Discovery of new materials using combinatorial synthesis and high-throughput characterization of thin-film materials libraries combined with computational methods

Abstract

This perspective provides an experimentalist's view on materials discovery in multinary materials systems-from nanoparticles over thin films to bulk-based on combinatorial thin-film synthesis and high-throughput characterization in connection with highthroughput calculations and materials informatics. Complete multinary materials systems as well as composition gradients which cover all materials compositions necessary for verification/falsification of hypotheses and predictions are efficiently fabricated by combinatorial synthesis of thin-film materials libraries. Automated high-quality high-throughput characterization methods enable comprehensive determination of compositional, structural and (multi)functional properties of the materials contained in the libraries. The created multidimensional datasets enable data-driven materials discoveries and support efficient optimization of newly identified materials, using combinatorial processing. Furthermore, these datasets are the basis for multifunctional existence diagrams, comprising correlations between composition, processing, structure and properties, which can be used for the design of future materials.

Symmetry prediction and knowledge discovery from X-ray diffraction patterns using an interpretable machine learning approach

“…Application of ML and related techniques for diffraction data analysis is a hot research topic in recent times 13 , 14 . Among various subtopics such as pattern decomposition and phase identification 15 – 18 cluster analysis and phase mapping 19 – 23 , similarity metrics for comparison of diffraction data 24 – 26 classification of a crystal symmetry 27 – 33 , a paper by Park et al 34 is relevant to this work.…”

Magnetic Colloidal Particles in Combinatorial Thin-Film Gradients for Magnetic Resonance Imaging and Hyperthermia

“…Efficient research methods and strategies have been developed for combinatorial fabrication of thin films and their high-throughput characterization. Most frequently, physical and chemical vapor deposition techniques have been applied for the rapid combination of libraries where wide-ranging compositional variation is generated [15].…”

Computational materials design: recent advances and open challenges related to colorimetry

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