Molecular Systems Engineering of High-Value Structured and Formulated Products
Lead Research Organisation:
Imperial College London
Department Name: Chemical Engineering
Abstract
The focus of research in Molecular Systems Engineering is the development of methods and tools for the design of better products and processes in applications where molecular interactions play a central role. To date we have developed a successful activity focussed mostly on large-scale gas-liquid processes. A strategic objective of this proposal is to make a leap to the more challenging high-value manufacturing arena, where formulated and structured products are prevalent. The combination of fundamental physical understanding, mathematical models, and numerical methods is the cornerstone of our approach. It allows us to reduce our dependence on rules-of-thumb which have traditionally been used to make models tractable but which have a limited validity. The success of this approach is strongly dependent upon the ability to exploit the synergies between molecular modelling and process engineering, as we have demonstrated in the design of novel processes for carbon dioxide capture from natural gas. Our team of investigators and RAs will be ideally positioned to overcome the challenges posed by high-value products and processes thanks to its current expertise, the investment we have made in breaking down the barriers to interdisciplinary work, and the new skills, continuity and flexibility afforded by a platform grant.
An overriding objective of the platform grant is to fast-track the careers of the individual researchers involved. Supporting the careers of researchers has always been central to our approach to research. This grant will give us a unique ability to push this further by providing us with the resources and critical mass to put in place a more structured development programme.
An overriding objective of the platform grant is to fast-track the careers of the individual researchers involved. Supporting the careers of researchers has always been central to our approach to research. This grant will give us a unique ability to push this further by providing us with the resources and critical mass to put in place a more structured development programme.
Planned Impact
The economic and societal impact of the proposed research will be realised through improvements in product and process design in the high-value chemical manufacturing sector, which includes pharmaceuticals, agrochemicals, consumer products, paints & coatings, refrigerants. These industries play an important role in the UK economy, and develop products which have a clear impact on healthcare and well-being. One aim of this platform grant is to develop techniques rooted in fundamentals that are relevant to practical applications and can be adopted by industry. The strong emphasis on the development of highly-skilled postdoctoral researchers will also be an important catalyst for technology transfer.
Four leading companies from the high-value chemical manufacturing sector (BMS, GSK, Syngenta, Procter & Gamble) have stated the importance of the challenges we aim to address, and the appropriateness of the methods we will pursue. They will benefit from the research through direct involvement with the work. We will also make sure we reach other industrial beneficiaries thanks to our engagement with the Chemistry Innovation KTN, the EPSRC Directed Assembly Grand Challenge Network, the Industrial Consortium of the Centre for Process Systems Engineering (CPSE) and professional societies.
The team of investigators has a very strong track record of transferring technology transfer through spin-out companies, software licensing, short courses and workshops, training of high-calibre researchers, consulting, and industrially-sponsored research. Notable achievements include (i) the creation of PSE Ltd, a high-technology company delivering software and consulting services to a large number of Fortune 500 companies and winner of the prestigious MacRobert Award of the Royal Academy of Engineering (2007), and (ii) the licensing of SAFT technology. The impact plan we have developed is based on a range of routes to maximise the likelihood of success and to reach as wide a community as possible: training of researchers, publication in leading journals, conference presentations, participating in CPSE industrial consortium meetings, provision of a website, development of advanced courses for undergraduate and MSc students, two workshops, and identification of new partners.
Four leading companies from the high-value chemical manufacturing sector (BMS, GSK, Syngenta, Procter & Gamble) have stated the importance of the challenges we aim to address, and the appropriateness of the methods we will pursue. They will benefit from the research through direct involvement with the work. We will also make sure we reach other industrial beneficiaries thanks to our engagement with the Chemistry Innovation KTN, the EPSRC Directed Assembly Grand Challenge Network, the Industrial Consortium of the Centre for Process Systems Engineering (CPSE) and professional societies.
The team of investigators has a very strong track record of transferring technology transfer through spin-out companies, software licensing, short courses and workshops, training of high-calibre researchers, consulting, and industrially-sponsored research. Notable achievements include (i) the creation of PSE Ltd, a high-technology company delivering software and consulting services to a large number of Fortune 500 companies and winner of the prestigious MacRobert Award of the Royal Academy of Engineering (2007), and (ii) the licensing of SAFT technology. The impact plan we have developed is based on a range of routes to maximise the likelihood of success and to reach as wide a community as possible: training of researchers, publication in leading journals, conference presentations, participating in CPSE industrial consortium meetings, provision of a website, development of advanced courses for undergraduate and MSc students, two workshops, and identification of new partners.
Publications
Zhu K
(2020)
Generating a Machine-Learned Equation of State for Fluid Properties.
in The journal of physical chemistry. B
Zheng L
(2019)
Employing SAFT Coarse-Grained Force Fields for the Molecular Simulation of Thermodynamic and Transport Properties of CO 2 - n -Alkane Mixtures
in Journal of Chemical & Engineering Data
Zhao B
(2017)
Predicting the Fluid-Phase Behavior of Aqueous Solutions of ELP (VPGVG) Sequences Using SAFT-VR.
in Langmuir : the ACS journal of surfaces and colloids
Wu L
(2018)
Demixing, surface nematization, and competing adsorption in binary mixtures of hard rods and hard spheres under confinement.
in The Journal of chemical physics
Wu L
(2013)
Liquid crystal phase behaviour of attractive disc-like particles.
in International journal of molecular sciences
Wu L
(2015)
Publisher's Note: "Orientational ordering and phase behaviour of binary mixtures of hard spheres and hard spherocylinders" [J. Chem. Phys. 143, 044906 (2015)].
in The Journal of chemical physics
Wu L
(2015)
Orientational ordering and phase behaviour of binary mixtures of hard spheres and hard spherocylinders.
in The Journal of chemical physics
Wehbe M
(2023)
Thermodynamic modelling of the nature of speciation and phase behaviour of binary and ternary mixtures of formaldehyde, water and methanol
in Molecular Physics
Vasileiadis M
(2015)
Prediction of the crystal structures of axitinib, a polymorphic pharmaceutical molecule
in Chemical Engineering Science
Valsecchi M
(2024)
Modelling the thermodynamic properties of the mixture of water and polyethylene glycol (PEG) with the SAFT- ? Mie group-contribution approach
in Fluid Phase Equilibria
Theodorakis PE
(2015)
Superspreading: mechanisms and molecular design.
in Langmuir : the ACS journal of surfaces and colloids
Theodorakis PE
(2015)
Modelling the superspreading of surfactant-laden droplets with computer simulation.
in Soft matter
Theodorakis P
(2019)
Molecular Dynamics Simulation of the Superspreading of Surfactant-Laden Droplets. A Review
in Fluids
Tchon D
(2021)
Three new polymorphs of 1,8-diacetylpyrene: a material with packing-dependent luminescence properties and a testbed for crystal structure prediction
in Journal of Materials Chemistry C
Sugden IJ
(2019)
Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. II. Smoothed intramolecular potentials.
in Acta crystallographica Section B, Structural science, crystal engineering and materials
Sugden I
(2016)
Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. I. Adaptive local approximate models.
in Acta crystallographica Section B, Structural science, crystal engineering and materials
Struebing H
(2013)
Computer-aided molecular design of solvents for accelerated reaction kinetics.
in Nature chemistry
Struebing H
(2017)
A QM-CAMD approach to solvent design for optimal reaction rates
in Chemical Engineering Science
Skutnik R
(2019)
The formation of biaxial nematic phases in binary mixtures of thermotropic liquid-crystals composed of uniaxial molecules
in Molecular Physics
Siougkrou E
(2014)
On the optimal design of gas-expanded liquids based on process performance
in Chemical Engineering Science
Schreckenberg J
(2014)
Modelling of the thermodynamic and solvation properties of electrolyte solutions with the statistical associating fluid theory for potentials of variable range
in Molecular Physics
Schmidt J
(2021)
Computational Screening of Chiral Organic Semiconductors: Exploring Side-Group Functionalization and Assembly to Optimize Charge Transport
in Crystal Growth & Design
Santiso E
(2013)
On the Calculation of Solid-Fluid Contact Angles from Molecular Dynamics
in Entropy
Description | Developed generic group contribution and simulation platform for the thermodynamic, structural and dynamical properties of complex fluid mixtures and molecular solids and materials. |
Exploitation Route | software and theoretical methodology and technology transfer |
Sectors | Agriculture, Food and Drink,Chemicals,Energy,Environment,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
URL | http://molecularsystemsengineering.org/ |
Description | Our cutting-edge work is of prime relevance to industry, as testified by collaborations in pharmaceuticals, biotechnology, energy, oil and gas, specialty chemicals, and personal care: ABB, AkzoNobel, AstraZeneca, BASF, BCURA, BMS, Borealis, BP, Britest, CIBA, E.ON, Eli Lilly, ICI, IFP, Ineos, P&G, Rhodia, Shell, Schlumberger, and Syngenta. Our work has had a major impact on process development at ICI/Ineos (production of replacement refrigerants), at BP Chemicals (acetyls), at BP Exploration (surfactants used in enhanced oil recovery to extend oil field lifetimes by a factor of up to 5) and at Borealis (increased gas-phase polyethylene production). We license our technologies via spin-off companies such as Process Systems Enterprise (PSE), including the gPROMS modelling software created under the leadership of CCP, which is used by over 70 companies and 250 universities worldwide and, more recently, our numerical methods for the integration of advanced gSAFT thermodynamics in process modelling. More recently we have extended the use of our methodology in the pharmaceutical industry (Pfizer, GSK, Eli Lilly, AstraZeneca) for the prediction of API solubility and partitioning, and in the area of carbon capture and storage. |
First Year Of Impact | 2013 |
Sector | Agriculture, Food and Drink,Chemicals,Digital/Communication/Information Technologies (including Software),Energy,Environment,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
Impact Types | Societal,Economic |
Title | Modelling and prediction of the thermophysical properties of aqueous mixtures of choline geranate and geranic acid (CAGE) using SAFT-g Mie |
Description | Calculated and experimental data for all the figures in the publication |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
Title | Modelling and prediction of the thermophysical properties of aqueous mixtures of choline geranate and geranic acid (CAGE) using SAFT-g Mie |
Description | Calculated and experimental data for all the figures in the publication |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |