Premium
A New Paradigm for Materials Discovery: Heuristics‐Assisted Combinatorial Chemistry Involving Parameterization of Material Novelty
Author(s) -
Park Woon Bae,
Shin Namsoo,
Hong KunPyo,
Pyo Myoungho,
Sohn KeeSun
Publication year - 2012
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.201102118
Subject(s) - materials science , heuristics , computer science , particle swarm optimization , novelty , sorting , nanotechnology , mathematical optimization , algorithm , mathematics , philosophy , theology
The combinatorial chemistry (combi‐chem) of inorganic functional materials has not yet led to the discovery of commercially interesting materials, in contrast to the many successful discoveries of heterogeneous catalysts leading to commercialization. Novel materials for practical use are likely hidden in the multicompositional search space that contains an infinite number of possible stoichiometries, as well as a large number of well‐known materials. To discover new, inorganic luminescent materials (phosphors) from the SrO‐CaO‐BaO‐La 2 O 3 ‐Y 2 O 3 ‐Si 3 N 4 ‐Eu 2 O 3 search space, heuristics optimization strategies, such as the non‐dominated‐sorting genetic algorithm (NSGA) and particle swarm optimization (PSO) are coupled with high‐throughput experimentation (HTE) in such a manner that the experimental evaluation of fitness functions for the NSGA and PSO is accomplished by the HTE. The proposed strategy also involves the parameterization of the material novelty to avoid systematically a futile convergence on well‐known, already‐established materials. Although the process starts with random compositions, we finally converge on a novel, single‐phase, yellow‐green‐emitting luminescent material, La 4– x Ca x Si 12 O 3+ x N 18− x :Eu 2+ , that has strong potential for practical use in white light‐emitting diodes (WLEDs).