A Gaussian convolutional optimization algorithm with tent chaotic mapping.

To solve the problems of the traditional convolution optimization algorithm (COA), which are its slow convergence speed and likelihood of falling into local optima, a Gaussian mutation convolution optimization algorithm based on tent chaotic mapping (TCOA) is proposed in this article. First, the tent chaotic strategy is employed for the initialization of individual positions to ensure a uniform distribution of the population across a feasible search space. Subsequently, a Gaussian convolution kernel is used for an extensive depth search within the search space to mitigate the likelihood of any individuals converging to a local optimum.

[Radial growth response of to climate change in the Cele desert oasis ecotone, China].

is an important tree species in the arid regions of Northwest China, which is sensitive to climate changes. Climate of the Northwest China is changing to be "warm and humid", but how it would affect the regional forest growth is not clear. In this study, the radial growth response of to major climatic factors and their temporal changes during 1984-2021 were analyzed by using dendrochronology method in the desert oasis ecotone of Cele in the southern Tarim basin.

Few-Shot Fault Diagnosis Based on an Attention-Weighted Relation Network.

As energy conversion systems continue to grow in complexity, pneumatic control valves may exhibit unexpected anomalies or trigger system shutdowns, leading to a decrease in system reliability. Consequently, the analysis of time-domain signals and the utilization of artificial intelligence, including deep learning methods, have emerged as pivotal approaches for addressing these challenges. Although deep learning is widely used for pneumatic valve fault diagnosis, the success of most deep learning methods depends on a large amount of labeled training data, which is often difficult to obtain.

Nitrogen-Doped Carbon-Assisted One-pot Tandem Reaction for Vinyl Chloride Production via Ethylene Oxychlorination.

A bifunctional catalyst comprising CuCl /Al O and nitrogen-doped carbon was developed for an efficient one-pot ethylene oxychlorination process to produce vinyl chloride monomer (VCM) up to 76 % yield at 250 °C and under ambient pressure, which is higher than the conventional industrial two-step process (≈50 %) in a single pass. In the second bed, active sites containing N-functional groups on the metal-free N-doped carbon catalyzed both ethylene oxychlorination and ethylene dichloride (EDC) dehydrochlorination under the mild conditions. Benefitting from the bifunctionality of the N-doped carbon, VCM formation was intensified by the surface Cl*-looping of EDC dehydrochlorination and ethylene oxychlorination.

Promotional effect of in situ generated hydroxyl on olefin selectivity of Co-catalyzed Fischer-Tropsch synthesis.

The understanding of the water effect on olefin selectivity in Fischer-Tropsch synthesis (FTS) is limited by the complexity of the reaction network. Herein, we employ propene hydrogenation as a model reaction to isolate the water effect on olefin adsorption and hydrogenation from the complex reaction of FTS. It is clearly observed that the added water inhibits the activity of propene hydrogenation on two cobalt catalysts supported on high-surface-area alumina (HAS AlO) and low-surface-area alumina (LSA AlO), respectively.

Towards rational catalyst design: boosting the rapid prediction of transition-metal activity by improved scaling relations.

Understanding the scaling relations of adsorption energies and activation energies greatly facilitates the computational catalyst design. To reduce the computational cost and guarantee efficiency, improved scaling relations were advocated in this study to rapidly acquire the energetics for transition metal surface reactions and further to rapidly and effectively map the activity of transition-metal catalysts. The overall catalytic activity for the surface reactions between C-, H- and O-containing species could be related to their adsorption energies using C, H and O binding energies as descriptors via improved scaling relations.

Potassium adsorption behavior on hcp cobalt as model systems for the Fischer-Tropsch synthesis: a density functional theory study.

Potassium (K), an important impurity in syngas from biomass, can have a large influence on the activity and selectivity of cobalt-based Fischer-Tropsch synthesis (FTS) catalysts in Biomass to Liquids (BTL) processes. In this work, the potassium adsorption behavior on hcp cobalt was systematically studied using density functional theory. The surface energy calculations and Wulff construction of the equilibrium shape of hcp cobalt showed it is dominated by 10 facets.