Novel Compact and low-Cost Ultraweak Fabry-Perot Interferometer as a Highly Sensitive Refractive Index Sensor

A novel compact refractive index (RI) sensor based on an ultra-weak intrinsic fiber Fabry-Perot interferometer (FPI) is proposed and demonstrated, which is simply fabricated by splicing a tiny section of thin-core fiber to a single-mode fiber. Such an FPI exhibits an average RI sensitivity of 240dB/RIU over a wide RI range of 1.3326-1.4305, with a maximum sensitivity of 1110.7dB/RIU at the RI of 1.4305. In addition, the FPI can also achieve the simultaneous measurement of the RI and temperature

High-sensitivity and large-dynamic-range fiber refractometer based on composite-cavity Fabry-Perot structure

Most sensors have the tradeoff dilemma of high sensitivity and large dynamic range. We demonstrate here an all-fiber refractive index sensor based on a composite intrinsic Fabry-Perot interferometer (FPI), which possesses the co-existence advantages of high sensitivity and large dynamic range. Experimental trends are in good agreement with the theoretical predictions. The co-existence of high sensitivity and large dynamic range in a composite FPI is of great significance to practical refractive index measurement

High-sensitivity and large-dynamic-range refractive index sensors employing weak composite Fabry-Perot cavities

Most sensors face a common tradeoff between high sensitivity and large dynamic range. We demonstrate here an all-fiber refractometer based on a dual cavity Fabry-Perot interferometer (FPI), which possesses the advantage of both high sensitivity and large dynamic range. Since the two composite cavities have a large cavity length difference, one can observe both fine and coarse fringes, which correspond to the long cavity and short cavity, respectively. The short cavity FPI and the use of an intensity demodulation method, mean that the individual fine fringe dips correspond to a series of quasi-continuous highly sensitive zones for refractive index measurement. By calculating the parameters of the composite FPI, we find that the range of the ultra-sensitive zones can be considerably adjusted to suite the end requirements. The experimental trends are in good agreement with the theoretical predictions. The co-existence of high sensitivity and large dynamic range in a composite FPI is of great significance to practical RI measurements

DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally, customizing ACO for a specific problem requires the expert design of knowledge-driven heuristics. In this paper, we propose DeepACO, a generic framework that leverages deep reinforcement learning to automate heuristic designs. DeepACO serves to strengthen the heuristic measures of existing ACO algorithms and dispense with laborious manual design in future ACO applications. As a neural-enhanced meta-heuristic, DeepACO consistently outperforms its ACO counterparts on eight COPs using a single neural model and a single set of hyperparameters. As a Neural Combinatorial Optimization method, DeepACO performs better than or on par with problem-specific methods on canonical routing problems. Our code is publicly available at https://github.com/henry-yeh/DeepACO.Comment: Accepted at NeurIPS 202

Modeling of a combined CH₄-assisted solid oxide co-electrolysis and Fischer-Tropsch synthesis system for low-carbon fuel production

10th International Conference on Applied Energy, ICAE 2018, Hong Kong, 22-25 August 2018201906 bcmaVersion of RecordPublishe

Neuroinflammation of traumatic brain injury: Roles of extracellular vesicles

Traumatic brain injury (TBI) is a major cause of neurological disorder or death, with a heavy burden on individuals and families. While sustained primary insult leads to damage, subsequent secondary events are considered key pathophysiological characteristics post-TBI, and the inflammatory response is a prominent contributor to the secondary cascade. Neuroinflammation is a multifaceted physiological response and exerts both positive and negative effects on TBI. Extracellular vesicles (EVs), as messengers for intercellular communication, are involved in biological and pathological processes in central nervous system (CNS) diseases and injuries. The number and characteristics of EVs and their cargo in the CNS and peripheral circulation undergo tremendous changes in response to TBI, and these EVs regulate neuroinflammatory reactions by activating prominent receptors on receptor cells or delivering pro- or anti-inflammatory cargo to receptor cells. The purpose of this review is to discuss the possible neuroinflammatory mechanisms of EVs and loading in the context of TBI. Furthermore, we summarize the potential role of diverse types of cell-derived EVs in inflammation following TBI

Efficient postprocessing technique for fabricating surface nanoscale axial photonics microresonators with subangstrom precision by femtosecond laser

We demonstrated the subangstrom precise correction of surface nanoscale axial photonics (SNAP) micro-resonators by the femtosecond (fs) laser postprocessing technique for the first time. The internal stress can be induced by fs laser inscriptions in the fiber, causing nanoscale effective radius variation (ERV). However, the obtained ultraprecise fabrication usually undergoes multiple tries. Here, we propose a novel postprocessing technique based on the fs laser that significantly reduces the ERV errors and improves the fabrication precision without iterative corrections. The postexposure process is achieved at the original exposure locations using lower pulse energy than that in the initial fabrication process. The results show that the ERV is nearly proportional to the pulse energy of the postexposure process. The slope of the ERV versus the pulse energy is 0.07 Å/nJ. The maximum of the postprocessed ERV can reach 8.0 Å. The repeatability was experimentally verified by accomplishing the correction on three SNAP microresonators with the precision of 0.75 Å. The developed fabrication technique with fs laser enables SNAP microresonators with new breakthrough applications for optomechanics and filters

Topological insulator Bi2Te3 films synthesized by metal organic chemical vapor deposition

Topological insulator (TI) materials such as Bi2Te3 and Bi2Se3 have attracted strong recent interests. Large scale, high quality TI thin films are important for developing TI-based device applications. In this work, structural and electronic properties of Bi2Te3 thin films deposited by metal organic chemical vapor deposition (MOCVD) on GaAs (001) substrates were characterized via X-ray diffraction (XRD), Raman spectroscopy, angle-resolved photoemission spectroscopy (ARPES), and electronic transport measurements. The characteristic topological surface states (SS) with a single Dirac cone have been clearly revealed in the electronic band structure measured by ARPES, confirming the TI nature of the MOCVD Bi2Te3 films. Resistivity and Hall effect measurements have demonstrated relatively high bulk carrier mobility of ~350 cm^2/Vs at 300K and ~7,400 cm^2/Vs at 15 K. We have also measured the Seebeck coefficient of the films. Our demonstration of high quality topological insulator films grown by a simple and scalable method is of interests for both fundamental research and practical applications of thermoelectric and TI materials.Comment: 14 pages, 4 figure

Biomass-derived carbon material as efficient electrocatalysts for the oxygen reduction reaction

Despite the abundance of carbon in nature, a significant portion of the existing biomass carbon materials in livestock, agriculture, and marine fishery industry are currently being wasted. Utilizing sustainable carbon materials as an alternative to noble Pt-based catalysts is crucial step to convert widely available and low-cost biomass resources into clean energy systems. Therefore, the rational synthesis of carbon-based catalysts for oxygen reduction reaction (ORR) has become a hot research focus in the field of electrochemistry. In this study, the recent progress in the synthesis of ORR electrocatalysts using sustainable biomass resources was reviewed; the activation and synthesis strategies of various biomass resources, as well as the microstructure and oxygen reduction performance of the prepared carbon-based catalysts were investigated. It is hoped that this review article will promote the understanding of various parameters from biomass as precursors for catalyst preparation and make contribute to the transition of biomass resources from the wasted carbon materials to the main catalysts in future energy devices.</p