To predict the solute concentration distribution (SCD) during continuous crystallization via a continuous oscillatory baffled crystallizer (COBC), a novel physics-informed neural network (PINN) based soft modelling method is proposed in this paper. By analyzing the sensitivity of solute concentration at the COBC outlet with respect to the main operating conditions (e.g., initial solution supersaturation ratio and liquid flow rate), a sensitivity analysis-based design of experiments (SA-DoE) is developed to generate informative data for model training, which can effectively reduce the number of experiments for implementation. Meanwhile, a pseudo twodimensional (2D) fluid kinetic model is built to reflect the relationship between the crystal velocity and liquid flow velocity during the continuous crystallization process via COBC, which can be effectively used in the PINNbased model building for predicting SCD. Simulation studies and experiments on the continuous crystallization process of beta form L-glutamic acid are conducted to demonstrate the effectiveness and advantage of the proposed modeling method.

Continuous oscillatory baffled reactors (COBRs) have been utilised in organic synthesis and crystallisation, however, no validation work has yet been conducted to determine if the fluid displacement caused by the oscillation at the start of the COBR is conserved at the end of the COBR. This work reports, for the first time, both experimental measurements and theoretical evaluations of the displacement. The experimental validation involves physically measuring the fluid displacement using a laser distance sensor located at the end of the COBR. Surprisingly, the measured displacement values at some operating conditions differ from the initial settings. The theoretical evaluation entails the determination of power dissipation across the COBR using the pressure measurements at four locations along the COBR. The model evaluated displacements agree well with the experimental measurements at all operational conditions, validating the methodologies used in this work.

Phosphatidylglycerol (PG) is a valuable product across pharmaceuticals, cosmetics and food industries, the conventional phospholipase D (PLD) syntheses however require organic solvents and very long reaction times to reach 50-74 % yield at millilitre scale. The novelty of this study is that we have developed a solvent-free, fully aqueous synthesis route of PG using PLD-catalysed transphosphatidylation of phosphatidylcholine (PC) with glycerol in a 250 mL oscillatory baffled reactor (OBR). By optimising temperature, PLD concentration, glycerol-to-PC ratio and mixing, we achieved 63.5 % PG conversion within 20 min with no detectable byproduct. Time-resolved kinetic analysis has revealed a three-phase mechanism in this reaction: an initial Michaelis-Menten behaviour, followed by product inhibition and eventual enzyme deactivation. We have then developed a multi-parameter kinetic model integrating intrinsic enzyme kinetics with operational variables, enabling quantitative predictions of reaction concentration, conversion and selectivity at high confidence level (R2>0.95). Coupling the green, solvent-free process with reactor intensification and mechanistic modelling establishes a scalable framework for PG manufacture and offers regulatory and sustainability advantages by avoiding volatile organic solvents and simplifying downstream processing.

For continuous crystallization of pharmaceutical and organic chemical compounds in a plug flow crystallizer, seed slurry, prepared in advance, is continuously fed into the crystallizer for controlled secondary nucleation and subsequently desired crystal properties. It is well known that the preparation of macro seed crystals using either the dry or wet method is a highly time-, energy- and material-intensive process, often taking many hours to prepare a 1 L seed slurry. The focus of this work is to examine whether how the seed slurry is made up could have any effect on the final crystal properties. We divide the seed slurry into two parts: the “saturation part” corresponds to the amount of solute required to establish solid–liquid equilibrium and is fully dissolved, and the “supersaturation part” involves a small amount of solid seed crystals in excess of the equilibrium saturation condition. The hypothesis states that if dissolved seed crystals have lost their surface properties (such as size, morphology, interfacial effects), the final crystal size distributions would then inherit that of the solid seed crystals. If this is true, this would provide a great and efficient shortcut for the lengthy and energy-intensive process of making up seed slurries, as product crystals from a previous batch of any size distribution could be used for the make-up of the saturation part of the seed slurry. Using adipic acid and L-glutamic acid with high and low solubilities, the hypothesis has been validated experimentally under batch conditions.

To address an open issue of sufficiently describing crystallization kinetics in a continuous oscillatory baffled crystallizer (COBC), a comprehensive kinetic modelling method is proposed in this paper, along with a steady-state optimization approach (SOA) for operating the COBC. Taking into account the axial dispersion of crystal quantity (ADCQ), velocity dispersion of crystal population (VDCP), and growth rate dispersion (GRD), a non-ideal plug flow micro-distribution model (NPF-MDM) is firstly established, which could be used to predict the crystal size distribution (CSD) and mean crystal size (MCS) in each zone of COBC. The model parameters are estimated by heterogeneous tracer experiments and continuous cooling crystallization (CCC) experiments in a real COBC named DN15. Based on the established NPF-MDM, an SOA is provided for operating the COBC. The tube length distribution across different temperature zones of COBC is optimized to determine the maximum attainable region of product MCS. By introducing an objective function related to the target crystal size and the CSD width of product crystals, a sensitivity analysis (SA) is presented to identify the critical operating conditions (COCs), including the seed recipe and net flow rate. Subsequently, the SA-based SOA is carried out. A growth optimizer algorithm is offered to solve the related nonconvex optimization problems. Experiments on the CCC of L-glutamic acid (LGA) via DN15 are performed to validate the proposed modelling and SOA.

A novel data-driven modeling and optimization method is proposed in this paper for cooling crystallization of l-glutamic acid (LGA) via a continuous oscillatory baffled crystallizer (COBC), based on the design of experiments (DoEs) for the main operating conditions of zone temperature setting and volume net flowrate. The crystal size distribution (CSD) can be effectively predicted by constructing a data-mapping model with double-layer basis functions, where the first layer is composed of wavelet basis functions for reshaping the steady-state CSD in each operating zone of COBC, and the second layer consists of polynomial basis functions for reflecting the nonlinear relationship between the above operating conditions and the corresponding CSD in each zone. Furthermore, a comprehensive cost function related to the desired crystal size, the distribution variance of product crystals and throughput is introduced to design an optimization method for the above operating conditions. A guaranteed convergence particle swarm optimization (GCPSO) algorithm is offered to solve the nonconvex optimization problem based on the established CSD prediction model. Experimental results on the continuous crystallization of LGA demonstrate that the above cost function and the desired crystal product yield can be improved over 23 % and 9 %, respectively, in comparison with all tests by DoEs.

The biological Power to Methane process (PtM) is gaining ground as an answer to the long-term renewable energy storage problem. Methane is an efficient hydrogen carrier, has an established worldwide transport infrastructure and can serve as a link between renewable power generation and a circular carbon economy. One of the defining factors regarding the scalability of the PtM process is the design of the reactor as it can determine the production rate / energy expenditure ratio. The tubular baffled reactor, a popular reactor design within the chemical industry has been assessed in the present study as a biomethanation reactor for the first time. The experiments were conducted with mixed cultures and the results point to high gas-liquid mass transfer capabilities as indicated by the methanation rates achieved (> 90% CH4 at 270 L/L/d mixed gas input rate). The gas/liquid flow ratio appears to have a stronger effect on methanation than the gas residence time. The working length of the reactor determines the pressure drop experienced by the culture, with higher pressure drops showing a negative correlation to methanogenesis.

By planting LEDs on the surfaces of orifice baffles, a novel batch oscillatory baffled photoreactor (OBPR) together with polymer-supported Rose Bengal (Ps-RB) beads are here used to investigate the reaction kinetics of a photo-oxidation reaction between α-terpinene and singlet oxygen (1O2). In the mode of NMR data analysis that is widely used for this reaction, α-terpinene and ascaridole are treated as a reaction pair, assuming kinetically singlet oxygen is in excess or constant. We have, for the first time, here examined the validity of the method, discovered that increasing α-terpinene initially leads to an increase in ascaridole, indicating that the supply of singlet oxygen is in excess. Applying a kinetic analysis, a pseudo-first-order reaction kinetics is confirmed, supporting this assumption. We have subsequently initiated a methodology of estimating the 1O2 concentrations based on the proportionality of ascaridole concentrations with respect to its maximum under these conditions. With the help of the estimated singlet oxygen data, the efficiency of 1O2 utilization and the photo efficiency of converting molecular oxygen to 1O2 are further proposed and evaluated. We have also identified conditions under which a further increase in α-terpinene has caused decreases in ascaridole, implying kinetically that 1O2 has now become a limiting reagent, and the method of treating α-terpinene and ascaridole as a reaction pair in the data analysis would no longer be valid under those conditions.

With the rapid development of novel photosensitizers/photocatalysts, photochemical transformation has become possible and practical. In this context, we report for the first time our work on testing and quantifying the durability and robustness of a heterogeneous photosensitizer, polymer-supported rose Bengal (Ps-RB) beads, in a model photo-oxidation reaction between α-terpinene and singlet oxygen (1O2). A novel photo reactor is used due to its capabilities of providing uniform suspensions of solid beads and uniform light distribution. We have proposed a methodology for quantifying the durability of the beads including the factors of loss of beads and the reduced product concentration. The results show that the durability of the Ps-RB beads has decreased by about 67% after five consecutive runs, and the half-life of the beads can be reached in less than 200 minutes. In addition, we have also identified the optimal bead mass in the novel photo reactor. Our work not only enriches the designs of new and better photosensitizers but also provides a comprehensive methodology for testing and validating photosensitizers.

In this paper we report our kinetic study of an oxidation reaction from valencene to nootkatone using enzyme in an oscillatory baffled reactor. The aims of this work are to elucidate the reaction mechanism and evaluate reaction kinetics. Towards these objectives, a full kinetic model using the Langmuir–Hinshelwood method was established and applied to the experimental data, allowing reactor schemes and orders to be confirmed and reaction rate constants to be extracted. Our full kinetic analysis suggests that most of the reversible reaction steps can be treated as irreversible, simplifying the overall reaction schemes. The effect of mass transfer on the kinetics was also investigated. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).

For using the continuous oscillatory baffled crystallizer (COBC) to conduct cooling crystallization of β form L-glutamic acid (LGA), a prediction model of crystal product size distribution and an optimization method of process operation conditions are proposed in this paper, based on the design of experiment. The oscillation frequency and cooling rates of front two zones of the COBC are taken as the input conditions to design a 3-factor and 3-level Box-Behnken experimental scheme. A prediction model of crystal product size distribution based on double-layer basis functions is constructed by examining the chord length distribution of crystal products under different experimental conditions. Then an objective function on the target crystal size distribution and product yield is introduced to establish an optimization method on the process operating conditions, based on the above prediction model. The effectiveness and advantages of the proposed method are verified by simulation and experiments on the continuous cooling crystallization process of p form LGA.

In this paper, an extended sectional quadrature method of moments (ESQMOM) is proposed to describe the kinetics of crystal growth and nucleation process, since the existing SQMOM could only be used for crystal aggregation and breakage process. A modified expression of particle number density is established with respect to the boundary nodes of all sections divided in the particle size range, and meanwhile, an interval merging strategy is developed to tackle the problem arising from particle flux flow between sections due to the crystal growth mechanism, such that moments could be predicted more precisely compared to the existing methods. Correspondingly, improved prediction of crystal size distribution (CSD) could be obtained. Based on these estimated moments, a multi-objective optimization algorithm is given to further improve estimation on the kinetic parameters of 0 form L-glutamic acid (0-LGA) cooling crystallization process. Simulation results on benchmark examples and experiments on seeded cooling crystallization of 0-LGA are given to illustrate the effectiveness and merits of the proposed method. (c) 2022 Elsevier Ltd. All rights reserved.

Experimental and numerical characterizations of flow in continuous oscillatory baffled reactors (COBR) have mainly been based on single phase in past decades. By coupling a primary Eulerian liquid phase with a secondary discrete Lagrangian phase consisting of solid particles of given density and size, this work investigates the effects of particle size on axial dispersion, evaluates residence times and velocities of particles, and quantifies the oscillation dampening caused by the presence of solid particles in a COBR.

In this paper, we report, for the first time, that a multiphase catalytic hydrogenation of 3-butyn-2-ol over Pd/Al2O3 catalyst has successfully been running in a continuous oscillatory baffled reactor (COBR) for over 12 h. Catalyst stability and attrition were examined, the results show that there was no catalyst loss for the whole duration of operation, the catalyst was stable for 9 h with 97% selectivity at a target conversion of 95%. Catalyst deactivation thereafter was assessed at a rate of 0.03% per h, this means that it would take 17 days (or 2040 cycles) of operation to achieve 50% of the target conversion. This is significantly better than the corresponding batch operation where half catalyst activity was reached after 32 cycles. In addition, one of the advantages of using COBR is that it allows the screening of several operational parameters in a single reaction run, as the steady state of operation was readily attained within 1 to 1.5 residence times.

An in situ measurement method is proposed for monitoring three-dimensional (3D) crystal size distribution (CSD) during a crystallization process, based on a binocular microvision system. The stereo particle shape is reconstructed from doubleview images captured by two microscopic cameras fixed at different angles outside the crystallizer. To overcome the influence from solution turbulence and uneven illumination background involved with in situ imaging, a microscopic double-view image analysis method is established to identify the key corners of each particle shape in the captured images, including corner detection and corner matching. Two fast algorithms are therefore given for online detection of two typical crystal morphologies of prismatic and needle-like shapes, such as alpha- and beta-forms of L-glutamic acid (LGA) crystals, respectively. On the basis of the identified key corners for different particle shapes, a 3D geometry model is established to approximately reconstruct the 3D shape for each imaged particle, such that 3D sizes of each particle could be quantitatively estimated, along with the particle volume. Experiments on the LGA cooling crystallization are performed to demonstrate the effectiveness of the proposed method.

In this paper, a cell average technique(CAT) based parameter estimation method is proposed for cooling crystallization involved with particle growth, aggregation and breakage, by establishing a more efficient and accurate solution in terms of the automatic differentiation(AD) algorithm. To overcome the deficiency of CAT that demands high computation cost for implementation, a set of ordinary differential equations(ODEs) entailed from CAT based discretized population balance equation(PBE) are solved by using the AD based high-order Taylor expansion. Moreover, an AD based trust-region reflective(TRR) algorithm and another interior-point(IP) algorithm are established for estimating the kinetic parameters associated with particle growth, aggregation and breakage. As a result, the estimation accuracy can be further improved while the computation cost can be significantly reduced, compared to the existing algorithms. Benchmark examples from the literature are used to illustrate the accuracy and efficiency of the AD-based CAT, TRR and IP algorithms in comparison with the existing algorithms. Moreover, seeded batch cooling crystallization experiments of β form L-glutamic acid are performed to validate the proposed method.

Hydrogenation often involves three phases where hydrogen-on-demand is the typical mode of operation in industrial scale reactors. In research labs and publications, however, continuous hydrogen flow has been used. This paper investigates the effect of such modes of operation on reaction rate using a selective hydrogenation of 3-butyn-2-ol over Pd/Al2O3 to obtain 3-buten-2-ol as the model reaction. The two modes of operation were first tested in a commercial PARR stirred tank reactor and then repeated in an oscillatory baffled reactor (OBR) in order to validate the experimental results. Our investigation demonstrates that an enhanced reaction performance and 10 times better H-2 efficiency were obtained when the pressure was maintained constant during the reaction by feeding gas as required, ie hydrogen-on-demand mode. The method of a continuous flow of hydrogen in hydrogenation means that excess hydrogen is vented out when operating at ambient pressures or builds up at elevated pressures. Our work also enables a comparison of reactor designs on reactor performance, and three times higher H-2 efficiency and 2.3 times shorter residence time were achieved when using the OBR instead of the PARR due to its enhanced and uniform mixing, regardless of the mode of operation.