As attractive analogue of graphene, boron monolayers have been theoretically predicted. However, due to electron deficiency of boron atom, synthesizing boron monolayer is very challenging in ...experiments. Using first-principles calculations, we explore stability and growth mechanism of various boron sheets on Cu(111) substrate. The monotonic decrease of formation energy of boron cluster B(N) with increasing cluster size and low diffusion barrier for a single B atom on Cu(111) surface ensure continuous growth of two-dimensional (2D) boron cluster. During growth process, hexagonal holes can easily arise at the edge of a 2D triangular boron cluster and then diffuse entad. Hence, large-scale boron monolayer with mixed hexagonal-triangular geometry can be obtained via either depositing boron atoms directly on Cu(111) surface or soft landing of small planar BN clusters. Our theoretical predictions would stimulate further experiments of synthesizing boron sheets on metal substrates and thus enrich the variety of 2D monolayer materials.
Ammonia has been used in important areas such as agriculture and clean energy. Its synthesis from the electrochemical reduction of N2 is an attractive alternative to the industrial method that ...requires high temperature and pressure. Currently, electrochemical N2 fixation has suffered from slow kinetics due to the difficulty of N2 adsorption and NN cleavage. Here, N-doped porous carbon (NPC) is reported as a cost-effective electrocatalyst for ammonia synthesis from electrocatalytic N2 reduction under ambient conditions, where its N content and species were tuned to enhance N2 chemical adsorption and NN cleavage. The resulting NPC was effective for fixing N2 to ammonia with a high ammonia production rate (1.40 mmol g–1 h–1 at −0.9 V vs RHE). Experiments combined with density functional theory calculations revealed pyridinic and pyrrolic N were active sites for ammonia synthesis and their contents were crucial for promoting ammonia production on NPC. The energy-favorable pathway for ammonia synthesis was *NN → *NHNH → *NH2–NH2 → 2NH3.
As one-dimension line defects, grain boundaries (GBs) can affect many intrinsic properties of graphene. In this paper, the mechanical properties of 20 representative graphene grain boundaries were ...studied using density functional theory and molecular dynamics. With different arrangements of the pentagonal and heptagonal rings, the grain boundary may remain flat or become inflected up to 72°. For the flat GBs, the intrinsic tensile strength decreases linearly with the formation energy with a maximum value of 93 GPa, close to that of a perfect graphene. The intrinsic tensile strength of the inflected GBs is found to generally decrease with increasing inflection angle. Stone–Wales transformation is identified as the major failure mechanism of graphene GBs at high temperatures, whereas the initial fracture site can be either on the boundary line or inside the domain. These theoretical results constitute a useful picture of the grain boundary effect on the mechanical properties of polycrystalline graphene.
It is of great importance to understand the origin of high oxygen-evolving activity of state-of-the-art multimetal oxides/(oxy)hydroxides at atomic level. Herein we report an evident improvement of ...oxygen evolution reaction activity via incorporating iron and vanadium into nickel hydroxide lattices. X-ray photoelectron/absorption spectroscopies reveal the synergistic interaction between iron/vanadium dopants and nickel in the host matrix, which subtly modulates local coordination environments and electronic structures of the iron/vanadium/nickel cations. Further, in-situ X-ray absorption spectroscopic analyses manifest contraction of metal-oxygen bond lengths in the activated catalyst, with a short vanadium-oxygen bond distance. Density functional theory calculations indicate that the vanadium site of the iron/vanadium co-doped nickel (oxy)hydroxide gives near-optimal binding energies of oxygen evolution reaction intermediates and has lower overpotential compared with nickel and iron sites. These findings suggest that the doped vanadium with distorted geometric and disturbed electronic structures makes crucial contribution to high activity of the trimetallic catalyst.
The oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are cornerstone reactions for many renewable energy technologies. Developing cheap yet durable substitutes of precious‐metal ...catalysts, especially the bifunctional electrocatalysts with high activity for both ORR and OER reactions and their streamlined coupling process, are highly desirable to reduce the processing cost and complexity of renewable energy systems. Here, a facile strategy is reported for synthesizing double‐shelled hybrid nanocages with outer shells of Co‐N‐doped graphitic carbon (Co‐NGC) and inner shells of N‐doped microporous carbon (NC) by templating against core–shell metal–organic frameworks. The double‐shelled NC@Co‐NGC nanocages well integrate the high activity of Co‐NGC shells into the robust NC hollow framework with enhanced diffusion kinetics, exhibiting superior electrocatalytic properties to Pt and RuO2 as a bifunctional electrocatalyst for ORR and OER, and hold a promise as efficient air electrode catalysts in Zn–air batteries. First‐principles calculations reveal that the high catalytic activities of Co‐NGC shells are due to the synergistic electron transfer and redistribution between the Co nanoparticles, the graphitic carbon, and the doped N species. Strong yet favorable adsorption of an OOH* intermediate on the high density of uncoordinated hollow‐site C atoms with respect to the Co lattice in the Co‐NGC structure is a vital rate‐determining step to achieve excellent bifunctional electrocatalytic activity.
A new strategy is developed for constructing a hollow nanostructured bifunctional oxygen reduction reaction/oxygen evolution reaction electrocatalyst with integrated high activity and fast kinetics by surface‐stabilized heterogeneous contraction of core–shell metal–organic frameworks. The resultant double‐shelled hybrid nanocages with an outer shell of mesoporous Co‐N‐doped graphitic carbon and an inner shell of microporous N‐doped carbon exhibit superior electrocatalytic performance to noble metals for oxygen reduction and evolution reactions.
Tungsten (W) and tungsten-rhenium (W–Re) alloys are considered as the preferred plasma facing materials and structure materials for advanced fusion reactors. Thermal conductivity is one of the ...critical concerns for their materials applications. Although the steady-state heat transfer model can be utilized to evaluate the thermal conductivity variation in a traditional way, the thermal parameters of the material must be known beforehand. However, there are rare studies on the role of phonon and electron scattering mechanisms over a wide temperature range during the thermal transport process. In this paper, a physics-based model is established to predict the thermal conductivities of pristine W and W-xRe alloys (x = 1, 3, 5, 10, 25 wt%) from 300 to 1200 K. The model, which contains various scattering mechanisms, can be used to assess the effects of dislocation, grain size and solute rhenium on the total thermal conductivity. The temperature-dependent thermal conductivity predicted by the physics-based model agrees well with the reported data. Our simulation results reveal that 1010 - 1013 m−2 dislocation densities in tungsten has almost no impact on the change of thermal conductivity, while an obvious decrease is observed at temperature below 400 K if dislocation density exceeds 1014 m−2. Both small grain size and more solute rhenium in W–Re alloy can severely degrade the ability of heat transport.
By means of first-principles computations, we investigated the catalytic capability of the Fe-anchored graphene oxide (Fe–GO) for CO oxidation with O2. The high-energy barrier of Fe atom diffusion on ...GO and the strong binding strength of Fe anchored on GO exclude the metal clustering problem and enhance the stability of the Fe–GO system. The Fe-anchored GO exhibits good catalytic activity for CO oxidation via the favorable Eley–Rideal (ER) mechanism with a two-step route, while the Langmuir–Hinshelwood (LH) mechanism is not kinetically favorable. The low-cost Fe-anchored GO system can be easily synthesized and serves as a promising green catalyst for low-temperature CO oxidation.
The graphene grain boundaries with periodic length up to 18Å have been studied using density functional theory. Atomic structures, thermodynamic stabilities and electronic properties of 40 grain ...boundaries with symmetric and nonsymmetric structures were investigated. According to the arrangements of pentagons and heptagons on the boundary, grain boundaries were cataloged into four classes. Some nonsymmetric grain boundaries constructed here have identical misorientation angles to the experimentally observed ones. The formation energies of grain boundaries can be correlated with the misorientation angle and inflection angle. Nonsymmetric grain boundaries possess comparable formation energies to their symmetric counterparts when the periodic length along the defect line is larger than 1nm. Analysis of electronic density of states shows that the existence of a grain boundary usually increases the density of states near the Fermi level, whereas some symmetric grain boundaries can open a small band gap due to local sp2-to-sp3 rehybridization.
Silicene, a silicon analogue of graphene, has attracted increasing attention during the past few years. As early as in 1994, the possibility of stage corrugation in the Si analogs of graphite had ...already been theoretically explored. But there were very few studies on silicene until 2009, when silicene with a low buckled structure was confirmed to be dynamically stable by ab initio calculations. In spite of the low buckled geometry, silicene shares most of the outstanding electronic properties of planar graphene (e.g., the "Dirac cone", high Fermi velocity and carrier mobility). Compared with graphene, silicene has several prominent advantages: (1) a much stronger spin-orbit coupling, which may lead to a realization of quantum spin Hall effect in the experimentally accessible temperature, (2) a better tunability of the band gap, which is necessary for an effective field effect transistor (FET) operating at room temperature, (3) an easier valley polarization and more suitability for valleytronics study. From 2012, monolayer silicene sheets of different superstructures were successfully synthesized on various substrates, including Ag(111), Ir(111), ZrB2(0001), ZrC(111) and MoS2 surfaces. Multilayer silicene sheets have also been grown on Ag(111) surface. The experimental successes have stimulated many efforts to explore the intrinsic properties as well as potential device applications of silicene, including quantum spin Hall effect, quantum anomalous Hall effect, quantum valley Hall effect, superconductivity, band engineering, magnetism, thermoelectric effect, gas sensor, tunneling FET, spin filter, and spin FET, etc. Recently, a silicene FET has been fabricated, which shows the expected ambipolar Dirac charge transport and paves the way towards silicene-based nanoelectronics. This comprehensive review covers all the important theoretical and experimental advances on silicene to date, from the basic theory of intrinsic properties, experimental synthesis and characterization, modulation of physical properties by modifications, and finally to device explorations.
Hand, foot and mouth disease (HFMD) is an increasingly serious public health problem, and it has caused an outbreak in China every year since 2008. Predicting the incidence of HFMD and analyzing its ...influential factors are of great significance to its prevention. Now, machine learning has shown advantages in infectious disease models, but there are few studies on HFMD incidence based on machine learning that cover all the provinces in mainland China. In this study, we proposed two different machine learning algorithms, Random Forest and eXtreme Gradient Boosting (XGBoost), to perform our analysis and prediction. We first used Random Forest to examine the association between HFMD incidence and potential influential factors for 31 provinces in mainland China. Next, we established Random Forest and XGBoost prediction models using meteorological and social factors as the predictors. Finally, we applied our prediction models in four different regions of mainland China and evaluated the performance of them. Our results show that: 1) Meteorological factors and social factors jointly affect the incidence of HFMD in mainland China. Average temperature and population density are the two most significant influential factors; 2) Population flux has different delayed effect in affecting HFMD incidence in different regions. From a national perspective, the model using population flux data delayed for one month has better prediction performance; 3) The prediction capability of XGBoost model was better than that of Random Forest model from the overall perspective. XGBoost model is more suitable for predicting the incidence of HFMD in mainland China.
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