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Crystal Face Distributions and Surface Site Densities of Two Synthetic Goethites: Implications for Adsorption Capacities as a Function of Particle Size.

Kenneth J T LiviMario VillalobosRowan LearyMaria VarelaJon BarnardMilton Villacís-GarcíaRodolfo ZanellaAnna GoodridgePaul Midgley
Published in: Langmuir : the ACS journal of surfaces and colloids (2017)
Two synthetic goethites of varying crystal size distributions were analyzed by BET, conventional TEM, cryo-TEM, atomic resolution STEM and HRTEM, and electron tomography in order to determine the effects of crystal size, shape, and atomic scale surface roughness on their adsorption capacities. The two samples were determined by BET to have very different site densities based on CrVI adsorption experiments. Model specific surface areas generated from TEM observations showed that, based on size and shape, there should be little difference in their adsorption capacities. Electron tomography revealed that both samples crystallized with an asymmetric {101} tablet habit. STEM and HRTEM images showed a significant increase in atomic-scale surface roughness of the larger goethite. This difference in roughness was quantified based on measurements of relative abundances of crystal faces {101} and {201} for the two goethites, and a reactive surface site density was calculated for each goethite. Singly coordinated sites on face {210} are 2.5 more dense than on face {101}, and the larger goethite showed an average total of 36% {210} as compared to 14% for the smaller goethite. This difference explains the considerably larger adsorption capacitiy of the larger goethite vs the smaller sample and points toward the necessity of knowing the atomic scale surface structure in predicting mineral adsorption processes.
Keyphrases
  • electron microscopy
  • aqueous solution
  • deep learning
  • mass spectrometry
  • machine learning
  • solid state
  • convolutional neural network
  • single molecule