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21 - 30 of 89 search results for TALK:PC53 20 |u:como.ceb.cam.ac.uk where 0 match all words and 89 match some words.
  1. Results that match 1 of 2 words

  2. Computational Modelling Group: Preprint 220

    https://como.ceb.cam.ac.uk/preprints/220/
    Ab initio MD simulations of a cPAH with 15 rings and two pentagons provided small fluctuations of the dipole moment at 1500 K, 10-20%, as well as binding a
  3. Computational Modelling Group: News item 91

    https://como.ceb.cam.ac.uk/news/91/
    News item 91. Preprint 99 published. 20 December 2010. Preprint 99, "A coupled CFD-population balance approach for nanoparticle synthesis in turbulent reacting flows". .
  4. Computational Modelling Group: Preprint 129

    https://como.ceb.cam.ac.uk/preprints/129/
    This gives the vertical stress, σ. 20. , on the disc. ... 20. plus (ii) the effect of τ; this sum gives an equation to predict the breakout factor N.
  5. Computational Modelling Group: News item 123

    https://como.ceb.cam.ac.uk/news/123/
    News item 123. Preprint 218 published. 20 January 2019. Preprint 218, "OntoKin: An Ontology for Chemical Kinetic Reaction Mechanisms", has been published!
  6. Computational Modelling Group: Preprint 274

    https://como.ceb.cam.ac.uk/preprints/274/
    OESI) at low blend strengths (5%) and a weaker linear reduction at higher blend strengths (10% and 20%).
  7. Computational Modelling Group

    https://como.ceb.cam.ac.uk/resources/flpyro/
    An example image and data are also available (FlPyroImageAndData.zip, 20 MB).
  8. Computational Modelling Group: Preprint 38

    https://como.ceb.cam.ac.uk/preprints/38/
    The total mass of soot produced in a laminar premixed flame is found to vary by no more than 20% as the model for the geometric effects of chemical reactions on
  9. Computational Modelling Group: Past Members

    https://como.ceb.cam.ac.uk/people/past/
    57 (4) 425 5304. 49 (0)721 6087622. 0191 208 4954. 44 (0)20 78825183.
  10. Computational Modelling Group: Preprint 42

    https://como.ceb.cam.ac.uk/preprints/42/
    f. H. 298K. = −598  20 kJ/mol. Finally, equilibrium calculations are performed to try to identify which intermediates are likely to be most prevalent in the high temperature industrial
  11. Computational Modelling Group: News item 140

    https://como.ceb.cam.ac.uk/news/140/
    If cyber-physical systems are integrated into our energy systems, carbon abatement potential can be expected to increase by 20 per cent, rising to 30 per cent when artificial intelligence (AI)

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