Materials Genome Approach Research Articles

Big data approach for effective ionic radii

Effective ionic radii are a useful tool for researchers in many disciplines. These radii are usually determined from interatomic distances and the values tabulated by Shannon and Prewitt are widely used since 1969. Here, we present a modern approach based on automated queries to materials databases followed by categorization and tabulation. This method is used to augment the available set of effective ionic radii by providing radii for missing anionic oxidation states and coordination numbers. Our approach proves to yield results that are consistent with known values for anions with well-established oxidation states. More exotic cases result in larger uncertainties due to the smaller amount of available structural data. Nevertheless, the provided estimates give reasonable values for cases that are untabulated at present. Furthermore, our approach is designed to continuously improve together with the growth of available databases. Furthermore, small tweaks of the presented application will allow us to also complement or revise ionic radii of cations. Thus, our approach is designed to update the old and useful concept of effective ionic radii, bringing it to modern days. Program summaryProgram Title:extend_anionic_radii.pyProgram Files doi:http://dx.doi.org/10.17632/sp4c25z8pn.1Licensing provisions: LGPL-3.0Programming language:Python3Supplementary material: The database of ionic radii is available online, preliminary under https://extend-sp-radii-new.herokuapp.com.Nature of problem: Determine the effective ionic radius for elements in anionic oxidation states (OS), depending on the coordination number (CN). This is done by harvesting the Materials Project (MP)[1] database. Newly found radii are adopted in a way that they coincide with reference values of the established Shannon–Prewitt (SP)[2] table for ionic radii.Solution method: For an element X in oxidation state OS, find all binary compounds contained in the MP that are composed by X and alkali or alkaline-earth metals. Determine OS and CN for all elements in each of the identified binary compounds (assume OS=+1 and +2 for alkali and alkaline-earth metals, respectively). Determine the nearest neighbor distances between the elements. From the obtained information and the SP reference values, compute the effective ionic radius of X, depending on OS and CN. •[[1]] A. Jain, S. P. Ong, G. Hautier, W. Chen, W. D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner,G. Ceder, K. A. Persson, Commentary: The materials project: A materials genome approach toaccelerating materials innovation, APL Mater. 1 (1). doi:10.1063/1.4812323.•[[2]] R. D. Shannon, C. T. Prewitt, Effective ionic radii in oxides and fluorides, Acta Cryst. B25 (1454) (1969)925–946.

A material genome approach towards exploration of Zn[sbnd] and Cd[sbnd] coordination complex polyester as dielectrics: Design, synthesis and characterization

Advances in materials can be achieved once we understand their property well. In this study, a series of zinc and cadmium aliphatic polyesters with varying numbers of methylene spacer(s), 1 to 8, are synthesized and characterized to understand their features, which control their dielectric properties. The rational co-design of these materials is adopted by Density Functional Theory (DFT) computations of local structural features, and physical properties as dielectric constant and band gap energies. Synthesized polyesters of zinc and cadmium exhibit high band gap energies, > 5 eV, with the dielectric constant from ca. 4.69-3.61 and ca. 6.61-4.01, respectively; with metal volume fractions ca. 3–12% experimentally, which supports the DFT computations strongly to behave as a good dielectric material. These initial studies give insight into the potential advantages and expansion of the chemical design space for developing new dielectrics and provide valuable validation and feedback to enrich Material Genome Initiative.

Accelerating the discovery of insensitive high-energy-density materials by a materials genome approach

Finding new high-energy-density materials with desired properties has been intensely-pursued in recent decades. However, the contradictory relationship between high energy and low mechanical sensitivity makes the innovation of insensitive high-energy-density materials an enormous challenge. Here, we show how a materials genome approach can be used to accelerate the discovery of new insensitive high-energy explosives by identification of “genetic” features, rapid molecular design, and screening, as well as experimental synthesis of a target molecule, 2,4,6-triamino-5-nitropyrimidine-1,3-dioxide. This as-synthesized energetic compound exhibits a graphite-like layered crystal structure with a high measured density of 1.95 g cm−3, high thermal decomposition temperature of 284 °C, high detonation velocity of 9169 m s−1, and extremely low mechanical sensitivities (impact sensitivity, >60 J and friction sensitivity, >360 N). Besides the considered system of six-member aromatic and hetero-aromatic rings, this materials genome approach can also be applicable to the development of new high-performing energetic materials.

From anti-perovskite to double anti-perovskite: tuning lattice chemistry to achieve super-fast Li+ transport in cubic solid lithium halogen–chalcogenides

Using a materials genome approach on the basis of density functional theory, we have formulated a new class of inorganic electrolytes for the fast diffusion of Li+ ions by fine-tuning the lattice chemistry of anti-perovskite structures.

Materials genome approach to organic ferroelectrics and piezoelectrics

We are implementing a materials genome strategy to discover or create new organic advanced functional materials. We are most interested in ferroelectric, piezoelectric and related properties. The three main components of the research are theory, synthesis, and measurement. The two main thrusts of the theory component are first-principles calculations, and data mining of archives such as the Cambridge Crystallographic Database (CCD) for organic compounds of interest. Novel formulations, including thin films, and new co-crystals of known electroactive organic components are also being investigated. Organic chemistry has historically not been as concerned with the electrical and mechanical properties of organic structures. This gives substantial weight to functional properties as a guide to the synthetic approach. Using this approach, we have identified several candidates. Of these, we have been able to successfully identify two new organic materials, both with electromechanical responses.

Multiscale Computational Framework for Discovery of Active, Durable and Non-Precious Electrocatalysts for Fuel Cell Systems

Innovative design of high functional materials in renewable energy systems plays a key role in powering transportation vehicles and portable electronics. This presentation introduces frontiers of research works by the first principles-based computational framework concerted on the purpose. As the example, nanoscale electro-catalysts in proton exchange membrane fuel cells (PEMFCs), Li-air batteries and solar cells for fuel generation are shown. It is clearly suggested that the method provide new design concept beyond conventional wisdom through the identification of fundamental descriptors and process mechanisms on and atomic level essentially leading to high efficiency of a whole system. The framework is potentially developed into a computational platform for the materials genome approach, which can substantially reduce the time period necessary from discovery to commercialization into markets of new materials.

High-throughputZTpredictions of nanoporous bulk materials as next-generation thermoelectric materials: A material genome approach

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Perspective: NanoMine: A material genome approach for polymer nanocomposites analysis and design

Polymer nanocomposites are a designer class of materials where nanoscale particles, functional chemistry, and polymer resin combine to provide materials with unprecedented combinations of physical properties. In this paper, we introduce NanoMine, a data-driven web-based platform for analysis and design of polymer nanocomposite systems under the material genome concept. This open data resource strives to curate experimental and computational data on nanocomposite processing, structure, and properties, as well as to provide analysis and modeling tools that leverage curated data for material property prediction and design. With a continuously expanding dataset and toolkit, NanoMine encourages community feedback and input to construct a sustainable infrastructure that benefits nanocomposite material research and development.

Toward a Materials Genome Approach for ionic liquids: synthesis guided by ab initio property maps.

The Materials Genome Approach (MGA) aims to accelerate development of new materials by incorporating computational and data-driven approaches to reduce the cost of identification of optimal structures for a given application. Here, we use the MGA to guide the synthesis of triazolium-based ionic liquids (ILs). Our approach involves an IL property-mapping tool, which merges combinatorial structure enumeration, descriptor-based structure representation and sampling, and property prediction using molecular simulations. The simulated properties such as density, diffusivity, and gas solubility obtained for a selected set of representative ILs were used to build neural network models and map properties for all enumerated species. Herein, a family of ILs based on ca. 200,000 triazolium-based cations paired with the bis(trifluoromethanesulfonyl)amide anion was investigated using our MGA. Fourteen representative ILs spreading the entire range of predicted properties were subsequently synthesized and then characterized confirming the predicted density, diffusivity, and CO2 Henry's Law coefficient. Moreover, the property (CO2, CH4, and N2 solubility) trends associated with exchange of the bis(trifluoromethanesulfonyl)amide anion with one of 32 other anions were explored and quantified.

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

Accelerating the discovery of advanced materials is essential for human welfare and sustainable, clean energy. In this paper, we introduce the Materials Project (www.materialsproject.org), a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials. This open dataset can be accessed through multiple channels for both interactive exploration and data mining. The Materials Project also seeks to create open-source platforms for developing robust, sophisticated materials analyses. Future efforts will enable users to perform ‘‘rapid-prototyping’’ of new materials in silico, and provide researchers with new avenues for cost-effective, data-driven materials design.