A Materials Perspective on Direct Recycling of Lithium-Ion Batteries: Principles,Challenges and Opportunities

As the dominant means of energy storage technology today, the widespread deployment of lithium-ion batteries (LIBs) would inevitably generate countless spent batteries at their end of life. From the perspectives of environmental protection and resource sustainability, recycling is a necessary strategy to manage end-of-life LIBs. Compared with traditional hydrometallurgical and pyrometallurgical recycling methods, the emerging direct recycling technology, rejuvenating spent electrode materials via a non-destructive way, has attracted rising attention due to its energy efficient processes along with increased economic return and reduced CO₂ footprint. This review investigates the state-of-the-art direct recycling technologies based on effective relithiation through solid-state, aqueous, eutectic solution and ionic liquid mediums and thoroughly discusses the underlying regeneration mechanism of each method regarding different battery chemistries. It is concluded that direct regeneration can be a more energy-efficient, cost-effective, and sustainable way to recycle spent LIBs compared with traditional approaches. Additionally, it is also identified that the direct recycling technology is still in its infancy with several fundamental and technological hurdles such as efficient separation, binder removal and electrolyte recovery. In addressing these remaining challenges, this review proposes an outlook on potential technical avenues to accelerate the development of direct recycling toward industrial applications.     

融合先验信息和特征约束的杆塔螺栓缺陷检测

目的 螺栓是输电线路中数量最多的紧固件,一旦出现缺陷就会影响电力系统的稳定运行。针对螺栓缺陷自动检测中存在的类内多样性和类间相似性挑战,提出了一种融合先验信息和特征约束的Faster R-CNN（fasterregions with convolutional neural network）模型训练方法。方法 在航拍巡检图像预处理阶段,设计了基于先验信息的感兴趣区域提取算法,能够提取被识别目标的上下文区域,从而减少模型训练阶段的数据量,帮助模型在训练阶段关注重点区域,提高其特征提取能力。在模型训练阶段,首先通过费舍尔损失约束Faster R-CNN模型的输出特征生成,使样本特征具有较小的类内距离和较大的类间间隔;然后采用K近邻算法处理样本特征得到K近邻概率,将其作为难易样本的指示以引导模型后续更加关注难样本。结果 在真实航拍巡检图像构建的螺栓数据集上进行测试,与基线模型相比,本文模型使螺栓识别的平均精度均值（mean average precision,mAP）提高了6.4%,其中正常螺栓识别的平均精度（average precision,AP）提高了0.9%,缺陷螺栓识别的平均精度提高了12%。结论 提出的融合先验信息和特征约束的输电杆塔螺栓缺陷检测方法在缺陷螺栓识别上获得了良好的效果,为实现输电线路螺栓缺陷的自动检测奠定了良好的基础。     

基于NS3-gym框架的智能干扰规避系统设计与实现

多智能体构建的无线通信网络在受到外部恶意干扰时,智能体需要与环境进行大量交互来学习干扰规律和优化抗干扰策略。为了有效模拟和验证智能体与外部干扰环境的学习交互过程,需要构建智能干扰规避仿真系统。提出了一种基于NS3-gym框架的智能干扰规避系统,NS3模拟智能通信网络场景并将感知到的网络状态数据作为智能体的输入,智能体对输入数据进行学习分析得到干扰规避决策,并通过gym与NS3之间的交互将其返回到NS3中的仿真网络进行抗干扰策略部署。NS3-gym框架提供了NS3和OpenAI gym之间进行信息交互的接口。在Ubuntu20.04系统下搭建了智能干扰规避系统的仿真平台,分别验证了Q学习算法以及WoLF-PHC算法在扫频干扰、贪婪随机策略干扰、跟随干扰、随机干扰四种场景下的抗干扰性能。仿真结果证明了所提系统架构与仿真平台的正确性和有效性。     

回路压降冲激法的研究

常见的电路分析方法有很多,如叠加定理、戴维南定理和回路电流分析法等。为简化电路分析的复杂程度和减少求解电路方程的运算量,在回路电流法和线性叠加定理的基础上,提出一种简便的电路分析方法——回路压降冲激法。在分析线性网络的电路中,通过实验对比分析得出该电路分析方法可以简化分析过程,并且运算量明显减少。     

Electrochemical determination of hydrazine based on polydopamine-reduced graphene oxide nanocomposite

In this work, a simple and mild procedure was employed to synthesize polydopamine-reduced graphene oxide (PDA-RGO) nanocomposites, where the sheets of graphene oxide were functionalized firstly with PDA through self-polymerization. FTIR was used to confirm that the GO sheets had been functionalized successfully with PDA and reduced. Besides, UV-Vis and X-ray diffraction spectroscopy were employed to further demonstrate the formation of RGO. The electrochemical property of the PDA-RGO has been studied by the determination of hydrazine. The results indicated that the electrochemical oxidation of hydrazine was significantly improved by the obtained PDA-RGO nanocomposite due to the increased available surface area of electrode. A quick amperometric response was observed with the electrochemical sensor based on PDA-RGO nanocomposite for the hydrazine measurement in a wide linear range of 0.03–100 μM, where the limit of the detection was 0.01 μM.     

Effects of Ge<Superscript>4+</Superscript> acceptor dopant on sintering and electrical properties of (K<Subscript>0.5</Subscript>Na<Subscript>0.5</Subscript>)NbO<Subscript>3</Subscript> lead-free piezoceramics

Lead-free (K_0.5Na_0.5)(Nb_1-xGe _x )O₃ (KNN-xGe, where x = 0-0.01) piezoelectric ceramics were prepared by conventional ceramic processing. The effects of Ge⁴⁺ cation doping on the phase compositions, microstructure and electrical properties of KNN ceramics were studied. SEM images show that Ge⁴⁺ cation doping improved the sintering and promoted the grain growth of the KNN ceramics. Dielectric and ferroelectric measurements proved that Ge⁴⁺ cations substituted Nb⁵⁺ ions as acceptors, and the Curie temperature (T_C) shows an almost linear decrease with increasing the Ge⁴⁺ content. Combining this result with microstructure observations and electrical measurements, it is concluded that the optimal sintering temperature for KNN-xGe ceramics was 1020°C. Ge⁴⁺ doping less than 0.4 mol.%can improve the compositional homogeneity and piezoelectric properties of KNN ceramics. The KNN-xGe ceramics with x = 0.2% exhibited the best piezoelectric properties: piezoelectric constant d₃₃ = 120 pC/N, planar electromechanical coupling coefficient k_p = 34.7%, mechanical quality factor Q_m = 130, and tanδ = 3.6%.     

Construction of point-line-plane (0-1-2 dimensional) Fe<Subscript>2</Subscript>O<Subscript>3</Subscript>-SnO<Subscript>2</Subscript>/graphene hybrids as the anodes with excellent lithium storage capability

The assembly of hybrid nanomaterials has opened up a new direction for the construction of high-performance anodes for lithium-ion batteries (LIBs). In this work, we present a straightforward, eco-friendly, one-step hydrothermal protocol for the synthesis of a new type of Fe₂O₃-SnO₂/graphene hybrid, in which zero-dimensional (0D) SnO₂ nanoparticles with an average diameter of 8 nm and one-dimensional (1D) Fe₂O₃ nanorods with a length of ~150 nm are homogeneously attached onto two-dimensional (2D) reduced graphene oxide nanosheets, generating a unique point-line-plane (0D-1D-2D) architecture. The achieved Fe₂O₃-SnO₂/graphene exhibits a well-defined morphology, a uniform size, and good monodispersity. As anode materials for LIBs, the hybrids exhibit a remarkable reversible capacity of 1,530 mA·g^?1 at a current density of 100 mA·g^?1 after 200 cycles, as well as a high rate capability of 615 mAh·g^?1 at 2,000 mA·g^?1. Detailed characterizations reveal that the superior lithium-storage capacity and good cycle stability of the hybrids arise from their peculiar hybrid nanostructure and conductive graphene matrix, as well as the synergistic interaction among the components.

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Incentives for quality improvement efforts coordination in supply chains with partial cost allocation contract

In this paper, we consider quality improvement efforts coordination in a two-stage decentralised supply chain with a partial cost allocation contract. The supply chain consists of one supplier and one manufacturer, both of which produce defective products. Two kinds of failure cost occur within the supply chain: internal and external. The supplier and the manufacturer determine their individual quality levels to maximise their own profits. We propose a partial cost allocation contract, under which the external failure cost is allocated between the manufacturer and the supplier at different rates based on information derived from failure root cause analysis. If the quality levels of the supplier and the manufacturer are observable, we show that the partial cost allocation contract coordinates the supply chain, provided that the failure root cause analysis does not erroneously identify the manufacturer’s fault as the supplier’s, and the supplier does not take responsibility for the manufacture’s fault. In the single moral hazard model, where only the quality level of the supplier is unobservable, the optimal share rates require the supplier to take some responsibility for the manufacture’s fault. However, in the double moral hazard model, where quality levels of the supplier and the manufacturer are unobservable to each other, the optimal share rates require the supplier not to take responsibility for the manufacturer’s fault. It is noted that the root cause analysis conducted by the manufacturer may have its disadvantage in attributing the fault to the supplier when both sides are at fault. We also propose a contract based on the dual root cause analysis to reduce the supplier’s penalty cost. Numerical results illustrate that the partial cost allocation contract satisfies the fairness criterion compared with the traditional cost allocation contract.     

氧化镧/聚丙烯防X射线复合纤维的制备及性能表征

先采用熔融纺丝方法制备了不同氧化镧含量的氧化镧/聚丙烯复合纤维,然后采用对二甲苯在相同处理时间(1 h)不同温度(105~109℃)下溶解复合纤维中的部分聚丙烯基体以提高纤维中氧化镧含量,并对处理过后的纤维进行扫描电镜、X射线屏蔽性能等测试。此外,采用硅烷偶联剂改性氧化镧,通过熔融纺丝法制备了表面活性氧化镧/聚丙烯复合纤维,并对其作了差示扫描量热分析、扫描电镜、力学测试等性能表征。实验结果表明,随未改性氧化镧添加量增加,纤维力学性能下降,玻璃化转变温度向低温方向移动,纤维热稳定提高;有机改性可改善氧化镧在聚丙烯中的分散,提高纤维的力学性能,纤维玻璃化转变温度较纯聚丙烯纤维升高;用对二甲苯在107℃处理1h所获取的复合纤维中氧化镧含量最高,X射线屏蔽性能最优。