Correlation between pattern density and linewidth variation in silicon photonics waveguides

We describe the correlation between the measured width of silicon waveguides fabricated with 193 nm lithography and the local pattern density of the mask layout. In the fabrication process, pattern density can affect the composition of the plasma in a dry etching process or the abrasion rate in a planarization step. Using an optical test circuit to extract waveguide width and thickness, we sampled 5841 sites over a fabricated wafer. Using this detailed sampling, we could establish the correlation between the linewidth and average pattern density around the test circuit, as a function of the radius of influence. We find that the intra-die systematic width variation correlates most with the pattern density within a radius of 200 gm, with a correlation coefficient of 0.57. No correlation between pattern density and the intra-die systematic thickness variation is observed. These findings can be used to predict photonic circuit yield or to optimize the circuit layout to minimize the effect of local pattern density. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen

Gaussian process regression for virtual metrology of microchip quality and the resulting strategic sampling scheme

Manufacturing of integrated circuits involves many sequential processes, often ex- ecuted to nanoscale tolerances, and the yield depends on the often unmeasured quality of intermediate steps. In the high-throughput industry of fabricating microelectronics on semi-conducting wafers, scheduling measurements of product quality before the electrical test of the complete IC can be expensive. We therefore seek to predict metrics of product quality based on sensor readings describing the environment within the relevant tool during the processing of each wafer, or to apply the concept of virtual metrology (VM) to monitor these intermediate steps. We model the data using Gaussian process regression (GPR), adapted to simultaneously learn the nonlinear dynamics that govern the quality characteristic, as well as their operating space, expressed by a linear embedding of the sensor traces’ features. Such Bayesian models predict a distribution for the target metric, such as a critical dimension, so one may assess the model’s credibility through its predictive uncertainty. Assuming measurements of the quality characteristic of interest are budgeted, we seek to hasten convergence of the GPR model to a credible form through an active sampling scheme, whereby the predictive uncertainty informs which wafer’s quality to measure next. We evaluate this convergence when predicting and updating online, as if in a factory, using a large dataset for plasma-enhanced chemical vapor deposition (PECVD), with measured thicknesses for ~32,000 wafers. By approximately optimizing the information extracted from this seemingly repetitive data describing a tightly controlled process, GPR achieves ~10% greater accuracy on average than a baseline linear model based on partial least squares (PLS). In a derivative study, we seek to discern the degree of drift in the process over the several months the data spans. We express this drift by how unusual the relevant features, as embedded by the GPR model, appear as the in- puts compensate for degrading conditions. This method detects the onset of consistently unusual behavior that extends to a bimodal thickness fault, anticipating its flagging by as much as two days.Mechanical Engineerin

NASA Thesaurus Supplement: A three part cumulative supplement to the 1982 edition of the NASA Thesaurus (supplement 2)

The three part cumulative NASA Thesaurus Supplement to the 1982 edition of the NASA Thesaurus includes: part 1, hierarchical listing; part 2, access vocabulary, and part 3, deletions. The semiannual supplement gives complete hierarchies for new terms and includes new term indications for terms new to this supplement

Microelectronics Process Engineering at San Jose State University: A Manufacturing-Oriented Interdisciplinary Degree Program

San Jose State University\u27s new interdisciplinary curriculum in Microelectronics Process Engineering is described. This baccalaureate program emphasizes hands-on thin-film fabrication experience, manufacturing methods such as statistical process control, and fundamentals of materials science and semiconductor device physics. Each course of the core laboratory sequence integrates fabrication knowledge with process engineering and manufacturing methods. The curriculum development process relies on clearly defined and detailed program and course learning objectives. We also briefly discuss our strategy of making process engineering experiences accessible for all engineering students through both Lab Module and Statistics Module series

Yield Enhancement of Digital Microfluidics-Based Biochips Using Space Redundancy and Local Reconfiguration

As microfluidics-based biochips become more complex, manufacturing yield will have significant influence on production volume and product cost. We propose an interstitial redundancy approach to enhance the yield of biochips that are based on droplet-based microfluidics. In this design method, spare cells are placed in the interstitial sites within the microfluidic array, and they replace neighboring faulty cells via local reconfiguration. The proposed design method is evaluated using a set of concurrent real-life bioassays.Comment: Submitted on behalf of EDAA (http://www.edaa.com/

Thermosonic flip chip interconnection using electroplated copper column arrays

Published versio

NASA Thesaurus Supplement: A three part cumulative supplement to the 1982 edition of the NASA Thesaurus (supplement 3)

The three part cumulative NASA Thesaurus Supplement to the 1982 edition of the NASA Thesaurus includes Part 1, Hierarchical Listing, Part 2, Access Vocabulary, and Part 3, Deletions. The semiannual supplement gives complete hierarchies for new terms and includes new term indications for entries new to this supplement