English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In many scientific fields, there is an interest in understanding the way inwhich complex chemical networks evolve. The chemical networks which researchersfocus upon, have become increasingly complex and this has motivated thedevelopment of automated methods for exploring chemical reactivity orconformational change in a black box manner, harnessing modern computingresources to automate mechanism discovery. In this work we present a newapproach to automated mechanism generation implemented which couples moleculardynamics and statistical rate theory to automatically find kineticallyimportant reactions and then solve the time evolution of the species in theevolving network. Key to this ChemDyME approach is the novel concept of kineticconvergence whereby the search for new reactions is constrained to thosespecies which are kinetically favorable at the conditions of interest. Wedemonstrate the capability of the new approach for two systems, a well-studiedcombustion system, and a multiple oxygen addition system relevant toatmospheric aerosol formation.

ChemDyME: Kinetically Steered, Automated Mechanism Generation Through Combined Molecular Dynamics and Master Equation Calculations