Predicting nanocrystal morphology governed by interfacial strain
Hongwei Liu, Xuan Cheng, Nagarajan Valanoor

TL;DR
This paper presents a model predicting the shape of NiO nanocrystals on substrates based on interfacial strain, explaining experimental observations and aiding design of hetero-epitaxial nanostructures.
Contribution
It introduces a quantitative model using the GWK theorem to predict nanocrystal shapes governed by interfacial strain, validated by experimental data.
Findings
Fully pseudomorphic interfaces lead to smooth embedded morphologies.
Relaxed interfacial strain results in truncated pyramidal shapes.
The model accurately predicts nanocrystal shapes and sizes.
Abstract
The shape dependence for the technologically important nickel oxide (NiO) nanocrystals on (001) strontium titanate substrates is investigated under the generalized Wulff-Kaichew (GWK) theorem framework. It is found that the shape of the NiO nanocrystals is primarily governed by the existence (or absence) of interfacial strain. Nanocrystals that have a fully pseudomorphic interface with the substrate (i.e. the epitaxial strain is not relaxed) form an embedded smooth ball-crown morphology with {001}, {011}, {111} and high-index {113} exposed facets with a negative Wulff point. On the other hand, when the interfacial strain is relaxed by misfit dislocations, the nanocrystals take on a truncated pyramidal shape, bounded by {111} faces and a {001} flat top, with a positive Wulff point. Our quantitative model is able to predict both experimentally observed shapes and sizes with good accuracy.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsZnO doping and properties · Copper-based nanomaterials and applications · Advanced Memory and Neural Computing
