Materials informatics

Materials informatics is a field of study that applies the principles of informatics to materials science and engineering to better understand the use, selection, development, and discovery of materials. This is an emerging field, with a goal to achieve high-speed and robust acquisition, management, analysis, and dissemination of diverse materials data with the goal of greatly reducing the time and risk required to develop, produce, and deploy a new materials, which generally takes longer than 20 years. [1]

This field of endeavor is not limited to some traditional understandings of the relationship between materials and information. Some more narrow interpretations include combinatorial chemistry, Process Modeling, materials property databases, materials data management and product life cycle management. Materials informatics is at the convergence of these concepts, but also transcends them and has the potential to achieve greater insights and deeper understanding by applying lessons learned from data gathered on one type of material to others. By gathering appropriate meta data, the value of each individual data point can be greatly expanded.

Beyond computational methods?

The concept of materials informatics is addressed by the Materials Research Society. For example, materials informatics is the theme of the December 2006 issue of the MRS Bulletin. The issue was guest-edited by John Rodgers of Innovative Materials, Inc., and David Cebon of Cambridge University, who describe the "high payoff for developing methodologies that will accelerate the insertion of materials, thereby saving millions of investment dollars."

The editors focus on a limited definition of materials informatics, "the application of computational methodologies to processing and interpreting scientific and engineering data concerning materials." They state that "specialized informatics tools for data capture, management, analysis, and dissemination" and "advances in computing power, coupled with computational modeling and simulation and materials properties databases" will enable such accelerated insertion of materials.

This view is not universally held. A broader definition goes beyond the use of computational methods to carry out the same experimentation.[2] An evolved view of informatics creates a framework in which a measurement or computation is not simply a data point but a step in an information-based learning process that uses the power of a collective to achieve greater efficiency in exploration. When properly organized, this framework crosses materials boundaries to uncover fundamental knowledge of the basis of physical, mechanical, and engineering properties.

Challenges

While there are many that believe in the future of informatics in the materials development and scaling process, many challenges remain. Hill, et. al., write that "Today, the materials community faces serious challenges to bringing about this data-accelerated research paradigm, including diversity of research areas within materials, lack of data standards, and missing incentives for sharing, among others. Nonetheless, the landscape is rapidly changing in ways that should benefit the entire materials research enterprise."[3] This remaining tension between traditional materials development methodologies and the use of more computationally, machine learning, and analytics approaches will likely exist for some time as the materials industry overcomes some of the cultural barriers necessary to fully embrace such new ways of thinking.

Analogy from Biology

The overarching goals of bioinformatics and systems biology may provide a useful analogy. Andrew Murray of Harvard University expresses the hope that such an approach "will save us from the era of "one graduate student, one gene, one PhD".[4] Similarly, the goal of materials informatics is to save us from one graduate student, one alloy, one PhD. Such goals will require more sophisticated strategies and research paradigms than applying computational methods to the same tasks set currently undertaken by students.

See also

(March 2007 JOM-e issue on M.I.)

References

  1. ↑ Mulholland, Gregory; Paradiso, Sean (23 March 2016). "Perspective: Materials informatics across the product lifecycle: Selection, manufacturing, and certification". APL Materials. 4 (5). doi:10.1063/1.4945422. Retrieved 28 November 2016.
  2. ↑ http://www.informaticsresearch.net/17.html
  3. ↑ Hill, Joanne; Mulholland, Gregory; Persson, Kristin; Seshadri, Ram; Wolverton, Chris; Meredig, Bryce (4 May 2016). "Materials science with large-scale data and informatics: Unlocking new opportunities". MRS Bulletin. 41 (5). doi:10.1557/mrs.2016.93. Retrieved 28 November 2016.
  4. ↑ http://www.100md.com/html/DirDu/2007/02/17/37/06/78.htm
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.