UManSysProp v1.0: an online and open-source facility for molecular property prediction and atmospheric aerosol calculations

Research output: Contribution to journalArticle

  • External authors:
  • Gordon Mcfiggans
  • Mark Barley
  • Michael K Bane
  • Bernard Aumont
  • Nicholas Dingle

Abstract

In this paper we describe the development and application of a new web-based facility, UManSysProp (http://umansysprop.seaes.manchester.ac.uk), for automating predictions of molecular and atmospheric aerosol properties. Current facilities include pure component vapour pressures, critical properties, and sub-cooled densities of organic molecules; activity coefficient predictions for mixed inorganic–organic liquid systems; hygroscopic growth factors and CCN (cloud condensation nuclei) activation potential of mixed inorganic–organic aerosol particles; and absorptive partitioning calculations with/without a treatment of non-ideality. The aim of this new facility is to provide a single point of reference for all properties relevant to atmospheric aerosol that have been checked for applicability to atmospheric compounds where possible. The group contribution approach allows users to upload molecular information in the form of SMILES (Simplified Molecular Input Line Entry System) strings and UManSysProp will automatically extract the relevant information for calculations. Built using open-source chemical informatics, and hosted at the University of Manchester, the facilities are provided via a browser and device-friendly web interface, or can be accessed using the user's own code via a JSON API (application program interface). We also provide the source code for all predictive techniques provided on the site, covered by the GNU GPL (General Public License) license to encourage development of a user community. We have released this via a Github repository (doi:10.5281/zenodo.45143). In this paper we demonstrate its use with specific examples that can be simulated using the web-browser interface.

Bibliographical metadata

Original languageEnglish
JournalGeoscientific Model Development
DOIs
StatePublished - 1 Mar 2016