Eintrag in der Universitätsbibliographie der TU Chemnitz
Sayyed, Mudassir Ali ; Seifert, Tom ; Zieger, Stephan ; Schwarzenberg, Simeon ; Deshmukh, Aditya ; Haase, Micha ; Langer, Jan
A Multi-Model Dataset for BOSCH Plasma-Etching: Optical Emission Spectra, Process Parameters, and Wafer Measurements for Data-Driven Plasma Modeling
| Universität: | Technische Universität Chemnitz | |
| Institut 1: | Professur Smart Systems Integration | |
| Institut 2: | Zentrum für Mikrotechnologien (ZfM) | |
| Dokumentart: | Artikel in Fachzeitschrift, referiert | |
| DOI: | doi:10.5281/zenodo.17122442 | |
| URL/URN: | https://zenodo.org/records/17122442 | |
| Quelle: | In: This dataset provides a comprehensive collection of process and measurement data from BOSCH plasma etching experiments conducted at the Center for Microtechnologies (ZFM), Chemnitz, Germany. The experiments were designed to investigate the influence of conditioning on chamber states and process outcomes. While the effect of different conditioning steps (O? plasma, O?/SF? plasma, repeated once, three times, or nine times on chuck, Si, and SiO? wafers) remained inconclusive, the resulting dataset is uniquely rich and valuable for data-driven modeling.The dataset includes three major components:Optical Emission Spectroscopy (OES): High-resolution plasma spectra recorded in situ (185?884 nm, 3648 channels, 25 Hz).Process Parameters: 31 machine parameters recorded at 5 Hz.Wafer Measurements: Pre- and post-etch oxide thickness and step heights measured at 9 and 89 spatial points, enabling characterization of etch depth, selectivity, and post-etch uniformity.Data is stored in NetCDF format with shared dictionaries for efficient compression and easy decoding. Additional CSV files provide wafer-level measurement results, while documentation and example Python scripts demonstrate how to access and process the data.This dataset is intended as a resource for both machine learning engineers and process experts. It enables studies of plasma cycle structures, development of predictive models for etch depth and uniformity, and exploration of data-driven approaches to etch process control.. - Zenodo. 2025 | |
| Freie Schlagwörter (Englisch): | Plasma-Etching , Data-Driven Plasma Modeling | |
Bemerkung: |
Dataset |
|
| OA-Lizenz | CC BY 4.0 |
