Application of statistical analysis methods on ToF-SIMS data of native and degraded polymers

Abstract

The widespread use of polymer coatings as passivation layers in the semiconductor industry has led to growing interest in understanding material and surface changes in technologically relevant polymers. One critical aspect in this context is the migration of ions and water through the polymer matrix, which can significantly compromise the long-term performance and reliability of semiconductor components, due to corrosion and other failure modes. As such, accurately tracking the progression of degradation within polymer layers is essential for evaluating their suitability in advanced electronic applications.To gain insight into near-surface changes and monitor degradation profiles with high depth resolution, Time of Flight Secondary Ion Mass Spectrometry (ToF-SIMS) was employed. While ToF-SIMS is not traditionally used for polymer analysis, its ability to provide high depth resolution and surface sensitivity makes it a promising technique for this purpose. However, the method yields large volumes of complex spectral data, as Tof-SIMS records a full mass spectrum over a defined mass range for each pixel, repeated for every layer in a depth profile. This necessitates the use of chemometric tools for efficient and meaningful interpretation. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were utilized to reduce dimensionality and identify key patterns in the data based on simple spectral descriptors.Initial studies demonstrated that common polymers could be successfully differentiated using ToF-SIMS in combination with chemometric analysis. These findings were further validated and extended by investigating the degradation behavior of high-performance polyimide (PI) and poly(p-phenylene-2,6-benzobisoxazole) (PBO) films deposited on silicon wafers. Accelerated aging was achieved through controlled ultraviolet (UV) radiation exposure, creating a simplified model system for studying near-surface degradation. Subsequent depth profile analysis revealed qualitative differences in the aged samples, including estimation of UV penetration depth when comparing near-surface to bulk level signal.The methodology developed in this work lays the groundwork for broader applications. In future experiments, more complex and industrially relevant degradation processes, such as water exposure, plasma treatment, and environmental aging, will be explored. The combination of ToF-SIMS and multivariate data analysis presents a robust framework for uncovering degradation mechanisms in polymer films, ultimately contributing to the development of more durable and reliable materials for microelectronic devices.