Data Management for Combinatorial Heterogeneous Catalysis: Methodology and Development of Advanced Tools

  • D. Farrusseng
  • L. Baumes
  • C. Mirodatos


As catalytic chemical processes become increasingly mature, innovation in this field is less and less likely. The industry is facing such a slow rate of discovery because the empirical development of new active solids by a trial and error process from a few selected samples remains highly speculative. As well as the low rate of investigation, this research strategy based on exhaustive studies and complete understanding is very time consuming. After decades of very intensive efforts, new and major breakthroughs based on experience and common knowledge cannot be expected in most research areas dealing with bulk chemistry. Therefore new research strategies must be developed to produce breakthroughs and a paradigm shift in chemical research to revitalize innovation.


Search Space Hybrid Algorithm Heterogeneous Catalysis Oxidative Dehydrogenation Vanadium Content 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Senkan, S. Combinatorial heterogeneous catalysis—a new path in an old field. Angew. Chem. Int. Ed. 2001, 40, 312–329.CrossRefGoogle Scholar
  2. 2.
    Jandeleit, B., Schaefer, D. J., Powers, T. S., Turner, H. W., Weinberg, W. H. Combinatorial materials science and catalysis. Angew. Chem., Int. Ed 1999, 38, 2494–2532.CrossRefGoogle Scholar
  3. 3.
    Newsam, J. M., Schuth, F. Combinatorial approaches as a component of high-throughput experimentation (HTE) in catalysis research. Biotechnol. Bioeng. 1999, 61, 203–216.CrossRefGoogle Scholar
  4. 4.
    Harold, M. P., Mills, P. L., Nicole, J. F. Stud. Surf. Sci. Catal. 2001, 133, 87–98.CrossRefGoogle Scholar
  5. 5.
    Cohan, P. Results and commercialization—progress in the practice of combinatorial materials science. Abstracts, 221st American Chemical Society Meeting, 2001, Paper BTEC-056.Google Scholar
  6. 6.
    Yoneda Y. Prospect, rather than retrospect, on the impact of computers in catalytic research and development. Catal. Today 1995, 23, 305–310.CrossRefGoogle Scholar
  7. 7.
    Harmon, L. A., Vayda, A. J., Schlosser, S. G. Informatics challenges in combinatorial materials discovery. Abstracts, 221st American Chemical Society Meeting, 2001, Paper BTEC-067.Google Scholar
  8. 8.
    Dorsett, D. R., Jr. Capturing the combinatorial workflow. Abstracts, 221st American Chemical Society Meeting, 2001, Paper BTEC-064.Google Scholar
  9. 9.
    Cong, P., Dehestani, A., Doolen, R., Giaquinta, D. M., Guan, S., Markov, V., Poojary, D., Self, K., Turner, H., Weinberg, W. H. Combinatorial discovery of oxidative dehydrogenation catalysts within the Mo-V-Nb-O system. Proc. Natl Acad. Sci. USA 1999 96, 11077–11080.CrossRefGoogle Scholar
  10. 10.
    Geisler, S., Vauthey, I., Zanthoff, H., Muhler, M. Presented at European Workshop on Combinatorial Catalysis (EuroCombiCat), Ischia, Italy, 2002.Google Scholar
  11. 11.
    Wolf, D., Buyevskaya, O. v., Baerns, M. An evolutionary approach in the combinatorial selection and optimization of catalytic materials. Appl. Caral. A 2000, 200, 63–77.CrossRefGoogle Scholar
  12. 12.
    Banares-Alcantara, R., Westerberg, A.W., Ko, E. I., Rychener, M. D. DECADE-A hybrid expert system for catalyst selection. I. Expert system consideration. Comput. Chem. Eng. 1987, 11, 265–277.CrossRefGoogle Scholar
  13. 13.
    Banares-Alcantara, R., Ko, E. I., Westerberg, A. W., Rychener, M. D. DECADE—A hybrid expert system for catalyst selection. II. Final architecture and results. Comput. Chem. Eng. 1988, 12, 923–938CrossRefGoogle Scholar
  14. 14.
    Kito, S., Hattori, T, Murakami Y. Expert systems approach to computer-aided design of catalysts. Appl. Catal 1989, 48, 107–121.CrossRefGoogle Scholar
  15. 15.
    Koerting, E., Baerns, M. Use of expert systems in catalyst development. Chemie Ingenieur Technik 1990, 62 (5), 365–372.CrossRefGoogle Scholar
  16. 16.
    Sun, Y. H., Li, Y.W. Expert system approach to the preparation of supported catalyst. Chem. Eng. Sci 1992, 47, 2799–2804.CrossRefGoogle Scholar
  17. 17.
    Prevoo, H., Derouane, E. G., Vercauteren, D. P. Development of a prototype expert system for catalysis by zeolites. AIP Conf. Proc. 1995, 330, 775–781.CrossRefGoogle Scholar
  18. 18.
    Selvam, T., Iyer, D. N., Deka, R. C., Chatterjee, A., Vetrivel, R. A computational “expert system” approach to design synthesis routes for zeolite catalysts. Stud. Surf. Sci. Catal. 1997, 105A, 133–140.CrossRefGoogle Scholar
  19. 19.
    Klanner, C., Baumes, L., Farrusseng, D., Mirodatos, C., Schueth, F. QASAR, in press.Google Scholar
  20. 20.
    Buyevskaya, O. V., Wolf, D., Baerns, M. Ethylene and propene by oxidative dehydrogenation of ethane and propane—Performance of rare-earth oxide-based catalysts and development of redox-type catalytic materials by combinatorial methods. Catal. Today 2000, 62, 91–99.CrossRefGoogle Scholar
  21. 21.
    Reetz, M. T, Jaeger, K. E. Enantioselective enzymes for organic synthesis created by directed evolution. Chem. Eur. J. 2000 6, 407–412.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • D. Farrusseng
    • 1
  • L. Baumes
    • 1
    • 2
  • C. Mirodatos
    • 1
  1. 1.Institut de Recherches sur la Catalyse—CNRSVilleurbanneFrance
  2. 2.Equipe de Recherche en Ingénierie des ConnaissancesUniversité Lumière Lyon 2BronFrance

Personalised recommendations