Imperial College London

Professor Omar K. Matar, FREng

Faculty of EngineeringDepartment of Chemical Engineering

Head of Department of Chemical Engineering
 
 
 
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Contact

 

+44 (0)20 7594 9618o.matar Website

 
 
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Assistant

 

Mr Avery Kitchens +44 (0)20 7594 6263

 
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Location

 

305 ACEACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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349 results found

Pico P, Kahouadji L, Shin S, Chergui J, Juric D, Matar OKet al., 2024, Drop encapsulation and bubble bursting in surfactant-laden flows in capillary channels, Physical Review Fluids, Vol: 9

We present a parametric study of the unsteady phenomena associated with the flow of elongated gas bubbles traveling through liquid-filled square capillaries under high Weber number conditions. These conditions induce the formation of an indentation at the back of the bubble that commonly gives way to a deep reentrant liquid jet penetrating the bubble. Subsequent steps include pinch-off events in the penetrating liquid to generate one or multiple encapsulated drops which may coalesce, in conjunction with the bursting of the bubble-liquid interface by either the liquid jet or the drops. Some of these interfacial instabilities have previously been reported experimentally and numerically for liquid-liquid flow in microchannels. We carry out three-dimensional direct numerical simulations based on a hybrid interface-tracking/level-set method capable of accounting for the presence and dynamic exchange of surfactants between the liquid bulk phase and the liquid-gas interface. Our results indicate that the delicate interplay among inertia, capillarity, viscosity, surfactant adsorption/desorption kinetics, and Marangoni stresses has a dramatic influence over the nonaxisymmetric morphological structures of the encapsulated drops-elongated bubble. This strong coupling also influences the pinch-off time, penetration depth of the liquid, and number, size, and velocity of the encapsulated drops across the bubble. The observed phenomena are summarized in three main morphological regimes based on surfactant-related parameters and dimensionless groups. A discussion of the flow regime maps is also provided.

Journal article

Heaney CE, Li Y, Matar OK, Pain CCet al., 2024, Applying convolutional neural networks to data on unstructured meshes with space-filling curves, Neural Networks, Pages: 106198-106198, ISSN: 0893-6080

Journal article

Chatterjee S, Abadie T, Wang M, Matar OK, Ruoff RSet al., 2024, Repeatability and Reproducibility in the Chemical Vapor Deposition of 2D Films: A Physics-Driven Exploration of the Reactor Black Box, Chemistry of Materials, Vol: 36, Pages: 1290-1298, ISSN: 0897-4756

Although chemical vapor deposition (CVD) remains the method of choice for synthesizing defect-free and high-quality 2D films (such as graphene and h-BN), the method has serious issues with process repeatability and reproducibility. This makes it difficult to build up from the literature, test a hypothesis quickly, or scale up a process. The primary reason for this is that the CVD reactor, to this day, remains a black box with a reaction environment that is poorly understood and cannot be measured or monitored directly. Consequently, it is also difficult to study process kinetics and growth mechanisms and correlate experimental results to atomic-level simulations. A possible way to overcome this problem is to use Computational Fluid Dynamics (CFD), both to identify the measurable external (process and reactor) parameters that control the reaction environment and to simulate this reaction environment and understand how it changes when these controllable external parameters are varied. This paper describes how this may be done in practice using the growth of single-layer graphene in a hot-wall tube reactor as the representative case and the CFD toolbox OpenFOAM. Based on our findings, we have shown why it is critical (1) to understand the flow properties inside the reactor and combine it with experimental results to study the growth process for graphene and other 2D films and (2) to measure, monitor, and report all relevant external parameters to ensure process repeatability and reproducibility.

Journal article

Lew JH, Hue KY, Matar O, Muller E, Luckham P, Sousa Santos A, Myo Thant MMet al., 2024, Atomic force microscopy and molecular dynamic simulation of adsorption of polyacrylamide with different chemistries onto calcium carbonate, Polymers, Vol: 16, ISSN: 2073-4360

This study investigates the interaction of polyacrylamide (PAM) of different functional groups (sulfonate vs. carboxylate) and charge density (30% hydrolysed vs. 10% hydrolysed) with calcium carbonate (CaCO3) via atomic force microscopy (AFM) and partly via molecular dynamic (MD) simulations. The PAM used were F3330 (30% hydrolysed), AN125 (25% sulfonated), and AN910 (% hydrolysed). A total of 100 ppm of PAMs was prepared in 0.1% NaCl, 3% NaCl, and 4.36% NaNO3 to be employed in AFM experiments, while oligomeric models (30 repeating units) of hydrolysed polyacrylamide (HPAM), sulfonated polyacrylamide (SPAM), and neutral PAM (NPAM) were studied on a model calcite surface on MD simulations. AFM analysis indicated that F3330 has a higher average adhesion and interaction energy with CaCO3 than AN125 due to the bulky sulfonate side group of AN125 interfering with SPAM adsorption. Steric repulsion of both PAMs was similar due to their comparable molecular weights and densities of the charged group. In contrast, AN910 showed lower average adhesion and interaction energy, along with slightly longer steric repulsion with calcite than F3330, suggesting AN910 adopts more loops and tails than the slightly flatter F3330 configuration. An increase in salt concentration from 0.1% to 3% NaCl saw a reduction in adhesion and interaction energy for F3330 and AN125 due to charge screening, while AN910 saw an increase, and these values increased further at 4.36% NaNO3. MD simulations revealed that the salt ions in the system formed salt bridges between PAM and calcite, indicating that the adhesion and interaction energy observed from AFM are likely to be the net balance between PAM charged group screening and salt bridging by the salt ions present. Salt ions with larger bare radii and smaller hydrated radii were shown to form stronger salt bridges.

Journal article

Matar OK, 2024, A soap boat trip on ‘Lake Marangoni’, Nature Chemical Engineering, Vol: 1, Pages: 190-190

Journal article

Municchi F, Markides CN, Matar OK, Magnini Met al., 2024, Computational study of bubble, thin-film dynamics and heat transfer during flow boiling in non-circular microchannels, Applied Thermal Engineering, Vol: 238, ISSN: 1359-4311

Flow boiling in multi-microchannel evaporators is one of the most efficient thermal management solutions forhigh-power-density applications. However, there is still a lack of understanding of the governing two-phaseheat and mass transfer processes that occur in these devices, which has resulted in a limited availability ofapplicable boiling heat transfer prediction methods based on first principles, and of reliable thermal designtools. This article presents a systematic analysis of the dynamics of bubbles and the surrounding liquid filmduring flow boiling in three-side-heated non-circular microchannels. The study is performed using a customversion of ESI OpenFOAM v2106 with a geometric volume-of-fluid method to capture the interface dynamics, also incorporating conjugate heat transfer through the evaporator walls. The hydraulic diameter of the channel is fixed to 𝐷ℎ = 0.229 mm and the range of width-to-height aspect ratios 𝜖 = 0.25−4 is examined. We investigate different fluids, namely water, HFE7100, R1233zd(E), R1234ze(E), and evaporator materials, namely copper, aluminium, silicon, stainless steel, with base heat fluxes in the range 𝑞𝑏 = 50 − 200 kW∕m2. The results show that conjugate heat transfer acts to make the temperature distributions around the perimeter of the channel cross-section more uniform, and that the topography of the lubricating film and the extension of the dry vapour patches that develop while the film is depleted both depend on the cross-sectional channel shape and influence the heat transfer performance significantly. For highly wetting conditions, channels with 𝜖 = 0.25 tend to allow enhanced heat transfer rates, with a spatially-averaged Nusselt number that is 50% higher than that obtained for 𝜖 = 1 (square channels) and 10% higher than that for 𝜖 = 4. This arises thanks to an extended evaporating film that covers the vertical walls which, owing to the three-side-heated configuration, contribute twice to the spatially-ave

Journal article

Hennessy MG, Craster RV, Matar OK, 2024, Time-dependent modelling of thin poroelastic films drying on deformable plates, European Journal of Applied Mathematics, Vol: 35, Pages: 62-95, ISSN: 0956-7925

Understanding the generation of mechanical stress in drying, particle-laden films is important for a wide range of industrial processes. One way to study these stresses is through the cantilever experiment, whereby a thin film is deposited onto the surface of a thin plate that is clamped at one end to a wall. The stresses that are generated in the film during drying are transmitted to the plate and drive bending. Mathematical modelling enables the film stress to be inferred from measurements of the plate deflection. The aim of this paper is to present simplified models of the cantilever experiment that have been derived from the time-dependent equations of continuum mechanics using asymptotic methods. The film is described using nonlinear poroelasticity and the plate using nonlinear elasticity. In contrast to Stoney-like formulae, the simplified models account for films with non-uniform thickness and stress. The film model reduces to a single differential equation that can be solved independently of the plate equations. The plate model reduces to an extended form of the Föppl-von Kármán (FvK) equations that accounts for gradients in the longitudinal traction acting on the plate surface. Consistent boundary conditions for the FvK equations are derived by resolving the Saint-Venant boundary layers at the free edges of the plate. The asymptotically reduced models are in excellent agreement with finite element solutions of the full governing equations. As the Péclet number increases, the time evolution of the plate deflection changes from t to t1/2 , in agreement with experiments.

Journal article

Hu J, Zhu K, Cheng S, Kovalchuk NM, Soulsby A, Simmons MJH, Matar OK, Arcucci Ret al., 2024, Explainable AI models for predicting drop coalescence in microfluidics device, Chemical Engineering Journal, Vol: 481, ISSN: 1385-8947

In the field of chemical engineering, understanding the dynamics and probability of drop coalescence is not just an academic pursuit, but a critical requirement for advancing process design by applying energy only where it is needed to build necessary interfacial structures, increasing efficiency towards Net Zero manufacture. This research applies machine learning predictive models to unravel the sophisticated relationships embedded in the experimental data on drop coalescence in a microfluidics device. Through the deployment of SHapley Additive exPlanations values, critical features relevant to coalescence processes are consistently identified. Comprehensive feature ablation tests further delineate the robustness and susceptibility of each model. Furthermore, the incorporation of Local Interpretable Model-agnostic Explanations for local interpretability offers an elucidative perspective, clarifying the intricate decision-making mechanisms inherent to each model's predictions. As a result, this research provides the relative importance of the features for the outcome of drop interactions. It also underscores the pivotal role of model interpretability in reinforcing confidence in machine learning predictions of complex physical phenomena that are central to chemical engineering applications.

Journal article

Lew JH, Luckham PF, Matar OK, Müller EA, Santos AS, Maung Maung MTet al., 2023, Consolidation of Calcium Carbonate Using Polyacrylamides with Different Chemistries, Powders, Vol: 3, Pages: 1-16

<jats:p>In this work, the consolidation of calcium carbonate (CaCO3) by polyacrylamide (PAM) of different molecular weights, charge densities, and functional groups was investigated via oscillatory rheology and unconfined compressive strength (UCS) analysis. Oscillatory rheology showed that the storage modulus G′ was approximately 10 times higher than the loss modulus G″, indicating a highly elastic CaCO3 sample upon consolidation via PAM. Both oscillatory rheology and UCS analysis exhibited similar trends, wherein the mechanical values (G′, G″, and UCS) first increased with increasing polymer dosage, until they reached a peak value (typically at 3 mgpol/gCaCO3), followed by a decrease in the mechanical values. This indicates that there is an optimum polymer dosage for the different PAM-CaCO3 colloidal systems, and that exceeding this value induces the re-stabilisation of the colloidal system, leading to a decreased degree of consolidation. Regarding the effect of the PAM molecular weight, the peak G′ and UCS values of CaCO3 consolidated by hydrolysed PAM (HPAM) of different molecular weights are very similar. This is likely due to the contour length of the HPAMs being either almost the same or longer than the average distance between two CaCO3 particles. The effect of the PAM charge density revealed that the peak G′ and UCS values decreased as the charge density of the PAM increased, while the optimum PAM dosage increased with decreasing PAM charge density. The higher likelihood of lower-charge PAM bridging between the particles contributes to higher elastic energy and mechanical strength. Finally, regarding the PAM functional group, CaCO3 consolidated by sulfonated polyacrylamide (SPAM) typically offers lower mechanical strength than that consolidated with HPAM. The bulky sulfonate side groups of SPAM interfere with the surface packing, reducing the number of polymers able to adsorb onto the surface and, eventually, reduci

Journal article

Valdes JP, Kahouadji L, Liang F, Shin S, Chergui J, Juric D, Matar OKet al., 2023, On the dispersion dynamics of liquid–liquid surfactant-laden flows in a SMX static mixer, Chemical Engineering Journal, Vol: 475, ISSN: 1385-8947

This study aims to elucidate, for the first time, the intricate fundamental physics governing the dispersion dynamics of a surfactant-laden two-phase liquid–liquid system in the well-known SMX static mixer. Following the analysis carried out in the preceding publication to this work (Valdes et al., 2023), a comparative assessment of the most relevant and recurrent deformation and breakup mechanisms is conducted for a 3-drop scenario and then extrapolated to a more industrially-relevant multi-drop set-up. A parametric study on relevant surfactant physico-chemical parameters (i.e., elasticity, sorption kinetics) is undertaken, isolating each property by considering insoluble and soluble surfactants. In addition, the role of Marangoni stresses on the deformation and breakage dynamics is explored. High fidelity, three-dimensional direct numerical simulations coupled with a state-of-the-art hybrid interface capturing algorithm are carried out, providing a wealth of information previously inaccessible via volume-averaged or experimental approaches.

Journal article

Savage T, Basha N, McDonough J, Matar OK, del Rio Chanona EAet al., 2023, Multi-fidelity data-driven design and analysis of reactor and tube simulations, Computers and Chemical Engineering, Vol: 179, ISSN: 0098-1354

Optimizing complex reactor geometries is vital to promote enhanced efficiency. We present a framework to solve this nonlinear, computationally expensive, and derivative-free problem. Gaussian processes are used to learn a multi-fidelity model of reactor simulations correlating multiple continuous mesh fidelities. The search space of reactor geometries is explored through lower fidelity simulations, evaluated based on a weighted acquisition function, trading off information gain with cost. Within our framework, DARTS, we derive a novel criteria for dictating optimization termination, ensuring a high fidelity solution is returned before budget is exhausted. We investigate the design of helical-tube reactors under pulsed-flow conditions, which have demonstrated outstanding mixing characteristics. To validate our results, we 3D print and experimentally validate the optimal reactor geometry, confirming mixing performance. Our approach is applicable to a broad variety of expensive simulation-based optimization problems, enabling the design of novel parameterized chemical reactors.

Journal article

Pico P, Nathanael K, Lavino AD, Kovalchuk NM, Simmons MJH, Matar OKet al., 2023, Silver nanoparticles synthesis in microfluidic and well-mixed reactors: A combined and PBM-CFD, CHEMICAL ENGINEERING JOURNAL, Vol: 474, ISSN: 1385-8947

Journal article

Lew JH, Matar O, Muller E, Luckham P, Santos A, Thant MMTet al., 2023, Atomic Force Microscopy of hydrolysed polyacrylamide adsorption onto calcium carbonate, Polymers, Vol: 15, ISSN: 2073-4360

In this work, the interaction of hydrolysed polyacrylamide (HPAM) of two molecular weights (F3330, 11–13 MDa; F3530, 15–17 MDa) with calcium carbonate (CaCO3) was studied via atomic force microscopy (AFM). In the absence of polymers at 1.7 mM and 1 M NaCl, good agreement with DLVO theory was observed. At 1.7 mM NaCl, repulsive interaction during approach at approximately 20 nm and attractive adhesion of approximately 400 pN during retraction was measured, whilst, at 1 M NaCl, no repulsion during approach was found. Still, a significantly larger adhesion of approximately 1400 pN during retraction was observed. In the presence of polymers, results indicated that F3330 displayed higher average adhesion (450–625 pN) and interaction energy (43–145 aJ) with CaCO3 than F3530’s average adhesion (85–88 pN) and interaction energy (8.4–11 aJ). On the other hand, F3530 exerted a longer steric repulsion distance (70–100 nm) than F3330 (30–70 nm). This was likely due to the lower molecular weight. F3330 adopted a flatter configuration on the calcite surface, creating more anchor points with the surface in the form of train segments. The adhesion and interaction energy of both HPAM with CaCO3 can be decreased by increasing the salt concentration. At 3% NaCl, the average adhesion and interaction energy of F3330 was 72–120 pN and 5.6–17 aJ, respectively, while the average adhesion and interaction energy of F3530 was 11.4–48 pN and 0.3–2.98 aJ, respectively. The reduction of adhesion and interaction energy was likely due to the screening of the COO− charged group of HPAM by salt cations, leading to a reduction of electrostatic attraction between the negatively charged HPAM and the positively charged CaCO3.

Journal article

Basha N, Savage T, McDonough J, del Rio Chanona EA, Matar OKet al., 2023, Discovery of mixing characteristics for enhancing coiled reactor performance through a Bayesian optimisation-CFD approach, Chemical Engineering Journal, Vol: 473, ISSN: 1385-8947

Plug flow characteristics are advantageous in various manufacturing processes for fine/bulk chemicals, pharmaceuticals, biofuels, and waste treatment as they contribute to maximising product yield. One such versatile flow chemistry platform is the coiled tube reactor subjected to oscillatory motion, producing excellent plug flow qualities equivalent to well-mixed tanks-in-series ‘N’. In this study, we discover the critical features of these flows that result in high plug flow performance using a data-driven approach. This is done by integrating Bayesian optimisation, a surrogate model approach, with Computational fluid dynamics that we treat as a black-box function to explore the parameter space of the operating conditions, oscillation amplitude and frequency, and net flow rate. Here, we correlate the flow characteristics as a function of the dimensionless Strouhal, oscillatory Dean, and Reynolds numbers to the reactor plug flow performance value ‘N’. Under conditions of optimal performance (specific examples are provided herein), the oscillatory flow is just sufficient to limit axial dispersion through flow reversal and redirection, and to promote Dean vortices. This automated, open-source, integrated method can be easily adapted to identify the flow characteristics that produce an optimised performance for other chemical reactors and processes.

Journal article

Traverso T, Abadie T, Matar OK, Magri Let al., 2023, Data-driven modeling for drop size distributions, Physical Review Fluids, Vol: 8

The prediction of the drop size distribution (DSD) resulting from liquid atomization is key to the optimization of multiphase flows from gas-turbine propulsion through agriculture to healthcare. Obtaining high-fidelity data of liquid atomization, either experimentally or numerically, is expensive, which makes the exploration of the design space difficult. First, to tackle these challenges, we propose a framework to predict the DSD of a liquid spray based on data as a function of the spray angle, the Reynolds number, and the Weber number. Second, to guide the design of liquid atomizers, the model accurately predicts the volume of fluid contained in drops of specific sizes while providing uncertainty estimation. To do so, we propose a Gaussian process regression (GPR) model, which infers the DSD and its uncertainty form the knowledge of its integrals and of its first moment, i.e., the mean drop diameter. Third, we deploy multiple GPR models to estimate these quantities at arbitrary points of the design space from data obtained from a large number of numerical simulations of a flat fan spray. The kernel used for reconstructing the DSD incorporates prior physical knowledge, which enables the prediction of sharply peaked and heavy-tailed distributions. Fourth, we compare our method with a benchmark approach, which estimates the DSD by interpolating the frequency polygon of the binned drops with a GPR. We show that our integral approach is significantly more accurate, especially in the tail of the distribution (i.e., large, rare drops), and it reduces the bias of the density estimator by up to 10 times. Finally, we discuss physical aspects of the model's predictions and interpret them against experimental results from the literature. This work opens opportunities for modeling drop size distribution in multiphase flows from data.

Journal article

Liang F, Kahouadji L, Valdes JP, Shin S, Chergui J, Juric D, Matar OKet al., 2023, Numerical simulation of surfactant-laden emulsion formation in an un-baffled stirred vessel, CHEMICAL ENGINEERING JOURNAL, Vol: 472, ISSN: 1385-8947

Journal article

Hue KY, Lew JH, Myo Thant MM, Matar O, Luckham P, Muller Eet al., 2023, Molecular dynamics simulation of polyacrylamide adsorption on calcite, Molecules, Vol: 28, Pages: 1-17, ISSN: 1420-3049

In poorly consolidated carbonate rock reservoirs, solids production risk, which can lead to increased environmental waste, can be mitigated by injecting formation-strengthening chemicals. Classical atomistic molecular dynamics (MD) simulation is employed to model the interaction of polyacrylamide-based polymer additives with a calcite structure, which is the main component of carbonate formations. Amongst the possible calcite crystal planes employed as surrogates of reservoir rocks, the (1 0 4) plane is shown to be the most suitable surrogate for assessing the interactions with chemicals due to its stability and more realistic representation of carbonate structure. The molecular conformation and binding energies of pure polyacrylamide (PAM), hydrolysed polyacrylamide in neutral form (HPAM), hydrolysed polyacrylamide with 33% charge density (HPAM 33%) and sulfonated polyacrylamide with 33% charge density (SPAM 33%) are assessed to determine the adsorption characteristics onto calcite surfaces. An adsorption-free energy analysis, using an enhanced umbrella sampling method, is applied to evaluate the chemical adsorption performance. The interaction energy analysis shows that the polyacrylamide-based polymers display favourable interactions with the calcite structure. This is attributed to the electrostatic attraction between the amide and carboxyl functional groups with the calcite. Simulations confirm that HPAM33% has a lower free energy than other polymers, presumably due to the presence of the acrylate monomer in ionised form. The superior chemical adsorption performance of HPAM33% agrees with Atomic Force Microscopy experiments reported herein.

Journal article

Zhu K, Cheng S, Kovalchuk N, Simmons M, Guo Y-K, Matar OK, Arcucci Ret al., 2023, Analyzing drop coalescence in microfluidic devices with a deep learning generative model, Physical Chemistry Chemical Physics, Vol: 25, Pages: 15744-15755, ISSN: 1463-9076

Predicting drop coalescence based on process parameters is crucial for experimental design in chemical engineering. However, predictive models can suffer from the lack of training data and more importantly, the label imbalance problem. In this study, we propose the use of deep learning generative models to tackle this bottleneck by training the predictive models using generated synthetic data. A novel generative model, named double space conditional variational autoencoder (DSCVAE) is developed for labelled tabular data. By introducing label constraints in both the latent and the original space, DSCVAE is capable of generating consistent and realistic samples compared to the standard conditional variational autoencoder (CVAE). Two predictive models, namely random forest and gradient boosting classifiers, are enhanced on synthetic data and their performances are evaluated based on real experimental data. Numerical results show that a considerable improvement in prediction accuracy can be achieved by using synthetic data and the proposed DSCVAE clearly outperforms the standard CVAE. This research clearly provides more insights into handling imbalanced data for classification problems, especially in chemical engineering.

Journal article

Constante-Amores CR, Kahouadji L, Shin S, Chergui J, Juric D, Castrejón-Pita JR, Matar OK, Castrejón-Pita AAet al., 2023, Impact of droplets onto surfactant-laden thin liquid films, Journal of Fluid Mechanics, Vol: 961, ISSN: 0022-1120

We study the effect of insoluble surfactants on the impact of surfactant-free droplets onto surfactant-laden thin liquid films via a fully three-dimensional direct numerical simulation approach that employs a hybrid interface-tracking/level-set method, and by taking into account surfactant-induced Marangoni stresses due to gradients in interfacial surfactant concentration. Our numerical predictions for the temporal evolution of the surfactant-free crown are validated against the experimental work by Che & Matar (Langmuir, vol. 33, 2017, pp. 12140–12148). We focus on the ‘crown-splash regime’, and we observe that the crown dynamics evolves through various stages: from the growth of linear modes (through a Rayleigh–Plateau instability) to the development of nonlinearities leading to primary and secondary breakup events (through droplet shedding modulated by an end-pinching mechanism). We show that the addition of surfactants does not affect the wave selection via the Rayleigh–Plateau instability. However, the presence of surfactants plays a key role in the late stages of the dynamics as soon as the ligaments are driven out from the rim. Surfactant-induced Marangoni stresses delay the end-pinching mechanisms to result in longer ligaments prior to their capillary singularity. Our results indicate that Marangoni stresses bridge the gap between adjacent protrusions promoting the adjacent protrusions' collision and the merging of ligaments. Finally, we demonstrate that the addition of surfactants leads to surface rigidification and consequently to the retardation of the flow dynamics.

Journal article

Kalli M, Pico P, Chagot L, Kahouadji L, Shin S, Chergui J, Juric D, Matar OK, Angeli Pet al., 2023, Effect of surfactants during drop formation in a microfluidic channel: a combined experimental and computational fluid dynamics approach, Journal of Fluid Mechanics, Vol: 961, Pages: 1-25, ISSN: 0022-1120

The effect of surfactants on the flow characteristics during rapid drop formation in a microchannel is investigated using high-speed imaging, micro-particle image velocimetry and numerical simulations; the latter are performed using a three- dimensional multiphase solver that accounts for the transport of soluble surfactants in the bulk and at the interface. Drops are generated in a flow-focusing microchannel, using silicone oil ( 4.6 mPa s) as the continuous phase and a 52 % w/w glycerol solution as the dispersed phase. A non-ionic surfactant (Triton X-100) is dissolved in the dispersed phase at concentrations below and above the critical micelle concentration. Good agreement is found between experimental and numerical data for the drop size, drop formation time and circulation patterns. The results reveal strong circulation patterns in the forming drop in the absence of surfactants, whose intensity decreases with increasing surfactant concentration. The surfactant concentration profiles in the bulk and at the interface are shown for all stages of drop formation. The surfactant interfacial concentration is large at the front and the back of the forming drop, while the neck region is almost surfactant free. Marangoni stresses develop away from the neck, contributing to changes in the velocity profile inside the drop.

Journal article

Cooper J, Bird M, Acha S, Amrit P, Chachuat B, Shah N, Matar Oet al., 2023, The Carbon Footprint of a UK Chemical Engineering Department – The Case of Imperial College London, The 30th CIRP Life Cycle Engineering Conference, Publisher: Elsevier, Pages: 444-449, ISSN: 2212-8271

As the UK strives towards net-zero it is important that all sectors, including Higher Education, take immediate measures to cut their greenhouse gas emissions. The greenhouse gases emitted by different Higher Education institutions are studied and are shown to be large. However, these studies are based on aggregated data, and it is therefore uncertain how effective institute-wide policies to cut emissions are at department level. Herein, we present a generic framework for university departments to calculate their carbon footprint considering Scope 1, 2 and 3 emissions. We estimate the carbon footprint of the Chemical Engineering Department at Imperial College London to be 7,620 and 8,330 tCO2eq in 2018/19 and 2019/20, respectively. Scope 3 emissions account for 54% of the Department's emissions with Scope 1 and 2 accounting for the remaining 46%. Scope 3 emissions are largely driven by purchased goods and travel, while Scope 1 emissions are predominantly from electricity usage.

Conference paper

Valdes JP, Kahouadji L, Liang F, Shin S, Chergui J, Juric D, Matar OKet al., 2023, Direct numerical simulations of liquid–liquid dispersions in a SMX mixer under different inlet conditions, Chemical Engineering Journal, Vol: 462, Pages: 1-18, ISSN: 1385-8947

The internal dynamics of static mixers handling liquid–liquid flows have been comprehensively explored over the past decade. Although the effect of the inlet configuration is often overlooked, a few studies have suggested a relationship between the phases’ initial set-up and the performance of the mixer in terms of the droplet size distribution (DSD). Accordingly, different dispersed phase morphologies at the inlet of a SMX static mixer have been tested and their effect on the overall dispersion performance of the mixer has been evaluated based on the DSD and growth of interfacial area. In particular, three representative scenarios are considered: (1) Isolated cases, where one and three individual droplets are injected, mimicking a controlled syringe injection; (2) Numerous variable-sized droplets, simulating a pre-mixed/dispersed inlet; and (3) Jet inlet, emulating a standard phase injection from a gear pump. In addition, this study provides novel insight into the underlying physics dictating droplet deformation and breakage in SMX mixers for industrially-relevant scenarios. This can be achieved thanks to the massively-parallel high-fidelity three-dimensional direct numerical simulations computed with a robust hybrid front-tracking/level-set algorithm, which provides a wealth of information on intricate interfacial dynamics; this information cannot be obtained via experimental or volume-averaged modelling techniques implemented in past studies.

Journal article

Chen J, Anastasiou C, Cheng S, Basha NM, Kahouadji L, Arcucci R, Angeli P, Matar OKet al., 2023, Computational fluid dynamics simulations of phase separation in dispersed oil-water pipe flows, Chemical Engineering Science, Vol: 267, Pages: 1-18, ISSN: 0009-2509

The separation of liquid–liquid dispersions in horizontal pipes is common in many industrial sectors. It remains challenging, however, to predict the separation characteristics of the flow evolution due to the complex flow mechanisms. In this work, Computational Fluid Dynamics (CFD) simulations of the silicone oil and water two-phase flow in a horizontal pipe are performed. Several cases are explored with different mixture velocities and oil fractions (15%-60%). OpenFOAM (version 8.0) is used to perform Eulerian-Eulerian simulations coupled with population balance models. The ‘blending factor’ in the multiphaseEulerFoam solver captures the retardation of the droplet rising and coalescing due to the complex flow behaviour in the dense packed layer (DPL). The blending treatment provides a feasible compensation mechanism for the mesoscale uncertainties of droplet flow and coalescence through the DPL and its adjacent layers. In addition, the influence of the turbulent dispersion force is also investigated, which can improve the prediction of the radial distribution of concentrations but worsen the separation characteristics along the flow direction. Although the simulated concentration distribution and layer heights agree with the experiments only qualitatively, this work demonstrates how improvements in drag and coalescence modelling can be made to enhance the prediction accuracy.

Journal article

Constante-Amores CR, Abadie T, Kahouadji L, Shin S, Chergui J, Juric D, Castrejon-Pita AA, Matar OKet al., 2023, Direct numerical simulations of turbulent jets: vortex-interface-surfactant interactions, Journal of Fluid Mechanics, Vol: 955, Pages: 1-25, ISSN: 0022-1120

We study the effect of insoluble surfactants on the spatio-temporal evolution of turbulent jets. We use three-dimensional numerical simulations and employ an interface-tracking/level-set method that accounts for surfactant-induced Marangoni stresses. The present study builds on our previous work (Constante-Amores et al., J. Fluid Mech., vol. 922, 2021, A6) in which we examined in detail the vortex–surface interaction in the absence of surfactants. Numerical solutions are obtained for a wide range of Weber and elasticity numbers in which vorticity production is generated by surface deformation and surfactant-induced Marangoni stresses. The present work demonstrates, for the first time, the crucial role of Marangoni stresses, brought about by surfactant concentration gradients, in the formation of coherent, hairpin-like vortex structures. These structures have a profound influence on the development of the three-dimensional interfacial dynamics. We also present theoretical expressions for the mechanisms that influence the rate of production of circulation in the presence of surfactants for a general, three-dimensional, two-phase flow, and highlight the dominant contribution of surfactant-induced Marangoni stresses.

Journal article

Panda D, Kahouadji L, Tuckerman LS, Shin S, Chergui J, Juric D, Matar OKet al., 2023, Axisymmetric and azimuthal waves on a vibrated sessile drop, Physical Review Fluids, Vol: 8

This paper is associated with a poster winner of a 2022 American Physical Society's Division of Fluid Dynamics (DFD) Gallery of Fluid Motion Award for work presented at the DFD Gallery of Fluid Motion. The original poster is available online at the Gallery of Fluid Motion, https://doi.org/10.1103/APS.DFD.2022.GFM.P0027

Journal article

Cheng S, Chen J, Anastasiou C, Angeli P, Matar OKK, Guo Y-K, Pain CCC, Arcucci Ret al., 2023, Generalised latent assimilation in heterogeneous reduced spaces with machine learning surrogate models, Journal of Scientific Computing, Vol: 94, Pages: 1-37, ISSN: 0885-7474

Reduced-order modelling and low-dimensional surrogate models generated using machine learning algorithms have been widely applied in high-dimensional dynamical systems to improve the algorithmic efficiency. In this paper, we develop a system which combines reduced-order surrogate models with a novel data assimilation (DA) technique used to incorporate real-time observations from different physical spaces. We make use of local smooth surrogate functions which link the space of encoded system variables and the one of current observations to perform variational DA with a low computational cost. The new system, named generalised latent assimilation can benefit both the efficiency provided by the reduced-order modelling and the accuracy of data assimilation. A theoretical analysis of the difference between surrogate and original assimilation cost function is also provided in this paper where an upper bound, depending on the size of the local training set, is given. The new approach is tested on a high-dimensional (CFD) application of a two-phase liquid flow with non-linear observation operators that current Latent Assimilation methods can not handle. Numerical results demonstrate that the proposed assimilation approach can significantly improve the reconstruction and prediction accuracy of the deep learning surrogate model which is nearly 1000 times faster than the CFD simulation.

Journal article

Savage T, Basha N, Matar OK, del Rio Chanona Aet al., 2023, Multi-fidelity Bayesian Optimisation of Reactor Simulations using Deep Gaussian Processes, Computer Aided Chemical Engineering, Pages: 511-517

Coiled tube reactors under pulsed-flow conditions have been shown to provide promising mixing characteristics. In order to validate performance in an industrial setting, and investigate the underlying physics of successful mixing, coiled tube reactors must be optimised. In this work, we apply a novel framework to locate optimal solutions to this nonlinear, computationally expensive, and derivative-free problem. Our optimisation framework takes advantage of deep Gaussian processes to learn a multi-fidelity surrogate model. We apply this model within a novel Bayesian optimisation algorithm, using faster, less accurate, and potentially biased lower-fidelity simulations to enable faster reactor optimisation. We subsequently investigate the physical insights into the swirling flows of these optimal configurations, directly informing the design of future coiled-tube reactors under pulsed-flow conditions. We demonstrate our design framework to be extensible to a broad variety of expensive simulation-based optimisation problems, supporting the design of the next-generation of highly parameterised chemical reactors.

Book chapter

Liang F, Kahouadji L, Valdes JP, Shin S, Chergui J, Juric D, Matar OKet al., 2022, Numerical study of oil–water emulsion formation in stirred vessels: effect of impeller speed, Flow: Applications of Fluid Mechanics, Vol: 2, Pages: 1-19, ISSN: 2633-4259

The mixing of immiscible oil and water by a pitched blade turbine in a cylindrical vessel is studied numerically. Three-dimensional simulations combined with a hybrid front-tracking/level-set method are employed to capture the complex flow and interfacial dynamics. A large eddy simulation approach, with a Lilly–Smagorinsky model, is employed to simulate the turbulent two-phase dynamics at large Reynolds numbers Re=1802−18 026 . The numerical predictions are validated against previous experimental work involving single-drop breakup in a stirred vessel. For small Re , the interface is deformed but does not reach the impeller hub, assuming instead the shape of a Newton's Bucket. As the rotating speed increases, the deforming interface attaches to the impeller hub which leads to the formation of long ligaments that subsequently break up into small droplets. For the largest Re studied, the system dynamics becomes extremely complex wherein the creation of ligaments, their breakup and the coalescence of drops occur simultaneously. The simulation outcomes are presented in terms of spatio-temporal evolution of the interface shape and vortical structures. The results of a drop size analysis in terms of the evolution of the number of drops, and their size distribution, is also presented as a parametric function of Re .

Journal article

Kahouadji L, Liang F, Valdes JP, Shin S, Chergui J, Juric D, Craster RV, Matar OKet al., 2022, The transition to aeration in turbulent two-phase mixing in stirred vessels, Flow, Turbulence and Combustion, Vol: 2, Pages: 1-20, ISSN: 0003-6994

We consider the mixing dynamics of an air–liquid system driven by the rotation of a pitched blade turbine (PBT) inside an open, cylindrical tank. To examine the flow and interfacial dynamics, we use a highly parallelised implementation of a hybrid front-tracking/level-set method that employs a domain-decomposition parallelisation strategy. Our numerical technique is designed to capture faithfully complex interfacial deformation, and changes of topology, including interface rupture and dispersed phase coalescence. As shown via transient, a three-dimensional (3-D) LES (large eddy simulation) using a Smagorinsky–Lilly turbulence model, the impeller induces the formation of primary vortices that arise in many idealised rotating flows as well as several secondary vortical structures resembling Kelvin–Helmholtz, vortex breakdown, blade tip vortices and end-wall corner vortices. As the rotation rate increases, a transition to ‘aeration’ is observed when the interface reaches the rotating blades leading to the entrainment of air bubbles into the viscous fluid and the creation of a bubbly, rotating, free surface flow. The mechanisms underlying the aeration transition are probed as are the routes leading to it, which are shown to exhibit a strong dependence on flow history.

Journal article

Chagot L, Quilodran-Casas C, Kalli M, Kovalchuk NM, Simmons MJH, Matar OK, Arcucci R, Angeli Pet al., 2022, Surfactant-laden droplet size prediction in a flow-focusing microchannel: a data-driven approach, LAB ON A CHIP, Vol: 22, Pages: 3848-3859, ISSN: 1473-0197

Journal article

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