Controlled Synthesis of Organic/Inorganic van der Waals Solid for Tunable Light-matter Interactions

Van der Waals (vdW) solids, as a new type of artificial materials that consist of alternating layers bonded by weak interactions, have shed light on fascinating optoelectronic device concepts. As a result, a large variety of vdW devices have been engineered via layer-by-layer stacking of two-dimensional materials, although shadowed by the difficulties of fabrication. Alternatively, direct growth of vdW solids has proven as a scalable and swift way, highlighted by the successful synthesis of graphene/h-BN and transition metal dichalcogenides (TMDs) vertical heterostructures from controlled vapor deposition. Here, we realize high-quality organic and inorganic vdW solids, using methylammonium lead halide (CH3NH3PbI3) as the organic part (organic perovskite) and 2D inorganic monolayers as counterparts. By stacking on various 2D monolayers, the vdW solids behave dramatically different in light emission. Our studies demonstrate that h-BN monolayer is a great complement to organic perovskite for preserving its original optical properties. As a result, organic/h-BN vdW solid arrays are patterned for red light emitting. This work paves the way for designing unprecedented vdW solids with great potential for a wide spectrum of applications in optoelectronics

Spontaneous Octahedral Tilting in the Cubic Inorganic Caesium Halide Perovskites CsSnX3_3 and CsPbX3_3 (X = F, Cl, Br, I)

The local crystal structures of many perovskite-structured materials deviate from the average space group symmetry. We demonstrate, from lattice-dynamics calculations based on quantum chemical force constants, that all the caesium-lead and caesium-tin halide perovskites exhibit vibrational instabilities associated with octahedral titling in their high-temperature cubic phase. Anharmonic double-well potentials are found for zone-boundary phonon modes in all compounds with barriers ranging from 108 to 512 meV. The well depth is correlated with the tolerance factor and the chemistry of the composition, but is not proportional to the imaginary harmonic phonon frequency. We provide quantitative insights into the thermodynamic driving forces and distinguish between dynamic and static disorder based on the potential-energy landscape. A positive band gap deformation (spectral blueshift) accompanies the structural distortion, with implications for understanding the performance of these materials in applications areas including solar cells and light-emitting diodes

A Map of the Inorganic Ternary Metal Nitrides

Exploratory synthesis in novel chemical spaces is the essence of solid-state chemistry. However, uncharted chemical spaces can be difficult to navigate, especially when materials synthesis is challenging. Nitrides represent one such space, where stringent synthesis constraints have limited the exploration of this important class of functional materials. Here, we employ a suite of computational materials discovery and informatics tools to construct a large stability map of the inorganic ternary metal nitrides. Our map clusters the ternary nitrides into chemical families with distinct stability and metastability, and highlights hundreds of promising new ternary nitride spaces for experimental investigation--from which we experimentally realized 7 new Zn- and Mg-based ternary nitrides. By extracting the mixed metallicity, ionicity, and covalency of solid-state bonding from the DFT-computed electron density, we reveal the complex interplay between chemistry, composition, and electronic structure in governing large-scale stability trends in ternary nitride materials

Automated computation of materials properties

Materials informatics offers a promising pathway towards rational materials design, replacing the current trial-and-error approach and accelerating the development of new functional materials. Through the use of sophisticated data analysis techniques, underlying property trends can be identified, facilitating the formulation of new design rules. Such methods require large sets of consistently generated, programmatically accessible materials data. Computational materials design frameworks using standardized parameter sets are the ideal tools for producing such data. This work reviews the state-of-the-art in computational materials design, with a focus on these automated $\textit{ab-initio}$ frameworks. Features such as structural prototyping and automated error correction that enable rapid generation of large datasets are discussed, and the way in which integrated workflows can simplify the calculation of complex properties, such as thermal conductivity and mechanical stability, is demonstrated. The organization of large datasets composed of $\textit{ab-initio}$ calculations, and the tools that render them programmatically accessible for use in statistical learning applications, are also described. Finally, recent advances in leveraging existing data to predict novel functional materials, such as entropy stabilized ceramics, bulk metallic glasses, thermoelectrics, superalloys, and magnets, are surveyed.Comment: 25 pages, 7 figures, chapter in a boo

Hierarchical Visualization of Materials Space with Graph Convolutional Neural Networks

The combination of high throughput computation and machine learning has led to a new paradigm in materials design by allowing for the direct screening of vast portions of structural, chemical, and property space. The use of these powerful techniques leads to the generation of enormous amounts of data, which in turn calls for new techniques to efficiently explore and visualize the materials space to help identify underlying patterns. In this work, we develop a unified framework to hierarchically visualize the compositional and structural similarities between materials in an arbitrary material space with representations learned from different layers of graph convolutional neural networks. We demonstrate the potential for such a visualization approach by showing that patterns emerge automatically that reflect similarities at different scales in three representative classes of materials: perovskites, elemental boron, and general inorganic crystals, covering material spaces of different compositions, structures, and both. For perovskites, elemental similarities are learned that reflects multiple aspects of atom properties. For elemental boron, structural motifs emerge automatically showing characteristic boron local environments. For inorganic crystals, the similarity and stability of local coordination environments are shown combining different center and neighbor atoms. The method could help transition to a data-centered exploration of materials space in automated materials design.Comment: 22 + 7 pages, 6 + 5 figure

A Most Unusual Zeolite Templating: Cage to Cage Connection of One Guest Molecule

An unusual case of a diquaternary ammonium dication, with large bulky end groups built from the tropane moiety and connected by a C4 methylene chain, is found to reside in zeolite SSZ-35 (STF). The structure of the guest/host product is such that the tropane bicylic entities reside in the shallow cavities of the cages of the STF structure and the C4 methylene chain runs through the 10-ring (~5.5 Å) window that connects the cages. This is a most unusual (and energy-intensive) templating of a zeolite structure with the guest molecule spanning two unit cells. The unusual result was found by single crystal studies with the addition of the use of the SQUEEZE program to show a consistent fit for the guest molecule following from measured electron densities in the crystal structure work. These analyses were followed with MAS NMR studies to confirm the integrity of the diquaternary guest molecule in the host sieve. A few comparative diquaternary guest molecules in MFI zeolite are also studied

Graphene-like conjugated pi-bond system in Pb1-xSnxSe

Following the identification of the pi bond in graphene, in this work, a pi bond constructed through side-to-side overlap of half-filled 6pz orbitals was observed in a non-carbon crystal of Pb1-xSnxSe (x=0.34) (PSS), a prototype topological crystalline insulator (TCI) and thermoelectric material with a high figure-of-merit (ZT). PSS compounds with a rock-salt type cubic crystal structure was found to consist of sigma bond connected covalent chains of Pb(Sn)-Se with an additional pi bond that is shared as a conjugated system among the four nearest neighbor Pb pairs in square symmetry within all (001) monoatomic layers per cubic unit cell. The pi bond formed with half-filled 6pz orbitals between Pb atoms is consistent with the calculated results from quantum chemistry. The presence of pi bonds was identified and verified with electron energy-loss spectroscopy (EELS) through plasmonic excitations and electron density (ED) mapping via an inverse Fourier transform of X-ray diffraction.Comment: 5 pages, 4 figures, to be published in Appl Phys. Let

Understanding macroscale functionality of metal halide perovskites in terms of nanoscale heterogeneities

Hybrid metal halide perovskites have shown an unprecedented rise as semiconductor building blocks for solar energy conversion and light-emitting applications. Currently, the field moves empirically towards more and more complex chemical compositions, including mixed halide quadruple cation compounds that allow optical properties to be tuned and show promise for better stability. Despite tremendous progress in the field, there is a need for better understanding of mechanisms of efficiency loss and instabilities to facilitate rational optimization of composition. Starting from the device level and then diving into nanoscale properties, we highlight how structural and compositional heterogeneities affect macroscopic optoelectronic characteristics. Furthermore, we provide an overview of some of the advanced spectroscopy and imaging methods that are used to probe disorder and non-uniformities. A unique feature of hybrid halide perovskite compounds is the propensity for these heterogeneities to evolve in space and time under relatively mild illumination and applied electric fields, such as those found within active devices. This introduces an additional challenge for characterization and calls for application of complimentary probes that can aid in correlating the properties of local disorder with macroscopic function, with the ultimate goal of rationally tailoring synthesis towards optimal structures and compositions