Structure Prediction of Ionic Epitaxial Interfaces with Ogre Demonstrated for Colloidal Heterostructures of Lead Halide Perovskites

Abstract

Colloidal epitaxial heterostructures are nanoparticles composed of two different materials connected at an interface, which can exhibit properties different from those of their individual components. Combining dissimilar materials offers opportunities to create several functional heterostructures. Yet, assessing structural compatibility (the main prerequisite for epitaxial growth) is challenging when pairing complex materials with different lattice parameters/crystal structures. This complicates both the selection of target heterostructures for synthesis and the assignment of interface models when new heterostructures are obtained. Here, we demonstrate Ogre as a powerful tool to accelerate the design and characterization of colloidal heterostructures. To this end we implemented developments tailored for the efficient prediction of epitaxial interfaces between ionic/polar materials, which encompass most colloidal semiconductors. These include pre-screening candidate models based on charge balance at the interface and using a classical potential for fast energy evaluations, with parameters automatically extracted from the input bulk structures. These developments are validated for CsPbBr3/Pb4S3Br2 heterostructures, where Ogre produces interface models in agreement with density functional theory and experiments. Furthermore, we use Ogre to rationalize the templating effect of CsPbCl3 on the growth of lead sulfochlorides, where perovskite seeds induce the formation of Pb4S3Cl2 rather than Pb3S2Cl2 due to better epitaxial compatibility. Combining Ogre simulations with experimental data enables us to unravel the structure and composition of the hitherto unsolved CsPbBr3/BixPbySz interface and assign a structure to many other reported metal halide/oxide based interfaces. The Ogre package is available on GitHub or via the OgreInterface desktop application, available for Windows, Linux and Mac.

103 pages, 48 figures

References in corpus (14)

• Why Some Interfaces Cannot be Sharp
• SCAN+rVV10: A promising van der Waals density functional
• Understanding the Instability of the Halide Perovskite CsPbI${}_3$ through Temperature-Dependent Structural Analysis
• MPInterfaces: A Materials Project based Python Tool for High-Throughput Computational Screening of Interfacial Systems
• Phase transitions in inorganic halide perovskites from machine learning potentials
• Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning
• Quantifying Dynamic Tilting in Halide Perovskites: Chemical Trends and Local Correlations
• Matching Crystal Structures Atom-to-Atom
• InterMat: Accelerating Band Offset Prediction in Semiconductor Interfaces with DFT and Deep Learning
• First principles feasibility assessment of a topological insulator at the InAs/GaSb interface
• Dependence of the electronic structure of the EuS/InAs interface on the bonding configuration
• Structure Prediction of Epitaxial Inorganic Interfaces by Lattice and Surface Matching with Ogre
• Topological Properties of SnSe/EuS and SnTe/CaTe Interfaces
• First Principles Assessment of CdTe as a Tunnel Barrier at the $\alpha$-Sn/InSb Interface

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