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Informatics for Combinatorial Experiments: Accelerating Data Interpretation

  • M. Stukowski (a1), C. Suh (a2), Krishna Rajan (a3), P. D. Tall (a4), A. C. Beye (a5), A. G. Ramirez (a6), W. O. Soboyejo (a7), M. L. Benson (a8) and P.K. Liaw (a9)...

Abstract

Combinatorial experiments provide a means of generating large amounts of experimental data; however that does not necessarily lead to high throughput interpretation of that data. In this paper we provide a brief summary of how one can use informatics techniques to accelerate data interpretation from high throughput experiments. We provide examples from high throughput nanoindentation and diffraction experiments.

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References

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1. Rajan, K., Suh, C., Rajagopalan, A., Li, X., Mat. Res. Soc. Symp. Proc., 700 (2002).
2. Suh, C. and Rajan, K., Appl. Surf. Sci., 223, 148 (2004).
3. Potyrailo, R. A., Wroczynski, R. J., Lemmon, J. P., Flanagan, W. P., Siclovan, O. P., J.Comb. Chem. 5, 8 (2003).
4. Tall, P. D., Coupeau, C., and Rabier, J., Scripta Mater. 49, 903908 (2003).
5. Benson, M. L., Saleh, T. A., Liaw, P. K., Choo, H., Wang, X.-L., Stoica, A. D., Daymond, M. R., Brown, D. W., Buchanan, R. A., and Klarstrom, D. L., Denver X-ray Conference 2004.
6. Jiang, L., Brooks, C. R., Liaw, P. K., Dunlap, J., Rawn, C. J., Peascoe, R. A., and Klarstrom, D. L., Met. Trans. A 35, 785 (2004).

Keywords

Informatics for Combinatorial Experiments: Accelerating Data Interpretation

  • M. Stukowski (a1), C. Suh (a2), Krishna Rajan (a3), P. D. Tall (a4), A. C. Beye (a5), A. G. Ramirez (a6), W. O. Soboyejo (a7), M. L. Benson (a8) and P.K. Liaw (a9)...

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