Search Results (293)

Highly integrable silicon carbide (SiC) has emerged as a promising platform for photonic integrated circuits (PICs), offering a comprehensive set of material and optical properties that are ideal for the integration of nonlinear devices and solid-state quantum defects. However, despite significant progress in nanofabrication technology, the development of SiC on an insulator (SiCOI)-based photonics faces challenges due to fabrication-induced material optical losses and complex processing steps. An alternative approach to mitigate these fabrication challenges is the direct deposition of amorphous SiC on an insulator (a-SiCOI). However, there is a lack of systematic studies aimed at producing high optical quality a-SiC thin films, and correspondingly, on evaluating and determining their optical properties in the telecom range. To this end, we have studied a single-source precursor, 1,3,5-trisilacyclohexane (TSCH, C₃H₁₂Si₃), and chemical vapor deposition (CVD) processes for the deposition of SiC thin films in a low-temperature range (650–800 °C) on a multitude of different substrates. We have successfully demonstrated the fabrication of smooth, uniform, and stoichiometric a-SiCOI thin films of 20 nm to 600 nm with a highly controlled growth rate of ~0.5 Å/s and minimal surface roughness of ~5 Å. Spectroscopic ellipsometry and resonant micro-photoluminescence excitation spectroscopy and mapping reveal a high index of refraction (~2.7) and a minimal absorption coefficient (<200 cm⁻¹) in the telecom C-band, demonstrating the high optical quality of the films. These findings establish a strong foundation for scalable production of high-quality a-SiCOI thin films, enabling their application in advanced chip-scale telecom PIC technologies. Full article

Silicon-based microcavity quantum dot lasers are attractive candidates for on-chip light sources in photonic integrated circuits due to their small size, low power consumption, and compatibility with silicon photonic platforms. However, integrating components like quantum dot lasers and photodetectors on a single chip remains challenging due to material compatibility issues and mode field mismatch problems. In this work, we have demonstrated monolithic integration of an InAs quantum dot microdisk light emitter, waveguide, and photodetector on a silicon platform using a shared epitaxial structure. The photodetector successfully monitored variations in light emitter output power, experimentally proving the feasibility of this integrated scheme. This work represents a key step toward multifunctional integrated photonic systems. Future efforts will focus on enhancing the light emitter output power, improving waveguide efficiency, and scaling up the integration density for advanced applications in optical communication. Full article

The fast-maturing photonic integration technology is calling for a versatile platform that supports both active and passive functions as well as high scalability through component miniaturization. Indium phosphide (InP) has long been recognized for its ability to deliver a comprehensive suite of photonic components. InP membrane technology has emerged as a next-generation solution that could unite the functional completeness with high scalability. This paper describes recent advancements in the InP-membrane-on-Si (IMOS) platform, which supports high-performance passives, polarization and mode handling, native light sources, amplifiers, modulators and detectors, and novel material integration. Full article

An optical power splitter (OPS) with arbitrary splitting ratios has attracted significant research interest for its broad applications in photonic integrated circuits. A series of OPSs with arbitrary splitting ratios based on silicon nitride (Si₃N₄) platforms are presented. The devices are designed with ultra-compact dimensions using three-dimensional finite-difference time-domain (3D FDTD) analysis and an inverse design algorithm. Within a 50 nm bandwidth (1525 nm to 1575 nm), we demonstrated a 1 × 2 OPS with splitting ratios of 1:1, 1:1.5, and 1:2; a 1 × 3 OPS with ratios of 1:2:1 and 2:1:2; and a 1 × 4 OPS with ratios of 1:1:1:1 and 2:1:2:1. The target splitting ratios are achieved by optimizing pixel distributions in the coupling region. The dimensions of the designed devices are 1.96 × 1.96 µm², 2.8 × 2.8 µm², and 2.8 × 4.2 µm², respectively. The designed devices achieve transmission efficiencies exceeding 90% and exhibit excellent power splitting ratios (PSRs). Full article

Liquid biopsy (LB) has gained attention as a valuable approach for cancer diagnostics, providing a minimally invasive option compared to conventional tissue biopsies and helping to overcome issues related to patient discomfort and procedural invasiveness. Recent advances in biosensor technologies, particularly photonic sensors, have improved the accuracy, speed, and real-time capabilities for detecting circulating biomarkers in biological fluids. Incorporating these tools into clinical practice facilitates more informed therapeutic choices and contributes to tailoring treatments to individual patient profiles. This review highlights the clinical potential of LB, examines technological limitations, and outlines future research directions. Departing from traditional biosensor focused reviews, it adopts a reverse-mapping approach grounded in clinically relevant tumor biomarkers. Specifically, biomarkers associated with prevalent cancers, such as breast, prostate, and lung cancers, serve as the starting point for identifying the most suitable photonic sensing platforms. The analysis underscores the need to align sensor design with the physicochemical properties of each biomarker and the operational requirements of the application. No photonic platform is universally optimal; rather, each exhibits specific strengths depending on performance metrics such as sensitivity, limit of detection, and easy system integration. Within this framework, the review provides a comprehensive assessment of emerging photonic biosensors and outlines key priorities to support their effective clinical translation in cancer diagnostics. Full article

This study presents a hybrid adaptive control strategy that integrates genetic algorithm (GA) optimization with an adaptive neuro-fuzzy inference system (ANFIS) for precise thermal regulation of single-photon avalanche diodes (SPADs). To address the nonlinear and disturbance-sensitive dynamics of SPAD systems, a performance-oriented dataset is constructed through multi-scenario simulations using settling time, overshoot, and steady-state error as fitness metrics. The genetic algorithm (GA) facilitates broad exploration of the proportional–integral–derivative (PID) controller parameter space while ensuring control stability by discarding low-performing gain combinations. The resulting high-quality dataset is used to train the ANFIS model, enabling real-time, adaptive tuning of PID gains. Simulation results demonstrate that the proposed GA-ANFIS-PID controller significantly enhances dynamic response, robustness, and adaptability over both the conventional Ziegler–Nichols PID and GA-only PID schemes. The controller maintains stability under structural perturbations and abrupt thermal disturbances without the need for offline retuning, owing to the real-time inference capabilities of the ANFIS model. By combining global evolutionary optimization with intelligent online adaptation, this approach improves both accuracy and generalization, offering a practical and scalable solution for SPAD thermal management in demanding environments such as quantum communication, sensing, and single-photon detection platforms. Full article

Polymer-based photonic sensors are emerging as cost-effective, scalable alternatives to conventional silicon and glass photonic platforms, offering unique advantages in flexibility, functionality, and manufacturability. This review provides a comprehensive assessment of recent advances in polymer photonic sensing technologies, focusing on material systems, fabrication techniques, device architectures, and application domains. Key polymer materials, including PMMA, SU-8, polyimides, COC, and PDMS, are evaluated for their optical properties, processability, and suitability for integration into sensing platforms. High-throughput fabrication methods such as nanoimprint lithography, soft lithography, roll-to-roll processing, and additive manufacturing are examined for their role in enabling large-area, low-cost device production. Various photonic structures, including planar waveguides, Bragg gratings, photonic crystal slabs, microresonators, and interferometric configurations, are discussed concerning their sensing mechanisms and performance metrics. Practical applications are highlighted in environmental monitoring, biomedical diagnostics, and structural health monitoring. Challenges such as environmental stability, integration with electronic systems, and reproducibility in mass production are critically analyzed. This review also explores future opportunities in hybrid material systems, printable photonics, and wearable sensor arrays. Collectively, these developments position polymer photonic sensors as promising platforms for widespread deployment in smart, connected sensing environments. Full article

Optical sensors have undergone significant evolution, transitioning from discrete optical microsystems toward sophisticated photonic integrated circuits (PICs) that leverage artificial intelligence (AI) for enhanced functionality. This review systematically explores the integration of optical sensing technologies with AI, charting the advancement from conventional optical microsystems to AI-driven smart devices. First, we examine classical optical sensing methodologies, including refractive index sensing, surface-enhanced infrared absorption (SEIRA), surface-enhanced Raman spectroscopy (SERS), surface plasmon-enhanced chiral spectroscopy, and surface-enhanced fluorescence (SEF) spectroscopy, highlighting their principles, capabilities, and limitations. Subsequently, we analyze the architecture of PIC-based sensing platforms, emphasizing their miniaturization, scalability, and real-time detection performance. This review then introduces the emerging paradigm of in-sensor computing, where AI algorithms are integrated directly within photonic devices, enabling real-time data processing, decision making, and enhanced system autonomy. Finally, we offer a comprehensive outlook on current technological challenges and future research directions, addressing integration complexity, material compatibility, and data processing bottlenecks. This review provides timely insights into the transformative potential of AI-enhanced PIC sensors, setting the stage for future innovations in autonomous, intelligent sensing applications. Full article

This study presents a microfluidic chip platform designed using a multiscale 3D printing strategy for fabricating microfluidic chips with integrated, high-resolution, and customizable membrane structures. By combining two-photon polymerization (2PP) for submicron membrane fabrication with liquid crystal display printing for rapid production of larger components, this approach addresses key challenges in membrane integration, including sealing reliability and the use of transparent materials. Compared to fully 2PP-based fabrication, the multiscale method achieved a 56-fold reduction in production time, reducing total fabrication time to approximately 7.2 h per chip and offering a highly efficient solution for integrating complex structures into fluidic chips. The fabricated chips demonstrated excellent mechanical integrity. Burst pressure testing showed that all samples withstood internal pressures averaging 1.27 ± 0.099 MPa, with some reaching up to 1.4 MPa. Flow testing from ~35 $\mathsf{\mu }$L/min to ~345 $\mathsf{\mu }$L/min confirmed stable operation in 75 $\mathsf{\mu }$m square channels, with no leakage and minimal flow resistance up to ~175 $\mathsf{\mu }$L/min without deviation from the predicted behavior in the 75 $\mathsf{\mu }$m. Membrane-integrated chips exhibited outlet flow asymmetries greater than 10%, indicating active fluid transfer across the membrane and highlighting flow-dependent permeability. Overall, this multiscale 3D printing approach offers a scalable and versatile solution for microfluidic device manufacturing. The method’s ability to integrate precise membrane structures enable advanced functionalities such as diffusion-driven particle sorting and molecular filtration, supporting a wide range of biomedical, environmental, and industrial lab-on-a-chip applications. Full article

In recent years, micro-combs, due to their compact structure and high efficiency, have proven to be a practical solution for optical sources. In this paper, an approach to flexibly modulating micro-combs is proposed, and a simulation platform based on ${\mathrm{Si}}_3{\mathrm{N}}_4$ micro-combs with highly integrated, tunable, and reconfigurable features is built. By means of the Lugiato–Lefever equation model, the dynamic evolution process of micro-combs is analyzed, and a micro-ring resonator is designed with a free spectral range of 7.24 nm, an effective mode area of $1.0829{\mu \mathrm{m}}^2$, and coherent comb lines spanning over 125 THz. Cascaded silicon nitride micro-ring filters are utilized to obtain reconfigurable modulation effects for Kerr-frequency micro-combs. Due to the significance of flexibly controlled optical sources with high-repetition rates and multiple channels for system-on-chip, our proposal has potential in photonic integrated circuit systems, such as high-density photonic computing and large-capacity optical communications, in the future. Full article

Early detection and continuous monitoring of diseases are critical to improving patient outcomes, treatment adherence, and diagnostic accuracy. Traditional melanoma diagnosis relies primarily on visual assessment and biopsy, with reported accuracies ranging from 50% to 90% and significant inter-observer variability. Among emerging diagnostic technologies, Raman spectroscopy has demonstrated considerable promise for non-invasive disease detection, particularly in early-stage skin cancer identification. A portable, real-time Raman spectroscopy system could significantly enhance diagnostic precision, reduce biopsy reliance, and expedite diagnosis. However, miniaturization of Raman spectrometers for portable use faces significant challenges, including weak signal intensity, fluorescence interference, and inherent trade-offs between spectral resolution and the signal-to-noise ratio. Recent advances in silicon photonics present promising solutions by facilitating efficient light collection, enhancing optical fields via high-index-contrast waveguides, and allowing compact integration of photonic components. This work introduces a numerical analysis of an integrated digital Fourier transform spectrometer implemented on a silicon-nitride (SiN) platform, specifically designed for Raman spectroscopy. The proposed system employs a switch-based digital Fourier transform spectrometer architecture coupled with a single optical power meter for detection. Utilizing a regularized regression method, we successfully reconstructed Raman spectra in the 800 cm⁻¹ to 1800 cm⁻¹ range, covering spectra of both benign and malignant skin lesions. Our results demonstrate the capability of the proposed system to effectively differentiate various skin cancer types, highlighting its feasibility as a non-invasive diagnostic sensor. Full article

Tunable photonic devices are increasingly pivotal in modern optical systems, enabling the dynamic control over light propagation, modulation, and filtering. This review systematically explores two prominent classes of materials, thermo-optic and electro-optic, for their roles in such tunable devices. Thermo-optic materials utilize refractive index changes induced by temperature variations, offering simple implementation and broad material compatibility, although often at the cost of slower response times. In contrast, electro-optic materials, particularly those exhibiting the Pockels and Kerr effects, enable rapid and precise refractive index modulation under electric fields, making them suitable for high-speed applications. The paper discusses the underlying physical mechanisms, material properties, and typical figures of merit for each category, alongside recent advancements in organic, polymeric, and inorganic systems. Furthermore, integrated photonic platforms and emerging hybrid material systems are highlighted for their potential to enhance performance and scalability. By evaluating the tradeoffs in speed, power consumption, and integration complexity, this review identifies key trends and future directions for deploying thermo-optic and electro-optic materials in the next generation tunable photonic devices. Full article

Silicon-based optical waveguides exhibit high Brillouin gain, enabling the realization of Brillouin lasers directly on silicon substrates. These lasers hold significant promise for applications such as tunable-frequency laser emission, ultrafast pulse generation via mode-locking techniques, and other advanced photonic functionalities. However, a key challenge in silicon-based Brillouin lasers is the requirement for long waveguide lengths to achieve sufficient optical feedback and reach the lasing threshold. This study proposes a novel floating waveguide architecture designed to significantly enhance the Brillouin gain in silicon-based systems. Furthermore, we introduce a breakthrough method for achieving wide-range phonon frequency tunability, enabling precise control over stimulated Brillouin scattering (SBS) dynamics. By strategically engineering the waveguide geometry (shape and dimensions), we demonstrate a tunable SBS phonon laser, offering a versatile platform for on-chip applications. Additionally, the proposed waveguide system features adjustable operating frequencies, unlocking new opportunities for compact Brillouin devices and integrated microwave photonic signal sources. Full article

Perfusable microvasculature is critical for advancing in vitro tissue models, particularly for neural applications where limited diffusion impairs organoid growth and fails to replicate neurovascular function. This study presents a versatile fabrication platform that integrates mesh-driven design, two-photon lithography (TPL), and modular interfacing to create multi-material, perfusable 3D microvasculatures. Various 2D and 3D capillary paths were test-printed using both polygonal and lattice support strategies. A double-layered capillary scaffold based on the Hilbert curve was used for comparative materials testing. Methods for printing rigid (OrmoComp), moderately stiff hydrogel (polyethylene glycol diacrylate, PEGDA 700), and soft elastomeric (photocurable polydimethylsiloxane, PDMS) materials were developed and evaluated. Cone support structures enabled high-fidelity printing of the softer materials. A compact heat-shrink tubing interface provided leak-free perfusion without bulky fittings. Physiologically relevant flow velocities and Dextran diffusion through the scaffold were successfully demonstrated. Cytocompatibility assays confirmed that all TPL-printed scaffold materials supported human neural stem cell viability. Among peripheral components, lids fabricated via fused deposition modeling designed to hold microfluidic needle adapters exhibited good biocompatibility, while those made using liquid crystal display-based photopolymerization showed significant cytotoxicity despite indirect exposure. Overall, this platform enables creation of multi-material microvascular systems facilitated by TPL technology for complex, 3D neurovascular modeling, blood–brain barrier studies, and integration into vascularized organ-on-chip applications. Full article

This research presents a novel square-shaped photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) sensor, designed using the external metal deposition (EMD) technique, for highly sensitive refractive index (RI) sensing applications. The proposed sensor operates effectively over an RI range of 1.33 to 1.37 and supports both x- polarized and y-polarized modes. It achieves a wavelength sensitivity of 15,800 nm/RIU and 14,300 nm/RIU, and amplitude sensitivities of 11,584 RIU⁻¹ and 11,007 RIU⁻¹, respectively, for the x-pol. and y-pol. The sensor also reports a resolution in the order of 10⁻⁶ RIU and a strong linearity of R² ≈ 0.97 for both polarization modes, indicating its potential for precision detection in complex sensing environments. Beyond the sensor’s structural and performance innovations, this work also explores the future integration of artificial intelligence (AI) into PCF-SPR sensor design. AI techniques such as machine learning and deep learning offer new pathways for sensor calibration, material optimization, and real-time adaptability, significantly enhancing sensor performance and reliability. The convergence of AI with photonic sensing not only opens doors to smart, self-calibrating platforms but also establishes a foundation for next-generation sensors capable of operating in dynamic and remote applications. Full article