Evaluation of surface analysis methods for characterization of trace metal surface contaminants found in silicon IC manufacturing

A major topic at recent silicon-based integrated circuit (IC) manufacturing symposia is the pursuit of decreased contamination levels. The aim is to remove contamination from both processes and materials. In conjunction with this effort, characterization methods are being pushed to lower and lower detection limits. In this paper, we evaluate surface analysis methods used to determine the concentration of inorganic contamination on unpatterned Si wafers. We compare sampling depths, detection limits, and applicability of each method for use in support of Si IC manufacturing. This comparison is further limited to Fe and Cu which are transition metal contaminants associated with manufacturing yield loss. The surface analysis methods included in this evaluation are: Total Reflection X-Ray Fluorescence (TXRF or TRXRF); Secondary Ion Mass Spectrometry (SIMS); two post-ionization'' methods Surface Analysis by Laser Ionization (SALI) and Sputter Initiated Resonant Ionization Spectroscopy (SIRIS); Heavy Ion Backscattering Spectroscopy (HIBS); and Vapor Phase Phase Decomposition (VPD) based methods Atomic Absorption (VPD-AA) along with VPD-TXRF. Sets of 6 in. Si wafers with concentration levels between 10{sup 9} atoms/cm{sup 2} and 10{sup 12} atoms/cm{sup 2} Fe and Cu were characterized by TXRF, SIMS, SIRIS, and HIBS. This data allows estimation of detection limits (DLs) and relative method accuracy. In Section 1 we describe each surface analysis method and the circumstance under which it would be used to support Si IC manufacturing. The equipment used for this comparison and the 150 mm Si wafer set are described in Section 2. Results from each method are contrasted in Section 3. Finally, a conclusion is presented in Section 4

Automated left ventricular diastolic function evaluation from phase-contrast cardiovascular magnetic resonance and comparison with Doppler echocardiography

International audienceBACKGROUND: Early detection of diastolic dysfunction is crucial for patients with incipient heart failure. Although this evaluation could be performed from phase-contrast (PC) cardiovascular magnetic resonance (CMR) data, its usefulness in clinical routine is not yet established, mainly because the interpretation of such data remains mostly based on manual post-processing. Accordingly, our goal was to develop a robust process to automatically estimate velocity and flow rate-related diastolic parameters from PC-CMR data and to test the consistency of these parameters against echocardiography as well as their ability to characterize left ventricular (LV) diastolic dysfunction. RESULTS: We studied 35 controls and 18 patients with severe aortic valve stenosis and preserved LV ejection fraction who had PC-CMR and Doppler echocardiography exams on the same day. PC-CMR mitral flow and myocardial velocity data were analyzed using custom software for semi-automated extraction of diastolic parameters. Inter-operator reproducibility of flow pattern segmentation and functional parameters was assessed on a sub-group of 30 subjects. The mean percentage of overlap between the transmitral flow segmentations performed by two independent operators was 99.7 ± 1.6%, resulting in a small variability ( 0.71) and receiver operating characteristic (ROC) analysis revealed their ability to separate patients from controls, with sensitivity > 0.80, specificity > 0.80 and accuracy > 0.85. Slight superiority in terms of correlation with echocardiography (r = 0.81) and accuracy to detect LV abnormalities (sensitivity > 0.83, specificity > 0.91 and accuracy > 0.89) was found for the PC-CMR flow-rate related parameters. CONCLUSIONS: A fast and reproducible technique for flow and myocardial PC-CMR data analysis was successfully used on controls and patients to extract consistent velocity-related diastolic parameters, as well as flow rate-related parameters. This technique provides a valuable addition to established CMR tools in the evaluation and the management of patients with diastolic dysfunction

Perspective: Optical measurement of feature dimensions and shapes by scatterometry

The use of optical scattering to measure feature shape and dimensions, scatterometry, is now routine during semiconductor manufacturing. Scatterometry iteratively improves an optical model structure using simulations that are compared to experimental data from an ellipsometer. These simulations are done using the rigorous coupled wave analysis for solving Maxwell’s equations. In this article, we describe the Mueller matrix spectroscopic ellipsometry based scatterometry. Next, the rigorous coupled wave analysis for Maxwell’s equations is presented. Following this, several example measurements are described as they apply to specific process steps in the fabrication of gate-all-around (GAA) transistor structures. First, simulations of measurement sensitivity for the inner spacer etch back step of horizontal GAA transistor processing are described. Next, the simulated metrology sensitivity for sacrificial (dummy) amorphous silicon etch back step of vertical GAA transistor processing is discussed. Finally, we present the application of plasmonically active test structures for improving the sensitivity of the measurement of metal linewidths