Taiyuan University of Technology

About: Taiyuan University of Technology is a education organization based out in Taiyuan, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 19027 authors who have published 16996 publications receiving 194715 citations. The organization is also known as: TUT & TYUT.

A novel hybrid system for feature selection based on an improved gravitational search algorithm and k-NN method

Abstract: We propose an improved gravitational search algorithm which makes the best of ergodicity of piecewise linear chaotic map to explore the global search while utilizing the sequential quadratic programming to accelerate the local search.Based on the binary improved gravitational search algorithm and the k-nearest neighbor (k-NN) method, a novel hybrid system is proposed to improve classification accuracy with an appropriate feature subset in binary problems.The proposed system is able to select the discriminating input features correctly and achieve high classification accuracy which is comparable to or better than well-known similar classifier systems. Feature selection is an important pre-processing step for solving classification problems. This problem is often solved by applying evolutionary algorithms in order to decrease the dimensional number of features involved. In this paper, we propose a novel hybrid system to improve classification accuracy with an appropriate feature subset in binary problems based on an improved gravitational search algorithm. This algorithm makes the best of ergodicity of piecewise linear chaotic map to explore the global search and utilizes the sequential quadratic programming to accelerate the local search. We evaluate the proposed hybrid system on several UCI machine learning benchmark examples, comparing our approaches with feature selection techniques and obtained better predictions with consistently fewer relevant features. Furthermore, the improved gravitational search algorithm is tested on 23 nonlinear benchmark functions and compared with 5 other heuristic algorithms. The obtained results confirm the high performance of the improved gravitational search algorithm in solving function optimization problems.

Structure and photoluminescence evolution of nanodots during pyrolysis of citric acid: from molecular nanoclusters to carbogenic nanoparticles

Abstract: Citric-acid-derived carbon nanodots are increasingly being explored as novel fluorescent nanomaterials due to their strong photoluminescence (PL). However, an accurate picture of the formation of carbon nanodots and an exhaustive structure–property correlation are still lacking. Herein we present a systematic investigation of the formation mechanism of carbon nanodots by following the pyrolysis of a citric acid–diethylenetriamine precursor at different temperatures. The collective nanodots are investigated by dynamic rheological measurements, exhibiting a strong pyrolytic temperature dependence of the viscoelastic properties. Atomic force microscopy, transmission electron microscopy, and Raman spectroscopy reveal that the synthesized “dots” at different pyrolytic temperatures are different in essence, and the transition of their chemical structure from molecular clusters to carbogenic nanoparticles during pyrolysis is highly verified. We find that a molecular fluorophore with intense PL predominates at low temperature (<250 °C), but a newly created quasi-molecular fluorophore with blue-shifted and decreased PL quantum yield predominates at high temperatures (300 °C). Time-resolved photoluminescence spectroscopy suggests that the strong PL suppression at high temperature is due mostly to a dramatic increase in the nonradiative decay rate of the quasi-molecular electronic state.

Insights into the effect of surface hydroxyls on CO2 hydrogenation over Pd/γ-Al2O3 catalyst: A computational study

Abstract: The elementary steps leading to the formation of HCOO and CO via CO2 hydrogenation, two important intermediates contributing to methanol and methane formation, respectively, have been explored to identify hydroxylation effect of the oxide support on the selectivity in CO2 hydrogenation on Pd/γ-Al2O3 catalyst by the density functional theory together with slab model calculations. Two models: tetramer Pd4 cluster supported on the dry γ-Al2O3(1 1 0) surface, D(Pd4), and on the hydroxylated γ-Al2O3(1 1 0) surface, H(Pd4), have been employed to model Pd/γ-Al2O3 catalyst. Meanwhile, Pd(1 1 1) surface is used to model the unsupported large Pd particle sizes. On D(Pd4), the formation of CO is preferred both kinetically and thermodynamically. On H(Pd4), HCOO formation becomes more favorable kinetically while CO formation is more facile thermodynamically. However, Pd(1 1 1) surface has not shown strong selectivity and activity for CO2 hydrogenation to HCOO or CO. These results show that varying the properties of γ-Al2O3 support can alter the selectivity of CO2 hydrogenation, moreover, the presence and number of low-coordinated Pd particles is of great importance to improve the overall activity and selectivity of CO2 hydrogenation. Our results also show that to achieve high selectivity of CO2 hydrogenation, Pd/γ-Al2O3 catalyst has to get help from additives, which should be able to improve its dispersion or to control the hydroxylation. The present study provides the basis and one of the directions to the design of improved catalysts in CO2 hydrogenation for methanol, methane and other products.