基于流量测点的热网变动阻力系数优化辨识

随着供热计量系统的普及，系统可以根据负荷的变化进行调整，管网的阻力系数随即发生变化。对变动阻力系数进行优化辨识是了解供热管网实时运行状况的有效手段。提出一种基于流量监测数据的供热管网变动阻力系数优化辨识方法，并利用遗传算法进行求解。对洛阳市某小区供暖季管网实际运行数据进行验证，辨识结果的相对误差在5%以内。结果表明：该方法可以在只有流量观测数据时得到精度较高的供热管网变动阻力系数，为供热系统的运行调节提供指导。     

“联用技术及元素形态”国际课程探索与实践*

充分利用线上教学的优势,对化学院本科生开设了“联用技术及元素形态”国际课程,避免了传统教学中组织、协调外籍/外地专家资源过程中必要的各种消耗,极大程度地整合教学资源、改善教学效果。在该课程的探索与实践过程中,学生们对痕量元素形态及基于等离子体质谱的各种联用技术产生了极大的兴趣,激发了他们的主动学习热情;教师之间及师生之间的沟通趋向更简单、更灵活、更实时,为后续线上线下混合式国际课程建设提供了良好的基础和借鉴。     

Optimization of heterogeneous Catalyst-assisted fatty acid methyl esters biodiesel production from Soybean oil with different Machine learning methods

There is a growing attention to the bio and renewable energies due to fast depletion of fossil fuels as well as the global warming problem. Here, we developed a modeling and simulation method by means of artificial intelligence (AI) for prediction of the bioenergy production from vegetable bean oil. AI methods are well known for prediction of complex and nonlinear process. Three distinct Adaptive Boosted models including Huber regression, LASSO, and Support Vector Regression (SVR) as well as artificial neural network (ANN) were applied in this study to predict actual yield of Fatty acid methyl esters (FAME) production. All boosted utilizing the Adaptive boosting algorithm. The important influencing parameters on the biodiesel production such as the catalyst loading (CAO/Ag, wt%) and methanol to oil (Soybean oil) molar ratio were selected as the input variables of models while the yield of FAME production was selected as output. Model hyper-parameters were tuned to maintain generality while improving prediction accuracy. The models were evaluated using three distinct metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Error rates of 8.16780E-01, 4.43895E-01, 2.06692E + 00, and 3.92713 E-01 were obtained with the MAE metric for boosted Huber, SVR, LASSO and ANN models. On the other hand, the RMSE error of these models were about 1.092E-02, 1.015E-02, 2.669E-02, and 1.01174E-02, respectively. Finally, the R-square score were calculated for boosted Huber, boosted SVR, and boosted LASSO as 0.976, 0.990, 0.872, and 0.99702, respectively. Therefore, it can be concluded that although the boosted SVR and ANN models were better models for prediction of process efficiency in terms of error, but all algorithms had high accuracy. The optimum yield of 83.77% and 81.60% for biodiesel production were observed at optimum operating values from boosted SVR and ANN models, respectively.     

Pressure-induced novel structure with graphene-like boron-layer in titanium monoboride

The recent discovery of the novel boron-framework in boron-rich metal borides with complex structures and intriguing features under high pressure has stimulated the search into the unique boron-network in the metal monoborides or boron-deficient metal borides at high pressure. Herein, based on the particle swarm optimization algorithm combined with first-principles calculations, we thoroughly explored the structural evolution and properties of TiB up to 200 GPa. This material undergoes a pressure-induced phase transition of $Pnma$ $\to $ $Cmcm$ $\to $ $Pmmm$. Besides of two known phases $Pnma$ and $Cmcm$, an unexpected orthorhombic $Pmmm$ structure was predicted to be energetically favored in the pressure range of 110.88-200 GPa. Intriguingly, the B covalent network eventually evolved from a one-dimensional zigzag chain in $Pnma$-TiB and $Cmcm$-TiB to a graphene-like B-sheet in $Pmmm$-TiB. On the basis of the microscopic hardness model, the calculated hardness ($H_{\rm v}$) values of $Pnma$ at 1 atm, $Cmcm$ at 100 GPa, and $Pmmm$ at 140 GPa are 36.81 GPa, 25.17 GPa, and 15.36 GPa, respectively. Remarkably, analyses of the density of states, electron localization function and the crystal orbital Hamilton population (COHP) exhibit that the bonding nature in the three TiB structures can be considered as a combination of the B-B and Ti-B covalent interactions. Moreover, the high hardness and excellent mechanical properties of the three TiB polymorphs can be ascribed to the strong B-B and Ti-B covalent bonds.     

On the Integration of Dielectrometry into Electrochemical Impedance Spectroscopy to Obtain Characteristic Properties of a Dielectric Thin Film

We demonstrate a novel impedimetric approach providing unprecedented insight into characteristic properties of dielectric thin films covering electrode surfaces. The concept is based on the joint interpretation of electrochemical impedance spectroscopy (EIS) together with dielectrometry (DEM) whose informative value is mutually interconnected. The advantage lies in the synergistic compensation of individual shortcomings adversely affecting conventional impedimetric analysis strategies relying exclusively on either DEM or the traditional EIS approach, which in turn allows a reliable determination of thickness and permittivity values. The versatility of the method proposed is showcased by an in-situ growth-monitoring of a nanoporous, crystalline thin film (HKUST-1) on an interdigitated electrode geometry.     

光纤基底TiNi形状记忆合金薄膜制备工艺

将TiNi基记忆合金薄膜与光纤相结合可制成智能化、集成化且成本经济的微机电系统和微传感器件.本文采用磁控溅射法在二氧化硅光纤基底上制备TiNi记忆合金薄膜,系统讨论了溅射工艺参数以及后续退火处理对薄膜质量的影响.采用自研制光纤镀膜掩膜装置在直径为125μm的光纤圆周表面上形成均匀薄膜.实验表明:在靶基距、背底真空度、Ar气流量和溅射时间一定的条件下,溅射功率存在最佳值;溅射压强较大时,薄膜沉积速率较低,但薄膜表面粗糙度较小.进行退火处理后,薄膜形成较良好的晶体结构,Ti_49.09Ni_50.91薄膜中马氏体B19′相和奥氏体B2相共存,但以B19′为主.根据本文研究结果,在玻璃光纤基底上制备高质量的TiNi基记忆合金薄膜是可实现的,本工作为下一步研制微机电系统和微型传感器做了基础准备.     

Generalized Jacobi spectral Galerkin method for fractional pantograph differential equation

This work is concerned with the extension of the Jacobi spectral Galerkin method to a class of nonlinear fractional pantograph differential equations. First, the fractional differential equation is converted to a nonlinear Volterra integral equation with weakly singular kernel. Second, we analyze the existence and uniqueness of solutions for the obtained integral equation. Then, the Galerkin method is used for solving the equivalent integral equation. The error estimates for the proposed method are also investigated. Finally, illustrative examples are presented to confirm our theoretical analysis.     

Effect of biaxial strain and hydrostatic pressure on the magnetic properties of bilayer CrI3

Two-dimensional van der Waals magnetic materials are intriguing for applications in the future spintronics devices, so it is crucial to explore strategy to control the magnetic properties. Here, we carried out first-principles calculations and Monte Carlo simulations to investigate the effect of biaxial strain and hydrostatic pressure on the magnetic properties of the bilayer CrI₃. We found that the magnetic anisotropy, intralayer and interlayer exchange interactions, and Curie temperature can be tuned by biaxial strain and hydrostatic pressure. Large compressive biaxial strain may induce a ferromagneticto-antiferromagnetic transition of both CrI₃ layers. The hydrostatic pressure could enhance the intralayer exchange interaction significantly and hence largely boost the Curie temperature. The effect of the biaxial strain and hydrostatic pressure revealed in the bilayer CrI₃ may be generalized to other two-dimensional magnetic materials.