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2025年-2035年硅光子和光子集成电路：技术、市场、预测
复合半导体、收发器、磷化铟/磷化铟光子集成电路、薄膜铌酸锂/薄膜铌酸锂光子集成电路、用于量子的光子集成电路、光学互连、制造、材料、光电共封装
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本报告对包括硅光子在内的光子集成电路行业进行了分类。报告概述了主要市场参与者、新兴材料（如薄膜铌酸锂和钛酸钡）以及关键应用（如人工智能），并据此预测硅光子和光子集成电路（PIC）市场的增长。IDTechEx还探讨了包括可编程光子学、光子量子计算机和光电共封装在内的新兴技术。该市场正迎来巨大的机遇，十年内市场规模预计将超过500亿美元。
本报告对硅光子学和光子集成电路（PICs）市场进行了全面分析，涵盖以下主题：
- 高性能基于PIC的收发器市场的关键玩家分析。
- 共封装光学（Co-Packaged Optics）及其关键概念的细分。
- 用于量子系统的光子集成电路分析。
- 光子材料的基准测试与比较，并按材料对行业进行细分。还包括对新兴材料如薄膜铌酸锂（TFLN）和钛酸钡（BTO）的深入见解。
- 光子集成电路的基础知识与关键概念，包括重要组件和基本原理。
- 人工智能如何改变对基于PIC收发器的需求分析，特别是Nvidia推荐的服务器架构如何需要大量收发器。
- PIC制造技术概览。
- PIC未来应用展望，如互连、LiDAR、生物传感器和气体传感器。
本报告基于广泛的研究和与行业专家的访谈，为任何对光子集成电路未来感兴趣的人士提供了宝贵的见解。
市场预测：
- 10年期光子集成电路市场总预测。
- 10年期用于人工智能、数据中心和高性能计算（HPC，数据通信）的PIC收发器出货量预测。
- 10年期数据通信用PIC收发器每Gbps成本预测。
- 10年期数据通信用PIC收发器市场预测。
- 10年期AI加速器出货量预测。
- 10年期5G用PIC收发器市场预测。
- 10年期5G用PIC收发器出货量预测。
- 10年期量子PIC市场预测。
- 10年期基于PIC的LiDAR市场预测。
- 10年期基于PIC的传感器市场预测。
本报告涵盖的主要内容：
- 执行摘要
- 简介与关键概念
• 技术背景：什么是硅光子学？
• 光子集成电路关键概念
- 制造与材料
• 关于SOI（绝缘体上硅）、SiN（氮化硅）、InP（磷化铟）、TFLN（薄膜铌酸锂）、BTO（钛酸钡）、聚合物及稀土金属的讨论、基准测试及关键公司分析。
- 应用
• 半导体能源危机
• 用于数据中心高性能收发器的光子集成电路
• 用于设备间互连的光子集成电路
• 高级封装与共封装光学
• 混合集成：共封装光学
• 用于人工智能和类脑计算的光子引擎与加速器
• 用于量子计算的光子集成电路
• 基于光子集成电路的传感器
• 基于光子集成电路的LiDAR
- 预测
- 公司概况
What are the benefits and challenges for Silicon Photonics and Photonic Integrated Circuits?
Photonic Integrated Circuits (PICs) are tiny optical systems made out of materials such as Silica (Glass), Silicon, or Indium Phosphide. PICs enable everything from complex optical designs that allow billions of bits of information to be sent and received in a package the size of a candy bar to artificial noses that can detect different compounds and molecules in the air around them. Their importance in high-speed communication within AI data centers is leading to rapid growth in demand for PIC-enabled transceivers to help machine learning models grow ever larger.
By leveraging the billions of dollars in investment in CMOS chip manufacturing, PICs can unlock new processing scaling potential beyond Moore's law. However, there are still significant challenges for the PIC market, such as material limitations, integration complexity, and cost management. Large demand volumes are required to offset the initial cost of designing and manufacturing PICs, and production lead times can take months. IDTechEx's new PIC report thoroughly investigates the PIC market and has identified Photonic Transceivers for AI as an emerging segment that is soon to be the largest source of demand for PICs.
What are the PIC materials of the future?
There is a wide variety of future PIC materials. Most of the current market uses Silicon and Silica-based PICs for light propagation. However, as an indirect bandgap semiconductor, silicon is not a practical light source or photodetector. Therefore, silicon is usually combined with III-V materials for light sources and photodetection. Leveraging the enormous existing integrated circuit manufacturing industry and generally taking advantage of mature node processes, silicon's market dominance is set to continue.
However, Thin Film Lithium Niobate (TFLN), with its moderate Pockels effect and low material loss, is emerging as a strong contender for applications that require high-performance modulation such as quantum systems or potentially high-performance transceivers in the future. Monolithic Indium Phosphide (InP) continues to be a major player due to its ability to detect and emit light. Additionally, innovative materials like Barium Titanite (BTO) and rare-earth metals are being explored for their potential in quantum computing and other cutting-edge applications.
How AI is changing the demand for Silicon Photonics and PICs
The rise of Artificial Intelligence (AI) has spurred an unprecedented demand for high-performance transceivers capable of supporting the massive data rates required by AI accelerators and data centers. Silicon Photonics and PICs are at the forefront of this revolution, with their ability to transmit data at speeds of 1.6Tbps and beyond. As shown by Nvidia's latest H200 server units, which according to IDTechEx's research, require approximately 2.5 800G transceivers per GPU, the need for efficient, high-bandwidth communication is becoming more critical for AI, positioning Silicon Photonics and PICs as essential components in the AI-driven future. The biggest driver of the development of PIC transceivers is AI, as higher-performance AI accelerators will require higher-performance transceivers, with 3.2Tbps transceivers expected to arrive by 2026.
What are the future applications?
Other applications for Silicon Photonics and PICs vary - from high-bandwidth chip-to-chip interconnects to advanced packaging and co-packaged optics, these technologies are paving the way for next-generation computing.
Photonic Engines and Accelerators: Using certain photonic components such as Mach-Zehnder Interferometers, and controlling these components through electro-optical interconnects, high-performance processors and programmable PIC devices can be designed and manufactured, unlocking higher performance than what is possible with electronic accelerators alone.
PIC-based Sensors: Certain PIC materials, such as Silicon Nitride, can used for a range of different sensors, from gas sensors to 'artificial noses'. The healthcare sensor industry may be able to take advantage of the miniaturization of optical components into PIC devices, which could see applications in Point-of-Care diagnostics or wearables.
PIC-based FMCW LiDAR has the potential to transform the automotive and agricultural industries with applications in drones and autonomous vehicles.
Quantum Systems: Companies investing in Trapped Ion and Photon-based Quantum Computing are looking to PICs for more stable and scalable quantum systems. The challenge lies in achieving the precise control of photons necessary for quantum computation.
Source: IDTechEx Research
The market for Silicon Photonics and PICs is experiencing robust growth, driven by the surge in AI and datacom transceiver demand. Key players in the industry such as Intel/Jabil, Coherent, and Infinera are actively using PICs within their transceivers. Innolight, a China-based transceiver company, hit 1.6Tbps of transfer speed in their latest transceivers in late 2023. Coherent, which has its own InP wafer fab facilities, is also developing higher-performance transceivers for 1.6T+ applications. Intel Silicon Photonics, which has transferred its transceiver business to Jabil, announced it had shipped over 8 million PICs since 2016, showing the maturity of the technology. IDTechEx forecasts that PIC technology is to continue to dominate the high-performance transceiver market, further solidifying its position as a critical component in the modern technological landscape.
What is in this report?
This report includes a detailed examination of the latest innovations in Silicon Photonics and Photonic Integrated Circuits, key technical trends, analysis across the value chain, major player analysis, and granular market forecasts.
The report covers the following topics:
- Key Player Analysis for the High-Performance PIC-based Transceiver Market.
- A breakdown of Co-Packaged Optics and its key concepts.
- Analysis of Photonic Integrated Circuits for Quantum Systems.
- Benchmarks and comparisons of photonic materials, with an industry breakdown by material. It also includes an insight into emerging materials such as Thin-Film Lithium Niobate (TFLN) and Barium Titanite (BTO).
- Photonic Integrated Circuit Fundamentals and Key Concepts, including important components, and underlying principles.
- An analysis of how AI is changing demand for PIC-based transceivers, with a look at how Nvidia's recommended server architecture requires large numbers of transceivers.
- An overview of PIC manufacturing techniques.
- A look into future applications of PICs such as interconnects, LiDAR, biosensors, and gas sensors.
The report is based on extensive research and interviews with industry experts and provides valuable insights for anyone interested in the future of photonic integrated circuits. It includes 32 company profiles, many from first-hand interviews, and summaries from events including SPIE Photonex 2024 and SPIE Photonics West 2024.
Market Forecasts:
- 10-year Total Photonic Integrated Circuit Market Forecast.
- 10-year PIC Transceivers for AI, Data Centers and HPC (Datacom) Unit Shipments Forecast
- 10-year PIC Transceivers for Datacom Cost per Gbps Forecast
- 10-year PIC Transceivers for Datacom Market Forecast
- 10-year AI Accelerator Unit Shipments Forecast
- 10-year PIC Transceivers for 5G Market Forecast
- 10-year PIC Transceivers for 5G Unit Shipments Forecast
- 10-year Quantum PIC Market Forecast
- 10-year PIC-based LiDAR Market Forecast
- 10-year PIC-based Sensor Market Forecast
| Report Metrics | Details |
|---|---|
| CAGR | The PIC datacom transceiver market forecast is expected to reach US$43.1 billion by 2035, growing at a CAGR of 23.6% since 2025. |
| Forecast Period | 2024 - 2035 |
| Forecast Units | Volume (units), Revenue (USD billions/millions) |
| Regions Covered | Worldwide |
| Segments Covered | Total Photonic Integrated Circuit Market Forecast PIC Transceivers for AI, Data Centers and HPC (Datacom) Unit Shipments Forecast PIC Transceivers for Datacom Cost per Gbps Forecast PIC Transceivers for Datacom Market Forecast AI Accelerator Unit Shipments Forecast PIC Transceivers for 5G Market Forecast PIC Transceivers for 5G Unit Shipments Forecast Quantum PIC Market Forecast PIC-based LiDAR Market Forecast PIC-based Sensor Market Forecast |
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| 1. | EXECUTIVE SUMMARY |
| 1.1. | Key Current & Future Photonic Integrated Circuits Applications |
| 1.2. | What are Photonic Integrated Circuits (PICs)? |
| 1.3. | Electronic and Photonic Integrated Circuits Compared |
| 1.4. | Advantages and Challenges of Photonic Integrated Circuits |
| 1.5. | Integration schemes of PICs |
| 1.6. | Integrated Photonic Transceivers |
| 1.7. | Datacom PIC-based Transceiver Market Key Players |
| 1.8. | Roadmap for PIC-based Transceivers (chart) |
| 1.9. | Operational Frequency Windows of Optical Materials |
| 1.10. | Silicon and Silicon-on-insulator (SOI) |
| 1.11. | Silicon Nitride (SiN) |
| 1.12. | Indium Phosphide |
| 1.13. | Organic Polymer on Silicon |
| 1.14. | Thin Film Lithium Niobate |
| 1.15. | Barium Titanite and Rare Earth metals |
| 1.16. | IDTechEx Platform Score (Materials Benchmarked) |
| 1.17. | PIC Material Platforms Benchmarked (Visualized) |
| 1.18. | Photonic Integrated Circuit Market (Materials) |
| 1.19. | Forecasting the PIC Transceiver Market: Changes From the 2024 Edition |
| 1.20. | PIC Transceivers for AI Units Forecast |
| 1.21. | Forecasting PIC Transceiver Pricing |
| 1.22. | PIC Datacom Transceiver Market Forecast |
| 1.23. | PIC-based Transceivers for 5G Forecast (Units and Market) |
| 1.24. | Quantum PIC Market Forecast |
| 1.25. | PIC-based Sensor Market Forecast |
| 1.26. | PIC-based LiDAR Market Forecast |
| 1.27. | Total PIC Market Data |
| 1.28. | Company Profiles and Articles included with this report |
| 2. | INTRODUCTION AND KEY CONCEPTS |
| 2.1. | Introduction |
| 2.1.1. | Silicon Photonics Definitions |
| 2.1.2. | What is the difference between PICs and Silicon Photonics? |
| 2.2. | Technology Background |
| 2.2.1. | What is an Integrated Circuit (IC)? |
| 2.2.2. | What are Photonic Integrated Circuits (PICs)? |
| 2.2.3. | Photonics versus Electronics |
| 2.2.4. | Electronic and Photonic Integrated Circuits Compared |
| 2.2.5. | Advantages and Challenges of Photonic Integrated Circuits |
| 2.2.6. | Silicon and Photonic Integrated Circuits |
| 2.2.7. | Key benefits of PICs |
| 2.3. | Photonic Integrated Circuit Key Concepts |
| 2.3.1. | Optical IO, Coupling and Couplers |
| 2.3.2. | Emission and Photon Sources/Lasers |
| 2.3.3. | Detection and Photodetectors |
| 2.3.4. | Compound Semiconductor Lasers and Photodetectors (III-V) |
| 2.3.5. | Modulation, Modulators, and Mach-Zehnder Interferometers |
| 2.3.6. | Light Propagation and Waveguides |
| 2.3.7. | Optical Component Density |
| 2.3.8. | Basic Optical Data Transmission |
| 2.3.9. | PIC Architecture |
| 3. | MATERIALS AND MANUFACTURING |
| 3.1. | Introduction |
| 3.1.1. | Wafers |
| 3.1.2. | Wafer sizes by platform |
| 3.1.3. | Integration schemes |
| 3.1.4. | Heterogenous Integration Techniques Compared |
| 3.1.5. | Micro-Transfer Printing for Heterogenous Integration of InP and Silicon Photonics |
| 3.1.6. | Operational Frequency Windows of Optical Materials |
| 3.1.7. | Important Wavelengths/Frequencies Summarized |
| 3.1.8. | Changing the Way Materials Behave in PICs |
| 3.1.9. | Research Institutions and PIC-only Foundries developing PICs (1) |
| 3.1.10. | Research Institutions and PIC-only Foundries developing PICs (2) |
| 3.1.11. | Research Institutions and PIC-only Foundries developing PICs (3) |
| 3.1.12. | Silicon and Silicon-on-insulator (SOI) |
| 3.1.13. | SOI and Silicon PIC Players |
| 3.1.14. | Silicon Semiconductor foundry in-house technologies |
| 3.1.15. | TSMC's entry to the silicon photonics market |
| 3.1.16. | CEA-Leti's and imec's Latest SOI PIC developments |
| 3.1.17. | SOI Benchmarked |
| 3.1.18. | Silicon Nitride (SiN) |
| 3.1.19. | SiN PIC Players |
| 3.1.20. | SiN Key Foundries |
| 3.1.21. | Case Study: AEPONYX SiN PICs |
| 3.1.22. | SiN Benchmarked |
| 3.1.23. | Silicon (SOI and SiN) device heterogenous integration |
| 3.1.24. | Indium Phosphide |
| 3.1.25. | InP PIC Players |
| 3.1.26. | InP Manufacturing |
| 3.1.27. | Indium Phosphide Incumbent Integration Technologies (1) |
| 3.1.28. | Indium Phosphide Incumbent Integration Technologies (2) |
| 3.1.29. | InP Benchmarked |
| 3.1.30. | Organic Polymer on Silicon |
| 3.1.31. | Case Study: How is Organic Polymer PICs are Manufactured (Lightwave Logic) |
| 3.1.32. | Polymer on Insulator Benchmarked |
| 3.1.33. | Thin Film Lithium Niobate |
| 3.1.34. | How is TFLN Manufactured |
| 3.1.35. | TFLN Integration and Modulator Geometry |
| 3.1.36. | TFLN Benchmarked |
| 3.1.37. | Barium Titanite and Rare Earth metals |
| 3.1.38. | Case Study: Lumiphase BTO-enhanced PICs |
| 3.1.39. | Case Study: How BTO PICs are Manufactured (Lumiphase) |
| 3.1.40. | BTO Benchmarked |
| 3.2. | Materials Benchmarked |
| 3.2.1. | IDTechEx Platform Score (Materials Benchmarked) |
| 3.2.2. | PIC Material Platforms Benchmarked (Visualized) |
| 3.2.3. | The PIC Design Cycle: Multi-Project Wafers |
| 3.2.4. | Case Study: Infinera Vertically Integrated PICs |
| 3.2.5. | Case Study: Coherent (II-VI) |
| 4. | APPLICATIONS |
| 4.1. | Future Applications for Photonic Integrated Circuits |
| 4.2. | The Semiconductor Energy Crisis |
| 4.2.1. | Semiconductor related-energy consumption growing rapidly |
| 4.2.2. | Imec: CO2 emissions per logic technology node are doubling every 10 years |
| 4.2.3. | PICs to improve compute efficiency beyond Moore's law |
| 4.3. | Photonic Integrated Circuits for High-Performance Transceivers for Data Centers |
| 4.3.1. | How an Optical Transceiver Works |
| 4.3.2. | PICs for data communication |
| 4.3.3. | Integrated Photonic Transceivers |
| 4.3.4. | Which Transceivers are using PICs? |
| 4.3.5. | PICs for 400G+ |
| 4.3.6. | Pluggable optics |
| 4.3.7. | 400G+ Pluggable Optic Form Factors |
| 4.3.8. | Pluggable Optical Line System (POLS) |
| 4.3.9. | Communication components - TROSA |
| 4.3.10. | Why do AI models need high-performance transceivers? |
| 4.3.11. | Datacom PIC-based Transceiver Market Key Players |
| 4.3.12. | Key Player Latest Datacom Transceivers Benchmarked |
| 4.3.13. | Interconnect families |
| 4.3.14. | Lanes in interconnect |
| 4.3.15. | Comparing roadmaps |
| 4.3.16. | Linear Drive and Linear Pluggable Optics (LPO) |
| 4.3.17. | Roadmap for PIC-based Transceivers (chart) |
| 4.4. | Photonic Integrated Circuits for On-Device Interconnects |
| 4.4.1. | Interconnects |
| 4.4.2. | Development trend for optical transceivers in high-end data centers |
| 4.4.3. | Overcoming the von Neumann bottleneck |
| 4.4.4. | Electrical Interconnects Case Study: Nvidia Grace Hopper for AI |
| 4.4.5. | Why improve on-device interconnects? |
| 4.4.6. | Improved Interconnects for Switches |
| 4.4.7. | Case Study: Ayer Labs TeraPHY |
| 4.4.8. | Case Study: Lightmatter's 'Passage' PIC-based Interconnect |
| 4.5. | Advanced Packaging and Co-Packaged Optics |
| 4.5.1. | Evolution roadmap of semiconductor packaging |
| 4.5.2. | Semiconductor packaging - an overview of technology |
| 4.5.3. | Key metrics for advanced semiconductor packaging performance |
| 4.5.4. | Four key factors of advanced semiconductor packaging |
| 4.5.5. | Overview of interconnection technique in semiconductor packaging |
| 4.5.6. | 2.5D advanced semiconductor packaging technology portfolio |
| 4.5.7. | Roles of glass in semiconductor packaging |
| 4.6. | Hybrid integration: Co-Packaged Optics |
| 4.6.1. | The emergence of co-packaged optics (CPO) |
| 4.6.2. | Co-packaged optics for network switch |
| 4.6.3. | Pluggable optics vs CPO - 1 |
| 4.6.4. | Pluggable optics vs CPO - 2 |
| 4.6.5. | Optical dies integration for compute silicon |
| 4.6.6. | Future challenges in CPO |
| 4.6.7. | Co-packaging vs Co-packaged optics (CPO) |
| 4.6.8. | Co-packaged optics - package structure |
| 4.6.9. | Value proposition of CPO |
| 4.6.10. | Co-Packaged Optics (CPO), key for advancing switching and AI networks |
| 4.6.11. | Key technology building blocks for CPO |
| 4.6.12. | Key packaging components for CPO |
| 4.6.13. | Broadcom's CPO development timeline |
| 4.6.14. | Broadcom's CPO portfolio |
| 4.6.15. | Fan-Out Embedded Bridge (FOEB) Structure for Co-Packaged Optics |
| 4.6.16. | Glass-based Co-packaged optics - vision |
| 4.6.17. | Glass-based Co-packaged optics - Packaging structure |
| 4.6.18. | Glass-based Co-packaged optics - process development |
| 4.6.19. | Corning's 102.4 Tb/s test vehicle |
| 4.6.20. | Turn-Key solution required for CPO |
| 4.7. | Photonic Engines and Accelerators for AI and Neuromorphic Compute |
| 4.7.1. | Photonic Processors - Overview |
| 4.7.2. | Photonic Processing for AI |
| 4.7.3. | Programmable Photonics, Software-Defined Photonics, & Photonic FPGAs |
| 4.7.4. | Case Study: iPronics' Programmable PIC |
| 4.8. | Photonic Integrated Circuits for Quantum Computing |
| 4.8.1. | Introduction to Quantum Computing |
| 4.8.2. | Quantum computing - photonics |
| 4.8.3. | Overview of photonic platform quantum computing |
| 4.8.4. | Comparing key players in photonic quantum computing |
| 4.8.5. | PICs for Quantum |
| 4.8.6. | Trends for Quantum PICs at SPIE Photonics West 2024 |
| 4.8.7. | Photonic Integrated Circuits versus Optical Tables and Fixed Optics |
| 4.8.8. | Advantages of Photonic Integrated Circuits versus Optical Tables and Fixed Optics |
| 4.8.9. | Disadvantages of Photonic Integrated Circuits versus Optical Tables and Fixed Optics |
| 4.8.10. | CEA Leti's Goals for Quantum PICS |
| 4.8.11. | Quantum Photonic Building Blocks (imec) |
| 4.8.12. | Initialization, manipulation, and readout of photonic platform quantum computers |
| 4.8.13. | Which platform for quantum PICs? |
| 4.8.14. | Future PIC Requirements of the Quantum Industry |
| 4.8.15. | Roadmap for photonic quantum hardware (chart) |
| 4.8.16. | SWOT Analysis: Photonic Quantum Computers |
| 4.9. | Photonic Integrated Circuit-based Sensors |
| 4.9.1. | Opportunities for PIC Sensors: Biomedical |
| 4.9.2. | Market players developing PIC Biosensors |
| 4.9.3. | Rockley Photonics: IP sale and likely end of PIC involvement |
| 4.9.4. | Opportunities for PIC Sensors: Gas Sensors |
| 4.9.5. | Market players developing PIC-based Gas Sensors |
| 4.9.6. | Opportunities for PIC Sensors: Structural Health Sensors |
| 4.9.7. | Market players developing Spectroscopic PICs |
| 4.10. | Photonic Integrated Circuit-based LiDAR |
| 4.10.1. | LiDAR in automotive applications |
| 4.10.2. | Opportunities for PIC Sensors: LiDAR Sensors |
| 4.10.3. | Core Aspects of LiDAR |
| 4.10.4. | Market players developing PIC-based LiDAR (1) |
| 4.10.5. | Market players developing PIC-based LiDAR (2) |
| 4.10.6. | LiDAR Wavelength and Material Trends |
| 4.10.7. | Major challenges of PIC-based FMCW lidars |
| 4.10.8. | E-Noses for Automotive |
| 5. | FORECASTS |
| 5.1. | Forecasting the PIC Transceiver Market: Changes From the 2024 Edition |
| 5.2. | Forecasting Growth in GPUs and Other Accelerators |
| 5.3. | Forecasts with table: Server boards, CPUs and GPUs/Accelerators |
| 5.4. | Optical Transceivers per AI Accelerator (Methodology) |
| 5.5. | Methodology - Transceiver Market Share by Speed |
| 5.6. | PIC Transceivers for AI Units Forecast |
| 5.7. | PIC Transceivers for AI Units Forecast |
| 5.8. | Forecasting PIC Transceiver Pricing |
| 5.9. | Forecasting PIC Transceiver Pricing: Tables |
| 5.10. | PIC Datacom Transceiver Market Forecast |
| 5.11. | PIC Datacom Transceiver Revenue Forecast with Table |
| 5.12. | PIC-based Transceivers for 5G Forecast (Units and Market) |
| 5.13. | Quantum PIC Market Forecast |
| 5.14. | Quantum PIC Market Forecast with Table |
| 5.15. | PIC-based Sensor Market Forecast |
| 5.16. | PIC-based LiDAR Market Forecast |
| 5.17. | Photonic Integrated Circuit Market (Materials) |
| 5.18. | Photonic Integrated Circuit Market by Material with Table |
| 5.19. | Total PIC Market Data |
| 6. | COMPANY PROFILES |
| 6.1. | Profiles |
| 6.1.1. | ACCRETECH (Grinding Tool) |
| 6.1.2. | AEPONYX |
| 6.1.3. | Amkor — Advanced Semiconductor Packaging |
| 6.1.4. | ASE — Advanced Semiconductor Packaging |
| 6.1.5. | Ayar Labs: AI Accelerator Interconnect |
| 6.1.6. | CEA-Leti (Advanced Semiconductor Packaging) |
| 6.1.7. | Ciena |
| 6.1.8. | Coherent: Photonic Integrated Circuit-Based Transceivers |
| 6.1.9. | EFFECT Photonics |
| 6.1.10. | EVG (D Hybrid Bonding Tool) |
| 6.1.11. | GlobalFoundries |
| 6.1.12. | HD Microsystems |
| 6.1.13. | Henkel (Semiconductor packaging, Adhesive Technologies division) |
| 6.1.14. | iPronics: Programmable Photonic Integrated Circuits |
| 6.1.15. | JCET Group |
| 6.1.16. | JSR Corporation |
| 6.1.17. | Lightelligence |
| 6.1.18. | Lightmatter |
| 6.1.19. | LioniX |
| 6.1.20. | LIPAC |
| 6.1.21. | LPKF |
| 6.1.22. | Lumiphase |
| 6.1.23. | Lumiphase - Company Profile - IDTechEx Portal |
| 6.1.24. | Mitsui Mining & Smelting (Advanced Semiconductor Packaging) |
| 6.1.25. | QuiX Quantum |
| 6.1.26. | NanoWired |
| 6.1.27. | QuiX Quantum (Update) |
| 6.1.28. | Resonac (RDL Insulation Layer) |
| 6.1.29. | Scintil Photonics |
| 6.1.30. | TOK |
| 6.1.31. | TSMC (Advanced Semiconductor Packaging) |
| 6.1.32. | Vitron (Through-Glass Via Manufacturing) — A LPKF Trademark |
| 6.2. | Articles |
| 6.2.1. | SPIE Photonics West 2024: Integrated Photonics for Quantum Systems - Article: Topic overview |
| 6.2.2. | SPIE Photonics West 2024: Photonic Integrated Circuit Manufacturing - Article: Event summary |
| 6.2.3. | Event Summary: SPIE Photonex 2024 |
到2035年，整个光子集成电路市场预计将超过540亿美元。
报告统计信息
| 幻灯片 | 226 |
|---|---|
| Companies | Over 30 |
| 预测 | 2035 |
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