钨中空位及其团簇的能量学和动力学性质参数

在总结前人钨中空位及其团簇的能量学和动力学行为的研究成果基础上，采用第一性原理方法系统计算了钨中空位及其团簇的结合能和扩散能垒。研究发现，交换关联泛函PW91和PBE较PBEsol、AM05和LDA更适合用于计算钨空位的能量学性质。基于第一性原理计算结果对文献中单空位形成能、双空位作用性质等争议性问题进行了讨论，并对钨经验势进行了评估。研究结果表明，钨中孤立单空位间总是相互排斥，而空位团簇（V_n>3）对单空位具有很强的吸引作用，其结合能随着所含空位个数增多呈现波动性增大的趋势。空位团簇稳定结构可通过最小化Wigner-Seitz表面积来确定，其结合能与V_n与V_n-1之间的Wigner-Seitz面积之差呈正比。     

A Skin-Inspired Triboelectric Nanogenerator with an Interpenetrating Structure for Motion Sensing and Energy Harvesting

Rapid advancements in wearable electronics impose the challenge on power supply devices. Herein, a flexible single-electrode triboelectric nanogenerator (SE-TENG) that enables both human motion sensing and biomechanical energy harvesting is reported. The SE-TENG is fabricated by interpenetrating Ag-coated polyethylene terephthalate (PET) nanofibers within a polydimethylsiloxane (PDMS) elastomer. The Ag coating and PDMS are performed as the electrode and dielectric material for the SE-TENG, respectively. The Ag-coated PET nanofibers enlarge the electrode surface area, which is beneficial to increase sensing sensitivity. The flexible SE-TENG sensor shows the capability of outputting alternating electrical signals with an open-circuit voltage up to 50 V and a short-circuit current up to 200 nA in response to externally applied pressure. It is used to sense various types of human motions and harvest electric energy from body motion. The harvested energy can successfully power wearable electronics, such as an electronic watch and light-emitting diode. Therefore, the as-prepared SE-TENG sensor with a pressure response and self-powered capability provides potential applications in wearable sensors or flexible electronics for personal healthcare and human–machine interfaces.     

中国石油工业上游发展面临的挑战与未来科技攻关方向

石油和天然气是全球和中国最重要的一次能源。石油工业的生存发展是由油气资源、市场、技术和社会政治经济环境等要素决定的，其中，技术进步是最活跃和最关键的因素之一。中国已成为全球油气生产消费大国，中国石油工业上游的发展也高度依赖石油科技的进步。中国石油工业已形成了先进完整的理论技术研发和装备制造体系，支撑了油气产量持续稳产和增产。未来是中国社会经济发展的关键期，石油工业必将面对重大挑战与新的技术需求，大力实施国家创新战略，发展具有国际领先水平的新一代勘探开发理论技术，支撑油气产业发展，保障国家油气能源安全。中国石油工业上游在未来面临的重大挑战与技术需求包括：①满足中国未来现代化建设的巨大油气需求和保障油气供应安全，这当中必须加大中国油气勘探开发，同时进一步扩大全球及"一带一路"油气投资与生产；②实现中国石油长期稳产2×10⁸t/a以上；③实现中国天然气产量上升至3 000×10⁸m³/a并长期稳产；④发展海洋及深水油气勘探开发先进技术与装备；⑤形成新一代石油工程服务技术装备和数字化转型。中国石油工业上游未来的科技攻关方向和研发重点包括：①先进的石油大幅度提高采收率技术；②大气田勘探与复杂气田提高采收率技术；③非常规油气勘探开发技术；④海洋及深水油气勘探开发技术及装备；⑤"一带一路"油气勘探开发技术；⑥新一代石油工程服务技术装备和数字化转型。     

Surface energies in high-entropy carbides with variable carbon stoichiometry

The carbon vacancy in high-entropy carbides (HECs) has a significant impact on their physical and chemical properties, yet relevant studies have still been relatively few. In this study, we investigate the surface energies of HECs with variable carbon vacancies through first-principles calculations. The results show that the surface energy of the (1 0 0) surface of the stoichiometric HECs is significantly lower than that of (1 1 1) surface. With the decrease in carbon stoichiometry, the surface energies of both (1 0 0) and (1 1 1) surfaces increase gradually, which is mainly due to the weakening of covalent bonding and the decrease of metal Hirshfeld-I (HI) charges. However, the surface energy of (1 0 0) surface increases more quickly than that of (1 1 1) surface and will exceed that of (1 1 1) surface when the carbon stoichiometry decreases to a certain extent, which is primarily attributed to the greater decrease rate of metal HI charges of (1 0 0) surface.     

Towards artificial intelligence at scale in the chemical industry

In the Industry 4.0 era, the chemical industry is embracing broad adoption of artificial intelligence (AI) and machine learning (ML) methods. This article provides a holistic view of how the industry is transforming digitally towards AI at scale. First, a historical perspective on how the industry used AI to aid humans in better decision-making is shown. Then state-of-the-art AI research addressing industrial needs on reliability and safety, process optimization, supply chain, material discovery, and reaction engineering is highlighted. Finally, a vision of the plant of the future is illustrated with critical components of AI-ready culture, model life cycle management, and renewed role of humans in chemical manufacturing.     

An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, due to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric modulated arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. The computational experiments considered a pool of twelve difficult head-and-neck tumor cases. It was possible to observe that, for some of these cases, the optimized noncoplanar arc trajectories led to significant treatment planning quality improvements, when compared with coplanar VMAT treatment plans. Although these experiments were done in a research environment treatment planning software (matRad), the conclusions can be of interest for a clinical setting: automated procedures can simplify the current treatment workflow, produce high-quality treatment plans, making better use of human resources and allowing for unbiased comparisons between different treatment techniques.     

超高层劲性结构及大型机械设备立体协同施工技术

基于某超高层建筑群项目的主体施工阶段,对超高层劲性结构建筑群项目施工过程中可能遇到的问题,诸如大型机械立体协同、钢结构与钢筋连接节点优化、钢结构桁架层施工等重难点进行总结分析,并提出相应的解决方案以供探讨,可为同类型工程提供参考经验。     

Rapid synthesis of garnet-type Li7La3Zr2O12 solid electrolyte with superior electrochemical performance

Li₇La₃Zr₂O₁₂-based garnet-type solid electrolytes are promising candidates for use in all-solid-state lithium batteries (ASSLBs). However, their potential in large-scale commercial applications is largely hindered by the time/energy-consuming and lithium-wasting synthetic method which typically needs a long-duration high temperature solid state reaction process. Herein we invent a fast preparation route that involves a short-period thermal reaction (1100 °C for 10 min) in laboratory muffle furnaces following by conventional hot pressing technique to get almost fully dense (Al, Ga, Ta, Nb)-doped garnet-type electrolytes with high phase purity (>99.9 %). The large and compact grains, low porosity and high phase purities of garnet ceramic electrolytes synthesized in this study ensure superior electrochemical performance. Particularly, Ga-doped cubic Li₇La₃Zr₂O₁₂ shows extremely low E_a values (0.17?0.18 eV) and record-high lithium ionic conductivities (>2 × 10^?3 S cm^-1 at 25 °C).     

Direct additive manufacturing of melt growth Al2O3-ZrO2 functionally graded ceramics by laser directed energy deposition

Functionally graded ceramics (FGC), which combine properties of different ceramics in one part, usually have better comprehensive function and structural efficiency. In this study, four different gradient transition Al₂O₃-ZrO₂ FGC samples were prepared by laser directed energy deposition (LDED) method. The results show that there is an obvious interface in direct transition sample. The transition section bears tensile stress caused by difference of thermophysical properties of materials, resulting in significant longitudinal cracks. Element transition in interface region shows a step sharp transition. The direct transition sample shows intergranular fracture and the bonding strength is very low. Gradient transition mode can effectively suppress cracks, and avoid the step transition of microstructure and elements. Elements, microhardness of 25, 20 wt% FGC samples realized a nearly linear smooth transition. The interface fracture of FGC samples changed to transgranular fracture, bonding strength was significantly improved, and the maximum flexural strength reached 160.19 MPa.     

基于孪生支持向量回归机的转炉炼钢终点预测

为了提高转炉炼钢的终点命中率，建立了一种新的转炉终点预测模型，实现了对转炉终点碳质量分数和温度的准确预测。模型采用K最近邻孪生支持向量机(KNNWTSVR)算法，将权重矩阵引入到目标函数中，并利用鲸群优化算法进行求解，提高了传统算法的性能；然后基于某炼钢厂260 t转炉的实际生产数据，建立了转炉炼钢终点预测模型。结果表明，预测模型的终点碳质量分数(误差±0.005%)和温度(误差±15 ℃)的终点单命中率分别为94%和88%，双命中率达到84%。与其他两种现有的建模方法相比，本模型取得了最优的预测效果。该方法满足转炉炼钢实际生产的需求，也可适用于钢铁冶金其他领域的数学建模。