3D IC and TSV technologies

Neueste Paper

• DeepOHeat-v2: Self-Improving Operator Learning for Fast and Trustworthy Thermal Optimization in 3D-IC Design

  Xinling Yu, Yixing Li, Ziyue Liu, Xin Ai, Zhiyu Zeng, Hai Li, Zheng Zhang · 18. August 2026

  Thermal-aware optimization of multi-die 3D integrated circuits evaluates many designs, each a costly heat-equation solve. Operator-learning surrogates replace this solve with a fast forward pass, ideally trained from physics alone, without labeled data. DeepOHeat-v1 made such surrogates fast and tru…

• Self-Attention to Operator Learning-based 3D-IC Thermal Simulation

  Zhen Huang, Hong Wang, Wenkai Yang, Muxi Tang, Depeng Xie, Ting-Jung Lin, Yu Zhang, Wei W. Xing, Lei He · 11. August 2026

  Thermal management in 3D ICs is increasingly challenging due to higher power densities. Traditional PDE-solving-based methods, while accurate, are too slow for iterative design. Machine learning approaches like FNO provide faster alternatives but suffer from high-frequency information loss and high-…

• FocusGS: Spatial Delta Layers for Local Repair and Deterministic Editing of Trained 3D Gaussian Assets

  Yiqun Pan, Yukun Shi · 3. August 2026

  3D Gaussian Splatting (3DGS) is evolving from one-time reconstruction into deliverable, inspectable, and maintainable visual assets. Existing workflows focus on global reconstruction, training-time density control, or open-ended generative editing, leaving trained assets without precise local mainte…

• From Physics to Surrogate Intelligence: A Unified Electro-Thermo-Optimization Framework for TSV Networks

  Mohamed Gharib, Leonid Popryho, Inna Partin-Vaisband · 28. Juli 2026

  High-density through-substrate vias (TSVs) enable 2.5D/3D heterogeneous integration but introduce significant signal-integrity and thermal-reliability challenges due to electrical coupling, insertion loss, and self-heating. Conventional full-wave finite-element method (FEM) simulations provide high …

• Virtual Sensing for Solder Layer Degradation and Temperature Monitoring in IGBT Modules

  Andrea Urgolo, Monika Stipsitz, H\`elios Sanchis-Alepuz · 23. März 2026

  Monitoring the degradation state of Insulated Gate Bipolar Transistor (IGBT) modules is essential for ensuring the reliability and longevity of power electronic systems, especially in safety-critical and high-performance applications. However, direct measurement of key degradation indicators - such …

• WarPGNN: A Parametric Thermal Warpage Analysis Framework with Physics-aware Graph Neural Network

  Haotian Lu, Jincong Lu, Sachin Sachdeva, Sheldon X. -D. Tan · 20. März 2026

  With the advent of system-in-package (SiP) chiplet-based design and heterogeneous 2.5D/3D integration, thermal-induced warpage has become a critical reliability concern. While conventional numerical approaches can deliver highly accurate results, they often incur prohib- itively high computational c…

• Deep Clustering based Boundary-Decoder Net for Inter and Intra Layer Stress Prediction of Heterogeneous Integrated IC Chip

  Kart Leong Lim, Ji Lin · 26. Februar 2026

  High stress occurs when 3D heterogeneous IC packages are subjected to thermal cycling at extreme temperatures. Stress mainly occurs at the interface between different materials. We investigate stress image using latent space representation which is based on using deep generative model (DGM). However…