Subsequently, geometrical approaches based on group-subgroup relations were developed 6 and the DFT modeling within the solid-state nudged elastic band (SSNEB) method was devised 7.Īll of the aforementioned approaches only consider the movement of atoms during the transition and do not account for the fact that reconstructive phase transition leads to changes in crystal structure connectivity, when some interatomic contacts are broken and some new contacts are created. However, no general scheme was proposed until the 1990’s, when the geometrically shortest pathways were identified manually. Mechanisms were suggested for phase transitions in metallic systems between face-centered cubic and hexagonal close packings or body-centered cubic and face-centered cubic structures (martensitic transformations), in ionic crystals between rock salt and zinc blende, and in covalent crystals between diamond and lonsdaleite, among others 3– 5. The first attempts to describe reconstructive phase transitions at the atomic level were undertaken long before the DFT era. Therefore, the development of specialized methods that can rapidly search for the most energetically favorable pathways is crucial. However, several serious obstacles remain, as there are an infinite number of possible transition pathways, and direct scanning of all possible atomic architectures (also termed configuration space, CS) requires huge computational effort. Modeling of solid-state transitions at the atomic level is now possible thanks to the rapid development of density functional theory (DFT) methods over the last 10–15 years. Indeed, the task of developing rational models for reconstructive phase transitions goes far beyond the specific fields of solid-state chemistry and physics. ![]() Since these genes are expected to essentially determine the properties of the material, computational approaches may provide a cost-effective, high-throughput method to shorten the time-to-market for novel materials. Such computational approaches could further accelerate identification and screening of the genes within a material, and complement high-throughput (combinatorial) experiments. In the recent Materials Genome Initiative project 2, the study of reconstructive phase transitions was approached as the identification, mutation and recombination of the underlying architectures ( genes) of complex materials systems. The displacement of atoms during the transition in inorganic solids is less obvious, and special methods are required to model and understand these processes. Single crystal-to-single crystal transformations typically occur in organic or metal-organic compounds, in which the mechanism of transformation usually mimics the reaction of isolated molecules. In this scenario, the substance preserves its crystallinity and the transformation is often followed by reversible or irreversible chemical reactions between molecules. ‘Single crystal -to- single crystal’ transformations have attracted special attention in the last few years 1. With respect to chemical reactions between molecules, such reconstructive processes are always followed by essential reorganization of the solid system, which often results in destruction of the solid system. ![]() The search for new materials requires a deep understanding of reconstructive processes, which occur at the atomic level and lead to significant changes in the architecture of the substance. Some new phases and unclear transition pathways are discovered in example systems including elementary substances, ionic compounds and molecular crystals. We demonstrate this approach rationalizes the configuration space of the solid system and enables prediction of new phases that are closely related to already known phases. We propose a universal model based on network representation of extended structures, which treats any reorganization in the solid state as a network transformation. As a result, the chemical nature of the transformation processes are overlooked, which limits the predictive power of the models. ![]() Modeling of solid-state transitions by geometrical, molecular dynamics or quantum-mechanical methods does not account for topological transformations. Understanding these mechanisms at the atomic level is crucial for proper explanation and prediction of chemical reactions and phase transitions in solids and, ultimately, for the design of new materials. Reconstructive solid-state transformations are followed by significant changes in the system of chemical bonds, i.e.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |