Yield analysis for repairable embedded memories

A built-in self-repair (BISR) scheme for random access memories (RAMs) with 2-D redundancy has a built-in redundancy analyzer (BIRA) for allocating the redundancy. The BIRA typically has a cache-like element called local bitmap for storing the fault information temporary. In this paper, a high-repair-efficiency BISR (HRE-BISR) scheme for RAMs is proposed. The HRE-BISR reuses the local bitmap to serve as spare bits such that it can repair more faults. In addition, a row/column/bit redundancy analysis (RCB-RA) algorithm for a RAM with spare rows, spare columns, and spare bits is presented. Simulation results show that the proposed HRE-BISR scheme can provide higher repair rate (RR) than a typical BISR scheme without reusing the local bitmap as spare bits. Only about 0.44% additional hardware overhead is needed to modify the local bitmap as spare bits. In addition, the HRE-BISR scheme using $3\times 3$ -bit local bitmap for RA only incurs about 0.08-ns delay penalty for a $512\times 16\times 32$ -bit RAM with one spare row and one spare column. However, the HRE-BIRA scheme with RCB-RA algorithm can provide 0.48%–11.95% increment of RR for different fault distributions.

Built-in self-repair (BISR) techniques are widely used for repairing embedded random access memories (RAMs). One key component of a BISR module is the built-in redundancy-analysis (BIRA) design. This paper presents an effective BIRA scheme which executes the 2-D redundancy allocation based on a 1-D local bitmap. Two BIRA algorithms for supporting two different redundancy organizations are also proposed. Simulation results show that the proposed BIRA scheme can provide high repair rate (i.e., the ratio of the number of repaired memories to the number of defective memories) for the RAMs with different fault distributions. Experimental results show that the hardware overhead of the BIRA design is only about 2.9% for an 8192 × 64-bit RAM with two spare rows and two spare columns. Also, the ratio of the BIRA analysis time to the test time is only about 0.02% if the March-CW test is performed. Furthermore, a simulation flow is proposed to determine the size of the 1-D local bitmap such that the BIRA algorithm can provide the best repair rate using the smallest-size 1-D local bitmap.

Defect density and defect size distributions (DDSDs) are key parameters used in IC yield loss predictions. Traditionally, memories and specialized test structures have been used to estimate these distributions. In this paper, we propose a strategy to accurately estimate DDSDs for shorts in metal layers using production IC test results.

The experimental determination of defect density distributions is described. These distributions are needed for calculating LSI yields. The defect densities appear to be distributed according to gamma distributions. An expression for the average yield for a semiconductor process is derived based on the results.

In this work we study the impact of ion implantation on the nonlinear optical properties in MgO:LiNbO3 via confocal second-harmonic microscopy. In detail, we spatially characterize the nonlinear susceptibility in carbon-ion implanted lithium niobate planar waveguides for different implantation energies and fluences, as well as the effect of annealing. In a further step, a computational simulation is used to calculate the implantation range of carbon-ions and the corresponding defect density distribution. A comparison between the simulation and the experimental data indicates that the depth profile of the second-order effective nonlinear coefficient is directly connected to the defect density that is induced by the ion irradiation. Furthermore it can be demonstrated that the annealing treatment partially recovers the second-order optical susceptibility.

Defect creation in InGaAs/GaAs multiple quantum wells–I. Structural properties

Memory built in self repair (BISR) is gaining importance since several years. Because defect densities are increasing with submicron scaling, more advanced solutions may be required for memories to be produced with the upcoming nanometric CMOS process generations. This problem will be exacerbated with nanotechnologies, where defect densities are predicted to reach levels that are several orders of magnitude higher than in current CMOS technologies. For such defect densities, traditional memory repair is not adequate. This work presents a diversified repair approach merging ECC codes and self-repair, for repairing memories affected by high defect densities. The approach was validated by means of statistical fault injection simulations considering defect densities as high as 3*10/sup -2/% (3% of cells are defective). The obtained results show that the approach provides close to 100% memory yield, by means of reasonable hardware cost, for technologies of very poor quality. Thus, the extreme defect densities that many authors predict for nanotechnologies do not represent a show-stopper, at least as concerning memories.

The annihilation process of pointlike topological defects moving irreversibly is studied as a model for the growth of order in quenched systems with O(N) symmetry in D=N dimensions. On the basis of the time-dependent Ginzburg-Landau model (TDGL), the defect picture is shown to be valid in any dimensions. We consider defects with pairwise power-type interaction. By a mean-field assumption we find that the total number N(t) of defects decreases as N(t)\ensuremath{\propto}${\mathit{t}}^{\mathrm{\ensuremath{-}}\mathit{D}/(\mathrm{\ensuremath{\beta}}+1)}$, where \ensuremath{\beta} is the exponent indicating the separation dependence of the force. We show analytically that this power law is valid for \ensuremath{\beta}D\ensuremath{\le}2\ensuremath{\beta} and confirm the analysis by the simulation of molecular dynamics of defects for various \ensuremath{\beta}'s in two dimensions. The distribution of defect density is well represented by the binomial distribution function in this parameter region. To keep the distribution uniform is a key of exhibiting mean-field behavior. The TDGL model realizes the mean-field power law only in two dimensions.

An integrated memory test system is presented. It includes a reconfigurable memory test module, a test algorithm editor, a memory fault simulator, and a test code generator. For a given memory organization, fault list, and test algorithm, the system automatically reports the fault coverage, generates control assembly codes, and produces circuit net list for test pattern generation. The system has been implemented in 9000 lines of C++ program based on the Microsoft Windows graphic user interface. It has been verified on different test algorithms and memory chips.

This paper uses a new mechanical model (FaultProp) to study fault nucleation and propagation in mechanically layered sequences. Field mapping of two outcrops in Sinai and Utah show complex fault patterns formed when a horizontal extensional strain is applied to interbedded strata with contrasting mechanical properties: closely spaced low throw layer-bound faults form in certain layers, but the outcrops also contain several larger faults cutting through the entire section. Mechanical modelling with FaultProp shows that the key factors controlling the distribution and density of layer-bound and through-cutting faults are the contrast in friction coefficient and ductility between the layers. If these results can be upscaled then it is hoped that this modelling approach will be able to predict complexity in larger scale fault zones in the subsurface.

This work provides a comprehensive investigation of nitrogen and aluminum doping and its consequences for the physical properties of 3C-SiC. Free-standing 3C-SiC heteroepitaxial layers, intentionally doped with nitrogen or aluminum, were grown on Si (100) substrate with different 4° off-axis in a horizontal hot-wall chemical vapor deposition (CVD) reactor. The Si substrate was melted inside the CVD chamber, followed by the growth process. Micro-Raman, photoluminescence (PL) and stacking fault evaluation through molten KOH etching were performed on different doped samples. Then, the role of the doping and of the cut angle on the quality, density and length distribution of the stacking faults was studied, in order to estimate the influence of N and Al incorporation on the morphological and optical properties of the material. In particular, for both types of doping, it was observed that as the dopant concentration increased, the average length of the stacking faults (SFs) increased and their density decreased.

The Vanadium Redox Flow Battery (VRFB) is a promising candidate for large scale energy storage. These systems are expected to operate for long cycle life ~ 10 years of lifetime (~ 500 - 2000 charge – discharge cycles).1 The VRFB’s system includes an posolyte (VO2 +/VO2+) and negolyte (V2+/V3+) compartments with carbon electrodes, and uses acidic electrolytes (usually 3M H2SO4). The carbon electrodes in VRFB need to perform in a harsh and corrosive environment associated with the charge/discharge cycling. In this study, we used polyacrylonitrile (PAN) based carbon papers as model carbon electrodes to study changes in the electrodes during cycling operation. The carbon papers were pre-treated according to the conventional approach by heating them in air at 500 ⁰C to incorporate oxygen functional groups on their surfaces.2,3 These pre-treated electrodes were then used in flow battery for 100-cycles at a current density of 80 mA/cm2. At the single cell level, the performance of these electrodes following the operation indicated a slight decrease in voltage efficiency (from 60 % to 52 %). This decrease in performance may be attributed to the electrode degradation during operation. Characterization of the electrode prior and following 100-cycles was performed using Raman spectroscopy, XPS analysis as well as electrochemical studies. Raman analysis showed differences between the fresh and the degraded carbon electrodes, including increasing defect and electronic density distribution. XPS analysis of the degraded electrodes suggest an alteration in the amount of oxygen functional groups. Electrochemical studies showed an decrease in the electron transfer kinetics after degradation, coupled with noticeable difference between the electrodes exposed to the posolyte (VO2 +/VO2+) and negolyte (V2+/V3+). The results provide insight into the stability of the oxygen functional groups during cycling operation which could assist in developing pre-treatment methods to functionalize the VRFB’s electrodes and for other similar electrochemical systems.

Defect prediction has been an active research area for over four decades. Despite numerous studies on defect prediction, the potential value of defect prediction in practice remains unclear. To address this issue, we performed a mixed qualitative and quantitative study to investigate what practitioners think, behave and expect in contrast to research findings when it comes to defect prediction. We collected hypotheses from open-ended interviews and a literature review of defect prediction papers that were published at ICSE, ESEC/FSE, ASE, TSE and TOSEM in the last 6 years (2012-2017). We then conducted a validation survey where the hypotheses became statements or options of our survey questions. We received 395 responses from practitioners from over 33 countries across five continents. Some of our key findings include: 1) Over 90 percent of respondents are willing to adopt defect prediction techniques. 2) There exists a disconnect between practitioners’ perceptions and well supported research evidence regarding defect density distribution and the relationship between file size and defectiveness. 3) 7.2 percent of the respondents reveal an inconsistency between their behavior and perception regarding defect prediction. 4) Defect prediction at the feature level is the most preferred level of granularity by practitioners. 5) During bug fixing, more than 40 percent of the respondents acknowledged that they would make a “work-around” fix rather than correct the actual error-causing code. Through a qualitative analysis of free-form text responses, we identified reasons why practitioners are reluctant to adopt defect prediction tools. We also noted features that practitioners expect defect prediction tools to deliver. Based on our findings, we highlight future research directions and provide recommendations for practitioners.

Sex and age structured matrix model applied to harvesting a white tailed deer population

A simple 1D transfer matrix model of a battery is introduced and parametrized using harvested individual cell components at 0 % and 100 % SoC. This model allows for the calculation of group velocity and attenuation. The results of the model show good agreement with measured values, highlighting increased attenuation and group velocity at the resonances. This emphasizes the importance of selecting a suitable interrogation frequency for ultrasound investigations in lithium‐ion batteries. The model accurately replicates the observed weakening of resonances with increasing SoC. Additionally, it provides the basis to fit US spectroscopy data in the future, enabling immediate determination of component thickness and the Young's modulus of individual components, along with aiding in the identification aging effects of the anode and cathode materials. The model can visualize wave propagation within the battery. At certain frequencies, standing waves form which could be used in high‐intensity ultrasound applications targeted at individual cell components.