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37 pages, 4553 KiB

Open AccessReview

Advances in Nanostructured Electrodes for Solid Oxide Cells by Infiltration or Exsolution

by Mingyue Dai, Futao Li, Shujuan Fang, Dedong He, Jichang Lu, Yu Zhang, Xiaohua Cao, Jiangping Liu, Dingkai Chen and Yongming Luo

Materials 2025, 18(8), 1802; https://doi.org/10.3390/ma18081802 - 15 Apr 2025

Cited by 1 | Viewed by 980

Abstract

Solid oxide cells (SOCs) are highly efficient and versatile devices capable of utilizing a variety of fuels, presenting promising solutions for energy conversion and renewable resource utilization. There is an urgent need for the strategic design of robust and high-efficiency materials to enhance both conversion and energy efficiencies before SOCs can be applied for large-scale industrial production. Nanocomposite electrodes, especially those fabricated through infiltration and metal nanoparticle exsolution, have emerged as highly active electrocatalytic materials that significantly improve the performance and durability of SOCs. This review systematically summarizes and analyzes recent advances in the nanoscale architecture of electrode materials fabricated via common nanoengineering strategies, including infiltration and in situ exsolution, with applications in CO₂/H₂O reduction, hydrocarbon electrochemical oxidation, solid oxide fuel cells, and reversible operation. Finally, this review highlights existing bottlenecks and promising breakthroughs in common nanotechnologies, aiming to provide useful references for the rational design of nanomaterials for SOCs. Full article

(This article belongs to the Special Issue Preparation and Optimization of Solid Oxide Fuel Cell Electrode and Electrolyte Materials)

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15 pages, 3364 KiB

Open AccessArticle

Resident Satisfaction of Urban Green Spaces through the Lens of Landsenses Ecology

by Sinan He, Dingkai Chen, Xiaoqi Shang, Linwei Han and Longyu Shi

Int. J. Environ. Res. Public Health 2022, 19(22), 15242; https://doi.org/10.3390/ijerph192215242 - 18 Nov 2022

Cited by 16 | Viewed by 3663

Abstract

Residents’ satisfaction of urban green space has been widely detected in living environments around the world. Most previous reports were performed with objective indicators to reflect the characteristics of vegetation and landscapes of residential green space. However, subjective senses as impact factors in the evaluation of residents’ satisfaction based on landsenses ecology are scarce. To address this, in this study, physical perception, aesthetic cognition, and psychological cognition as latent variables in a structural equation model were investigated to determine the residents’ satisfaction in Xiamen, in southeast China, a famously high green space coverage region. The results indicate that physical perception is the fundamental condition to improve residents’ satisfaction, while aesthetic cognition and psychological cognition are the direct factors that influenced residents’ satisfaction. Residents exhibit a preference for the residential green space which contains more biodiversity and landscape diversity, a higher biomass, and greater openness. In addition, the residents’ perception significantly related to greenspace characteristics. The results provide a scientific basis for urban green space planning and optimization of ecological resources’ allocation. Full article

(This article belongs to the Special Issue 2nd Edition of Urban Green Spaces)

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13 pages, 1902 KiB

Open AccessFeature PaperArticle

Occurrence, Distribution and Ecological Risk Assessment of Contaminants in Baiyangdian Lake, China

by Sinan He, Mengjing Lin, Longyu Shi and Dingkai Chen

Water 2022, 14(21), 3352; https://doi.org/10.3390/w14213352 - 22 Oct 2022

Cited by 11 | Viewed by 2366

Abstract

Understanding the ecosystem risk of contaminants in the surface water of lakes in scenic areas is important for environmental management. Here, a comprehensive ecological risk assessment evaluation method was established to assess the ecological risk of 14 water quality indicators of Baiyangdian Lake in the spring, summer, and autumn. The results show that the indices of ammonia nitrogen and permanganate exceed the Class III standard limit for water quality. Baiyangdian Lake is generally in a state of mesotrophication, and some areas are slightly eutrophic; the degree of eutrophication is higher in the summer and autumn than in the spring. The lake water at the inlet is eutrophic and polluted, with an inferior water quality. Heavy metals are almost not detected in Baiyangdian Lake. The heavy metal pollution indices of Nanliuzhuang and Caiputai are slightly higher than those of other areas. The ecological risk quotient of petroleum is high. The comprehensive ecological risk of the Baiyangdian Lake is at Level 4, owing to the continuous development of aquaculture and tourism in recent years. We should start the monitoring, management, and strengthening of water quality supervision to achieve the ecological and environmental planning goals of Baiyangdian Lake. Full article

(This article belongs to the Special Issue Pollution Control and Ecological Restoration in Freshwater and Marine Systems)

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14 pages, 4034 KiB

Open AccessArticle

Cyber Security Tool Kit (CyberSecTK): A Python Library for Machine Learning and Cyber Security

by Ricardo A. Calix, Sumendra B. Singh, Tingyu Chen, Dingkai Zhang and Michael Tu

Information 2020, 11(2), 100; https://doi.org/10.3390/info11020100 - 11 Feb 2020

Cited by 15 | Viewed by 13880

Abstract

The cyber security toolkit, CyberSecTK, is a simple Python library for preprocessing and feature extraction of cyber-security-related data. As the digital universe expands, more and more data need to be processed using automated approaches. In recent years, cyber security professionals have seen opportunities to use machine learning approaches to help process and analyze their data. The challenge is that cyber security experts do not have necessary trainings to apply machine learning to their problems. The goal of this library is to help bridge this gap. In particular, we propose the development of a toolkit in Python that can process the most common types of cyber security data. This will help cyber experts to implement a basic machine learning pipeline from beginning to end. This proposed research work is our first attempt to achieve this goal. The proposed toolkit is a suite of program modules, data sets, and tutorials supporting research and teaching in cyber security and defense. An example of use cases is presented and discussed. Survey results of students using some of the modules in the library are also presented. Full article

(This article belongs to the Special Issue Machine Learning with Python)

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9 pages, 2845 KiB

Open AccessArticle

Widely Tunable Monolithic Mid-Infrared Quantum Cascade Lasers Using Super-Structure Grating Reflectors

by Dingkai Guo, Jiun-Yun Li, Liwei Cheng, Xing Chen, Terry Worchesky and Fow-Sen Choa

Photonics 2016, 3(2), 25; https://doi.org/10.3390/photonics3020025 - 3 May 2016

Cited by 7 | Viewed by 6047

Abstract

A monolithic, three-section, and widely tunable mid-infrared (mid-IR) quantum cascade laser (QCL) is demonstrated. This electrically tuned laser consists of a gain section placed between two super structure grating (SSG) distributed Bragg reflectors (DBRs). By varying the injection currents to the two grating sections of this device, its emission wavelength can be tuned from 4.58 μm to 4.77 μm (90 cm⁻¹) with a supermode spacing of 30 nm. This type of SSG-DBR QCLs can be a compact replacement for the external cavity QCL. It has great potential to achieve gap-free and even further tuning ranges for sensor applications. Full article

(This article belongs to the Special Issue Quantum Cascade Lasers - Advances and New Applications)

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