rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Information Science for Materials Discovery and Design
  name:
    name part: Lookman, Turab.
    role:
      role term: editor.
  name:
    name part: Alexander, Francis J.
    role:
      role term: editor.
  name:
    name part: Rajan, Krishna.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    edition: 1st ed. 2016.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVII, 307 p. 134 illus., 88 illus. in color. online resource.
  abstract: This book deals with an information-driven approach to plan materials discovery and design, iterative learning. The authors present contrasting but complementary approaches, such as those based on high throughput calculations, combinatorial experiments or data driven discovery, together with machine-learning methods. Similarly, statistical methods successfully applied in other fields, such as biosciences, are presented. The content spans from materials science to information science to reflect the cross-disciplinary nature of the field. A perspective is presented that offers a paradigm (codesign loop for materials design) to involve iteratively learning from experiments and calculations to develop materials with optimum properties. Such a loop requires the elements of incorporating domain materials knowledge, a database of descriptors (the genes), a surrogate or statistical model developed to predict a given property with uncertainties, performing adaptive experimental design to guide the next experiment or calculation and aspects of high throughput calculations as well as experiments. The book is about manufacturing with the aim to halving the time to discover and design new materials. Accelerating discovery relies on using large databases, computation, and mathematics in the material sciences in a manner similar to the way used to in the Human Genome Initiative. Novel approaches are therefore called to explore the enormous phase space presented by complex materials and processes. To achieve the desired performance gains, a predictive capability is needed to guide experiments and computations in the most fruitful directions by reducing not successful trials. Despite advances in computation and experimental techniques, generating vast arrays of data; without a clear way of linkage to models, the full value of data driven discovery cannot be realized. Hence, along with experimental, theoretical and computational materials science, we need to add a “fourth leg’’ to ou…
  table of contents: From the Contents: Introduction -- Data-Driven Discovery of Physical, Chemical, and Pharmaceutical Materials -- Cross-Validation and Inference in Bioinformatics/Cancer Genomics -- Applying MQSPRs - New Challenges and Opportunities.
  note: edited by Turab Lookman, Francis J. Alexander, Krishna Rajan.
  subject:
    topic: Materials science
  subject:
    topic: Data mining
  subject:
    topic: Statistical physics
  subject:
    topic: Dynamical systems
  subject:
    topic: Engineering
    topic: Materials
  subject:
    topic: Nanotechnology
  subject:
    topic: Materials Science
  subject:
    topic: Nanotechnology
  subject:
    topic: Materials Engineering
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Statistical Physics, Dynamical Systems and Complexity
  subject:
    topic: Characterization and Evaluation of Materials
  classification: T174.7
  classification: TA418.9.N35
  classification: 620.115
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Series in Materials Science, 225
  identifier: 9783319238715
  identifier: http://dx.doi.org/10.1007/978-3-319-23871-5
  record info:
    record creation date: 151212
    record change date: 20151212094803.0
    record identifier: 978-3-319-23871-5