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Preparation and Characterization of Porous Carbon/RDX Nanocomposite Energetic Materials

Jiang Ju, Su Jin-Xiao, Liu Zhi-Tao, Du Ping, Liao Xin, Li Xiao-An

Central European Journal of Energetic Materials

2023

Vol. 20, no. 3

284--301

A novel energetic material was fabricated by filling porous carbon with 1,3,5-trinitro-1,3,5-triazinane (RDX) via the ultrasonic stirring method. Characterization (TEM, BET, XRD, FTIR, etc.) was performed to determine the micromorphology, crystal structure, and specific surface area. TEM images indicated that the RDX particles were homogeneously distributed in the channels of the porous carbon, FTIR spectra and the XRD curve of the C/RDX composite exhibited the combined characteristics of porous carbon and RDX. The BET test data also confirmed this situation. The thermal decomposition kinetics and thermodynamics of the C/RDX nanocomposite energetic material were investigated at various heating rates (5, 10, 15, and 20 K·min⁻¹). The test results showed that the thermal decomposition temperature and the critical temperature of thermal explosion were lower than for RDX alone by 46.8 and 40.69 ℃, respectively. The activation energy of the C/RDX composite was lower than those of raw RDX and a C/RDX physical mixture, indicating that the C/RDX composite exhibited high thermolysis activity.

Quality assessment of Moringa seed shells based on fingerprinting using HPLC-DAD

Zhu Yangin, Du Ping, Huang Shaojun, Yin Qinhong, Yang Yaling

Acta Chromatographica

2020

Vol. 32, no. 1

28--33

A fingerprint analysis method was established for the quality control of Moringa seed shells by high-performance liquid chromatography with diode array detection (HPLC–DAD). The HPLC–DAD separation was performed on a Thermo Hypersil Gold C18 (4.6 mm × 250 mm, 5 μm) column by gradient elution with acetonitrile–water as mobile phase. The fingerprint of Moringa seed shells was established with good precision, reproducibility, and stability obtaining within 60 min, and 13 common peaks in the fingerprint were designed. Similarity analysis, principal component analysis (PCA), and hierarchical clustering analysis (HCA) were carried out to analyze the obtained fingerprints. The similarity among 11 batches of samples in addition to No. 5 and 6 was no less than 0.92. Eleven samples could be classified into 2 clusters. The HPLC fingerprint technology and application of chemical pattern recognition can provide a more comprehensive reference for the quality control of medicinal plants.