Development of a New Technique for Discovering Systematically Hidden Patterns

Abstract

Materials design is still mainly based on the in materials science known concepts and intuition of the experimentalists. Analyzing the conditions that make it possible to search for the in materials science known concepts shows that it was not a new technique, a unique experimental observation, or an abstruse theory which formed the take-off point. It was rather the amassing of a critical volume of experimentally determined data in the literature that permitted an individual with deep insight to perceive an underlying pattern not previously apparent. Extending these facts to a new area of materials design leads to the following four key-points: I) The creation and the use of huge, critically evaluated materials databases which comprehensively covers the published world literature (materials databases). II) Computer-aided reduction of the elemental property parameters and systematic combinations of them to find the relevant 3D-feature sets which qualitatively can link materials properties with the chemical species present (semi-empirical approaches). III) Refinement and optimization of the qualitatively obtained results under II) with the help of neuro-computing leading to quantitative results (neuro-computing). IV) Focusing on predicted, most promising materials systems with the aim to reduce the experimental work for its verification, as well as trying to create a theoretical based explanation for such quantitative results (first principle calculations).

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Document Details

Document Type
Technical Report
Publication Date
Mar 14, 1999
Accession Number
ADA366111

Entities

People

  • Pierre Villars

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Advanced Materials
  • Atomic Properties
  • Binary Alloys
  • Chemical Elements
  • Chemistry
  • Contracts
  • Crystal Structure
  • Crystals
  • Data Sets
  • Databases
  • Magnetic Resonance
  • Materials
  • Materials Science
  • Phase Diagrams
  • Physics
  • Ternary Compounds
  • Three Dimensional

Readers

  • Computational Modeling and Simulation
  • Neural Network Machine Learning.
  • Systems Analysis and Design