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Development of New Sensing Materials Using Combinatorial and High-Throughput Experimentation

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Computational Methods for Sensor Material Selection

Part of the book series: Integrated Analytical Systems ((ANASYS))

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Abstract

New sensors with improved performance characteristics are needed for applications as diverse as bedside continuous monitoring, tracking of environmental pollutants, monitoring of food and water quality, monitoring of chemical processes, and safety in industrial, consumer, and automotive settings. Typical requirements in sensor improvement are selectivity, long-term stability, sensitivity, response time, reversibility, and reproducibility. Design of new sensing materials is the important cornerstone in the effort to develop new sensors. Often, sensing materials are too complex to predict their performance quantitatively in the design stage. Thus, combinatorial and high-throughput experimentation methodologies provide an opportunity to generate new required data to discover new sensing materials and/or to optimize existing material compositions. The goal of this chapter is to provide an overview of the key concepts of experimental development of sensing materials using combinatorial and high-throughput experimentation tools, and to promote additional fruitful interactions between computational scientists and experimentalists.

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Author information

Authors and Affiliations

  1. Chemical and Biological Sensing Laboratory, Materials Analysis and Chemical Sciences, General Electric Company, Global Research Center, New York, 12309, Niskayuna, USA

    Radislav A. Potyrailo

  2. Department of Nanobiotechnology, Lausitz University of Applied Sciences, Senftenberg, Germany

    Vladimir M. Mirsky

Authors
  1. Radislav A. Potyrailo
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  2. Vladimir M. Mirsky
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Correspondence to Radislav A. Potyrailo .

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Editors and Affiliations

  1. Jet Propulsion Lab., California Institute of Technology, Oak Grove Drive 4800, Pasadena, 91109-8099, U.S.A.

    Margaret A. Ryan

  2. Jet Propulsion Lab., California Institute of Technology, Oak Grove Drive 4800, Pasadena, 91109-8099, U.S.A.

    Abhijit V. Shevade

  3. Pomona College, Seaver Chemistry Laboratory, N. College Avenue 645, Claremont, 91711, U.S.A.

    Charles J. Taylor

  4. Jet Propulsion Lab., California Institute of Technology, Oak Grove Drive 4800, Pasadena, 91109-8099, U.S.A.

    M. L. Homer

  5. Molecular Simulations Center, California Institute of Technology, Pasadena, 91125, U.S.A.

    Mario Blanco

  6. KWJ Engineering, Inc., Central Avenue 8440, Newark, 94560, U.S.A.

    Joseph R. Stetter

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Potyrailo, R.A., Mirsky, V.M. (2009). Development of New Sensing Materials Using Combinatorial and High-Throughput Experimentation. In: Ryan, M., Shevade, A., Taylor, C., Homer, M., Blanco, M., Stetter, J. (eds) Computational Methods for Sensor Material Selection. Integrated Analytical Systems. Springer, New York, NY. https://doi.org/10.1007/978-0-387-73715-7_7

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