MCM-41 silica particles with several morphologies have been controllably synthesized with a basic medium. Nanospherical MCM-41 silica with an average size of 110 nm was produced through reaction of extremely low surfactant concentrations of CTAB with TEOS in the sodium hydroxide medium at 353 K, while a submicrometer-sized silica rod, 0.3-0.6 µm in diameter and 1 µm in length, and micrometer-sized oblate silica with nominal diameter around 1 µm were synthesized in aqueous ammonia, where the size and the morphology were controlled by varing the content of the solvent. A morphogenetic mechanism that is based on the deposition of self-assembled silicate surfactant rodlike micelles is proposed and explains well the controllability of the morphology.

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The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can decompose signals into several narrow-band components, which is advantageous to quantitatively evaluate signal characteristics. In this paper, we present a comparative study of four kinds of adaptive decomposition algorithms, including some algorithms deriving from empirical mode decomposition (EMD), empirical wavelet transform (EWT), variational mode decomposition (VMD) and Vold–Kalman filter order tracking (VKF_OT). Their principles, advantages and disadvantages, and improvements and applications to signal analyses in dynamic analysis of mechanical system and machinery fault diagnosis are showed. Examples are provided to illustrate important influence performance factors and improvements of these algorithms. Finally, we summarize applicable scopes, inapplicable scopes and some further works of these methods in respect of precise filters and rough filters. It is hoped that the paper can provide a valuable reference for application and improvement of these methods in signal processing.