Due to the rise of 5G, IoT, AI, and high-performance computing applications, datacenter traffic has grown at a compound annual growth rate of nearly 30%. Furthermore, nearly three-fourths of the datacenter traffic resides within datacenters. The conventional pluggable optics increases at a much slower rate than that of datacenter traffic. The gap between application requirements and the capability of conventional pluggable optics keeps increasing, a trend that is unsustainable. Copackaged optics (CPO) is a disruptive approach to increasing the interconnecting bandwidth density and energy efficiency by dramatically shortening the electrical link length through advanced packaging and co-optimization of electronics and photonics. CPO is widely regarded as a promising solution for future datacenter interconnections, and silicon platform is the most promising platform for large-scale integration. Leading international companies (e.g., Intel, Broadcom and IBM) have heavily investigated in CPO technology, an inter-disciplinary research field that involves photonic devices, integrated circuits design, packaging, photonic device modeling, electronic-photonic co-simulation, applications, and standardization. This review aims to provide the readers a comprehensive overview of the state-of-the-art progress of CPO in silicon platform, identify the key challenges, and point out the potential solutions, hoping to encourage collaboration between different research fields to accelerate the development of CPO technology.
Thermally activated delayed fluorescence (TADF) small molecule bis-[3-(9,9-dimethyl-9,10-dihydroacridine)-phenyl]-sulfone (m-ACSO2) was used as a universal host to sensitize three conventional fluorescent polymers for maximizing the electroluminescent performance. The excitons were utilized via inter-molecular energy transfer and the non-radiative decays were successfully refrained in the condensed states. Therefore, the significant enhancement of the electroluminescent efficiencies was demonstrated. For instance, after doping poly(9,9-dioctylfluorene-co-benzothiadiazole) (F8BT) into m-ACSO2, the external quantum efficiency (EQE) was improved by a factor of 17.0 in the solution-processed organic light-emitting device (OLED), as compared with the device with neat F8BT. In terms of the other well-known fluorescent polymers, i.e., poly (para-phenylene vinylene) copolymer (Super Yellow, SY) and poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene] (MEH-PPV), their EQEs in the devices were respectively enhanced by 70% and 270%, compared with the reference devices based on the conventional host 1,3-di(9H-carbazol-9-yl) benzene (mCP). Besides the improved charge balance in the bipolar TADF host, these were partially ascribed to reduced fluorescence quenching in the mixed films.
Flexible and wearable electronics represent paramount technologies offering revolutionized solutions for medical diagnosis and therapy, nerve and organ interfaces, fabric computation, robot-in-medicine and metaverse. Being ubiquitous in everyday life, piezoelectric materials and devices play a vital role in flexible and wearable electronics with their intriguing functionalities, including energy harvesting, sensing and actuation, personal health care and communications. As a new emerging flexible and wearable technology, fiber-shaped piezoelectric devices offer unique advantages over conventional thin-film counterparts. In this review, we survey the recent scientific and technological breakthroughs in thermally drawn piezoelectric fibers and fiber-enabled intelligent fabrics. We highlight the fiber materials, fiber architecture, fabrication, device integration as well as functions that deliver higher forms of unique applications across smart sensing, health care, space security, actuation and energy domains. We conclude with a critical analysis of existing challenges and opportunities that will be important for the continued progress of this field.
Microwave photonic sensors are promising for improving sensing resolution and speed of optical sensors. In this paper, a high-sensitivity, high-resolution temperature sensor based on microwave photonic filter (MPF) is proposed and demonstrated. A micro-ring resonator (MRR) based on silicon-on-insulator is used as the sensing probe to convert the wavelength shift caused by temperature change to microwave frequency variation via the MPF system. By analyzing the frequency shift with high-speed and high-resolution monitors, the temperature change can be detected. The MRR is designed with multi-mode ridge waveguides to reduce propagation loss and achieves an ultra-high Q factor of 1.01 × 106. The proposed MPF has a single passband with a narrow bandwidth of 192 MHz. With clear peak-frequency shift, the sensitivity of the MPF-based temperature sensor is measured to be 10.22 GHz/℃. Due to higher sensitivity and ultra-narrow bandwidth of the MPF, the sensing resolution of the proposed temperature sensor is as high as 0.019 ℃.
We report a new nBn photodetector (nBn-PD) design based on the InAlSb/AlSb/InAlSb/InAsSb material systems for mid-wavelength infrared (MWIR) applications. In this structure, delta-doped compositionally graded barrier (δ-DCGB) layers are suggested, the advantage of which is creation of a near zero valence band offset in nBn photodetectors. The design of the δ-DCGB nBn-PD device includes a 3 μm absorber layer (n-InAs0.81Sb0.19), a unipolar barrier layer (AlSb), and 0.2 μm contact layer (n-InAs0.81Sb0.19) as well as a 0.116 μm linear grading region (InAlSb) from the contact to the barrier layer and also from the barrier to the absorber layer. The analysis includes various dark current contributions, such as the Shockley–Read–Hall (SRH), trap-assisted tunneling (TAT), Auger, and Radiative recombination mechanisms, to acquire more precise results. Consequently, we show that the method used in the nBn device design leads to diffusion-limited dark current so that the dark current density is 2.596 × 10-8 A/cm2 at 150 K and a bias voltage of - 0.2 V. The proposed nBn detector exhibits a 50% cutoff wavelength of more than 5 μm, the peak current responsivity is 1.6 A/W at a wavelength of 4.5 μm and a - 0.2 V bias with 0.05 W/cm2 backside illumination without anti-reflective coating. The maximum quantum efficiency at 4.5 μm is about 48.6%, and peak specific detectivity (D*) is of 3.37 × 1010 cm·Hz1/2/W. Next, to solve the reflection concern in this nBn devices, we use a BaF2 anti-reflection coating layer due to its high transmittance in the MWIR window. It leads to an increase of almost 100% in the optical response metrics, such as the current responsivity, quantum efficiency, and detectivity, compared to the optical response without an anti-reflection coating layer.
Due to the advantages of low propagation loss, wide operation bandwidth, continuous delay tuning, fast tuning speed, and compact footprints, chirped Bragg grating waveguide has great application potential in wideband phased array beamforming systems. However, the disadvantage of large group delay error hinders their practical applications. The nonlinear group delay spectrum is one of the main factors causing large group delay errors. To solve this problem, waveguides with nonlinear gradient widths are adopted in this study to compensate for the nonlinear effect of the grating apodization on the mode effective index. As a result, a linear group delay spectrum is obtained in the experiment, and the group delay error is halved.
Most learning-based methods previously used in image dehazing employ a supervised learning strategy, which is time-consuming and requires a large-scale dataset. However, large-scale datasets are difficult to obtain. Here, we propose a self-supervised zero-shot dehazing network (SZDNet) based on dark channel prior, which uses a hazy image generated from the output dehazed image as a pseudo-label to supervise the optimization process of the network. Additionally, we use a novel multichannel quad-tree algorithm to estimate atmospheric light values, which is more accurate than previous methods. Furthermore, the sum of the cosine distance and the mean squared error between the pseudo-label and the input image is applied as a loss function to enhance the quality of the dehazed image. The most significant advantage of the SZDNet is that it does not require a large dataset for training before performing the dehazing task. Extensive testing shows promising performances of the proposed method in both qualitative and quantitative evaluations when compared with state-of-the-art methods.
