#DATATHIEF TO DIGITIZE HOW TO#
Additionally, there are unresolved questions regarding how to recognize and assign value to emerging data sets. For one, the data necessary for optimization of complex, multi-dimensional systems are not readily available and means for automated data integration from primary literature sources do not yet exist. making high-throughput computational modeling more viable.ĭatabase creation is difficult for several reasons. as well as preliminary screening techniques 15–18 15. for simulated experiments have improved by considering simplified models and potentials, 7,12–14 7. Likewise, the tools and software packages, such as density functional theory (DFT), 10,11 10. In recent years, there have been significant advances in identifying materials descriptors and structure-property relationships in a wide variety of materials systems for many different applications. A prerequisite to this ambitious goal is (i) a theoretical understanding of the physical mechanisms and structure-property relationships governing materials properties, (ii) computational and modeling tools that are sufficiently rapid and calibrated to simulate virtual experiments, and (iii) experimental databases for training the computational tools and validating the screening methodologies thereafter.
The goal is to “discover, develop, manufacture, and deploy advanced materials at least twice as fast as is possible today, at a fraction of the cost.” This will require a collaborative approach between theory, simulation, modeling, and experimentation leveraging both existing and computed data to create iterative screening methodologies to reduce the number of costly and time consuming physical experiments. Holdren et al., National Science and Technology Council OSTP, Washington, USA,2011.
President Obama, can be considered the next evolution of ICME by extending this approach towards the accelerated discovery of new materials. The Materials Genome Initiative (MGI), launched in 2011 by the U.S.
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