Combinatorial and Artificial Intelligence Methods in Materials Science II: Volume 804Radislav A. Potyrailo Over the past two years, combinatorial and artificial intelligence methods in materials science have become more accepted as a means to synthesize, test, characterize, and predict promising candidate materials. These methods open up the exploration of multidimensional chemical composition and process parameter space at a previously unavailable level of detail and can rapidly optimize molecular properties and process conditions that are difficult to predict using existing knowledge. Scientists from academic, industrial and governmental laboratories worldwide come together here with interdisciplinary presentations that: identify gaps in cross-discipline knowledge that hinder further research; outline emerging development areas; and stimulate nontraditional solutions to difficult multidisciplinary problems in high-throughput materials research. Topics include: combinatorial approaches to electronics materials, polymers and coatings, and nanomaterials and catalysts; instrumentation and methods for high-throughput analysis; and library design, data management and informatics. In particular, the book demonstrates that combinatorial methods have matured in catalyst research. Several remarkable scale-up reports are presented signifying the power of this new scientific methodology. |
Contents
Multilayer Transparent Conducting Oxide Thin Film | 21 |
High Throughput Screening of Materials for Solid Oxide | 27 |
Combinatorial Fabrication and Studies of Small Molecular | 32 |
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2004 Materials Research activity adsorption alloy analysis analytical annealing applications array automated band gap BuO)3SiOH calculated catalysts cathode characterization Chem chemical coating colorants combinatorial chemistry combinatorial library combinatorial method composition compounds concentration crystal structure data mining database deposition descriptors developed devices diagram diffraction DMQC dopants doped dose electrochemical electron emission energy experimental fiber fibrinogen fluorescence gradient grid high-throughput high-throughput screening hydrogen intensity lattice layer linear magnetic MALDI mass mass spectrometry Materials Research Society Materials Science measured metal molecules optical oxide parameters particles performance phase phase diagram Phys polymer polymerization polythiophene Potyrailo predict prepared Proc properties ratio reactor resin sample scanning screening Seebeck coefficient selected sensor shown in Figure shows SnO2 solution spectra steam reforming substrate surface Symp synthesis technique Technology temperature ternary thermal thickness thin films throughput values