Atomic Clusters: Structure, Reactivity, Bonding, and Dynamics

Atomic clusters lie somewhere in between isolated atoms and extended solids with distinctly different reactivity patterns. They are known to be useful as catalysts facilitating several reactions of industrial importance. Various machine learning based techniques have been adopted in generating their global minimum energy structures. Bond-stretch isomerism, aromatic stabilization, Rener-Teller effect, improved superhalogen/superalkali properties, and electride characteristics are some of the hallmarks of these clusters. Different all-metal and nonmetal clusters exhibit a variety of aromatic characteristics. Some of these clusters are dynamically stable as exemplified through their fluxional behavior. Several of these cluster cavitands are found to be agents for effective confinement. The confined media cause drastic changes in bonding, reactivity, and other properties, for example, bonding between two noble gas atoms, and remarkable acceleration in the rate of a chemical reaction under confinement. They have potential to be good hydrogen storage materials and also to activate small molecules for various purposes. Many atomic clusters show exceptional opto-electronic, magnetic, and nonlinear optical properties. In this Review article, we intend to highlight all these aspects.

Solid State Materials Chemistry

This comprehensive textbook provides a modern, self-contained treatment for upper undergraduate and graduate level students. It emphasizes the links between structure, defects, bonding, and properties throughout, and provides an integrated treatment of a wide range of materials, including crystalline, amorphous, organic and nano- materials. Boxes on synthesis methods, characterization tools, and technological applications distil specific examples and support student understanding of materials and their design. The first six chapters cover the fundamentals of extended solids, while later chapters explore a specific property or class of material, building a coherent framework for students to master core concepts with confidence, and for instructors to easily tailor the coverage to fit their own single semester course. With mathematical details given only where they strengthen understanding, 400 original figures and over 330 problems for hands-on learning, this accessible textbook is ideal for courses in chemistry and materials science.

A Partial Anion Disorder in SrVO2H Induced by Biaxial Tensile Strain

SrVO2H, obtained by a topochemical reaction of SrVO3 perovskite using CaH2, is an anion-ordered phase with hydride anions exclusively at the apical site. In this study, we conducted a CaH2 reduction of SrVO3 thin films epitaxially grown on KTaO3 (KTO) substrates. When reacted at 530 °C for 12 h, we observed an intermediate phase characterized by a smaller tetragonality of c/a = 0.96 (vs. c/a = 0.93 for SrVO2H), while a longer reaction of 24 h resulted in the known phase of SrVO2H. This fact suggests that the intermediate phase is a metastable state stabilized by applying tensile strain from the KTO substrate (1.4%). In addition, secondary ion mass spectrometry (SIMS) revealed that the intermediate phase has a hydrogen content close to that of SrVO2H, suggesting a partially disordered anion arrangement. Such kinetic trapping of an intermediate state by biaxial epitaxial strain not only helps to acquire a new state of matter but also advances our understanding of topochemical reaction processes in extended solids.

Zintl Phases as Reactive Precursors for Synthesis of Novel Silicon and Germanium-Based Materials

Recent experimental and theoretical work has demonstrated significant potential to tune the properties of silicon and germanium by adjusting the mesostructure, nanostructure, and/or crystalline structure of these group 14 elements. Despite the promise to achieve enhanced functionality with these already technologically important elements, a significant challenge lies in the identification of effective synthetic approaches that can access metastable silicon and germanium-based extended solids with a particular crystal structure or specific nano/meso-structured features. In this context, the class of intermetallic compounds known as Zintl phases has provided a platform for discovery of novel silicon and germanium-based materials. This review highlights some of the ways in which silicon and germanium-based Zintl phases have been utilized as precursors in innovative approaches to synthesize new crystalline modifications, nanoparticles, nanosheets, and mesostructured and nanoporous extended solids with properties that can be very different from the ground states of the elements.

Single Crystal Automated Refinement (SCAR): A Data-Driven Method for Solving Inorganic Structures

<p>Single crystal diffraction is one of the most common experimental techniques in chemistry for determining a crystal structure. However, the process of crystal structure solution and refinement is not always straightforward. Methods to simplify and rationalize the path to the most optimal crystal structure model have been incorporated into various data processing and crystal structure solution software, with the focus generally on aiding macromolecular or protein structure solution. In this work, we propose a new method that uses single crystal data to solve the crystal structures of inorganic, extended solids called “Single Crystal Automated Refinement (<i>SCAR</i>).” The approach was developed using data mining and machine-learning methods and considers several structural features common in inorganic solids, like atom assignment based on physically reasonable distances, atomic statistical mixing, and crystallographic site deficiency. The output is a tree of possible solutions for the data set with a corresponding fit score indicating the most reasonable crystal structure. Here, the foundation for <i>SCAR</i> is presented followed by the implementation of <i>SCAR</i> to solve two newly synthesized and previously unreported phases, ZrAu_0.5Os_0.5 and Nd₄Mn₂AuGe₄. The structure solutions are found to be comparable with manually solving the data set, including the same refined mixed occupancies and atomic deficiency, supporting the validity of this automatic structure solution method. The proposed <i>SCAR</i> program is thusly verified to be a fast and reliable assistant in solving even complex single crystal diffraction data for extended inorganic solids.</p>

Single Crystal Automated Refinement (SCAR): A Data-Driven Method for Solving Inorganic Structures

<p>Single crystal diffraction is one of the most common experimental techniques in chemistry for determining a crystal structure. However, the process of crystal structure solution and refinement is not always straightforward. Methods to simplify and rationalize the path to the most optimal crystal structure model have been incorporated into various data processing and crystal structure solution software, with the focus generally on aiding macromolecular or protein structure solution. In this work, we propose a new method that uses single crystal data to solve the crystal structures of inorganic, extended solids called “Single Crystal Automated Refinement (<i>SCAR</i>).” The approach was developed using data mining and machine-learning methods and considers several structural features common in inorganic solids, like atom assignment based on physically reasonable distances, atomic statistical mixing, and crystallographic site deficiency. The output is a tree of possible solutions for the data set with a corresponding fit score indicating the most reasonable crystal structure. Here, the foundation for <i>SCAR</i> is presented followed by the implementation of <i>SCAR</i> to solve two newly synthesized and previously unreported phases, ZrAu_0.5Os_0.5 and Nd₄Mn₂AuGe₄. The structure solutions are found to be comparable with manually solving the data set, including the same refined mixed occupancies and atomic deficiency, supporting the validity of this automatic structure solution method. The proposed <i>SCAR</i> program is thusly verified to be a fast and reliable assistant in solving even complex single crystal diffraction data for extended inorganic solids.</p>

Prediction of amorphous structure and stability of P-N and N-CO extended solids under pressure

ABSTRACTThe amorphous structures of poly-CO, P-N and N-CO extended solids at high pressures were predicted using density functional theory (DFT) and evolutionary algorithms employing variable and fixed concentrations of components methods. Compression of random network of poly-CO up to 45 GPa results in elimination of small rings of the amorphous network. The amorphous structure with stoichiometry N9P was found to be dynamically stable (no imaginary frequencies in phonon-dispersion curve), stable relative transformation to solid nitrogen and phosphorus, but metastable according to convex hull calculations. The amorphous structure of the N-CO extended solid was obtained with various concentrations of N atoms under isotropic compression up to 50 GPa and release of pressure down to 5 GPa calculated using DFT. The higher concentration of CO is found to be favourable for stabilization of an amorphous covalent N-C-O network consisting of chains and a cage of the network. Upon lowering the pressure and decomposition of the compressed extended solid, atoms are disconnected first from the ends of polymeric chains, while rings of random network are sustained almost intact. Results of a calculated Raman spectra are compared with available experimental results.

Development of a robust tool to extract Mulliken and Löwdin charges from plane waves and its application to solid-state materials

A robust tool to extract Mulliken and Löwdin charges for (extended) solids from plane waves has been developed and applied.