Analysis of operating limits and combustion state regulation for low-calorific value gases in industrial burners

The effective and efficient utilization of low-calorific value (LCV) gases has gained increasing attention in scientific research and industrial fields. In this study, the combustion characteristics of three LCV gases in practical devices are analyzed by using a nonadiabatic perfectly stirred reactor model. The complete steady-state solution in the temperature-residence time parameter space is obtained with arc-length continuation. The stable operation region is quantified by the eigenvalue analysis. The transition of solution curves is quantified with heat loss coefficient. Five key system parameters are systematically investigated on their effects on stability limits. With the combustion performance being quantified by a combustion state index, a combustion state regulation method is proposed to find the optimal regulation path of system parameters. Active subspace method is further applied to shorten the regulation step by identifying the active direction. The proposed method and findings are useful for optimal regulation of burning LCV gases in industrial burners.     

基于滚动摩擦作用下玉米颗粒在模拟筒仓卸料中的力链分析（网络首发、推荐阅读）

针对颗粒滚动摩擦作用对筒仓中玉米颗粒的力链空间分布进行研究，通过EDEM离散元软件建立筒仓模型与仿真玉米颗粒模型进行卸粮仿真模拟，并与筒仓卸料实验作流态对比，验证模型与仿真结果的准确性。通过对模拟仓进行切片观察和数据处理，对比分析了不同摩擦情况下力链的细观参数随时间演化规律。模拟结果表明：颗粒间摩擦系数越大，卸粮完成的最终时间越长；颗粒间滚动摩擦系数越小，颗粒由整体流转变为管状流的时间越早。对于有漏斗的筒仓来说，减小颗粒间摩擦会改变整体流和管状流之间的极限，从而增加产生管状流的面积。标准滚动摩擦系数下玉米颗粒在卸料过程中会出现起拱-塌陷效应；减小滚动摩擦，玉米颗粒卸料较稳定，未出现起拱的应力突增、以及拱塌陷的应力衰减；增大颗粒间滚动摩擦不但会增加拱效应，且出现成拱高度距离漏斗口更高。     

Oxidation State Modulation of Bismuth for Efficient Electrocatalytic Nitrogen Reduction to Ammonia

Electrocatalytic nitrogen reduction reaction (NRR) is a promising strategy for ammonia (NH₃) production under ambient conditions. However, it is severely impeded by the challenging activation of the NN bond and the competing hydrogen evolution reaction (HER), which makes it crucial to design electrocatalysts rationally for efficient NRR. Herein, the rational design of bismuth (Bi) nanoparticles with different oxidation states embedded in carbon nanosheets (Bi@C) as efficient NRR electrocatalysts is reported. The NRR performance of Bi@C improves with the increase of Bi⁰/Bi³⁺ atomic ratios, indicating that the oxidation state of Bi plays a significant role in electrochemical ammonia synthesis. As a result, the Bi@C nanosheets annealed at 900  ° C with the optimal oxidation state of Bi demonstrate the best NRR performance with a high NH₃ yield rate and remarkable Faradaic efficiency of 15.10  ± 0.43% at − 0.4 V versus RHE. Density functional theory calculations reveal that the effective modulation of the oxidation state of Bi can tune the p-filling of active Bi sites and strengthen adsorption of *NNH, which boost the potential-determining step and facilitate the electrocatalytic NRR under ambient conditions. This work may offer valuable insights into the rational material design by modulating oxidation states for efficient electrocatalysis.     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Precipitous weakening of quartz at the α–β phase inversion

Crystalline quartz has long been identified as among the weakest of abundant crustal minerals. This weakness is particularly evident around the α–β phase inversion at 573°C, in which Si–O bonds undergo a displacive structural transformation from trigonal to hexagonal symmetry. Here we present data using indentation testing methodologies that highlight the precipitous extent of the transformational weakening. Although the indentations are localized over relatively small specimen contact areas, the data quantify the essential deformation and fracture properties of quartz in a predominantly (but not exclusively) compressive stress field, at temperatures and pressures pertinent to conditions in the earth's crust.     

Modulation of electrical transport in calcium cobaltite ceramics and thick films through microstructure control and doping

Ca₃Co₄O₉ is a promising p-type thermoelectric oxide material having intrinsically low thermal conductivity. With low cost and opportunities for automatic large scale production, thick film technologies offer considerable potential for a new generation of micro-sized thermoelectric coolers or generators. Here, based on the chemical composition optimized by traditional solid state reaction for bulk samples, we present a viable approach to modulating the electrical transport properties of screen-printed calcium cobaltite thick films through control of the microstructural evolution by optimized heat-treatment. XRD and TEM analysis confirmed the formation of high-quality calcium cobaltite grains. By creating 2.0 at% cobalt deficiency in Ca_2.7Bi_0.3Co₄O_9+δ, the pressureless sintered ceramics reached the highest power factor of 98.0 μWm^?1 K^-2 at 823 K, through enhancement of electrical conductivity by reduction of poorly conducting secondary phases. Subsequently, textured thick films of Ca_2.7Bi_0.3Co_3.92O_9+δ were efficiently tailored by controlling the sintering temperature and holding time. Optimized Ca_2.7Bi_0.3Co_3.92O_9+δ thick films sintered at 1203 K for 8 h exhibited the maximum power factor of 55.5 μWm^?1 K^-2 at 673 K through microstructure control.     

改进的CAGAN在虚拟试衣中的应用

针对CAGAN（Conditional Analogy GAN）换衣后效果模糊，在目标衣服与原始衣服长短不一致时效果一般，相对目标衣服保留过少的细节等问题做了相关研究并对CAGAN进行了改进，提出了新的虚拟试衣方式。经过改进的CAGAN生成一个粗糙的结果，由该结果得到目标衣服穿在模特身上改变形状后的mask，接下来利用mask对目标衣服进行变形，综合变形的衣服和第一步的结果便得到最终的试衣图像。实验结果表明，该方法解决了前面存在的问题，而且取得了非常好的效果。     

VO2/GaAs异质结的制备及其光电特性研究

采用直流磁控溅射和后退火氧化工艺在p型GaAs单晶衬底上成功制备了n-VO_2/pGaAs异质结,研究了不同退火温度和退火时间对VO_2/GaAs异质结性能的影响,并分析其结晶取向、化学组分、膜层质量以及光电特性。结果表明,在退火时间2 h和退火温度693 K下能得到相变性能最佳的VO_2薄膜,相变前后电阻变化约2个数量级。VO_2/GaAs异质结在308 K、318 K和328 K温度下具有较好的整流特性,对应温度下的阈值跳变电压分别为6.9 V、6.6 V和6.2 V,该结果为基于VO_2相变特性的异质结光电器件的设计与应用提供了可行性。     

调控Al2O3晶型控制MgAl2O4:Mn4+荧光粉中Mn价态研究

Mn⁴⁺激活红光荧光粉是白光半导体发光二极管(wLEDs)领域当前研究热点之一。Mn⁴⁺离子²E→⁴A₂跃迁在铝酸盐中的最短发光波长是在MgAl₂O₄中实现的651 nm发光, 由于其结构中含有形成四面体或八面体配位的两种阳离子格位(Mg²⁺/Al³⁺), 易造成所掺杂锰元素存在多种价态(+2/+4/+3等)。本研究通过改变起始原料中Al₂O₃的晶型(γ/α比例)及退火处理来调控锰离子在MgAl₂O₄晶格中的占据格位, 对其主要存在价态实现调控。采用荧光光谱和紫外-可见-近红外漫反射光谱技术来表征所合成荧光粉中Mn离子的价态及其演变。研究发现, 高α/(α+γ)比铝源促进Mn²⁺形成, 而低α/(α+γ)比铝源促进Mn⁴⁺形成。通过使用高活性纳米γ-Al₂O₃为铝源, 有效抑制了锰离子在MgAl₂O₄中Mg²⁺格位的占据及Mn²⁺离子的形成, 经空气中1550 ℃保温5 h的一次高温热处理即可制备出在可见光区只有Mn⁴⁺红光发光的高纯高亮度MgAl₂O₄:Mn⁴⁺荧光粉。氧化铝晶型影响锰离子掺杂格位和掺杂价态的本质规律是: 氧化铝活性决定实际固溶掺杂反应步骤, 进而影响锰离子掺杂格位和价态。本研究提出的反应步骤调控作为反应气氛、电荷补偿剂、反应温度三种调控方法外的一种新方法, 为Mn⁴⁺激活铝酸盐荧光粉中锰离子掺杂价态调控提供了新思路。     

小微数据包高效无线传输技术的发展和趋势

5G-NR和B5G系统都需能高效地支持小微数据包(块)的传输,且在不同的无线传输技术(如宽带或超低时延)之间快速灵活地切换。系统梳理和比较和小微数据包(块)相关的多种无线传输技术,如两步RACH、预配置授权和公共资源竞争等,分析它们对3GPP各个系统和各个RAN协议的影响和复杂度优劣等,并进一步展望其未来发展和应用趋势。