Combinatorial and high-throughput experimental approaches and related informatics, modeling and data-mining methods have permitted researchers to accelerate the pace at which new, complex materials and device systems are discovered, optimized and understood. Today, the development and application of these revolutionary approaches continue to grow and diversify. This book offers an international, interdisciplinary perspective for scientists and engineers interested in combinatorial, high-throughput and advanced informatics approaches to materials research. The range of disciplines includes materials science; chemistry; physics; electrical, chemical and mechanical engineering; materials modeling; and data systems engineering. Presentations share successful studies, and illuminate current and emerging challenges in areas including: the design and fabrication of combinatorial libraries for materials and devices; high-throughput characterization methods for such systems; automation of instrumentation and data analysis; advanced modeling and data mining techniques for rapid materials design and properties prediction; and data system design and software for combinatorial workflows.

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.

Chemical sensors are in high demand for applications as varied as water pollution detection, medical diagnostics, and battlefield air analysis. Designing the next generation of sensors requires an interdisciplinary approach. The book provides a critical analysis of new opportunities in sensor materials research that have been opened up with the use of combinatorial and high-throughput technologies, with emphasis on experimental techniques. For a view of component selection with a more computational perspective, readers may refer to the complementary volume of Integrated Analytical Systems edited by M. Ryan et al., entitled “Computational Methods for Sensor Material Selection”.

A comprehensive look at the latest advances in soft material gradients Tremendous progress has been made in the field of surface-bound soft material gradients in recent years, with intriguing new areas of investigation opening up and advances in bioanalytics changing the way high-throughput screening methods are used in the design and discovery of catalysts and new materials. This volume provides the first complete, up-to-date summary of the progress in this field, showing readers how to harness the powerful properties of soft matter gradients in the design and development of modern functional materials. Contributed chapters from experts in diverse fields help bridge areas of materials science, chemistry, and biomaterials, covering fabrication techniques, gradients in self-assembled monolayers, polymer gradients, dynamic gradient structures, structure and assembly, mechanical properties, sensors, biomaterial applications, protein adsorption, and organization of cells on gradient surfaces. Readers will learn how to implement the techniques described in the book in their own work, while improving efficacy and lowering research and production costs. Soft Matter Gradient Surfaces is an invaluable resource for chemists, physicists, biologists, and engineers, and anyone who would like to take advantage of these unique soft matter building blocks.

Combinatorial Materials Science describes new developments and research results in catalysts, biomaterials, and nanomaterials, together with informatics approaches to the analysis of Combinatorial Science (CombiSci) data. CombiSci has been used extensively in the pharmaceutical industry, but there is enormous potential in its application to materials design and characterization. Addressing advances and applications in both fields, Combinatorial Materials Science: Integrates the scientific fundamentals and interdisciplinary underpinnings required to develop and apply CombiSci concepts Discusses the development and use of CombiSci for the systematic and accelerated investigation of new phenomena and of the complex structure-function interplay in materials Covers the development of new library design strategies for materials processing and for high-throughput tools for rapid sampling Uses a unique, unified approach of applying combinatorial methods to unravel the non-linear structure-function relationships in diverse materials (both hard and soft), together with advances in informatics With chapters written by leading researchers in their specialty areas, this authoritative guide is a must-have resource for scientists and engineers in materials science research, biochemists, chemists, immunologists, cell biologists, polymer scientists, chemical and mechanical engineers, statisticians, and computer scientists. It is also a great text for graduate-level courses in materials science/engineering, polymer science, chemical engineering, and chemistry.

This volume surveys recent research on autonomous sensor networks from the perspective of enabling technologies that support medical, environmental and military applications. State of the art, as well as emerging concepts in wireless sensor networks, body area networks and ambient assisted living introduce the reader to the field, while subsequent chapters deal in depth with established and related technologies, which render their implementation possible. These range from smart textiles and printed electronic devices to implanted devices and specialized packaging, including the most relevant technological features. The last four chapters are devoted to customization, implementation difficulties and outlook for these technologies in specific applications.

The first to provide systematically organized information on all three important aspects of artificial receptor design, this book brings together knowledge on an exceptionally hot and multidisciplinary field of research. Strong emphasis is placed on the methodology for discovering artificial receptors, with both definitions for chemosensitivity as well as experimental setups supplied. There follows coverage of numerous classes of artificial receptors, including synthesis, immobilization on surfaces, and quantitative data on properties. The third part of the book focuses on receptor arrays for artificial nose and tongue applications and the whole is rounded off with an outlook and an appendix with all relevant quantitative data on artificial receptors.

The MRS Symposium Proceeding series is an internationally recognised reference suitable for researchers and practitioners.

This book deals with an information-driven approach to plan materials discovery and design, iterative learning. The authors present contrasting but complementary approaches, such as those based on high throughput calculations, combinatorial experiments or data driven discovery, together with machine-learning methods. Similarly, statistical methods successfully applied in other fields, such as biosciences, are presented. The content spans from materials science to information science to reflect the cross-disciplinary nature of the field. A perspective is presented that offers a paradigm (codesign loop for materials design) to involve iteratively learning from experiments and calculations to develop materials with optimum properties. Such a loop requires the elements of incorporating domain materials knowledge, a database of descriptors (the genes), a surrogate or statistical model developed to predict a given property with uncertainties, performing adaptive experimental design to guide the next experiment or calculation and aspects of high throughput calculations as well as experiments. The book is about manufacturing with the aim to halving the time to discover and design new materials. Accelerating discovery relies on using large databases, computation, and mathematics in the material sciences in a manner similar to the way used to in the Human Genome Initiative. Novel approaches are therefore called to explore the enormous phase space presented by complex materials and processes. To achieve the desired performance gains, a predictive capability is needed to guide experiments and computations in the most fruitful directions by reducing not successful trials. Despite advances in computation and experimental techniques, generating vast arrays of data; without a clear way of linkage to models, the full value of data driven discovery cannot be realized. Hence, along with experimental, theoretical and computational materials science, we need to add a “fourth leg’’ to our toolkit to make the “Materials Genome'' a reality, the science of Materials Informatics.

Provides everything readers need to know for applying the power of informatics to materials science There is a tremendous interest in materials informatics and application of data mining to materials science. This book is a one-stop guide to the latest advances in these emerging fields. Bridging the gap between materials science and informatics, it introduces readers to up-to-date data mining and machine learning methods. It also provides an overview of state-of-the-art software and tools. Case studies illustrate the power of materials informatics in guiding the experimental discovery of new materials. Materials Informatics: Methods, Tools and Applications is presented in two parts?Methodological Aspects of Materials Informatics and Practical Aspects and Applications. The first part focuses on developments in software, databases, and high-throughput computational activities. Chapter topics include open quantum materials databases; the ICSD database; open crystallography databases; and more. The second addresses the latest developments in data mining and machine learning for materials science. Its chapters cover genetic algorithms and crystal structure prediction; MQSPR modeling in materials informatics; prediction of materials properties; amongst others. -Bridges the gap between materials science and informatics -Covers all the known methodologies and applications of materials informatics -Presents case studies that illustrate the power of materials informatics in guiding the experimental quest for new materials -Examines the state-of-the-art software and tools being used today Materials Informatics: Methods, Tools and Applications is a must-have resource for materials scientists, chemists, and engineers interested in the methods of materials informatics.