Predictive Structure to Thermal Conductivity Modeling Framework for BEOL Interconnect Stacks in Advanced Technology Nodes Enabled by Extensive Layer Resolved Thermal Measurements
Abstract
The increasing structural complexity of BEOL interconnect stacks in advanced integrated circuits demands a structure-aware thermal conductivity (\k{appa}) modeling framework. However, generalizable models derived from layer-resolved thermal measurements that quantitatively capture the dependence of \k{appa} on interconnect structures remain lacking, limiting predictive thermal analysis. Here, we establish an experimentally derived, structure-aware \k{appa} modeling framework enabled by time-domain thermoreflectance measurements with ~100 nm depth resolution. Statistical analysis of a compiled dataset comprising over 40 experimentally measured layer-resolved \k{appa} values across diverse BEOL layers reveals a generalizable empirical structure-to-\k{appa} relationship, enabling predictive modeling based on interconnect structure. An intra-layer three-dimensional \k{appa} distribution model based on effective medium theory and realistic layouts further resolves spatial \k{appa} variations within practical interconnect layers. Together, these models establish an experimentally derived, structure-aware \k{appa} modeling framework for predictive and generalizable thermal analysis of advanced interconnect stacks and 3D ICs.
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BibTeX
@misc{huang2026predictive,
title = {{Predictive Structure to Thermal Conductivity Modeling Framework for BEOL Interconnect Stacks in Advanced Technology Nodes Enabled by Extensive Layer Resolved Thermal Measurements}},
author = {Zifeng Huang and Yiyang Sun and Tianyu Jia and Runsheng Wang and Zhe Cheng},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.20379},
eprint = {2609.20379},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.20379},
}
RIS
TY - UNPB
TI - Predictive Structure to Thermal Conductivity Modeling Framework for BEOL Interconnect Stacks in Advanced Technology Nodes Enabled by Extensive Layer Resolved Thermal Measurements
AU - Zifeng Huang
AU - Yiyang Sun
AU - Tianyu Jia
AU - Runsheng Wang
AU - Zhe Cheng
PY - 2026
DA - 2026/09/17
PB - arXiv
DO - 10.48550/arxiv.2609.20379
UR - https://arxiv.org/abs/2609.20379
AB - The increasing structural complexity of BEOL interconnect stacks in advanced integrated circuits demands a structure-aware thermal conductivity (\k{appa}) modeling framework. However, generalizable models derived from layer-resolved thermal measurements that quantitatively capture the dependence of \k{appa} on interconnect structures remain lacking, limiting predictive thermal analysis. Here, we establish an experimentally derived, structure-aware \k{appa} modeling framework enabled by time-domain thermoreflectance measurements with ~100 nm depth resolution. Statistical analysis of a compiled dataset comprising over 40 experimentally measured layer-resolved \k{appa} values across diverse BEOL layers reveals a generalizable empirical structure-to-\k{appa} relationship, enabling predictive modeling based on interconnect structure. An intra-layer three-dimensional \k{appa} distribution model based on effective medium theory and realistic layouts further resolves spatial \k{appa} variations within practical interconnect layers. Together, these models establish an experimentally derived, structure-aware \k{appa} modeling framework for predictive and generalizable thermal analysis of advanced interconnect stacks and 3D ICs.
ER -