公众号记得加星标⭐️，第一时间看推送不会错过。 来源 ： 内容编译自semiengineering 。 随着出口管制的加强以及人们对人工智能芯片走私和假冒的担忧日益加剧，位置验证作为一种以最小 努力加强供应链监督的方式正受到越来越多的关注。 过去，这种追踪方式是安排一名或多名员工在晶圆厂现场监督整个生产流程，全程跟踪芯片直至目的 地，并记录每个密封的包装箱。这种方法成本高昂，而且容易被滥用。从 GDSII 代码交付到晶圆 厂，到最终交付给客户，在供应链的每个阶段，都很难记录数百万个芯片，而且如果涉及来自多个来 源的多个芯片，这种方法会变得非常难以操作。 或许更重要的是，既然已经有技术可以更好地保护供应链，为什么还要派人去维护呢？这个问题的答 案很复杂，而且可能带有政治色彩。但技术正在进步和改进。 有几种主要方法可以随时跟踪芯片的位置（从制造到目的地），包括： 以上所有方法都依赖于相对成熟的现有方法，并且比中间人解决方案具有更高的粒度。位置验证可以 追踪芯片的发货地点，甚至包括芯片的使用时间。 "如果你拥有验证技术，那么你就可以鱼与熊掌兼得，"进步研究所 (Institute for Progress) 的技术 ...

如果您希望可以时常见面，欢迎标星收藏哦~ 来源：本文编译自eetjp 。 2025年9月30日，英飞凌科技公司（以下简称"英飞凌"）的日本子公司——英飞凌科技日本公司 （以下简称"英飞凌"）面向日本客户举办了题为"RISC-V微控制器与汽车应用的未来：英飞凌的愿 景与生态系统构建"的研讨会活动。来自汽车制造商和一级制造商的相关人士出席了此次活动。 根据科技信息服务机构TechInsights 2025年3月发布的数据，英飞凌在2024年汽车半导体市场中以 13.5%的市场份额位居第一。此外，根据Omdia 2025年5月发布的数据，英飞凌在2024年微控制器 市场中也排名第一。英飞凌总裁Hajime Kobe表示："英飞凌的优势在于销售不集中在任何特定地 区，我们在全球范围内保持着较高的市场份额。" 在 汽 车 微 控 制 器 方 面 ， 英 飞 凌 此 前 已 开 发 出 采 用 自 有 内 核 的 "AURIX" 以 及 基 于 Arm 内 核 的 "TRAVEO" 和 "Auto PSOC" 。 但 随 着 软 件 定 义 汽 车 （ SDV ） 的 趋 势 ， 该 公 司 还 将 开 发 采 用 RI ...

公众号记得加星标⭐️，第一时间看推送不会错过。 塑造电力电子的未来：GaN 在关键高增长市场的扩张 下一波扩张预计将出现在汽车市场，向电气化和高级驾驶辅助系统的转变正在推动传统功率器件的极限。GaN 器 件如今已广泛应用于 LiDAR 系统，而 GaN 车载充电器 (OBC) 有望成为下一个销量驱动力。非车载直流充电器和 牵引逆变器正随着更多参考设计的出现而日趋成熟。预计汽车和移动出行市场将从 2024 年到 2030 年以 **73% 的惊人复合年增长率（CAGR）**增长。 同样，超大规模数据中心正在寻求能效解决方案来管理不断增长的工作负载。英伟达（NVIDIA）正与领先的宽 禁带芯片制造商合作，将 SiC 和 GaN 技术集成到其 800 V 高压直流（HVDC）电源系统中，这为 GaN 在未来三 到四年内大规模应用于数据中心铺平了道路。GaN 在支持这些架构方面具有独特的优势，它能够实现更高效的电 源转换并腾出宝贵的电路板空间。对于 AI 服务器和网络设备而言，采用 GaN 正成为一种竞争的必需品。加上电 信领域，预计该市场将在 2024 年到 2030 年间以 53% 的显著复合年增长率增长。 来源 ...

作为宽禁带半导体的两大代表材料，氮化镓（GaN）目前在消费电子快充领域蓬勃发展，而 碳化硅（SiC）则在新能源汽车的应用场景中逐渐普及。这两种第三代半导体材料各有千 秋：GaN以其高开关频率和低开关损耗优势在高频应用中大放异彩，SiC则凭借高电压、高 温度工作能力在功率转换领域独树一帜。 如今，随着人工智能的强势崛起，这两种材料的应用边界正在不断拓展，为碳化硅和氮化镓 创造了前所未有的增量市场——AI数据中心服务器电源（PSU）。 AI数据中心的电力挑战： 从传统到变革 生成式人工智能的火热应用以及AI芯片算力的爆发式增长，正在重新定义数据中心的电力需求。 根 据 英 飞 凌 的 预 测 ， 单 个 GPU 的 功 耗 将 呈 指 数 级 增 长 ， 从 目 前 的 1000W 激 增 至 2030 年 的 约 2000W。与此同时，AI服务器机架的峰值功耗将达到惊人的300kW以上——这相当于几年前传统 服务器总功耗的数十倍。 更为严峻的是，英飞凌估计到2030年，数据中心的电力消耗可能高达全球的7%，大致相当于印度 目前的全国能源消耗量。这一数据清晰地描绘了AI带来的高能耗危机。 在这种背景下，数据中心电 ...

英飞凌执行副总裁兼后端运营主管 George Lee 表示："我们的员工在产品质量方面树立了高标 准，并将在新的所有权下继续努力。" "MPI 的业务模式将通过服务广泛的客户群，实现工厂的更 多 样 化 利 用 。 我 相 信 ， 这 一 举 措 将 为 曼 谷 的 员 工 提 供 卓 越 的 长 期 发 展 前 景 ， 让 他 们 能 够 加 入 MPI，并接管所有生产相关员工的运营。我们将继续保持密切合作，为客户提供成熟的产品和尖端 解决方案。" 如果您希望可以时常见面，欢迎标星收藏哦~ 来源：内容来自半导体芯闻综合。 英飞凌科技股份公司已达成最终协议，将其位于泰国曼谷/暖武里府的后端制造工厂转让给英飞凌 值得信赖的供应商马来西亚太平洋工业有限公司（MPI）。在工厂转移的同时，英飞凌还与 MPI 签订了长期供应协议。此外，两家公司同意加强合作伙伴关系，共同开发创新封装解决方案。 这一战略举措将一家新的半导体公司引入该国，进一步丰富了当地的半导体生态系统。MPI 是一 家总部位于马来西亚的投资控股公司。MPI 的子公司以 Carsem 的名义为全球客户提供外包半导 体组装、封装和测试服务（OSAT），已有 ...

Summary of Key Points from the Conference Call Industry Overview: Global Semiconductor - **Sales Performance**: Global total semiconductor sales decreased by 5.2% month-over-month (M/M) in July, but still exceeded the 10-year and 5-year seasonal averages by approximately 290 basis points (bps) and 420 bps, respectively [1] - **Ex-Memory IC Sales**: Sales of semiconductors excluding memory integrated circuits (ICs) increased by 3.0% M/M, marking a significant reversal from typical seasonal declines of 5-3% [1] - **Logic Sales**: Logic sales reached a record high of $24.5 billion, up 1.7% M/M, outperforming the 10-year seasonal average by about 400 bps, driven by an all-time high average selling price (ASP) [1] - **Analog and MPU Sales**: Analog sales rose by 9.1% M/M, while microprocessor unit (MPU) sales increased by 0.6%, both above their respective 10-year seasonal averages [1] - **Year-over-Year Growth**: Year-over-year (YoY) total semiconductor sales growth accelerated to 24.4%, with year-to-date (YTD) growth at 18.3% [1] Memory Segment Insights - **Memory Sales Decline**: Memory sales fell by 22.8% M/M, which is approximately 360 bps below the 10-year seasonal average [2] - **ASP and Volume Changes**: Average selling prices (ASP) for memory decreased by 5.4% M/M, while volume declined by 18.4% M/M, aligning with normal seasonal patterns [2] - **Future Pricing Forecast**: Forecasts indicate that DDR and NAND contract pricing will rise by 3% quarter-over-quarter (Q/Q) in Q3 and 5% in Q4 of 2025, with expectations of continued undersupply into Q3 2026 [2] Future Projections - **Industry Revenue Forecasts**: The semiconductor industry revenue is projected to reach approximately $701 billion in 2025 (+16% YoY) and $841 billion in 2026 (+20% YoY), supported by increased logic revenues and extended DRAM/NAND undersupply [1] - **Q3:25 Outlook**: Street estimates suggest total semiconductor revenue will grow by 12.3% Q/Q, with ex-memory semiconductor sales increasing by 10.6% Q/Q [3] Preferred Stocks - **US Stocks**: Preferred stocks in the US include AVGO, NVDA, and TXN [1] - **International Stocks**: Internationally preferred stocks include ASE, Eugene Technology, Infineon, MediaTek, Renesas, SK Hynix, and TSMC [1] Additional Insights - **ASP Trends**: The ASP for logic products showed a slight decline of 0.5% M/M, while the overall ASP for semiconductors is expected to trend positively in the coming quarters [6] - **Market Dynamics**: The semiconductor market is experiencing a complex interplay of demand and supply dynamics, with certain segments like logic and analog showing resilience while memory faces challenges [1][2] This summary encapsulates the key insights and projections from the conference call, highlighting the current state and future outlook of the semiconductor industry.

Core Viewpoint - The global ultra-low power (ULP) microcontroller market is experiencing strong growth, projected to increase from $9.78 billion in 2025 to $15.27 billion by 2030, driven by rising energy efficiency demands in consumer electronics and the proliferation of smart home and building management systems [1][2]. Group 1: Market Growth and Drivers - The ULP microcontroller market is expected to grow significantly due to the increasing demand for battery-powered devices that are smaller and more feature-rich [1]. - The analog device segment is anticipated to lead the market in 2025, highlighting the importance of precise signal measurement, conditioning, and conversion in sensors, medical devices, and industrial automation [1][3]. - The demand for ULP MCUs is accelerating in wearable medical devices, environmental sensors, and connected electronics, bridging consumer electronics and industrial sectors [1][3]. Group 2: Automotive Sector Impact - ULP MCUs are crucial for advanced driver-assistance systems (ADAS), infotainment systems, battery management, and in-vehicle sensors, with their low-power standby mode and quick wake-up features being essential for electric and hybrid vehicles [2][4]. - The automotive sector is expected to hold a significant share of the ULP MCU market, driven by the integration of these controllers in key functionalities like tire pressure monitoring systems and climate control modules [4]. Group 3: Regional Insights - North America is projected to lead the global ULP MCU market, fueled by strong applications in IoT, industrial automation, and energy-efficient consumer electronics [2][5]. - The surge in demand for smart home deployments, wearable medical devices, and battery-powered industrial sensors is creating substantial market opportunities in North America [5][6]. - Government initiatives like the CHIPS and Science Act are promoting semiconductor innovation, further enhancing the competitive landscape for ULP MCUs in the region [5]. Group 4: Key Players and Innovations - Major players in the ULP MCU market include Infineon Technologies, NXP Semiconductors, Renesas Electronics, and STMicroelectronics, emphasizing the strategic importance of ULP microcontrollers in the next-generation electronic ecosystem [3]. - Companies are focusing on low-power designs and collaborating with OEMs in high-growth verticals to strengthen their market position [6].

Core Insights - The global automotive semiconductor market is projected to reach $68 billion in 2024, with Infineon Technologies leading the market [3] - The market is expected to grow at a compound annual growth rate (CAGR) of 12%, reaching $132 billion by 2030 [4] - The average semiconductor price per vehicle is anticipated to rise from approximately $759 in 2024 to about $1,332 by 2030 [4] Market Growth Factors - The growth is supported by three structural factors: increased electrification, regulatory requirements for advanced safety features, and the evolution of electrical/electronic architectures [6] - The adoption of dual-motor plug-in hybrid electric vehicles (PHEVs) is expected to grow at an average rate of 19% from 2024 to 2030, while battery electric vehicles (BEVs) will grow at a rate of 14% [6] Price Trends and Technology Adoption - The rapid decline in the price of N-type silicon carbide (SiC) substrates is expanding the application of SiC MOSFETs in inverters for both BEVs and PHEVs [7] - Artificial intelligence is increasingly being integrated into various sectors, including automotive, particularly in advanced driver-assistance systems (ADAS) [7] Market Share and Key Players - The top five companies account for nearly half of the automotive semiconductor market, with Infineon holding a 12% market share and over $8 billion in sales [8] - NXP Semiconductors ranks second with a 10% market share, followed by STMicroelectronics with 9% [8] Regional Developments - China aims to increase the localization rate of automotive components to 25% by 2025, with domestic semiconductor manufacturers gaining traction in the market [10] - TSMC and Samsung are competing in the 16nm and below process technology, with significant implications for the automotive sector [11]

Core Viewpoint - The article discusses the evolving landscape of artificial intelligence (AI) processing solutions, highlighting the need for companies to balance current performance with future adaptability in AI models and methods. Various processing units such as GPUs, ASICs, NPUs, and FPGAs are being utilized across different applications, from high-end smartphones to low-power edge devices [1][12]. Summary by Sections AI Processing Units - Companies are exploring a range of processing units for AI tasks, including GPUs, ASICs, NPUs, and DSPs, each with unique advantages and trade-offs in terms of power consumption, performance, flexibility, and cost [1][2]. - GPUs are favored in data centers for their scalability and flexibility, but their high power consumption limits their use in mobile devices [2]. - NPUs are optimized for AI tasks, offering low power and low latency, making them suitable for mobile and edge devices [2]. - ASICs provide the highest efficiency and performance for specific tasks but lack flexibility and have high development costs, making them ideal for large-scale, targeted deployments [3]. Custom Silicon - The trend towards custom silicon is growing, with major tech companies like NVIDIA, Microsoft, and Google investing in tailored chips to optimize performance for their specific software needs [4]. - Custom AI accelerators can provide significant advantages, but they require a robust ecosystem to support software development and deployment [4]. Flexibility and Adaptability - The rapid evolution of AI algorithms necessitates flexible hardware solutions that can adapt to new models and use cases, as traditional ASICs may struggle to keep pace with these changes [4][5]. - The need for adaptable architectures is emphasized, as AI capabilities may grow exponentially, putting pressure on decision-makers to choose the right processing solutions [4][5]. Role of DSPs and FPGAs - DSPs are increasingly being replaced or augmented by AI-specific processors, enhancing capabilities in areas like audio processing and motion detection [7]. - FPGAs are seen as a flexible alternative, allowing for algorithm updates without the need for complete hardware redesigns, thus combining the benefits of ASICs and general-purpose processors [8]. Edge Device Applications - Low-power edge devices are utilizing MCUs equipped with DSPs and NPUs to meet specific processing needs, differentiating them from high-performance mobile processors [10]. - The integration of AI capabilities into edge devices is becoming more prevalent, with companies developing specialized MCUs for machine learning and context-aware applications [10][11]. Conclusion - The edge computing landscape is characterized by a complex mix of specialized and general-purpose processors, with a trend towards customization and fine-tuning for specific workloads [12].

Core Viewpoint - SkyWater Technology's acquisition of Infineon's 200mm wafer fab in Austin, Texas, will quadruple its production capacity, expanding traditional node production from 130nm to 65nm, and is expected to meet the needs of various clients including the U.S. Department of Defense and quantum computing manufacturers [2][4]. Group 1: Acquisition and Capacity Expansion - The acquisition will increase SkyWater's annual wafer production capacity to approximately 400,000 wafers, which is four times its previous capacity [2]. - The deal provides critical processing capabilities, including back-end-of-line (BEOL) technology, essential for connecting various devices on a chip [2]. - SkyWater has signed multiple supply agreements with Infineon, valued at over $1 billion, to produce chips for the next four years [4]. Group 2: Market Dynamics and Strategic Positioning - A significant portion of semiconductor manufacturing capacity has shifted overseas, with 80% to 90% of microcontrollers and embedded electronics produced outside the U.S., primarily in China and Taiwan, creating challenges for U.S. defense and industrial sectors [3]. - The U.S. government is increasingly aware of the need for secure domestic supply chains, as highlighted by ongoing investigations by the Department of Commerce [3]. - SkyWater aims to differentiate itself from larger foundries like TSMC by focusing on technology-as-a-service products, which is gaining attention in the industry [4]. Group 3: Collaboration and Innovation - SkyWater has a long-standing partnership with Google, having developed the first open-source process design kit (PDK) for mixed-signal technology [5]. - The company is positioning itself as a leading foundry for quantum hardware innovation, collaborating with companies like D-Wave and PsiQuantum [5]. - SkyWater's research focuses on superconductors and photonics, working closely with clients to develop custom manufacturing processes that differ from traditional foundry operations [5].