Computer Aided Design (CAD) alignment is a key requirement for dynamic fault isolation. CAD alignment between the drawn layout and the physical reflected image from the device helps to navigate and observe the physical location of the suspected circuitry. Conventionally, large structures such as the boundaries of Static Random-Access Memory (SRAM) cells are used as reference for coarse CAD alignment and the shallow trench isolation (STI) layer is used for fine alignment while analyzing logic cell structures. With technology scaling, especially into FinFETs, the fine alignment has become more challenging as the reflected optical image of STI layer is poorly resolved. In this paper, we discuss the enhanced CAD alignment techniques in Synopsys Avalon that uses features “Minimum object size (dimension based)”, and “net search” developed in the CAD tool, Synopsys Avalon, combined with Amplitude lock-in Dynamic Photon Emission Microscopy (D-PEM) technique to assist a finer CAD alignment.

Electrooptical investigations such as laser voltage probing (LVP) and dynamic laser stimulation (DLS) are very popular electrical fault isolation techniques (EFI) that use lasers on semiconductor circuits to study the functionality of transistors while the device is in operation. While many studies have been undertaken to understand interaction between laser and planar devices, three-dimensional devices such as FinFETs have interesting physiologies that have not been fully explored. In this work, we study the interaction of polarized light with the n-type metal oxide semiconductor (NMOS) FinFETs, experimentally and through Multiphysics simulations. We report highly directional electrooptical interactions in the FinFET. LVP signals are stronger when the laser used is polarized parallel to the fin and laser stimulation stronger when the laser used is polarized parallel to the gate. These findings affect future laser stimulation and probing investigations for EFI.

Short wavelength probing (SWP) uses wavelengths of light shorter than 1100 nm or energies higher than silicon bandgap for laser probing applications. While SWP allows a significant improvement to spatial resolution, there are aberrations to the collected laser probing waveforms which result in difficulties in signal interpretations. In this work, we assess the signals collected through SWP (785 nm) and introduce a photodiode model to explain the observations. We also present a successful case study using 785 nm for failure analysis in sub-20 nm FinFET technology.

Dynamic Photon Emission Microscopy (D-PEM) is an established technique for isolating short and open failures, where photons emitted by transistors are collected by sensitive infra-red detectors while the device under test is electrically exercised with automated test equipment (ATE). Common tests, such as scan, use patterns that are generated through Automatic Test Pattern Generator (ATPG) in compressed mode. When these patterns are looped for D-PEM, it results in indeterministic states within cells during the load or unload sequences, making interpretation of emission challenging. Moreover, photons are emitted with lower probability and lesser energies for smaller technology nodes such as the FinFET. In this paper, we will discuss executing scan tests in manners that can be used to bring out emission which did not show up in conventional test loops.

Combinational logic analysis (CLA) using laser voltage probing allows studying standard cells such as NOR or NAND gates as a whole, instead of individual transistors. The process involves building a reference library of laser probing (LP) waveforms and comparing them to signals from the real device. While CLA has greatly increased the success rate and turn-around time for LP, there are difficulties in signal interpretation. This is partly due to the lack of precise understanding of the laser interaction area and probe placement and partly due to difficulties identifying the correct logic states in the waveform. In this work, we have significantly improved the CLA process by first predicting the shape of the waveform based on laser interaction with the target circuitry and second, implementing an automated pattern search algorithm to further increase the speed and reliability of CLA using LP.