Search

Single-atom catalysts (SACs) supported on two-dimensional (2D) nanomaterials with high activity for the oxygen evolution reaction (OER) and the oxygen reduction reaction (ORR) are highly desirable for renewable energy applications. Herein, we systemically investigate the electrocatalytic properties of transition metal atom-doped graphene-like GaN(g-GaN) monolayers by means of density functional theory. Our results reveal that Fe/g-GaN, Ni/g-GaN, and Au/g-GaN can be high-activity bifunctional electrocatalysts. Specifically, the Ni/g-GaN overpotential for the OER/ORR is estimated as 0.26/0.38 V, suggesting its extremely high catalytic performance. As an efficient descriptor for the adsorption strength of reactions on substrates, the TM atom d-band centers are found to linearly correlate with Gibbs free energies of HO* and HOO* species. This work provides an effective guidance to design high-activity SACs for the OER and ORR.

Harris hawks optimizer (HHO) is a relatively novel meta-heuristic approach that mimics the behavior of Harris hawk over the process of predating the rabbits. The simplicity and easy implementation of HHO have attracted extensive attention of many researchers. However, owing to its capability to balance between exploration and exploitation is weak, HHO suffers from low precision and premature convergence. To tackle these disadvantages, an improved HHO called VGHHO is proposed by embedding three modifications. Firstly, a novel modified position search equation in exploitation phase is designed by introducing velocity operator and inertia weight to guide the search process. Then, a nonlinear escaping energy parameter

Extension of the light absorption range and a reduction of the possibility of the photo-generated electron–hole pair recombination are the main tasks to break the bottleneck of the photocatalytic application of TiO2. In this paper, we systematically investigate the electronic and optical properties of Sc-doped, C-doped, and Sc/C-codoped TiO2 (101) surfaces using spin-polarized DFT+U calculations. The absorption coefficient of the Sc/C-codoped TiO2 (101) surfaces were enhanced the most compared with the other two doped systems in the high energy region of visible light, which can be attributed to the shallow impurity states. Furthermore, we studied the optical absorption properties with the change of the impurity concentration. The Sc/C-codoped TiO2 (101) surface with 5.56% impurity concentration exhibited optimal photocatalytic performance in the visible region. These results may be helpful for designing the high-performance of the photocatalysts by doping.

Rational design of high-performance anode materials is of paramount importance for developing rechargeable lithium ion batteries (LIBs) and sodium ion batteries (SIBs). In this work, a ZrC2 monolayer is predicted by performing the particle swarm optimization (PSO) algorithm. The high energetic, dynamic, and thermal stabilities of the ZrC2 monolayer are confirmed by cohesive energy, phonon dispersion, and molecular dynamics simulations, respectively. Unexpectedly, we find that the theoretical specific capacity for Na on the ZrC2 monolayer reaches as high as 932 mA h g−1, which is even higher than that of Li. Meanwhile, the diffusion energy barrier of Na on the ZrC2 monolayer is only 0.02 eV, ensuring the ultrafast charge/discharge rate. Additionally, the calculated open-circuit voltage (OCV) suggests that the change of Na intercalation voltage is steady. Therefore, our results consistently demonstrate that the ZrC2 monolayer can be an ideal anode material for SIBs.

Achieving an effective nitrogen reduction reaction (NRR) under mild conditions is a great challenge for industrial ammonia synthesis. NRR is often accompanied by a competing hydrogen evolution reaction (HER), which causes an extremely low Faraday efficiency. We systematically investigated the NRR reactivity of atom-pair catalysts (APCs) formed by 20 transition metal (TM) elements supported by N-doped graphene via three reaction pathways. By analyzing the correlation among the limiting potential, Gibbs free energy, and d-band center, we evaluated the activity trends of the TM APCs. Our computations revealed that the enzymatic pathway is the most suitable reaction pathway for the TM APCs, and the intrinsic activity trend of these APCs can be determined by the d-band center-based descriptor, which has a simple linear correlation with the bonding/antibonding orbital population. In addition, the NRR APCs with excellent performance have been screened out through selective analysis of the competing HER in the electrocatalytic NRR process.

Two-dimensional (2D) semiconductors with novel mechanical behaviors and electronic features are highly sought for a variety of potential applications. In this paper, by means of first-principles theory we study the mechanical and electronic properties of 2D IV–VI materials in detail, including SiS, SiSe, and Si2SSe. We reveal that the large values of negative Poisson's ratio (NPR) make these monolayers promising candidates for auxetic materials. Specifically, the in-plane NPR value of SiS monolayers reaches up to −0.19 in the x direction. In addition, the electrons in SiS monolayers have remarkably high mobility in the x direction, while the holes prefer to conduct in the y direction. Furthermore, under biaxial strain, the bandgaps of all these monolayers can be tuned effectively with ranges over 1.2 eV. All these appealing properties make SiS monolayers promising candidates for nanomechanic and optoelectronic applications.

Butterfly optimization algorithm (BOA) is a relatively novel optimization technique for solving function optimization as well as real world applications. However, the paramount challenge in BOA is that it is prone to stagnation in local optima. The purpose of this study is to balance the exploration and exploitation abilities of BOA when two new strategies are introduced. The dynamic inertia weight based on Logistic model as the first strategy is introduced to modify the position updating equation. Another strategy is the opposition-based learning. A new variant of BOA called BBOA based on these two strategies is proposed. Ten widely used benchmark test functions and 30 complex benchmarks from CEC 2014 are selected to verify the effectiveness of BBOA. The used benchmark problems are composed of unimodal, multimodal, rotated, shifted, hybrid and composite functions. The experimental results and analysis show that the proposed BBOA has better exploration ability than the conventional BOA when solving different characteristics functions. Finally, BBOA is applied to solve three real-world engineering applications and sixteen feature selection problems. The results demonstrate that BBOA can outperform other competitors in terms of the accuracy of solution on constrained engineering design and feature selection problems.

Meta-heuristic algorithms are widely viewed as feasible techniques to solve continuous large-scale numerical optimization problems. Grey wolf optimizer (GWO) is a relatively new stochastic algorithm with only a few parameters to adjust that can be easily used for global optimization. This paper presents an efficient and robust GWO (ERGWO) variant to solve large-scale numerical optimization problems. Inspired by particle swarm optimization, a nonlinearly adjustment strategy for parameter control is designed to balance exploration and exploitation. Additionally, a modified position-updating equation is presented to improve convergence speed. The performance of ERGWO is verified on 18 benchmark large-scale numerical optimization problems with dimensions ranging from 30 to 10,000, 30 benchmarks from CEC 2014, 30 functions in CEC 2017, respectively. Numerical experiments are performed to compare ERGWO to the basic GWO algorithm, other GWO variants, and other well-known meta-heuristic search techniques. Simulations demonstrate that the proposed ERGWO algorithm can find high quality solutions with low computational cost and very fast convergence.

The Schottky barrier height (SBH) is a critical parameter that determines the carrier transfer at metal/semiconductor interfaces. In this work, the interfacial properties of Hf2NT2/MSSe (T = F, O, OH; M = Mo, W) heterostructures are systematically investigated using first-principles calculations. It is found that, for MoSSe and WSSe, the use of S or Se atomic layers in contact with Hf2NT2 can give significantly different SBHs. In addition, SB-free contact for electron injection can be realized for F–S interfaces in Hf2NF2/MoSSe and Hf2NF2/WSSe heterostructures. Furthermore, the SBHs of the heterostructures can be tuned by applying compressive strain and p-type ohmic contact can be obtained for O–Se interfaces in Hf2NO2/MoSSe and Hf2NO2/WSSe heterostructures. This work proposes a feasible strategy to regulate the SBHs of interfaces.

Grey wolf optimizer (GWO) is a relatively new algorithm in the field of swarm intelligence for solving numerical optimization as well as real-world optimization problems. However, the paramount challenge in GWO is that it is prone to stagnation in local optima. The main goal of this paper is to improve the searchability of GWO when a new learning strategy is introduced in the algorithm. This new operator, called refraction learning, is essentially an opposite-learning strategy that is inspired by the principle of light refraction in physics. This proposed operator is applied to the current global optima of the swarm in the GWO algorithm and is beneficial to help the population for jumping out of the local optima. A novel variant of GWO called RL-GWO based on refraction learning is proposed. A theoretical proof of convergence is provided. We investigate the performance of RL-GWO using two sets of benchmark test functions, i.e., 23 widely used benchmark test functions, and 30 test functions from the IEEE CEC 2014. A non-parametric Wilcoxon's test is performed to observe the impact of improving the global optima in the algorithm. It is concluded that RL-GWO is an efficient, effective, and reliable algorithm for solving function optimization problems.

Rational design of high-performance anode materials is of paramount importance for developing rechargeable lithium ion batteries (LIBs) and sodium ion batteries (SIBs). In this work, a ZrC

A predator and prey-hibernation system with mutation and impulsive effects is presented in this work. The globally asymptotically stable solution \((\widetilde{x}, \widetilde{y},0)\) of system (1) exists. System (1) is proved to be permanent. Finally, simulations are presented to explain the results.

Achieving an effective nitrogen reduction reaction (NRR) under mild conditions is a great challenge for industrial ammonia synthesis. NRR is often accompanied by a competing hydrogen evolution reaction (HER), which causes an extremely low Faraday efficiency. We systematically investigated the NRR reactivity of atom-pair catalysts (APCs) formed by 20 transition metal (TM) elements supported by N-doped graphene via three reaction pathways. By analyzing the correlation among the limiting potential, Gibbs free energy, and

Van der Waals (vdWs) heterostructures have attracted significant research attention due to their tunable electronic structures and potential for device applications. In this study, the interfacial properties of graphene/In2Te3 heterostructures are systematically explored by employing first principles calculations. It is revealed that the electronic structures of graphene and In2Te3 monolayer are well preserved upon contact. The transition between the n-type Ohmic and p-type Schottky contacts can be realized for the graphene/In2Te3 heterostructures by switching the polarity of In2Te3. The findings reported in this study are not only vital for basic theoretical research, but also provide a feasible strategy to control the Schottky barriers for vdWs heterostructures.

Establishing accurate and reliable models based on the measured data for photo-voltaic (PV) modules are significant to design, control and evaluate the PV systems. Although many meta-heuristic algorithms have been proposed in the literature, achieving reliable, accurate and quick parameters identification for PV models is still a challenge. This paper develops a variant of butterfly optimization algorithm (called EABOA) to identify the unknown parameters of PV models. In EABOA, a new position search equation and good-point set are proposed to balance between exploration and exploitation. 12 classical benchmark test problems are firstly selected for verifying the effectiveness of EABOA, and the results indicate that EABOA provides better performance than other selected algorithms. Then, EABOA is applied to identify the unknown parameters of three benchmark test PV models, i.e., single diode (SD), double diode (DD) and PV module models. The comparison results with some other reported parameter identification methods from literature suggest that the proposed EABOA outperforms most approaches in terms of accuracy and reliability. The least SIAE value of EABOA is smaller than other compared algorithms about 56.6%, 5.84%, and 10.2% for SD, DD, and PV module models, respectively. Finally, EABOA is applied to solve parameter identification problem of practical module and obtains the satisfactory results.

We extend the hotspot model to include the virtuality dependence and use it to study the exclusive and dissociative production combined with the dipole amplitude in the target rapidity representation. We determined that virtuality takes effect on a number of hotspots, thus providing a better description of the production data at HERA. The collinear improved Balitsky-Kovchegove equation in the target rapidity representation is numerically solved and used to fit the experimental data with a series of hotspot sizes. We infer that virtuality significantly influences the number and size of hotspots. The expression resulting from the fit with the collinear improved dipole amplitude in the target rapidity representation is more reasonable than the corresponding originating from the leading order fit, which indicates that the collinear improved evolution equation in the target rapidity representation can provide a relatively good depiction of the exclusive and dissociative HERA data.

Artificial bee colony (ABC) algorithm has been successfully applied to solve constrained optimization problems (COPs). However, it is noteworthy that when using ABC to deal with COPs, the commonly used constraint-handling technique is the Deb’s feasibility-based rules. To our limited knowledge, the present ABC and its variants with augmented Lagrangian (AL) multiplier method have not been found applications to the COPs. In this paper, a novel constrained optimization method, named IABC-MAL, which integrates the benefit of the improved ABC (IABC) algorithm capability for obtaining the global optimum with the modified AL (MAL) method to handle constraints. This paper presents the first effort to integrate ABC algorithm with the AL method. To verify the performance of the proposed IABC-MAL, 24 well-known benchmark test problems at CEC2006, 18 benchmark test problems at CEC2010, and 5 engineering design problems are employed. Experiment results demonstrate that the proposed IABC-MAL algorithm shows better performance in comparison with other state-of-the-art algorithms from the literature.

Single-atom catalysis offers an effective way to reduce the amount of used noble metals and maximizes their catalytic activity. We systematically explore electrocatalytic performances of Pt doped Mo

The Schottky barrier height (SBH) is a critical parameter that determines the carrier transfer at metal/semiconductor interfaces. In this work, the interfacial properties of Hf2NT2/MSSe (T = F, O, OH; M = Mo, W) heterostructures are systematically investigated using first-principles calculations. It is found that, for MoSSe and WSSe, the use of S or Se atomic layers in contact with Hf2NT2 can give significantly different SBHs. In addition, SB-free contact for electron injection can be realized for F-S interfaces in Hf2NF2/MoSSe and Hf2NF2/WSSe heterostructures. Furthermore, the SBHs of the heterostructures can be tuned by applying compressive strain and p-type ohmic contact can be obtained for O-Se interfaces in Hf2NO2/MoSSe and Hf2NO2/WSSe heterostructures. This work proposes a feasible strategy to regulate the SBHs of interfaces.

The inclusive $J/\Psi$ production by direct and resolved photoproduction in the $\gamma$p scattering is calculated based on the nonrelativistic quantum chromodynamics (NRQCD) factorization formalism, which is in good agreement with the experimental data of total cross section distribution of heavy quarkonium production at HERA. Then we extend the formalism including the direct and resolved photoproduction processes to resolved pomeron model to study the heavy quarkonium photoproduction at the LHC energies. We present the predictions of rapidity and transverse momentum distributions of the inclusive diffractive $J/\Psi$, $\Psi(2S)$ and $\Upsilon$ photoproduction in pp, pPb and PbPb collisions at the LHC energies. Our numerical results indicate that the resolved photoproduction processes play an important role in the heavy quarkonium production. Especially for pp collisions, the contribution of resolved photoproduction processes is the largest, which can reach to $28\%$, $13\%$ and $44\%$ for the rapidity distributions of $J/\Psi$, $\Psi(2S)$ and $\Upsilon$ inclusive diffractive photoproduction, respectively., Comment: 10 pages

Butterfly optimization algorithm (BOA), as a recently proposed meta-heuristic optimization technique, performs competitively in solving numerical optimization problems as well as real-world applications. However, BOA has low precision, slow convergence and may be prone to local optimum, when solving complex or high-dimensional optimization problems. To overcome these defects, a modified BOA (called PIL-BOA) with adaptive gbest-guided search strategy and pinhole-imaging-based learning is proposed. Firstly, a modified position updated equation by introducing the global best (gbest) solution and the inertia weight is designed to efficiently improve the exploitation capability and the solution precision. Secondly, a novel pinhole-imaging learning strategy based on the principle of optics is presented to effectively search the unknown regions and avoid premature convergence. 23 classical problems and 60 complex optimization tasks from CEC 2014 and CEC 2017 are used to further investigate the effectiveness of PIL-BOA. The comparison results demonstrate that PIL-BOA has better performance than most compared algorithms on benchmark test functions. Finally, PIL-BOA is applied to solve feature selection problems and fault diagnosis in real-world wind turbine. The results show that PIL-BOA is superior to other competitors in term of classification accuracy.

Two-dimensional (2D) semiconductors with desirable bandgaps and high carrier mobility have great potential in electronic and optoelectronic applications. In the present work, 2D M-ScN, H-ScN, and O-ScN are predicted by the swarm-intelligent global structure search method. The low formation energies and high dynamical and thermal stabilities indicate the high feasibility of experimental synthesis of these ScN monolayers. The electronic structure calculations reveal that M-ScN and O-ScN are both direct bandgap semiconductors with the bandgaps of 1.39 and 2.14 eV, respectively, while H-ScN has a large indirect bandgap of 3.21 eV. In addition, both M-ScN and H-ScN exhibit ultra-high electron mobilities (3.09 × 104 cm2 V−1 s−1 and 1.22 × 104 cm2 V−1 s−1, respectively). More notably, O-ScN is found to be a promising 2D auxetic and ferroelastic material. The values of negative Possion’s ratios and reversible strain of this monolayer are predicted to be −0.27% and 15%, respectively.

Winter hibernation constitutes an effective strategy of animals in order to correspond survive cold environments and limited availability of food, it plays an important role in biological evolution. In this work, we firstly introduce hibernation behaviors of prey population into predator–prey systems with impulsive effect, then construct a periodic switched predator–prey system with winter hibernation in prey population and impulsive effect. We prove that the solutions of system (2.1) are uniformly ultimately bounded. We obtain the conditions of the globally asymptotically stable predator-extinction boundary periodic solution of system (2.1) , and also obtain the permanent conditions of system (2.1) . Finally, numerical analysis is employed to illustrate the results. Our results provide reliable tactic for the biological economics management and the protection of biodiversity.

Tunable optical reflectance using a monolithic encapsulated grating in fused silica is presented based on the guided-mode resonance (GMR) effect. The resonance location can be altered by slightly varying the thickness of the top layer. For small thickness of the grating layer, the variation of the grating thickness can be tailored to create variable optical reflectance at the same operating wavelength with the filter linewidth and the reflection sidebands kept almost the same. By proper choosing the grating thickness, the novel dual functional device that combines functions of narrowband filtering and three-port beam splitting in the resonance domain can be obtained using the monolithic encapsulated grating. Multiline reflection filters can be obtained by increasing the thickness of the top layer, and tunable reflectivity for multiple operating wavelengths can be obtained by changing the grating thickness.

This paper presents a novel constrained optimization algorithm named MAL-IGWO, which integrates the benefit of the improved grey wolf optimization (IGWO) capability for discovering the global optimum with the modified augmented Lagrangian (MAL) multiplier method to handle constraints. In the proposed MAL-IGWO algorithm, the MAL method effectively converts a constrained problem into an unconstrained problem and the IGWO algorithm is applied to deal with the unconstrained problem. This algorithm is tested on 24 well-known benchmark problems and 3 engineering applications, and compared with other state-of-the-art algorithms. Experimental results demonstrate that the proposed algorithm shows better performance in comparison to other approaches.

In this paper, we consider a hibernation plankton-nutrient chemostat model with impulsive switched systems describing. Employing the discrete dynamical system determined by the stroboscopic map, we obtain a plankton-extinction periodic solution. Further, it is globally asymptotically stable. The permanent condition of the system (2.1) is also obtained by the theory on impulsive differential equation. Our results reveal that the impulsive diffusion amount plays an important role on the chemostat system.

The oasis vegetation are important components of ecosystem in arid area. Water requirement of the oasis vegetation works as the important ecological factor in arid area. In this work, we consider the influence of the water resources on the oasis vegetation, and establish an oasis-vegetation-degradation model with impulsive irrigation and diffusion at differential moments in arid area. All solutions of system (2.2) are proved to be uniformly ultimately bounded. The condition for globally asymptotic stability boundary periodic solution of the oasis-vegetation-degradation is obtained. The permanent condition of system (2.2) is also obtained. It is concluded that the approach of combining impulsive irrigation with impulsive diffusion provides reliable tactic basis for preventing the oasis vegetation from degradation while the rainfall decreases in arid area.

To understand the effect of impulsive vaccination and restricting infected individuals boarding transports on disease spread, we establish an SIR model with impulsive vaccination, impulsive dispersal and restricting infected individuals boarding transports. This SIR epidemic model for two regions, which are connected by transportation of non-infected individuals, portrays the evolvement of diseases. We prove that all solutions of the investigated system are uniformly ultimately bounded. We also prove that there exists globally asymptotically stable infection-free boundary periodic solution. The condition for permanence is discussed. It is concluded that the approach of impulsive vaccination and restricting infected individuals boarding transports provides reliable tactic basis for preventing disease spread., Highlights • An SIR epidemic model with restricting infected individuals boarding transports was investigated. • Impulsive vaccination and dispersal are considered, which are more reasonable. • Two thresholds are obtained for Infection-free of the system.