With the development of clean hydrogen energy, the cost effective and high‐performance hydrogen evolution reaction (HER) electrocatalysts are urgently required. Herein, a green, facile, and ...time‐efficient Ru doping synergistic with air‐plasma treatment strategy is reported to boost the HER performance of CoNi‐layered double hydroxide (LDH) nanotube arrays (NTAs) derived from zeolitic imidazolate framework nanorods. The Ru doping and air‐plasma treatment not only regulate the oxygen vacancy to optimize the electron structure but also increase the surface roughness to improve the hydrophilicity and hydrogen spillover efficiency. Therefore, the air plasma treated Ru doped CoNi‐LDH (P‐Ru‐CoNi‐LDH) nanotube arrays display superior HER performance with an overpotential of 29 mV at a current density of 10 mA cm−2. Furthermore, by assembling P‐Ru‐CoNi‐LDH as both cathode and anode for two‐electrode urea‐assisted water electrolysis, a small cell voltage of 1.36 V is needed at 10 mA cm−2 and can last for 100 h without any obvious activity attenuation that showing outstanding durability. In general, the P‐Ru‐CoNi‐LDH can improve the HER performance from intrinsic electronic structure regulation cooperated with extrinsic surface wettability modification. These findings provide an effective intrinsic and extrinsic synergistic effect avenue to develop high performance HER electrocatalysts, which is potential to be applied to other research fields.
With the Ru‐doping in CoNi‐LDH, the air‐plasma treatment was tend to introduce appropriate O and N filling that can effectively regulate the electronic structure. What's more, the plasma treatment also increases the superwettability of the samples which facilitate the H2 spillover process. The synergistically regulation of the intrinsic electronic structure and interface wettability of CoNi‐LDH can boost the HER process.
Deep learning (DL) is a new machine learning (ML) methodology that has found successful implementations in many application domains. However, its usage in communications systems has not been well ...explored. This paper investigates the use of the DL in modulation classification, which is a major task in many communications systems. The DL relies on a massive amount of data and, for research and applications, this can be easily available in communications systems. Furthermore, unlike the ML, the DL has the advantage of not requiring manual feature selections, which significantly reduces the task complexity in modulation classification. In this paper, we use two convolutional neural network (CNN)-based DL models, AlexNet and GoogLeNet. Specifically, we develop several methods to represent modulated signals in data formats with gridlike topologies for the CNN. The impacts of representation on classification performance are also analyzed. In addition, comparisons with traditional cumulant and ML-based algorithms are presented. Experimental results demonstrate the significant performance advantage and application feasibility of the DL-based approach for modulation classification.
Tuning the emissive color changes of lanthanide (Ln) complexes is an important and appealing project for promoting the applications of Ln-complexes. A solvothermal reaction of 4-cyano-3-methylbenzoic ...acid (HL) and Ln(NO
3
)
3
·6H
2
O affords three isostructural Ln-complexes Eu(L)
3
(H
2
O)
2
n
(
1-Ln
) (Ln = Eu, Gd and Tb) with one-dimensional chain structures.
1-Eu
and
1-Tb
show bright red and green emissions with absolute quantum yields of 3.06% and 11.96%, respectively, and the energy transfer was analyzed in detail through combined calculations. Interestingly, a series of heterometallic doped
1-Tb
x
Eu
1−
x
coordination polymers were also obtained by mixing different ratios of Eu
3+
and Tb
3+
ions, which possess continuous luminescent color changes from green to yellow, orange and red. In addition,
1-Eu
exhibits high quenching efficiency and low detection limit (∼10
−4
M) for the simultaneous sensing of MnO
4
−
, CrO
4
2−
and Cr
2
O
7
2−
ions in water.
Three synthesized Ln-CPs show tunable emission colors through bimetallic doping and sensing for MnO
4
−
, CrO
4
2−
and Cr
2
O
7
2−
ions in water.
A model-by-model analysis for historical simulations was necessary for identifying reasonably performing models in the updated Coupled Model Intercomparison Project (CMIP6) over the Tibetan Plateau. ...To determine whether the capacity of the CMIP6 models in simulating temperature and precipitation over the Plateau has been enhanced, we compared the outputs of 23 CMIP6 models with an observational dataset (CN05.1) for the period 1961–2014. The results suggest the systematic model biases (cold bias and wet bias) in the Tibetan Plateau still exist in CMIP6. Most models in CMIP6 realistically simulated the surface temperature and spatial distribution of precipitation, with a pattern correlation exceeding 0.75. The bias in the mean surface temperature of the multi-model ensemble (MME) simulation was 1.08 °C lower than the observational data, which had been decreased compared with the cold bias of CMIP5 (1.52 °C). At the seasonal scale, most models exhibited a warm temperature bias in summer and a cold bias in winter. The CMIP6 MME displayed a higher reproducibility of the precipitation amplitude over dry regions compared with CMIP5 and a lower ability over wet regions.
Oriented liquid crystal networks (LCNs) can undergo reversible shape change at the macroscopic scale upon an order–disorder phase transition of the mesogens. This property is explored for developing ...soft robots that can move under external stimuli, such as light in most studies. Herein, electrically driven soft robots capable of executing various types of biomimetic locomotion are reported. The soft robots are composed of a uniaxially oriented LCN strip, a laminated Kapton layer, and thin resistive wires embedded in between. Taking advantage of the combined attributes of the actuator, namely, easy processing, reprogrammability, and reversible shape shift between two 3D shapes at electric power on and off state, the concept of a “Janus” soft robot is demonstrated, which is built from a single piece of the material and has two parts undergoing opposite deformations simultaneously under a uniform stimulation. In addition to complex shape morphing such as the movement of oarfish and sophisticated devices like self‐locking grippers, electrically powered “Janus” soft robots can accomplish versatile locomotion modes, including crawling on flat surfaces through body arching up and straightening down, crawling inside tubes through body stretching and contraction, walking like four‐leg animals, and human‐like two‐leg walking while pushing a load forward.
Soft robots based on liquid crystal polymers are built to possess two parts capable of simultaneous and opposite deformations upon an order–disorder phase transition. This design enables various electrically powered locomotion modes, including moving on flat surface through body arching up–straightening down, crawling in a tunnel‐like tube through body stretching–contraction, four‐leg walking, and two‐leg walking while pushing a load.
The performance of Li‐ion batteries (LIBs) is highly dependent on their interfacial chemistry, which is regulated by electrolytes. Conventional electrolyte typically contains polar solvents to ...dissociate Li salts. Herein we report a weakly solvating electrolyte (WSE) that consists of a pure non‐polar solvent, which leads to a peculiar solvation structure where ion pairs and aggregates prevail under a low salt concentration of 1.0 M. Importantly, WSE forms unique anion‐derived interphases on graphite electrodes that exhibit fast‐charging and long‐term cycling characteristics. First‐principles calculations unravel a general principle that the competitive coordination between anions and solvents to Li ions is the origin of different interfacial chemistries. By bridging the gap between solution thermodynamics and interfacial chemistry in batteries, this work opens a brand‐new way towards precise electrolyte engineering for energy storage devices with desired properties.
A weakly solvating electrolyte affords a new path towards anion‐derived interfacial chemistry in lithium‐ion batteries. By formulating electrolyte with a non‐polar solvent, ion pairs and aggregates prevail under normal concentrations and give rise to anion‐derived interphases on graphite electrodes with superior electrochemical performances.
Modulation classification is one of the key tasks for communications systems monitoring, management, and control for addressing technical issues, including spectrum awareness, adaptive transmissions, ...and interference avoidance. Recently, deep learning (DL)-based modulation classification has attracted significant attention due to its superiority in feature extraction and classification accuracy. In DL-based modulation classification, one major challenge is to preprocess a received signal and represent it in a proper format before feeding the signal into deep neural networks. This article provides a comprehensive survey of the state-of-the-art DL-based modulation classification algorithms, especially the techniques of signal representation and data preprocessing utilized in these algorithms. Since a received signal can be represented by either features, images, sequences, or a combination of them, existing algorithms of DL-based modulation classification can be categorized into four groups and are reviewed accordingly in this article. Furthermore, the advantages as well as disadvantages of each signal representation method are summarized and discussed.
Metal sulfides with excellent redox reversibility and high capacity are very promising electrode materials for sodium‐ion batteries. However, their practical application is still hindered by the poor ...rate capability and limited cycle life. Herein, a template‐based strategy is developed to synthesize nitrogen‐doped carbon‐coated Cu9S5 bullet‐like hollow particles starting from bullet‐like ZnO particles. With the structural and compositional advantages, these unique nitrogen‐doped carbon‐coated Cu9S5 bullet‐like hollow particles manifest excellent sodium storage properties with superior rate capability and ultra‐stable cycling performance.
Sodium storage: Bullet‐like Cu9S5 hollow particles coated with a layer of nitrogen‐doped carbon are synthesized by a template‐based strategy. Their structure and composition allow these carbon‐coated Cu9S5 hollow bullets to exhibit enhanced sodium storage performance in terms of excellent rate capability and ultra‐stable cycle life.
The ability to optically reconfigure an existing actuator of a liquid crystal polymer network (LCN) so that it can display a new actuation behavior or function is highly desired in developing ...materials for soft robotics applications. Demonstrated here is a powerful approach relying on selective polymer chain decrosslinking in a LCN actuator with uniaxial LC alignment. Using an anthracene‐containing LCN, spatially controlled optical decrosslinking can be realized through photocleavage of anthracene dimers under 254 nm UV light, which alters the distribution of actuation (crosslinked) and non‐actuation (decrosslinked) domains and thus determines the actuation behavior upon order‐disorder phase transitions. Based on this mechanism, a single actuator having a flat shape can be reconfigured in an on‐demand manner to exhibit reversible shape transformation such as self‐folding into origami three‐dimensional structures. Moreover, using a dye‐doped LCN actuator, a light‐fueled microwalker can be optically reconfigured to adopt different locomotion behaviors, changing from moving in the laser scanning direction to moving in the opposite direction.
Walk along: Selective polymer chain decrosslinking in a liquid crystal polymer network (LCN) actuator is demonstrated. Spatially controlled optical decrosslinking alters the distribution of the actuation (crosslinked) and non‐actuation (decrosslinked) domains, and determines the actuation behavior upon the order–disorder phase transition. By using a dye‐doped LCN actuator, a light‐fueled microwalker can be optically reconfigured.
Lithium (Li) metal anodes hold great promise for next‐generation high‐energy‐density batteries, while the insufficient fundamental understanding of the complex solid electrolyte interphase (SEI) is ...the major obstacle for the full demonstration of their potential in working batteries. The characteristics of SEI highly depend on the inner solvation structure of lithium ions (Li+). Herein, we clarify the critical significance of cosolvent properties on both Li+ solvation structure and the SEI formation on working Li metal anodes. Non‐solvating and low‐dielectricity (NL) cosolvents intrinsically enhance the interaction between anion and Li+ by affording a low dielectric environment. The abundant positively charged anion–cation aggregates generated as the introduction of NL cosolvents are preferentially brought to the negatively charged Li anode surface, inducing an anion‐derived inorganic‐rich SEI. A solvent diagram is further built to illustrate that a solvent with both proper relative binding energy toward Li+ and dielectric constant is suitable as NL cosolvent.
The introduction of cosolvents with non‐solvating and low‐dielectricity (NL) properties can intrinsically enhance the interaction between anion and Li+ and regulate the solvation structures in electrolytes, which favors an upgraded anion‐derived solid electrolyte interphase (SEI) on lithium metal anodes.
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