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Recently, graph-theoretic methods have increasingly been employed to generate near-best (n-best) heat recovery networks, aiming to maximize energy recovery efficiency. The exploration of these n-best networks has proven pivotal for making informed decisions. Nevertheless, existing studies in this domain have not attempted to study the favourability of these generated networks based on their respective dynamic control performance. This performance metric reflects the network’s ability to maintain target temperature even under disturbances. The network topologies play important role in both economic (i.e., total annual cost (TAC)) and dynamic control aspects. To address this gap, this work introduces a hybrid approach. First, all combinatorically feasible heat recovery networks are generated using P-HENS. Thereafter, each network undergoes dynamic control performance evaluation through Aspen Plus simulations. The final step involves optimization of the network structures based on fuzzy method which avoids over-prioritization. To illustrate the efficacy of the proposed methodology, it is applied to solve a 5-stream problem. Results showed that Network A with the least TAC ($122,249) is not necessarily associated with the greatest dynamic performance (with failure rate of 15 %). Network C which offers the balance performance (with TAC of $122,666 and failure rate of 0 %) is chosen.

This study demonstrates the successful integration of process simulation using CHEMCAD into Sunway University's Chemical Engineering Thermodynamics curriculum, replacing the traditional lab sessions. This approach has two main benefits, i.e., it provides early exposure to process simulation software, bridging theory and practice, and it supports new chemical engineering programs where labs may not be fully operational. Aligned with Sunway University's commitment to innovative educational approaches, the impact of this integration on the students’ learning experiences is evident through feedback collected from a comprehensive survey conducted with a group of seven students enrolled in Chemical Engineering Thermodynamics in April 2023. The survey's three sections gathered the students’ perceptions, enjoyed aspects, challenges faced, and suggestions. Findings highlight the students’ positive views on the integration, enhancing comprehension of thermodynamics concepts and real-world applications. They also recognized the value of hands-on simulation experience for essential process simulation skills. The students appreciated the practical relevance in highlighting thermodynamics’ real-world importance. Challenges related to software access and technical issues were addressed, with planned improvements. The students expressed interest in deeper learning, including complex simulations, graphical representation use, and external resource access. While many found the integration effective, suggestions for more hands-on engagement and research resource access were noted.

This perspective article highlights our opinions on the imperative of incorporating Process Intensification (PI) into undergraduate chemical engineering education, recognizing its pivotal role in preparing future engineers for contemporary industrial challenges. The trajectory of PI, from historical milestones to its significance in advancing the United Nations’ Sustainable Development Goals (SDGs), reflects its intrinsic alignment with sustainability, resource efficiency, and environmental stewardship. Despite its critical relevance, the absence of dedicated PI courses in numerous undergraduate chemical engineering programs presents an opportunity for educational enhancement. An exploration of global PI-related courses reveals the potential of educational platforms to fill this void. To address this gap, we advocate for the introduction of a standalone PI course as a minor elective, minimizing disruptions to established curricula while acknowledging the scarcity of PI expertise. The challenges associated with PI integration encompass faculty workload, specialized expertise, curriculum content standardization, and industry alignment. Surmounting these challenges necessitates collaborative efforts among academia, industry stakeholders, and policymakers, emphasizing the manifold benefits of PI, faculty development initiatives, and the establishment of continuous improvement mechanisms. The incorporation of PI into curricula signifies a transformative approach, cultivating a cadre of innovative engineers poised to meet the demands of the evolving industrial landscape.

This paper explores the integration of large language models (LLMs), such as ChatGPT, in chemical engineering education, departing from conventional practices that may not be universally accepted. While there is ongoing debate surrounding the acceptance of LLMs, driven by concerns over computational instability and potential inconsistencies, their inevitability in shaping our communication and interaction with technology cannot be ignored. As educators, we are positioned to play a vital role in guiding students toward the responsible, effective, and synergetic use of LLMs. Focusing specifically on distillation column design in undergraduate mass-transfer courses, this study demonstrates how ChatGPT can be utilized as an auxiliary tool to create interactive learning environments and simulate real-world engineering thinking processes. It emphasizes the need for students to develop critical thinking skills and a thorough understanding of LLM principles, taking responsibility for their use and creations. While ChatGPT should not be solely relied upon, its integration with fundamental principles of chemical engineering is crucial. The effectiveness and limitations of ChatGPT are exemplified through two case studies, showcasing the importance of manual calculations and established simulation software as primary tools for guiding and validating engineering results and analyses. This paper also addresses the pedagogical implications of integrating LLMs into mass transfer courses, encompassing curriculum integration, facilitation, guidance, and ethical considerations. Recommendations are provided for incorporating LLMs effectively into the curriculum. Overall, this study contributes to the advancement of chemical engineering education by examining the benefits and limitations of LLMs as educational aids in the design process.

This work presents a two-step method to reduce the energy consumption (in terms of the reboiler duty) of a natural gas sweetening process via a physical-chemical solvent mixture (Step 1) followed by a techno-economic analysis of 15 different absorber-stripper configurations (Step 2). Initially, an amine-based sweetening process using a H2S-free sour gas was simulated on Aspen HYSYS and the simulation results were validated against real plant data. In Step 1, different ratios of Sulfinol-M and Sulfinol-D based sweetening process were simulated and the superior physical-chemical solvent mixture that provides the lowest reboiler duty while meeting the sweet gas CO2 product concentration specification (i.e., less than 2 mol.%) is the Sulfinol-M solvent that contains 38 wt.% methyl diethanolamine (MDEA), 40 wt.% Sulfolane, and 22 wt.% water. This Sulfinol-M based model is then optimized via a parametric analysis to further improve its performance in terms of the reboiler duty prior to Step 2. The optimized Sulfinol-M based model achieved 65% saving in the reboiler duty while fulfilling the CO2 concentration specification in product gas relative to the base case. In Step 2, four main absorber-stripper configurations, namely absorber intercooling (AI), lean amine stream split flow (LASSF), rich amine stream split flow (RASSF), and mechanical vapor recompression (MVR) along with their 11 possible combinations were simulated in an attempt to decrease the energy consumption of the process and hence, ranked based on their total cost of production (TCOP). The results revealed that the integration of LASSF + RASSF provides the best option as it achieved the lowest TCOP of $4.60 M while fulfilling the CO2 concentration in product gas and contributed to 6.39% savings in the reboiler duty compared to the optimized conventional Sulfinol-M based model.

This study reexamined the possibility of improving the separation of binary azeotropic mixture containing tetrahydrofuran (THF) and ethanol from previous work (J Chem Technol Biotechnol 2015; 90: 1463–1472) that rely on the extractive distillation (ED) using ethylene glycol (EG) as solvent. Here, dimethyl sulfoxide (DMSO) is proposed as an alternative solvent for the ED, and its feasibility is preliminary screened and compared against the usage of EG. The conceptual ED using DMSO is designed by manipulating all the design variables until the minimum product specifications (i.e. purity) are achieved. Then, the conceptual design is further optimised using particle swarm algorithm to obtain the ideal column configuration and the performance is compared against the ED using ethylene glycol (EG) and pressure swing distillation (PSD) (i.e. best process) from previous work based on economic and CO2 emission. Overall, the optimised ED using DMSO provides 36% and 37% lower economic and CO2 emission with respect to the ED using EG. In comparison to PSD (i.e. best process) from previous work, it provides 24% and 25% reduction in TAC and CO2 emission. Lastly, a control structure is developed for the proposed ED using DMSO that can effectively handle ± 10% throughput and ± 5% feed composition disturbances without the need of a composition controller as in the case of previous work.

The reactive-extractive distillation (RED) has the advantages of combining the beneficial features of both reaction and separation processes. Relative to the conventional reactive or extractive distillation-based processes, the RED is also less energy intensive as it relies on the reaction heat produced for the subsequent separation process. Therefore, the application of RED for ternary azeotropic separation has become the subject of popular interest, as evident by the increasing number of publications since 2020. This review paper is the first that puts together, in a chronological manner, all the existing studies on the RED to date, starting from the initial three column reactive-extractive distillation (TCRED) to the most recent dividing wall reactive-extractive distillation (DW-RED), for ternary azeotropic separation, so that the rapid progress in this area is summarised and any existing gaps in these studies become easier to identify for future work. The last part of this review provides three potential areas for future work, i.e. analysis of the sustainability of RED, combination of different process intensification strategies to improve the energy efficiency and separation performance, and further exploration on the control studies for the RED.

In this work, the previously developed techno-economic framework in Kong et al. (2018) is extended to evaluate three different configurations of DRIZO process for natural gas dehydration: Case (i) – recycling of the regenerator overhead, Case (ii) – recycling of the flash vapour, and Case (iii) – recycling of both the flash vapour and the regenerator overhead into the dehydration system. The best configuration of DRIZO process is Case (iii), which is used as a representative case for subsequent comparison against other dehydration processes evaluated in our previous work. Our techno-economic analysis reveals that Case (iii) can regenerate tri-ethylene glycol (TEG) with the highest purity and the lowest TEG loss rate and volatile organic compound (VOC) emission. This translates to the lower water content in the dry product gas and also the higher HHV relative to Case (i) and Case (ii). A higher HHV generally signifies a higher gross profit margin. Nevertheless, DRIZO process is not economically feasible in comparison to the other dehydration processes from our previous work, mainly because of the high capital expenditure and the associated operating cost. Relative to the other dehydration processes, although the gross profit margin for DRIZO process is about $100,000 higher, it is not sufficient to compensate the high capital and operating expenses due to the high TCOP of about $500,000 to $600,000. Therefore, our analysis recommends the use of stripping gas dehydration process that consumes a portion of dry product gas to achieve the desired water dew point specification for its highest gross profit margin. Keywords: Dehydration, Glycol regeneration, Natural gas, Tri-ethylene glycol, Aspen HYSYS, Techno-economic analysis