Moore’s law approaches its physical limits, conventional electronic systems encounter fundamental bottlenecks in data transmission bandwidth, computational efficiency, and energy consumption. Silicon photonics emerges as a transformative solution that enables seamless photonics-electronics convergence, fundamentally addressing these limitations that constrain the future of information technology. By synergistically combining the inherent parallelism and high bandwidth capabilities of light with the mature processing infrastructure of silicon electronics, this convergence creates unified platforms that transcend traditional performance boundaries and establish new benchmarks across critical application domains. The strategic significance of silicon photonics lies in its ability to provide integrated photonic-electronic solutions across three foundational pillars of modern information infrastructure: optical communication, optical sensing, and optical computing. This convergence enables each domain to leverage the complementary strengths of both photonic and electronic technologies, creating synergistic capabilities that neither could achieve independently. Through this unified approach, silicon photonic systems deliver exceptional energy efficiencies via hybrid light-electronic processing, positioning photonics-electronics convergence as an essential enabler for artificial intelligence acceleration, edge computing applications, and next-generation technological advancement.

The comprehensive review of silicon photonics presented in this article plays a significant academic role during the ongoing shift from traditional electronic architectures to photonic-electronic integrated systems. The significance of such systematic reviews extends beyond documenting existing knowledge to providing strategic guidance for a field undergoing fundamental technological transformation. The timing of focused research synthesis is particularly relevant as the semiconductor industry and broader technology ecosystem address the approaching limits of Moore’s law scaling. At this transition point, the research community and industry benefit from authoritative consolidation of knowledge that has developed across multiple disciplines. Comprehensive reviews help bridge knowledge gaps by integrating insights from materials science, device physics, system integration, and application domains into unified analytical frameworks. Such consolidation supports informed decision-making regarding research priorities and technological roadmaps in the post-Moore era.

Systematic reviews in silicon photonics also establish intellectual coherence within this rapidly evolving, interdisciplinary field. Silicon photonics research spans from fundamental physics to commercial applications, often creating compartmentalized knowledge development. By examining technological evolution across optical communication, sensing, and computing domains, comprehensive reviews facilitate cross-pollination of ideas and identify synergistic opportunities that might otherwise remain unrecognized. This synthetic approach accelerates innovation by enabling researchers to leverage insights from adjacent areas. Such reviews provide valuable intellectual infrastructure for coordinated advancement toward photonic-electronic integration, transforming distributed research efforts into coherent strategic vision supporting the post-Moore era transition.

The exponential growth of global internet traffic and artificial intelligence (AI)-driven applications has created an insatiable demand for data transmission capacity, rendering conventional copper-based interconnects inadequate. Silicon photonic integration addresses this critical bottleneck by enabling multi-channel parallelism and dense wavelength division multiplexing (DWDM), achieving single-chip data transmission rates exceeding terabits per second (Fig. 6). Significant advances in modulation technologies have been achieved through innovations in Mach-Zehnder modulators (MZMs) and microring modulators (MRMs), with modulation bandwidths surpassing 110 GHz. These breakthroughs have enabled the development of energy-efficient co-packaged optics (CPO), which deliver substantial power reductions compared to traditional pluggable transceiver modules. This technology has become indispensable for next-generation hyperscale data centers and exascale high-performance computing infrastructures (Fig. 7). Silicon photonics has also revolutionized optical sensing applications, particularly in lidar systems for autonomous vehicles and robotics (Figs. 14 and 15). The technology enables unprecedented integration density and performance capabilities through frequency-modulated continuous-wave (FMCW) lidar systems integrated with optical phased arrays (OPAs), demonstrating high-resolution beam steering and long-range detection capabilities. Remarkable scaling progress has been achieved from early proof-of-concept systems to large-scale optical phased array implementations, while monolithic integration breakthroughs have enabled solid-state FMCW lidar systems with real-time multi-dimensional imaging capabilities and enhanced ranging performance. These advances have culminated in the demonstration of parallel processing capabilities through advanced microcomb integration and sophisticated opto-electronic co-packaging technologies, positioning silicon photonic lidar as a commercially viable solution for autonomous vehicles and advanced sensing applications. Photonic-electronic synergistic architectures represent a paradigm shift beyond the traditional von Neumann bottleneck. Photonic neural networks and matrix accelerators exploit the inherent parallelism and high bandwidth of light, achieving energy efficiencies several orders of magnitude higher than conventional electronic systems. Advanced architectures including Mach-Zehnder interferometer (MZI) meshes, microring weight banks, intensity modulation arrays, and metasurface diffractive optical networks have demonstrated energy efficiency exceeding 100 TOPS/W (TOPS: tera operations per second). These systems enable real-time inference on complex AI models such as ResNet and bidirectional encoder representations from Transformers (BERT) (Figs. 17 and 18). The integration of non-volatile phase-change materials and plasmonic modulators further enhances computational speed and efficiency, positioning silicon photonics as a disruptive technology in high-performance computing and edge AI applications.

Despite substantial technological advances, achieving industrial-scale viability in silicon photonics requires addressing fundamental scientific barriers to large-scale integration. The foremost challenge stems from inherent material compatibility issues, where significant lattice mismatches and thermal expansion coefficient differentials between dissimilar materials generate interfacial defects and thermomechanical stress, critically degrading optical performance parameters and compromising long-term reliability. Equally critical is achieving nanoscale precision control and high manufacturing yield across massively integrated photonic-electronic arrays, where increasing integration densities exponentially amplify the performance impact of process variations. System-level packaging and thermal management present additional complexities arising from the contrasting requirements of temperature-sensitive photonic components and power-dissipating electronic circuits.

Transformative pathways forward include three-dimensional heterogeneous integration utilizing through-silicon vias and micro-bump technologies, transcending planar density limitations through vertical stacking and functional layer co-optimization. The emergence of chiplet-based modular design paradigms enables standardized photonic input/output cores, enhancing system configurability while reducing development cycles. Most significantly, the deep convergence of artificial intelligence with photonics will unlock transformative capabilities through deep learning-enabled inverse design, enabling discovery of novel micro/nano-photonic structures beyond empirical intuition, while AI-driven process optimization and autonomous device tuning will dramatically improve manufacturing yield and operational reliability. These advances will catalyze profound transformations across the information technology landscape. Silicon photonics will underpin terabit-per-second optical backbones essential for 6G networks, enable miniaturized high-sensitivity sensors for autonomous mobility and smart infrastructure, and drive photonic-electronic convergence toward distributed computing paradigms that harness the inherent parallelism of light for unprecedented computational efficiency in exascale artificial intelligence applications.

As the pivotal enabler for the post-Moore era, silicon photonics represents both an evolutionary imperative and a defining opportunity to augment human cognitive capabilities. Through sustained cross-disciplinary innovation, this technology will establish the indispensable technological foundation for an intelligently interconnected future, marking a transformative chapter in information technology evolution.