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The synthesis of [(PbSe)1+δ]m(TiSe2)n[(SnSe2)1+γ]m(TiSe2)n heterostructures with designed nanoarchitectures by self assembly of amorphous precursors

Targeted heterostructures containing intergrown two dimensional (2D) layers of 3 different constituent layers, SnSe2, PbSe and TiSe2, were prepared by controlling the composition and sequence of elemental bilayers within a designed precursor. Varying the structure of the precursor enabled the number...

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Bibliographic Details
Published in:Nanoscale 2016-07, Vol.8 (28), p.13646-13651
Main Authors: Merrill, Devin R, Sutherland, Duncan R, Ditto, Jeffrey J, Moore, Daniel B, Falmbigl, Matthias, Medlin, Douglas L, Johnson, David C
Format: Article
Language:English
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Summary:Targeted heterostructures containing intergrown two dimensional (2D) layers of 3 different constituent layers, SnSe2, PbSe and TiSe2, were prepared by controlling the composition and sequence of elemental bilayers within a designed precursor. Varying the structure of the precursor enabled the number of structural units of each constituent and the sequence of crystalline 2D layers to be precisely controlled. The stacking of the 2D layers, their structures, and the segregation of the elements between them were determined using X-ray diffraction and electron microscopy techniques, with the observed sequence of the 2D layers consistent with the targeted intergrowth. This ability to prepare targeted heterostructures is critical, since the number of possible configurations in the final compound increases rapidly as the number of constituents increases, from almost 60 000 with two constituents to over 130 million with three constituents and to over 35 billion with four constituents for 20 or fewer distinct layers in the unit cell. This general route for synthesizing specific multiple component heterostructures will accelerate the feedback loop in this growing research area, permitting theorists to assume specific structures in the search for enhanced properties and providing experimentalists with crystallographically aligned samples to test these predictions.
ISSN:2040-3364
2040-3372
DOI:10.1039/c6nr03406c