Laser Voltage Probing (LVP) is an essential Failure Analysis (FA) technique that has been widely adopted by the industry. Waveforms that are collected allow for the analyst to understand various internal failure modes related to timing or abnormal circuit behavior. As technology nodes shrink to the point where multiple transistors reside within the diffraction-limited laser spot size, interpretation of the waveforms can become extremely difficult. In this paper we discuss some of the evolving challenges faced by LVP and propose a new technique known as Differential LVP (dLVP) that can be used to debug marginal failing devices that exhibit a pass/fail boundary in their shmoo plot. We demonstrate how separate pass and fail LVP waveforms can be collected simultaneously and compared to immediately identify whether logic is corrupted and when the corruption occurs. The benefits of this new technique are many. They include guarantees of equivalent pass vs. fail data independent of crosstalk, system noise, stage drift, probe placement, temperature effects, or the diffraction-limited resolution of the probe system. Implementing dLVP into existing tools could extend their effective lifetimes and improve their efficacy related to the demands posed by the debug of 5nm technologies and smaller geometries. We anticipate that fully integrated and evolved dLVP will complement workhorse FA applications such as Laser Assisted Device Alteration (LADA) and Soft Defect Localization (SDL) analysis. Wherein those techniques map timing marginalities propagating to, and observed by, a capture flop, dLVP can extend such capabilities by identifying the first instance of corrupted logic inside the flop and map the corruption all the way to the chip output pin.

Near Infra-Red (NIR) techniques such as Laser Voltage Probing/Imaging (LVP/I), Dynamic Laser Stimulation (DLS), and Photon Emission Microscopy (PEM) are indispensable for Electrical Fault Isolation/Electrical Failure Analysis (EFI/EFA) of silicon Integrated Circuit (IC) devices. However, upcoming IC architectures based on Buried Power Rails (BPR) with Backside Power Delivery (BPD) networks will greatly reduce the usefulness of these techniques due to the presence of NIR-opaque layers that block access to the transistor active layer. Alternative techniques capable of penetrating these opaque layers are therefore of great interest. Recent developments in intense, focused X-ray microbeams for micro X-Ray Fluorescence (μXRF) microscopy open the possibility to using X-rays for targeted and intentional device alteration. In this paper, we will present results from our preliminary investigations into X-ray Device Alteration (XDA) of flip-chip packaged FinFET devices and discuss some implications of our findings for EFI/EFA.

While 2.5D and 3D solutions continue to drive advancements in the electronics packaging industry, challenges persist with their reliability and qualification. In this paper, we introduce a new technique that may prove valuable for nondestructive, in-situ measurements of package and die warpage. This system allows for the powerful visualization tools of Computed Tomography to be applied to samples at elevated and cryogenic temperatures over a broad temperature range (+125C to -257C).

The adoption of 3D packaging technology necessitates the development of new approaches to failure electronic device analysis. To that end, our team is developing a tool called the quantum diamond microscope (QDM) that leverages an ensemble of nitrogen vacancy (NV) centers in diamond, achieving vector magnetic imaging with a wide field-of-view and high spatial resolution under ambient conditions. Here, we present the QDM measurement of 2D current distributions in an 8-nm flip chip IC and 3D current distributions in a multi-layer PCB. Magnetic field emanations from the C4 bumps in the flip chip dominate the QDM measurements, but these prove to be useful for image registration and can be subtracted to resolve adjacent current traces in the die at the micron scale. Vias in 3D ICs display only Bx and By magnetic fields due to their vertical orientation and are difficult to detect with magnetometers that only measure the Bz component (orthogonal to the IC surface). Using the multi-layer PCB, we show that the QDM’s ability to simultaneously measure Bx , By , and Bz is advantageous for resolving magnetic fields from vias as current passes between layers. We also show how spacing between conducting layers is determined by magnetic field images and how it agrees with the design specifications of the PCB. In our initial efforts to provide further z -depth information for current sources in complex 3D circuits, we show how magnetic field images of individual layers can be subtracted from the magnetic field image of the total structure. This allows for isolation of signal layers and can be used to map embedded current paths via solution of the 2D magnetic inverse. In addition, the paper also discusses the use of neural networks to identify 2D current distributions and its potential for analyzing 3D structures.

The emergence of heterogenous integration driven by system-in-package (SiP) technology not only increases the complexity of semiconductor failure analysis, but also makes it more difficult to protect intellectual property because of the growing need to share design information to facilitate fault isolation in assembly and test. One way to address these challenges is through a computer-aided design (CAD) database that can be navigated across multiple components without exposing sensitive information. This paper describes the development and use of such a resource and how it enables safe and secure data sharing among supply chain partners.

In this paper, we discuss the use of spontaneous photon emission microscopy (PEM) for observing filaments formed in HfO 2 resistive random access memory (ReRAM) cells. The setup employs a CCD and an InGaAs camera, revealing photon emissions in both forward ( set ) and reverse ( reset ) bias conditions. Photon emission intensity is modeled using an electric-field equation and inter-filament distance and density are determined assuming a uniform spatial distribution. The paper also discusses the use of high frame rate and prolonged photon emission measurements to assess lifetime and reliability and explains how single filament fluctuations and multiple filaments in a single cell were observed for the first time.

We present a new method for backside integrated circuit (IC) magnetic field imaging using Quantum Diamond Microscope (QDM) nitrogen vacancy magnetometry. We demonstrate the ability to simultaneously image the functional activity of an IC thinned to 12 µm remaining silicon thickness over a wide fieldof- view (3.7 x 3.7 mm 2 ). This 2D magnetic field mapping enables the localization of functional hot-spots on the die and affords the potential to correlate spatially delocalized transient activity during IC operation that is not possible with scanning magnetic point probes. We use Finite Element Analysis (FEA) modeling to determine the impact and magnitude of measurement artifacts that result from the specific chip package type. These computational results enable optimization of the measurements used to take empirical data yielding magnetic field images that are free of package-specific artifacts. We use machine learning to scalably classify the activity of the chip using the QDM images and demonstrate this method for a large data set containing images that are not possible to visually classify.

Getting accurate fault isolation during failure analysis is mandatory for success of Physical Failure Analysis (PFA) in critical applications. Unfortunately, achieving such accuracy is becoming more and more difficult with today’s diagnosis tools and actual process node such as BCD9 and FinFET 7 nm, compromising the success of subsequent PFA done on defective SoCs. Electrical simulation is used to reproduce emission microscopy, in our previous work and, in this paper, we demonstrate the possibility of using fault simulation tools with the results of electrical test and fault isolation techniques to provide diagnosis with accurate candidates for physical analysis. The experimental results of the presented flow, from several cases of application, show the validity of this approach.

Rapid identification of organic contamination in the semi and semi related industry is a major concern for research and manufacturing. Organic contamination can affect a system or subsystem’s performance and cause premature failure of the product. As an example, in February 2019 the Taiwan Semiconductor Manufacturing Company (TMSC), a major semiconductor manufacturer, reported that a photoresist it used included a specific element which was abnormally treated, creating a foreign polymer in the photoresist resulting in an estimated loss of $550M [1].

Currently gaps in non-destructive 2D and 3D imaging in PFA for advanced packages and MEMS exist due to lack of resolution to resolve sub-micron defects and the lack of contrast to image defects within the low Z materials. These low Z defects in advanced packages include sidewall delamination between Si die and underfill, bulk cracks in the underfill, in organic substrates, Redistribution Layer, RDL; Si die cracks; voids within the underfill and in the epoxy. Similarly, failure modes in MEMS are often within low Z materials, such as Si and polymers. Many of these are a result of mechanical shock resulting in cracks in structures, packaging fractures, die adhesion issues or particles movements into critical locations. Most of these categories of defects cannot be detected non-destructively by existing techniques such as C-SAM or microCT (micro x-ray computed tomography) and XRM (X-ray microscope). We describe a novel lab-based X-ray Phase contrast and Dark-field/Scattering Contrast system with the potential to resolve these types of defects. This novel X-ray microscopy has spatial resolution of 0.5 um in absorption contrast and with the added capability of Talbot interferometry to resolve failure issues which are related to defects within organic and low Z components.