Theoretical insights into the role of defects in the optimization of the electrochemical capacitance of graphene

Graphene-based frameworks suffer from a low quantum capacitance due to graphene’s Dirac point at the Fermi level.This theoretical study investigated the effect structural defects,nitrogen and boron doping,and surface epoxy/hydroxy groups have on the electronic structure and capacitance of graphene.Density functional theory calculations reveal that the lowest energy configurations for nitrogen or boron substitutional doping occur when the dopant atoms are segregated.This elucidates why the magnetic transition for nitrogen doping is experimentally only observed at higher doping levels.We also highlight that the lowest energy configuration for a single vacancy defect is magnetic.Joint density functional theory calculations show that the fixed band approximation becomes increasingly inaccurate for electrolytes with lower dielectric constants.The introduction of structural defects rather than nitrogen or boron substitutional doping,or the introduction of adatoms leads to the largest increase in density of states and capacitance around graphene’s Dirac point.However,the presence of adatoms or substitutional doping leads to a larger shift of the potential of zero charge away from graphene’s Dirac point.

An adaptive fuel cell hybrid vehicle propulsion sizing model

As we enter the age of electrochemical propulsion,there is an increasing tendency to discuss the viability or otherwise of different electrochemical propulsion systems in zero-sum terms.These discussions are often grounded in a specific use case;however,given the need to electrify the wider transport sector it is evident that we must consider systems in a holistic fashion.When designed adequately,the hybridisation of power sources within automotive applications has been demonstrated to positively impact fuel cell efficiency,durability,and cost,while having potential benefits for the safety of vehicles.In this paper,the impact of the fuel cell to battery hybridisation degree is explored through the key design parameter of system mass.Different fuel cell electric hybrid vehicle(FCHEV)scenarios of various hydridisation degrees,including light-duty vehicles(LDVs),Class 8 heavy goods vehicles(HGVs),and buses are modelled to enable the appropriate sizing of the proton exchange membrane(PEMFC)stack and lithium-ion battery(LiB)pack and additional balance of plant.The operating conditions of the modelled PEMFC stack and battery pack are then varied under a range of relevant drive cycles to identify the relative performance of the systems.By extending the model further and incorporating a feedback loop,we are able to remove the need to include estimated vehicle masses a priori enabling improving the speed and accuracy of the model as an analysis tool for vehicle mass and performance estimation.

Thickness-averaged model for numerical simulation of electroosmotic flow in three-dimensional microfluidic chips

The microfiuidic system is a multi-physics interaction field that has at- tracted great attention. The electric double layers and electroosmosis are important flow-electricity interaction phenomena. This paper presents a thickness-averaged model to solve three-dimensional complex electroosmotic flows in a wide-shallow microchan- nel/chamber combined （MCC） chip based on the Navier-Stokes equations for the flow field and the Poisson equation to the electric field. Behaviors of the electroosmotic flow, the electric field, and the pressure are analyzed. The quantitative effects of the wall charge density （or the zeta potential） and the applied electric field on the electroosmotic flow rate are investigated. The two-dimensional thickness-averaged flow model greatly simplifies the three-dimensional computation of the complex electroosmotic flows, and correctly reflects the electrookinetic effects of the wall charge on the flow. The numerical results indicate that the electroosmotic flow rate of the thickness-averaged model agrees well with that of the three-dimensional slip-boundary flow model. The flow streamlines and pressure distribution of these two models are in qualitative agreement.

Vehicles PEMFC Power System Mathematical Model for Integrated Design

In this paper, the mathematical dynamical model of a PEMFC （proton exchange membrane fuel cells） stack, integrated with an automotive synchronous electrical power drive, developed in Matlab environment, is shown. Lots of simulations have been executed in many load conditions. In this paper, the load conditions regarding an electrical vehicle for disabled people is reported. The innovation in this field concerns the integration, in the PEMFC stack mathematical dynamic model, of a synchronous electrical power drive for automotive purposes. Goal of the simulator design has been to create an useful tool which is able to evaluate the behaviour of the whole system so as to optimize the components choose. As regards the simulations with a synchronous electrical power drive, the complete mathematical model allows to evaluate the PEMFC stack performances and electrochemical efficiency.

Electroosmotic flow of Eyring fluid in slit microchannel with slip boundary condition

In consideration of the electroosmotic flow in a slit microchannel, the con-stitutive relationship of the Eyring fluid model is utilized. Navier＇s slip condition is used as the boundary condition. The governing equations are solved analytically, yielding the velocity distribution. The approximate expressions of the velocity distribution are also given and discussed. Furthermore, the effects of the dimensionless parameters, the electrokinetic parameter, and the slip length on the flow are studied numerically, and appropriate conclusions are drawn.

Co-flocculation mechanism and physical model

Analysed and summarized the dynamics and chemical factors in the co (co-agulation)-flocculation process. A completely new definition for co-flocculation was given. If a colloid particle didn抰 contact with drug to emerge (physical) chemical effect, the possi-bility for the colloid particle to coagulate (flocculate) was rather small, only at the floccula-tion stage; it may be caught by net or settled by differential sedimentation. Base on sev-eral assumed important premises, the several steps and physical model of co-flocculation process were given, and the mixing, coagulation and flocculation were proposed accord-ing to their essentiality.

Bifunctional polyaniline electrode tailored hybridized solar cells for energy harvesting from sun and rain

Pursuit of energy-harvesting or-storage materials to realize outstanding electricity output from nature has been regarded as a promising strategy to resolve the energy-lack issue in the future. Among them,the solar cell as a solar-to-electrical conversion device has been attracted enormous interest to improve the efficiency. However, the ability to generate electricity is highly dependent on the weather conditions,in other words, there is nearly zero power output in dark-light conditions, such as rainy, cloudy, and night, lowering the monolithic power generation capacity. Here, we present a bifunctional polyaniline film via chemical bath deposition, which can harvest energy from the rain, yielding an induced current of 2.57 μA and voltage of 65.5 μV under the stimulus of real raindrop. When incorporating the functional PANi film into the traditional dye sensitized solar cell as a counter electrode, the hybridized photovoltaic can experimentally realize the enhanced output power via harvesting energy from rainy and sunny days. The current work may show a new path for development of advanced solar cells in the future.

可重构低熵智能车间布局建模与优化

针对智能车间布局,采用单元布局的方式分别对单元间布局和单元内布局进行建模,设计涵盖物料搬运成本、时间损失成本、单元重构成本、设备成本、车间面积利用率和布局柔性等面向低熵化车间布局的多目标函数,给出包括边界约束、间距约束和固定位置约束等符合车间实际情况的定量约束条件。针对车间布局模型多变量、多约束和非线性的特点,设计一种基于精英策略和自适应交叉、变异算子的双层遗传元胞算法进行求解。通过典型企业作业车间布局改造实例分析,验证模型和算法的可行性和有效性。

肿瘤治疗电场的双层金属丝网传感器电场测试方法研究

目的提出并验证了一种双层金属丝网传感器(MWMS)测量肿瘤治疗电场(TTFields)的新方法。方法通过COMSOL建立圆柱模型并进行仿真,验证了双层MWMS的有效性。明胶和NaCl按照一定比例配置来模拟头颅内部组织和用猪肌肉替代肿瘤组织,并设计单层MWMS测量系统验证单层MWMS测量效果。结果仿真结果表明,双层MWMS在测量精度上明显优于单层MWMS。实际测试结果表明,单层MWMS可以测出模拟头颅内部组织区域的电场强度和猪肌肉所在位置。结论双层MWMS为TTFields的电场测量提供了更加精确的工具。

考虑氢能储运特性的配电网集群划分与氢能系统选址定容策略

电-氢能源系统(IEHS)的合理规划对能源结构转型具有重要意义,充分利用氢储能的可移动特性可降低IEHS综合成本,提出一种考虑氢能储运特性的配电网集群划分与氢能系统规划策略。首先,将氢能系统拆分为多个氢能子系统(HES),建立多个HES之间的气氢拖车交通运输及储运成本模型;其次,基于电力-交通网架结构与新能源分布情况提出配电网集群划分方法;最后,根据集群划分结果,建立HES双层选址定容模型,该模型以IEHS年综合成本最低为目标,分层解决单个集群内HES的容量配置问题、各集群内部HES选址定容及气氢拖车配置问题。结果表明:提出的策略可以减小氢能储运压力、降低IEHS综合成本,提升风、光消纳水平,加快系统潮流计算迭代收敛速度。

面向光储充一体化社区的有序充电策略研究

针对当前有序充电策略优化目标单一且未考虑新能源出力的现状,提出了面向光储充一体化社区的有序充电策略。首先,将降低社区负荷峰谷差作为电网层优化目标,将减少用户充电费用作为用户层优化目标,完成双层多目标有序充电模型的设计。其次,设计基于云边协同的调度架构,将电网层优化模型部署在云端侧,用户层优化模型部署在边缘侧。该架构能有效利用边缘侧的计算资源,缓解云端侧面对电动汽车大规模接入时的计算压力。最后,以5种充电场景为例进行算例分析。实验表明,与无序充电相比,所提策略能够使社区负荷峰谷差减少40.47%,充电均价减少52.63%。与单层有序充电策略相比,该策略综合效果优势明显,在保障配电网安全稳定运行的同时,兼顾电动汽车用户的经济利益。

Machine learning modeling for fuel cell-battery hybrid power system dynamics in a Toyota Mirai 2 vehicle under various drive cycles

Electrification is considered essential for the decarbonization of mobility sector, and understanding and modeling the complex behavior of modern fuel cell-battery electric-electric hybrid power systems is challenging, especially for product development and diagnostics requiring quick turnaround and fast computation. In this study, a novel modeling approach is developed, utilizing supervised machine learning algorithms, to replicate the dynamic characteristics of the fuel cell-battery hybrid power system in a 2021 Toyota Mirai 2nd generation (Mirai 2) vehicle under various drive cycles. The entire data for this study is collected by instrumenting the Mirai vehicle with in-house data acquisition devices and tapping into the Mirai controller area network bus during chassis dynamometer tests. A multi-input - multi-output, feed-forward artificial neural network architecture is designed to predict not only the fuel cell attributes, such as average minimum cell voltage, coolant and cathode air outlet temperatures, but also the battery hybrid system attributes, including lithium-ion battery pack voltage and temperature with the help of 15 system operating parameters. Over 21,0000 data points on various drive cycles having combinations of transient and near steady-state driving conditions are collected, out of which around 15,000 points are used for training the network and 6,000 for the evaluation of the model performance. Various data filtration techniques and neural network calibration processes are explored to condition the data and understand the impact on model performance. The calibrated neural network accurately predicts the hybrid power system dynamics with an R-squared value greater than 0.98, demonstrating the potential of machine learning algorithms for system development and diagnostics.

Integration of multi-physics and machine learning-based surrogate modelling approaches for multi-objective optimization of deformed GDL of PEM fuel cells

The development of artificial intelligence(AI)greatly boosts scientific and engineering innovation.As one of the promising candidates for transiting the carbon intensive economy to zero emission future,proton exchange membrane(PEM)fuel cells has aroused extensive attentions.The gas diffusion layer(GDL)strongly affects the water and heat management during PEM fuel cells operation,therefore multi-variable optimization,including thickness,porosity,conductivity,channel/rib widths and compression ratio,is essential for the improved cell performance.However,traditional experiment-based optimization is time consuming and economically unaffordable.To break down the obstacles to rapidly optimize GDLs,physics-based simulation and machine-learning-based surrogate modelling are integrated to build a sophisticated M 5 model,in which multi-physics and multi-phase flow simulation,machine-learning-based surrogate modelling,multi-variable and multi-objects optimization are included.Two machine learning methodologies,namely response surface methodol-ogy(RSM)and artificial neural network(ANN)are compared.The M 5 model is proved to be effective and efficient for GDL optimization.After optimization,the current density and standard deviation of oxygen dis-tribution at 0.4 V are improved by 20.8%and 74.6%,respectively.Pareto front is obtained to trade off the cell performance and homogeneity of oxygen distribution,e.g.,20.5%higher current density is achieved when sacrificing the standard deviation of oxygen distribution by 26.0%.

模型差异性混合储能系统建模及功率分配

该文从锂电池和燃料电池的混合储能特性出发,针对已有文献的拓扑结构,对比选取适用于功率分配的混合储能拓扑模型和建模方法,并在组合过程中通过分析选取最合适的变换方式组成混合储能模型,最后通过仿真验证所提模型可在进行功率分配的前提下提高储能系统荷电状态偏移,延长储能系统寿命。

质子交换膜燃料电池核心基材性能研究进展

由于对清洁能源的需求不断扩大,质子交换膜燃料电池(Proton Exchange Membrane Fuel Cell,PEMFC)作为一种环保、可靠的新能源电池装置越来越受关注。但是PEMFC现在还有很多问题亟待解决,比如:核心基础材料制造困难、催化剂稳定性低、电池气-液管理等问题。气体扩散层是PEMFC中最重要的部件之一,通常包含碳纸支撑层和微孔层。为了达到PEMFC高性能材料和电池运行的稳定性,本文综述了近年来气体扩散层制备、结构模拟、双极板制备、催化剂层制备以及气-液传输的研究,以期为PEMFC的未来发展提供参考。

离子交换膜的选择透过性机理

分析了传统的双电层理论或Donnan膜平衡理论在解释离子交换膜的选择透过性机理上存在的局限性,提出了“空穴传导-双电层”假说,认为离子交换膜在溶液中由于反离子的迁移在膜内留下“离子空穴”,同时在膜的两侧形成“双电层”结构,“空穴”和“双电层”共同作用的结果使溶液中与反离子同号的离子能够通过离子交换膜,而与反离子异号的离子无法进入离子交换膜,从而使其具有选择透过性.在此基础上,用“空穴传导-双电层”假说对离子交换膜在无电场和有电场作用的选择透过性进行了合理的分析.

电化学基础(Ⅲ)——双电层模型及其发展

双电层模型描述了电极与溶液相界面之间电荷层的结构,是电极平衡和电极过程动力学在电化学过程中的具体表现,是现代电化学的基础理论之一。双电层理论对现代电化学的推动作用主要体现在电化学分析方法与双电层电容器等领域。通过回顾双电层理论提出的科学背景和发展历程,了解其发现问题、解决问题的思路,对于深化电化学工程领域的探索与创新具有重要意义。

异源细胞质小麦的赤霉病抗性研究

为了探索异源细胞质在小麦抗赤霉病育种中利用的可能性 ,用麦穗单花定位注射接种法、双层培养法、电导率法研究了小麦 3个近缘属 9个近缘种植物的细胞质对小麦赤霉病抗性的遗传效应。结果表明 ,9个近缘种的细胞质对小麦的赤霉病抗性存在明显的细胞质遗传效应和核质互作遗传效应 ,异质系的赤霉病抗性因核质组合的不同而有差异。具偏凸山羊草细胞质的小麦异质系 (Ae.ventricosa) Pe 10 6 8- 0 6 9和 (Ae.ventricosa)鉴 9的植株水平抗性和细胞水平抗性比其核亲本增强 ,并且在不同年度的田间和室内鉴定中抗性表现稳定。穗轴及叶片细胞的质膜透性测定结果显示 ,小麦异质系的赤霉病抗性与植株在受到病菌毒素侵害时的质膜透性呈负相关。选择理想的核质组合和行之有效的筛选、鉴定方法是培育抗赤霉病异源细胞质小麦材料的关键。

脉冲电场诱导细胞内外膜电穿孔模型与跨膜电位的仿真

基于经典的球形单细胞3层介电模型,同时考虑细胞核对跨膜电位的影响,提出了更为合理和接近实际的球形单细胞的多层介电模型,给出了稳恒电场和任意时变脉冲电场作用下细胞膜和核膜跨膜电位的计算方法。仿真结果表明:当脉宽减小时核膜跨膜电位增加,而脉宽增大时细胞膜跨膜电位增强;当脉宽在100-500ns范围时能有效实现肿瘤细胞膜和核膜电穿孔,同时不影响正常细胞。计算结果与实验吻合得很好,为肿瘤的电化学疗法和基因疗法的临床应用提供了理论指导。

新型准对称无机膜的正渗透去除Cd^(2+)的效能

正向渗透(forward osmosis,FO)是一种以溶液渗透压差为驱动力的新型膜技术。课题组在先前研究中使用微界面溶胶凝胶法制备了一种全新的准对称结构无机薄膜(QSTFI膜),与传统的有机聚合FO膜相比具有更大的优势。本文考察了QSTFI膜分离去除水中重金属Cd2+的效能,讨论了Cd2+浓度、提取液浓度以及膜表面带电性对Cd2+去除的影响机制。采用扫描电子显微镜(SEM)表征了QSTFI膜的微观形貌,使用能量色散光谱(EDS)、傅里叶变换红外光谱(FTIR)表征了膜的化学组成,并使用原子力显微镜(AFM)表征膜表面带电特性。结果表明,QSTFI膜表面带负电荷,能够与液相主体中的Cd2+通过静电引力形成双电层结构,双电层的Debye厚度越大越有利于膜对Cd2+的截留。FO实验测试中原液Cd2+浓度为10 mg·L-1的条件下,QSTFI膜对Cd2+截留率超过99%,水通量最大值可达到69 L·m-2·h-1(提取液为2.0 mol·L-1 Na Cl)。本研究为拓展FO技术在含重金属废水处理的潜在应用前景提供了理论依据和指导。