be obtained in a nanoprobing setup which involves no applied bias across the channel. This was performed on nFET logic devices in 7 nm technology and attributed to the Seebeck effect, or heating from the SEM beam. In this work, the experiments are continued to both nFET and pFET devices and on both 22 nm and 5 nm devices. Further discussion about the opportunities and evidence for Seebeck effect in nanoprobing are discussed.

This presentation addresses topics of relevance to scanning electron microscopy, including SEM basics, electron guns, electron optics, beam-specimen interactions, signal detection, sample prep and cleanliness, low-voltage imaging, nonconductive imaging, voltage contrast, stage biasing, electron channeling contrast imaging, magnetic contrast imaging, STEM-in-SEM, 3D imaging and analytics, and image post-processing.