MIV void defect model - Ansys simulation dataset

All models are built using three‑dimensional parametric geometric modeling, where key physical dimensions of the MIV (such as via diameter, height, and dielectric layer thickness) are defined as parameter variables. Users can directly open the model files in Ansys Q3D Extractor or HFSS, adjust the parameters, and run simulations to rapidly obtain parasitic parameter results for different dimensional configurations.The Python codes section includes a series of scripts for rapid computation based on the MIV analytical model described in the associated paper.

Given the geometric dimensions of the MIV, these codes can quickly calculate the RLGC parasitic parameters. All Python codes are provided as .py files, with NumPy as the primary scientific computing dependency.The model simulation data section constitutes the main data content of the dataset and originates from three sources: (1) parasitic parameter data obtained by simulating MIVs with varying physical dimensions using Ansys Q3D Extractor; (2) parasitic parameter data from simulations of MIVs with void defects of different physical sizes, where the void geometry (e.g. position and diameter) is controlled as independent variables in the simulation models; and (3) corresponding analytical results computed by the Python codes based on the equivalent‑circuit model.

The simulation data are stored in tabular format (.csv or .xlsx), with each record corresponding to a specific combination of MIV geometric parameters or defect dimensions along with its simulation/calculation results.The full research paper part contains the complete text of the research paper corresponding to this dataset.The image processing part includes the software project files used for image processing, intermediate files generated during processing, and all original images used in the paper.All simulation data have undergone adaptive mesh convergence verification using the built‑in functionality of Ansys software, ensuring that the mesh density achieves sufficient computational accuracy.

Comparative verification between the parasitic parameters extracted by Q3D and the full‑wave simulation results from HFSS shows good agreement over a wide frequency range. The errors introduced in the simulations mainly arise from modeling approximations due to geometric simplification and deviations between the assigned material parameters (e.g., silicon substrate conductivity, dielectric permittivity) and actual values.

These errors are within acceptable limits and do not compromise the scientific validity of the data or the reliability of the conclusions.