Search

Crystal regeneration has been observed in macroscopic paracetamol crystals post breakage along their cleavage plane. High resolution imaging confirmed regeneration rates to be 3-fold faster than growth prior to breakage. Further analysis of the solute-solvent interactions is required to elucidate the process which currently lacks linearity with traditional growth theories.

Evolutionary Population Dynamics (EPD) refers to eliminating poor individuals in nature, which is the opposite of survival of the fittest. Although this method can improve the median of the whole population of the meta-heuristic algorithms, it suffers from poor exploration capability to handle high-dimensional problems. This paper proposes a novel EPD operator to improve the search process. In other words, as the primary EPD mainly improves the fitness of the worst individuals in the population, and hence we name it the Fitness-Based EPD (FB-EPD), our proposed EPD mainly improves the diversity of the best individuals, and hence we name it the Diversity-Based EPD (DB-EPD). The proposed method is applied to the Grey Wolf Optimizer (GWO) and named DB-GWO-EPD. In this algorithm, the three most diversified individuals are first identified at each iteration, and then half of the best-fitted individuals are forced to be eliminated and repositioned around these diversified agents with equal probability. This process can free the merged best individuals located in a closed populated region and transfer them to the diversified and, thus, less-densely populated regions in the search space. This approach is frequently employed to make the search agents explore the whole search space. The proposed DB-GWO-EPD is tested on 13 high-dimensional and shifted classical benchmark functions as well as 29 test problems included in the CEC2017 test suite, and four constrained engineering problems. The results obtained by the proposal upon implemented on the classical test problems are compared to GWO, FB-GWO-EPD, and four other popular and newly proposed optimization algorithms, including Aquila Optimizer (AO), Flow Direction Algorithm (FDA), Arithmetic Optimization Algorithm (AOA), and Gradient-based Optimizer (GBO). The experiments demonstrate the significant superiority of the proposed algorithm when applied to a majority of the test functions, recommending the application of the proposed EPD operator to any other meta-heuristic whenever decided to ameliorate their performance.

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.

Plastic pollution, more specifically from food packaging and containers which account for the largest share of 36% of current plastic production, is one of the greatest threats to the natural environment and human health. Thus, the development of alternative renewable plastics are needed to complement a circular economy and reduce resource depletion. Seaweeds have been known to possess good film forming properties ideal for bioplastic production, and Sargassum natans-an invasive brown seaweed which has been inundating the shores of the Caribbean, has been shown to be an excellent candidate. This study presents, for the first time, the development of a novel optimized biodegradable alginate composite bioplastic as an alternative to traditional plastic packaging. The optimization process was carried out using Response Surface Methodology (RSM) resulting in a formulation of 6 wt% alginate, 0.263 wt% starch, 0.35 wt% CMC, 0.065 g/g sorbitol and 0.025 g/g PEG 200- with ultra-high oxygen barrier (OP - 0.2 cm3 μm m−2 d−1 kPa−1), good water vapor barrier (WVP - 2.18 × 10−12 g m/m2 s Pa) and high tensile modulus ( - 3.93 GPa)- with no migration of additives into a simulated aqueous food system in 10 days. Furthermore, composite films were found to fully degrade in 14 days and possessed better OP, higher WVP and comparable material properties to HDPE, PET and PLA. Ultimately, our results support alginate composite films as a viable alternative for food packaging best fitted for low moisture environments-encouraging the use of renewable materials for packaging innovation and supporting UNSDGs.

This research has investigated the structural changes and pozzolanic activity produced in acid activated smectite clay. The activation treatment used HCl at different concentrations, using different times and at a range of temperatures. X-ray diffraction, Fourier transform infrared spectroscopy and scanning electron microscopy coupled with energy dispersive X-ray spectroscopy were used to determine the acid dissolution mechanism and characterise the activated clay mineral structure. Acid activation causes dehydroxylation of smectite clay, followed by leaching of octahedral cations. This results in the formation of a silica-rich amorphous phase that exhibits substantial pozzolanic activity compared to the same clay sample that had undergone calcining treatment at 850. The optimum sample was activated for 8 h using 5 M HCl at 90 °C. This was 93 % amorphous. Mortar prisms prepared with 25 % replacement of Portland cement by acid activated smectite produced 93 % compressive strength of plain Portland cement mortar.

Self-amplifying RNA (saRNA) is a next-generation vaccine platform, but like all nucleic acids, requires a delivery vehicle to promote cellular uptake and protect the saRNA from degradation. To date, delivery platforms for saRNA have included lipid nanoparticles (LNP), polyplexes and cationic nanoemulsions; of these LNP are the most clinically advanced with the recent FDA approval of COVID-19 based-modified mRNA vaccines. While the effect of RNA on vaccine immunogenicity is well studied, the role of biomaterials in saRNA vaccine effectiveness is under investigated. Here, we tested saRNA formulated with either pABOL, a bioreducible polymer, or LNP, and characterized the protein expression and vaccine immunogenicity of both platforms. We observed that pABOL-formulated saRNA resulted in a higher magnitude of protein expression, but that the LNP formulations were overall more immunogenic. Furthermore, we observed that both the helper phospholipid and route of administration (intramuscular versus intranasal) of LNP impacted the vaccine immunogenicity of two model antigens (influenza hemagglutinin and SARS-CoV-2 spike protein). We observed that LNP administered intramuscularly, but not pABOL or LNP administered intranasally, resulted in increased acute interleukin-6 expression after vaccination. Overall, these results indicate that delivery systems and routes of administration may fulfill different delivery niches within the field of saRNA genetic medicines., Graphical abstract Unlabelled Image

Acinetobacter baumannii is an opportunistic pathogen with a high mortality rate due to multi-drug-resistant strains. The synthesis and uptake of the iron-chelating siderophores acinetobactin (Acb) and preacinetobactin (pre-Acb) have been shown to be essential for virulence. Here, we report the kinetic and structural characterization of BauF, a flavin-dependent siderophore-interacting protein (SIP) required for the reduction of Fe(III) bound to Acb/pre-Acb and release of Fe(II). Stopped-flow spectrophotometric studies of the reductive half-reaction show that BauF forms a stable neutral flavin semiquinone intermediate. Reduction with NAD(P)H is very slow (k obs, 0.001 s-1) and commensurate with the rate of reduction by photobleaching, suggesting that NAD(P)H are not the physiological partners of BauF. The reduced BauF was oxidized by Acb-Fe (k obs, 0.02 s-1) and oxazole pre-Acb-Fe (ox-pre-Acb-Fe) (k obs, 0.08 s-1), a rigid analogue of pre-Acb, at a rate 3-11 times faster than that with molecular oxygen alone. The structure of FAD-bound BauF was solved at 2.85 Å and was found to share a similarity to Shewanella SIPs. The biochemical and structural data presented here validate the role of BauF in A. baumannii iron assimilation and provide information important for drug design. Published version

In the present paper, we present a method for solving the population balance equation (PBE) with the complete range of kinetic processes included: namely aggregation, fragmentation, nucleation and growth. The method is based on the finite volume scheme and features guaranteed conservation of the first moment by construction, accurate prediction of the size distribution, applicability to an arbitrary non-uniform grid, robustness and computational efficiency which is instrumental for coupling with computational fluid dynamics (CFD). The treatment of aggregation is based on the previous work by Liu and Rigopoulos (2019). An analysis of the aggregation terms in the PBE is made, and the source of conservation error in finite element/volume methods is elucidated. It is subsequently shown how this error is overcome in the present method via a coordinate transformation applied to the aggregation birth double integral resulting from the application of the finite volume method. The contributions to the birth term are delineated and their corresponding death fluxes identified. An aggregation map is then constructed for mapping birth and death fluxes, thus allowing the finite volume method to operate in terms of fluxes and achieve conservation of mass. The method is then extended to fragmentation, for which a map is also constructed to represent the birth and death fluxes. In the implementation, the aggregation and fragmentation maps are pre-tabulated to allow fast computation. It is also shown how the method can be coupled with a total variation diminishing (TVD) scheme for the treatment of growth with minimal numerical diffusion. The method is validated with a number of test cases including analytical solutions and numerical solutions of the discrete PBE for aggregation (theoretical and free molecule/Brownian kernels), fragmentation, aggregation-fragmentation and aggregation-growth. In all cases, the method produces very accurate results, while also being computationally efficient due to the pre-tabulation of the maps and the simplicity of the algorithm carried out per time step.

Natural convection is intensively explored, especially in a valley-shaped trapezoidal enclosure, because of its broad presence in both technical settings and nature. This study deals with a trapezoidal cavity, which is initially filled with linearly stratified air. Although the sidewalls remain adiabatic, the bottom wall is heated, and the top wall is cooled. For the stratified fluid (air), the temperature of the fluid adjacent to the top and the bottom walls is the same as that of the walls. Natural convection in the trapezoidal cavity is simulated in two dimensions using numerical simulations, by varying Rayleigh numbers (Ra) from 100 to 108 with constant Prandtl number, Pr = 0.71, and aspect ratio, A = 0.5. The numerical results demonstrate that the development of natural convection from the beginning is dependent on the Rayleigh numbers. According to numerical results, the development of transient flow within the enclosure owing to the predefined conditions for the boundary may be categorized into three distinct stages: early, transitional, and steady or unsteady. The flow characteristics at each of the three phases and the impact of the Rayleigh number on the flow’s growth are quantified. Unsteady natural convection flows in the enclosure are described and validated by numerical results. In addition, heat transfer through the bottom and the top surfaces is described in this study.

Perovskite solar cells (PSCs) have captured the attention of the global energy research community in recent years by showing an exponential augmentation in their performance and stability. The supremacy of the light-harvesting efficiency and wider band gap of perovskite sensitizers have led to these devices being compared with the most outstanding rival silicon-based solar cells. Nevertheless, there are some issues such as their poor lifetime stability, considerable J–V hysteresis, and the toxicity of the conventional constituent materials which restrict their prevalence in the marketplace. The poor stability of PSCs with regard to humidity, UV radiation, oxygen and heat especially limits their industrial application. This review focuses on the in-depth studies of different direct and indirect parameters of PSC device instability. The mechanism for device degradation for several parameters and the complementary materials showing promising results are systematically analyzed. The main objective of this work is to review the effectual strategies of enhancing the stability of PSCs. Several important factors such as material engineering, novel device structure design, hole-transporting materials (HTMs), electron-transporting materials (ETMs), electrode materials preparation, and encapsulation methods that need to be taken care of in order to improve the stability of PSCs are discussed extensively. Conclusively, this review discusses some opportunities for the commercialization of PSCs with high efficiency and stability.

The recently developed polyoxometalate (POM)–ionosolv concept offers an interesting strategy to generate two valuable product streams from lignocellulosic biomass, a solid cellulose-rich pulp and short-chain carboxylic acids like formic acid and acetic acid in a simple and cost-efficient manner. This study aimed to find optimum parameters for the two steps of the transformation by performing a sensitivity analysis on the initial ionosolv fractionation step as well as kinetic investigations of the following POM-catalyzed oxidation step. The results were transferred to the POM–ionosolv concept to find the overall process optimum. Beech wood was used as an industrially relevant substrate for ionosolv fractionation with the low-cost ionic liquid triethylammonium sulfate, [TEA][HSO4], and the HPA-5 [H8PV5Mo7O40] POM catalyst for the oxidation of the dissolved components in an oxygen atmosphere. As the most seminal finding, we defined optimum conditions of 125 °C, 1200 rpm, 30 bar oxygen, and 24 h reaction time in ionic liquid containing 70% water, achieving 72% xylose extraction from beech wood, which resulted in a 39% formic acid yield. We suggest that the fractionation and catalytic conversion are carried out at different water contents for maximum conversion efficiency for each step.

Several outbreaks of COVID-19 caused by imported cases have occurred in China following the successful control of the outbreak in early 2020. In order to avoid recurrences of such local outbreaks, it is important to devise an efficient control and prevention strategy. In this paper, we developed a stochastic discrete model of the COVID-19 epidemic in Guangzhou in 2021 to compare the effectiveness of centralized quarantine and compulsory home quarantine measures. The model was calibrated by using the daily reported cases and newly centralized quarantined cases. The estimated results showed that the home quarantine measure increased the accuracy of contact tracing. The estimated basic reproduction number was lower than that in 2020, even with a much more transmissible variant, demonstrating the effectiveness of the vaccines and normalized control interventions. Sensitivity analysis indicated that a sufficiently implemented contact tracing and centralized quarantine strategy in the initial stage would contain the epidemic faster with less infections even with a weakly implemented compulsory home quarantine measure. However, if the accuracy of the contact tracing was insufficient, then early implementation of the compulsory home quarantine with strict contact tracing, screening and testing interventions on the key individuals would shorten the epidemic duration and reduce the total number of infected cases. Particularly, 94 infections would have been avoided if the home quarantine measure had been implemented 3 days earlier and an extra 190 infections would have arisen if the home quarantine measure was implemented 3 days later. The study suggested that more attention should be paid to the precise control strategy during the initial stage of the epidemic, otherwise the key group-based control measure should be implemented strictly.

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.

A reactive Molecular Dynamics (MD) study of n-dodecane combustion at high temperatures under externally applied electrostatic fields is performed to investigate their effect on chemical kinetics. A local charge equilibration method is used to enable charge transfers up to the overlap of the atomic orbitals and introduce molecular polarization induced by an electric field. The atomic charges of an isolated n-dodecane molecule with and without external electrostatic fields are first compared with Density Functional Theory (DFT) computations, to assess the accuracy of the charge equilibration method and its ability to capture polarization. Then, the impact of external electrostatic fields on the reaction kinetics of fuel, oxidizer and products is studied for a range of ambient temperatures and densities. The activation energy and pre-exponential factor of Arrhenius-type reactions under various electrostatic fields are also investigated by performing Nudged Elastic Band (NEB) computations on selected reactions’ Minimum Energy Path (MEP) and by analysing the collision frequency, respectively. Results show that the atomic charge transfers due to close interactions and molecular polarisation are relatively weak in all investigated conditions, leading to the necessity of strong external electric fields to induce changes to chemical kinetics. The consumption rate of n-dodecane decreases for strong electrostatic fields, whereas for low values of the electrostatic field strength no clear trend is observed. In addition, at high temperature and density conditions, oxygen consumption increases under strong electrostatic fields, whereas the opposite trend is observed as the temperature and density decrease. NEB analysis shows alterations of the activation energy up to 2.3 kcal/mol for oxygen compound reactions with varying strength of the external electrostatic field. Furthermore, analysis of the translational, rotational and vibrational kinetic energy modes and collision frequency reveals the influence of translational motion and molecular stabilization on the reaction rates. The kinetics of oxygen molecules was found to be of primary importance to determine the reaction behaviour under external electrostatic fields, as oxygen molecules have a direct effect on the oxidation reactions and also indirectly affect n-dodecane pyrolysis when an electrostatic field is present. This study provides fundamental understanding of the interactions between heavy hydrocarbons and electrostatic fields for the development of future hybrid thermal-electrical technologies.

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.

Over the years, due to the surge in energy demand, the use of alternative fuels has emerged as an interesting area of research. In the current work, a comparative study was conducted by employing gasoline, 6% ethanol–gasoline (E6), and 12% ethanol–gasoline (E12) in a spark-ignition engine. Performance, emissions, and lube oil damage tests were conducted at a constant load by varying engine speed. E12 showed improved performance, i.e., 7.82% higher torque and 14.69% improved brake thermal efficiency (BTE) in comparison with neat gasoline. In addition, CO, CO2, HC, and NOx emissions were found to be minimal for E12. Furthermore, lubricating oil properties (kinematic viscosity, flash point, and total base number (TBN)) and wear debris (iron, aluminum, and copper) showed a visibly improved performance with gasoline compared to E6 and E12. The highest decline in kinematic viscosity of 27.87%, compared to fresh oil, was recorded for E12. Thus, the lube oil properties have to be modified according to the chemical properties of the alternative fuel.

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)

Under mild conditions of room temperature and pressure, and using either pure oxygen or air, aldehydes are converted using a heterogeneous Fe–N/C catalyst to produce the corresponding organic peroxy acid and acylperoxy radicals, which forms the epoxide from cyclohexene with high yield (91% for isobutyraldehyde in O2). Real-time monitoring of the rate of oxygen consumption and the electrochemical potential of the Fe–N/C catalyst has been used to study the formation of the peroxy acid and subsequent catalytic epoxidation of cyclohexene. Using isobutyraldehyde, it is shown that the aldehyde and the iron-based carbon catalyst (Fe–N/C) are involved in the rate determining step. Addition of a radical scavenger increases the induction time showing that radicals are initiated by the reaction between the aldehyde and the catalyst. Furthermore, UV-vis spectroscopy with 2,2′-azino-di-(3-ethylbenzthiazoline sulfonic acid) (ABTS) proved the in situ formation of peroxy acid. In the presence of cyclohexene, the peroxy acid leads to the corresponding epoxide with high yield. Monitoring the open circuit potential (OCP) and oxygen flow concurrently follows the production of the peroxy acid. The epoxidation reaction can take place only when the increase in open circuit potential is greater than 0.14 V, suggesting an in situ direct link between the relative oxidative strength of the peroxy acid and the likelihood of epoxidation.

Bubble size distribution (BSD) is a factor that is well known for influencing the performance of many industrial processes, such as froth flotation. The most commonly used method for measuring bubble size consists of processing photographs of the bubbles. However, the source code of the algorithms for performing the image processing has been seldom published. This article addresses the above by presenting a comprehensive open-source software for processing images of bubbles, allowing researchers to quantify BSD. This software - Bubble Analyser - includes a standard image processing algorithm that was tested against manually segmented images, showing errors under 5% in the calculation of the Sauter mean diameter, the most common descriptor of BSD. Additionally, Bubble Analyser has been designed to easily incorporate new segmentation algorithms developed by other researchers, in order to expand the software capabilities, allow for algorithm comparisons, and foster collaboration in research.

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.

Cationic Lewis acids (LAs) are gaining interest as targets for frustrated Lewis pair (FLP)-mediated catalysis. Unlike neutral boranes, which are the most prevalent LAs for FLP hydrogenations, the Lewis acidity of cations can be tuned through modulation of the counteranion; however, detailed studies on such anion effects are currently lacking in the literature. Herein, we present experimental and computational studies which probe the mechanism of H2 activation using iPr3SnOTf (1-OTf) in conjunction with a coordinating (quinuclidine; qui) and noncoordinating (2,4,6-collidine; col) base and compare its reactivity with {iPr3Sn·base}­{Al­[OC­(CF3)3]4} (base = qui/col) systems which lack a coordinating anion to investigate the active species responsible for H2 activation and hence resolve any mechanistic roles for OTf– in the iPr3SnOTf-mediated pathway.

The indirect nature of silicon (Si) emission currently limits the monolithic integration of photonic circuitry with Si electronics. Approaches to circumvent the optical shortcomings of Si include band structure engineering via alloying (e.g., SixGe1–x–ySny) and/or strain engineering of group IV materials (e.g., Ge). Although these methods enhance emission, many are incapable of realizing practical lasing structures because of poor optical and electrical confinement. Here, we report on strong optoelectronic confinement in a highly tensile-strained (ε) Ge/In0.26Al0.74As heterostructure as determined by X-ray photoemission spectroscopy (XPS). To this end, an ultrathin (∼10 nm) ε-Ge epilayer was directly integrated onto the In0.26Al0.74As stressor using an in situ, dual-chamber molecular beam epitaxy approach. Combining high-resolution X-ray diffraction and Raman spectroscopy, a strain state as high as ε ∼ 1.75% was demonstrated. Moreover, high-resolution transmission electron microscopy confirmed the highly ordered, pseudomorphic nature of the as-grown ε-Ge/In0.26Al0.74As heterostructure. The heterointerfacial electronic structure was likewise probed via XPS, revealing conduction- and valence band offsets (ΔEC and ΔEV) of 1.25 ± 0.1 and 0.56 ± 0.1 eV, respectively. Finally, we compare our empirical results with previously published first-principles calculations investigating the impact of heterointerfacial stoichiometry on the ε-Ge/InxAl1–xAs energy band offset, demonstrating excellent agreement between experimental and theoretical results under an As0.5Ge0.5 interface stoichiometry exhibiting up to two monolayers of heterointerfacial As–Ge diffusion. Taken together, these findings reveal a new route toward the realization of on-Si photonics. Accepted version

This study uses data acquired from three-dimensional discrete element method simulations to reconsider what measure of state can be used to predict stiffness in granular materials. A range of specimens with linear and gap-graded particle size distributions are considered and stiffness is measured using small amplitude strain probes. Analysis of the data firstly confirms that the void ratio, which is typically used as a measure of state in experimental soil mechanics, does not correlate well with shear stiffness. However, the empirical expressions developed by Hardin and his colleagues can capture variations in stiffness, provided an appropriate state variable is used. The study then highlights that the contribution of individual contacts to the overall stiffness is highly variable, depending on both the contact force transmitted and the particle size. Analyses explore how the stress transmission both within and between the different size fractions affects the overall stiffness. This heterogeneity in stiffness relates to the heterogeneity in the stress transmission amongst the different fractions. By considering the heterogeneity of stress distribution amongst different particle size fractions, a new semi-empirical stress-based state variable is proposed that provides insight into the factors that influence stiffness.

Degradation of dye pollutants by the photocatalytic process has been regarded as the most efficient green method for removal organic dyes from contaminated water. The current research work describes the synthesis of Fe3O4@SiO2@Ru hybrid magnetic composites (HMCs) and their photocatalytic degradation of two azo dye pollutants, methyl orange (MO) and methyl red (MR), under irradiation of visible light. The synthesis of Fe3O4@SiO2@Ru HMCs involves three stages, including synthesis of Fe3O4 magnetic microspheres (MMSs), followed by silica (SiO2) coating to get Fe3O4@SiO2 MMSs, and then incorporation of presynthesized Ru nanoparticles (~3 nm) onto the surface of Fe3O4@SiO2 HMCs. The synthesized HMCs were characterized by XRD, FTIR, TEM, EDS, XPS, BET analysis, UV-DRS, PL spectroscopy, and VSM to study the physical and chemical properties. Furthermore, the narrow band gap energy of the HMC photocatalyst is a significant parameter that provides high photocatalytic properties due to the high light adsorption. The photocatalytic activity of synthesized Fe3O4@SiO2@Ru HMCs was assessed by researching their ability to degrade the aqueous solution of MO and MR dyes under visible radiation, and the influence of various functional parameters on photocatalytic degradation has also been studied. The results indicate that the photocatalytic degradation of MO and MR dyes is more than 90%, and acid media favors better degradation. The probable mechanism of photodegradation of azo dyes by Fe3O4@SiO2@Ru HMC catalysts has been proposed. Furthermore, due to the strong ferromagnetic Fe3O4 core, HMCs were easily separated from the solution after the photocatalytic degradation process for reuse. Also, the photocatalytic activity after six cycles of use is greater than 90%, suggesting the stability of the synthesized Fe3O4@SiO2@Ru HMCs.

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.

The economic viability of adsorbing crystal violet (CV) using pepper seed spent (PSS) as a biosorbent in an aqueous solution has been studied. A parametrical investigation was conducted considering parameters like initial concentration of dye, time of contact, pH value, and temperature variation. The analysis of experimental data obtained was carried out by evaluating with the isotherms of Freundlich, Sips, Tempkin, Jovanovic, Brouers–Sotolongo, Toth, Vieth–Sladek, Radke–Prausnitz, Langmuir, and Redlich–Peterson. The adsorption kinetics were studied by implementing the Dumwald-Wagner, Weber-Morris, pseudo-first-order, pseudo-second-order, film diffusion, and Avrami models. The experimental value of adsorption capacity ( Q m = 129.4 mg g − 1 ) was observed to be quite close to the Jovanovic isotherm adsorption capacity ( Q m = 82.24 mg g − 1 ) at ( R 2 ), coefficient of correlation of 0.945. The data validation was found to conform to that of pseudo-second-order and Avrami kinetic models. The adsorption process was specified as a spontaneous and endothermic process owing to the thermodynamic parametrical values of Δ G 0 , Δ H 0 , and Δ S 0 . The value of Δ H 0 is an indicator of the process’s physical nature. The adsorption of CV to the PSS was authenticated from infrared spectroscopy and scanning electron microscopy images. The interactions of the CV-PSS system have been discussed, and the observations noted suggest PSS as a feasible adsorbent to extract CV from an aqueous solution.

Diclofenac is one of the most popular non-steroidal anti-inflammatory drugs (NSAIDs) which has been widely used worldwide. Despite its popularity, its accumulation in the environment poses danger to the aquatic lives and its removal from the environment is paramount important. Although some conventional adsorbents such as activated carbon can be readily used to address this issue, they usually suffer from low diclofenac adsorption capacity (around 200 mg g$^{−1}$), resulting in bulky adsorption systems. To overcome this problem, high performance materials such as metal organic frameworks (MOFs) can be employed. Here, we report that we synthesised defective MOF-801 for enhanced diclofenac adsorption via a simple and environmentally benign approach. Differing from a conventional MOF synthesis that usually requires the use of organic solvents at high temperature, the defective MOF-801 could be synthesised at room temperature and by changing the reaction medium from dimethylformamide to water. In addition, we have also successfully shown in this study that the defect concentration in MOF-801 can be rationally tuned by adjusting the modulator concentration (formic acid) in the synthesis solution. The resulting defective MOF-801 can then be used for environmental remediation, which we have shown here by employing them as an adsorbent for diclofenac removal from water streams. The enhanced adsorption of defective MOF-801 in comparison to its non-defective counterpart is due to the pore enlargement of the defective MOF-801 which provides a better pathway to access the adsorption sites. The maximum diclofenac adsorption capacity in a highly defective MOF-801 can reach as high as 680 mg g$^{−1}$, which is almost 4 times higher than its non-defective counterpart. This study then opens possibilities to engineer the MOF particles for environmental remediation.

NSGA-II is an evolutionary multi-objective optimization algorithm that has been applied to a wide variety of search and optimization problems since its publication in 2000. This study presents a review and bibliometric analysis of numerous NSGA-II adaptations in addressing scheduling problems. This paper is divided into two parts. The first part discusses the main ideas of scheduling and different evolutionary computation methods for scheduling and provides a review of different scheduling problems, such as production and personnel scheduling. Moreover, a brief comparison of different evolutionary multi-objective optimization algorithms is provided, followed by a summary of state-of-the-art works on the application of NSGA-II in scheduling. The next part presents a detailed bibliometric analysis focusing on NSGA-II for scheduling applications obtained from the Scopus and Web of Science (WoS) databases based on keyword and network analyses that were conducted to identify the most interesting subject fields. Additionally, several criteria are recognized which may advise scholars to find key gaps in the field and develop new approaches in future works. The final sections present a summary and aims for future studies, along with conclusions and a discussion.

Multi-scale analysis of turbulence-flame interaction is performed using experimental data sets from three methane- and propane-fired premixed, turbulent V-flames, at an approach flow turbulent Reynolds number of 450 and a ratio of r.m.s. fluctuating velocity from the mean to laminar flame speed of between 2.1 and 3.0, straddling the border between corrugated flamelets and thin reaction zone in the Borghi-Peters diagram. The measurements were made in the plane of a single laser sheet using stereo particle image velocimetry SPIV and planar laser-induced fluorescence to measure three orthogonal components of velocity and flame OH. Methods to approximate the remaining, unmeasured, out of plane derivatives are described. The instantaneous SPIV images were bandpass filtered at user-specified characteristic length scales Lω and Ls (for vorticity and strain rate, respectively) resulting in instantaneous bandpass-filtered velocity fields, u̲bLω and u̲bLs, which were further analysed to give the bandpass filtered vorticity field, ω̲Lω=∇×u̲bLω, the strain-rate field, eijLs, and the tangential strain rate field aTLs. This work quantifies two aspects of turbulence-flame interaction. The first aspect is that of the flame interaction of eddies of size Ls on the turbulence, as found by the statistics of the alignment of vorticity with strain rate. We find that vortical eddies with scale about Lω=2δth (where δth is the flame thickness) are stretched by Ls structures which are larger than about 2 Lω, with this factor broadly true also for vortical eddies of scales Lω=4δth and Lω=6δth. Within the limitations of the data set, these findings are consistent with those in the literature on reacting and non-reacting flows, suggesting that the premixed flame has had little influence on the vortex stretching mechanism. The second aspect of turbulence-flame interaction examined is that of flame surface-averaged tangential strain rate imparted by eddies. Eddies with length scales Ls smaller than 3 or 4δth are likely to have the strongest individual contribution but eddies of this length scale and smaller may contribute only about 1/5th of the total tangential strain rate. This is to be compared with the value of 10% that has been reported in the literature based on analysis of DNS predictions of premixed flames at turbulent Reynolds numbers up to 110. Eddies with length scale Ls larger than about 20δth contribute a negligible amount to the total tangential strain rate. We have found no evidence that the Lewis number up to about 1.8 has an observable effect, but this may reflect the limitations of the current experiment. In the context of large eddy simulations (LES) of premixed combustion, these results are preliminary experimental evidence supporting the suggestion that resolving turbulence scales down to a few multiples of δth might be adequate to capture much of the flame straining caused by turbulence.

Electrochemical CO2 reduction is a potential approach to manufacture carbon-neutral fuels and chemicals. To deploy CO2 electrolysis in the practical production of fuels and chemicals, energetically efficient electrolyzers are required. However, carbonate formation and the consequent CO2 crossover from cathodes to anodes cause unacceptable energy consumption, making the cost of CO2 electroreduction lower than the threshold for economic viability. Herein, we provide quantitative analyses of the impact of carbonate formation on the product costs of CO2 electroreduction products. Using the electrosynthesis of alcohols and ethylene as examples, we conducted techno-economic assessments (TEAs), and found that carbonate formation impacts the production costs of alcohols and ethylene by altering the costs of electrolyzer, CO2, and separation. Solving the carbonate formation issue reduces the production cost by 744-1696 USD per tonne, nearly equal to the market prices of the products. Finally, we conclude that inhibiting carbonate formation, together with improving reaction selectivity and productivity, would decrease the production costs by more than 90%.

Modelling of soot formation and oxidation of biodiesel fuels is a challenge, due to the complexity of the chemical reactions and soot formation pathways. In this paper, the discretised population balance approach and a PAH-HACA based detailed soot model have been coupled with an in-house CFD code to simulate a laminar diffusion flame with blends of different components of oxygenated biodiesel fuel, and employed to predict combustion performance and soot formation. The simulation aims to reproduce a target experiment which investigated the effects of dibutyl ether (DBE) addition to the biodiesel surrogate (methyl decanoate, MD) by increasing the mole fraction of DBE from 0 to 40%. A combined and reduced MD–DBE–PAH mechanism developed from three sub-mechanism branches has been employed in the simulation. The simulation results show that temperature rises as the DBE percentage increases to 40%. The swallow-tail shape of the soot occurrence zone and the quantity of soot production are correctly predicted. Regarding the effect of soot suppression, the model has basically captured the reducing tendency of soot formation in the measurements as the DBE addition increases from 0% to 40%. Concentrations of PAHs and C3 species contributing to the formation of aromatic rings are slightly reduced due to the addition of DBE, which is a leading cause of soot suppression. However, on the whole, the numerical solution featured much smaller differences than those observed in the experiment among laminar flames with different MD/DBE ratios, because the combined MD–DBE–PAH mechanism only present a slight difference of concentrations of soot precursor species.

Electroresponsive hydrogels possess a conducting material component and respond to electric stimulation through reversible absorption and expulsion of water. The high level of hydration, soft elastomeric compliance, biocompatibility, and enhanced electrochemical properties render these hydrogels suitable for implantation in the brain to enhance the transmission of neural electric signals and ion transport. This review provides an overview of critical electroresponsive hydrogel properties for augmenting electric stimulation in the brain. A background on electric stimulation in the brain through electroresponsive hydrogels is provided. Common conducting materials and general techniques to integrate them into hydrogels are briefly discussed. This review focuses on and summarizes advances in electric stimulation of electroconductive hydrogels for therapeutic applications in the brain, such as for controlling delivery of drugs, directing neural stem cell differentiation and neurogenesis, improving neural biosensor capabilities, and enhancing neural electrode-tissue interfaces. The key challenges in each of these applications are discussed and recommendations for future research are also provided. Accepted version

Hydrous iridium oxides (IrOx) are the best oxygen evolution electrocatalysts available for operation in acidic environments. In this study, we employ time-resolved operando spectroelectrochemistry to investigate the redox-state kinetics of IrOx electrocatalyst films for both water and hydrogen peroxide oxidation. Three different redox species involving Ir3+, Ir3.x+, Ir4+, and Ir4.y+ are identified spectroscopically, and their concentrations are quantified as a function of applied potential. The generation of Ir4.y+ states is found to be the potential-determining step for catalytic water oxidation, while H2O2 oxidation is observed to be driven by the generation of Ir4+ states. The reaction kinetics for water oxidation, determined from the optical signal decays at open circuit, accelerates from ∼20 to

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

It is challenging to measure the hydrodynamics of stirred tank reactors when they contain multiphase flows comprising liquid, gas bubbles and particles. Radioactive particle tracking techniques such as positron emission particle tracking (PEPT) are the only established techniques to determine internal flow behaviour due to the inherent opacity and density of fluid and the vessel walls. The profiles of solids flow are an important tool for robust reactor design and optimisation and offer insight into underlying transport processes and particle–fluid–bubble interactions for applications such as froth flotation. In this work, measurements with PEPT were performed with two tracer particles differing in surface hydrophobicity to characterise the solids hydrodynamics in a baffled vessel agitated with a Rushton turbine. The location data from PEPT were averaged with time to estimate the probability density function (PDF) of particle velocity in individual voxels. The peaks of these voxel distributions were used to produce profiles of solids flow in different azimuthal and horizontal slices. Bimodal vertical velocity distributions were observed in the impeller radial jet which suggest the particles experienced trajectory crossing effects due to inertia. Statistical tests were performed to compare the velocity distributions of the hydrophilic and hydrophobic tracer particles, which indicated similar average flow behaviour in the liquid or pulp phase of the vessel and differences near the air inlet, in the impeller discharge stream and pulp–froth interface. With tracers designed to represent gangue and valuable mineral species, the differences in velocity reveal interactions such as bubble–particle attachment and entrainment.

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

Chimeric Antigen Receptor (CAR)-T cell therapies are a type of patient-specific cell immunotherapy demonstrating promising results in the treatment of aggressive blood cancer types. CAR-T cells follow a 1:1 business model, translating into manufacturing lines and distribution nodes being exclusive to the production of a single therapy, hindering volumetric scale up. In this work, we address manufacturing capacity bottlenecks via a Mixed Integer Linear Programming (MILP) model. The proposed formulation focuses on the design of candidate supply chain network configurations under different demand scenarios. We investigate the effect of an intermediate storage option upstream of the network as means of: (a) debottlenecking manufacturing lines and (b) increasing facility utilisation. In this setting, we assess cost-effectiveness and flexibility of a decentralised supply chain and we evaluate network performance with respect to two key performance indicators (KPIs): (a) average production cost and (b) average response treatment time. The trade-off between cost-efficiency and responsiveness is examined and discussed.

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.

We report the speeds of sound in liquid toluene (methylbenzene) measured using double-path pulse-echo apparatus independently at The University of Western Australia (UWA) and Imperial College London (ICL). The UWA data were measured at temperatures between (306 and 423) K and at pressures up to 65 MPa with standard uncertainties of between (0.02 and 0.04)%. At ICL, measurements were made at temperatures between (283.15 and 473.15) K and at pressures up to 390 MPa with standard uncertainty of 0.06%. By means of thermodynamic integration, the measured sound-speed data were combined with initial density and isobaric heat capacity values obtained from extrapolated experimental data to derive a comprehensive set of thermodynamic properties of liquid toluene over the full measurement range. Extensive uncertainty analysis was performed by studying the response of derived properties to constant and dynamic perturbations of the sound-speed surface, as well as the initial density and heat capacity values. The relative expanded uncertainties at 95% confidence of derived density, isobaric heat capacity, isobaric expansivity, isochoric heat capacity, isothermal compressibility, isentropic compressibility, thermal pressure coefficient and internal pressure were estimated to be (0.2, 2.2, 1.0, 2.6, 0.6, 0.2, 1.0 and 2.7)%, respectively. Due to their low uncertainty, these data and derived properties should be well suited for developing a new and improved fundamental Helmholtz equation of state for toluene.

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.

One of the most crucial aspects of image segmentation is multilevel thresholding. However, multilevel thresholding becomes increasingly more computationally complex as the number of thresholds grows. In order to address this defect, this paper proposes a new multilevel thresholding approach based on the Evolutionary Arithmetic Optimization Algorithm (AOA). The arithmetic operators in science were the inspiration for AOA. DAOA is the proposed approach, which employs the Differential Evolution technique to enhance the AOA local research. The proposed algorithm is applied to the multilevel thresholding problem, using Kapur’s measure between class variance functions. The suggested DAOA is used to evaluate images, using eight standard test images from two different groups: nature and CT COVID-19 images. Peak signal-to-noise ratio (PSNR) and structural similarity index test (SSIM) are standard evaluation measures used to determine the accuracy of segmented images. The proposed DAOA method’s efficiency is evaluated and compared to other multilevel thresholding methods. The findings are presented with a number of different threshold values (i.e., 2, 3, 4, 5, and 6). According to the experimental results, the proposed DAOA process is better and produces higher-quality solutions than other comparative approaches. Moreover, it achieved better-segmented images, PSNR, and SSIM values. In addition, the proposed DAOA is ranked the first method in all test cases.

Neural network surrogate models are often used to replace complex mathematical models in black-box and grey-box optimization. This strategy essentially uses samples generated from a complex model to fit a data-driven, reduced-order model more amenable for optimization. Neural network models can be trained in Sobolev spaces, i.e., models are trained to match the complex function not only in terms of output values, but also the values of their derivatives to arbitrary degree. This paper examines the direct impacts of Sobolev training on neural network surrogate models embedded in optimization problems, and proposes a systematic strategy for scaling Sobolev-space targets during NN training. In particular, it is shown that Sobolev training results in surrogate models with more accurate derivatives (in addition to more accurately predicting outputs), with direct benefits in gradient-based optimization. Three case studies demonstrate the approach: black-box optimization of the Himmelblau function, and grey-box optimizations of a two-phase flash separator and two flashes in series. The results show that the advantages of Sobolev training are especially significant in cases of low data volume and/or optimal points near the boundary of the training dataset—areas where NN models traditionally struggle.

The integrity of coral reef ecosystems worldwide rests on a fine-tuned symbiotic interaction between an invertebrate and a dinoflagellate microalga from the family Symbiodiniaceae. Recent advances in bottom-up shotgun proteomic approaches and the availability of vast amounts of genetic information about Symbiodiniaceae have provided a unique opportunity to better understand the molecular mechanisms underpinning the interactions of coral-Symbiodiniaceae. However, the resilience of this dinoflagellate cell wall, as well as the presence of polyanionic and phenolics cell wall components, requires the optimization of sample preparation techniques for successful implementation of bottom-up proteomics. Therefore, in this study we compare three different workflows—filter-aided sample preparation (FASP), single-pot solid-phase-enhanced sample preparation (SP3), and stop-and-go-extraction tips (STAGETips, ST)—to develop a high-throughput proteotyping protocol for Symbiodiniaceae algal research. We used the model isolate Symbiodinium tridacnidorum. We show that SP3 outperformed ST and FASP with regard to robustness, digestion efficiency, and contaminant removal, which led to the highest number of total (3799) and unique proteins detected from 23,593 peptides. Most of these proteins were detected with ≥2 unique peptides (73%), zero missed tryptic peptide cleavages (91%), and hydrophilic peptides (&gt, 70%). To demonstrate the functionality of this optimized SP3 sample preparation workflow, we examined the proteome of S. tridacnidorum to better understand the molecular mechanism of peridinin-chlorophyll-protein complex (PCP, light harvesting protein) accumulation under low light (LL, 30 μmol photon m−2 s−1). Cells exposed to LL for 7 days upregulated various light harvesting complex (LHCs) proteins through the mevalonate-independent pathway, proteins of this pathway were at 2- to 6-fold higher levels than the control of 120 μmol photon m−2 s−1. Potentially, LHCs which were maintained in an active phosphorylated state by serine/threonine-protein kinase were also upregulated to 10-fold over control. Collectively, our results show that the SP3 method is an efficient high-throughput proteotyping tool for Symbiodiniaceae algal research.

Well-defined amphiphilic diblock copolymers and statistical copolymers were synthesised and investigated as polymeric surfactants. Specifically, two series of linear diblock copolymers-totaling 21 copolymers-were studied. In both series, the same hydrophobic monomer (ethyl methacrylate, EtMA) was used, whereas the hydrophilic monomer was changed. The first series was based on the non-ionic hydrophilic monomer, poly(ethylene glycol) methyl ether methacrylate (PEGMA, 300 g/mol), while the second series was based on the ionic, hydrophilic monomer, 2-(dimethylamino)ethyl methyl methacrylate (DMAEMA). The molar mass (MM) and compositions were systematically varied to investigate their effect on the final properties of the polymer. The aqueous solution properties of the copolymers, such as their cloud points, effective pKa values, hydrodynamic diameters, critical micelle concentrations and hydrophile-lipophile balances were determined. The hydrophobic content affected the thermoresponsive ability and the pKa of the polymer solutions significantly. Finally, the emulsifying properties of block copolymers were studied by preparing emulsions containing 1 w/w% of the polymer at the same water to methyl laurate ratio and observing their stability for 1 month. The stability of the emulsions was affected by both the MM and composition of the polymers, but to different extents for the non-ionic compared to the ionic series of polymeric macrosurfactants.

A new algorithm, Material Generation Algorithm (MGA), was developed and applied for the optimum design of engineering problems. Some advanced and basic aspects of material chemistry, specifically the configuration of chemical compounds and chemical reactions in producing new materials, are determined as inspirational concepts of the MGA. For numerical investigations purposes, 10 constrained optimization problems in different dimensions of 10, 30, 50, and 100, which have been benchmarked by the Competitions on Evolutionary Computation (CEC), are selected as test examples while 15 of the well-known engineering design problems are also determined to evaluate the overall performance of the proposed method. The best results of different classical and new metaheuristic optimization algorithms in dealing with the selected problems were taken from the recent literature for comparison with MGA. Additionally, the statistical values of the MGA algorithm, consisting of the mean, worst, and standard deviation, were calculated and compared to the results of other metaheuristic algorithms. Overall, this work demonstrates that the proposed MGA is able provide very competitive, and even outstanding, results and mostly outperforms other metaheuristics.

Advanced Therapy Medicinal Products (ATMPs) are a novel class of biological therapeutics that utilise ground-breaking clinical interventions to prevent and treat life-threatening diseases. At the same time, viral vector-based and RNA-based platforms introduce a new generation of vaccine manufacturing processes. Their clinical success has led to an unprecedented rise in the demand that, for ATMPs, leads to a predicted market size of USD 9.6 billion by 2026. This paper discusses how mathematical models can serve as tools to assist decision-making in development, manufacturing and distribution of these new product classes. Recent contributions in the space of process, techno-economic and supply chain modelling are highlighted. Lastly, we present and discuss how Process Systems Engineering can be further advanced to support commercialisation of advanced therapeutics and vaccines.

A method for forming electromagnetic waves with a tunable nonzero orbital angular momentum (OAM) is proposed. The approach is based on transforming an incident plane wave into a helical one using an electrically tunable ferroelectric lens. It uses high-resistive thin/thick film electrodes with a special discrete topology. The correlation between film electrodes topology and the highest order of OAM modes that the lens can form is described. A lens prototype based on Ba0.55Sr0.45TiO3 ferroelectric material and operating at a frequency of 60 GHz was designed, manufactured, and tested. The amplitude and phase distribution of the OAM wave with l = +1 formed by prototype were measured to confirm the effectiveness of the proposed method. The proposed lens has a combination of advantages such as low dimensions, electrical control over the OAM modes, and the possibility to operate in the millimeter wavelength range.