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Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art Radislav Potyrailo*

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Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art Radislav Potyrailo* REVIEW pubs.acs.org/acscombsci Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art Radislav Potyrailo* Chemistry and Chemical Engineering, GE Global Research Center, Niskayuna, New York 12309, United States Krishna Rajan Department of Materials Science and Engineering and Institute for Combinatorial Discovery, Iowa State University, Ames, Iowa 50011, United States Klaus Stoewe Universit€at des Saarlandes, Technische Chemie, Campus C4.2, 66123, Saarbruecken, Germany Ichiro Takeuchi Department of Materials Science and Engineering, University of Maryland, College Park, Maryland 20742, United States Bret Chisholm Center for Nanoscale Science and Engineering and Department of Coatings and Polymeric Materials, North Dakota State University, Fargo, North Dakota 58102, United States Hubert Lam Chemistry and Chemical Engineering, GE Global Research Center, Niskayuna, New York 12309, United States ABSTRACT: Rational materials design based on prior knowledge is attractive because it promises to avoid time-consuming synthesis and testing of numerous materials candidates. However with the increase of complexity of materials, the scientific ability for the rational materials design becomes progressively limited. As a result of this complexity, combinatorial and high-throughput (CHT) experimentation in materials science has been recognized as a new scientific approach to generate new knowledge. This review demonstrates the broad applicability of CHT experimentation technologies in discovery and optimiza- tion of new materials. We discuss general principles of CHT materials screening, followed by the detailed discussion of high-throughput materials characteriza- tion approaches, advances in data analysis/mining, and new materials develop- ments facilitated by CHT experimentation. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, electronic and functional materials, polymer-based industrial coatings, sensing materials, and biomaterials. KEYWORDS: materials science, combinatorial and high-throughput (CHT) experimentation, electronic and functional materials, polymer-based industrial coatings, sensing materials, biomaterials ’ CONTENTS 3. Materials Development Examples 589 1. Introduction 580 3.1. Catalysis 589 2. General Principles 580 3.1.1. Homogeneous Catalysts 590 2.1. Experimental Planning 581 2.2. Materials Synthesis 581 Received: January 14, 2011 2.3. Materials Characterization 581 Revised: May 24, 2011 2.4. Data Analysis and Mining 585 Published: June 06, 2011 r 2011 American Chemical Society 579 dx.doi.org/10.1021/co200007w | ACS Comb. Sci. 2011, 13, 579–633 ACS Combinatorial Science REVIEW 3.1.2. HomogeneousÀHeterogeneous Hybrid This knowledge is typically obtained from extensive experimen- Approaches 591 tal and simulation data. However, with the increase of structural 3.1.3. Heterogeneous Catalysts 592 and functional complexity of materials, the ability to rationally define the precise requirements that result in a desired set of 3.1.4. Influences of Preparation Effects 598 performance properties becomes increasingly limited.1 Thus, in 3.1.5. Kinetic Studies 598 addition to limited examples of rational materials design, a variety 3.2. Electronic and Functional Materials 599 of materials have been discovered using detailed experimental 3.2.1. Combinatorial Investigation of observations or simply by chance, reflecting a general situation in “ ” 2,3 Lead-Free Piezoelectric Materials 599 materials design that is still too dependent on serendipity . 3.2.2. Thermoelectric Materials and Gate In materials science, the materials properties depend not only on composition, but also on morphology, microstructure, Stack Materials 601 and other parameters that are related to the material-prepara- 3.2.3. Combinatorial Mapping of Structural tion conditions. As a result of this complexity, combinatorial Phases Across Ternary Metallic Alloy and high-throughput (CHT) experimentation in materials Systems 602 science has been recognized as a new scientific approach to generate significant new knowledge as summarized in recent 3.3. Polymer-Based Industrial Coatings 603 À reviews and books.4 20 3.3.1. Cross-Linkers for Polyurethane This review demonstrates the broad applicability of CHT Dispersions 604 experimentation technologies in discovery and optimization of 3.3.2. Polyurethane-Siloxane Fouling-Release new materials. We discuss general principles of CHT materials Coatings 604 screening, followed by the discussion of the opportunities and 3.3.3. Polysiloxane-Based Coatings Possessing new materials developments facilitated by CHT experimenta- Tethered Quaternary Ammonium Salt tion. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, 607 Groups electronic and functional materials, polymer-based industrial 3.3.4. Polyurethane-Based Coatings Containing coatings, sensing materials, and biomaterials. Tethered Triclosan Groups 608 3.3.5. Radiation-Curable Coatings 608 2. GENERAL PRINCIPLES 3.3.6. Hybrid OrganicÀInorganic Coatings 608 Combinatorial or high-throughput materials screening is a 3.4. Sensing Materials 609 process that couples the capability for parallel production of large 3.4.1. Materials for Sensors Based on Radiant arrays of diverse materials together with different high-through- Energy Transduction 610 put measurement techniques for various intrinsic and perfor- 3.4.2. Materials for Sensors Based on mance properties followed by the navigation in the collected data “ ” 4,11,15,21À26 “ Mechanical Energy Transduction 612 for identifying lead materials. The terms combina- ” “ 3.4.3. Materials for Sensors Based on torial materials screening and high-throughput experimenta- tion” are typically interchangeably applied for all types of 614 Electrical Energy Transduction automated parallel and rapid sequential evaluation processes of 3.5. Biomaterials 617 materials and process parameters that include truly combinator- 3.5.1. Biomaterials Used for Drug/Gene ial permutations or their selected subsets. Delivery 618 Individual aspects of accelerated materials development have 3.5.2. Hydrogels for Drug/Gene Delivery 620 been known for decades. These aspects include combinatorial and factorial experimental designs,27 parallel synthesis of materi- 3.5.3. Organic Biomaterials with Cell als on a single substrate,28,29 screening of materials for perfor- and Stem Cell Systems 621 mance properties,9 and computer data processing.30,31 In 1970, 3.5.4. Inorganic Surfaces with Cell Systems 622 an integrated materials-development workflow was introduced 4. Summary and Outlook 623 by Hanak32 with four key aspects that included (1) complete Author Information 623 compositional mapping of a multicomponent system in one Acknowledgment 624 experiment, (2) simple rapid nondestructive all-inclusive chemi- Extended Glossary 624 cal analysis, (3) testing of properties by a scanning device, and (4) computer data processing. Hanak was truly ahead of his time References 625 21 and “it took 25 years for the world to realize his idea”. In 1995, applications of combinatorial methodologies in materials science were reinitiated by Xiang, Schultz, and co-workers.33 Since then, combinatorial tools have been employed to discover and opti- 1. INTRODUCTION mize a wide variety of materials (see Table 1). Rational design and optimization of materials based on prior A typical combinatorial materials development cycle is out- knowledge is a very attractive approach because it could avoid lined in Figure 1. Compared to the initial idea of Hanak32 (see time-consuming synthesis and testing of numerous materials Figure 1A), the modern workflow (Figure 1B) has several new candidates. However, to be quantitatively successful, rational important aspects, such as design/planning of experiments, design requires detailed knowledge regarding relation of intrinsic materials theory/modeling and informatics, and scale up. In properties of materials to a set of their performance properties. CHT screening of materials, concepts originally thought as 580 dx.doi.org/10.1021/co200007w |ACS Comb. Sci. 2011, 13, 579–633 ACS Combinatorial Science REVIEW Table 1. Examples of Materials Explored Using Combina- torial and High-Throughput Experimentation Techniques materials examples ref materials examples ref superconductor materials 33 zeolites 473 ferroelectric materials 474 polymers 475 magnetoresistive materials 476 metal alloys 477 luminescent materials 478 materials for methanol 479 fuel cells structural materials 480 materials for solid oxide 481 fuel cells hydrogen storage materials 482 materials for solar cells 483 organic light-emitting materials 484 automotive coatings 247 ferromagnetic shape-memory 485 waterborne coatings 486 alloys thermoelastic shape-memory 487 vaporÀbarrier coatings 269 alloys heterogeneous catalysts 488 marine coatings 263 homogeneous catalysts 489 fouling-release coatings 490 polymerization catalysts 491 organic dyes 492 electrochemical catalysts 164 polymeric sensing materials 389 Figure 1. Concepts of the combinatorial materials-development work- 32 electrocatalysts for 493 metal oxide sensing materials 494 flow. (A) Initial concept proposed by Hanak in 1970. (B) Modern “ ” 19 hydrogen evolution combinatorial materials cycle . fuel cell anode catalysts 495 formulated sensing materials 332 37 enantioselective catalysts 496 agricultural materials 497 became more attractive. At present, methods for CHT
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