Band 10, Heft 1-2

Solar energy has become a vital source for generating and harvesting electricity. Enhancing the efficiency of solar modules is an essential factor for successful transition to a sustainable and green energy production. Since natural fiber composites (NFCs) possess various outstanding properties, they can be used as an adequate alternative to synthetic fibers and environmentally harmful materials that are used in photovoltaic (PV) applications and module components. Solar modules are believed to undergo a decline in efficiency when exposed to excessive sun radiation, which eventually caused by a gradual escalation in temperature. Therefore, utilizing appropriate NFCs in the rear components and backsheets of solar modules could significantly contribute to the overall efficiency of these modules and enhance their thermal stability.

This chapter provides an overview of the principles and modelling of membrane-based modules for haemodialysis, the most common renal replacement therapy. Following an introduction on the structure, function and diseases of the kidney, the technological evolution of membranes for blood purification is outlined and the main transport mechanisms involved are described, making a distinction between pure haemodialysis, haemodiafiltration and haemofiltration. The main performance figures of a hollow-fiber module are introduced and their dependence on the parameters that characterize the device is illustrated. A multi-scale modelling approach is then presented, in which preliminary single-fiber CFD simulations are used to derive the hydraulic permeability of a fiber bundle and the relevant mass transfer coefficients as functions of the local velocities. The predicted correlations are then fed to a module-scale model, in which blood and dialysate compartments are simulated as interpenetrated porous media while appropriate source terms account for the exchange of solutes and water between the two fluids. The model predictions are three-dimensional flow and concentration distributions, from which, in particular, performance figures such as clearance and ultrafiltration flow rate can be extracted as functions of the module geometrical and physical characteristics. Validation tests are also presented and the results of a parametrical sensitivity assessment are discussed.

The liver, our body’s chemical factory, is central to metabolism, homeostasis, and detoxification. The advent of systems biology and computational modelling has revolutionised our understanding of the liver system and its diseases. This chapter focuses on the application of computational modelling, specifically a kinetic model of fructose metabolism, to explore the relationship between fructose and liver disease progression. We begin by reviewing the fundamental aspects of liver anatomy and physiology, setting the stage for an in-depth discussion on the alarming crisis of metabolic dysfunction-associated steatotic liver disease (MASLD). Through a specific case study, we provide insights into the metabolic events triggered by fructose intake and illustrate how computational models can predict disease progression and identify potential therapeutic targets, paving the way for personalised treatment plans. The chapter concludes by discussing the challenges and future directions in the field, emphasising the transformative potential of engineering principles in medicine.

Quantitative systems pharmacology (QSP) is a discipline that integrates experimental and mathematical modelling practice to perform a variety of analysis in the pharmaceutical research and development space. As the pharma industry strives for leaner product development, reduction of time and costs, and the implementation of the personalized medicine ambition, modeling and simulation approaches are recognized as pivotal components to achieve these goals. Since there are notable similarities between chemical engineering modelling approaches and those of QSP, our aspiration for this chapter is setting the stage for further contribution by engineers in this space. To this end, we provide a concise overview of the various modelling applications currently employed across the pharmaceutical research and development value chain. We then focus on QSP, detailing specific research areas that benefit from its use, the relevant mathematical modelling techniques, and emphasizing its parallels with chemical engineering modelling. Finally, we illustrate two concrete examples of QSP applications in oncological drug development.

Modeling drug release in solid tumors is a convergence point between chemical engineering and medicine. Consequently, many studies have been conducted to unravel the mechanisms behind drug distribution after administration. In addition, several approaches have been explored, ranging from pharmacokinetic and pharmacodynamic models to microscopic transport models through macroscopic transport models. This chapter focuses on the latter, macroscopic transport models, and discusses how these models can predict the processes involved in drug delivery, in free form or vehicle transported. We start by presenting some of the differentiating physiological parameters in cancer tissues and then the main equations used for modeling, including fluid flow, mass transport, and cell uptake. Also, the use of some dimensionless parameters explaining the processes that control transportation will be examined. Lastly, the final section will explore the process employed for building geometries to simulate solid tumors, as well as current research being conducted on patient-specific simulations made using medical images.

Indigenous science is fast becoming a pathway to teach the principles of sustainability and green science or green chemistry towards sustainable development, management and conservation of the world’s ecosystems for posterity. This study sought to explore students’ own ideas about sustainability and ‘green’ practices through the indigenous multi-stage production of palm oil. A case study that employed a mixed method approach engaged 86 purposively chosen pre-service teachers. Questionnaires that partly allowed for participants to share their own ideas about palm oil production with respect to sustainability and green practices were used to collect data. Findings from analysed data indicated a positive shift in attitude, knowledge and views towards sustainability and green science practices in their communities as against their entry point.

This study is the simulation of several forms of the most recent Field Effect Transistor (FET) and its electrical characteristics and designed using nanomaterials. The best FET to employ for sensor design in biomedical applications has been determined based on many examples and investigations. In order to overcome the difficulties of detecting disease-causing antigens, FET-based biosensors have been developed to increase sensitivity to disease-causing antigens at the micro- and nanoscale. To find the best transistor, various transistor types with various material layers are introduced. The sensor array consists of 64 cells, arranged into three categories – core, periphery, and middle – designed to enhance the sensitivity of cell detection. Three reference voltages are produced by a current reference circuit to bias the bottom gates of the CNTFETs, which generate maximum current in response to electrostatic changes at the top gate. These voltages are then processed to determine the concentration of the analyte, with the sensor array achieving a sensitivity of 130 μA/V. In NANOHUB.ORG (online Tool), all simulations are run, and performance is displayed in the form of simulation results, graphs, and tables.

Growing concerns over our dependence on finite, non-renewable resources like petroleum and metals have driven the development of eco-friendly technologies centered on advanced hybrid nanomaterials. Among these, the use of renewable nanocellulose – ranging in size from 1 to 100 nm – has gained significant attention in nanotechnology research. Derived from sustainable sources, nanocellulose offers notable advantages; however, challenges persist when integrating it with metal oxide nanoparticles (MONPs). These challenges include high reactivity in cellular environments, elevated production costs, and a tendency to aggregate, leading to instability in both liquid and dry states. Aggregation can impair uniform dispersion and result in sediment formation in certain applications. A promising solution to these challenges is hybridizing MONPs with functionalized nanocellulose, a method widely adopted by researchers. This approach is cost-effective, environmentally sustainable, and produces a renewable material with low density, excellent stability, superior mechanical properties, and biocompatibility. However, several questions remain unresolved, such as the most commonly used functionalization techniques for MONPs hybridization, the underlying mechanisms, and the specific benefits of this hybridization. Based on current findings, oxidation and carboxymethylation emerge as the most frequently used functionalization techniques for hybridizing MONPs with nanocellulose. These processes introduce carboxylic acid and carboxymethyl groups, respectively, which act as capping agents that readily bond with MONPs. This results in high degrees of substitution (DS) and improved nanoparticle dispersion. Furthermore, hybridization enhances properties such as thermal stability, UV protection, antibacterial activity, adsorption capacity, and mechanical performance, underscoring its potential for diverse applications.

This review provides insight on how the application of core chemical engineering concepts helps with current challenges in dermal permeation research from a mathematical modelling perspective. The skin fundamentally behaves like a diffusion reactor, where mass conservation featuring Fick’s diffusion flux can be applied to obtain the differential equations that govern the permeation of a chemical compound. Advanced phenomena like systemic circulation or complex thermodynamics can be added mathematically into the models to complement the diffusion equation. Depending on research objectives, the reach of these mechanistic continuum mechanics models can: i) consider the skin as a homogeneous compartment, where spatial dependency is overlooked, or ii) include detailed spatio-temporally-discretised geometric descriptions of complex features like the bricks-and-mortar layout of the stratum corneum. The capabilities of this powerful approach to study advanced topics in dermatological research are discussed. These include topics such as the role of the hair follicle as a shortcut to bypass the stratum corneum, the effect of evaporation during the application of multicomponent formulations, and the facilitation of skin permeation by means of external forces (i.e., electromagnetic fields and mechanical action). The chapter closes with a note on current challenges towards the future development of mechanistic skin Digital Twins, which are gaining further importance of late to avoid animal experimentation in dermatological research.

Environmental impact evaluation across a product’s complete journey is achieved through Life Cycle Assessment (LCA), a systematic approach that examines each stage from beginning to end. This methodology considers everything from obtaining initial materials to final disposal, including manufacturing processes, distribution networks, consumer usage, and end-of-life handling through recycling or waste management. The goal is to comprehend the overall environmental footprint. Several challenges hinder the adoption of bio-fiber composites in the energy sector, despite their environmental advantages. This chapter identifies key challenges, such as inefficiencies in raw material extraction, high energy consumption during production, and waste management issues during disposal. The objective is to outline the principles of LCA, review recent research, and propose technological and policy solutions to address these challenges. Case studies from various energy sectors are also examined. In conclusion, the chapter emphasizes the significance of ongoing research and development to enhance the lifecycle sustainability of natural fiber composites. The analysis reveals key information that helps drive the shift to environmentally friendly and renewable energy solutions.