Transition metal atoms anchored on nitrogen-doped α-arsenene as efficient electrocatalysts for nitrogen electroreduction reaction

Electrocatalytic reduction of N₂ to NH₃ under ambient conditions, inspired by biological nitrogen fixation, is a new approach to address the current energy shortage crisis. As a result, developing efficient and low-cost catalysts is critical. The catalytic activity, catalytic mechanism, and selectivity of α-arsenene (α-Ars) catalysts anchored with various transition metal atoms and doped with different numbers of N atom were investigated for N₂ reduction reaction (NRR) in this paper. Results reveal that compared with WN₃-α-Ars which is coordinated with three N atoms, asym-WN₂As-α-Ars that coordinated with two N atoms not only exhibits high catalytic activity (U_L = ?0.36 V), but can also successfully suppress the hydrogen evolution reaction (HER). It is manifested that reducing the number of coordination atoms can promote the selectivity of the transition metal (TM) loaded N-doped arsenene catalysts. Furthermore, activity origin analyses show both the charge on 1N–NH and φ form volcano-type relationship with the limiting potential. The active center of the catalyst, which acts as the charge transporter and has the moderate ability to retrieve charges, is the most efficient in NRR. Overall, this research creates high performance NRR catalysts by varying the number of coordinating N atoms, which provides a novel idea for the development of new NRR catalysts.     

Theoretical investigation of intrinsic point defects and the oxygen migration behavior in rare earth hafnates

In this work, the composition-dependent point defect types and formation energies of RE₂Hf₂O₇ (RE = La, Ce, Pr, Nd, Pm, Sm, Eu and Gd) as well as the oxygen diffusion behavior are systematically investigated by first-principles calculations. The possible defect reactions and dominant defect complexes under stoichiometric and non-stoichiometric conditions are revealed. It is found that O Frenkel pairs are the predominant defect in stoichiometric pyrochlore hafnates. Hf-RE cation anti-site defects, accompanied by RE vacancies and/or oxygen interstitials, are stable in the non-stoichiometric case of HfO₂ excess. On the other hand, RE-Hf anti-site defects together with oxygen vacancies and/or RE interstitials are preferable in the case of RE₂O₃ excess. The energy barriers for the migration along the V_O48f - V_O48f pathway of pyrochlore hafnates were calculated to be between 0.81 eV and 0.89 eV. Based on these results, a defect engineering strategy is proposed and the pyrochlore hafnates investigated here are predicted to exhibit potential oxygen ionic conductivity.     

Design and characteristics of a new type laminar plasma torch for materials processing

Laminar plasma jet(LPJ) generated by laminar plasma torch(LPT) has a favorable temperature and velocity distribution. Thus, it is superior to the turbulent plasma jet in material processing.However, most of the reported LPTs usually operate at a relatively low output power with a relatively low arc voltage and thermal efficiency, which limits its capabilities. In this context, this paper attempts to design a new type of high-power LPT with a relatively low arc current and a high thermal efficiency. In the first section, the design principle of the main components is studied and discussed in detail, and a new high-power LPT is proposed. Then, the experimental characteristics of the proposed high-power LPT are examined. Experimental results reveal the following characteristics of the proposed LPT.(1) The max jet length of the proposed LPT reaches at 540 mm.(2) Its mean arc voltage is higher than 290 V when the LPT works with arc currents lower than 200 A, leading to an output power greater than 50 kW.(3) The mean thermal efficiency is higher than 50%. Lastly, the proposed LPT has been applied to spheroidize the aluminum oxide powers. The experiment results for the production of spherical powders show that the proposed LPT has a good characteristic for material processing.     

Materials Design of Solar Cell Absorbers Beyond Perovskites and Conventional Semiconductors via Combining Tetrahedral and Octahedral Coordination

Tetrahedral coordination structures, e.g. crystalline Si, GaAs, CdTe, and octahedral coordination structures, e.g. perovskites, represent two classes of successful crystal structures hitherto for solar cell absorbers. Here, via first‐principles calculations and crystal symmetry analysis, the two classes of semiconductors are shown exhibiting complementary properties in terms of bond covalency/ionicity, optical property, defect tolerance, and stability, which are correlated with their respective coordination number. Therefore, a spinel structure is proposed, which combines tetrahedral and octahedral coordination into a single crystal structure, as an alternative to perovskite and conventional semiconductors for potential photovoltaic applications. The case studies of a class of 105 spinel AB₂X₄ systems identify five spinel compounds HgAl₂Se₄, HgIn₂S₄, CdIn₂Se₄, HgSc₂S₄, and HgY₂S₄ as promising solar cell absorbers. In particular, HgAl₂Se₄ has suitable bandgap (1.36 eV by GW0 calculation), small direct–indirect bandgap difference (24 meV), appropriate carrier effective mass (m_e = 0.08 m₀, and m_h = 0.69 m₀), strong optical absorption, and high dynamic stability. This study suggests that crystal systems with mixed tetrahedral and octahedral coordination may open a viable route for emerging solar cell absorbers.     

Ab initio calculations of the NO2 fission for CL-20 conformers

NO₂ fission is regarded to be the most important initial decomposition process of 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20). In this study, four CL-20 conformers based on the ε-CL-20 were obtained after the optimization at m062x/cc-pvtz level, and the bond length, bond order and bond dissociation energy of the N-N bonds were examined to investigate the stability of these bonds. In addition, the rate constants and activation energy of the NO₂ fission were evaluated using the microcanonical variational transition state theory (μVT). The calculation results have shown that N-N bonds in the case of pseudo-equatorial and axial of nitro groups are the most stable and the least stable, respectively, by evaluating the bond length, bond order and minimum energy path (MEP). The NO₂ fission rate constants are affected by not only the stability of N-N bonds but also the repulsion forces from the other nitro groups, and the fission process for pseudo-equatorial positioning of nitro groups is easier to be accelerated due to the increase of the repulsion forces. The decomposition of CL-20 conformer may mainly originate from the fission of the pseudo-equatorial positioning of nitro groups, especially for CL-20 III conformer because of the significant low activation energy.     

Single-Crystalline TiO2(B) Nanobelts with Unusual Large Exposed {100} Facets and Enhanced Li-Storage Capacity

The {100} facet of single-crystalline TiO₂(B) is an ideal platform for inserting Li ions, but it is hard to be obtained due to its high surface energy. Here, the single-crystalline TiO₂(B) nanobelts from H₂Ti₃O₇ with nearly 70% {100} facets exposed are synthesized, which significantly enhances Li-storage capacity. The first-principle calculations demonstrate an ab in-plane 2D diffusion through the exposed {100} facets. As a consequence, the nanobelts can significantly accommodate Li ions in LiTiO₂ formula with specific capacity up to 335 mAh g⁻¹, which is in good agreement with the electrochemical characterizations. Coating with conductive and protective poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate), the cut-off discharge voltage is as low as 0.5 V, leading to a capacity of 160.7 mAh g⁻¹ after 1500 cycles with a retention rate of 66% at 1C. This work provides a practical strategy to increase the Li-ion capacity and cycle stability by tailoring the crystal orientation and nanostructures.     

Highly disordered ionic distribution in α-dicalcium silicate for structure relaxation

Dicalcium silicate, which is found in steelmaking slag for dephosphorization, exists as the hexagonal α phase at high temperatures. The α-dicalcium silicate forms a solid solution with tricalcium phosphate in the entire composition range, although the reason for high solubility of phosphorus remains unclear in view of the crystal structure. It has previously been reported that the crystal structure of α-dicalcium silicate consists of a symmetric arrangement of Ca²⁺ ions and SiO₄⁴⁻ tetrahedra, although other polymorphs exhibit asymmetric arrangements. However, because the occupation probability of each atomic site in the α polymorph is not limited to unity, it has not been qualified how these ions are exactly arranged. In this study, the ionic distribution in the α polymorph of dicalcium silicate was evaluated by first-principles calculation based on density functional theory (DFT), as well as by molecular dynamics (MD) simulation with a polarizable ion model optimized by DFT calculation. The results indicated that the completely symmetric ionic arrangement, as reported for the α phase, is the most unstable. Electronic-state calculation and MD simulation indicated that a highly disordered ionic arrangement spontaneously forms in the α-phase crystal for structure relaxation when held at high temperatures, or when phosphorus is incorporated.     

Integration of machine learning and first principles models

Model building and parameter estimation are traditional concepts widely used in chemical, biological, metallurgical, and manufacturing industries. Early modeling methodologies focused on mathematically capturing the process knowledge and domain expertise of the modeler. The models thus developed are termed first principles models (or white-box models). Over time, computational power became cheaper, and massive amounts of data became available for modeling. This led to the development of cutting edge machine learning models (black-box models) and artificial intelligence (AI) techniques. Hybrid models (gray-box models) are a combination of first principles and machine learning models. The development of hybrid models has captured the attention of researchers as this combines the best of both modeling paradigms. Recent attention to this field stems from the interest in explainable AI (XAI), a critical requirement as AI systems become more pervasive. This work aims at identifying and categorizing various hybrid models available in the literature that integrate machine-learning models with different forms of domain knowledge. Benefits such as enhanced predictive power, extrapolation capabilities, and other advantages of combining the two approaches are summarized. The goal of this article is to consolidate the published corpus in the area of hybrid modeling and develop a comprehensive framework to understand the various techniques presented. This framework can further be used as the foundation to explore rational associations between several models.     

基于VMD和改进TCN的短期光伏发电功率预测

光伏发电功率存在波动性,且光伏出力易受各种气象特征影响,传统TCN网络容易过度强化空间特性而弱化个体特性。针对上述问题,文中提出一种基于VMD和改进TCN的短期光伏发电功率预测模型。通过VMD将原始光伏发电功率时间序列分解为若干不同频率的模态分量,将各个模态分量以及相对应的气象数据输入至改进TCN网络进行建模学习。利用中心频率法确定VMD的最优分解模态分解个数。在传统TCN预测模型的基础上,使用DropBlock正则化取代Dropout正则化以达到抑制卷积层中信息协同的效果,并引入注意力机制自主挖掘并突出关键气象输入特征的影响,量化各气象因素对光伏发电的影响,从而提高预测精度。以江苏省某光伏电站真实数据为例进行仿真实验,结果表明所提预测方法的RMSE为0.62 MW,MAPE为2.03%。     

Vanadium based zinc spinel oxides: Potential materials as photoanode for water oxidation and optoelectronic devices

In the recent past, layered zinc-based vanadium spinel oxides (ZnVOs) have shown an intriguing way to accomplish the challenges of energy conversion, storage, and utilization issues. Here, through first-principles calculations, a comprehensive study has been carried out to investigate the AV₂M (where A = Zn, Zn₂, Zn₃, Zn_4, and M = O₄, O₆, O₇, O₈, O₉ respectively) electronic, photocatalytic, and optical properties. Formation energies with a negative sign express that the final compounds from the pure elements are possible and cohesive energies revealed that compounds are energetically stable. Spin-polarized calculations are also taken into account for better approximation of the electronic properties (band structure and density of states). All layered structures show indirect bandgap for spin-up calculations in range 0.3 eV–2.4 eV, while spin-down calculations show mix trends in range 2.3 eV–3.50 eV. An appropriate band edge with large enough kinetic over-potentials of the oxygen evolution reaction (ΔE_V ≥ 1.244 eV) makes them potential candidates as photoanode for water splitting. ZnV₂O₄ is more suitable for OER as it has small kinetic overpotential as compared to the oxidation potential of water. Interestingly, all ZnVOs display a dramatically large coefficient (~10⁵ cm⁻¹) for optical absorption. Photogenerated electrons and holes on the layered zinc-based vanadium spinel oxide surfaces could make these spinel oxides promising materials for photocatalytic water splitting and solar energy conversion.