MATERIALS GENOME INITIATIVE - Thematic Program for 2017 Sanibel Symposium

Detalles del proyecto

Descripción

Transforming the impact of computational materials science is one of the goals of the Materials Genome Initiative (MGI). A bold, multi-agency federal program, the MGI aims to convert the discovery of materials with needed properties from an esoteric art to a well-founded computationally based methodology. The goal to accelerate the time from discovery to development of new materials can be made possible through rapid computational generation of large volumes of predictive-quality data, schema and insight gained.

Topics of the conference will include 1) complex and functional materials, 2) quantum materials, 3) density functional theory in materials, 4) high-throughput simulations, and 5) machine learning. In the early stages of MGI, tremendous progress has already been made on these topics. Unexpected challenges have emerged as well. Therefore, it is timely to survey the progress, assess the obstacles, and discuss new and revised research paths. As a multi-specialty theoretical and computational endeavor, a special forum is needed. The Sanibel Symposium, with its long, successful record of focusing on theory and computation of materials and their molecular constituents, is ideally suited for this purpose. For the 2017 conference, the Sanibel organizers propose to devote a substantial fraction (five plenary and invited sessions totaling 15 speakers) to a thematic program on the status and outlook of MGI. New ideas and improved directions for MGI can be expected to emerge from the stimulus of the formal presentations and informal discussions.

The conference encourages the participation of students, post-docs, and junior scientists with a conscious effort, characteristic of the Sanibel Symposia, to stimulate the participation of women and under-represented minorities.

EstadoFinalizado
Fecha de inicio/Fecha fin15/2/1714/2/18

Financiación

  • Basic Energy Sciences: USD15,000.00

!!!ASJC Scopus Subject Areas

  • Genética
  • Biología molecular
  • Energía (todo)

Huella digital

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