Assessing the feasibility and sustainability of a surfactin production process: a techno-economic and environmental analysis.

Biosurfactants have been profiled as a sustainable replacement for chemical-based surfactants since these bio-based molecules have higher biodegradability. Few research papers have focused on assessing biosurfactant production to elucidate potential bottlenecks. This research aims to assess the techno-economic and environmental performance of surfactin production in a potential scale of 65m3, considering different product yields and involving the European energy crisis of 2021-2022. The conceptual design, simulation, techno-economic, and environmental assessments were done by applying process engineering concepts and software tools such as Aspen Plus v.9.0 and SimaPro v.8.3.3. The results demonstrated the high economic potential of surfactin production since the higher values in the market offset the low fermentation yields, low recovery efficiency, and high capital investment. The sensitivity analysis of the economic assessment elucidated a minimum surfactin selling price between 29 and 31 USD/kg of surfactin, while a minimum processing scale for economic feasibility between 4 and 5 kg/h is needed to reach an equilibrium point. The environmental performance must be improved since the carbon footprint was 43 kg CO2eq/kg of surfactin. The downstream processing and energy demand are the main bottlenecks since these aspects contribute to 63 and 25% of the total emissions. The fermentation process and downstream process are key factors for future optimization and research.

Bibliometric and Co-Occurrence Study of Process System Engineering (PSE) Applied to the Polyvinyl Chloride (PVC) Production.

PVC is widely used in packaging, electrical insulation, and medical devices due to its versatility owing to its resistance, incombustible and barrier properties as well as affordable cost. In the present study, bibliometric and co-occurrence analyses are proposed to identify trends, gaps, future directions, and challenges regarding process system engineering (PSE) applied to the production process of PVC using VOSviewer as a tool for analyzing the data obtained from SCOPUS. A mapping of different topics alluding to simulation of PVC production was provided to gain a better insight into the development of the topic and its progression. The findings indicate that the literature on this topic falls into five different clusters: modeling and simulation of PVC production, process control and optimization, and optimization strategies of the process. From a co-occurrence study we identified that mathematics and statistics applied to polymer chemistry, separation phenomena, and polymer production are the main areas of interest for further research. The trends suggest that Monte Carlo and numerical simulation can contribute to a deeper understanding of PVC's properties and behavior. In addition, the focus on plastics and microplastics reflects concerns about the environmental impact. A bibliometric study evidenced that PSE provides the tools for improvement in PVC production processes by employing advanced process engineering techniques. Modelling and new algorithms for simulation methods of continuous polymerization processes are important to enhance accuracy and efficiency across various applications. The study also proposes a research agenda for future researchers working in the field of the use of PSE applied to the PVC production process.

Carbon dioxide conversion via reverse water-gas shift reaction: Reactor design.

The reverse water gas shift (RWGS) reaction converts carbon dioxide (CO2) and hydrogen (H2) to syngas, which is used to produce various high-added-value chemicals. This process has attracted great interest from researchers as a way of mitigating the potential environmental impacts of this greenhouse gas, with emphasis on global warming. This work aims to model and simulate an industrial catalytic reactor using kinetic data for the RWGS reaction. The simulation was carried out in Aspen Plus® v10. The thermodynamic analysis showed that the appropriate conditions for the reaction are feed molar ratio (H2/CO2) of 0.8:1, 750 °C, and 20 bar. The RWGS process proceeds in a multi-tubular fixed bed reactor with 36.26% CO2 conversion and 96.41% CO selectivity, at residence times in the order of 2.7 s. These results are at near-equilibrium CO2 conversion with higher CO selectivity.

Modeling and Validation of a LiOH Production Process by Bipolar Membrane Electrodialysis from Concentrated LiCl.

Electromembrane processes for LiOH production from lithium brines obtained from solar evaporation ponds in production processes of the Salar de Atacama are considered. In order to analyze high concentrations' effect on ion exchange membranes, the use of concentrated LiCl aqueous solutions in a bipolar membrane electrodialysis process to produce LiOH solutions higher than 3.0% by mass is initially investigated. For this purpose, a mathematical model based on the Nernst-Planck equation is developed and validated, and a parametric study is simulated considering as input variables electrolyte concentrations, applied current density, stack design, process design and membrane characteristics. As a novelty, this mathematical model allows estimating LiOH production in a wide concentration range of LiCl, HCl and LiOH solutions and its effect on the process, providing data on final LiOH solution purity, current efficiency, specific electricity consumption and membrane performance. Among the main results, a concentration of 4.0% to 4.5% by LiOH mass is achieved, with a solution purity higher than 95% by mass and specific electrical energy consumption close to 4.0 kWh/kg. The work performed provides key information on process sensitivity to operating conditions and process design characteristics. These results serve as a guide in the application of this technology to lithium hydroxide production.

Simulation of Organic Liquid Product Deoxygenation through Multistage Countercurrent Absorber/Stripping Using CO2 as Solvent with Aspen-HYSYS: Process Modeling and Simulation.

In this work, the deoxygenation of organic liquid products (OLP) obtained through the thermal catalytic cracking of palm oil at 450 °C, 1.0 atmosphere, with 10% (wt.) Na2CO3 as a catalyst, in multistage countercurrent absorber columns using supercritical carbon dioxide (SC-CO2) as a solvent, with an Aspen-HYSYS process simulator, was systematically investigated. In a previous study, the thermodynamic data basis and EOS modeling necessary to simulate the deoxygenation of OLP was presented. This work addresses a new flowsheet, consisting of 03 absorber columns, 10 expansions valves, 10 flash drums, 08 heat exchanges, 01 pressure pump, and 02 make-ups of CO2, aiming to improve the deacidification of OLP. The simulation was performed at 333 K, 140 bar, and (S/F) = 17; 350 K, 140 bar, and (S/F) = 38; 333 K, 140 bar, and (S/F) = 25. The simulation shows that 81.49% of OLP could be recovered and that the concentrations of hydrocarbons in the extracts of absorber-01 and absorber-02 were 96.95 and 92.78% (wt.) on a solvent-free basis, while the bottom stream of absorber-03 was enriched in oxygenated compounds with concentrations of up to 32.66% (wt.) on a solvent-free basis, showing that the organic liquid products (OLP) were deacidified and SC-CO2 was able to deacidify the OLP and obtain fractions with lower olefin contents. The best deacidifying condition was obtained at 333 K, 140 bar, and (S/F) = 17.

Why Does Not Nanotechnology Go Green? Bioprocess Simulation and Economics for Bacterial-Origin Magnetite Nanoparticles.

Nanotechnological developments, including fabrication and use of magnetic nanomaterials, are growing at a fast pace. Magnetic nanoparticles are exciting tools for use in healthcare, biological sensors, and environmental remediation. Due to better control over final-product characteristics and cleaner production, biogenic nanomagnets are preferable over synthetic ones for technological use. In this sense, the technical requirements and economic factors for setting up industrial production of magnetotactic bacteria (MTB)-derived nanomagnets were studied in the present work. Magnetite fabrication costs in a single-stage fed-batch and a semicontinuous process were US$ 10,372 and US$ 11,169 per kilogram, respectively. Depending on the variations of the production process, the minimum selling price for biogenic nanomagnets ranged between US$ 21 and US$ 120 per gram. Because these prices are consistently below commercial values for synthetic nanoparticles, we suggest that microbial production is competitive and constitutes an attractive alternative for a greener manufacturing of magnetic nanoparticles nanotools with versatile applicability.

Simulation of Organic Liquid Products Deoxygenation by Multistage Countercurrent Absorber/Stripping Using CO2 as Solvent with Aspen-HYSYS: Thermodynamic Data Basis and EOS Modeling.

In this work, the thermodynamic data basis and equation of state (EOS) modeling necessary to simulate the fractionation of organic liquid products (OLP), a liquid reaction product obtained by thermal catalytic cracking of palm oil at 450 °C, 1.0 atmosphere, with 10% (wt.) Na2CO3 as catalyst, in multistage countercurrent absorber/stripping columns using supercritical carbon dioxide (SC-CO2) as solvent, with Aspen-HYSYS was systematically investigated. The chemical composition of OLP was used to predict the density (ρ), boiling temperature (Tb), critical temperature (Tc), critical pressure (Pc), critical volume (Vc), and acentric factor (ω) of all the compounds present in OLP by applying the group contribution methods of Marrero-Gani, Han-Peng, Marrero-Pardillo, Constantinou-Gani, Joback and Reid, and Vetere. The RK-Aspen EOS used as thermodynamic fluid package, applied to correlate the experimental phase equilibrium data of binary systems OLP-i/CO2 available in the literature. The group contribution methods selected based on the lowest relative average deviation by computing Tb, Tc, Pc, Vc, and ω. For n-alkanes, the method of Marrero-Gani selected for the prediction of Tc, Pc and Vc, and that of Han-Peng for ω. For alkenes, the method of Marrero-Gani selected for the prediction of Tb and Tc, Marrero-Pardillo for Pc and Vc, and Han-Peng for ω. For unsubstituted cyclic hydrocarbons, the method of Constantinou-Gani selected for the prediction of Tb, Marrero-Gani for Tc, Joback for Pc and Vc, and the undirected method of Vetere for ω. For substituted cyclic hydrocarbons, the method of Constantinou-Gani selected for the prediction of Tb and Pc, Marrero-Gani for Tc and Vc, and the undirected method of Vetere for ω. For aromatic hydrocarbon, the method of Joback selected for the prediction of Tb, Constantinou-Gani for Tc and Vc, Marrero-Gani for Pc, and the undirected method of Vetere for ω. The regressions show that RK-Aspen EOS was able to describe the experimental phase equilibrium data for all the binary pairs undecane-CO2, tetradecane-CO2, pentadecane-CO2, hexadecane-CO2, octadecane-CO2, palmitic acid-CO2, and oleic acid-CO2, showing average absolute deviation for the liquid phase (AADx) between 0.8% and 1.25% and average absolute deviation for the gaseous phase (AADy) between 0.01% to 0.66%.

Computer-aided simulation and exergy analysis of TiO2 nanoparticles production via green chemistry.

BACKGROUND: The production of photocatalytic nanoparticles such as TiO2 has received increasing interest for biomedical and wastewater treatment applications. However, the conventional synthesis of such materials faces several environmental concerns. METHODS: In this work, green synthesis is addressed to prepare TiO2 nanoparticles at large scale using Lemongrass (Cymbopogon citratus) and titanium isopropoxide (TTIP). This process was designed and modeled using computer-aided process engineering (CAPE) in order to obtain the extended mass/energy balances, as well as operating parameters. Process simulation was carried out using the commercial software Aspen Plus®. In addition, energy performance of large-scale nanoparticle production was analyzed to identify alternatives for process improvement from an exergetic point of view. RESULTS: The production capacity of the plant was estimated as 1,496 t/y of TiO2 nanoparticles by the conversion of 32,675 t/y lemongrass and 5,724 t/y TTIP. Hence, the overall production yield is 0.26 kg TiO2/kg TTIP. Exergy analysis reported an overall exergy efficiency of 0.27% and an exergy loss of 159,824.80 MJ/h. These results suggest that such a process requires the implementation of process improvement strategies to reach a more sustainable design from energy and thermodynamic viewpoints.

Comprehensive assessment of the L-lysine production process from fermentation of sugarcane molasses.

L-Lysine is an essential amino acid that can be produced by chemical processes from fossil raw materials, as well as by microbial fermentation, the latter being a more efficient and environmentally friendly procedure. In this work, the production process of L-lysine-HCl is studied using a systematic approach based on modeling and simulation, which supports decision making in the early stage of process design. The study considers two analysis stages: first, the dynamic analysis of the fermentation reactor, where the conversion of sugars from sugarcane molasses to L-lysine with a strain of Corynebacterium glutamicum is carried out. In this stage, the operation mode (either batch or fed batch) and operating conditions of the fermentation reactor are defined to reach the maximum technical criteria. Afterwards, the second analysis stage relates to the industrial production process of L-lysine-HCl, where the fermentation reactor, upstream processing, and downstream processing are included. In this stage, the influence of key parameters on the overall process performance is scrutinized through the evaluation of several technical, economic, and environmental criteria, to determine a profitable and sustainable design of the L-lysine production process. The main results show how the operating conditions, process design, and selection of evaluation criteria can influence in the conceptual design. The best plant design shows maximum product yield (0.31 g L-lysine/g glucose) and productivity (1.99 g/L/h), achieving 26.5% return on investment (ROI) with a payback period (PBP) of 3.8 years, decreasing water and energy consumption, and with a low potential environmental impact (PEI) index.

Life cycle assessment of carbon capture and utilization from ammonia process in Mexico.

Post-combustion CO2 capture (PCC) of flue gas from an ammonia plant (AP) and the environmental performance of the carbon capture utilization (CCU) technology for greenhouse gas (GHG) emissions to an enhanced oil recovery (EOR) system in Mexico was performed as case study. The process simulations (PS) and life cycle assessment (LCA) were used as supporting tools to quantify the CO2 capture and their environmental impacts, respectively. Two scenarios were considered: 1) the AP with its shift and CO2 removal unit and 2) Scenario 1 plus PCC of the flue gas from the AP primary reformer (AP-2CO2) and the global warming (GW) impact. Also, the GW of the whole of a CO2-EOR project, from these two streams of captured CO2, was evaluated. Results show that 372,426 tCO2/year can be PCC from the flue gas of the primary reformer and 480,000 tons/y of capacity from the AP. The energy requirement for solvent regeneration is estimated to be 2.8 MJ/kgCO2 or a GW impact of 0.22 kgCO2e/kgCO2 captured. GW performances are 297.6 kgCO2e emitted/barrel (bbl) for scenario one, and 106.5 kgCO2e emitted/bbl for the second. The net emissions, in scenario one, were 0.52 tCO2e/bbl and 0.33 tCO2e/bbl in scenario two. Based on PS, this study could be used to evaluate the potential of CO2 capture of 4080 t/d of 4 ammonia plants. The integration of PS-LCA to a PCC study allows the applicability as methodological framework for the development of a cluster of projects in which of CO2 could be recycled back to fuel, chemical, petrochemical products or for enhanced oil recovery (EOR). With AP-2CO2, "CO2 emission free" ammonia production could be achieved.

Yeast biomass production: a new approach in glucose-limited feeding strategy.

The aim of this work was to implement experimentally a simple glucose-limited feeding strategy for yeast biomass production in a bubble column reactor based on a spreadsheet simulator suitable for industrial application. In biomass production process using Saccharomyces cerevisiae strains, one of the constraints is the strong tendency of these species to metabolize sugars anaerobically due to catabolite repression, leading to low values of biomass yield on substrate. The usual strategy to control this metabolic tendency is the use of a fed-batch process in which where the sugar source is fed incrementally and total sugar concentration in broth is maintained below a determined value. The simulator presented in this work was developed to control molasses feeding on the basis of a simple theoretical model in which has taken into account the nutritional growth needs of yeast cell and two input data: the theoretical specific growth rate and initial cell biomass. In experimental assay, a commercial baker's yeast strain and molasses as sugar source were used. Experimental results showed an overall biomass yield on substrate of 0.33, a biomass increase of 6.4 fold and a specific growth rate of 0.165 h(-1) in contrast to the predicted value of 0.180 h-1 in the second stage simulation.

Yeast biomass production: a new approach in glucose-limited feeding strategy

The aim of this work was to implement experimentally a simple glucose-limited feeding strategy for yeast biomass production in a bubble column reactor based on a spreadsheet simulator suitable for industrial application. In biomass production process using Saccharomyces cerevisiae strains, one of the constraints is the strong tendency of these species to metabolize sugars anaerobically due to catabolite repression, leading to low values of biomass yield on substrate. The usual strategy to control this metabolic tendency is the use of a fed-batch process in which where the sugar source is fed incrementally and total sugar concentration in broth is maintained below a determined value. The simulator presented in this work was developed to control molasses feeding on the basis of a simple theoretical model in which has taken into account the nutritional growth needs of yeast cell and two input data: the theoretical specific growth rate and initial cell biomass. In experimental assay, a commercial baker's yeast strain and molasses as sugar source were used. Experimental results showed an overall biomass yield on substrate of 0.33, a biomass increase of 6.4 fold and a specific growth rate of 0.165 h-1 in contrast to the predicted value of 0.180 h-1 in the second stage simulation.(AU)

Yeast biomass production: a new approach in glucose-limited feeding strategy

The aim of this work was to implement experimentally a simple glucose-limited feeding strategy for yeast biomass production in a bubble column reactor based on a spreadsheet simulator suitable for industrial application. In biomass production process using Saccharomyces cerevisiae strains, one of the constraints is the strong tendency of these species to metabolize sugars anaerobically due to catabolite repression, leading to low values of biomass yield on substrate. The usual strategy to control this metabolic tendency is the use of a fed-batch process in which where the sugar source is fed incrementally and total sugar concentration in broth is maintained below a determined value. The simulator presented in this work was developed to control molasses feeding on the basis of a simple theoretical model in which has taken into account the nutritional growth needs of yeast cell and two input data: the theoretical specific growth rate and initial cell biomass. In experimental assay, a commercial baker's yeast strain and molasses as sugar source were used. Experimental results showed an overall biomass yield on substrate of 0.33, a biomass increase of 6.4 fold and a specific growth rate of 0.165 h-1 in contrast to the predicted value of 0.180 h-1 in the second stage simulation.