Seeking Genuine Vocations through Sustainability in Chemical Engineering

Sustainability in education is essential in raising awareness among pupils regarding the interconnected global challenges that we are facing and, at the same time, cultivating and transforming their mindsets to embrace and adopt sustainable lifestyles. In particular, college students who might briefly encounter sustainability issues during their courses of study would bring their values and attitudes regarding sustainability into their future workplace and beyond. In this article, we focus on sustainability in engineering education at the tertiary level, particularly in chemical engineering, and reveal how these potential engineers could seek genuine vocations when choosing their careers without compromising sustainability. The article begins with a description of what constitutes chemical engineering and its branches in plain language. It then outlines what to expect when one enrolls in a chemical engineering program as an undergraduate or graduate student. This includes the core subjects to obtain, skill sets to master, and other essential expertise that could be useful in the workplace. Since chemical engineering is one of the disciplines where the paradox of improving and impairing is conspicuous, it is also essential to delve deeper into the sustainability facet of the field, specifically in higher education. The discussion continues with career options for enthusiastic chemical engineers and how these young and early-career graduates could discover their reason for well-being and life purpose as aspiring chemical engineers, while at the same time maintaining and enhancing the sustainability in their vocations.

Variability of complex oscillatory regimes in the stochastic model of cold-flame combustion of a hydrocarbon mixture

Processes of the cold-flame combustion of a mixture of two hydrocarbons are studied on the base of a three-dimensional nonlinear dynamical model. Bifurcation analysis of the deterministic model reveals mono- and bistability parameter zones with equilibrium and oscillatory attractors. For this model, effects of random disturbances in the bistability parameter zone are studied. We show that random forcing causes transitions between coexisting stable equilibria and limit cycles with the formation of complex stochastic mixed-mode oscillations. Properties of these oscillatory regimes are studied by means of statistics of interspike intervals. A phenomenon of anti-coherence resonance is discussed. This article is part of the theme issue 'Transport phenomena in complex systems (part 2)'.

In silico model-based inference: an emerging approach for inverse problems in engineering better medicines

Identifying the network of biochemical interactions that underpin disease pathophysiology is a key hurdle in drug discovery. While many components involved in these biological processes are identified, how components organize differently in health and disease remains unclear. In chemical engineering, mechanistic modeling provides a quantitative framework to capture our understanding of a reactive system and test this knowledge against data. Here, we describe an emerging approach to test this knowledge against data that leverages concepts from probability, Bayesian statistics, and chemical kinetics by focusing on two related inverse problems. The first problem is to identify the causal structure of the reaction network, given uncertainty as to how the reactive components interact. The second problem is to identify the values of the model parameters, when a network is known a priori.

Solution of Chemical Master Equations for Nonlinear Stochastic Reaction Networks

Stochasticity in the dynamics of small reacting systems requires discrete-probabilistic models of reaction kinetics instead of traditional continuous-deterministic ones. The master probability equation is a complete model of randomly evolving molecular populations. Because of its ambitious character, the master equation remained unsolved for all but the simplest of molecular interaction networks. With the first solution of chemical master equations, a wide range of experimental observations of small-system interactions may be mathematically conceptualized.

A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12

Monoclonal antibodies represent some of the most promising molecular targeted immunotherapies. However, understanding mechanisms by which tumors evade elimination by the immune system of the host presents a significant challenge for developing effective cancer immunotherapies. The interaction of cancer cells with the host is a complex process that is distributed across a variety of time and length scales. The time scales range from the dynamics of protein refolding (i.e., microseconds) to the dynamics of disease progression (i.e., years). The length scales span the farthest reaches of the human body (i.e., meters) down to the range of molecular interactions (i.e., nanometers). Limited ranges of time and length scales are used experimentally to observe and quantify changes in physiology due to cancer. Translating knowledge obtained from the limited scales observed experimentally to predict patient response is an essential prerequisite for the rational design of cancer immunotherapies that improve clinical outcomes. In studying multiscale systems, engineers use systems analysis and design to identify important components in a complex system and to test conceptual understanding of the integrated system behavior using simulation. The objective of this review is to summarize interactions between the tumor and cell-mediated immunity from a multiscale perspective. Interleukin-12 and its role in coordinating antibody-dependent cell-mediated cytotoxicity is used illustrate the different time and length scale that underpin cancer immunoediting. An underlying theme in this review is the potential role that simulation can play in translating knowledge across scales.