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A saturation–capillary pressure relationship is proposed that is applicable for all wettabilities, including mixed-wet and oil-wet or hydrophobic media. This formulation is more flexible than existing correlations that only match water-wet data, while also allowing saturation to be written as a closed-form function of capillary pressure: we can determine capillary pressure explicitly from saturation, and vice versa. We propose $$P_{{\text{c}}} = A + B\tan \left( {\frac{\pi }{2} - \pi S_{e}^{C} } \right)\,{\text{for}}\,0 \le S_{{\text{e}}} \le 1,$$ P c = A + B tan π 2 - π S e C for 0 ≤ S e ≤ 1 , where $$S_{{\text{e}}}$$ S e is the normalized saturation. A indicates the wettability: $$A>0$$ A > 0 is a water-wet medium, $$A A < 0 is hydrophobic while small A suggests mixed wettability. B represents the average curvature and pore-size distribution which can be much lower in mixed-wet compared to water-wet media with the same pore structure if the menisci are approximately minimal surfaces. C is an exponent that controls the inflection point in the capillary pressure and the asymptotic behaviour near end points. We match the model accurately to 29 datasets in the literature for water-wet, mixed-wet and hydrophobic media, including rocks, soils, bead and sand packs and fibrous materials with over four orders of magnitude difference in permeability and porosities from 20% to nearly 90%. We apply Leverett J-function scaling to make the expression for capillary pressure dimensionless and discuss the behaviour of analytical solutions for spontaneous imbibition.

We report the results of modelling the transport of n-octane and n-hexadecane and their mixtures through carbonaceous nanopores at high-pressure conditions. Pores are modelled as smooth slit sheets with perturbations added as ridges and steps and a version of the Statistical Associating Fluid Theory (SAFT-γ Mie) is used both as equation of state and as a coarse-grained force field to account for fluid-fluid and fluid-solid molecular interactions. Molecular simulation allowed the description of transport diffusivities in terms of molecular flow, using boundary driven non-equilibrium molecular dynamics (BD-NEMD). Transport diffusivities are also independently calculated using equilibrium and external force non-equilibrium molecular dynamics (EF-NEMD) simulations, after accounting for the adsorption on the pores. We show consistency between the approaches for quantifying transport in terms of permeabilities (Darcy flows) and transport diffusivities. We find that smooth slit carbon pore models, which are commonly employed in literature as surrogates for kerogen regions in shale, are an inadequate representation of ultra-confined natural pores. For slit pores, the flow patterns are characterized by a fully-mutualized plug-like flow and fast transport. However, by incorporating even a small amount of rugosity (roughness) to the solid walls, the diffusion coefficients decrease dramatically with surface roughness significantly affecting the characteristic transport and velocity profiles inside the pores. In all cases, it is seen that there are important cross-correlation effects, influencing the way components of the mixture flow together. Calculated self-diffusivities are orders of magnitude smaller than the observed transport diffusivities for liquid mixtures. This work has a direct impact on the understanding and modelling of unconventional hydrocarbon recovery and flow in organic shale rocks.

The thermal runaway of Lithium-ion batteries (LIBs) is a fire hazard. The Accelerating Rate Calorimetry (ARC) device is commonly used to investigate thermal runaway parameters of LIBs by assuming adiabatic conditions. However, this assumption ignores internal heat transfer within the cell and external heat transfer at the cell surface. In this work, we conducted ARC experiments using prismatic LiCoO2 cells of 50 mm in side to study the effect of heat transfer limitations. Results show that the external temperature difference between this cell surface and ARC walls varies between 0 and 1.5 ℃ before thermal runaway and increases from 10 to 130 ℃ while thermal runaway occurs. Ignoring external heat transfer causes the heat of reaction of the cell to be underestimated by 12%. To study the internal heat transfer, two models are developed and show that heat transfer causes an internal temperature difference that causes an error of kinetics estimation, and the error grows with cell size. Ignoring heat transfer leads to errors on the thermal runaway parameters quantified by ARC, and these errors could propagate to battery safety design and predictions. This study contributes to designing better ARC experiments and a better understanding of battery safety.

We have carried out the traditional analysis of a set of dynamic breakthrough experiments on the $$\hbox {CO}_2$$ CO 2 /He system adsorbing onto activated carbon by fitting a 1D dynamic column breakthrough model to the transient experimental profiles. We have quantified the uncertainties in the fitted model parameters using the techniques of Bayesian inference, and have propagated these parametric uncertainties through the dynamic model to assess the robustness of the modelling. We have found significant uncertainties in the outlet mole fraction profile, internal temperature profile and internal adsorption profiles of approximately $$\pm 15\%$$ ± 15 % . To assess routes to reduce these uncertainties we have applied a global variance-based sensitivity analysis to the dynamic model using the Sobol method. We have found that approximately $$70\%$$ 70 % of the observed variability in the modelling outputs can be attributed to uncertainties in the adsorption isotherm parameters that describe its temperature dependence. We also make various recommendations for practitioners, using the developed Bayesian statistical tools, regarding the choice of the isotherm model, the choice of the fitting data for the extraction of system specific parameters and the simplification of the wall energy balance.

Abstract Flow of complex fluids in porous structures is pertinent in many biological and industrial processes. For these applications, elastic turbulence, a viscoelastic instability occurring at low Re—arising from a non-trivial coupling of fluid rheology and flow geometry—is a common and relevant effect because of significant over-proportional increase in pressure drop and spatio-temporal distortion of the flow field. Therefore, significant efforts have been made to predict the onset of elastic turbulence in flow geometries with constrictions. The onset of flow perturbations to fluid streamlines is not adequately captured by Deborah and Weissenberg numbers. The introduction of more complex dimensionless numbers such as the M-criterion, which was meant as a simple and pragmatic method to predict the onset of elastic instabilities as an order-of-magnitude estimate, has been successful for simpler geometries. However, for more complex geometries which are encountered in many relevant applications, sometimes discrepancies between experimental observation and M-criteria prediction have been encountered. So far these discrepancies have been mainly attributed to the emergence from disorder. In this experimental study, we employ a single channel with multiple constrictions at varying distance and aspect ratios. We show that adjacent constrictions can interact via non-laminar flow field instabilities caused by a combination of individual geometry and viscoelastic rheology depending (besides other factors) explicitly on the distance between adjacent constrictions. This provides intuitive insight on a more conceptual level why the M-criteria predictions are not more precise. Our findings suggest that coupling of rheological effects and fluid geometry is more complex and implicit and controlled by more length scales than are currently employed. For translating bulk fluid, rheology determined by classical rheometry into the effective behaviour in complex porous geometries requires consideration of more than only one repeat element. Our findings open the path towards more accurate prediction of the onset of elastic turbulence, which many applications will benefit. Article Highlights We demonstrate that adjacent constrictions “interact” via the non-laminar flow fields caused by individual constrictions, implying that the coupling of rheological effects and fluid geometry is more complex and implicit. The concept of characterizing fluid rheology independent of flow geometry and later coupling back to the geometry of interest via dimensionless numbers may fall short of relevant length scales, such as the separation of constrictions which control the overlap of flow fields. By providing direct experimental evidence illustrating the cause of the shortcoming of the status-quo, the expected impact of this work is to challenge and augment existing concepts that will ultimately lead to the correct prediction of the onset of elastic turbulence.

Excess adsorption of CO2, CH4, N2, and H2 on ZIF-8 was measured gravimetrically in the pressure range ranging from vacuum to 30 MPa at 298.15, 313.15, 333.15, 353.15, and 394.15 K using a magnetic suspension balance. The textural properties of the adsorbent material─i.e., skeletal density, surface area, pore volume, and pore-size distribution─were estimated by helium gravimetry and N2 (77 K) physisorption. The adsorption isotherms were fitted with the Sips isotherm model and the virial equation, and the values of isosteric heat of adsorption and Henry constants for the gases were determined using the latter.

Understanding the evolution of solute concentration gradients underpins the prediction of porous media processes limited by mass transfer. Here, we present the development of a mathematical model that describes the dissolution of spherical bubbles in two-dimensional regular pore networks. The model is solved numerically for lattices with up to 169 bubbles by evaluating the role of pore network connectivity, vacant lattice sites and the initial bubble size distribution. In dense lattices, diffusive shielding prolongs the average dissolution time of the lattice, and the strength of the phenomenon depends on the network connectivity. The extension of the final dissolution time relative to the unbounded (bulk) case follows the power-law function, $${B^k/\ell }$$ B k / ℓ , where the constant $$\ell$$ ℓ is the inter-bubble spacing, B is the number of bubbles, and the exponent k depends on the network connectivity. The solute concentration field is both the consequence and a factor affecting bubble dissolution or growth. The geometry of the pore network perturbs the inward propagation of the dissolution front and can generate vacant sites within the bubble lattice. This effect is enhanced by increasing the lattice size and decreasing the network connectivity, yielding strongly nonuniform solute concentration fields. Sparse bubble lattices experience decreased collective effects, but they feature a more complex evolution, because the solute concentration field is nonuniform from the outset.

Advantages of ionic liquids (ILs) over volatile organic solvents in chemical processes include no or negligible evaporative losses and high tunability. However, the conventional production of aprotic ILs via metathesis can be unattractive (both economically and environmentally) because of its high complexity, while the performance of other synthesis routes remains unclear. Existing life-cycle assessments furthermore fail to combine the production and use phases of these solvents, leading to erroneous conclusion about their sustainability credentials. This paper compares a one-pot, halide-free production route to 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM][BF4] against metathesis and two conventional fuel desulfurization solvents, namely, acetonitrile and dimethylformamide (DMF). Halide-free synthesis is predicted to reduce the cost and environmental impacts associated with the production of [BMIM][BF4] by 2–5-fold compared to metathesis. Upon including the use phase of the solvents in fuel desulfurization and accounting for the uncertainty in background data, halide-free [BMIM][BF4] consistently presents the lowest cost and environmental impacts, while DMF is the worst in class. As well as exemplifying the importance of synthesis routes of ILs on their sustainability, these results highlight the need to include the use phase of solvents for more comprehensive life-cycle assessments.

This study investigated the important role of agitation in obtaining consistent and reproducible results when moving from preliminary qualitative screenings for protein crystallisation to quantitative batch crystallisation experiments. Lysozyme-thaumatin binary protein mixture was used as the model protein system in this study. Poor reproducibility between batches were observed for non-agitated crystallisation conditions even if the same sampling timing and frequency applied. With agitation, from 0 to 200 rpm investigated in this study, improved reproducibility of protein crystallisation was observed with increased agitation. Additionally, agitation also had impacts on supersaturation exhaustion rate, yield and crystal size. Moreover, in agitated batch crystallisation, it was found that target protein crystallisation process was decelerated in the presence of protein impurity. In conclusion, we emphasised the essential role of agitation in protein crystallisation experiments else misleading conclusions with inconsistency might be drawn from non-agitated systems.

Low salinity water flooding is a promising enhanced oil recovery technique that has been observed, in experiments over a range of scales, to increase oil production by up to 14% in some systems. However, there is still no way of reliably predicting which systems will respond favourably to the technique. This shortcoming is partly because of a relative lack of pore scale observations of low salinity water flooding. This has led to a poor understanding of how mechanisms on the scale of micrometres lead to changes in fluid distribution on the scale of centimetres to reservoir scales. In this work, we use X-ray micro-CT scanning to image unsteady state experiments of tertiary low salinity water flooding in Berea, Castlegate, and Bunter sandstone micro-cores. We observe fluid saturations and characterise the wetting state of samples using imagery of fluid–solid fractional wetting and pore occupancy analysis. In the Berea sample, we observed an additional oil recovery of 3 percentage points during low salinity water flooding, with large volumes of oil displaced from small pores but also re-trapping of mobilised oil in large pores. In the Bunter sandstone, we observed 4 percentage point additional recovery with significant displacement of oil from small pores and no significant retrapping of oil in large pores. However, in the Castlegate sample, we observed just 1 percentage point of additional recovery and relatively small volumes of oil mobilisation. We observe a significant wettability alteration towards more water-wet conditions in the Berea and Bunter sandstones, but no significant alteration in the Castlegate sample. We hypothesise that pore structure, specifically the topology of large pores impacted recovery. We find that poor connectivity of the largest pores in each sample is strongly correlated to additional recovery. This work is the first systematic comparison of the pore scale response to low salinity flooding across multiple sandstone samples. Moreover, it gives the first pore scale insights into the role of pore geometry and topology on the mobilisation of oil during low salinity water flooding.

Despite the large quantity of works dedicated to the analysis and modelling of deposition in single-phase flows, very few models have been proposed for deposition of solids in two-phase pipe flows of gas and liquid. A comprehensive mechanistic model for transient, multiphase pipe flow with phase change is proposed, which takes into account effects of deposition by mass diffusion, ageing, and shearing of the deposit layer. Validation is performed with an exhaustive database of experimental data from the literature, for steady and transient flows without deposition, and deposit thickness measurements for single-phase, slug and stratified flows. Most of the predictions are within a 20% error band from the experimental data, with slightly worse performance in the case of deposition in slug flows. A surrogate model is also developed based on active-learning sampling of the simulator results, demonstrating a technique that could be used for optimization or design of engineering devices.

Gas adsorption at high pressures in porous solids is commonly quantified in terms of the excess amount adsorbed. Despite the wide spectrum of adsorbent morphologies available, the analysis of excess adsorption isotherms has mostly focused on microporous materials and the role of mesoporosity remains largely unexplored. Here, we present supercritical CO2 adsorption isotherms measured at $$T=308$$ T = 308 K in the pressure range $$p=0.02{-}21$$ p = 0.02 - 21 MPa on three adsorbents with distinct fractions of microporosity, $$\phi_2$$ ϕ 2 , namely a microporous metal-organic framework ($$\phi_2=70$$ ϕ 2 = 70 %), a micro-mesoporous zeolite ($$\phi_2=38$$ ϕ 2 = 38 %) and a mesoporous carbon ($$\phi_2 ϕ 2 < 0.1 %). The results are compared systematically in terms of excess and net adsorption relative to two distinct reference states–the space filled with gas in the presence/absence of adsorbent–that are defined from two separate experiments using helium as the probing gas. We discuss the inherent difficulties in extracting from the supercritical adsorption isotherms quantitative information on the properties of the adsorbed phase (its density or volume), because of the nonuniform distribution of the latter within and across the different classes of pore sizes. Yet, the data clearly reveal pore-size dependent adsorption behaviour, which can be used to identify characteristic types of isotherm and to complement the information obtained using the more traditional textural analysis by physisorption.

Abstract Most analyses of fluid flow in porous media are conducted under the assumption that the permeability is constant. In some “stress-sensitive” rock formations, however, the variation of permeability with pore fluid pressure is sufficiently large that it needs to be accounted for in the analysis. Accounting for the variation of permeability with pore pressure renders the pressure diffusion equation nonlinear and not amenable to exact analytical solutions. In this paper, the regular perturbation approach is used to develop an approximate solution to the problem of flow to a linear constant-pressure boundary, in a formation whose permeability varies exponentially with pore pressure. The perturbation parameter αD is defined to be the natural logarithm of the ratio of the initial permeability to the permeability at the outflow boundary. The zeroth-order and first-order perturbation solutions are computed, from which the flux at the outflow boundary is found. An effective permeability is then determined such that, when inserted into the analytical solution for the mathematically linear problem, it yields a flux that is exact to at least first order in αD. When compared to numerical solutions of the problem, the result has 5% accuracy out to values of αD of about 2—a much larger range of accuracy than is usually achieved in similar problems. Finally, an explanation is given of why the change of variables proposed by Kikani and Pedrosa, which leads to highly accurate zeroth-order perturbation solutions in radial flow problems, does not yield an accurate result for one-dimensional flow. Article Highlights Approximate solution for flow to a constant-pressure boundary in a porous medium whose permeability varies exponentially with pressure. The predicted flowrate is accurate to within 5% for a wide range of permeability variations. If permeability at boundary is 30% less than initial permeability, flowrate will be 10% less than predicted by constant-permeability model.

Soot formation in combustors is a complex process comprising highly intermittent interactions between physical and chemical processes across a wide range of time-scales and the influence of turbulence on the soot inception process remains substantially conjectural. The current study quantifies the impact of flame temperature, equivalence ratio, and strain rate on PAH concentrations in premixed turbulent ethylene flames crossing the soot inception limit using a back–to–burnt opposed jet configuration that provides accurate control of flow parameters. The upper nozzle features fractal grid generated turbulence and provides premixed ethylene/air mixtures with equivalence ratios 1.7 ≤ ϕ ≤ 2.2 with flames stabilised against well-defined lower nozzle hot combustion products (HCP) from N2 diluted H2 flames. The flame structures are initially analysed using PAH/CH2O/PLIF and elastic light scattering with gas chromatography–mass spectrometry (GC–MS) subsequently used to quantify PAH samples from inside the turbulent flame brush. A combination of hot nitrogen dilution and a heated sampling line is used to minimise PAH and particle losses during sample extraction. The work quantifies the growth in PAH concentrations across the soot inception limit and shows that the rate of strain exerts a dominant influence. It is further shown, through centrifuging of samples, that soot particles contain large amounts of PAHs (e.g. benzo[a]pyrene) with EDX used to quantify the growth in carbon deposition.

With the emergence of stretchable/wearable devices, functions, such as sensing, energy storage/harvesting, and electrical conduction, should ideally be carried out by a single material, while retaining its ability to withstand large elastic deformations, to create compact, functionally-integrated and autonomous systems. A new class of trimodal, stretchable yarn-based transducer formed by coating commercially available Lycra® yarns with PEDOT:PSS is presented. The material developed can sense strain (first mode), and temperature (second mode) and can power itself thermoelectrically (third mode), eliminating the need for an external power-supply. The yarns were extensively characterized and obtained an ultrahigh (gauge factor ∼3.6 × 105, at 10–20% strain) and tunable (up to about 2 orders of magnitude) strain sensitivity together with a very high strain-at-break point (up to ∼1000%). These PEDOT:PSS-Lycra yarns also exhibited stable thermoelectric behavior (Seebeck coefficient of 15 μV K−1), which was exploited both for temperature sensing and self-powering (∼0.5 μW, for a 10-couple module at ΔT ∼ 95 K). The produced material has potential to be interfaced with microcontroller-based systems to create internet-enabled, internet-of-things type devices in a variety of form factors.

The chemical engineering journal 446, 137104 (2022). doi:10.1016/j.cej.2022.137104, Adsorptive separation of propylene and propane, an important step of polypropylene production, is more energy-efficient than distillation. However, the challenge lies in the design of an adsorbent which exhibits both high selectivity and uptake. Herein, we hypothesise that enhancing the propylene affinity of the adsorption sites while keeping a suitable pore size can address this challenge. To do so, we performed silver exchange of a commercial zeolite Y, thereby making the adsorbent design easily scalable. We characterised the adsorbent using analytical, spectroscopic and imaging tools, tested its equilibrium and dynamic sorption properties using volumetric and gravimetric techniques and compared its performance to those of state-of-the-art adsorbents as well as other silver-functionalised adsorbents. The silver-exchanged zeolite Y (Ag-Y) exhibited one of the best selectivity vs uptake performances reported so far. Ag-Y also displayed fast adsorption kinetics and reversible propylene sorption, making it a promising new benchmark for propylene/propane separation. Synchrotron-based pair distribution function analyses identified the silver cations’ location which confirmed that the silver sites are easily accessible to the adsorbates. This aspect can, in part, explain the propylene/propane separation performance observed. The overall design strategy proposed here to enhance sorption site affinity and maintain pore size could be extended to other adsorbents and support the deployment of adsorption technology for propylene/propane separation., Published by Elsevier, Amsterdam

New approaches for enhanced oil recovery (EOR) with a reduced environmental footprint are required to improve recovery from mature oil fields, and when combined with carbon capture and storage (CCS) can provide useful options for resource maximisation during the net zero transition. Electrical heating is investigated as a potential EOR method in carbonate reservoirs. Samples were placed in an apparatus surrounded by a wire coil across which different DC (direct current) voltages were applied. Monitoring the imbibition of both deionized water (DW) and seawater (SW) into initially oil-wet Austin chalk showed that water imbibed into the rock faster when heated in the presence of a magnetic field. This was associated with a reduction in the water–air contact angle over time measured on the external surface of the sample. Without heating, the contact angle reduced from 127° approaching water-wet conditions, 90°, in 52 min, while in the presence of heating with 3 V, 6 V, and 9 V applied across a sample 17 mm in length, the time required to reach the same contact angle was only 47, 38 and 26 min, respectively, while a further reduction in contact angle was witnessed with SW. The ultimate recovery factor (RF) for an initially oil-wet sample imbibed by DW was 13% while by seawater (SW) the recorded RF was 26% in the presence of an electrical heating compared with 2.8% for DW and 11% for SW without heating. We propose heating as an effective way to improve oil recovery, enhancing capillary-driven natural water influx, and observe that renewable-powered heating for EOR with CCS may be one option to improve recovery from mature oil fields with low environmental footprint.

In unresolved flow CFD-DEM simulations, the porosity values for each CFD cell are determined using a coarse-graining algorithm. While this approach enables coupled simulations of representative numbers of particles, the influence of the porosity local to the particles on the fluid-particle interaction force is not captured. This contribution considers a two-grid coarse-graining method that determines a local porosity for each particle using a radical Voronoi tessellation of the system. A relatively fine, regular point cloud is used to map these local porosity data to the CFD cells. The method is evaluated using two different cases considering both disperse and tightly packed particles. The data show that the method conserves porosity data, is reasonably grid-independent and can generate a relatively smooth porosity field. The new method can more accurately predict the fluid-particle interactive force for polydisperse particle system than alternative methods that have been implemented in unresolved CFD-DEM codes., 22 pages, 21 figures. Article published in Powder Technology (see https://doi.org/10.1016/j.powtec.2021.02.025)

The creation of drag-reducing surfaces in deformed tubes is of vital importance to thermal management, energy, and environmental applications. However, it remains a great challenge to tailor the surface structure and wettability inside the deformed tubes of slim and complicated feature. Here, we describe an electrochemical anodization strategy to achieve uniform and superhydrophobic coating of TiO2 nanotube arrays throughout the inner surface in deformed/bend titanium tubes. Guided by a hybrid carbon fibre cathode, conformal electric field can be generated to adaptatively fit the complex geometries in the deformed tube, where the structural design with rigid insulating beads can self-stabilize the hybrid cathode at the coaxial position of the tube with the electrolyte flow. As a result, we obtain a superhydrophobic coating with a water contact angle of 157° and contact angle hysteresis of less than 10°. Substantial drag reduction can be realised with an overall reduction up to 25.8 % for the anodized U-shaped tube. Furthermore, we demonstrate to spatially coat tubes with complex geometries, to achieve energy-saving liquid transportation. This facile coating strategy has great implications in liquid transport processes with the user-friendly approach to engineer surface regardless of the deformation of tube/pipe.

Pyrolysis is a key process in all stages of wood burning from ignition to extinction. Understanding each stage is crucial to tackle wildfires and assess the fire safety of timber buildings. A model of appropriate complexity of wood pyrolysis and oxidation is missing, which limits the understanding of fires fuelled by wood. Progress towards this aim has been slow in recent years, as the role of chemical kinetics is still debated. Three predominant theories hypothesis that chemistry is either infinitely fast (de Ris), a function of char depth (Atreya), or a function of heat flux (Suuberg). This paper proposes a novel multi-scale model of wood pyrolysis and oxidation for predicting the charring of timber. The chemical kinetics sub-model was previously validated at the microscale (mg-samples). We favourably compare the complete model against a large range of mesoscale experiments (g-samples) found in the literature of different moisture contents (0–30%), heat fluxes (0–60 kW/m2), oxygen concentrations (0–21%), grain directions (parallel/perpendicular), and combinations thereof. The model was then used to calculate the transient Damkohler number of wood at different depths and heat fluxes. This analysis showed that chemistry and heat transfer are both important at all heat fluxes and stages of burning relevant to fire, which unifies the three theories by Suuberg, Atreya, and de Ris. We argue that the model is of currently appropriate complexity to predict the charring of timber. These findings improve our understanding of wood pyrolysis and the modelling of timber burning across scales.

The solvent‐dependent polymorphism of the active pharmaceutical ingredient (API) carbamazepine is interpreted from calculations of the solid‐state and API‐solvent intermolecular interactions. These simulations suggested that apolar solute‐solute interactions could be disrupted by apolar solvents. In contrast, the polar solute‐solute interactions were found to be easily disrupted by polar and protic solvents. This is consistent with experimental observations that the crystallization of the metastable form II is more dominant in apolar solvents. The Mercury program remains the gold standard in terms of usability; however, further expansion into more complex simulation techniques could make this package of even greater use in pharmaceutical manufacturing workflows.

Made available in DSpace on 2020-12-12T01:25:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-06-01 The use of protic ammonium ionic liquids (PILs) in the pretreatment of lignocellulosic biomass is a promising alternative to using expensive aprotic ionic liquids such as 1-ethyl-3-methylimidazolium acetate, [Emim][OAc]. In this work, the PIL monoethanolammonium acetate, [MEA][OAc], was used for the pretreatment of sugar cane bagasse. The study investigated changing the acid base ratio (ABR) from 0.1 to 10 and recycling of the solvent. We determined the lignin extraction, lignin recovery, solvent recovery, and enzymatic saccharification yield and compared the performance to that of the pure amine base, monoethanolamine. We found that lignin extraction and glucose release during enzymatic saccharification increased with base (amine) content, reaching up to 84% and 96%, respectively, after 72 h of saccharification for the 0.1 ABR. Up to 97% of the solvent was recovered for the 1.0 ABR. A higher acid content led to increased hemicellulose extraction into the liquid phase and reduced ionic liquid recovery. A partial conversion of the PIL into N-(hydroxyethyl) acetamide was observed after pretreatment, with up to 86% of conversion after the sixth use for the 1.0 ABR. A negative correlation (R2 = 0.96) was found between the acetamide content in the solvent and the saccharification yield. The drop in pretreatment performance was also correlated with a decrease in accumulated lignin recovery and the molecular weight of the isolated lignins. Acetamide formation was reduced when excess base was present. Recycling of the mixture with 0.5 ABR showed that the performance was unchanged (97% saccharification yield) after three uses, although 28% of the mixture was converted into the acetamide. The study shows that protic acetate ILs made from primary amines form an equilibrium with their amide and a low ABR is required in order to maintain high pretreatment efficiency when the PIL is reused. Process and Products Development Department Faculty of Chemical Engineering State University of Campinas (UNICAMP), Av. Albert Einstein, 500 Department of Chemical Engineering Imperial College London Department of Bioprocess and Biotechnology College of Agricultural Sciences São Paulo State University (UNESP), Av. Universitária, 3780 Department of Bioprocess and Biotechnology College of Agricultural Sciences São Paulo State University (UNESP), Av. Universitária, 3780

The rigid cellular materials widely used for personal impact protection can be effective but tend to be inconveniently thick, and to be less effective after a first impact. A macroscopically structured panel material, molded as a two‐dimensional matrix of re‐entrant cells, has been specifically designed and optimized for body‐worn protection. These panels are injection molded from a blend of rate‐stiffening polyborodimethylsiloxane with a thermoplastic elastomer, optimized to minimize the impact force transmitted to the anvil in standard drop‐weight tests even as monolithic slab specimens. The concurrently designed, impact‐protective molded panels offer equivalent protection in thinner, lighter, and more wearable layers. Their re‐entrant cellular structure and rate‐stiffening material allow them to conform easily to individual wearers and to allow free movement at normal rates, while offering enhanced protection under one or more impacts at the same location.

Smouldering peatland fires are capable of burning vast amounts of organic soils, resulting in the release of greenhouse gases into the atmosphere, as well as a significant deterioration of air quality causing in major regional crises known as haze events. Fundamental understanding of smouldering fire spread is essential for the development of mitigating technologies. In this paper, we have systematically conducted 63 experiments studying the individual and combined influence of two key factors affecting multidimensional smouldering spread in organic soils: moisture content (MC) and inorganic content (IC). Both lateral and in-depth smouldering spread were investigated using a novel shallow reactor. This shallow depth allows a greater number of experiments to be performed in a short period of time compared to deeper samples. Lateral spread was found to decrease linearly with moisture content (R2 > 90%); while in-depth spread rate increased linearly up to 300% from moisture content of 0% to 140%. Increased inorganic content linearly decreased the lateral spread rate but had little influence on in-depth spread in drier samples. Interestingly, in wetter samples, in-depth spread was in fact sensitive to inorganic content. A novel approach combining lateral and in-depth spread rates as vector components, revealed that the global spread is independent of moisture content, with an average spread rate of 8.7 and 8.4 cm/h for 2.5 and 40% IC, with changes in direction according to moisture content; going in-depth for wet soils, and laterally for dry soils. Similarly, increasing the IC encouraged downward spread for wet samples. We also report observations of a bifurcation of lateral spread, where spread would locally extinguish where the in-depth spread was greater than the lateral spread. These findings provide previously unknown insight into the relationship between lateral and in-depth spread in smouldering fires, ultimately improving the fundamental understanding of such fires.

The oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-diformylfuran (DFF) using oxygen (1 atm) with a TEMPO and CuCl catalyst system is investigated using a range of imidazolium-based ionic liquids (ILs) and various bases at different HMF substrate loadings (10-50%). This represents the first example of HMF to DFF conversion in ionic liquid media under homogeneous catalysis conditions, revealing dramatic differences in performance between the ILs. In the non-coordinating, hydrophobic ionic liquid, [bmim][NTf2], 90% DFF yield is obtained at 5 mol% catalyst loading after 6 hours at 80 °C at a very high 40% HMF loading. Increasing the temperature to 100 °C leads to a lower yield, attributed to loss of volatile TEMPO from the reaction medium. A system using TEMPO and pyridine immobilized within the ionic liquid [bmim][NTf2] results in selective conversion of HMF to high purity DFF. It also allows the DFF formed to be isolated by sublimation in 81% yield before a further cycle is performed. Subsequent catalyst deactivation is probed by X-ray photoelectron spectroscopy (XPS). Synthesis from fructose in a two-step process achieves a 55% isolated DFF yield. This approach overcomes significant drawbacks previously reported for this transformation, such as solvent toxicity, separation and purification problems as well as the need for high oxygen pressures. Further oxidation of HMF with this system leads to a 62% yield of 5-formyl-2-furancarboxylic acid (FFCA). The separation of this compound can be achieved by sublimation of DFF followed by solvent extraction.

A key challenge in maximizing the effectiveness of model-based design of experiments for calibrating nonlinear process models is the inaccurate prediction of information that is afforded by each new experiment. We present a novel methodology to exploit prior probability distributions of model parameter estimates in a bi-objective optimization formulation, where a conditional-value-at-risk criterion is considered alongside an average information criterion. We implement a tractable numerical approach that discretizes the experimental design space and leverages the concept of continuous-effort experimental designs in a convex optimization formulation. We demonstrate effectiveness and tractability through three case studies, including the design of dynamic experiments. In one case, the Pareto frontier comprises experimental campaigns that significantly increase the information content in the worst-case scenarios. In another case, the same campaign is proven to be optimal irrespective of the risk attitude. An open-source implementation of the methodology is made available in the Python software Pydex.

The metal-organic framework (MOF) MIL-68(In)-NH$_{2}$ was tested for dye removal from wastewater and carbon capture gas separation. MIL-68(In)-NH$_{2}$ was synthesized as a neat, supported MOF thin film membrane and as spherical particles using pyridine as a modulator to shape the morphology. The neat MIL-68(In)-NH$_{2}$ membranes were employed for dye removal in cross-flow geometry, demonstrating strong molecular sieving. MIL-68(In)-NH$_{2}$ particles were used for electrospinning of poylethersulfone mixed-matrix membranes, applied in dead-end filtration with unprecedented adsorption values. Additionally, the neat MOF membranes were used for H$_{2}$/CO$_{2}$ and CO$_{2}$/CH$_{4}$ separation.

Determination of the explosion severity parameters of biomass is crucial for the safety management and dust explosion risk assessment of biomass-processing industries. These are commonly determined following experimental tests in the 20L sphere according to the international standards. Recently, CFD simulations have emerged as a reliable alternative to predict the explosion behavior with good accuracy and reduced labor and capital. In this work, numerical simulations of biomass dust explosions are conducted with the open-source CFD code OpenFOAM. The multi-phase (gas-solid) flow is treated in an Eulerian-Lagrangian framework, using a two-way coupling regime and considering the reactions of biomass conversion (moisture evaporation, devolatilization, and char oxidation), the combustion of volatile gases, and convective and radiative heat transfer. The model is validated with pressure-time and concentration-dependent experimental measurements of two biomass samples. Results suggest that the characteristics of the cold-flow (ı.e., turbulence levels, actual dust concentration, spatial distribution of the dust cloud, and turbophoresis effect) govern the course of the explosion process, and depend strongly on particle size, dust concentration, and ignition delay time effects. These findings may be relevant in the design of better dust explosion testing devices and to the reexamination of the guidelines for the operation of the experiment. Finally, a thorough discussion on the explosion pressures, degree of biomass conversion, flame temperature, flame propagation patterns, and the dust agglomeration effect is presented.

This work demonstrates the importance of transport phenomena on the synthesis of halide perovskite nanoplatelets. Illustrated herein for CsPbBr3, we demonstrate the need for fast and homogeneous mixing to achieve monodispered crystals, in this case with sharp blue emission. The modularity of our synthesis method, combining fluid dynamic simulations, bespoke 3D flow reactors and on-line measurements (UV-vis absorbance and photoluminescence) reveals fundamental understanding about the growth of these perovskite nano-materials, which in turn leads to superlative size reducibility (2.2 ±0.3 nm) and properties (sharp blue emission at 472 nm wavelength, and PLQY 24.5±0.4%). The counterpart conventional hot injection batch synthesis with the same precursors, conditions and reaction temperature yields a product with PL at 501 nm with large batch to batch variations. Understanding the dynamics of the synthesis in the very early stages (within the first 100-300 ms) shows that mixing of the precursors plays a key role not only during the nucleation step, as previously believed, but also during the growth stage. Such fluid properties can be easily predicted in purposefully designed 3D microreactors to provide a consistent and steady output capable of fulfilling the large demand of blue light emitters for a variety of applications.

This work reports saturated-phase densities for the CO2 + methylcyclohexane system at temperatures between 298 and 448 K and at pressures up to the critical pressure. The densities were measured with a standard uncertainty of

The results from a series of well characterised, unstable, miscible displacement experiments in a Hele Shaw cell with a quarter five-spot source-sink geometry are presented, with comparisons to detailed numerical simulation. We perform repeated experiments at adverse viscosity ratios from 1 - 20 and Peclet numbers from 10$^4$ - 10$^6$ capturing the transition from 2D to 3D radial fingering and experimental uncertainty. The open-access dataset provides time-lapse images of the fingering patterns, transient effluent profiles, and meta-information for use in model validation. We find the complexity of the fingering pattern increases with viscosity ratio and Peclet number, and the onset of fingering is delayed compared to linear displacements, likely due to Taylor dispersion stabilisation. The transition from 2D to 3D fingering occurs at a critical Peclet number that is consistent with recent experiments in the literature. 2D numerical simulations with hydrodynamic dispersion and different mesh orientations provide good predictions of breakthrough times and sweep efficiency obtained at intermediate Peclet numbers across the range of viscosity ratios tested, generally within the experimental uncertainty. Specific finger wavelengths, tip shapes, and growth are hard to replicate; model predictions using velocity dependent longitudinal dispersion or simple molecular diffusion bound the fingering evolution seen in the experiments, but neither fully capture both fine-scale and macroscopic measures. In both cases simulations predict sharper fingers than the experiment. A weaker dispersion stabilisation seems necessary to capture the experimental fingering at high viscosity ratio, which may also require anisotropic components. 3D models with varying dispersion formulations should be explored in future developments to capture the full range of effects at high viscosity ratio and Peclet number., 24 pages, 9 figures

Recent advances in machine learning, coupled with low-cost computation, availability of cheap streaming sensors, data storage and cloud technologies, has led to widespread multi-disciplinary research activity with significant interest and investment from commercial stakeholders. Mechanistic models, based on physical equations, and purely data-driven statistical approaches represent two ends of the modelling spectrum. New hybrid, data-centric engineering approaches, leveraging the best of both worlds and integrating both simulations and data, are emerging as a powerful tool with a transformative impact on the physical disciplines. We review the key research trends and application scenarios in the emerging field of integrating simulations, machine learning, and statistics. We highlight the opportunities that such an integrated vision can unlock and outline the key challenges holding back its realisation. We also discuss the bottlenecks in the translational aspects of the field and the long-term upskilling requirements of the existing workforce and future university graduates., 20 pages, 2 figures

Microstructured membrane reactors present a promising approach to master the productivity and safety challenges during the direct synthesis of hydrogen peroxide. However, various mass transport processes occur in this complex system. In order to gain a deeper understanding of these processes, the saturation and desaturation behaviour of the liquid reaction medium with the gaseous reactants is investigated experimentally to examine possible cross-contamination. Moreover, the employed PDMS membrane’s permeances to hydrogen and oxygen are researched at different pressures, by using a variable-pressure/constant-volume setup for the behaviour at ambient pressure and a constant-pressure/variable-volume setup for the behaviour at elevated pressures. A mathematical model in MATLAB is applied to simulate the results. It is shown that a certain desaturation of the gasses through the membrane occurs, and the results are underlined by the modelled ones using a solution-diffusion model in MATLAB. Thus a constant flushing of the gas channels of the reactor is required for safety reasons. Moreover, the measured permeance values indicate that the species transport is mainly limited by the diffusion in the liquid phase and not the membrane resistance.

Understanding fluid flow in granular materials is essential for many engineering applications, including petroleum recovery, groundwater movement and embankment stability. This study investigates the influence of particle angularity on permeability and fluid-particle interaction forces. A random shape generator based on spherical harmonics is used to create irregular-shaped particles with different levels of angularity. Granular packings of uniformly sized (monodisperse) particles are then constructed with the discrete element method (DEM), and pore-scale computational fluid dynamics (CFD) simulations are used to determine the flow fields and the resulted fluid-particle interaction. The more angular particle assemblies thus generated are less permeable, and their fluid-particle interaction forces are higher. However, angularity has limited influence on flow rate distribution and flow tortuosity. The influence of angularity is localized. An increase in angularity generates a larger variance of the pressure distribution on the particle surfaces, thus increasing the pressure component of the fluid-particle interaction force.

To investigate the influence of fluid purity on the adsorption properties, adsorption kinetics and adsorption equilibria of two methanol samples with different water content on an activated carbon were studied. The purity of the methanol samples was 98.5% and 99.9%. Measurements were conducted at 298 K and 318 K using a magnetic suspension balance and cover a wide p/p0 range. To determine effective diffusion time constants and mass transfer coefficients, adsorption kinetics were evaluated using an isothermal and a nonisothermal Fickian diffusion model, and the linear driving force model. The pressure dependence of the kinetic parameters was studied and discussed. A small influence of sample purity on the adsorption equilibria was observed, as the purer methanol sample showed slightly higher equilibrium loadings than the less pure sample. However, significantly faster adsorption kinetics were observed for the purer sample at all temperature and pressure conditions. Compared to the less pure sample, the determined effective diffusion time constants and the mass transfer coefficients were up to 98% and 35% higher, respectively.

Fouling in gas turbines is caused by airborne contaminants which, under certain conditions, adhere to aerodynamic surfaces upon impact. The growth of solid deposits causes geometric modifications of the blades in terms of both mean shape and roughness level. The consequences of particle deposition range from performance deterioration to life reduction to complete loss of power. Due to the importance of the phenomenon, several methods to model particle sticking have been proposed in literature. Most models are based on the idea of a sticking probability, defined as the likelihood a particle has to stick to a surface upon impact. Other models investigate the phenomenon from a deterministic point of view by calculating the energy available before and after the impact. The nature of the materials encountered within this environment does not lend itself to a very precise characterization, consequently, it is difficult to establish the limits of validity of sticking models based on field data or even laboratory scale experiments. As a result, predicting the growth of solid deposits in gas turbines is still a task fraught with difficulty. In this work, two non-dimensional parameters are defined to describe the interaction between incident particles and a substrate, with particular reference to sticking behavior in a gas turbine. In the first part of the work, historical experimental data on particle adhesion under gas turbine-like conditions are analyzed by means of relevant dimensional quantities (e.g. particle viscosity, surface tension, and kinetic energy). After a dimensional analysis, the data then are classified using non-dimensional groups and a universal threshold for the transition from erosion to deposition and from fragmentation to splashing based on particle properties and impact conditions is identified. The relation between particle kinetic energy/surface energy and the particle temperature normalized by the softening temperature represents the original non-dimensional groups able to represent a basis of a promising adhesion criterion.

All polymers are flammable to some degree. For safety, polymer flammability is most commonly reduced through flame retardants that are designed to primarily act chemically as opposed to physically. Here, we investigate computationally using the code Gpyro how inert additives such as hollow glass spheres (HGS) and boron nitride platelets (BNP) alter the flammability properties of glass fibre reinforced polybutylene terephthalate (PBT-GF), in a cone heater and UL94 setup. The Gpyro model is first validated against experiments and another code, both from the literature, for pure PBT-GF. According to the predictions, HGS leads to higher surface temperatures but lower temperatures in-depth, whereas adding BNP yields the opposite effect. Modelling numerically the cone heater setup shows that at 50% HGS loading, the time to ignition is reduced to a quarter while the semi-steady state mass loss rate is reduced to a third; at 50% BNP loading, the time to ignition is doubled while the peak mass loss rate is approximately doubled. In the UL94 setup, where the sample is smaller than cone heater, the effects are similar although less pronounced. A sensitivity study of the thermophysical properties shows that time to ignition is primarily controlled by emissivity, density and specific heat capacity, while peak mass loss rate is controlled by thermal conductivity and specific heat capacity. This work shows how heat transfer within a thermoplastic polymer can be utilised to improve its flammability characteristics through inert additives as well as the limitations of this retardancy approach.

Black carbon (BC) particle number (PN) emissions from various sources contribute to the deterioration of air quality, adverse health effects, and anthropogenic climate change. This paper critically reviews different fractal aggregate theories to develop a new methodology that relates BC PN and mass concentrations (or emissions factors). The new methodology, named as the fractal aggregate (FA) model is validated with measurements from three different BC emission sources: an internal combustion engine, a soot generator, and two aircraft gas turbine engines at ground and cruise conditions. Validation results of the FA model show that R2 values range from 0.44 to 0.95, while the Normalised Mean Bias is between −27.7% and +26.6%. The model estimates for aircraft gas turbines represent a significant improvement compared to previous methodologies used to estimate aviation BC PN emissions, which relied on simplified assumptions. Uncertainty and sensitivity analyses show that the FA model estimates have an asymmetrical uncertainty bound ( − 54 % , + 103 % ) at a 95% confidence interval for aircraft gas turbine engines and are most sensitive to uncertainties in the geometric standard deviation of the BC particle size distribution. Given the improved performance in estimating BC PN emissions from various sources, we recommend the implementation of the FA model in future health and climate assessments, where the impacts of PN are significant.

Pore network models (PNMs) offer a computationally efficient way to analyse transport in porous media. Their effectiveness depends on how well they represent the topology and geometry of real pore systems, for example as imaged by X-ray CT. The performance of two popular algorithms, maximum ball and watershed, is evaluated for three porous systems: an idealised medium with known pore throat properties and two rocks with different morphogenesis—carbonate and sandstone. It is demonstrated that while the extracted PNM simulates simple flow (permeability) with acceptable accuracy, their topological and geometric properties are significantly different. This suggests that such PNM may not serve more complex studies, such as reactive/convective transport of contaminants or bacteria, and further research is necessary to improve the interpretation of real pore spaces with networks. Linear topology–geometry relations are derived and presented to stimulate development of more realistic PNM.

Generalized Multiple Mapping Conditioning (MMC) allows for the use of any physical quantity to represent the required reference variable provided that it delivers the desired behavior. The binomial Langevin model (BLM) has been shown to predict higher statistical moments with good accuracy. However, joint-scalar modeling for many scalars becomes problematic because scalar bounds must be specified as conditional on other scalars to preserve elemental balances. The resulting volumes in state space become exceptionally complex for realistic problem sizes. In the current work, this central difficulty is avoided by using only velocity and mixture fraction statistics from the BLM with the latter used as the MMC reference variable. The principal advantage of this method is that the implementation of the binomial Langevin mixture fraction is relatively straightforward and provides a direct physical link to MMC. The MMC model is closed using an augmented modified Curl’s model where the selection of particle pairs for (turbulent) mixing ensures proximity in reference space and a corresponding closeness in physical space. The method is evaluated for a lifted methane jet flame undergoing auto-ignition in a vitiated coflow. Most of the major features of the flow are well reproduced and found to generally outperform other modeling approaches, including Large Eddy Simulations using simplified treatments of turbulence–chemistry interactions such as unsteady flamelet/progress variable descriptions.

The paper evaluates the interaction between atomization quality and atomization efficiency, which has not been understood, although it is commonly observed that the atomization quality of different atomizers does not improve linearly with addition of energy. The results quantify the energy exchange between the air and liquid streams of a twin water impinging jets atomizer and its consequences on atomization characteristics and explain the behavior of quality and efficiency. The liquid jet breakup length, liquid jets separation distance at the breakup region and spray angles were measured with high speed photography and the droplet characteristics, such as spatial distributions of mean droplet velocities and diameters and normalized liquid volume flux with Phase Doppler Anemometry (PDA). The results show that the breakup length decreased and the separation distance of the interacting liquid jets at the geometrical ‘impingement’ region increased rapidly as Air-to-Liquid Momentum Ratio (ALMR) increased and then remained constant for ALMR>9. Spray angles were different on different planes through the spray and generally decreased with increasing ALMR and were insensitive to the liquid jets impingement angle. The spatial distributions of average droplet size, velocity and normalized liquid volume flux in the sprays became elongated normal to the plane of the two liquid jets for larger liquid flow rates, in agreement with the spray angle in the near nozzle region. The spatially-averaged Sauter Mean Diameter (SMD) of the sprays quantified uniquely the atomization quality and showed, for the first time, that it did not depend on liquid jets impingement angle. The average SMD

The mixture fraction and reaction progress variables are key for presumed probability density function (PDF) based flamelet models for partially premixed flames. The importance of the joint statistics of these two variables are evaluated using a joint composition-enthalpy transported PDF/Finite Volume method applied to established databases for inhomogeneous jet flames. The accuracy of the approach is first examined for three flames with different mixture fraction inlet profiles and departures from blow-off. The (joint-) statistics of mixture fraction and reaction progress variable are subsequently analysed with the covariance of the two variables used to evaluate the assumption of statistical independence. Results show that the current approach is able to reproduce the near-field features of both homogeneous and inhomogeneous jet flames. The latter leads to a stratified premixed flame that evolves to diffusion-dominated combustion as the influence of the pilot fades. In agreement with measured data, the mixture fraction variance is strongly affected by the near-field combustion mode and the misalignment with the reaction progress variable variance is obvious in the stratified premixed flame. It is shown that the covariance of the mixture fraction and reaction progress variable is influenced by turbulence-chemistry interactions and that, generally, the two parameters remain strongly correlated with the consequence that the assumption of statistical independence is implausible.

Scramjet propulsion systems can be the key to deliver the next generation of hypersonic planes. The high costs and complexity of gathering experimental data is a limiting factor in the development of such engine. In this context, numerical simulation has become increasingly popular to investigate supersonic combustion phenomena that otherwise would be prohibitively expensive. Despite recent progress, the simulation of high-speed compressible and reactive flows is still very challenging and presents many associated challenges. The chemical source term is highly non-linear and most combustion models are designed to operate in low-Mach number conditions. The present work investigates the use of Probability Density Function (PDF) in the context of Large Eddy Simulation models under supersonic conditions. Two approaches are considered: an extension of the joint scalar-enthalpy PDF for high-speed flows and a novel joint velocity-scalar-energy PDF model. Both formulations use the Eulerian stochastic fields approach implemented in a fully compressible density-based CFD code. The performance of the models are investigated in a supersonic lifted flame, comparing the stochastic formulations with traditional models that neglect sub-grid fluctuations. The results show that sub-grid contributions are important at coarse meshes and the stochastic fields approach can reproduce the experimental data and the scatter observed. The simulations suggest that the scalar-enthalpy PDF is the most robust formulations and the sub-grid closures of the joint velocity-scalar PDF need further investigation.

Smouldering combustion of peat drives the largest fires on Earth, and their emissions play an important role in global carbon balance and regional air quality. Here we report a series of controlled laboratory experiments of peat fires. Peat samples of 100% moisture content in dry basis were burnt in an open-top reactor with dimensions of 20 × 20 × 10 cm. The diagnostics are a unique set of simultaneous measurements consisting of real-time mass loss, up to 20 different gas species concentration, size-fractioned particle mass (PM10, PM2.5 and PM1), temperature profile, and visual and infrared imaging. This comprehensive framework of measurements reveals that the evolution of the emissions varies in time with four observed stages (ignition, growth, steady and burn out) which are characterised by different combustion dynamics. Mass flux measurements show that CO2, CO, CH4 and NH3 are the four most predominant gas species emitted in the steady stage. Incorporating the mass loss rate, the transient emission factors (EFm) of both gas and particle species are calculated and reported here for the first time. Averaging the steady stage, the EFm of PM2.5 reached 23.12 g kg-1, which accounts for 87.2% of the total particle mass, and PM1 EFm was reported to be 15.04 g kg-1. The EFm of alkane species (CH4, C2H6, C3H8, C4H10) were found to peak within the ignition stage, whereas the EFm of CO2, CO and NH3 kept increasing during the steady stage. Because of these measurements, for the first time we were able to validate the EF calculated by assuming averaged values and a carbon balance, which is the preferred method used in remote sensing and atmospheric sciences. This work contributes to a better understanding of peat fire emissions and could help develop strategies tackling regional haze.

Combustion under highly strained conditions or at low Damkohler numbers requires external enthalpy sources to ensure stability. Such flames deviate from the conventional bimodal flame structure and chemically active fluid states become statistically relevant. The current work utilises a multi-fluid analysis in order to quantify the impact of such conditions on a turbulent (Ret ≃ 350) lean (Φ = 0.50) premixed DME / air flame with Da ≃ 0.29. The flames were aerodynamically stabilised in a back-to-burnt opposed jet configuration with the temperature of the external enthalpy support varied from 1200 ≤ THCP (K) ≤ 1600. Simultaneous Mie scattering, CH2O and OH–PLIF and PIV were used to quantify the transition from spatially distributed chemical reactions to reaction zones that appear flamelet-like. The analysis shows that in the current configuration such structures are only present at high THCP. By contrast, the low temperature chemistry is continuously active with CH2O increasingly more spatially distributed with reducing support temperature. The current analysis provides novel insights into low Damkohler number combustion and burning mode transitions by means of (i) multi-fluid probability statistics, (ii) the structure of formaldehyde and hydroxyl layers and (iii) their cross–correlation as well as (iv) the underlying strain rate statistics on material surfaces.

Droplet-based microfluidic extraction is a promising way for effective lanthanides extraction due to its outstanding mass transfer performance. The separation process can be greatly enhanced with the droplet-based microfluidic extraction technique. However, the interactions between mass transfer, microfluidic dynamics and extraction kinetics are still unclear, which has hindered further manipulation on microfluidic extraction to boost extraction performance. In this study, the mechanisms of microfluidic droplet-based extraction and separation intensification of lanthanides are for the first time unveiled by using a numerical simulation model. The limiting factors for the performance of droplet-based microfluidic extraction are identified through a model-based parametric analysis. The numerical analyses provide a comprehensive understanding of droplet-based microfluidic extraction systems and offer operation and optimization guidelines for future research in this area.

Structural softwood (timber) recently gained attention by architects and engineers as a construction material for high-rise buildings. Regulations restrict the height of these buildings due to safety concerns as their fire behaviour is poorly understood. The fire behaviour and loss of loadbearing capacity of timber is controlled by charring, whose chemical kinetics has rarely been studied. Current models of charring assume, without proof, the same reaction scheme and kinetic parameters apply to all wood species, which potentially introduces a large uncertainty. Here, the hypothesis is tested that the kinetics of different wood species insignificantly affects their charring behaviour. The kinetics is modelled by a microscale kinetic model—including pyrolysis and char oxidation reactions—which assumes that the three main components (cellulose, hemicellulose, and lignin) of wood degrade independently. Variation in the kinetics between different wood species is captured by their different chemical compositions within a wood group (softwood or hardwood). Hardwood is included for comparison. A database of over 600 compositions was compiled from literature, and studied across scales using a microscale (mg-samples) and mesoscale (kg-samples) model. All reactions, kinetic parameters, and physical properties were selected from literature. Both models were validated using blind predictions of high-fidelity experiments from literature. Variation in kinetics were found to have a small effect on the predicted mass loss rate at both scales (±1 g/m2-s) and a negligible effect on the predicted temperatures (±16 K) across different depths, heat fluxes, and oxygen concentrations at the mesoscale. These results prove, for the first time, that the variation in kinetics is negligible for predicting charring across scales. A kinetic model of charring derived for one wood species should be valid for all wood species within softwood or hardwood. Modellers should, therefore, focus on the difference in the physical properties instead of the kinetics between wood species.

We combine reduced order modelling and system identification to reconstruct the temporal evolution of large scale vortical structures behind the blades of a Rushton impeller. We performed Direct Numerical Simulations at Reynolds number 600 and employed proper orthogonal decomposition (POD) to extract the dominant modes and their temporal coefficients. We then applied the identification algorithm, N4SID, to construct an estimator that captures the relation between the velocity signals at sensor points (input) and the POD coefficients (output). We show that the first pair of modes can be very well reconstructed using the velocity time signal from even a single sensor point. A larger number of points improves accuracy and robustness, and also leads to better reconstruction for the second pair of POD modes. Application of the estimator derived at Re=600 to the flows at Re=500 and 700, shows that it is robust with respect to changes in operating conditions.

We predict waterflood displacement on a pore-by-pore basis using pore network modelling. The pore structure is captured by a high-resolution image. We then use an energy balance applied to images of the displacement to assign an average contact angle, and then modify the local pore-scale contact angles in the model about this mean to match the observed displacement sequence. Two waterflooding experiments on oil-wet rocks are analysed where the displacement sequence was imaged using time-resolved synchrotron imaging. In both cases the capillary pressure in the model matches the experimentally obtained values derived from the measured interfacial curvature. We then predict relative permeability for the full saturation range. Using the optimised contact angles distributed randomly in space has little effect on the predicted capillary pressures and relative permeabilities, indicating that spatial correlation in wettability is not significant in these oil-wet samples. The calibrated model can be used to predict properties outside the range of conditions considered in the experiment.

Granular activated carbon (GAC) adsorption has found wide application as a treatment process for the removal of natural organic matter, small organic compounds (e.g. pesticides), inorganic compounds (e.g. heavy metals), taste and odour compounds in water over many years. During GAC operation, contaminants are adsorbed and the carbon becomes progressively saturated over time, requiring periodic regeneration of the media to restore its capacity. Chemical regeneration has been identified as an effective alternative to off-site thermal regeneration, which is the most commonly practiced carbon regeneration technique for carbon exhausted by organic contaminants. Off-site thermal regeneration poses significant disadvantages as it is a time-consuming process and represents a significant operational cost (e.g. reduced productivity) and environmental (energy/CO2) burden to water utilities. Chemical regeneration can be performed on-site, either in situ or off-line, by exposing the spent (exhausted) GAC to a selected chemical, or a combination of chemicals, to remove the adsorbed contaminants. Prior research on chemical regeneration has been limited in extent, but has considered both organic and inorganic solutions. Despite a significant number of studies, a suitable regenerant solution for desorbing a wide range of aqueous contaminants in drinking water treatment has not been identified to-date. In this paper, we provide a critical review of the performance of alternative regenerant solutions for the chemical regeneration of GAC loaded with different organic contaminants.