Purpose This review paper aims to focus on recent advances of carbon nanotubes (CNTs) to produce gas sensors. Gas sensors are widely used for monitoring hazardous gas leakages and emissions in the industry, households and other areas. For better safety and a healthy environment, it is highly desirable to have gas sensors with higher accuracy and enhanced sensing features. Design/methodology/approach In this review, the authors focus on recent contributions of CNTs to the technology for developing different types of gas sensors. The design, fabrication process and sensing mechanism of each gas sensor are summarized, together with their advantages and disadvantages. Findings Nowadays, CNTs are well-known materials which have attracted a significant amount of attention owing to their excellent electrical, electronic and mechanical properties. On exposure to various gases, their properties allow the detection of gases using different methods. Therefore, over recent years, researchers have developed several different types of gas sensors along with other types of sensors for temperature, strain, pressure, etc. Originality/value The main purpose of this review is to introduce CNTs as candidates for future research in the field of gas sensing applications and to focus on current technical challenges associated with CNT-based gas sensors.

This paper presents a novel optimization-based approach for the design of heat-integrated crude oil distillation units, which are widely used in refineries. The methodology presented combines, within a unified framework, surrogate distillation column models based on artificial neural networks, feasibility constraints constructed using a support vector machine, and pinch analysis to maximize heat recovery, in order to optimize the distillation column

The complex nature of crude oil distillation units, including their interactions with the associated heat recovery network and the large number of degrees of freedom, makes their optimization a very challenging task. We address here the design of a complex crude oil distillation unit by integrating rigorous tray-by-tray column simulation using commercial process simulation software with an optimization algorithm. While several approaches were proposed to tackle this problem, most of them relied on simplified models that are unable to deal with the whole complexity of the problem. The design problem is herein formulated to consider both structural variables (the number of trays in each column section) and operational variables (feed inlet temperature, pump-around duties and temperature drops, stripping steam flow rates and reflux ratio). A simulation-optimization approach for designing such a complex system is applied, which searches for the best design while accounting for heat recovery opportunities using pinch analysis. The approach is illustrated by its application to a specific distillation unit, in which numerical results demonstrate that the new approach is capable of identifying appealing design options while accounting for industrially relevant constraints.

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Rapid global COVID-19 pandemic response by mass vaccination is currently limited by the rate of vaccine manufacturing. This study presents a techno-economic feasibility assessment and comparison of three vaccine production platform technologies deployed during the COVID-19 pandemic: (1) adenovirus-vectored (AVV) vaccines, (2) messenger RNA (mRNA) vaccines, and (3) the newer self-amplifying RNA (saRNA) vaccines. Besides assessing the baseline performance of the production process, impact of key design and operational uncertainties on the productivity and cost performance of these vaccine platforms is quantified using variance-based global sensitivity analysis. Cost and resource requirement projections are computed for manufacturing multi-billion vaccine doses for covering the current global demand shortage and for providing annual booster immunisations. The model-based assessment provides key insights to policymakers and vaccine manufacturers for risk analysis, asset utilisation, directions for future technology improvements and future epidemic/pandemic preparedness, given the disease-agnostic nature of these vaccine production platforms.