Abstract
Many materials systems comprise complex structures where multiple materials are integrated to achieve a desired performance. Often in these systems, it is a combination of both the materials and their structure that dictate performance. Here the authors layout an integrated computational–statistical–experimental methodology for hierarchical materials systems that takes a holistic design approach to both the material and structure. The authors used computational modeling of the physical system combined with statistical design of experiments to explore an activated carbon adsorption bed. The large parameter space makes experimental optimization impractical. Instead, a computational–statistical approach is coupled with physical experiments to validate the optimization results.
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Acknowledgments
Research presented was supported by the National Science Foundation through grant 1727316. This work made use of the Cornell Center for Materials Research Shared Facilities, which are supported through the NSF MRSEC program (DMR-1719875). This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation grant number ACI-1548562 through STAMPEDE2 at the Texas Advanced Computing Center through allocation TG-CCR180027. The authors thank Cabot Corporation for supplying the activated carbons used in this work, and Ian Miller for running preliminary experiments as part of his Undergraduate Research coursework at the Pennsylvania State University.
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The supplementary material for this article can be found at https://doi.org/10.1557/mrc.2019.60
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Ryan, E., Pollard, Z.A., Ha, QT. et al. Designing heterogeneous hierarchical material systems: a holistic approach to structural and materials design. MRS Communications 9, 628–636 (2019). https://doi.org/10.1557/mrc.2019.60
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DOI: https://doi.org/10.1557/mrc.2019.60