231 results found
Jonuzaj S, Gupta A, Adjiman CS, 2018, The design of optimal mixtures from atom groups using Generalized Disjunctive Programming, Computers and Chemical Engineering, ISSN: 0098-1354
© 2018 The Authors. A comprehensive computer-aided mixture/blend design methodology for formulating a general mixture design problem where the number, identity and composition of mixture constituents are optimized simultaneously is presented in this work. Within this approach, Generalized Disjunctive Programming (GDP) is employed to model the discrete decisions (number and identities of mixture ingredients) in the problems. The identities of the components are determined by designing molecules from UNIFAC groups. The sequential design of pure compounds and blends, and the arbitrary pre-selection of possible mixture ingredients can thus be avoided, making it possible to consider large design spaces with a broad variety of molecules and mixtures. The proposed methodology is first applied to the design of solvents and solvent mixtures for maximising the solubility of ibuprofen, often sought in crystallization processes; next, antisolvents and antisolvent mixtures are generated for minimising the solubility of the drug in drowning out crystallization; and finally, solvent and solvent mixtures are designed for liquid-liquid extraction. The GDP problems are converted into mixed-integer form using the big-M approach. Integer cuts are included in the general models leading to lists of optimal solutions which often contain a combination of pure and mixed solvents.
Adjiman CS, Harrison NM, Weider SZ, 2017, Molecular science and engineering: a powerful transdisciplinary approach to solving grand challenges, Briefing paper, 1
The concept of molecular science and engineering – melding a deep understanding of molecular science with an engineering mind-set – is emerging as a powerful way to create novel, effective and sustainable solutions to global grand challenges, such as the growing threat of antimicrobial resistance. By blurring the boundaries between scientificand engineering disciplines, in this holistic approach, final function and end-use requirements become an integral part of the underlying scientific research. Commercially ready materials can thus become a reality in an accelerated, flexible and economic manner. In other words, molecular science and engineering can fundamentally alter the way molecules are identified and designed for real-world usage. It is not enough to simply make molecules; we must make molecules work for a complex world.The notion of bringing researchers, industry and government communities together to work on grand challenges has a long and illustrious history – think, for instance, of the Manhattan Project, the industrial scale-up of penicillin and the Moon landings. More recently, the idea of ‘convergence’ – tackling grand challenges with a multifaceted array of scientists, engineers, clinicians and beyond – has become more formally recognised as a valuable way to stimulate societally important and ground-breaking research. Molecular science and engineering is a specific, yet far-reaching, part of this convergence landscape.Within the growing worldwide molecular science and engineering community, the Institute for Molecular Science and Engineering (IMSE) was founded in 2015 as Imperial College London’s newest Global Institute. The Institute’s overarching aim is to bring the College’s engineers, scientists, medics and business researchers together with awide array of external stakeholders – and to remove the boundaries between these disciplines – to find innovative molecular-based scie
Diamanti A, Adjiman CS, Piccione PM, et al., 2017, Development of Predictive Models of the Kinetics of a Hydrogen Abstraction Reaction Combining Quantum-Mechanical Calculations and Experimental Data, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 56, Pages: 815-831, ISSN: 0888-5885
Gu B, Adjiman CS, Xu XY, 2017, The effect of feed spacer geometry on membrane performance and concentration polarisation based on 3D CFD simulations, JOURNAL OF MEMBRANE SCIENCE, Vol: 527, Pages: 78-91, ISSN: 0376-7388
Hutacharoen P, Dufal S, Papaioannou V, et al., 2017, Predicting the solvation of organic compounds in aqueous environments: from alkanes and alcohols to pharmaceuticals, Industrial and Engineering Chemistry Research, Vol: 56, Pages: 10856-0876, ISSN: 0888-5885
The development of accurate models to predict the solvation, solubility, and partitioning of nonpolar and amphiphilic compounds in aqueous environments remains an important challenge. We develop state-of-the-art group-interaction models that deliver an accurate description of the thermodynamic properties of alkanes and alcohols in aqueous solution. The group-contribution formulation of the statistical associating fluid theory based on potentials with a variable Mie form (SAFT-γ Mie) is shown to provide accurate predictions of the phase equilibria, including liquid–liquid equilibria, solubility, free energies of solvation, and other infinite-dilution properties. The transferability of the model is further exemplified with predictions of octanol–water partitioning and solubility for a range of organic and pharmaceutically relevant compounds. Our SAFT-γ Mie platform is reliable for the prediction of challenging properties such as mutual solubilities of water and organic compounds which can span over 10 orders of magnitude, while remaining generic in its applicability to a wide range of compounds and thermodynamic conditions. Our work sheds light on contradictory findings related to alkane–water solubility data and the suitability of models that do not account explicitly for polarity.
Jonuzaj S, Adjiman CS, 2017, Designing optimal mixtures using generalized disjunctive programming: Hull relaxations, CHEMICAL ENGINEERING SCIENCE, Vol: 159, Pages: 106-130, ISSN: 0009-2509
Nerantzis D, Adjiman CS, 2017, Enclosure of all index-1 saddle points of general nonlinear functions, JOURNAL OF GLOBAL OPTIMIZATION, Vol: 67, Pages: 451-474, ISSN: 0925-5001
Nerantzis D, Adjiman CS, 2017, An interval-matrix branch-and-bound algorithm for bounding eigenvalues, OPTIMIZATION METHODS & SOFTWARE, Vol: 32, Pages: 872-891, ISSN: 1055-6788
Struebing H, Obermeier S, Siougkrou E, et al., 2017, A QM-CAMD approach to solvent design for optimal reaction rates, CHEMICAL ENGINEERING SCIENCE, Vol: 159, Pages: 69-83, ISSN: 0009-2509
Brand CV, Graham E, Rodriguez J, et al., 2016, On the use of molecular-based thermodynamic models to assess the performance of solvents for CO2 capture processes: monoethanolamine solutions, FARADAY DISCUSSIONS, Vol: 192, Pages: 337-390, ISSN: 1359-6640
Chremos A, Forte E, Papaioannou V, et al., 2016, Modelling the phase and chemical equilibria of aqueous solutions of alkanolamines and carbon dioxide using the SAFT-gamma SW group contribution approach, FLUID PHASE EQUILIBRIA, Vol: 407, Pages: 280-297, ISSN: 0378-3812
Eriksen DK, Lazarou G, Galindo A, et al., 2016, Development of intermolecular potential models for electrolyte solutions using an electrolyte SAFT-VR Mie equation of state, MOLECULAR PHYSICS, Vol: 114, Pages: 2724-2749, ISSN: 0026-8976
Gopinath S, Galindo A, Jackson G, et al., 2016, A feasibility-based algorithm for Computer Aided Molecular and Process Design of solvent-based separation systems, 26th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 73-78, ISSN: 1570-7946
Gopinath S, Jackson G, Galindo A, et al., 2016, Outer Approximation Algorithm with Physical Domain Reduction for Computer-Aided Molecular and Separation Process Design, AICHE JOURNAL, Vol: 62, Pages: 3484-3504, ISSN: 0001-1541
Gu B, Xu XY, Adjiman CS, 2016, A predictive model for spiral wound reverse osmosis membrane modules: The effect of winding geometry and accurate geometric details, Computers and Chemical Engineering, Vol: 96, Pages: 248-265, ISSN: 1873-4375
A new one-dimensional predictive model for spiral wound modules (SWMs) applied to reverse osmosis membrane systems is developed by incorporating a detailed description of the geometric features of SWMs and considering flow in two directions. The proposed model is found to capture existing experimental data well, with similar accuracy to the widely-used plate model in which the SWM is assumed to consist of multiple thin rectangular channels. However, physical parameters that should in principle be model-independent, such as membrane permeability, are found to differ significantly depending on which model is used, when the same data sets are used for parameter estimation. Conversely, when using the same physical parameter values in both models, the water recovery predicted by the plate-like model is 12–20% higher than that predicted by the spiral model. This discrepancy is due to differences in the description of geometric features, in particular the active membrane area and the variable channel heights through the module, which impact on predicted performance and energy consumption. A number of design variables – the number of membrane leaves, membrane dimensions, centre pipe radius and the height of feed and permeate channels – are varied and their effects on performance, energy consumption and calculated module size are analysed. The proposed spiral model provides valuable insights into the effects of complex geometry on the performance of the SWM as well as of the overall system, at a low computational cost.
Jonuzaj S, Adjiman CS, 2016, A Convex Hull Formulation for the Design of Optimal Mixtures, 26th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 2325-2330, ISSN: 1570-7946
Jonuzaj S, Akula PT, Kleniati P-M, et al., 2016, The Formulation of Optimal Mixtures with Generalized Disjunctive Programming: A Solvent Design Case Study, AICHE JOURNAL, Vol: 62, Pages: 1616-1633, ISSN: 0001-1541
Papadopoulos AI, Badr S, Chremos A, et al., 2016, Computer-aided molecular design and selection of CO2 capture solvents based on thermodynamics, reactivity and sustainability, MOLECULAR SYSTEMS DESIGN & ENGINEERING, Vol: 1, Pages: 313-334, ISSN: 2058-9689
Papaioannou V, Calado F, Lafitte T, et al., 2016, Application of the SAFT-gamma Mie group contribution equation of state to fluids of relevance to the oil and gas industry, FLUID PHASE EQUILIBRIA, Vol: 416, Pages: 104-119, ISSN: 0378-3812
Paulavicius R, Kleniati P-M, Adjiman CS, 2016, Global optimization of nonconvex bilevel problems: implementation and computational study of the Branch-and-Sandwich algorithm, 26th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 1977-1982, ISSN: 1570-7946
Reilly AM, Cooper RI, Adjiman CS, et al., 2016, Report on the sixth blind test of organic crystal structure prediction methods, ACTA CRYSTALLOGRAPHICA SECTION B-STRUCTURAL SCIENCE CRYSTAL ENGINEERING AND MATERIALS, Vol: 72, Pages: 439-459, ISSN: 2052-5206
Sadeqzadeh M, Papaioannou V, Dufal S, et al., 2016, The development of unlike induced association-site models to study the phase behaviour of aqueous mixtures comprising acetone, alkanes and alkyl carboxylic acids with the SAFT-gamma Mie group contribution methodology, FLUID PHASE EQUILIBRIA, Vol: 407, Pages: 39-57, ISSN: 0378-3812
Sugden I, Adjiman CS, Pantelides CC, 2016, Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. I. Adaptive local approximate models, ACTA CRYSTALLOGRAPHICA SECTION B-STRUCTURAL SCIENCE CRYSTAL ENGINEERING AND MATERIALS, Vol: 72, Pages: 864-874, ISSN: 2052-5206
Burger J, Papaioannou V, Gopinath S, et al., 2015, A hierarchical method to integrated solvent and process design of physical CO2 absorption using the SAFT- Mie approach, AICHE JOURNAL, Vol: 61, Pages: 3249-3269, ISSN: 0001-1541
Gopinath S, Galindo A, Jackson G, et al., 2015, Computer aided molecular and process design using complex process and thermodynamic models: A screening based approach, Pages: 107-109
Copyright © American Institute of Chemical Engineers. All rights reserved. The design of optimal processing materials (molecules) and optimal process variables for a given process is referred to as Computer Aided Molecular and Process Design (CAMPD). Processing materials used to achieve process goals include mass separating agents (such as solvents for absorption, extraction, leaching and adsorbents), catalysts, heat transfer fluids and reaction medium solvents. Choosing processing molecules influences the optimal process variables and vice versa. Molecular and process decision variables are linked, interacting with each other in a complex manner. Hence, neither of these decisions can be made in isolation.
Habgood M, Sugden IJ, Kazantsev AV, et al., 2015, Efficient Handling of Molecular Flexibility in Ab Initio Generation of Crystal Structures, JOURNAL OF CHEMICAL THEORY AND COMPUTATION, Vol: 11, Pages: 1957-1969, ISSN: 1549-9618
Kleniati P-M, Adjiman CS, 2015, A generalization of the Branch-and-Sandwich algorithm: From continuous to mixed-integer nonlinear bilevel problems, COMPUTERS & CHEMICAL ENGINEERING, Vol: 72, Pages: 373-386, ISSN: 0098-1354
Nerantzis D, Adjiman CS, 2015, Deterministic Global Optimization and Transition States, 12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING (PSE) AND 25TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING (ESCAPE), PT A, Vol: 37, Pages: 851-856, ISSN: 1570-7946
Papadokonstantakis S, Badr S, Hungerbühler K, et al., 2015, Toward Sustainable Solvent-Based Postcombustion CO<inf>2</inf> Capture: From Molecules to Conceptual Flowsheet Design, Computer Aided Chemical Engineering, Vol: 36, Pages: 279-310, ISSN: 1570-7946
© 2015 Elsevier B.V. Solvent-based postcombustion carbon dioxide (CO < inf > 2 < /inf > ) capture requires minimum retrofitting of current CO < inf > 2 < /inf > -emitting power plants but is challenging because of the high energy penalty in solvent regeneration and the environmental impacts of solvent degradation. Research efforts are predominantly based on lab and pilot-scale experiments to select solvents and process systems which improve the overall performance of this technology. Notwithstanding the value of the experimental efforts, this study proposes an efficient computational approach for screening a vast number of commercial and novel solvents and process configurations. Computer-aided molecular design, advanced group contribution methods, process synthesis, and multicriteria sustainability assessment are combined to provide new insights in solvent-based CO < inf > 2 < /inf > capture. This study provides details of the data requirements, highlights several high-performance solvents and process configurations, and quantifies the benefits from economic, life cycle, and hazard assessment perspective. Thus, it also provides information for the experimental approaches, focusing on a narrower, near-optimum design space.
Rhazaoui K, Cai Q, Kishimoto M, et al., 2015, Towards the 3D Modelling of the Effective Conductivity of Solid Oxide Fuel Cell Electrodes - Validation against experimental measurements and prediction of electrochemical performance, ELECTROCHIMICA ACTA, Vol: 168, Pages: 139-147, ISSN: 0013-4686
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