Electrocapacitive Deionization: Mechanisms,Electrodes, and Cell Designs

Capacitive deionization (CDI) is an emerging water desalination technology for removing different ionic species from water, which is based on electric charge compensation by these charged species. CDI is becoming popular because it is more energy-efficient and cost-effective than other technologies, such as reverse osmosis and distillation, specifically in dealing with brackish water having low or moderate salt concentrations. Over the past decade, the CDI research field has witnessed significant advances in the used electrode materials, cell architectures, and associated mechanisms for desalination applications. This review article first discusses ion storage/removal mechanisms in carbon and Faradaic materials aided by advanced in situ analysis techniques and computations. It then summarizes research progress toward electrode materials in terms of structure, surface chemistry, and composition. More still, it discusses CDI cell architectures by highlighting their different cell design concepts. Finally, current challenges and future research directions are summarized to provide guidelines for future CDI research.     

Wearable Organic Electrochemical Transistor Array for Skin-Surface Electrocardiogram Mapping Above a Human Heart

Electrocardiogram (ECG) mapping can provide vital information in sports training and cardiac disease diagnosis. However, most electronic devices for monitoring ECG signals need to use multiple long wires, which limit their wearability and conformability in practical applications, while wearable ECG mapping based on integrated sensor arrays has been rarely reported. Herein, ultra-flexible organic electrochemical transistor (OECT) arrays used for wearable ECG mapping on the skin surface above a human heart are presented. QRS complexes of ECG signals at different recording distances and directions relative to the heart are obtained. Furthermore, the ECG signals are successfully analyzed by the devices before and after exercise, indicating potential applications in some sports training and fitness scenarios. The OECT arrays that can conveniently monitor spacial ECG signals in the heart region may find niche applications in wearable electronics and healthcare products in the future.     

An Intrinsically Nonflammable Electrolyte for Prominent-Safety Lithium Metal Batteries with High Energy Density and Cycling Stability

Nex-generation high-energy-density storage battery, assembled with lithium (Li)-metal anode and nickel-rich cathode, puts forward urgent demand for advanced electrolytes that simultaneously possess high security, wide electrochemical window, and good compatibility with electrode materials. Herein an intrinsically nonflammable electrolyte is designed by using 1 M lithium difluoro(oxalato)borate (LiDFOB) in triethyl phosphate (TEP) and N-methyl-N-propyl-pyrrolidinium bis(trifluoromethylsulfonyl)imide [Pyr₁₃][TFSI] ionic liquid (IL) solvents. The introduction of IL can bring plentiful organic cations and anions, which provides a cation shielding effect and regulates the Li⁺ solvation structure with plentiful Li⁺-DFOB⁻ and Li⁺-TFSI⁻ complexes. The unique Li⁺ solvation structure can induce stable anion-derived electrolyte/electrode interphases, which effectively inhibit Li dendrite growth and suppress side reactions between TEP and electrodes. Therefore, the LiNi_0.9Co_0.05Mn_0.05O₂ (NCM90)/Li coin cell with this electrolyte can deliver stable cycling even under 4.5 V and 60 °C. Moreover, a Li-metal battery with thick NCM90 cathode (≈ 15 mg cm⁻²) and thin Li-metal anode (≈ 50 µm) (N/P ≈ 3), also reveals stable cycling performance under 4.4 V. And a 2.2 Ah NCM90/Li pouch cell can simultaneously possess prominent safety with stably passing the nail penetration test, and high gravimetric energy density of 470 Wh kg⁻¹ at 4.4 V.     

Mitigating Surface Deficiencies of Perovskite Single Crystals Enables Efficient Solar Cells with Enhanced Moisture and Reverse-Bias Stability

Metal halide perovskite single crystals are promising for diverse optoelectronic applications due to their outstanding properties. In comparison to the bulk, the crystal surface suffers from high defect density and is moisture sensitive; however, surface modification strategies of perovskite single crystals are relatively deficient. Herein, solar cells based on methylammonium lead triiodide (MAPbI₃) thin single crystals are selected as a prototype to improve single-crystal perovskite devices by surface modification. The surface trap passivation and protection against moisture of MAPbI₃ thin single crystals are achieved by one bifunctional molecule 3-mercaptopropyl(dimethoxy)methylsilane (MDMS). The sulfur atom of MDMS can coordinate with bare Pb²⁺ of MAPbI₃ single crystals to reduce surface defect density and nonradiative recombination. As a result, the modified devices show a remarkable efficiency of 22.2%, which is the highest value for single-crystal MAPbI₃ solar cells. Moreover, MDMS modification mitigates surface ion migration, leading to enhanced reverse-bias stability. Finally, the cross-link of silane molecules forms a protective layer on the crystal surface, which results in enhanced moisture stability of both materials and devices. This work provides an effective way for surface modification of perovskite single crystals, which is important for improving the performance of single-crystal perovskite solar cells, photodetectors, X-ray detectors, etc.     

Understanding Boosted Selective CO2-to-CO Photoreduction with Pure Water Vapor over Hierarchical Biomass-Derived Carbon Matrix

Solar-driven CO₂ reduction reaction (CO₂RR) with water into carbon-neutral fuels is of great significance but remains challenging due to thermodynamic stability and kinetic inertness of CO₂. Biomass-derived nitrogen-doped carbon (N-C_b) have been considered as promising earth-abundant photocatalysts for CO₂RR, although their activities are not ideal and the reaction mechanism is still unclear. Herein, an efficient catalyst is developed for CO₂-to-CO conversion realized on diverse N-C_b materials with hierarchical pore structures. It is demonstrated that the CO₂-to-CO conversion preferentially takes place on positively charged carbon atoms next to pyridinic-N using two representatives treated pollens with the largest difference in pyridinic-N density and N content as model photocatalysts. Systematic experimental results indicate that surface local electric field originating from charge separation can be boosted by hierarchical pore structures, doped N, as well as pyridinic-N. Mechanistic studies reveal that positively charged carbon atoms next to pyridinic-N serve as active sites for CO₂RR, reduce the energy barrier on the formation of CO*, and facilitate the CO₂RR performance. All these benefits cooperatively contribute to treated chrysanthemum pollen catalyst exhibiting excellent CO formation rate of 203.2 µmol h⁻¹ g⁻¹ with 97.2% selectivity in pure water vapor. These results provide a new perspective into CO₂RR on N-C_b, which shall guide the design of nature-based photocatalysts for high-performance solar-fuel generation.     

CuI Encapsulated within Single-Walled Carbon Nanotube Networks with High Current Carrying Capacity and Excellent Conductivity

High current carrying capacity and high conductivity are two important indicators for materials used in microscale electronics and inverters. However, it is challenging to obtain high conductivity and high current carrying capacity at the same time since high conductivity requires a weakly bonded system to provide free electrons, while high current carrying capacity requires a strongly bonded system. In this paper, CuI@SWCNT networks by filling the single-walled carbon nanotubes (SWCNTs) with CuI is ingeniously prepared. CuI@SWCNT shows good stability due to the confinement protection of SWCNTs. Through the host-guest hybridization, CuI@SWCNT networks exhibit a current carrying capacity of 2.04 × 10⁷ A cm⁻² and a conductivity of 31.67 kS m⁻¹. Their current carrying capacity and conductivity are significantly improved compared with SWCNT. The Kelvin probe force microscopy measurements show a drop of surface potential energy after SWCNT filled with CuI, indicating that the CuI guest molecules regulate the position of the Fermi level of SWCNTs, increasing carrier concentration, achieving high conductivity and high current carrying capacity. This study offers ideas and solutions for the regulation of high-performance carbon tube networks, which hold great promise for future applications in carbon-based electronic devices.     

A Fullerene Seeded Strategy for Facile Construction of Nitrogen-Doped Carbon Nano-Onions as Robust Electrocatalysts

Carbon nano-onions (CNOs) as a novel form of carbon materials hold peculiar structural features but their electrocatalytic applications are largely discouraged by the demanding synthesis conditions (e.g., ≥1500 °C and vacuum). Using C₆₀ fullerene molecules as the sacrificial seeds and melamine as the main feedstock, herein, a novel strategy for the facile construction of CNOs nanoparticles is presented with ultrafine sizes (≈5 nm) at relatively low temperatures (≤900 °C) and atmospheric pressure. During the calcination, in-depth characterizations reveal that C₆₀ can retain the melamine-derived graphitic carbon nitride from complete sublimation at high temperatures (≥700 °C). Owing to the N removal and subsequent pentagon generation, severely deformed graphitic fragments together with the disintegrated C₆₀ molecules merge into larger sized nanosheets with high curvature, eventually leading to the formation of N-doped defect-rich CNOs. Owing to the integration of multiple favorable structural features of pentagons, edges, and N dopants, the CNOs obtained at 900 °C present superior oxygen reduction half-wave potential (0.853 V_RHE) and zinc–air cathode performance to the commercial Pt/C (0.838 V_RHE). Density functional theory calculation further uncovers that the carbon atoms adjacent to the N-doped edged pentagons are turned into the ORR-active sites with O₂ protonation as the rate-determining step.     

CBOE Volatility Index Forecasting under COVID-19: An Integrated BiLSTM-ARIMA-GARCH Model

After the outbreak of COVID-19, the global economy entered a deep freeze. This observation is supported by the Volatility Index (VIX), which reflects the market risk expected by investors. In the current study, we predicted the VIX using variables obtained from the sentiment analysis of data on Twitter posts related to the keyword “COVID-19,” using a model integrating the bidirectional long-term memory (BiLSTM), autoregressive integrated moving average (ARIMA) algorithm, and generalized autoregressive conditional heteroskedasticity (GARCH) model. The Linguistic Inquiry and Word Count (LIWC) program and Valence Aware Dictionary for Sentiment Reasoning (VADER) model were utilized as sentiment analysis methods. The results revealed that during COVID-19, the proposed integrated model, which trained both the Twitter sentiment values and historical VIX values, presented better results in forecasting the VIX in time-series regression and direction prediction than those of the other existing models.     

自动驾驶交叉路口测试场景建模及验证方法

自动驾驶汽车在缓解交通拥堵和消除交通事故方面发挥着重要作用.为了保证自动驾驶系统的安全性和可靠性,在自动驾驶汽车部署到公共道路之前,必须进行全面的测试.现有的测试场景数据大多来源于交通事故和交通违法场景,而且自动驾驶系统最基本的安全需求就是遵守交通法规,这充分体现了自动驾驶汽车遵守交通规则的重要性.然而,目前严重缺少针对交通法规构建的自动驾驶测试场景.因此,本文从交通法规出发,根据自动驾驶系统安全需求,提出交叉路口测试场景的Petri网建模及形式化验证方法.首先,依据自动驾驶测试场景对交规进行分类,提取适合自动驾驶汽车的文本交规,并进行半形式化表征.其次,以覆盖道路交通安全法规以及测试场景功能测试规程为目标,融合交叉路口场景要素的交互行为,合理选择并组合测试场景要素,布设交叉路口测试场景.然后,基于交规的测试场景被建模为一个Petri网,其中,库所描述自动驾驶汽车的状态,变迁表示状态的触发条件,并选择时钟约束规范语言（CCSL）作为中间语义语言,将Petri网转换为一个可进行形式化验证的中间语义模型,提出具体的转换方法.最后,通过Tina软件分析验证交规场景模型的活性、有界性和可达性,结果表明所建模型的正确性,并基于SMT的分析工具MyCCSL来分析CCSL约束,采用LTL公式以形式化方法验证交规场景模型的一致性.     

选择并融合粗细粒度特征的细粒度图像识别

目的 在细粒度图像识别任务中,类内图像姿势方差大,需要找到类内变化小的共性,决定该任务依赖于鉴别性局部的细粒度特征;类间图像局部差异小,需要找到类间更全面的不同,决定该任务还需要多样性局部的粗粒度特征。现有方法主要关注粗细粒度下的局部定位,没有考虑如何选择粗细粒度的特征及如何融合不同粒度的特征。为此,提出一种选择并融合粗细粒度特征的细粒度图像识别方法。方法 设计一个细粒度特征选择模块,通过空间选择和通道选择来突出局部的细粒度鉴别性特征;构建一个粗粒度特征选择模块,基于细粒度模块选择后的局部,挖掘各局部间的语义和位置关系,从而获得为细粒度局部提供补充信息的粗粒度多样性特征;融合这两个模块中提取到的细粒度特征和粗粒度特征,形成互补的粗细粒度表示,以提高细粒度图像识别方法的准确性。结果 在CUB-200-2011（caltech-UCSD birds-200-2011）、Stanford Cars和FGVC-Aircraft（fine-grained visual classification aircraft） 3个公开的标准数据集上进行广泛实验,结果表明,所提方法的识别准确率分别达到90.3%、95.6%和94.8%,明显优于目前主流的细粒度图像识别方法,相较于对比方法中的最好结果,准确率相对提升0.7%、0.5%和1.4%。结论 提出的方法能够提取粗粒度和细粒度两种类型的视觉特征,同时保证特征的鉴别性和多样性,使细粒度图像识别的结果更加精准。