Computational modelling is the use of mathematics, statistics, and computer simulation to make predictions for real-world things. It's a kind of "virtual R&D".

The academic world is full of predictive modelling tools for polymers, liquids, formulations, surfactants, and dispersions. It is a bleeding-edge area of research, particularly as compute power grows rapidly.

Harnessing computational modelling for commercial R&D is much more challenging. It requires deep technical expertise, careful interpretation of output, and selective use in order to benefit these industries in a measurable way. Modern materials and formulations are exceptionally complex at the chemical level. Similar complexity is involved in modelling these systems.

Vanson Viridis helps you exploit cutting-edge computational modelling, so that you can do R&D faster, more ecologically, and more economically. We offer expertise in

• directly modelling your formulations and materials, to provide predictions and data that accelerate your product R&D

• code development and knowledge exchange, in collaboration with existing in-house modellers in your organisation

• strategy consultancy, for more broadly incorporating computational modelling into your R&D lifecycle

Our core technical domain is computational modelling at the molecular and coarse-molecular scales. Below are some of our application areas, predictive capabilities, and tools we employ.

Application areas
polymeric materials
liquid / surfactant formulations
nanoparticle / colloidal dispersions
liquid crystalline materials (liquid, elastomer)

Modelling capabilities
phase behavior: critical temperatures, phase separation / blending, solubility, IFT
self-assembly: copolymer and surfactant molecular morphology
rheology: shear viscosity, elasticity

Computational tools
molecular dynamics (LAMMPS, Hoomd-Blue, custom codes)
Monte Carlo (custom codes)
polymer self-consistent field theory
analytical methods

We provide our service by

• Directly carrying out modelling for you, on your system(s) of interest

• Collaboration with modellers already in your organisation, to help co-develop your computational tools and contribute new methodological expertise.

In both cases, we can cover

• Interpreting model output into practical guidance and insight for your R&D.

• Maximizing commercial value out of model data.

Virtual R&D is not just about computational modelling. It’s also about embracing new ways of thinking about scientific development. This can be challenging (and sometimes feel threatening) to a well-established R&D pipeline.

We provide consultancy to help you address questions like

• How do you start off deployment of computational modelling?

• How long will it take to see an impact on your product pipeline?

• Do you need to build an in-house modelling team to be successful? 

• If so, which areas of expertise do you need, and how large should the team be?

Examples of service we provide to solve these obstacles are

• Building a tailored strategy to incorporate modelling into your R&D lifecycle

• Planning, hiring, and directing a new in-house modeling/sim team within your group, to accelerate your R&D program

• Guidance, collaboration, education, and/or management for existing modelling team members in your group

Vanson Viridis has its own in-house compute resources for small/medium-sized simulations, and for prototyping large simulations.

For more extensive computational work we employ Amazon Web Services. If desired, for confidentiality or convenience, we can also do calculations on dedicated compute resources available within your organization. 

Vanson Viridis was founded by Nicholas Tito, Ph.D in 2023. Growing up on the coast of Maine in the United States, Nick was inspired to study physical sciences by the powerful winter cyclones that strike his home town each year.

Nick started his career with doctoral and post-doctoral work in Physical Chemistry at Dartmouth, University of Cambridge, and TU Eindhoven. His research focuses on theory and coarse-grained simulation of polymeric materials (melts, glasses, networks, elastomers), and liquid crystals for functional devices. Nick got hands-on experience with the chemical R&D industry at RheoCube, an innovative cloud-sim tech startup in Amsterdam, where he evolved through the roles of modelling expert, team leader, product owner, and Director of Science. Much of his work focused on connecting client R&D needs to the capabilities of computational modelling.

With this range of skills under his belt, Nick founded Vanson Viridis: a firm that partners with ambitious clients in the chemical and materials industry to leverage computational modelling as a potent form of "R&D digitization".