Constructing Wide-Temperature Lithium-Sulfur Batteries by Using a Covalent Organic Nanosheet Wrapped Carbon Nanotube.

Lithium-sulfur (Li-S) batteries hold the superiority of eminent theoretical energy density (2600 Wh kg-1 ). However, the ponderous sulfur reduction reaction and the issue of polysulfide shuttling pose significant obstacles to achieving the practical wide-temperature operation of Li-S batteries. Herein, a covalent organic nanosheet-wrapped carbon nanotubes (denoted CON/CNT) composite is synthesized as an electrocatalyst for wide-temperature Li-S batteries. The design incorporates the CON skeleton, which contains imide and triazine functional units capable of chemically adsorbing polysulfides, and the underlaid CNTs facilitate the conversion of captured polysulfides enabled by enhanced conductivity. The electrocatalytic behavior and chemical interplay between polysulfides and the CON/CNT interlayer are elucidated by in situ X-ray diffraction detections and theoretical calculations. Resultantly, the CON/CNT-modified cells demonstrate upgraded performances, including wide-temperature operation ranging from 0 to 65 °C, high-rate performance (625 mAh g-1 at 5.0 C), exceptional high-rate cyclability (1000 cycles at 5.0 C), and stable operation under high sulfur loading (4.0 mg cm-2 ) and limited electrolyte (5 µL mgs -1 ). These findings might guide the development of advanced Li-S batteries.

Long-Lasting Zinc-Iodine Batteries with Ultrahigh Areal Capacity and Boosted Rate Capability Enabled by Nickel Single-Atom Electrocatalysts.

Zinc-iodine (Zn-I2) batteries have garnered significant attention for their high energy density, low cost, and inherent safety. However, several challenges, including polyiodide dissolution and shuttling, sluggish iodine redox kinetics, and low electrical conductivity, limit their practical applications. Herein, we designed a highly efficient electrocatalyst for Zn-I2 batteries by uniformly dispersing Ni single atoms (NiSAs) on hierarchical porous carbon skeletons (NiSAs-HPC). In situ Raman analysis revealed that the conversion of soluble polyiodides (I3- and I5-) was significantly accelerated using NiSAs-HPC because of the remarkable electrocatalytic activity of NiSAs. The resulting Zn-I2 batteries with NiSAs-HPC/I2 cathodes delivered exceptional rate capability (121 mAh g-1 at 50 C), and ultralong cyclic stability (over 40 000 cycles at 50 C). Even under 11.6 mg cm-2 iodine, Zn-I2 batteries still exhibited an impressive cyclic stability with a capacity retention of 93.4% and 141 mAh g-1 after 10 000 cycles at 10 C.

In Situ Construction of Zn2Mo3O8/ZnO Hierarchical Nanosheets on Graphene as Advanced Anode Materials for Lithium-Ion Batteries.

Transition-metal oxides as anodes for lithium-ion batteries (LIBs) have attracted enormous interest because of their high theoretical capacity, low cost, and high reserve abundance. Unfortunately, they commonly suffer from poor electronic and ionic conductivity and relatively large volume expansion during discharge/charge processes, thereby triggering inferior cyclic performance and rate capability. Herein, a molybdenum-zinc bimetal oxide-based composite structure (Zn2Mo3O8/ZnO/rGO) with rectangular Zn2Mo3O8/ZnO nanosheets uniformly dispersed on reduced graphene oxide (rGO) has been prepared by using a simple and controllable cyanometallic framework template method. The Zn2Mo3O8/ZnO rectangular nanosheets with desirable porous features are composed of nanocrystalline subunits, facilitating the exposure of abundant active sites and providing sufficient contact with the electrolyte. Benefiting from the composition and structural merits as well as the induced synergistic effects, the Zn2Mo3O8/ZnO/rGO composite as LIB anodes delivers superior electrochemical properties, including high reversible capacity (960 mA h g-1 after 100 cycles at 200 mA g-1), outstanding rate performance (417 mA h g-1 at 10,000 mA g-1), and admirable long-term cyclic stability (862 mA h g-1 after 400 cycles at 1000 mA g-1). The mechanism of lithium storage and the formation of SEI film are systematically elucidated. This work provides an effective strategy for synthesizing promising Mo-cluster compound-based anodes for high-performance LIBs.

Nitrogen-Doped Carbon Nanotube Forests Planted on Cobalt Nanoflowers as Polysulfide Mediator for Ultralow Self-Discharge and High Areal-Capacity Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries with high theoretical energy density have caught enormous attention for electrochemical power source applications. However, the development of Li-S batteries is hindered by the electrochemical performance decay that resulted from low electrical conductivity of sulfur and serious shuttling effect of intermediate polysulfides. Moreover, the areal capacity is usually restricted by the low areal sulfur loadings (1.0-3.0 mg cm-2). When the areal sulfur loading increases to a practically accepted level above 3.0-5.0 mg cm-2, the areal capacity and cycling life tend to become inferior. Herein, we report an effective polysulfide mediator composed of nitrogen-doped carbon nanotube (N-CNT) forest planted on cobalt nanoflowers (N-CNTs/Co-NFs). The abundant pores in N-CNTs/Co-NFs can allow a high sulfur content (78 wt %) and block the dissolution/diffusion of polysulfides via physical confinement, and the Co nanoparticles and nitrogen heteroatoms (4.3 at. %) can enhance the polysulfide retention via strong chemisorption capability. Moreover, the planted N-CNT forest on N-CNTs/Co-NFs can enable fast electron transfer and electrolyte penetration. Benefiting from the above merits, the sulfur-filled N-CNTs/Co-NFs (S/N-CNTs/Co-NFs) cathodes with high areal sulfur loadings exhibit low self-discharge rate, high areal capacity, and stable cycling performance.

Oxygen Vacancy Engineering Promoted Photocatalytic Ammonia Synthesis on Ultrathin Two-Dimensional Bismuth Oxybromide Nanosheets.

The catalytic conversion of nitrogen to ammonia is one of the most important processes in nature and chemical industry. However, the traditional Haber-Bosch process of ammonia synthesis consumes substantial energy and emits a large amount of carbon dioxide. Solar-driven nitrogen fixation holds great promise for the reduction of energy consumption and environmental pollution. On the basis of both experimental results and density functional theory calculations, here we report that the oxygen vacancy engineering on ultrathin BiOBr nanosheets can greatly enhance the performance for photocatalytic nitrogen fixation. Through the addition of polymetric surfactant (polyvinylpyrrolidone, PVP) in the synthesis process, VO-BiOBr nanosheets with desirable oxygen vacancies and dominant exposed {001} facets were successfully prepared, which effectively promote the adsorption of inert nitrogen molecules at ambient condition and facilitate the separation of photoexcited electrons and holes. The oxygen defects narrow the bandgap of VO-BiOBr photocatalyst and lower the energy requirement of exciton generation. In the case of the specific surface areas are almost equal, the VO-BiOBr nanosheets display a highly improved photocatalytic ammonia production rate (54.70 µmol·g-1·h-1), which is nearly 10 times higher than that of the BiOBr nanoplates without oxygen vacancies (5.75 µmol·g-1·h-1). The oxygen vacancy engineering on semiconductive nanomaterials provides a promising way for rational design of catalysts to boost the rate of ammonia synthesis under mild conditions.

Porous-Shell Vanadium Nitride Nanobubbles with Ultrahigh Areal Sulfur Loading for High-Capacity and Long-Life Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries hold great promise for the applications of high energy density storage. However, the performances of Li-S batteries are restricted by the low electrical conductivity of sulfur and shuttle effect of intermediate polysulfides. Moreover, the areal loading weights of sulfur in previous studies are usually low (around 1-3 mg cm-2) and thus cannot fulfill the requirement for practical deployment. Herein, we report that porous-shell vanadium nitride nanobubbles (VN-NBs) can serve as an efficient sulfur host in Li-S batteries, exhibiting remarkable electrochemical performances even with ultrahigh areal sulfur loading weights (5.4-6.8 mg cm-2). The large inner space of VN-NBs can afford a high sulfur content and accommodate the volume expansion, and the high electrical conductivity of VN-NBs ensures the effective utilization and fast redox kinetics of polysulfides. Moreover, VN-NBs present strong chemical affinity/adsorption with polysulfides and thus can efficiently suppress the shuttle effect via both capillary confinement and chemical binding, and promote the fast conversion of polysulfides. Benefiting from the above merits, the Li-S batteries based on sulfur-filled VN-NBs cathodes with 5.4 mg cm-2 sulfur exhibit impressively high areal/specific capacity (5.81 mAh cm-2), superior rate capability (632 mAh g-1 at 5.0 C), and long cycling stability.

Highly Efficient Retention of Polysulfides in "Sea Urchin"-Like Carbon Nanotube/Nanopolyhedra Superstructures as Cathode Material for Ultralong-Life Lithium-Sulfur Batteries.

Despite high theoretical energy density, the practical deployment of lithium-sulfur (Li-S) batteries is still not implemented because of the severe capacity decay caused by polysulfide shuttling and the poor rate capability induced by low electrical conductivity of sulfur. Herein, we report a novel sulfur host material based on "sea urchin"-like cobalt nanoparticle embedded and nitrogen-doped carbon nanotube/nanopolyhedra (Co-NCNT/NP) superstructures for Li-S batteries. The hierarchical micromesopores in Co-NCNT/NP can allow efficient impregnation of sulfur and block diffusion of soluble polysulfides by physical confinement, and the incorporation of embedded Co nanoparticles and nitrogen doping (∼4.6 at. %) can synergistically improve the adsorption of polysulfides, as evidenced by beaker cell tests. Moreover, the conductive networks of Co-NCNT/NP interconnected by nitrogen-doped carbon nanotubes (NCNTs) can facilitate electron transport and electrolyte infiltration. Therefore, the specific capacity, rate capability, and cycle stability of Li-S batteries are significantly enhanced. As a result, the Co-NCNT/NP based cathode (loaded with 80 wt % sulfur) delivers a high discharge capacity of 1240 mAh g-1 after 100 cycles at 0.1 C (based on the weight of sulfur), high rate capacity (755 mAh g-1 at 2.0 C), and ultralong cycling life (a very low capacity decay of 0.026% per cycle over 1500 cycles at 1.0 C). Remarkably, the composite cathode with high areal sulfur loading of 3.2 mg cm-2 shows high rate capacities and stable cycling performance over 200 cycles.

Self-Templated Formation of Interlaced Carbon Nanotubes Threaded Hollow Co3S4 Nanoboxes for High-Rate and Heat-Resistant Lithium-Sulfur Batteries.

Lithium-sulfur batteries (Li-S) have attracted soaring attention due to the particularly high energy density for advanced energy storage system. However, the practical application of Li-S batteries still faces multiple challenges, including the shuttle effect of intermediate polysulfides, the low conductivity of sulfur and the large volume variation of sulfur cathode. To overcome these issues, here we reported a self-templated approach to prepare interconnected carbon nanotubes inserted/wired hollow Co3S4 nanoboxes (CNTs/Co3S4-NBs) as an efficient sulfur host material. Originating from the combination of three-dimensional CNT conductive network and polar Co3S4-NBs, the obtained hybrid nanocomposite of CNTs/Co3S4-NBs can offer ultrahigh charge transfer properties, and efficiently restrain polysulfides in hollow Co3S4-NBs via the synergistic effect of structural confinement and chemical bonding. Benefiting from the above advantages, the S@CNTs/Co3S4-NBs cathode shows a significantly improved electrochemical performance in terms of high reversible capacity, good rate performance, and long-term cyclability. More remarkably, even at an elevated temperature (50 °C), it still exhibits high capacity retention and good rate capacity.

CsPb0.9Sn0.1IBr2 Based All-Inorganic Perovskite Solar Cells with Exceptional Efficiency and Stability.

The emergence of perovskite solar cells (PSCs) has generated enormous interest in the photovoltaic research community. Recently, cesium metal halides (CsMX3, M = Pb or Sn; X = I, Br, Cl or mixed halides) as a class of inorganic perovskites showed great promise for PSCs and other optoelectronic devices. However, CsMX3-based PSCs usually exhibit lower power conversion efficiencies (PCEs) than organic-inorganic hybrid PSCs, due to the unfavorable band gaps. Herein, a novel mixed-Pb/Sn mixed-halide inorganic perovskite, CsPb0.9Sn0.1IBr2, with a suitable band gap of 1.79 eV and an appropriate level of valence band maximum, was prepared in ambient atmosphere without a glovebox. After thoroughly eliminating labile organic components and noble metals, the all-inorganic PSCs based on CsPb0.9Sn0.1IBr2 and carbon counter electrodes exhibit a high open-circuit voltage of 1.26 V and a remarkable PCE up to 11.33%, which is record-breaking among the existing CsMX3-based PSCs. Moreover, the all-inorganic PSCs show good long-term stability and improved endurance against heat and moisture. This study indicates a feasible way to design inorganic halide perovskites through energy-band engineering for the construction of high-performance all-inorganic PSCs.

All-Inorganic Perovskite Solar Cells.

The research field on perovskite solar cells (PSCs) is seeing frequent record breaking in the power conversion efficiency (PCE). However, organic-inorganic hybrid halide perovskites and organic additives in common hole-transport materials (HTMs) exhibit poor stability against moisture and heat. Here we report the successful fabrication of all-inorganic PSCs without any labile or expensive organic components. The entire fabrication process can be operated in ambient environment without humidity control (e.g., a glovebox). Even without encapsulation, the all-inorganic PSCs present no performance degradation in humid air (90-95% relative humidity, 25 °C) for over 3 months (2640 h) and can endure extreme temperatures (100 and -22 °C). Moreover, by elimination of expensive HTMs and noble-metal electrodes, the cost was significantly reduced. The highest PCE of the first-generation all-inorganic PSCs reached 6.7%. This study opens the door for next-generation PSCs with long-term stability under harsh conditions, making practical application of PSCs a real possibility.

Hierarchical artificial bee colony algorithm for RFID network planning optimization.

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

Multistage Competitive Opinion Maximization With Q-Learning-Based Method in Social Networks.

Competitive opinion maximization (COM) aims to determine some individuals (i.e., seed nodes) from social networks, propagating the desired opinions toward a target entity to their neighbors through social relationships when facing with its competitors (components) and maximize the opinion spread after the specific time. Current studies on COM are still in its infancy, while the only work merely considers the scenario that the strategy of competitors is known but ignores the unknown scenario. In addition, previous studies on COM cannot easily address the situation where some users might dynamically change their opinions. To address the COM issue, we investigate the multistage COM and propose a brand-new Q-learning-based opinion maximization framework (QOMF). Our QOMF consists of two components: dynamic opinion propagation and seeding process. We formulate the COM problem by maximizing relative effective opinions. To produce a dynamic opinion series more realistically, we design an opinion propagation model by joining the activation process and a dynamic opinion process. Moreover, we also verify that the opinion propagation model can reach convergence within finite iterations. To acquire the seed nodes, we design a multistage Q-learning seeding scheme by considering known and unknown competitor strategies, respectively. Experimental results on three real datasets demonstrate that the proposed method outperforms the benchmarks on reaching relatively effective opinions.

Engineering a Dynamic Solvent-Phobic Liquid Electrolyte Interphase for Long-Life Lithium Metal Batteries.

The heterogeneity, species diversity, and poor mechanical stability of solid electrolyte interphases (SEIs) in conventional carbonate electrolytes result in the irreversible exhaustion of lithium (Li) and electrolytes during cycling, hindering the practical applications of Li metal batteries (LMBs). Herein, this work proposes a solvent-phobic dynamic liquid electrolyte interphase (DLEI) on a Li metal (Li-PFbTHF (perfluoro-butyltetrahydrofuran)) surface that selectively transports salt and induces salt-derived SEI formation. The solvent-phobic DLEI with C-F-rich groups dramatically reduces the side reactions between Li, carbonate solvents, and humid air, forming a LiF/Li3PO4-rich SEI. In situ electrochemical impedance spectroscopy and Ab-initio molecular dynamics demonstrate that DLEI effectively stabilizes the interface between Li metal and the carbonate electrolyte. Specifically, the LiFePO4||Li-PFbTHF cells deliver 80.4% capacity retention after 1000 cycles at 1.0 C, excellent rate capacity (108.2 mAh g-1 at 5.0 C), and 90.2% capacity retention after 550 cycles at 1.0 C in full-cells (negative/positive (N/P) ratio of 8) with high LiFePO4 loadings (15.6 mg cm-2) in carbonate electrolyte. In addition, the 0.55 Ah pouch cell of 252.0 Wh kg-1 delivers stable cycling. Hence, this study provides an effective strategy for controlling salt-derived SEI to improve the cycling performances of carbonate-based LMBs.

Wide-Temperature Operation of Lithium-Sulfur Batteries Enabled by Multi-Branched Vanadium Nitride Electrocatalyst.

High-performance lithium-sulfur (Li-S) batteries that can work normally under harsh conditions have attracted tremendous attention; however, the sluggish reaction kinetics of polysulfide conversions at low temperatures as well as the notorious polysulfide shuttling at high temperatures remain to be resolved. Herein, a multibranched vanadium nitride (MB-VN) electrocatalyst has been designed and deployed for Li-S batteries. Both experimental (time-of-flight secondary ion mass spectroscopy and adsorption tests) and theoretical results verify the strong chemical adsorption capability and high electrocatalytic activity of MB-VN with respect to polysulfides. Moreover, in situ Raman characterization manifests the effective inhibition of polysulfide shuttling by the MB-VN electrocatalyst. Using MB-VN-modified separators, the Li-S batteries deliver an excellent rate capability (707 mAh g-1 at 3.0 C) and great cyclic stability (678 mAh g-1 after 400 cycles at 1.0 C) at room temperature. With 6.0 mg cm-2 of sulfur and a lean electrolyte volume of ∼6 µL mgs-1, Li-S batteries exhibit a high areal capacity of 5.47 mAh cm-2. Even over a wide temperature range (-20 to +60 °C), the Li-S batteries still maintain stable cyclic performance at high current rates. This work demonstrates that metal nitride based electrocatalysts can realize low-/high-temperature-tolerant Li-S batteries.

Realizing anti-self-discharged lithium-sulfur batteries by using hierarchical porous carbon nanofibers embedded with Fe/Ni-N catalytic sites.

Lithium-sulfur (Li-S) batteries are featured with high gravimetric energy density, yet their commercial application is significantly deteriorated with the severe self-discharging resulted from the polysulfides shuttle and sluggish electrochemical kinetics. Here, a hierarchical porous carbon nanofibers implanted with Fe/Ni-N (denoted as Fe-Ni-HPCNF) catalytic sites are prepared and used as a kinetics booster toward anti-self-discharged Li-S batteries. In this design, the Fe-Ni-HPCNF possesses interconnected porous skeleton and abundant exposed active sites, enabling fast Li-ion conduction, excellent shuttle inhibition and catalytic ability for polysulfides' conversion. Combined with these advantages, this cell with the Fe-Ni-HPCNF equipped separator exhibits an ultralow self-discharged rate of 4.9% after resting for one week. Moreover, the modified batteries deliver a superior rate performance (783.3 mAh g-1 at 4.0 C) and an outstanding cycling life (over 700 cycles with 0.057% attenuation rate at 1.0 C). This work may guide the advanced design of anti-self-discharged Li-S batteries.

Recent Progress for Concurrent Realization of Shuttle-Inhibition and Dendrite-Free Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries have become one of the most promising new-generation energy storage systems owing to their ultrahigh energy density (2600 Wh kg-1 ), cost-effectiveness, and environmental friendliness. Nevertheless, their practical applications are seriously impeded by the shuttle effect of soluble lithium polysulfides (LiPSs), and the uncontrolled dendrite growth of metallic Li, which result in rapid capacity fading and battery safety problems. A systematic and comprehensive review of the cooperative combination effect and tackling the fundamental problems in terms of cathode and anode synchronously is still lacking. Herein, for the first time, the strategies for inhibiting shuttle behavior and dendrite-free Li-S batteries simultaneously are summarized and classified into three parts, including "two-in-one" S-cathode and Li-anode host materials toward Li-S full cell, "two birds with one stone" modified functional separators, and tailoring electrolyte for stabilizing sulfur and lithium electrodes. This review also emphasizes the fundamental Li-S chemistry mechanism and catalyst principles for improving electrochemical performance; advanced characterization technologies to monitor real-time LiPS evolution are also discussed in detail. The problems, perspectives, and challenges with respect to inhibiting the shuttle effect and dendrite growth issues as well as the practical application of Li-S batteries are also proposed.

An Adaptive Localized Decision Variable Analysis Approach to Large-Scale Multiobjective and Many-Objective Optimization.

This article proposes an adaptive localized decision variable analysis approach under the decomposition-based framework to solve the large-scale multiobjective and many-objective optimization problems (MaOPs). Its main idea is to incorporate the guidance of reference vectors into the control variable analysis and optimize the decision variables using an adaptive strategy. Especially, in the control variable analysis, for each search direction, the convergence relevance degree of each decision variable is measured by a projection-based detection method. In the decision variable optimization, the grouped decision variables are optimized with an adaptive scalarization strategy, which is able to adaptively balance the convergence and diversity of the solutions in the objective space. The proposed algorithm is evaluated with a suite of test problems with 2-10 objectives and 200-1000 variables. Experimental results validate the effectiveness and efficiency of the proposed algorithm on the large-scale multiobjective and MaOPs.

Learning to Optimize: Reference Vector Reinforcement Learning Adaption to Constrained Many-Objective Optimization of Industrial Copper Burdening System.

The performance of decomposition-based algorithms is sensitive to the Pareto front shapes since their reference vectors preset in advance are not always adaptable to various problem characteristics with no a priori knowledge. For this issue, this article proposes an adaptive reference vector reinforcement learning (RVRL) approach to decomposition-based algorithms for industrial copper burdening optimization. The proposed approach involves two main operations, that is: 1) a reinforcement learning (RL) operation and 2) a reference point sampling operation. Given the fact that the states of reference vectors interact with the landscape environment (quite often), the RL operation treats the reference vector adaption process as an RL task, where each reference vector learns from the environmental feedback and selects optimal actions for gradually fitting the problem characteristics. Accordingly, the reference point sampling operation uses estimation-of-distribution learning models to sample new reference points. Finally, the resultant algorithm is applied to handle the proposed industrial copper burdening problem. For this problem, an adaptive penalty function and a soft constraint-based relaxing approach are used to handle complex constraints. Experimental results on both benchmark problems and real-world instances verify the competitiveness and effectiveness of the proposed algorithm.