Scan chain failure analysis using laser voltage imaging

Design-for-test methodologies have enabled considerable reduction in test time and improvement in defect isolation. Defects which impede correct operation of scan chains are a significant fraction of yield loss. Isolating these defects is an important but underserved activity.Image-based technologies examining an extended area of die are popular diagnostics techniques because they provide intuitive and useful results. Emission based microscopy and laser fault isolation techniques, both static and dynamic, are readily available. However, neither technique provides insight to specific timing characteristics of the IC. Photoemission microscopy suffers from decreasing signal strength at lower voltages, and laser techniques can be difficult to perform with production test setups, requiring involved test pattern and setup adaptation.In this paper, we describe two scan chain defect localization case studies using Laser Voltage Imaging [1] on 40 nm bulk CMOS technology operating at 0.9 V. Results are also compared to other diagnostics techniques, including software-based shift analysis and photoemission microscopy.     

Stability of the Y2O3–SiO2 system in high-temperature,high-velocity water vapor

High-temperature, high-velocity water vapor (steam-jet) exposures were conducted on Y₂O₃, Y₂SiO₅, Y₂Si₂O₇, and SiO₂ for 60 hours at 1400°C. Volatility of Y₂O₃ was not observed. Phase-pure Y₂SiO₅ exhibited SiO₂ loss forming Y₂O₃ and porosity. A mixed porous and dense Y₂SiO₅ layer formed on the surface of Y₂Si₂O₇ due to SiO₂ depletion. The mechanisms and kinetics of the reaction between SiO₂ and H₂O(g) to form Si(OH)₄(g) from Y₂SiO₅, Y₂Si₂O₇, and SiO₂ are discussed.     

Detailed characterization of particulates emitted by pre-commercial single-cylinder gasoline compression ignition engine

Gasoline Compression Ignition (GCI) engines have the potential to achieve high fuel efficiency and to significantly reduce both NOx and particulate matter (PM) emissions by operating under dilute, partially-premixed conditions. This low temperature combustion strategy is dependent upon direct-injection of gasoline during the compression stroke and potentially near top dead center (TDC). The timing and duration of the in-cylinder injections can be tailored based on speed and load to create optimized conditions that result in a stable combustion.     

A tunable integration method for the simulation of power systemdynamics

Accurate simulation of power-systems dynamics over an extended time period results in a model that is relatively stiff; the solution of such models requires a numerical integration method that is not only fast and accurate, but also capable of using long time steps. An integration method which can be numerically tuned to suit the system of equations is developed and is shown to be superior to the trapezoidal rule when very long time steps are used. While the fixed-tuning methods are easy to implement, they are not recommended since they resulted in no significant improvements. Adaptively tuned techniques performed better and some worthwhile gains were obtained with long time steps     

An iterative method for calculating the shielding effectiveness andlight transmittance of multilayered media

A simple, rapid, and accurate numerical method is presented for calculating the shielding effectiveness and the light transmittance of multilayered media. A uniform treatment is used to obtain the shielding effectiveness of the layers at microwave frequencies and their light transmittance at optical frequencies. The method is completely general and does not involve any approximation. It can be applied at any frequency, for vertical or oblique incidence, to lossless or lossy, isotropic or anisotropic media consisting of any number of dielectric and metallic layers. In order to illustrate the versatility of the method, the shielding effectiveness and the light transmittance of two different structures consisting of a gold film deposited over a plastic substrate and of a plastic substrate sandwiched between two gold films are analyzed under different conditions     

On Darwinian Networks

We suggest Darwinian Networks (DNs) as a simplification of working with Bayesian networks (BNs). DNs adapt a handful of well‐known concepts in biology into a single framework that is surprisingly simple yet remarkably robust. With respect to modeling, on one hand, DNs not only represent BNs but also faithfully represent the testing of independencies in a more straightforward fashion. On the other hand, with respect to three exact inference algorithms in BNs, DNs simplify each of them while unifying all of them. DNs can determine good elimination orderings using the same platform as used for modeling and inference. Finally, we demonstrate how DNs can represent two additional frameworks. Practical benefits of DNs include faster algorithms for inference and modeling.     

Silicon microfabricated column with microfabricated differential mobility spectrometer for GC analysis of volatile organic compounds

A 3.0-m-long, 150-microm-wide, 240-microm-deep channel etched in a 3.2-cm-square silicon chip, covered with a Pyrex wafer, and coated with a dimethyl polysiloxane stationary phase is used for the GC separation of volatile organic compounds. The column, which generates approximately 5500 theoretical plates, is temperature-programmed in a conventional convection oven. The column is connected through a heated transfer line to a microfabricated differential mobility spectrometer. The spectrometer incorporates a 63Ni source for atmospheric-pressure chemical ionization of the analytes. Nitrogen or air transport gas (flow 300 cm(3)/min) drives the analyte ions through the cell. The spectrometer operates with an asymmetric radio frequency (RF) electric field between a pair of electrodes in the detector cell. During each radio frequency cycle, the ion mobility alternates between a high-field and a low-field value (differential mobility). Ions oscillate between the electrodes, and only ions with an appropriate differential mobility reach a pair of biased collectors at the downstream end of the cell. A compensation voltage applied to one of the RF electrodes is scanned to allow ions with different differential mobilities to pass through the cell without being annihilated at the RF electrodes. A unique feature of the device is that both positive and negative ions are detected from a single experiment. The combined microfabricated column and detector is evaluated for the analysis of volatile organic compounds with a variety of functionalities.     

Nanoparticles Containing Oxidized Cholesterol Deliver mRNA to the Liver Microenvironment at Clinically Relevant Doses

Using mRNA to produce therapeutic proteins is a promising approach to treat genetic diseases. However, systemically delivering mRNA to cell types besides hepatocytes remains challenging. Fast identification of nanoparticle delivery (FIND) is a DNA barcode‐based system designed to measure how over 100 lipid nanoparticles (LNPs) deliver mRNA that functions in the cytoplasm of target cells in a single mouse. By using FIND to quantify how 75 chemically distinct LNPs delivered mRNA to 28 cell types in vivo, it is found that an LNP formulated with oxidized cholesterol and no targeting ligand delivers Cre mRNA, which edits DNA in hepatic endothelial cells and Kupffer cells at 0.05 mg kg^?1. Notably, the LNP targets liver microenvironmental cells fivefold more potently than hepatocytes. The structure of the oxidized cholesterols added to the LNP is systematically varied to show that the position of the oxidative modification may be important; cholesterols modified on the hydrocarbon tail associated with sterol ring D tend to outperform cholesterols modified on sterol ring B. These data suggest that LNPs formulated with modified cholesterols can deliver gene‐editing mRNA to the liver microenvironment at clinically relevant doses.     

Disclosure of personal data in ecommerce: A cross-national comparison of Estonia and the United States

This study examines how demographic variables affect willingness to disclose and perceived risks of disclosing personally identifying information (PII, also referred to as personal data in Europe) in ecommerce in the United States and Estonia. The study utilized a 17-item list of potential disclosure items (name, email address, etc.), categorized reliably into six sub-indices: contact information, payment information, life history information, financial/medical information, work-related information, and online account information. Online disclosure consciousness (ODC) is introduced as a framework to conceptualize, explain the study’s findings, and empirically measure the gap between one’s willingness to disclose and perceived risk pertaining to the overall 17-item index used in the study, the sub-indices, and particular items. The results show significant gaps among participants both within and across nations. Despite Estonia’s advanced adoption and progressive policies and practices toward the Internet, Americans are more willing to disclose, and less concerned about perceived risks. The findings suggest willingness to disclose and risk aversion can and should be analyzed empirically together. The theoretical model provides an alternative conceptualization to the ideas of the privacy paradox, privacy calculus, and privacy cost-benefit ratios. Implications for theory, consumers, marketing practice, and public policy are discussed. Importantly, the study can inform increased adoption of ecommerce and the digital economy, while also protecting consumer’s personal data.