Journal of advanced manufacturing and processing最新文献

As the occurrences of cancer rise and the requirement for biotherapeutics increases, there is a growing demand for cost-efficient methods to manufacture mammalian cell-based biopharmaceuticals. Currently, the most cost-efficient manufacturing solution is the cultivation of cells in perfusion mode. Perfusion allows for high cell densities of up to 200 million viable cells per mL (MVC mL⁻¹) to be achieved, resulting in an increase in yield and volumetric productivity, which is the production of product per unit volume and time. However, culturing in perfusion mode requires large volumes of media, which is a significant expense in process development. Therefore, methods that allow rapid optimization of perfusion media are desirable to decrease operating costs and increase productivity. In this work, a quasi-perfusion methodology using microwell plates (MWP) is used for media optimization to culture CHO-S cells producing IgG1 monoclonal antibodies (mAb) known as trastuzumab, which have clinical applications treating HER2+ breast cancer. Results show blending glucose-rich supplements and sodium butyrate with perfusion-specific base media can lead to an 8-fold increase in monoclonal antibody titre compared with traditional fed-batch media. The original and optimized media were then scaled-up to a custom made, mini bioreactor (MBR) running in perfusion mode. Two-fold higher cell density is achieved in the MBR compared with the MWP, however, when normalizing for cell density, mAb productivity is comparable between the two methodologies. The combined MWP and 250 mL MBR methodology is an optimization tool that enables process development cost savings due to reduced volume of media utilization.

This paper investigates the model performance of an industrial box used to remove ammonia from the air using a doped activated carbon. To this end, process models are developed and experimental measurements are carried out. The models are based on momentum and mass balance equations along with thermodynamic, hydrodynamic and adsorption kinetic relations. The measurements consist of pressure drops in the air purification box and breakthrough curves of ammonia on activated carbon. The models are implemented and solved using COMSOL Multiphysics®. Adsorption is investigated by means of a Fickian multi-scale model, which demonstrated to efficiently predict the experimental data. The optimal values of the most estimable unknown parameters involved in each model, as well as their confidence intervals are determined from experimental measurements. The performance of the industrial air purification model is rigorously assessed using statistical criteria, including mean-square error (RMSE = 0.0013) and Pearson correlation coefficient (r = 0.999).

Predicting the separation performance of decanter centrifuges is challenging due to dynamic events within the apparatus. Current methods for designing decanter centrifuges rely on simplified models, often leading to inaccuracies. Consequently, manufacturers must perform time-intensive pilot scale experiments to derive their own correction factors. Growing computing power sparks interest in alternative modeling strategies. Grey box models (GBM) combine mechanistic white box models (WBM) and data-driven black box models (BBM), with the optimal structure (parallel or serial) varying by application. For modeling decanter centrifuges, we propose a serial GBM that comprises an artificial neural network that outputs unknown material parameters into a first-principle multi-compartment model. Comparing this approach to alternative data-driven modeling strategies (pure BBM, parallel GBM), we conclude that the serial GBM excels in terms of extrapolation, prediction ability, and transparency while also enabling a better comprehension of the separation process.

Promising forward osmosis (FO) membrane desalination is a potentially viable energy-efficient performance technology compared to other techniques. Searching for the ideal draw solute that creates high osmotic pressure difference and ease of regeneration is critical for water desalination using the FO system. However, many fundamental aspects still need to be adapted, such as needing more screening potential anions and cations based on the predictive method. The Group Contribution Method (GCM) was used in this study to predict the value of the van't Hoff factor denoted by (i). In the end, 1-butyl-3-methylimidazolium tetrafluoroborate ([C₄C₁im][BF₄]) was selected as a draw solution for later experimental work.

In this work, we used a previously described computational fluid dynamics (CFD) model of a roll-to-roll coating process for the fabrication of thin-film composite membranes to predict the final coating thickness for PolyActive™, a commercially available multiblock copolymer utilized for CO₂ removal membranes. We found a strong thickening effect that could not be explained by our previous model. We investigated the process experimentally. In addition, we conducted a variety of simulations with extensions of the initial CFD model. Based on our findings, we conclude that the Marangoni effect, that is, gradients of surface tension that induce secondary flow patterns in the meniscus region, is the most likely source of the observed thickening. We explain the simulation results in order to understand the physical mechanisms at play and to show how especially surface tension gradients that arise from the particular flow structure in the meniscus may explain the additional transfer of polymer solution to the membrane. Finally, we draw some conclusions on future research and give ideas on future improvements of the process. To our knowledge, Marangoni effects for the coating of PolyActive™ were not described so far in the literature, even though it is a well-known polymer for gas separation membranes targeted at CO₂ removal. Roll-to-roll coating is a well-established coating method and often believed to be suitable for the scale-up of membrane production, therefore we think that this work will help membrane researchers who are using similar coating devices to be cautious about possible complications in the process.

This paper revisits the economics of manufacturing N-ethylcarbazole (NEC), a strong candidate for large-scale liquid organic hydrogen carrier (LOHC) supply chains, because of its high H₂ storage capacity (6 wt%), selective hydrogenation and dehydrogenation reactions, and favorable reaction enthalpy and reaction temperatures compared to other LOHC systems. Two different process routes for producing NEC from industrial chemicals are selected out of 10 possible options: one using aniline and the other using cyclohexanone and nitrobenzene as feedstock. The required capital and operational costs are estimated to determine a NEC break-even cost for a capacity of 225 ktpa. NEC break-even costs of $3.0 and $2.6 per kg LOHC are found for the routes. This is significantly less than the $40/kg cost that has generally been reported in literature for NEC, thus improving the economic viability of using NEC as LOHC. The total fixed capital costs are estimated to be $200 MM and $250 MM. Furthermore, the prices of the feedstock show the largest influence (76% and 72%) on the final NEC break-even costs. The overall LOHC price contribution to the levelized H₂ cost is estimated to be $0.77–$0.90 per kg H₂ for a 60-day roundtrip and $0.09–$0.10 per kg H₂ for a 7-day roundtrip. It is important to note that both routes rely heavily on laboratory scale data and the corresponding assumptions that stem from this limitation. Therefore, this research can serve as a guide to future experimental studies into validating the key assumptions made for this analysis.

Chemical companies have used modularization to reduce capital costs and project timelines, putting capital to work faster and lowering the risk of entering new markets. Nevertheless, the impacts of using modularization along with advanced technologies, such as process intensification, have not yet been fully realized, often due to the uncertain business risks associated with their implementation. Therefore, new methods are needed for quantifying the impact of modular chemical process intensification (MCPI) on the capital and operating costs of chemical plants to help build a business case for this novel approach. This article presents a new conceptual range estimation technique for total cost of ownership that addresses the deficiencies of existing methods for quantifying MCPI impacts. The incorporation of percentage range estimates was employed to allow for adaptability across various cost and size scales. This work also begins to elucidate how chemical engineering and construction firms can benefit from MCPI and identifies barriers that inhibit MCPI applications in the chemical industry.

In this commentary, we discuss the concept of an elliptical economy as opposed to a circular economy. The change of shape emphasizes that the duration of the different phases of the lifecycle is often different and so the implications for the lifecycle may be important.