Systematic Control of Experimental Inconsistency in Combinatorial Materials Science

Abstract

We developed a method to systematically control experimental inconsistency, which is one of the most troublesome and difficult problems in high-throughput combinatorial experiments. The topic of experimental inconsistency is never addressed, even though all scientists in the field of combinatorial materials science face this very serious problem. Experimental inconsistency and material property were selected as dual objective functions that were simultaneously optimized. Specifically, in an attempt to search for promising phosphors with high reproducibility, photoluminescence (PL) intensity was maximized, and experimental inconsistency was minimized by employing a multiobjective evolutionary optimization-assisted combinatorial materials search (MOEO combinatorial material search) strategy. A tetravalent manganese-doped alkali earth germanium/titanium oxide system was used as a model system to be screened using MOEO combinatorial materials search. As a result of MOEO reiteration, we identified a halide-detached deep red phosphor with improved PL intensity and reliable reproducibility.

Experimental Design for Combinatorial Experiments

“…This can be done using a multiobjective genetic algorithm (MOGA) or a nondominated sorting genetic algorithm (NGSA) (Zitzler et al, 2000). Sharma et al (2009) used NGSA by Pareto-ranking the population into groups, with the first group having the highest fitness in the GA. Successive GA generations drove the population toward the highest fitness region (in a Pareto sense). In this case, the vector of factors was the presence and amount of six metals in a phosphor; the response vector was made up of the luminosity and the inconsistency of the phosphor.…”

Discovery of New Green Phosphors and Minimization of Experimental Inconsistency Using a Multi‐Objective Genetic Algorithm‐Assisted Combinatorial Method

“…[5] In this regard, the combination of GA and HTE results in a highly efficient system that enables the development of new materials and catalysts. [4,[6][7][8][9] For instance, we have identified some luminescent multi-compositional inorganic compounds using GACMS. [6][7][8][9] Error-free experimental processes are also very important in GACMS, because evaluation of an unknown objective function is performed by actual synthesis and subsequent characterization.…”

“…In this regard, we used a MOGA-assisted combinatorial materials search (MOGACMS) to simultaneously minimize experimental inconsistency and optimize luminance, thereby identifying promising phosphors. [9] Specifically, we set both the luminance and the inconsistency index as objective functions in our MOGACMS process. The inconsistency index is defined as the relative difference in luminance between two compounds with identical compositions from separately prepared libraries.…”

Search for phosphors for use in displays and lighting using heuristics‐based combinatorial materials science

“…[13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] We have been working on combinatorial chemistry to search for luminescent materials spanning from a conventional to the heuristic approach, i.e., simple mixing to smart mixing during last few years. [20][21][22][23][24][25][26][27] After the implementation of genetic-algorithm-assisted combinatorial material science (GACMS) we reduced the cost and time by reducing both the size of the population and the number of generations required for satisfactory optimization. [24][25][26][27] However, it is unfortunate that the commercialization of materials through combinatorial chemistry was limited except for a few luminescent materials.…”

“…[20][21][22][23][24][25][26][27] After the implementation of genetic-algorithm-assisted combinatorial material science (GACMS) we reduced the cost and time by reducing both the size of the population and the number of generations required for satisfactory optimization. [24][25][26][27] However, it is unfortunate that the commercialization of materials through combinatorial chemistry was limited except for a few luminescent materials. 20 The causes are many, but one troublesome problem, which may give rise to scale-up complications in the industry, is experimental inconsistency.…”