0000000001137794

AUTHOR

Ran Bi

showing 2 related works from this author

Incorporation of trace metals Cu, Zn, and Cd into gypsum: Implication on their mobility and fate in natural and anthropogenic environments

2020

Abstract The coexistence of calcium (Ca2+), sulfate (SO42−) with trace metal cations (M(II)) can possibly lead to M(II)-gypsum coprecipitation and solid solution formation. However, gypsum's role in the fixation of M(II) is still largely unknown. This study investigated the precipitation of Ca2+ and SO42− in the presence of M(II) (i.e., Cu2+, Zn2+, or Cd2+) and the incorporation of the metal cations into the gypsum structure at different environmental conditions. Trace metals in two natural gypsum samples (Yunnan and Neimeng, China) and one hydrometallurgical byproduct gypsum sample from a Cu refinery were also assessed. X-ray diffraction, scanning electron microscopy-energy dispersive X-ra…

SupersaturationGypsum010504 meteorology & atmospheric sciencesTrace AmountsPrecipitation (chemistry)CoprecipitationInorganic chemistryGeologyengineering.material010502 geochemistry & geophysics01 natural sciencesMetalchemistry.chemical_compoundchemistryGeochemistry and Petrologyvisual_artengineeringvisual_art.visual_art_mediumTrace metalSulfateGeology0105 earth and related environmental sciencesChemical Geology
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Global stability of coupled Markovian switching reaction–diffusion systems on networks

2014

Abstract In this paper, we investigate the stability problem for some Markovian switching reaction–diffusion coupled systems on networks (MSRDCSNs). By using the Lyapunov function, we establish some novel stability principles for stochastic stability, asymptotically stochastic stability, globally asymptotically stochastic stability and almost surely exponential stability of the MSRDCSNs. These stability principles have a close relation to the topology property of the network. We also provide a systematic method for constructing global Lyapunov function for these MSRDCSNs by using graph theory. The new method can help analyze the dynamics of complex networks.

Lyapunov functionRelation (database)Computer Science Applications1707 Computer Vision and Pattern RecognitionTopology (electrical circuits)Graph theoryStochastic coupled systemsComplex networkStability (probability)Computer Science Applicationssymbols.namesakeControl and Systems EngineeringControl theoryReaction–diffusion systemNetworks; Reaction-diffusion; Stability; Stochastic coupled systems; Control and Systems Engineering; Analysis; Computer Science Applications1707 Computer Vision and Pattern RecognitionsymbolsApplied mathematicsNetworksReaction-diffusionMarkovian switchingStabilityAnalysisMathematicsNonlinear Analysis: Hybrid Systems
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