As AI, HPC, and power electronics continue to push thermal design limits, thermal interface materials (TIMs) are increasingly required to accommodate surface non-coplanarity while maintaining low thermal resistance under limited assembly pressure. Compressible metal TIMs offer a unique combination of high thermal conductivity and mechanical compliance, making them attractive for next-generation cooling applications.

This study investigates the effects of installation time, applied pressure, material thickness, and pattern geometry on the thermal performance of compressible indium-based metal TIMs. Thermal resistance measurements were conducted using ASTM D5470 methodology at elevated temperature under pressures ranging from 20–50 psi. Multiple TIM thicknesses and surface patterns were evaluated over a 72-hour test duration to characterize the evolution of bond line thickness and effective thermal resistance.

Results show that installation time and applied pressure have the most significant impact on thermal performance due to continued plastic deformation and reduction of interfacial resistance. While TIM thickness influences bulk thermal resistance, its overall effect is moderated by the high thermal conductivity of indium. Pattern geometry plays a critical role during initial installation by concentrating local pressure and improving surface conformity, particularly in applications with non-coplanar mating surfaces.

The findings provide practical design guidelines for selecting compressible metal TIM configurations and assembly conditions to optimize thermal performance and long-term reliability in AI accelerators, data center hardware, and power electronic systems.

随着人工智能（AI）、高性能计算（HPC）及功率电子技术持续推动，系统功率密度不断提升，散热设计面临越来越严苛的挑战。热界面材料（Thermal Interface Materials, TIM）除了能适应界面的非共面（Non-Coplanarity）特性，还需要在有限的装配压力下维持低热阻，保证稳定且高效的导热性能。可压缩金属 TIM 兼具高导热率与优异的机械适配性，已成为下一代高效散热解决方案的重要发展方向。

本研究探讨了安装时间、施加压力、材料厚度及图案结构（Pattern Geometry）对可压缩金属铟基 TIM 导热性能的影响。热阻测试采用 ASTM D5470 标准方法，在高温条件且在 20–50 psi 压力范围内进行评估。研究涵盖多种 TIM 厚度及图案设计，持续测试 72 小时，以表征结合层厚度（Bond Line Thickness, BLT）和有效热阻随时间的变化规律。

研究结果表明，安装时间与施加压力对热性能影响最为显著。这主要归因于材料持续发生塑性变形（Plastic Deformation），使界面接触更加充分，从而降低界面热阻。虽然 TIM 材料厚度会影响其自身热阻，但由于铟具有极高的导热率，其整体影响相对有限。图案设计则在初始装配阶段发挥关键作用，可提高局部接触压力并增强表面贴合能力，特别适用于非共面的应用场景。

本研究结果为可压缩型金属 TIM 的材料和图案选型，以及装配方式选择提供了非常实用的设计指南，以此来提升 AI 加速器、数据中心硬件及功率电子系统中的散热性能与长期可靠性。

Topic: AI-assisted_Protocol_Analysis_Solution

With the increasing design complexity of advanced integrated circuits, chip testing has become quite complex. More than 90% of test items require the specified protocol set to enter a predefined operating mode before measurement execution. This process is achieved by configuring registers through a chip protocol such as I2C, JTAG, or SPI. In complex test scenarios, a single ATE test program may include tons of register initialization and dynamic configuration operations. In addition, register configuration processes and subsequent measurement operations often interleave, and the accuracy of test results depends on the precise timing window after the target register state configuration is completed.

There are several challenges listed below that will be experienced:

1. Verification of register configuration mostly depends on manual inspection during program development and debugging.
2. Engineers must pick out the specified cycle ranges which need to insert measurement actions from amounts of configuration cycles in register configuration sequences.
3. Modification and validation of register configurations typically depend on a lot of manual work like parsing and trial-and-error debugging.

To resolve these problems, this paper released an AI-assisted SMT8 protocol-based pattern parsing and optimization method. Chapter 1 provides a detailed overview of the background and current state of ATE test, and Chapter 2 describes the core functions of the method. The method performs protocol-level decoding of DFT raw test vectors to automatically extract register address mappings, configuration data, and execution cycle information. Furthermore, a local AI-driven data analysis module is introduced to analyze and interpret the test plan contents and automatically compare parsed register configuration behavior with the test plan specifications.

This framework focuses on the following key technical challenges:

1. Abstraction of waveform information in raw test vectors.
2. versatile protocol Compatibility.
3. Accurate localization of cycle ranges for register configuration segments.
4. Local AI model preset tuning and verification skill definition.

The method consists of waveform reconstruction, protocol action serialization, protocol rule matching, test data processing, and AI analysis.

Experimental results demonstrate that the method significantly improves register configuration readability and debugging efficiency in ATE-based chip testing workflows. Compared with conventional manual analysis approaches:

1. The time spent on register configuration consistency verification is reduced from 18 hours per project to 2 hours per project (almost 88% save).
2. The time spent on register configuration modification during debugging is reduced from 10 hours per project to 4 hours per project (reduce 60% time cost).
3. The overall test program development and debugging cycle is reduced by approximately 30% on average.
4. The program error rate is reduced by 70%.

By combining automatic protocol-level decoding of raw test vectors with local AI analysis modules, the method effectively solves the register configuration problem in complex ATE testing, achieving significant improvements in both efficiency and accuracy.

主题：基于 SMT8 协议解析与本地 AI 分析的 ATE 寄存器配置自动验证与优化方法

随着先进集成电路设计复杂度的不断提升，芯片测试也变得日益复杂。超过90%的测试项目要求在执行测量前，通过指定的协议集使系统进入预定义的工作模式。这一过程通常通过 I2C、JTAG 或 SPI 等芯片协议对寄存器进行配置来实现。在复杂的测试场景中，单个 ATE 测试程序可能包含大量寄存器初始化和动态配置操作。此外，寄存器配置过程与后续的测量操作往往交错进行，测试结果的准确性取决于目标寄存器状态配置完成后的精确时序窗口。

这会出现如下这些挑战：

1. 寄存器配置正确性验证主要依赖于程序开发和调试期间的手动检查。
2. 工程师必须在大量寄存器序列配置中，筛选出需要插入测量操作的指定时间节点。
3. 寄存器配置的修改和验证通常依赖于大量手动工作。

为解决这些问题，提出了基于 SMT8 协议解析与本地 AI 分析的 ATE 寄存器配置自动验证与优化方法。本文结构如下：第1章详细概述了 ATE 测试的背景及现状，第2章描述了该方法的核心功能，包括对 DFT 原始测试向量进行协议级解码，自动提取寄存器地址映射、配置数据和执行周期信息。除此之外，还引入了一个基于本地 AI 的数据分析模块，用于分析 Test Plan 内容，最后将原始测试向量解析出的寄存器配置与 AI 从 Test Plan 提取的寄存器配置规范进行比对，并生成结果报告。

该框架重点解决了以下关键技术挑战：

1. 原始测试向量中波形信息的抽象化。
2. 通用的协议兼容性。
3. 寄存器配置段时钟周期的精确定位。
4. 本地 AI 模型预设的调优及验证。

实验结果表明，该方法显著提高了基于 ATE 的芯片测试工作流中寄存器配置的可读性和调试效率。与传统的手动分析方法相比：

1. 用于寄存器配置一致性验证的时间从每个项目 18 小时减少到每个项目 2 小时（节省近 88%）。
2. 调试过程中用于修改寄存器配置的时间从每个项目 10 小时减少到 4 小时（时间成本降低 60%）。
3. 测试程序的整体开发和调试周期平均缩短了约 30%。
4. 程序错误率降低了 70%。

通过将原始测试向量的协议级自动解码与本地 AI 分析模块相结合，该方法有效解决了复杂 ATE 测试中的寄存器配置问题，在效率和准确性方面均实现了显著提升。

Fiber weave effect (FWE) on PCBs induces PN skew within differential pairs, which triggers severe insertion loss resonance in high-speed applications such as 112Gbps PAM4 systems. This paper verifies that PN skew acts as the root cause and proposes an innovative compensation scheme.

By coating high-dielectric-constant (high-Dk) solder mask on the faster transmission line, the propagation delays of differential traces are well balanced. Experimental results demonstrate that the proposed method eliminates resonance and reduces PN skew from -36 ps to below 10 ps.

This technique provides a simple and low-cost solution for skew mitigation.

With 14 years of SIPI simulation experience, I have conducted SIPI simulations for mobile phone SoC chips, CPU chips, ADCs and DACs, as well as simulations of 800G and 1.6T optical modules. Currently, I am engaged in SIPI simulation of FT boards at Pi Semiconductor.

PCB 上的玻纤效应（FWE）会在差分对中引起 PN 时延差（PN Skew），从而在 112Gbps PAM4 等高速场景下导致严重的插损谐振。本文确定了 PN 时延差是根本原因，并提出了一种新颖的补偿方法。

通过在速度较快的传输线上涂覆高介电常数的绿油，我们有效地平衡了传输时延。实验结果表明，该方法能消除谐振，并将 PN 时延差 从 -36 皮秒 降低至 10 皮秒以下。

这是一种简单、低成本降低延时差的解决方案。

14年SIPI仿真经验，先后从事手机SOC芯片、CPU芯片、ADC、DAC芯片的SIPI仿真、800G/1.6T光模块仿真。目前在圆周率半导体从事FT板的SIPI仿真工作。

With the growth of the demand for entertainment, high resolution and high refresh rate displayers become increasingly popular. These products are always featured with display resolution up to 4k and refresh rates up to 300Hz, which means they need a high bandwidth and high-speed process unit. Normally, Display Driver Chip is equipped with high performance analog modules, variety of display interface modules and complex digital processing modules. To test this chip, there are several special notices list below:

1. Cost sensitive both on hardware solution and software test time
2. High performance demand on analog tests both at high Frequency (up to 75Mhz) and high resolution (up to 24 bits), it is a great challenge for tester and data processing
3. To meet high parallelism and high-performance testing requirements, strict LB design to ensure high-quality SI and PI is essential.
4. Complex circuit designed involve multi-site data Consistency problem

In this paper, we delivered a high efficiency test solution based on a real case. This test solution included hardware LB design and software test program develop algorithm. It includes 4 chapters for description:

1. Generally, introduce the test DUT background (like spec target, IP module, test requirement). Then recommend an optimized 16 sites hardware solution with high parallelism. List the key point of how to control test time, TTR suggestions based on the real case.
2. Completely test process introduction of analog module. Including 75Mhz with 14 bits ADC test and 1KHz 24bits DAC test. To prove WSMX AWG performance can meet the spec of the target DUT, we collect real experiment data which include 10MHz to 100MHz dynamic performance of sine wave with WSMX HS unit. And a special calculation algorithm will be shown in this part, which can obviously improve test performance of dynamic parameters like SNR/SNDR/THD/SFDR even test with non-coherence sample (SNR can improve over 30dB in some extremely condition).
3. LB design special notice, detail descript signal routing rules while testing. A holey signal path placement suggestion based on real case will be added here (In some extremely condition, THD will have 20dB gap).
4. Demonstrate the root causes of multi-site inconsistency problems across analog test items and provide effective optimization solutions. (yield can improve obviously)

In addition, the target device is already in mass production, analog test performance meets the goal. So, the reference test result will be also past at the end.

Chelsea Zhou

Develop Application Engineer of ADVANTEST. Obtained a bachelor’s degree in electronic information systems in 2022. With more than 4 years of experience in developing ATE test programs. Engaged in digital, high-speed and mixed-signal chip testing, providing ATE chip test software and hardware solutions for leading semiconductor corporations in the Chinese mainland.

随着娱乐应用需求的持续增长，高分辨率、高刷新率显示产品日益普及。当前显示器产品分辨率可达 4K，刷新率可超过 300Hz，对芯片带宽和高速数据处理能力提出了更高要求。显示驱动芯片（Display Driver Chip）通常集成高性能模拟模块、多种显示接口模块以及复杂数字处理模块，因此其测试面临诸多挑战，包括硬件成本与测试时间控制、高频高精度模拟性能验证、高并行测试下的信号完整性（SI）与电源完整性（PI）设计，以及多站点测试一致性等问题。

本文基于实际量产项目，提出了一套针对显示驱动芯片的高效率测试解决方案，涵盖硬件 Load Board 设计与软件测试程序开发两大部分。首先介绍被测器件（DUT）的产品背景、性能指标、IP 模块特性及测试需求，并结合实际案例提出优化的 16 Site 高并行硬件方案，以及降低测试时间（Test Time Reduction, TTR）的关键策略。

其次，详细介绍模拟模块测试流程，包括 75 MHz、14 位 ADC 测试以及 1 kHz、24 位 DAC 测试。通过实际实验数据验证 WSMX 高速 AWG 平台在 10 MHz 至 100 MHz 范围内的动态性能，并提出一种改进算法，在非相干采样条件下仍可显著提升 SNR、SNDR、THD 及 SFDR 等动态参数的测试精度，极端条件下 SNR 提升可超过 30 dB。

此外，论文还总结了模拟测试中 Load Board 设计和信号布线的关键注意事项，并结合实际案例给出优化建议。在某些极端条件下，合理的信号路径设计可使 THD 性能改善超过 20 dB。同时，针对多 Site 测试中的数据一致性问题，深入分析其根本原因，并提出有效优化方案，从而显著提升量产测试良率。最终，基于已经量产的目标产品验证了该方案的有效性，测试结果表明模拟性能满足设计目标要求。

周淑婷

现任 Advantest 应用开发工程师（Application Engineer），于2022年获得电子信息系统专业学士学位。拥有4年以上ATE测试程序开发经验，专注于数字、高速接口及混合信号芯片测试。为中国大陆领先的半导体企业提供ATE测试软件和硬件解决方案，具备丰富的量产测试开发与技术支持经验。