Kazimierz Wikiel

Multi-way standardization of an AC voltammetric analyzer for electrometallization baths

Two standardization techniques were implemented for transferring three multi-way calibration models for determining of the suppressor concentration in industrial copper electrometallization baths used in semiconductor manufacturing. Parallel Factor analysis (PARAFAC) for multi-way array decomposition coupled with Inverse Least Squares (ILS) (PARAFAC/ILS) regression, Direct Trilinear Decomposition (DTLD) coupled with ILS (DTLD/ILS), and Multi-linear Partial Least Squares (N-PLS) regressions were employed to develop and test calibration models based on trilinear Alternating Current (AC) voltammetric data. The calibration transfer was performed by Direct Standardization (DS) and Reverse Standardization (RS) on the voltammetric data. The pairwise performance of standardization techniques and decomposition/regression techniques was studied comparatively in order to assess reliability and robustness of analytical model transfer.

Copper ECD Process of ULSI Circuits Controlled by Electroanalysis Combined with Multi-way Chemometrics. Transfer of the PARAFAC/ILS Calibration

Since the emergence of electrochemically deposited (ECD) copper for damascene processing in the late 1990’s, reductions in the sizes of trenches and vias in ultra large scale integrated (ULSI) circuits have been placing increasingly stringent demands on plating bath control in order to satisfy strict chip manufacturing standards. The quality of the final product of the ECD process is determined by parameters like uniformity of deposit thickness across the wafer surface, appropriate mechanical properties, and super-filling characteristics in sub-100 nm features. These requirements can be met by employing multicomponent plating solutions, whose composition is based on sulfuric acid / copper sulfate aqueous solutions containing chloride ion and three organic additives known as accelerator, suppressor, and leveler.

Online Monitoring of Copper Damascene Electroplating Bath by Voltammetry: Selection of Variables for Multiblock and Hierarchical Chemometric Analysis of Voltammetric Data

The Real Time Analyzer (RTA) utilizing DC- and AC-voltammetric techniques is an in situ, online monitoring system that provides a complete chemical analysis of different electrochemical deposition solutions. The RTA employs multivariate calibration when predicting concentration parameters from a multivariate data set. Although the hierarchical and multiblock Principal Component Regression- (PCR-) and Partial Least Squares- (PLS-) based methods can handle data sets even when the number of variables significantly exceeds the number of samples, it can be advantageous to reduce the number of variables to obtain improvement of the model predictions and better interpretation. This presentation focuses on the introduction of a multistep, rigorous method of data-selection-based Least Squares Regression, Simple Modeling of Class Analogy modeling power, and, as a novel application in electroanalysis, Uninformative Variable Elimination by PLS and by PCR, Variable Importance in the Projection coupled with PLS, Interval PLS, Interval PCR, and Moving Window PLS. Selection criteria of the optimum decomposition technique for the specific data are also demonstrated. The chief goal of this paper is to introduce to the community of electroanalytical chemists numerous variable selection methods which are well established in spectroscopy and can be successfully applied to voltammetric data analysis.