Designed to meet the demands of advanced semiconductor technologies, the Dragonfly G5 system is purpose-built to deliver high-performance, reliable inspection and metrology across complex heterogeneous integration processes. Leveraging next generation high speed line scan 2D imaging and custom-engineered objectives, the system achieves over 3X throughput improvement compared to its predecessor, with submicron sensitivity down to 150nm. 

Continuing the legacy of innovation, the Dragonfly G5 system introduces a multi-angle illumination channel that significantly improves signal-to-noise ratio for faint defect detection. Combined with powerful AI-driven algorithms, it enhances both the detectability and classification of critical, yield-impacting defects–empowering fabs to maintain quality and accelerate time-to-yield. 

The Dragonfly G5 system expands process control flexibility for wafer-to-wafer and die-to-wafer bonding by integrating high-speed IR imaging to detect sub-surface defects. It incorporates the latest generation of 3Di™ technology, extending bump height metrology capabilities to support next-generation microbumps essential for 3D integration. This enables additional inspection and metrology touchpoints across increasingly complex packaging architectures. 

The primary application of non-contact CV metrology is monitoring dielectric properties during IC manufacturing. Unlike conventional electrical measurements, it requires no sample preparation, eliminating the need for MOS capacitor structures. This reduces metrology cost and enables fast data feedback in both R&D and manufacturing environments. 

The corona-Kelvin method uses a corona discharge in air to deposit an electric charge (DQC) on the wafer surface. A vibrating Kelvin-probe then measures the resulting surface voltage (V), enabling determination of the differential capacitance (C= DQC/DV). By monitoring surface voltage in both dark and illuminated conditions, the system separates two key components: dielectric voltage (VD) and semiconductor surface potential (VSB), enabling determination of flat band voltage (VFB). 

Analysis of the resulting charge-voltage data yields electrical parameters, including trap density (Dit), flat band voltage (Vfb), dielectric charge (Qtot), dielectric capacitance (CD), Equivalent Oxide Thickness (EOT), leakage current, and tunneling characteristics. 

As more high aspect ratio processes are used in multiple industry segments, there are metrology needs for monitoring of related processes, including dimensions and properties of carbon film hard masks and etched 3D structures. 

The Aspect S delivers high-throughput, low COO, non-contact, non-destructive measurements of dimensions and uniformity of layers and etched structures used in integrated circuit manufacturing. The small spot size makes the tool suitable for measurements of scribe line test structures as in-line process control. The unique technology and analysis capability simplifies system calibration requirements and removes the effect of substrate variations for key layer measurements.  

While the software contains advanced features for measurement recipe and analysis model creation, it has a user-friendly interface and implementation that allows the fab customers to create and manage the recipe system for Aspect S tool fleets. 

Thickness map from amorphous carbon film

There is no disputing the detrimental effect of metallic contamination on the integrity of the critical gate oxide used in integrated circuits. During high temperature processing, contamination in the silicon wafer often precipitates at the Si/dielectric interface or segregates into the dielectric—both scenarios can cause premature device failure and reduced yield. As device dimensions shrink, the tolerance for contamination decreases, requiring ever-lower background levels of metals like iron (Fe). Over the past 25 years, the IC industry has reduced typical Fe concentrations by more than three orders of magnitude, yet further reduction is essential, especially for applications like CMOS image sensors. 

The FAaST Digital SPV system addresses this challenge with industry-leading sensitivity and speed. It provides a fast, non-contact, and preparation-free method for full-wafer imaging of contamination. High-resolution maps of minority carrier diffusion length and Fe concentration are generated in minutes, enabling fabs to detect and control contamination at levels as low as the E7 cm⁻³ range. 

Figure 1. Typical background Fe concentration in new IC Fablines (blue) and the state-of-the-art SPV detection limit (red)

The CnCV system utilizes a novel constant surface potential corona charging, which enables the precision required over a large voltage range. The patented technology includes charge- and photo-assisted modes, especially suited for speed and precision on WBG materials and structures, including SiC, Ga2O3, GaN, and AlGaN/GaN HEMT. Additionally, Corona-Kelvin characterization includes electrical properties of dielectrics and interfaces of films on SiC and GaN epi layers. An automated top-side edge contact (TSEC) is also available enabling characterization of WBG on insulating/semi-insulating substrates. Automated bias-temperature stress (BTS) measurements are also available with the CnCV system, providing a fast, noncontact way to quantify the reliability of passivated SiC and GaN. 

Beyond typical CV type parameters, the full wafer corona approach allows for QUAD (quality, uniformity, and defect) mapping. The electrical defect imaging, QUAD-EDI, mode is especially designed for SiC. It provides a unique means for quick screening of epi electrical defectivity enabling improvement in device yield prediction. 

Figure 1. QUAD-EDI Map on final metallized device wafer after Merged Schottky PiN diode fabrication identifying failed dies.

Yield Optimizer software is the next incarnation of analytics on the evolutionary scale. The software’s disruptive technology analyzes relationships between multivariant data and their complex interactions. By examining any set of conceivable inputs and outputs, Yield Optimizer software identifies the relationships and interactions that lead to positive operational changes. Easily understood visuals empower even casual users to understand what is important before making adjustments.

Yield Optimizer software evaluates multiple models and suggests the best one for the data. Using machine learning, it examines the interactions between in-process metrology readings and end-of-line test results for any semiconductor product family and recommends changes to the in-process metrology targets. When licensed as a service, it enables users to leverage an on-demand infrastructure to apply easily understood workflows for complex analytics without the overhead.