Materials Genome Initiative

The Materials Genome Initiative (MGI) project element is a cross-Center effort that is focused on the integration of computational tools to simulate manufacturing processes and materials behavior. These computational simulations will be utilized to gain understanding of processes and materials behavior to accelerate process development and certification to more efficiently integrate new materials in existing NASA projects and to lead to the design of new materials for improved performance. This NASA effort looks to collaborate with efforts at other government agencies and universities working under the national MGI. MGI plans to develop integrated computational/experimental/ processing methodologies for accelerating discovery and insertion of materials to satisfy NASA's unique mission demands. The challenges include validated design tools that incorporate materials properties, processes, and design requirements; and materials process control to rapidly mature emerging manufacturing methods and develop certified manufacturing processe

Materials Genome Initiative Element

NASA is committed to developing new materials and manufacturing methods that can enable new missions with ever increasing mission demands. Typically, the development and certification of new materials and manufacturing methods in the aerospace industry has required more than 20 years of development time with a costly testing and certification program. To reduce the cost and time to mature these emerging technologies, NASA is developing computational materials tools to improve understanding of the material and guide the certification process

Materials Genome Initiative and Nuclear Fuel Element Material

核能由于其高能量密度和低污染排放等优点,已经成为未来能源的重要组成部分。然而,民用核燃料材料因其特殊的放射性,实验研究的安全防护成本极高,尤其是; 经过辐照后的核燃料材料,分析和表征手段极其有限,如果采用传统的试错法材料研发方法,将会使材料的研发成本大幅提高,因此,材料基因工程的研究思路正是; 适合于新型民用核燃料材料研究的技术路线。本研究组多年来以开发新型民用核燃料元件材料为目标,通过第一性原理和CALPHAD技术的结合,先后建立了U; 、Pu等锕系元素的多组元热力学数据库,并建立了辐照场作用下的热力学模型,对辐照场作用下核燃料材料的相变热力学和动力学进行了深入研究,在热力学数据; 库的基础上,运用相场动力学模型对核燃料元件材料的凝固和时效过程组织演化规律进行了系统的研究。这种基于材料基因工程的多尺度、多组元的材料设计研发思; 路为我国新一代具有自主知识产权的民用核燃料元件材料的成分设计、组织控制、工艺优化、性能改善及服役时间预测提供了重要的理论基础,同时对材料基因工程; 方法在材料开发中的广泛应用具有重要意义。Nuclear energy is an important part of the future source of energy due; to their higher energy density and lower emission of pollutants.; However, the traditional research method of "trial-and-error" may result; in higher costs and lower efficiency because of the radioactivity of the; nuclear fuel element material. The idea of Materials Genome; Initiative(MGI) is suitable for the research and development of the; nuclear fuel element material. Focused on the nuclear fuel element; material,our research group developed a multi-component thermodynamic; database including U,Pu and other elements,by coupling CALPHAD method; and the first-principle method. Based on the thermodynamic database, the; thermodynamic model under irradiation was established and the phase; transformations under irradiation were systematically investigated. The; microstructure evolutions during solidification and aging were simulated; by using the Phase-Field method. The present multiscale and; multi-component materials design method based on MGI can provide; important information for the design of composition,microstructure; controlling and property improvement of nuclear fuels materials.中央高校基本科研业务费; 国家自然科学基金资助项

The Mendeleev-Meyer force project

Here we present the Mendeleev–Meyer Force Project which aims at tabulating all materials and substances in a fashion similar to the periodic table. The goal is to group and tabulate substances using nanoscale force footprints rather than atomic number or electronic configuration as in the periodic table. The process is divided into: (1) acquiring nanoscale force data from materials, (2) parameterizing the raw data into standardized input features to generate a library, (3) feeding the standardized library into an algorithm to generate, enhance or exploit a model to identify a material or property. We propose producing databases mimicking the Materials Genome Initiative, the Medical Literature Analysis and Retrieval System Online (MEDLARS) or the PRoteomics IDEntifications database (PRIDE) and making these searchable online via search engines mimicking Pubmed or the PRIDE web interface. A prototype exploiting deep learning algorithms, i.e. multilayer neural networks, is presented.Award-winningPostprint (author's final draft

Building a Disciplinary, World-Wide Data Infrastructure

Sharing scientific data, with the objective of making it fully discoverable, accessible, assessable, intelligible, usable, and interoperable, requires work at the disciplinary level to define in particular how the data should be formatted and described. Each discipline has its own organization and history as a starting point, and this paper explores the way a range of disciplines, namely materials science, crystallography, astronomy, earth sciences, humanities and linguistics get organized at the international level to tackle this question. In each case, the disciplinary culture with respect to data sharing, science drivers, organization and lessons learnt are briefly described, as well as the elements of the specific data infrastructure which are or could be shared with others. Commonalities and differences are assessed. Common key elements for success are identified: data sharing should be science driven; defining the disciplinary part of the interdisciplinary standards is mandatory but challenging; sharing of applications should accompany data sharing. Incentives such as journal and funding agency requirements are also similar. For all, it also appears that social aspects are more challenging than technological ones. Governance is more diverse, and linked to the discipline organization. CODATA, the RDA and the WDS can facilitate the establishment of disciplinary interoperability frameworks. Being problem-driven is also a key factor of success for building bridges to enable interdisciplinary research.Comment: Proceedings of the session "Building a disciplinary, world-wide data infrastructure" of SciDataCon 2016, held in Denver, CO, USA, 12-14 September 2016, to be published in ICSU CODATA Data Science Journal in 201

Computational Materials Genome Initiative by High-Throughput Approaches

<p>Recently, in materials innovations, computational methods are used more frequently than in past decades. In this thesis, the materials genome initiative, an advanced new framework, will be introduced. With this blueprint, our efficient high-throughput software, AFLOW, has been implemented with several compatible functions for ma- terials properties investigations, such as prototype searching, phase diagram studying and magnetic properties discovering. With this effective tool, we apply ab initio cal- culations to discover new generation of specific materials properties.</p><p>An efficient algorithm for prototypes comparision has been designed and imple- mented into our high-throughput framework AFLOW. In addition, prototypes clas- sification was utilized to differentiate the our materials database. This classification will accelerate the materials properties searching speed. With respect to structure prototypes, low temperature phase diagrams were used for binary and ternary alloy systems stability investigation. The alogrithms have been integrated into AFLOW. With this tool, we systematically explored the binary Ru systems and Tc systems and predicted new stable compounds.</p>Dissertatio