This study advances the development of syngas fermentation by presenting the first industrial-scale process design for producing isopropanol (IPA) and acetone from steel mill off-gas, with a total production capacity of 46–50 ktonne per year. The process was rigorously developed in Aspen Plus, with a comprehensive techno-economic assessment and life-cycle analysis performed to evaluate the process performance. The developed process maximizes energy efficiency by utilizing the heat content of steel off-gas and implementing advanced heat pump systems. As a result, the process is thermally self-sufficient and can operate solely on renewable electricity. Efficient utilization of waste gases results in substantial reductions in global warming potential compared with petrochemical-based production (144–160% for IPA and 138–149% for acetone). The unit production cost of 0.58–0.74 $/kg_IPA/Ac and potential profit margins of 49–65% testify to the cost-effectiveness of the developed process. These findings demonstrate the environmental and economic sustainability of syngas fermentation from steel mill off-gas, establishing it as a potentially viable alternative to conventional petrochemical processes. This technology may hold great potential in reducing environmental impacts and carbon emissions in industrial chemical production.

The evolution of artificial intelligence (AI), machine learning (ML), and neural networks (NN) is transforming the landscape of scientific and engineering modeling. It also prompts a debate on the role of first-principles modeling (FPM) in chemical engineering. While data-driven methods excel at interpolation and very rapid development, they often lack physical fidelity, interpretability, and reliable extrapolation capabilities. This article provides a personal academic and industrial perspective on the synergistic integration of FPM and AI-based methods, highlighting their complementary roles in process systems engineering. We argue that FPM (based on fundamental conservation laws and mechanistic understanding of phenomena), remains indispensable for ensuring robustness, safety, physical consistency, and adaptability of models in PSE. Moreover, we analyze the synergistic potential of hybrid approaches by deconstructing the model-building workflow. The latter is the primary lens to identify key decision points where integration delivers maximum value, moving beyond a simple paradigm comparison. Using this structured analysis of the model-building workflow, we identify several major opportunities for this integration, particularly where first-principles knowledge is incomplete. The discussion extends to practical strategies for model validation, scalability, and industrial applications, supported by case studies, as well as the potential of LLMs in assisting the future developments of FPM. Finally, we conclude that a physics-informed foundation for modeling is not obsolete but is instead critical for guiding the safe and reliable application of AI in chemical engineering.

The electrification of chemical processes and CO₂ utilization are key approaches to improving efficiency and reducing CO₂ emissions in the process industry. The development of electrolyzers has gathered momentum, enabling the potential introduction of renewable electrons into the manufacture of CO₂-based chemicals. While the performance of electrolyzers is subject to improvements driven by the experimental community, the generation of waste heat is unavoidable due to electrical resistances and process inefficiencies within the electrochemical cells. Nonetheless, reusing this waste heat has yet to be investigated for CO₂ electrolyzers. This novel work shows the potential for upgrading the electrolyzer waste heat by means of a heat pump, enabling its utilization in the separation processes downstream of the carbon dioxide electrolyzer. The product chosen is formic acid (60 kt/y), and for our system, the waste heat represents approximately 60 % of the power input to the electrochemical cells, and it can be upgraded from 50 °C to 120 °C to drive the azeotropic distillation of formic acid and water. This integration results in the electrification of 76 % of the separation energy duty, yielding a decrease in CO₂ emissions of 29–84 % compared to the conventional production, depending on the source of electricity. The results demonstrate that the use of traditional heating media in thermal separation processes can be offset and substituted with (renewable) electrical energy, allowing for an increased overall system efficiency. This approach can be readily extended to different productions based on carbon dioxide electroreduction, for example for methanol and ethanol manufacture. This eco-efficient process design leads to a deeper penetration of renewable energy into chemical manufacturing, as both reaction and separation are driven by electricity.

Enzymatic biodiesel production offers advantages in overcoming the limitations of base-catalyzed process that is sensitive to free fatty acid contents and acid-catalyzed process that requires high operating conditions. The present study is the first to explore the techno-economic viability of enzymatic biodiesel production from castor oil considering both conventional reactor-distillation and enzymatic reactive distillation (ERD) technologies. The ERD technology was assessed by previous studies for other chemical systems, while the ERD prospect for biodiesel process currently remains unknown. This work proposes a reliable thermodynamic model and a new power-law kinetic expression for the specific assessed system. The realistic approach of reactor and enzymatic reactive distillation design in this study suggests that compared to the ERD scheme, the conventional process achieves slightly higher conversion (99.65% vs 97.61%) at substantially lower specific energy use (1.50 vs 3.93 GJ/tonne FAME) and lower specific CO₂ emissions (0.12 vs 0.31 kg CO₂/tonne FAME), with comparable production costs (2.05 vs 2.11 USD/kg). Due to the inherent slow reaction in enzymatic systems and an unfavorable components’ volatility order in the biodiesel system, a standalone ERD without pre-reactors is not practically viable. Despite the fact that the reactive distillation scheme offers advantages of process integration in some chemical reaction systems, this study reveals that sometimes process intensification fails to outperform conventional processes, particularly in enzymatic biodiesel production.

Multi-stage mechanical vapor recompression (MVR) is a promising route to electrify and intensify distillation for wide-boiling separations, yet its deployment is often constrained by the requirements for effective inter-stage cooling and utilization of the associated sensible heat. This work proposes and evaluates liquid injection as a compact intensification alternative to conventional exchanger-based intercooling in a two-stage MVR system. Unlike prior work on the discretely heat integrated distillation column (D-HIDiC), this study introduces liquid injection directly into MVR systems, eliminating intercooler hardware while maintaining energy performance. Four configurations are examined: a two-stage MVR without intercooling (MVR #1), an intercooled MVR with internal heat recovery to an additional bottom reboiler (MVR #2), a liquid injection MVR without an intercooler (MVR #3), and a liquid injection MVR combined with pre-compressor splitting (MVR #4) to mitigate the increased second-stage compressor load caused by injection. Compared with conventional distillation (CDiC, 10,073 kW reboiler duty), all MVR cases reduce the final energy input to 1759–1850 kW (81.6–82.5% savings) with COP values of 5.445–5.727; MVR #4 achieves the lowest compressor power (1759 kW) and the highest COP (5.727). On a primary-energy basis (36.6% electricity conversion efficiency), the MVR schemes deliver 49.8–52.3% savings versus CDiC. Overall, liquid injection enables equipment simplification with competitive efficiency, while pre-compressor splitting provides a practical tuning degree of freedom to recover or improve performance without sacrificing compactness.

This study investigates the dynamics and control of discretely heat integrated distillation columns, focusing on two configurations: one utilizing a liquid pumparound loop and the other employing liquid injection for waste heat recovery in a multi-stage vapor recompression cycle. These innovative designs eliminate the need for vapor splitters, simplifying operation and enhancing control robustness. As case study, the methanol/water separation process was modelled to achieve 99.99 mol % purity for both products. Dynamic simulations were conducted in Aspen Dynamics to evaluate the control performance for ± 20 % throughput and composition disturbances. Results demonstrated that the proposed control structures, which rely on inferential temperature-based strategies, effectively maintain product specifications and ensure stable operation. This work provides valuable insights into the practical implementation of discretely heat integrated distillation columns, offering a pathway toward energy-efficient and operationally flexible distillation systems.

Distillation is widely used for separating liquid mixtures, but its high heating demand poses challenges for achieving net-zero emissions. This study presents an innovative approach to electrifying distillation for load adaptability and flexible operation, aligning with dynamic electricity markets driven by renewables. The approach integrates flash vapor circulation and thermal storage into the distillation to optimize power usage and capitalizes on economic opportunities from load-flexible operation in response to fluctuating electricity pricing. A methanol/water distillation case study, using two typical electricity pricing scenarios, demonstrates that the proposed approach is more economically efficient than mechanical vapor recompression distillation, especially in lowering operational costs when the latter operates under fixed electricity pricing. However, compressor capital costs significantly impact overall costs, with sensitivity analysis examining different cost models. This approach can be applied to general distillation, allowing integration with the power sector and demand response programs, while enhancing flexibility, decarbonization, and efficiency.

Fermentation can be used to obtain a wide variety of valuable high-boiling components. Among these components, microorganisms can produce aliphatic diols (e.g. propanediols, butanediols, etc.) in significant concentrations (e.g. 5–15 wt.%). Nonetheless, the high boiling points of these components, presence of microorganisms, and formation of by-products complicate recovery after fermentation. Hence, this perspective offers valuable insights into downstream processing options. A novel methodology was developed for recovering high-boiling components from dilute aqueous solutions, whereby both light and heavy impurities are present. The main steps in the proposed methodology are heat pump-assisted preconcentration and final purification in a dividing-wall column. These steps allow effective separation of high-purity product from water, light and heavy impurities. Furthermore, processes for recovery of 1,3-propanediol, 2,3-, 1,4- and 1,3-butanediol, designed according to the proposed methodology, were compared. Downstream processing performance is mainly determined by the product concentration in the fermentation broth, but is also influenced by the amount of impurities in the broth.

Green solvents have emerged as promising green entrainers to substitute conventional entrainers in extractive distillation to separate azeotropic mixtures. However, the limited availability of thermodynamic data for green-solvent-containing mixtures continues to hinder their practical implementation in this process. This study is the first to report experimental vapor–liquid equilibrium (VLE) data for the n-hexane + ethanol azeotropic system containing the greener entrainer 1-butylpyrrolidin-2-one (NBP) alongside the benchmark entrainer 1-methylpyrrolidin-2-one (NMP). Using a Fischer Labodest VLE602 ebulliometer, VLE measurements were performed at pressures of 50.0 and 100.0 kPa and various entrainer-to-feed ratios (E/F). The reliability of the reported VLE data was tested and confirmed using the Van Ness thermodynamic consistency test. The results show that NBP enhances relative volatility and effectively eliminates the azeotrope, performing comparably to the benchmark entrainer NMP. The nonrandom-two-liquid (NRTL) model was utilized to regress the investigated VLE data and determine the optimum binary interaction parameters (BIPs). As a result, the NRTL model demonstrates good agreement with the experimental data. This thermodynamic modeling confirms the data’s reliability and suitability for process design, highlighting NBP’s potential as an environmentally friendly alternative entrainer in extractive distillation.

In this work, dimethyl isosorbide (DMI) and 1-butylpyrrolidin-2-one (NBP), as biobased and greener organic solvents, were used for the first time as entrainers in extractive distillation to separate a close-boiling mixture of methylcyclohexane and toluene. Vapor–liquid equilibrium (VLE) data were collected for pseudoternary mixtures consisting of methylcyclohexane and toluene in the presence of DMI and NBP at various entrainer-to-feed ratios (E/F) and pressures. The VLE measurements were conducted by using a Fischer Labodest VLE602 ebulliometer, and the thermodynamic consistency of the data was verified by using the Van Ness test. Both DMI and NBP were found to increase the relative volatility of methylcyclohexane to toluene, successfully eliminating close-boiling behavior. Compared to benchmark entrainers, both outperformed 1-methylpyrrolidin-2-one (NMP) and sulfolane under certain conditions. In comparison with other green entrainers, DMI and NBP showed similar performance to gamma-valerolactone (GVL) and Cyrene under specific conditions. The VLE data were accurately correlated by using the nonrandom two-liquid (NRTL) model.

This study investigates the dynamics and control of a fully electrified heat pump assisted distillation system based on the flash vapor circulation (FVC) concept. The proposed configuration enables complete electrification without auxiliary steam. Two control structures are developed and evaluated in Aspen Dynamics under ± 20 % disturbances in throughput and composition. The first structure CS1 employs single-end temperature control with fixed reflux ratio and demonstrates satisfactory performance in most cases. However, it shows minor deviations in product purity under large composition changes. To address this, a second structure CS2 incorporates an additional composition controller to adjust the reflux ratio, achieving improved purity regulation and energy flexibility. The results confirm the dynamic feasibility and controllability of FVC-based distillation, supporting its integration in future sustainable and flexible separation systems.

BACKGROUND: 2-Phenylethanol (2PE) is a valuable aroma component that can be obtained through de-novo fermentation from glucose. However, its toxicity at very low concentrations (<2.5 g L⁻¹) limits the fermentation titer, rate and yield. To address these limitations, in-situ product removal has been explored, leading to a recent scale-up to pilot scale. Nonetheless, an industrial scale has yet to be achieved. RESULTS: This original research pioneers conceptual development of two large-scale (2 ktonne_2PE/y) production processes for 2PE via de-novo fermentation from glucose. Liquid–liquid extraction with oleyl alcohol and adsorption by hydrophobic resins followed by ethanol desorption, were alternatives considered for in-situ 2PE removal. For either design, solvent recovery and final purification were performed using advanced distillation techniques, including a heat pump-assisted distillation and a dividing-wall column. A fermentation titer of approximately 1.5 g_2PE/L_broth minimized production costs by achieving balance between upstream and downstream processing costs. This resulted in a cost-effective 2PE production for both designs of the recovery process (9.03–9.40 $/kg_2PE). Sensitivity analysis revealed that glucose, oleyl alcohol, and ethanol costs strongly impact total production costs. CONCLUSION: This novel study provides a comprehensive and scalable process framework for the large-scale production of 2PE through de-novo fermentation. Integrating in-situ product removal and energy-efficient purification strategies, it marks a significant step forward in industrial biotechnology.