journal article·2015-01

Exploring the Possibilities and Limitations of a Nanomaterials Genome

Chenxi Qian, Todd Siler, Geoffrey A. Ozin

Small· Volume 11· Issue 1
Publisher page

Abstract

What are we going to do with the cornucopia of nanomaterials appearing in the open and patent literature, every day? Imagine the benefits of an intelligent and convenient means of categorizing, organizing, sifting, sorting, connecting, and utilizing this information in scientifically and technologically innovative ways by building a Nanomaterials Genome founded upon an all‐purpose Periodic Table of Nanomaterials. In this Concept article, inspired by work on the Human Genome project, which began in 1989 together with motivation from the recent emergence of the Materials Genome project initiated in 2011 and the Nanoinformatics Roadmap 2020 instigated in 2010, we envision the development of a Nanomaterials Genome (NMG) database with the most advanced data‐mining tools that leverage inference engines to help connect and interpret patterns of nanomaterials information. It will be equipped with state‐of‐the‐art visualization techniques that rapidly organize and picture, categorize and interrelate the inherited behavior of complex nanomatter from the information programmed in its constituent nanomaterials building blocks. A Nanomaterials Genome Initiative (NMGI) of the type imagined herein has the potential to serve the global nanoscience community with an opportunity to speed up the development continuum of nanomaterials through the innovation process steps of discovery, structure determination and property optimization, functionality elucidation, system design and integration, certification and manufacturing to deployment in technologies that apply these versatile nanomaterials in environmentally responsible ways. The possibilities and limitations of this concept are critically evaluated in this article.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Machine Learning in Materials Science · Advanced biosensing and bioanalysis techniques · Computational Drug Discovery Methods

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Chemistry University of Toronto 80 St. George Street Toronto Ontario M5S 3H6 Canada

ArtScience Publications PO Box 372117 Denver Colorado 80237 USA

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