Tektronix (United States)

Underfill material plays a crucial role in flip-chip package reliability, thus it necessary to accurately understand the mechanical properties. The material itself is nonlinear and is dependent on degree of cure, temperature, strain rate and thermal aging, among others. In this work, two underfill materials were characterized for thermal expansion and viscoelastic properties over a wide temperature range. A second set of each material was thermally aged through flip-chip processing steps and 250 thermal cycles and then characterized. Temperature dependent thermal expansion and time-temperature dependent moduli curves were generated to represent each material type. These material models were then implemented into a nonlinear finite element model of a flip-chip package to evaluate package stress interaction through processing steps and thermal cycling. The influence that each underfill material had with and without thermal aging was analyzed with respect to typical package failure mechanisms.

Nanomechanical test instruments can precisely measure force and displacement and produce repeatable load-unload curves that can be used in characterizing mechanical behaviour at the nanoscale. In this study, a newly developed translucent nanomechanical test instrument was used in deriving reproducible stiffness values for ultra nano crystalline diamond (UNCD)-made atomic force microscope (AFM) cantilevers that are used for mechanical properties characterization of DLC films. The instrument which is calibrated according to the ISO-14577 standard is integrated with nano/micropositioners and multi-view optical microscopes to facilitate precise manipulation of those AFM cantilevers that were dozens of micrometers in size. Experimental results on UNCD-made AFM cantilever stiffness measurements are provided and compared with theoretical and batch production values.

The NASA Juno mission includes a six-channel microwave radiometer system (MWR) operating in the 1.3–50 cm wavelength range in order to retrieve abundances of ammonia and water vapor from the microwave signature of Jupiter (see Janssen et al. 2016). In order to plan observations and accurately interpret data from such observations, over 6000 laboratory measurements of the microwave absorption properties of gaseous ammonia, water vapor, and aqueous ammonia solution have been conducted under simulated Jovian conditions using new laboratory systems capable of high-precision measurement under the extreme conditions of the deep atmosphere of Jupiter (up to 100 bars pressure and 505 K temperature). This is one of the most extensive laboratory measurement campaigns ever conducted in support of a microwave remote sensing instrument. New, more precise models for the microwave absorption from these constituents have and are being developed from these measurements. Application of these absorption properties to radiative transfer models for the six wavelengths involved will provide a valuable planning tool for observations, and will also make possible accurate retrievals of the abundance of these constituents during and after observations are conducted.

As the capacity of integrated circuits increases, it is becoming increasingly difficult to ensure that a chip is free of design errors. Designers are increasingly turning to FPGA prototyping platforms to validate their designs much more extensively than is possible using simulation. A key challenge is one of visibility; signals can only be observed if they can be driven to pins of a chip. To enhance visibility during debug, designers regularly instrument their design with on-chip circuitry to record a small subset of signals at-speed for later off-chip analysis. The selection of which signals should be recorded critically affects the effectiveness of this approach. In this paper, we present an algorithm that ranks all signals in a design based on their predicted importance during validation. Compared to previous techniques, which analyze the circuit at the gate level, our algorithm works directly on the parse-tree representation of the circuit, and hence is orders of magnitude faster than these previous techniques. Our algorithm has been implemented as an integral part of Tektronix Certus, a commercial validation suite.

Having two, or more, transistors with different values of f <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</inf> and BV <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CEO</inf> provides flexibility to circuit designers in making tradeoffs of power and performance. The process complexity and resulting cost of fabricating these transistors on the same wafer is another important factor. Three different approaches for co-integrating high-performance and high-breakdown SiGe npn HBTs with minimal process deviation are presented herein. The work features a high-performance HBT with f <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</inf> × BV <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CEO</inf> product of 500GHz-V and a high-breakdown HBT with over 430GHz-V integrated on the same wafer with one-mask deviation.

Recently, an analysis of current scanned-beam laser projection systems was presented and showed that the maximum achievable Class 2 eye-safe luminous flux levels are fundamentally limited by the nature of the projection architecture. In this paper, an improved estimate for the maximum Class 2 eye-safe luminous flux is derived by considering unidirectional and bidirectional scan patterns. It is shown that, due to pulse spacing conditions at the edge of the projected image, the maximum Class 2 eye-safe luminous flux could be significantly lower when employing a bidirectional scan pattern than for the unidirectional case.

A stochastic flash analog-to-digital converter (ADC) is presented. A standard flash uses a resistor string to set individual comparator trip points. A stochastic flash ADC uses random comparator offset to set the trip points. Since the comparators are no longer sized for small offset, they can be shrunk down into digital cells. Using comparators that are implemented as digital cells produces a large variation of comparator offset. Typically, this is considered a disadvantage, but in our case, this large standard deviation of offset is used to set the input signal range. By designing an ADC that is made up entirely of digital cells, it is a natural candidate for a synthesizable ADC. Comparator trip points follow the nonlinear transfer function described by a Gaussian cumulative distribution function, and a technique is presented that reduces this nonlinearity by changing the overall transfer function of the stochastic flash ADC. A test chip is fabricated in 0.18- CMOS to demonstrate the concept.

Although cochlear implant patients are achieving increasingly higher levels of performance, speech perception in noise continues to be problematic. The newest generations of implant speech processors are equipped with preprocessing and/or external accessories that are purported to improve listening in noise. Most speech perception measures in the clinical setting, however, do not provide a close approximation to real-world listening environments. To assess speech perception for adult cochlear implant recipients in the presence of a realistic restaurant simulation generated by an eight-loudspeaker (R-SPACE) array in order to determine whether commercially available preprocessing strategies and/or external accessories yield improved sentence recognition in noise. Single-subject, repeated-measures design with two groups of participants: Advanced Bionics and Cochlear Corporation recipients. Thirty-four subjects, ranging in age from 18 to 90 yr (mean 54.5 yr), participated in this prospective study. Fourteen subjects were Advanced Bionics recipients, and 20 subjects were Cochlear Corporation recipients. Speech reception thresholds (SRTs) in semidiffuse restaurant noise originating from an eight-loudspeaker array were assessed with the subjects' preferred listening programs as well as with the addition of either Beam preprocessing (Cochlear Corporation) or the T-Mic accessory option (Advanced Bionics). In Experiment 1, adaptive SRTs with the Hearing in Noise Test sentences were obtained for all 34 subjects. For Cochlear Corporation recipients, SRTs were obtained with their preferred everyday listening program as well as with the addition of Focus preprocessing. For Advanced Bionics recipients, SRTs were obtained with the integrated behind-the-ear (BTE) mic as well as with the T-Mic. Statistical analysis using a repeated-measures analysis of variance (ANOVA) evaluated the effects of the preprocessing strategy or external accessory in reducing the SRT in noise. In addition, a standard t-test was run to evaluate effectiveness across manufacturer for improving the SRT in noise. In Experiment 2, 16 of the 20 Cochlear Corporation subjects were reassessed obtaining an SRT in noise using the manufacturer-suggested "Everyday," "Noise," and "Focus" preprocessing strategies. A repeated-measures ANOVA was employed to assess the effects of preprocessing. The primary findings were (i) both Noise and Focus preprocessing strategies (Cochlear Corporation) significantly improved the SRT in noise as compared to Everyday preprocessing, (ii) the T-Mic accessory option (Advanced Bionics) significantly improved the SRT as compared to the BTE mic, and (iii) Focus preprocessing and the T-Mic resulted in similar degrees of improvement that were not found to be significantly different from one another. Options available in current cochlear implant sound processors are able to significantly improve speech understanding in a realistic, semidiffuse noise with both Cochlear Corporation and Advanced Bionics systems. For Cochlear Corporation recipients, Focus preprocessing yields the best speech-recognition performance in a complex listening environment; however, it is recommended that Noise preprocessing be used as the new default for everyday listening environments to avoid the need for switching programs throughout the day. For Advanced Bionics recipients, the T-Mic offers significantly improved performance in noise and is recommended for everyday use in all listening environments.