首页> 外文会议>Intelligent Processing and Manufacturing of Materials, 1999. IPMM '99. Proceedings of the Second International Conference on >Interplay between large materials databases, semi-empirical approaches, neuro-computing and first principle calculations
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Interplay between large materials databases, semi-empirical approaches, neuro-computing and first principle calculations

机译:大型材料数据库,半经验方法,神经计算和第一原理计算之间的相互作用

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Analyzing the conditions that make it possible to search for materials science concepts, it is shown that it was 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: 1) creation and use of huge, critically evaluated materials databases; 2) computer-aided reduction of elemental parameters and systematic combinations of them to find the relevant feature sets which can link materials properties qualitatively with the chemical species present; 3) refinement and optimisation of qualitatively-obtained results under (2) with the help of neurocomputing leading to more explicit quantitative results; and 4) focusing on predicted, most-promising materials systems with the aim to reduce the experimental work for verification, as well as trying to create a theoretically-based explanation for such quantitative results.
机译:分析使搜索材料科学概念成为可能的条件,结果表明,正是由于大量文献中实验确定的数据的积累,才使有深刻见识的个人能够感知到以前不曾发现的潜在模式。将这些事实扩展到材料设计的新领域会导致以下四个关键点:1)创建和使用庞大的,经过严格评估的材料数据库; 2)计算机辅助的元素参数还原和系统的组合,以找到相关的特征集,这些特征集可以将材料的性质定性地与存在的化学物质联系起来; 3)在神经计算的帮助下,对(2)下定性获得的结果进行细化和优化,从而得到更明确的定量结果; 4)着眼于预测的,最有希望的材料系统,以减少用于验证的实验工作,并试图为这种定量结果创建基于理论的解释。

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