In situ observation of synthesized nanoparticles in ultra-dilute aerosols via X-ray scattering

In-air epitaxy of nanostructures (Aerotaxy) has recently emerged as a viable route for fast, large-scale production. In this study, we use small-angle X-ray scattering to perform direct in-flight characterizations of the first step of this process, i.e., the engineered formation of Au and Pt aerosol nanoparticles by spark generation in a flow of N₂ gas. This represents a particular challenge for characterization because the particle density can be extremely low in controlled production. The particles produced are examined during production at operational pressures close to atmospheric conditions and exhibit a lognormal size distribution ranging from 5–100 nm. The Au and Pt particle production and detection are compared. We observe and characterize the nanoparticles at different stages of synthesis and extract the corresponding dominant physical properties, including the average particle diameter and sphericity, as influenced by particle sintering and the presence of aggregates. We observe highly sorted and sintered spherical Au nanoparticles at ultra-dilute concentrations (< 5 × 10⁵ particles/cm³) corresponding to a volume fraction below 3 × 10^–10, which is orders of magnitude below that of previously measured aerosols. We independently confirm an average particle radius of 25 nm via Guinier and Kratky plot analysis. Our study indicates that with high-intensity synchrotron beams and careful consideration of background removal, size and shape information can be obtained for extremely low particle concentrations with industrially relevant narrow size distributions.

     

罩式退火温度对高强IF钢组织及性能的影响

为研究不同退火温度下高强IF钢的组织性能及织构的变化规律,采用温箱式电阻炉加热模拟罩式退火工艺,研究了不同退火温度下高强IF钢210P1冷轧板力学性能;对不同退火温度钢板的r90进行了统计并对其进行显微组织观察;采用X射线衍射仪及热场发射扫描电镜对不同退火温度的罩式退火成品板进行了织构分析。结果表明,在高强IF钢210P1冷轧板的罩式退火过程中,提高退火温度将使晶粒明显长大。随着退火温度的升高,屈服强度及抗拉强度下降,伸长率升高,n值略有上升,板材横向r值增加较明显,有利织构{111}取向密度增加,不利织构{100}取向密度降低。     

Enhanced Multi-attribute Combinative Double Auction (EMCDA) for Resource Allocation in Cloud Computing

Wireless Personal Communications - Cloud computing is a growing technology where lot of heterogeneous resources are available and large amount of requests are submitted by the customers...     

Evaluation of the degree of rate control via automatic differentiation

The degree of rate control (DRC) quantitatively identifies the kinetically relevant (sometimes known as rate-limiting) steps of a complex reaction network. This concept relies on derivatives which are commonly implemented numerically, for example, with finite differences (FDs). Numerical derivatives are tedious to implement, and can be problematic, and unstable or unreliable. In this study, we demonstrate the use of automatic differentiation (AD) in the evaluation of the DRC. AD libraries are increasingly available through modern machine learning frameworks. Compared with the FDs, AD provides solutions with higher accuracy with lower computational cost. We demonstrate applications in steady-state and transient kinetics. Furthermore, we illustrate a hybrid local-global sensitivity analysis method, the distributed evaluation of local sensitivity analysis, to assess the importance of kinetic parameters over an uncertain space. This method also benefits from AD to obtain high-quality results efficiently.