Complex formulated products, such as shampoos, detergent powders
and liquids, processed foods, paints, adhesives, lubricants and
pesticide granules, are ubiquitous in everyday and industrial life. The
UK market for formulated products is worth around £180bn a year, with
further potential in emerging overseas markets of around £1,000bn
(Chemistry Innovation KTN Strategy Report 2010). Whilst in civil and
mechanical engineering, the design process is done almost entirely by
computer with reduced physical prototyping formulated product design is
still predominantly an ad hoc labour-intensive process. Scientists from
the Computational Chemistry Group in SCD have teamed up with Unilever,
Syngenta and Infineum, to secure a TSB backed £1 million project to
advance the development of formulated products using Computer Aided
The CAF project will build upon the potential of mesoscale
modelling to drive a radical change in speed of formulated product
design for manufacturability and in-use performance. The technical
challenge is to develop predictive models that are simple yet accurate
enough to enable predictive product design. This will reduce the time to
market and development costs of a new or reformulated product. Initial
results within the consortium across an extended formulation space
(detergents, speciality chemicals, agro-technical formulations) are
encouraging, to the point where the solution behaviour, formulation
stability and surface interaction properties are accurately predicted
for small subsets of chemical entities. The research team from the SCD
will expand the capabilities of the established mesoscale method,
dissipative particle dynamics (DPD), by incorporating appropriate
physical models required to reproduce important experimental behaviour.
Developments made to the DPD methodology during this project will
address a number of deficiencies within the current framework and will
broaden the range of applicability of this method. These developments
will permit the simulation of more realistic and complex systems and
will provide greater understanding into the mode of action of many
different formulated products.
It is expected that there will be a number of positive outcomes
from this project beyond the immediate commercial partners, who stand to
develop better products faster and more sustainably. Academic
beneficiaries from the field of condensed matter will be able to make
the most of the advances to the DPD methodology and it is anticipated
that the developments will be of use to researchers in other areas such
as biophysics, e.g. the simulation of biomembranes and lipid bilayers.
Furthermore, it is expected that DPD will play an ever-increasing role
in multi-scale modelling approaches through bridging of the atomistic
and continuum scales. In such approaches, atomistic simulations are
performed to build the DPD models, followed by DPD simulations that
provide the necessary input to the continuum codes. Implementations of
such approaches can circumvent assumptions in the continuum codes since
the mesoscale simulations can provide more accurate estimates of the
thermodynamic state within the localised regions compared to a
constitutive equation. With an improved DPD framework resulting from
this work even more accurate estimates can be achieved. DPD methodology
developments occurring during the project will be fully incorporated
into the UK academic DPD simulation code, DL_MESO. This simulation code
is freely available to academic users world-wide under license.
For more information please contact Rick Anderson.
M A Seaton, R L Anderson, S Metz and W Smith, DL_MESO: Highly
scalable mesoscale simulation, Molecular Simulation 39, 2013, 796 – 821.
M A Johnston, W C Swope, K E Jordan, P B Warren, M G Noro, D J Bray, R L Anderson, Towards a Standard Protocol for Micelle Simulation, Journal of Physical Chemistry B 120, 2016, 6337 - 6351.