Evaluation of the Oxidation Reactivity and Behavior of Exhaust Soot Particles from Diesel Engines with Different Emission Levels

The aim of this study was to investigate the oxidation reactivity and behavior of exhaust particulate matter(PM)from diesel engines.PM samples from two diesel engines(1K,CY4102)with different emission levels were collected by a thermophoretic system and a quartz filter.The oxidation reactivity,oxidation behaviors,and physicochemical properties of the PM samples were analyzed using thermogravimetric analysis(TGA),high-resolution transmission electron microscopy(HRTEM),Fourier-transform infrared spectrometry(FTIR),and Raman spectroscopy.The results showed that there was a great difference in the oxidation reactivity of soot particles emitted by the two different diesel engines.A qualitative analysis of the factors influencing oxidation reactivity showed that the nanostructure,degree of graphitization,and relative concentration of aliphatic C—H functional groups were the most important factors,whereas no significant correlation was found between the primary particle size and activation energy of the diesel soot.Based on the oxidation behavior analysis,the diesel soot particles exhibited both internal and surface oxidation modes during the oxidation process.Surface oxidation was dominant during the initial stage,and as oxidation progressed,the mode gradually changed to internal oxidation.Internal oxidation mode of soot particles from the 1K engine was significantly higher than that of CY4102.

Performance, Combustion and Emission Characteristics of Oxygenated Diesel in DI Engines: A Critical Review

The transition from non-renewable to renewable energy sources is a significant challenge of our time. In the fuel industry, oxygenated additives such as butanol are transforming conventional fuels into renewable biofuels. This technology has been utilized in reciprocating engines for decades. This paper reviews the viability of using an n-butanol blend as a short-term replacement for diesel by analyzing its physical and chemical properties, combustion, performance, and emission characteristics in compression ignition (CI) engines under various conditions, including variable load, speed, acceleration, and both stationary and transient cycles. N-Butanol exhibits higher viscosity, better lubricity, higher heating value, improved blend stability, enhanced cold-flow properties, and higher density. These factors influence spray formation, injection timing, atomization, and combustion characteristics. Its higher oxygen content improves the diffusion combustion stage and efficiency. Adding 5% and 10% n-butanol to diesel increases pressure and apparent heat release rate, slightly reduces temperature, and improves thermal efficiency, with mixed effects on CO and THC emissions and a notable decrease in particulate matter emissions. Fuel consumption increases, while the impact on NOx emissions varies. A 10% butanol blend is considered optimal for enhancing performance and reducing particulate emissions without significantly affecting NOx emissions. Blending up to 40% butanol with diesel does not require engine modifications or ECU recalibrations in engines calibrated for pure diesel. Due to its advantageous properties and performance, n-butanol is recommended as a superior alcohol-diesel blend than ethanol for short-term diesel replacement.

Engines of Advancement

Chinese investment contributes to the industrialisation of Africa.Hasnaine Yavarhoussen,CEO of Groupe Filatex,the leading private energy producer in Madagascar,travelled to Beijing on the occasion of the 2024 Summit of the Forum on China-Africa Cooperation(FOCAC).As a key economic player in Madagascar and the African continent,Groupe Filatex participated in this high-level forum as part of the official Malagasy economic delegation.

A Study on How Urban Rail Operators Can Secure New Growth Engines for the Future Approach: The Case of Underground Urban Logistics System

Seoul Metro is Seoul’s leading metro company, transporting up to 3 billion people annually. However, future ridership is expected to plummet due to an aging and shrinking population with one of the fastest declining total fertility rates in the world. The COVID-19 pandemic in 2019 accelerated this phenomenon. On the contrary, the e-commerce and home delivery industries have developed significantly since COVID-19. Seoul’s current logistics infrastructure cannot handle it. Under the inflection point of declining passenger transportation demand and increasing urban logistics demand, urban rail operators need new growth engines. Therefore, it is necessary to consider the introduction of an UULS (underground urban logistics system) that transports parcels instead of passengers through urban railways. If the UULS becomes a reality, it can be expected to secure scarce logistics land in cities, protect the environment and prevent traffic congestion by operating eco-friendly mass urban transportation, and acquire new revenue sources for urban rail operators. The UULS’s B/C ratio is 1.32. The sensitivity analysis shows that the ratio is above 1 in most cases where the unit cost of transportation is not significantly reduced.

基于C#语言与ArcGIS Engine 的开采沉陷预计系统开发

为了预计煤层开采引发的地表移动变形,基于极坐标系的概率积分法,借助C#语言和ArcGIS Engine组件工具库设计开发了矿区开采沉陷预计系统。开采沉陷预计系统适用于不规则形状的开采工作面,能够对开采区域地表各点不同开采时间后的下沉、水平移动、水平变形、倾斜、曲率进行预计,并对预计结果进行后处理,绘制地表移动变形云图。以陕西省某矿308工作面开采为例,根据工作面的开采条件、地层岩性等特征选取概率积分参数并代入本系统进行地表移动变形预计,将结果与实测地表移动变形进行对比分析。结果表明:使用该系统预计的地表下沉值与实测下沉值的相对误差小于10%,且下沉盆地形态与实际基本吻合,该系统的预计结果较为可靠,对矿区的开采沉陷预计具有一定的适用性。

基于Google earth engine渭-库绿洲果园遥感提取

针对干旱区果园大面积遥感提取困难、识别精度低等问题,本研究基于GEE(Google earth engine)平台,综合应用Sentinel-1/Sentinel-2影像构建特征集。通过对比原始特征组合、Jeffries-Matusita(J-M)距离、属性重要度3种优化方式,结合随机森林(Random forest,RF)分类方法,对比得到最佳优化方式,探索果园最优分类特征集。结果表明:识别效果最好的方案为G17 JM,总体精度为91.25%,kappa系数为0.89,面积精度为82.55%。最优特征集为B8_asm、B8_ent、B8_idm、NDVI re3、B6、B7、a、e、b、EVI、B11、B8A、B8、VV。使用J-M距离进行特征集优化,有效降低数据量、提高计算效率,更有利于精确遥感识别果园种植面积。表明GEE快速、准确获取果园种植面积的可行性,为获取果园动态变化提供强有力的基础。

基于Unreal Engine的虚拟现实技术在元宇宙图书馆中的应用

以虚拟现实技术作为研究切入点,探索元宇宙图书馆建设的技术实现路径。通过文献调研对比分析现有的虚拟现实技术,寻找一种适合高校图书馆自主研发的技术实现方法,并通过具体案例验证该方法的现实可行性。研究发现基于Unreal Engine的虚拟现实技术具有低成本、低代码量、可扩展等优点,适合经费少、计算机人才短缺的高校图书馆。对高校图书馆推进元宇宙图书馆建设具有一定的参考价值。

Biomimetic natural biomaterials for tissue engineering and regenerative medicine:new biosynthesis methods,recent advances,and emerging applications

Biomimetic materials have emerged as attractive and competitive alternatives for tissue engineering(TE)and regenerative medicine.In contrast to conventional biomaterials or synthetic materials,biomimetic scaffolds based on natural biomaterial can offer cells a broad spectrum of biochemical and biophysical cues that mimic the in vivo extracellular matrix(ECM).Additionally,such materials have mechanical adaptability,micro-structure interconnectivity,and inherent bioactivity,making them ideal for the design of living implants for specific applications in TE and regenerative medicine.This paper provides an overview for recent progress of biomimetic natural biomaterials(BNBMs),including advances in their preparation,functionality,potential applications and future challenges.We highlight recent advances in the fabrication of BNBMs and outline general strategies for functionalizing and tailoring the BNBMs with various biological and physicochemical characteristics of native ECM.Moreover,we offer an overview of recent key advances in the functionalization and applications of versatile BNBMs for TE applications.Finally,we conclude by offering our perspective on open challenges and future developments in this rapidly-evolving field.

Compositional and Hollow Engineering of Silicon Carbide/Carbon Microspheres as High-Performance Microwave Absorbing Materials with Good Environmental Tolerance

Microwave absorbing materials(MAMs)characterized by high absorption efficiency and good environmental tolerance are highly desirable in practical applications.Both silicon carbide and carbon are considered as stable MAMs under some rigorous conditions,while their composites still fail to produce satisfactory microwave absorption performance regardless of the improvements as compared with the individuals.Herein,we have successfully implemented compositional and structural engineering to fabricate hollow Si C/C microspheres with controllable composition.The simultaneous modulation on dielectric properties and impedance matching can be easily achieved as the change in the composition of these composites.The formation of hollow structure not only favors lightweight feature,but also generates considerable contribution to microwave attenuation capacity.With the synergistic effect of composition and structure,the optimized SiC/C composite exhibits excellent performance,whose the strongest reflection loss intensity and broadest effective absorption reach-60.8 dB and 5.1 GHz,respectively,and its microwave absorption properties are actually superior to those of most SiC/C composites in previous studies.In addition,the stability tests of microwave absorption capacity after exposure to harsh conditions and Radar Cross Section simulation data demonstrate that hollow SiC/C microspheres from compositional and structural optimization have a bright prospect in practical applications.

基于ArcGIS Engine的风暴潮淹没适应气候变化策略辅助决策系统开发

本研究构建了基于ArcGIS Engine的风暴潮淹没适应气候变化策略辅助决策系统,将风暴潮淹没适应气候变化策略研究过程流程化和简单化,并提供7个面向用户开放的决策端口,辅助决策者做出科学的风暴潮淹没适应气候变化策略选择。以青岛市风暴潮淹没为例的系统应用,进一步验证了该系统能够切实提高研究过程的分析效率,为中国沿海地区的适应风暴潮灾害提供技术支持。

基于Google Earth Engine的八门湾红树林年际变化监测

该文基于Google Earth Engine(GEE)云平台,选择Landsat系列卫星数据,采用支持向量机(support vector machines,SVM)分类方法对八门湾地区进行地物类型分类,并基于分类结果监测该地区红树林年际变化。结果表明:红树林与陆地树木之间除红外波段外反射光谱曲线极其相似,利用红外波段特征指数并结合地形数据可进行有效区分,分类结果总体精度达到0.91;研究区红树林存在先减少后增加的变化趋势,在2009—2013年减少,2014—2016年基本保持不变,2017—2021年缓慢增加,红树林增加和坑塘减少时期是在“南红北柳”政策颁布之后,说明退塘还林政策成效显著;红树林主要是和坑塘相互变化转移,说明毁林造塘和退塘还林是影响该地区红树林变化的重要因素。红树林年际变化监测结果可以精细化分析红树林演变过程,并能精确量化红树林与其他土地类型的转化过程,从而在经济、政策上分析红树林演变因素,更有效地保护红树林。

基于Google Earth Engine遥感大数据云平台的盐城盐沼植被精细分类研究

江苏省自1982年开始引种互花米草以来,滨海盐沼植被景观格局发生了巨大变化,芦苇和互花米草面积不断增长,挤占了碱蓬生态位,破坏了生态系统平衡。滨海盐沼湿地是三大蓝碳生态系统之一,具有高固碳和缓解温室效应的生态功能。利用遥感云平台手段监测滨海盐沼植被时空动态变化规律,可为滨海盐沼湿地生态系统保护以及修复提供科学支撑。本文选取植被类型丰富的江苏沿海地区为研究区,基于Google Earth Engine(GEE)平台,选取2000-2020年的Landsat 5、Landsat 7、Landsat 8以及Sentinel-2影像,提出了一种湿地植被提取方法。首先,构建盐城盐沼湿地地表覆盖分类体系,选取样本点,计算特征指数,进行地物分类;然后,利用时间谐波分析法对盐沼植被归一化植被指数(NDVI)变化特征进行分析,确定三类盐沼植被的物候差异;最后,基于物候特征,利用随机森林(Random Forest,RF)分类法提取盐城滨海湿地盐沼植被地表覆盖信息。结果表明:(1)相较传统监测方法,本文所构建的滨海盐沼植被精细化提取方法能够对滨海盐沼植被进行有效细分和监测;(2)2000-2020年,芦苇和互花米草面积呈扩张趋势,碱蓬面积不断缩减;(3)盐城三种典型盐沼植被NDVI值呈现不同变化特征;(4)降水对盐沼植被生长的影响较为显著,气温对盐沼植被生长的直接影响较小。研究结果可为盐城盐沼湿地自然遗产保护以及湿地生态可持续发展提供科学支撑。

Ionization Engineering of Hydrogels Enables Highly Efficient Salt‑Impeded Solar Evaporation and Night‑Time Electricity Harvesting

Interfacial solar evaporation holds immense potential for brine desalination with low carbon footprints and high energy utilization.Hydrogels,as a tunable material platform from the molecular level to the macroscopic scale,have been considered the most promising candidate for solar evaporation.However,the simultaneous achievement of high evaporation efficiency and satisfactory tolerance to salt ions in brine remains a challenging scientific bottleneck,restricting the widespread application.Herein,we report ionization engineering,which endows polymer chains of hydrogels with electronegativity for impeding salt ions and activating water molecules,fundamentally overcoming the hydrogel salt-impeded challenge and dramatically expediting water evaporating in brine.The sodium dodecyl benzene sulfonate-modified carbon black is chosen as the solar absorbers.The hydrogel reaches a ground-breaking evaporation rate of 2.9 kg m−2 h−1 in 20 wt%brine with 95.6%efficiency under one sun irradiation,surpassing most of the reported literature.More notably,such a hydrogel-based evaporator enables extracting clean water from oversaturated salt solutions and maintains durability under different high-strength deformation or a 15-day continuous operation.Meantime,on the basis of the cation selectivity induced by the electronegativity,we first propose an all-day system that evaporates during the day and generates salinity-gradient electricity using waste-evaporated brine at night,anticipating pioneer a new opportunity for all-day resource-generating systems in fields of freshwater and electricity.

Interface Engineering of Titanium Nitride Nanotube Composites for Excellent Microwave Absorption at Elevated Temperature

Currently,the microwave absorbers usually suffer dreadful electromagnetic wave absorption(EMWA)performance damping at elevated temperature due to impedance mismatching induced by increased conduction loss.Consequently,the development of high-performance EMWA materials with good impedance matching and strong loss ability in wide temperature spectrum has emerged as a top priority.Herein,due to the high melting point,good electrical conductivity,excellent environmental stability,EM coupling effect,and abundant interfaces of titanium nitride(TiN)nanotubes,they were designed based on the controlling kinetic diffusion procedure and Ostwald ripening process.Benefiting from boosted heterogeneous interfaces between TiN nanotubes and polydimethylsiloxane(PDMS),enhanced polarization loss relaxations were created,which could not only improve the depletion efficiency of EMWA,but also contribute to the optimized impedance matching at elevated temperature.Therefore,the TiN nanotubes/PDMS composite showed excellent EMWA performances at varied temperature(298-573 K),while achieved an effective absorption bandwidth(EAB)value of 3.23 GHz and a minimum reflection loss(RLmin)value of−44.15 dB at 423 K.This study not only clarifies the relationship between dielectric loss capacity(conduction loss and polarization loss)and temperature,but also breaks new ground for EM absorbers in wide temperature spectrum based on interface engineering.

Frilled Lizard Optimization: A Novel Bio-Inspired Optimizer for Solving Engineering Applications

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.

Biomaterials and tissue engineering in traumatic brain injury:novel perspectives on promoting neural regeneration

Traumatic brain injury is a serious medical condition that can be attributed to falls, motor vehicle accidents, sports injuries and acts of violence, causing a series of neural injuries and neuropsychiatric symptoms. However, limited accessibility to the injury sites, complicated histological and anatomical structure, intricate cellular and extracellular milieu, lack of regenerative capacity in the native cells, vast variety of damage routes, and the insufficient time available for treatment have restricted the widespread application of several therapeutic methods in cases of central nervous system injury. Tissue engineering and regenerative medicine have emerged as innovative approaches in the field of nerve regeneration. By combining biomaterials, stem cells, and growth factors, these approaches have provided a platform for developing effective treatments for neural injuries, which can offer the potential to restore neural function, improve patient outcomes, and reduce the need for drugs and invasive surgical procedures. Biomaterials have shown advantages in promoting neural development, inhibiting glial scar formation, and providing a suitable biomimetic neural microenvironment, which makes their application promising in the field of neural regeneration. For instance, bioactive scaffolds loaded with stem cells can provide a biocompatible and biodegradable milieu. Furthermore, stem cells-derived exosomes combine the advantages of stem cells, avoid the risk of immune rejection, cooperate with biomaterials to enhance their biological functions, and exert stable functions, thereby inducing angiogenesis and neural regeneration in patients with traumatic brain injury and promoting the recovery of brain function. Unfortunately, biomaterials have shown positive effects in the laboratory, but when similar materials are used in clinical studies of human central nervous system regeneration, their efficacy is unsatisfactory. Here, we review the characteristics and properties of various bioactive materials, followed by the introduction of applications based on biochemistry and cell molecules, and discuss the emerging role of biomaterials in promoting neural regeneration. Further, we summarize the adaptive biomaterials infused with exosomes produced from stem cells and stem cells themselves for the treatment of traumatic brain injury. Finally, we present the main limitations of biomaterials for the treatment of traumatic brain injury and offer insights into their future potential.

基于Google Earth Engine的前郭县春季农田覆膜提取

本文基于Google Earth Engine(GEE)云平台,综合考虑光学影像的波段反射率、光谱指数特征和雷达影像的极化、纹理特征,分别构建仅使用光学特征、仅使用雷达特征以及光学和雷达特征组合3种特征输入组合;根据精度确定最佳输入特征后,分别结合机器学习中的分类与回归树、支持向量机、最小距离分类法、梯度提升树和随机森林5种方法建立覆膜提取模型,依据结果精度评估不同方法的性能,并基于最优化模型提取出最终的覆膜农田面积。结果表明:①最佳输入特征为波段反射率特征+光谱指数特征+极化特征+纹理特征;②采用随机森林方法建立的模型精度最高,研究区I的总体精度达到了95.84%,Kappa系数为0.95,地物错分率为1.2%,明显优于其他4种方法(地物错分率较分类与回归树、支持向量机、最小距离和梯度提升树法降低0.8%、7.3%、38.0%和0.3%),研究区II的验证精度达到了87.84%,证明该模型在覆膜提取中可以取得更加准确的结果;③使用本文方法得到2022年研究区I覆膜农田面积为1302.48 km2,估算地膜使用量约为7585.62 t。本文综合考虑光学和雷达影像在地物识别中的特点建立模型,可以准确、高效的识别农田地膜,掌握地膜面积,对环境治理与防治具有重要意义。

基于ArcGIS Engine的乡镇区域洪灾应急路径规划和制图系统设计与实现

近年来,极端天气引起的洪涝灾害频繁发生,给人民生命财产安全造成巨大威胁。乡镇区域由于基础设施不够完善、应急救援信息化建设相对薄弱,是人员、经济损失最为严重的区域。针对上述问题,基于ArcGIS Engine设计并开发了乡镇区域洪灾应急路径规划和制图系统,通过设计灾区信息查询、道路更新、救援路径规划、应急地图制图和灾情统计等功能,优化救援路径规划方案,提高应急地图制图效率,为乡镇区域洪灾应急救援提供支持和服务。

Phase-engineering modulation of Mn-based oxide cathode for constructing super-stable sodium storage

The Mn-based oxide cathode with enriched crystal phase structure and component diversity can provide the excellent chemistry structure for Na-ion batteries.Nevertheless,the broad application prospect is obstructed by the sluggish Na^(+)kinetics and the phase transitions upon cycling.Herein,we establish the thermodynamically stable phase diagram of various Mn-based oxide composites precisely controlled by sodium content tailoring strategy coupling with co-doping and solid-state reaction.The chemical environment of the P2/P'3 and P2/P3 biphasic composites indicate that the charge compensation mechanism stems from the cooperative contribution of anions and cations.Benefiting from the no phase transition to scavenge the structure strain,P2/P'3 electrode can deliver long cycling stability(capacity retention of 73.8%after 1000 cycles at 10 C)and outstanding rate properties(the discharge capacity of 84.08 mA h g^(-1)at 20 C)than P2/P3 electrode.Furthermore,the DFT calculation demonstrates that the introducing novel P'3 phase can significantly regulate the Na^(+)reaction dynamics and modify the local electron configuration of Mn.The effective phase engineering can provide a reference for designing other high-performance electrode materials for Na-ion batteries.

From VIB‑to VB‑Group Transition Metal Disulfides:Structure Engineering Modulation for Superior Electromagnetic Wave Absorption

The laminated transition metal disulfides(TMDs),which are well known as typical two-dimensional(2D)semiconductive materials,possess a unique layered structure,leading to their wide-spread applications in various fields,such as catalysis,energy storage,sensing,etc.In recent years,a lot of research work on TMDs based functional materials in the fields of electromagnetic wave absorption(EMA)has been carried out.Therefore,it is of great significance to elaborate the influence of TMDs on EMA in time to speed up the application.In this review,recent advances in the development of electromagnetic wave(EMW)absorbers based on TMDs,ranging from the VIB group to the VB group are summarized.Their compositions,microstructures,electronic properties,and synthesis methods are presented in detail.Particularly,the modulation of structure engineering from the aspects of heterostructures,defects,morphologies and phases are systematically summarized,focusing on optimizing impedance matching and increasing dielectric and magnetic losses in the EMA materials with tunable EMW absorption performance.Milestones as well as the challenges are also identified to guide the design of new TMDs based dielectric EMA materials with high performance.