Surface N Sites Mediate the Formation of Li Metal Cluster@N-Enriched Hierarchically Porous Carbon for Ultrahigh-Capacity Lithium Storage.

Graphite is the popular anode material of current lithium-ion batteries (LIBs). However, its low specific capacity and poor lithium intercalation potential hinder its use for high-power and large-scale energy storage. To meet the demand for energy storage, novel anode materials with high capacity, fast chargeable capability, and long cycle life are of great interest. Herein, we demonstrate an advanced nitrogen-enriched hierarchical porous carbon serving as a lithiophilic anode material for ultrahigh capacity and long-life LIBs. NHPC-700 (under optimal synthetic conditions), featuring a high surface area, rich N-doping, high porosity, and partially graphitized nanosheet structures, is successfully fabricated from a Schiff-base copolymer via a template-incipient wetness impregnation method. NHPC-700 exhibits an ultrahigh reversible lithium storage capacity of 2796 mA h g-1 at 0.1 A g-1 while still maintaining a high capacity of 526 mA h g-1 at 10 A g-1 after 1000 cycles. Theoretical and experimental studies reveal that this remarkable Li storage performance can be attributed to the large number of N lithiophilic sites on the inner surface of the small mesoporous pores. These sites guide Li metal nucleation in the initial period and control well the volume variation during charge/discharge cycles, thus exhibiting excellent cycle stability and great potential for practical application.

MW-MADDPG: a meta-learning based decision-making method for collaborative UAV swarm.

Unmanned Aerial Vehicles (UAVs) have gained popularity due to their low lifecycle cost and minimal human risk, resulting in their widespread use in recent years. In the UAV swarm cooperative decision domain, multi-agent deep reinforcement learning has significant potential. However, current approaches are challenged by the multivariate mission environment and mission time constraints. In light of this, the present study proposes a meta-learning based multi-agent deep reinforcement learning approach that provides a viable solution to this problem. This paper presents an improved MAML-based multi-agent deep deterministic policy gradient (MADDPG) algorithm that achieves an unbiased initialization network by automatically assigning weights to meta-learning trajectories. In addition, a Reward-TD prioritized experience replay technique is introduced, which takes into account immediate reward and TD-error to improve the resilience and sample utilization of the algorithm. Experiment results show that the proposed approach effectively accomplishes the task in the new scenario, with significantly improved task success rate, average reward, and robustness compared to existing methods.

Intelligent air defense task assignment based on hierarchical reinforcement learning.

Modern air defense battlefield situations are complex and varied, requiring high-speed computing capabilities and real-time situational processing for task assignment. Current methods struggle to balance the quality and speed of assignment strategies. This paper proposes a hierarchical reinforcement learning architecture for ground-to-air confrontation (HRL-GC) and an algorithm combining model predictive control with proximal policy optimization (MPC-PPO), which effectively combines the advantages of centralized and distributed approaches. To improve training efficiency while ensuring the quality of the final decision. In a large-scale area air defense scenario, this paper validates the effectiveness and superiority of the HRL-GC architecture and MPC-PPO algorithm, proving that the method can meet the needs of large-scale air defense task assignment in terms of quality and speed.

Appropriate aggregation is needed for highly active Pt/Al2O3 to enable hydrogenation of chlorinated nitrobenzene.

The atomic dispersion of a noble metal with a reducible support has been reported to be beneficial for catalytic hydrogenation reactions. Conversely, we found that Pt particles (3-5 nm) could be obtained on the non-reducible support Al2O3 by weakening the interaction between the metal and support using oleic acid, and the turnover frequency of catalyzing the hydrogenation of chlorinated nitrobenzene could reach 3700 h-1, which is three orders of magnitude higher than that of atomic platinum species.

Nanosheets of Ni-SAPO-34 Molecular Sieve for Selective Oxidation of Cyclohexanone to Adipic Acid.

Nanosheets of nickel doped SAPO-34 molecular sieves in thickness of ∼10 nm (denoted as NS-Ni-SAPO-34) has been successfully prepared through a morphology-reserved method of synthesis. A special aluminum phosphate in two-dimensional layered structure is used as precursor and converts to crystallized SAPO-34 molecular sieve, in nanosheet morphology reserved from the aluminum phosphate precursor, under hydrothermal conditions with tetraethyl orthosilicate and templates of mixed amines added. It is found that adequate amount of nickel, ∼5 wt %, added to the synthetic system is a key factor for the morphology-reserved synthesis. By characterization, the nickel is proved to be doped in the framework of the molecular sieve, which more likely helps to balance the high surface energy of nanosheet products. The NS-Ni-SAPO-34 shows excellent catalytic performance for oxidation of cyclohexanone to adipic acid by gaseous oxygen.

Gradient-based elephant herding optimization for cluster analysis.

Clustering analysis is essential for obtaining valuable information from a predetermined dataset. However, traditional clustering methods suffer from falling into local optima and an overdependence on the quality of the initial solution. Given these defects, a novel clustering method called gradient-based elephant herding optimization for cluster analysis (GBEHO) is proposed. A well-defined set of heuristics is introduced to select the initial centroids instead of selecting random initial points. Specifically, the elephant optimization algorithm (EHO) is combined with the gradient-based algorithm GBO for assigning initial cluster centers across the search space. Second, to overcome the imbalance between the original EHO exploration and exploitation, the initialized population is improved by introducing Gaussian chaos mapping. In addition, two operators, i.e., random wandering and variation operators, are set to adjust the location update strategy of the agents. Nine datasets from synthetic and real-world datasets are adopted to evaluate the effectiveness of the proposed algorithm and the other metaheuristic algorithms. The results show that the proposed algorithm ranks first among the 10 algorithms. It is also extensively compared with state-of-the-art techniques, and four evaluation criteria of accuracy rate, specificity, detection rate, and F-measure are used. The obtained results clearly indicate the excellent performance of GBEHO, while the stability is also more prominent.

Gaussian Perturbation Specular Reflection Learning and Golden-Sine-Mechanism-Based Elephant Herding Optimization for Global Optimization Problems.

Elephant herding optimization (EHO) has received widespread attention due to its few control parameters and simple operation but still suffers from slow convergence and low solution accuracy. In this paper, an improved algorithm to solve the above shortcomings, called Gaussian perturbation specular reflection learning and golden-sine-mechanism-based EHO (SRGS-EHO), is proposed. First, specular reflection learning is introduced into the algorithm to enhance the diversity and ergodicity of the initial population and improve the convergence speed. Meanwhile, Gaussian perturbation is used to further increase the diversity of the initial population. Second, the golden sine mechanism is introduced to improve the way of updating the position of the patriarch in each clan, which can make the best-positioned individual in each generation move toward the global optimum and enhance the global exploration and local exploitation ability of the algorithm. To evaluate the effectiveness of the proposed algorithm, tests are performed on 23 benchmark functions. In addition, Wilcoxon rank-sum tests and Friedman tests with 5% are invoked to compare it with other eight metaheuristic algorithms. In addition, sensitivity analysis to parameters and experiments of the different modifications are set up. To further validate the effectiveness of the enhanced algorithm, SRGS-EHO is also applied to solve two classic engineering problems with a constrained search space (pressure-vessel design problem and tension-/compression-string design problem). The results show that the algorithm can be applied to solve the problems encountered in real production.

Surrounded catalysts prepared by ion-exchange inverse loading.

The supported catalyst featuring highly dispersed active phase on support is the most important kind of industrial catalyst. Extensive research has demonstrated the critical role (in catalysis) of the interfacial interaction/perimeter sites between the active phase and support. However, the supported catalyst prepared by traditional methods generally presents low interface density because of limit contact area. Here, an ion-exchange inverse loading (IEIL) method has been developed, in which the precursor of support is controllably deposited onto the precursor of active phase by ion-exchange reaction, leading to an active core surrounded (by support) catalyst with various structures. The unique surrounded structure presents not only high interface density and mutually changed interface but also high stability due to the physical isolation of active phase, revealing superior catalytic performances to the traditional supported catalysts, suggesting the great potential of this new surrounded catalyst as the upgrade of supported catalyst in heterogeneous catalysis.

Morphology-Reserved Synthesis of Discrete Nanosheets of CuO@SAPO-34 and Pore Mouth Catalysis for One-Pot Oxidation of Cyclohexane.

Discrete nanosheets of silicon-doped AlPO4 molecular sieves (SAPO-34) with a thickness of ≈7 nm have been prepared through morphology-reserved synthesis with a lamellar aluminum phosphate as precursor. Cages of the nanosheets are in situ incorporated with copper oxide clusters. The CuO@SAPO-34 nanosheets exhibit a large external surface area with a high number of (010) channel pores on the surface. Due to the thin morphology, copper oxide clusters occupy the outmost cages with a probability >50 %. The distinctive configuration facilitates a new concept of pore mouth catalysis, i.e., reactant molecules larger than the pores cannot enter the interior of the molecular sieves but can interact with the CuO clusters at "the mouth" of the pore. In heterogeneous catalysis, CuO@SAPO-34 nanosheets have shown top performance in one-pot oxidation of cyclohexane to adipic acid by O2 , a key compound for the manufacture of nylon-66, which is so far produced using non-green nitric acid oxidation.

Two dimensional oxygen-vacancy-rich Co3O4 nanosheets with excellent supercapacitor performances.

A set of identical Co3O4 nanosheets with different oxygen vacancy amounts are rationally designed by varied reduction treatments and comparison of their properties. Remarkably, the oxygen-vacancy-rich Co3O4 nanosheets (OVR-Co3O4 NSs) exhibit excellent electrochemical performance for their potential use as a promising candidate for the next generation of supercapacitors.

Preparation of Coaxial-Line and Hollow Mn2O3 Nanofibers by Single-Nozzle Electrospinning and Their Catalytic Performances for Thermal Decomposition of Ammonium Perchlorate.

Coaxial-line and hollow Mn2O3 nanofibers have been synthesized by a simple single-nozzle electrospinning method without using a complicated coaxial jet head, combined with final calcination. The crystal structure and morphology of the Mn2O3 nanofibers were investigated by using the X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The results indicate that the electrospinning distance has important influence on the morphology and structure of the obtained Mn2O3 nanofibers, which changes from hollow fibers for short electrospinning distance to coaxial-line structure for long electrospinning distance after calcination in the air. The formation mechanisms of different structured Mn2O3 fibers are discussed in detail. This facile and effective method is easy to scale up and may be versatile for constructing coaxial-line and hollow fibers of other metal oxides. The catalytic activity of the obtained Mn2O3 nanofibers on thermal decomposition of ammonium perchlorate (AP) was studied by differential scanning calorimetry (DSC). The results show that the hollow Mn2O3 nanofibers have good catalytic activity to promote the thermal decomposition of AP.

Degradation of (14)C-labeled few layer graphene via Fenton reaction: Reaction rates, characterization of reaction products, and potential ecological effects.

Graphene has attracted considerable commercial interest due to its numerous potential applications. It is inevitable that graphene will be released into the environment during the production and usage of graphene-enabled consumer products, but the potential transformations of graphene in the environment are not well understood. In this study, (14)C-labeled few layer graphene (FLG) enabled quantitative measurements of FLG degradation rates induced by the iron/hydrogen peroxide induced Fenton reaction. Quantification of (14)CO2 production from (14)C-labeled FLG revealed significant degradation of FLG after 3 days with high H2O2 (200 mmol L(-1)) and iron (100 µmol L(-1)) concentrations but substantially lower rates under environmentally relevant conditions (0.2-20 mmol L(-1) H2O2 and 4 µmol L(-1) Fe(3+)). Importantly, the carbon-14 labeling technique allowed for quantification of the FLG degradation rate at concentrations nearly four orders of magnitude lower than those typically used in other studies. These measurements revealed substantially faster degradation rates at lower FLG concentrations and thus studies with higher FLG concentrations may underestimate the degradation rates. Analysis of structural changes to FLG using multiple orthogonal methods revealed significant FLG oxidation and multiple reaction byproducts. Lastly, assessment of accumulation of the degraded FLG and intermediates using aquatic organism Daphnia magna revealed substantially decreased body burdens, which implied that the changes to FLG caused by the Fenton reaction may dramatically impact its potential ecological effects.

Organic-free synthesis of ultrathin gold nanowires as effective SERS substrates.

We present a novel and facile fabrication of ultrathin gold nanowires in the absence of organic reagents. Measurements of surface-enhanced Raman scattering (SERS) demonstrated that the obtained organic-free ultrathin Au nanowires can serve as simple and effective SERS substrates.

Novel impurity-free hexagonal hydroxyapatite nanotubes for local delivery of antibiotics in orthopedic surgery: in vitro release validation.

Hydroxyapatite (HA) has been studied recently as a drug carrier in prevent implant infections due to its biocompatibility and osteoconductive properties, but most of these studies failed to control infection. The aim of the present study was to evaluate the potential of this impurity-free novel HA nanotube as a carrier for drug delivery in a controlled manner. Gentamicin was selected as an antibiotic to study the drug-carrier properties of this novel HA nanotube. Gentamicin was introduced into the HA nanotubes through immersion and evaporation process. Gentamicin-loaded HA nanotubes were then placed in phosphate buffered saline (PBS) and drug release profile was then monitored by measuring free genntamicin in the solution. An initial burst release of the drug occurred in the first 24 hours; subsequently, 84.7% of the drug was released from the nanotubes in 9 days. After 13 d, the concentrations of released drug were measured close to 2 µg/ml. The porosity of the gentamicin-loaded HA nanotubes was also observed using a Hitachi s-4800 high-resolution SEM, further confirming the drug-carrier property of HA nanotubes. Our novel bone substitute is an effective prophylactic tool for the local delivery of gentamicin to prevent periprosthetic infections.

Thickness-dependent SERS activities of gold nanosheets controllably synthesized via photochemical reduction in lamellar liquid crystals.

Gold nanosheets (AuNSs) with well-tuned thicknesses were synthesized by a facile photochemical reduction method in lamellar liquid crystals. It is found that ∼50 nm thick AuNSs present much stronger surface-enhanced Raman scattering (SERS) effect than that of AuNSs with thicknesses of ∼8 nm and 100 nm.

Organoamine-assisted biomimetic synthesis of faceted hexagonal hydroxyapatite nanotubes with prominent stimulation activity for osteoblast proliferation.

Uniform single-crystalline hydroxyapatite nanotubes with hexagonal facets are synthesized via a distinctive organoamines-assisted biomimetic route. These novel HA nanotubes exhibit exceptional performance in stimulating osteoblast proliferation, which gives them intriguing potential for bone repair.

Biological uptake and depuration of radio-labeled graphene by Daphnia magna.

Graphene layers are potential candidates in a large number of applications. However, little is known about their ecotoxicological risks largely as a result of a lack of quantification techniques in complex environmental matrices. In this study, graphene was synthesized by means of graphitization and exfoliation of sandwich-like FePO4/dodecylamine hybrid nanosheets, and (14)C was incorporated in the synthesis. (14)C-labeled graphene was spiked to artificial freshwater and the uptake and depuration of graphene by Daphnia magna were assessed. After exposure for 24 h to a 250 µg/L solution of graphene, the graphene concentration in the organism was nearly 1% of the organism dry mass. These organisms excreted the graphene to clean artificial freshwater and achieved roughly constant body burdens after 24 h depuration periods regardless of the initial graphene exposure concentration. Addition of algae and humic acid to water during the depuration period resulted in release of a significant fraction (>90%) of the accumulated graphene, but some still remained in the organism. Accumulated graphene in adult Daphnia was likely transferred to the neonates. The uptake and elimination results provided here support the environmental risk assessment of graphene and the graphene quantification method is a powerful tool for additional studies.

Inorganic nanotubes formation through the synergic evolution of dynamic templates and metallophosphates: from vesicles to nanotubes.

A novel synergic evolution of dynamic assembly, from vesicles to nanotubes, between the metallophosphates and organic amines, is disclosed, by which the multicomponent metallophosphate (Cu(2)(OH)PO(4)) nanotubes are synthesized for the first time.

Biomimetic synthesis of aluminophosphate nanorolls induced by mixed organoamines.

Natural kingite-like aluminophosphate nanorolls were obtained by biomimetic synthesis using a mixed-organoamine template.

In situ synthesis of horizontally aligned metal-boron alloy nanotubes on a silicon substrate with liquid crystal template.

In this paper, an interesting strategy has been described for the direct synthesis of parallel aligned metal-boron alloy nanotubes on silicon substrates, involving the use of lyotropic liquid crystal of non-ionic-anionic mixed surfactants. In particular, super-long, up to the scale of millimetres, nanotubes with well-controlled inner and outer diameters can be obtained. The current lyotropic liquid crystal template method could be used as an effective strategy for the in situ synthesis of aligned one-dimensional nanostructures with the wet chemical method. The results further prove the rolling-up mechanism for the formation of noncrystal metal-boron alloy nanotubes with a layered lyotropic liquid crystal precursor.