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Methanol is considered a key and platform compound to produce high value‐added chemicals, and it could contribute to energy transition, decreasing the dependence of fossil fuels. This paper presents a methanol synthesis simulation over a commercial Cu/ZnO/Al2O3, which is used at industrial scale. With the aim of exploring renewable raw materials as alternative to synthesize this alcohol, synthesis gas was obtained as a starting mixture from gasification of residual coffee pulp, which is an agro‐industrial waste widely generated in coffee producing countries. Currently, the raw materials most used to obtain methanol are natural gas and coal, so the use of agro‐industrial waste as a raw material would achieve greener methanol production. Design of experiments and ANOVA were applied to obtain results with statistical significance. Residual coffee pulp gasification conditions and reaction temperature were the controlled variables, while methanol production was selected as a response one. The simulation runs and ANOVA were analyzed and compared with the literature reports, and it was observed that methanol production is possible avoiding the catalyst deactivation. For the best obtained conditions, the profiles along the reactor of chemical species molar fraction, stochiometric number, methanol production and pressure drop were shown. [ABSTRACT FROM AUTHOR]

The demand for cement has significantly increased, growing by 8% in the year 2022 and by a further 12% in 2023. It is highly anticipated that this trend will continue, and it will result in significant growth by 2030. However, cement production is highly energy-intensive, with 70 to 80% of the total energy consumed during the clinker formation, which is the main cement production process. Minimising energy losses requires a radical approach that includes optimising the performance of the kilns and significantly improving their energy efficiency. One of the most efficient approaches to optimise the performance of the kilns and reduce energy losses is by integrating process re-engineering models, which leverage process data analytics, machine learning, and computational methods. This study employed a model-based integration approach to improve energy efficiency during clinker formation. Energy consumption data were collected from two semi-automated cement production plants. The data were analysed using a regression model in Minitab (Minitab 21.1.0) statistical software. The analysis resulted in a linear energy consumption equation that links energy consumption to both production and energy loss. Dynamic simulations and modelling using Simulink in MATLAB were performed based on a proportional–integral–derivative (PID)-controlled system. The dynamic behaviour of the model was evaluated using data from Plant A and validated with data from Plant B. The energy efficiency equation was established as a mathematical model that explains energy improvements based on incorporating parameters for the cement kiln system and disturbances from the environment. [ABSTRACT FROM AUTHOR]

The processing of long glass fibre-reinforced thermoplastics results in considerable fibre damage, particularly during plasticising. By using thermoplastic foam injection moulding (FIM) with a constant blowing agent atmosphere, fibre damage during plasticisation can be reduced. This can be attributed to the reduction of the melt viscosity on the one hand and the influence of the melting behaviour on the other. Therefore, the influence of the FIM and the process parameters on the fibre length and the fibre length distribution are analysed and compared with the influence of the process parameters on the melt viscosity. [ABSTRACT FROM AUTHOR]

Sliver nanowires (Ag NWs) are promising building blocks for electronic nanodevices, and therefore, their precise movement and assembly are urgently needed. Here, molecular dynamics simulations are conducted to model the manipulation of Ag NWs on a silicon substrate using a tungsten (W) probe. The focus is on understanding the deformation and motion mechanisms of the Ag NWs induced by the moving probe. Throughout the manipulation process, Ag NWs undergo four distinct stages: plastic deformation, deformation extension, a hybrid stage, and either movement or fracture. At the contact area between the probe and the Ag NWs, as well as in regions of stress concentration, Ag atoms are observed to transition from FCC to HCP, BCC, and even amorphous states. Notably, the BCC phase serves as an intermediate transition state during this lattice transformation. The manipulation parameters, particularly the velocity and displacement of the probe, significantly influence the outcome of the Ag NWs. High-speed manipulation with small displacements tends to result in Ag NW fracture, whereas low-speed manipulation with larger displacements facilitates the bending or movement of the Ag NWs. Drawing from the observed deformation behaviors, a nanomanipulation platform integrated within a scanning electron microscope (SEM) was developed. This platform enables the in situ pushing, cutting, bending, and rotating of Ag NWs using a W probe, employing various probe feeding strategies. By combination of two or more of these manipulation operations, complex close-loop structures, such as triangles and hexagons, were successfully assembled via Ag NWs. This research offers valuable insights into the precise and controlled manipulation of Ag NWs, paving the way for the fabrication of sophisticated, high-performance nanodevices. [ABSTRACT FROM AUTHOR]

This study presents an innovative approach utilising molecular dynamics simulations to elucidate the polymerisation and neck formation mechanisms of phenolic resin during laser powder bed fusion (L-PBF). By developing system and dual-particle models and employing infrared thermal imaging, we established a heat source model for phenolic resin under varying parameters. Our molecular dynamics simulations, using the ReaxFF reactive force field, indicate that high-power lasers significantly enhance cross-linking, achieving a peak polymerisation degree of 78.9% at 30W and 35W power levels. Conversely, increased scanning speed slows product degradation, reducing the polymerisation degree. The interplay of laser power and scanning speed influences polymerisation, with total input energy and heating rate impacting polymerisation and molecular size. Additionally, we investigated neck formation, revealing that small vortices evolve into larger ones during sintering, promoting neck formation. Optical microscopy confirmed diverse neck shapes under different conditions. Quantitative data showed that at a scanning speed of 1000 mm/s, the polymerisation degree reached 93%, with only 2 molecules remaining post-simulation. At 30W power, the largest individual molecule observed was C849H703O117. This research offers crucial insights for selective laser sintering processes, emphasising the importance of high energy input and optimal heating rates for well-formed necks. [ABSTRACT FROM AUTHOR]

During the oxidation of SiGe regions, Si is preferably incorporated into the oxide, while Ge atoms accumulate at the SiGe side of the interface. Moreover, during oxidation of fin structures of Si/SiGe superlattices, Ge atoms diffuse from SiGe regions to Si regions along the oxide/SiGe interface, as recently reported. This surface diffusion can be used for the formation of Si nanowires surrounded by SiGe, and possibly for the fabrication of gate all‐around transistors. Herein, a new process simulation model is presented which describes SiGe oxidation and the diffusion of Ge atoms along the interface. During oxidation, Ge atoms can be trapped at the oxide/SiGe interface, diffuse along the interface, and be re‐emitted into the SiGe bulk. The model reproduces measured oxidation rates, the pileup of Ge atoms at the SiGe side of planar oxide/SiGe interfaces, the injection of self‐interstitials and the reduction of vacancies at oxidizing SiGe surfaces, and the recently reported diffusion of Ge atoms along the surface of fin structures made of Si/SiGe superlattices. [ABSTRACT FROM AUTHOR]

A comprehensive process model for 4H‐SiC oxidation is created and calibrated against a very large collection of experimental data. The model reproduces measured oxide thickness for Si‐face, C‐face, and a‐face SiC wafers, in the temperature range 950–1500 °C, in the pressure range 0.25–4.0 atm, in the thickness range 3–1600 nm, and for SiC doping ranging between 1019 cm−3 n‐type and 1019 cm−3 p‐type. The model is based on the Massoud model: Oxidation is driven by oxidants (O2, H2O) which are present in the gas phase, diffuse through the oxide, and form SiO2 at the oxide–SiC interface. For thin oxides, the interface reaction rate includes empirical correction terms which add to the oxidation rate, and which asymptotically approach zero with increasing oxide thickness. For dry oxidation, a remarkable dependence on the O2 partial pressure is discovered: For thick oxides, the oxidation rate scales linearly with the pressure, but the correction term for thin oxides scales with the square root of the pressure. This suggests that the atomistic processes responsible for the fast initial growth of oxides involve the splitting of O2 molecules into two O atoms. [ABSTRACT FROM AUTHOR]

The system integration of cross‐industrial networks in the Carbon2Chem® project relies on numerical simulations. Hence, this study validates the methanol synthesis loop models vs. the measurements from a demonstration plant, focusing on the thermodynamic, kinetic, and dynamic aspects. The plant can produce up to 500 L per week of methanol from real blast furnace gases of the thyssenkrupp steel plant in Duisburg. Despite its small size, it comprises a recycle gas loop and an original reactor tube of 6 m in length. After validation, the simulation models are used to analyze the dynamic operation limits of the plant, and they are transferred to the model of an industrial size to analyze the operation of cross‐industrial networks with volatile boundary conditions. [ABSTRACT FROM AUTHOR]

Due to the tool-less fabrication of parts and the high degree of geometric design freedom, additive manufacturing is experiencing increasing relevance for various industrial applications. In particular, the powder bed fusion of metals using a laser beam (PBF-LB/M) process allows for the metal-based manufacturing of complex parts with high mechanical properties. However, residual stresses form during PBF-LB/M due to high thermal gradients and a non-uniform cooling. These lead to a distortion of the parts, which reduces the dimensional accuracy and increases the amount of post-processing necessary to meet the defined requirements. To predict the resulting residual stress state and distortion prior to the actual PBF-LB/M process, this paper presents the finite-element-based simulation tool AscentAM with its core module and several sub-modules. The tool is based on open-source programs and utilizes a sequentially coupled thermo-mechanical simulation, in which the significant influences of the manufacturing process are considered by their physical relations. The simulation entirely emulates the PBF-LB/M process chain including the heat treatment. In addition, algorithms for the part pre-deformation and the export of a machine-specific file format were implemented. The simulation results were verified, and an experimental validation was performed for two benchmark geometries with regard to their distortion. The application of the optimization sub-module significantly minimized the form deviation from the nominal geometry. A high level of accuracy was observed for the prediction of the distortion at different manufacturing states. The process simulation provides an important contribution to the first-time-right manufacturing of parts fabricated by the PBF-LB/M process. [ABSTRACT FROM AUTHOR]

Featured Application: Polystyrene recycling. This work proposes a conceptual design for recovering polystyrene (PS) using solvents of agro-industrial origin. The literature describes the dilution of expanded polystyrene (EPS) in limonene, followed by its insolubilization with alcohols for recovery. However, there is no information on the solubility limit for the PS + limonene + alcohol system, which is critical for the process design. To determine the solubility limit, we diluted the waste EPS in D-limonene, mixed it with ethanol to form a precipitate, and used a gravimetric method to measure the mass of the compounds. These results allowed for the conceptual design of an EPS recycling process using a chemical process simulator, which includes a separator, a distillation column, and auxiliary equipment such as heaters, coolers, and pumps. An empirical correlation was obtained for the solubility limit, which enabled the design of a process for the treatment of 52 kg/s of PS using 0.75 kg/s of ethanol and 2.4 kg/s of D-limonene once the stationary state had been reached. The distillation column is six-stage, with a reflux ratio of 1.5 and duties of 30,000 and −25 847 kW for the condenser and reboiler, respectively. [ABSTRACT FROM AUTHOR]

Most commercial software used to simulate the injection molding process of semi-crystalline thermoplastic polymers do not explicitly take into account the polymer crystallization, which could lead to errors in the estimations of filling as well as warpage and shrinkage. This is mainly due to the common complexity of the models used to describe crystallization and the challenging respective model parameter identification under injection molding conditions. To close this gap, in this work, we use a simple thermo-mechanical crystallization model to describe the flow-induced and quiescent crystallization of an unreinforced semi-crystalline thermoplastic material during injection molding. The crystallization model is implemented in the commercial software Autodesk® Moldflow® Insight 2021 using the Solver API feature alongside crystallization-dependent viscosity, PVT, and solidification models. The model parameters were identified using a calibration workflow that employs surrogate models representing the simulated pressure results to perform a multi-objective optimization. The filling predictions as well as the calculated pressure fields are presented using the calibrated model parameters in comparison to those measured during the actual injection molding of a polyoxymethylene (POM) part using different process conditions. The results show major improvements in the estimations of the time-depending pressure field as well as the level of filling of the produced parts. [ABSTRACT FROM AUTHOR]

This study reports the comparative energy and exergy analysis of ortho-para hydrogen and non-ortho-para hydrogen conversion in hydrogen liquefaction process. Two cases were simulated, case A – hydrogen liquefaction with ortho-parahydrogen conversion and case B – hydrogen liquefaction without ortho-parahydrogen conversion. This is the first study that presents a comparative energy and exergy analysis between such two cases. In this research, a hydrogen liquefaction process was designed adopting cascaded five-stage Brayton refrigeration cycle. The process was simulated in Aspen PLUS. The process used a mixed refrigerant (of liquefied natural gas) refrigeration cycle to precool the gaseous hydrogen feed from 26 °C temperature to −192 °C temperature, and mixed refrigerant (of nelium) was subsequently used to further deep-cool the the hydrogen stream from −192 °C temperature to −245.99 °C temperature in the cryogenic section of the process. Liquefaction was achieved by expanding the hydrogen through Joule-Thomson valve at −248.37 °C and 1 bar. The simulated results of the two cases showed the specific energy consumption of case A to be 8.45 kWhr/kg LH , and that of case B to be 15.65 kWhr/kg LH respectively. The results also indicated a total exergy efficiency of 92.42% in case A and 87.18% in case B. The research results showed that the hydrogen liquefaction designed with configuration of ortho-parahydrogen conversion has better performance indicators than the liquefaction without ortho-parahydrogen conversion. Therefore, hydrogen liquefaction with ortho-parahydrogen conversion can be considered in the design and development of new hydrogen liquefaction plants. Process optimization is recommended to further enhance the specific energy consumption and exergy efficiency of both processes. • Comparative analysis of ortho-para and non-ortho-para hydrogen conversion. • Ortho-para Process is more energy efficient than non-ortho-para process. • Average exergy efficiency of 89.8% achieved in the analysed processes. • Integration of three refrigeration cycles to achieve hydrogen liquefaction. [ABSTRACT FROM AUTHOR]

Chemical looping dry reforming of methane (CLDRM) using perovskites as a catalyst is considered a promising option for producing hydrogen from biogas. In this work, the life-cycle performance of a system compiling a CLDRM unit paired with a water gas shift unit, a pressure swing adsorption unit, and a combined cycle scheme to provide steam and electricity was assessed. The main data needed to reflect the behavior of the reforming reaction was obtained experimentally and implemented in an Aspen Plus® simulation. Inventory data was obtained through process simulation and used to assess the environmental performance of the process in terms of carbon footprint, acidification, freshwater eutrophication, ozone depletion, photochemical ozone formation, and depletion of minerals and metals. Overall, the environmental viability of the production of green hydrogen from biogas was found to be heavily dependent on the biogas leakage in anaerobic digestion plants. The CLDRM system was benchmarked against a conventional DRM implementation for the same feedstock. While the conventional DRM plant environmentally outperformed the perovskite-based CLDRM, the latter might present advantages from an implementation point of view. [Display omitted] • Scaled-up chemical looping dry reforming of biogas for hydrogen production was simulated. • The life-cycle performance of the configuration with a perovskite catalyst was assessed. • Environmental hotspots refer to biogas leakage, natural gas processes, and catalyst metals. • Environmental advantages of conventional dry reforming were linked to heat integration. • Green hydrogen qualification requires avoiding leakages from anaerobic digestion plants. [ABSTRACT FROM AUTHOR]

A numerical model of packing applied to rigid objects is presented. It aims at describing a random stack of polymer composite chips in order to model the packing step of an existing recycling technique. The geometric properties of the stack play a major role in the mechanical properties of the recycled products. Short, simple and effective geometric descriptors of the stack are proposed. Their ability to differentiate random stacks is illustrated with an example. Then, a validation is proposed based on experimental data obtained from a bench specially designed for this work. The tests consist in the free fall of square chips. Finally, the developed model is compared to other models (free fall and packing of fibers) in order to enforce its relevance in the simulation of packing of rigid objects. [ABSTRACT FROM AUTHOR]

This research introduces multi‐objective stochastic optimization (MOSO) and non‐dominated sorting differential evolution (NSDE) in‐house coded algorithms for enhancing the optimization of the resin transfer molding (RTM) process during the mold‐fill phase for composite parts. Glass fiber‐vinyl ester‐based automotive bonnet and carbon fiber‐RTM6‐based aircraft wing flap parts were used as the case studies. Initially, the NSDE algorithm was developed for the simultaneous optimization of dry‐spot content and mold‐fill time by changing the locations of gates and vents with pre‐fixed port numbers. Then, the MOSO algorithm was designed for the concurrent optimization of the dry‐spot content, mold‐fill time and total number of ports by changing both the numbers and locations of gates and vents. The effect of race‐tracking was also investigated using higher permeability values at the composite part‐cut edges. When compared, the MOSO algorithm predicted less dry‐spot content, number of ports, mold‐fill time and uniform resin flow‐front progressions with lesser functional evaluations and computational time than the NSDE algorithm. Highlights: The non‐dominated sorting differential evolution (NSDE) and multi‐objective stochastic optimization (MOSO) algorithms were developed for the optimization of the mold fill phase of resin transfer molded composite parts.The development of the NSDE algorithm aimed to concurrently optimize the dry‐spot content and mold‐fill time by changing the locations of gates and vents with pre‐fixed port numbers.The MOSO algorithm was designed to concurrently optimize dry‐spot content, mold‐fill time, and the total number of ports by varying both the numbers and locations of gates and vents.The MOSO algorithm predicted better‐automated mold‐fill phase optimalities for the resin transfer molded composite parts compared to the NSDE algorithm. [ABSTRACT FROM AUTHOR]

Objective Being a kind of traditional fossil fuel, petroleum has complex compositions, which makes it difficult to accurately control in refineries. Under the requirements of intelligent manufacturing, establishing a reasonable and reliable refining process model and accurately predicting the impact from upstream and downstream during the refining process can help achieve intelligent regulation and optimization of the refining process. Methods Based on Aspen HYSYS software and the reactor module integrated with lumped kinetic model, a rigorous simulation process of atmospheric and vacuum distillation-hydrocracking from crude oil to product was established. Based on the simulation, the influence of the volume ratio of hydrogen-containing gas to oil on the reaction products flow rate and the amount of hydrogen was investigated. On this basis, the change of product output of downstream hydrocracking unit was obtained by using Matlab to drive process simulation under the condition of fluctuation of upstream crude oil ratio. Results The simulation had high accuracy, with an average relative error of 0.41%. When the proportion of domestic crude oil increased from 20% to 50%, the production of diesel products decreased by 13.9%, the production of naphtha products increased by 6.1%, and total production decreased by 8.7%. Conclusions Based on the program-driven Aspen HYSYS, an atmospheric and vacuum distillation and hydrocracking model have been established, which includes the complete process from petroleum to products, and can analyze and optimize refining process. This model contributes to the implementation of intelligent refining and the transformation of traditional refining enterprises towards intelligence and digitization. [ABSTRACT FROM AUTHOR]

Recent SARS-CoV-2 pandemic elevated research interest in microorganism-related diseases, and protective health application importance such as vaccination and immune promoter agents emerged. Among the production methods for proteins, recombinant technology is an efficient alternative and frequently preferred method. However, since the production and purification processes vary due to the protein nature, the effect of these differences on the cost remains ambiguous. In this study, brucellosis and its two important vaccine candidate proteins (rOmp25 and rEipB) with different properties were selected as models, and industrial-scale production processes were compared with the SuperPro Designer® for estimating the unit production cost. Simulation study showed raw material cost by roughly 60% was one of the barriers to lower-cost production and 52.5 and 559.8 $/g were estimated for rEipB and rOmp25, respectively. Techno-economic evaluation of recombinant protein produced for vaccine purposes Recombinant proteins rOmp25 and rEipB production process using E.coli BL21 Effect of outer membrane and periplasmic space proteins on purification cost Simulated cost estimation of rEipB and rOmp25 were 52.5 and 559.8 $/g, respectively [ABSTRACT FROM AUTHOR]

Composite materials are increasingly important in making high-performance products. However, contemporary composites manufacturing processes still encounter significant challenges that range from inherent material stochasticity to manufacturing process variabilities. This paper proposes a novel smart Industrial Internet of Things framework, which is also referred to as an Artificial Intelligence of Things (AIoT) framework for composites manufacturing. This framework improves production performance through real-time process monitoring and AI-based forecasting. It comprises three main components: (i) an array of temperature, heat flux, dielectric, and flow sensors for data acquisition from production machines and products being made, (ii) an IoT-based platform for instantaneous sensor data integration and visualisation, and (iii) an AI-based model for production process forecasting. Via these components, the framework performs real-time production process monitoring, visualisation, and prediction of future process states. This paper also presents a proof-of-concept implementation of the framework and a real-world composites manufacturing case study that showcases its benefits. [ABSTRACT FROM AUTHOR]

This study examines a numerical method to simulate the production of novel multi-material metal-composite components, where an additive-manufactured cellular solid is infiltrated by a sheet molding compound (SMC) in a single-step compression molding operation. A single-fiber numerical approach is adopted to predict microstructural changes, such as fiber orientation, fiber-matrix separation, and fiber volume content variations during molding. The accuracy of the numerical predictions is confirmed by physical samples using micro-computed tomography and optical microscopy investigations at both the qualitative and quantitative scales. From optical microscopy observations, there emerged a positive correlation between experimental outcomes and simulation results, accurately capturing fiber swirling, wrinkling, and draping that occurred during molding. At a quantitative scale, a 0.6% mismatch was observed when void volume and unfilled areas were compared, as measured by micro-computed tomography and numerical simulation. [ABSTRACT FROM AUTHOR]

Water hyacinth (WH) is an aquatic weed with an experimentally proven potential as a feedstock for bioethanol production. Unlike other bioethanol feedstocks, water hyacinth has no requirement for land use and resource consumption for cultivation. This study evaluates scaled-up bioethanol production process routes, modelled using the Aspen Plus process simulator to analyse the process performance of water hyacinth as a bioethanol feedstock. Four process scenarios are developed by combining two different feedstock pretreatment methods (i.e., alkali pretreatment and diluted acid pretreatment) and bioethanol dehydration techniques (i.e., azeotropic distillation and extractive distillation). Mass and energy flows of the four scenarios are comparatively analysed. Results show that the alkali pretreatment method provides a higher bioethanol yield (i.e., 254 L/tonne-WH) compared with the dilute acid pretreatment method (i.e., 210 L/tonne-WH). In addition, the process route combining alkali pretreatment and extractive dehydration techniques indicates the least process energy consumption of 45,310 MJ/m3 of bioethanol. The process energy flow analysis evaluates two energy sustainability indicators, i.e., net energy gain and renewability factor, with further interpretation of variation effects of the key process parameters through a sensitivity analysis. The feasible ways of utilising water hyacinth as a fuel-grade bioethanol feedstock for industrial-scale production are discussed. [ABSTRACT FROM AUTHOR]

Bioenergy recovery from biomass is essential to address an eco-friendly disposal route for industrial by-products. This study focuses on the energy recovery from agro-industrial by-products in a combined heat and power unit (CHP) operating with a gas turbine fed with biogas. A rigorous thermodynamic model was presented and used for the energy generation assessment. The biogas was produced from anaerobic digestion (AD) of macaúba and açaí by-products with and without subcritical water pretreatment. The proposed methodology is easily applied and may provide answers to subside the conceptual design of an industrial plant operating with a CHP with a gas turbine for energy recovery. Simulation results showed electric and thermal energy potentials of, respectively, 3.4 and 11.2 MW when pretreatment is applied before the AD of macaúba shells. The thermal energy surplus was 58% higher than that obtained with direct AD of macaúba shells. On the other hand, applying subcritical water pretreatment of açaí seeds followed by AD to obtain biogas was not energetically profitable. However, feeding biogas from the direct AD of açaí seeds into the CHP would produce 3.4 and 7 MW, respectively, of electric and thermal energy. Moreover, considering the electricity replacement of 3.4 MW, 3699 tCO2-eq year−1 of greenhouse gas emissions could be avoided. Finally, using process simulation of first principle models for energy assessment was evinced to be a powerful tool to evaluate the viability of CHP operating with a gas turbine for bioenergy recovery in the food industry. [ABSTRACT FROM AUTHOR]

Efforts from the scientific community and the private sector are required to lower the costs of large‐scale production of nanomaterials (NMs) to enhance their commercialization. In this work, the computer‐aided process design of large‐scale NM synthesis procedures is comprehensively reviewed. Moreover, a generalized process flow diagram for all large‐scale production processes was constructed by surveying numerous scalable experimental procedures reported in the literature. Previous studies reporting simulation cases of large‐scale production processes of NMs and nanocomposites (NCs) are also reviewed based on the type of material produced, e.g., oxides, sulfides, carbonaceous materials, organic materials, metals, and other types of NMs. Finally, technical insights from classical chemical engineering specializations, such as altering process configurations, optimizing process variables, integrating chemical processes, utilizing renewable energy sources, conducting computational calculations, employing machine learning techniques, and studying the process's environmental impact, are reviewed for large‐scale NMs and NCs synthesis. [ABSTRACT FROM AUTHOR]

Natural pigment production represents an innovative and sustainable alternative to synthetic pigments. However, its industrial production to meet the global demand for pigments poses technological and economic challenges. In this work, a process design and simulation were conducted using SuperPro Designer to produce a blue natural pigment known as indigoidine, which is in high demand as a natural alternative to synthetic blue dyes in industries. The process design included upstream, bioreaction, and downstream processing to produce 113 tons per year of dry indigoidine. For the conception and design of the bioprocess, experimental data reported in the literature, such as kinetic and stoichiometric parameters, culture media, feeding strategy, and volumetric power input, were taken into account. The economic and profitability indicators of four scenarios were assessed based on a base scenario, which involved changing the typical stirred tank reactor to an airlift reactor, decreasing indigoidine recovery, and reducing biomass production. It was estimated that the use of an airlift reactor significantly improves the profitability of the bioprocess, while a 50 % decrease in biomass concentration (less than 40 g/L) significantly affected the profitability of the process. Finally, an equilibrium production point of around 56 tons per year was determined to balance total revenues with operational costs. This is the first work that offers valuable insights into the scaling-up of natural pigment indigoidine production using bacteria. [ABSTRACT FROM AUTHOR]

Since the advanced Integrated Circuit (IC) manufacturing process has reached the 14 nm technology node and beyond, the pattern size of integrated circuits has become much smaller than the theoretical minimum resolution of lithography. In order to further extend the performance of immersion lithography, the industry introduces Multiple Patterning Technology (MPT) and Negative Tone Development (NTD) lithography technology. MPT and NTD lithography have greatly improved the process window of immersion lithography, enabling ArF immersion lithography to extend to 7 nm or even 5 nm technology nodes and below. However, MPT still has limited ability to improve the process window for some special patterns. For example，for the poly gate process in Front End of Line (FEOL) or the metal routing process in Back End of Line (BEOL), IC design often uses a special kind of patterns, such as the bi-line or tri-line structures. Due to the fact that some type of the bi-line/tri-line structures have a semi-dense pattern on each side, the process window of these patterns are relatively narrow, making them difficult to manufacture. This paper focuses on the patterning technology scheme of bi-line/tri-line structures in IC design under the diffraction limit of 193 nm immersion lithography. This paper explores the solution for bi-line/tri-line patterns through mask split strategy and NTD lithography process simulation with a physical model, including illumination conditions, Optical Proximity Correction (OPC) methods, and photoresist process parameter design. This study provides a reference scheme for subsequent NTD process development and patterning technology, as well as a reference idea for IC design methods.

Compression resin transfer moulding (CRTM) has been widely used to manufacture automotive parts with reduced production cycle times. With the development of fast curing thermosetting resins, the CRTM process is a viable option for the high production rates in the transportation industry. However, the dynamic resin curing behaviour poses a potential risk of manufacturing defects in the part. In order to reduce the risk during the development of the tool and the process parameters, this paper proposes a modelling framework for the CRTM process when using fast curing resin systems. The work specifically focused on the coupling between heat transfer, resin cure, resin flow and preform compaction using a commercial code, PAM-RTM. The tool captures accurately the preform filling, temperature and resin pressure evolution during the injection and compression phase. The application of the framework was demonstrated for a complex 3D demonstrator. The predicted preform filling had an accuracy of 73% for the flow front evolution compared to the experimental results. This work demonstrates the validity of the framework proposed when dealing with resin systems that are challenging to process. [ABSTRACT FROM AUTHOR]

Due to the tool-less fabrication of parts and the high degree of geometric design freedom, additive manufacturing is experiencing increasing relevance for various industrial applications. In particular, the powder bed fusion of metals using a laser beam (PBF-LB/M) process allows for the metal-based manufacturing of complex parts with high mechanical properties. However, residual stresses form during PBF-LB/M due to high thermal gradients and a non-uniform cooling. These lead to a distortion of the parts, which reduces the dimensional accuracy and increases the amount of post-processing necessary to meet the defined requirements. To predict the resulting residual stress state and distortion prior to the actual PBF-LB/M process, this paper presents the finite-element-based simulation tool AscentAM with its core module and several sub-modules. The tool is based on open-source programs and utilizes a sequentially coupled thermo-mechanical simulation, in which the significant influences of the manufacturing process are considered by their physical relations. The simulation entirely emulates the PBF-LB/M process chain including the heat treatment. In addition, algorithms for the part pre-deformation and the export of a machine-specific file format were implemented. The simulation results were verified, and an experimental validation was performed for two benchmark geometries with regard to their distortion. The application of the optimization sub-module significantly minimized the form deviation from the nominal geometry. A high level of accuracy was observed for the prediction of the distortion at different manufacturing states. The process simulation provides an important contribution to the first-time-right manufacturing of parts fabricated by the PBF-LB/M process.

Software process simulation (SPS) has become an effective tool for software process management and improvement. However, its adoption in industry is less than what the research community expected due to the burden of measurement cost and the high demand for domain knowledge. The difficulty of extracting appropriate metrics with real data from process enactment is one of the great challenges. We aim to provide evidence‐based support of the process metrics for software process (simulation) modeling. A systematic literature review was performed by extending our previous review series to draw a comprehensive understanding of the metrics for process modeling following our proposed ontology of metrics in SPS. We identify 131 process modeling studies that collectively involve 1975 raw metrics and classified them into 21 categories using the coding technique. We found product and process external metrics are not used frequently in SPS modeling while resource external metrics are widely used. We analyze the causal relationships between metrics. We find that the models exhibit significant diversity, as no pairwise relationship between metrics accounts for more than 10% SPS models. We identify 17 data issues may encounter in measurement and 10 coping strategies. The results of this study provide process modelers with an evidence‐based reference of the identification and the use of metrics in SPS modeling and further contribute to the development of the body of knowledge on software metrics in the context of process modeling. Furthermore, this study is not limited to process simulation but can be extended to software process modeling, in general. Taking simulation metrics as standards and references can further motivate and guide software developers to improve the collection, governance, and application of process data in practice. [ABSTRACT FROM AUTHOR]

The development of wind power has brought about increasing challenges in decommissioning, among which DWTBs (decommissioned wind turbine blades) are the most difficult component to deal with. To enable the cost-effective, energy-efficient, and environmentally friendly large-scale utilization of DWTBs, an experimental study on thermogravimetric and pyrolysis characteristics of DWTBs was carried out. A new process involving recycling glass fiber with pyrolysis gas re-combustion and flue gas recirculation as the pyrolysis medium was innovatively proposed, and the simulation calculation was carried out. Thermogravimetric experiments indicated that glass fiber reinforced composite (GFRC) was the main heat-generating part in the heat utilization process of blades, and the blade material could basically complete pyrolysis at 600 °C. As the heating rate increased, the formation temperature, peak concentration, and proportion of combustible gas in the pyrolysis gas also increased. The highest peak concentration of CO gas was observed, with CO2 and C3H6 reaching their peaks at 700 °C. The solid product obtained from pyrolysis at 600 °C could be oxidized at 550 °C for 40 min to obtain clean glass fiber. And the pyrolysis temperature increased with the increase in the proportion of recirculation flue gas. When the proportion of recirculation flue gas was 66%, the pyrolysis temperature could reach 600 °C, meeting the necessary pyrolysis temperature for wind turbine blade materials. The above research provided fundamental data support for further exploration on high-value-added recycling of DWTBs. [ABSTRACT FROM AUTHOR]

The hydrogen–water isotope catalytic exchange process has been widely applied in the tritium-containing water treatment process. It can be compared and analyzed conveniently with process simulation software. In this study, the catalytic exchange process was simulated by Aspen Plus software (V11). According to the simulation results, the main reaction process was that HDO in the liquid phase converts into HD in the gas phase, and the reaction mainly occurred at the bottom of the column, exhibiting a two-orders-of-magnitude-higher reaction amount compared to that observed in the top section. Different side reactions occur at distinct positions along the column, exhibiting a reaction amount that is lower by one to two orders of magnitude compared to the main reaction and aligning in the same direction as the main reaction. The optimum operating temperature is 60~80 °C, with the best performance observed at 70 °C, because of the large reaction equilibrium constant and the suitable ratio of vapor to hydrogen (1:4~1:1.5) in the gas phase. The influence of the residence time was investigated by introducing reaction kinetic equations. The residence time should be more than 1 s to ensure an adequate reaction. The influence of operating conditions on the hydrogen–water isotope catalytic exchange process can be deeply investigated by process simulation, and more mass transfer process quantities can be obtained. It plays a promoting role in guiding the process design and condition optimization. [ABSTRACT FROM AUTHOR]

The technical and economic challenges are enormous in developing gas wells with a high CO2 content (> 50 mol %), such as the East Natuna gas field, which has 71 mol % (86 mass %). Carbon capture technology in gas wells with high CO2 content is studied to find a more economical one. In this study, the technology for capturing high concentrations of CO2 is varied from gas wells, Controlled Freeze Zone (CFZ), and cryogenic distillation which will be analyzed based on cost. Variations in the CO2 content of gas wells are 75 %, 80 %, 85 %, 90 %, and 95 % in mass fraction simulated using Aspen Plus V.11.0. Based on this research, CFZ technology and cryogenic distillation can obtain purity up to 99 % and recovery above 78 %. However, the total annual cost (annual capital and operating costs) of CFZ technology is lower than cryogenic distillation technology, so CFZ technology is suitable for capturing CO2 in gas wells with high CO2 content. [ABSTRACT FROM AUTHOR]

The CO2 phase change capture process has low regeneration energy consumption, but in actual production, the CO2 content (mole fraction, the same below) in flue gas generated by the upstream process is unstable, which can lead to changes in the overall energy consumption of the process. Therefore, it is necessary to study the adjustment strategies of the process parameters under different CO2 content of flue gas. Using Python to invoke Aspen Plus to simulate the near isothermal CO2 capture technology, and the effects of adsorption tower temperature (ta), desorption tower temperature (td), liquid/gas ratio (v), amine concentration (c) and desorption liquid circulation ratio (s) on the regeneration energy consumption and CO2 capture rate and the corresponding regulation strategies were analyzed. The results show that td has the most significant effect on CO2 capture rate, and the correlation coefficient is the highest (74.78%) when the CO2 content is 5.00%. ta has the most significant impact on regeneration energy consumption, and when CO2 content is 20.00%, its correlation coefficient is the highest (-55.26%). With the CO2 content increases from 5.00% to 20.00%, the regeneration energy consumption decreases from 2.35 GJ/t to 2.13 GJ/t under the condition that the CO2 capture rate is greater than 90.00%. In addition, ta, td, c and v should be adjusted accordingly according to CO2 content to ensure that CO2 capture rate is greater than 90.00% and the regeneration energy consumption is lowest. [ABSTRACT FROM AUTHOR]

Maximizing the use of digitally captured data is a key requirement for many of the late adopters of digital infrastructure. One of the newcomers is the chemical industry in the area of digitized laboratories. Here, tools and services that satisfy individual needs still need to be developed and distributed within the community. This work explores the potential of using graph databases — specifically those modeled via ontological knowledge graphs — to describe complex data linkages and draw logical conclusions. While knowledge graphs are not widely utilized in catalysis research, this study introduces a methodology to highlight their usability for semantic description and integration into diverse value chains with contact to the domain of (bio)chemistry and catalysis. A demonstration is performed how ontologies and their knowledge graphs can be applied to perform essential functions of semantic annotation to chemical reactions, which are difficult to model relational. Traditional data description methods can be neglected using description logic, showing how logical inferences at the machine level can enrich data. This work also illustrates the seamless integration of this enhanced data into process simulations, connecting semantic description with practical applications. The immediate benefits for catalysis research are emphasized and the development of new tools and services envisioned. By clarifying how these graphs can be integrated into existing workflows, researchers are empowered to make the most of digitally acquired data in catalytic processes. This practical methodology lays the foundation for improved decision-making and innovation, fostering advancements in the field of catalysis research. [ABSTRACT FROM AUTHOR]

The conversion of biomass residues into syngas through gasification is attractive for energy and process industry applications. However, transportation, storage, and operational challenges limit the conventional direct solid biomass gasification process. To address these issues, the intermediate conversion of biomass to bio‐oil has emerged as a promising alternative. Bio‐oil offers improved transport and storage capabilities due to its higher mass and energy density, enabling the decoupling of solid biomass supply and syngas demand. This study compares two routes for syngas production: direct gasification of solid biomass and indirect gasification using bio‐oil from biomass pyrolysis as an intermediate with biochar and pyrolysis gas supplying thermal energy to the pyrolysis stage. Biochar combustion provides about 1.4 MJ kg−1 of dry biomass to maintain the pyrolysis temperature at 480°C. Using AspenPlus® simulations, the composition and Low Heating Value of the syngas produced by both routes are analyzed. Energy and exergy analysis at different equivalence ratios and temperatures revealed that direct gasification has higher efficiencies than indirect gasification. At 1000°C and an equivalence ratio of 0.4, the highest energy and exergy efficiencies occurred in direct gasification processes. The energy efficiency of direct and indirect gasification amounted to 62% and 53%, respectively. At the same time, the corresponding exergy efficiencies were 65% and 61%. The syngas of direct and indirect gasification processes is a starting point to produce energy, synthetic fuels, and chemicals; this study provides insights for designing and optimizing biomass gasification processes. [ABSTRACT FROM AUTHOR]

As the aerospace industry continues to adopt additively manufactured (AM) parts for flight hardware, process simulation becomes more attractive to improve the manufacturing process by understanding how process parameters affect part quality and performance. Process simulation can also be used to predict and prevent build failures before the printing process. The powder bed fusion process of Ti-6Al-4V material is modeled using commercial finite element software to simulate the selective laser melting process. The thermal history is obtained from transient heat transfer analysis. Both the inherent strain approach and a sequential thermal-mechanical approach are employed to predict residual stress and part distortion. A National Agency for Finite Element Methods and Standards (NAFEMS) benchmark problem is presented as a numerical example. It is a thin wall structure with geometry features that can lead to part defects due to thermal distortion. It is shown that both analysis approaches are able to capture the thin-member bridging behavior, stepping behavior, and general distortion contour plot as those published by NAFEMS. [ABSTRACT FROM AUTHOR]

While there are software tools available for helping to conduct life cycle assessment (LCA), such as OpenLCA, these tools lack integration with process design, simulation, and optimization software. As LCA has a critical role in sustainable product design, this paper presents a platform called EMSO_OLCA, which integrates the LCA provided by OpenLCA into the Environment for Modeling, Simulation, and Optimization (EMSO). EMSO_OLCA incorporates a database of environmental impact assessment methodologies from OpenLCA and aligns with the principles of LCA outlined in ISO 14040 and ISO 14044. Validation tests were conducted to compare the results obtained by the LCA of sugarcane ethanol using OpenLCA and EMSO_OLCA, revealing a high level of agreement. The average relative error was 0.045%, indicating a negligible discrepancy between the tools. Moreover, it took only 0.3 s for the calculation, which is desirable for use with process system engineering tools. A second case study was applied to combined steam and electricity production from the combustion of sugarcane bagasse and straw in a combined heat and power system. The results show the integration of LCA with simulation and sensitivity analysis tools, thus supporting sustainable decision-making processes. EMSO_OLCA bridges the gap between LCA and process engineering, enabling a holistic approach to the sustainability, design, and implementation of environmentally friendly solutions. [ABSTRACT FROM AUTHOR]

Biomass chemical looping hydrogen generation (CLH) process is a new thermochemical conversion technology which could realize the efficient conversion of biomass to hydrogen. In this study, the fuel reaction stage is decoupled into two stages, namely pyrolysis and gasification stages, but the AR in the general CLH process is removed. The oxygen carrier is used to couple the pyrolysis, gasification and hydrogen generation stages. As such, by coupling a tar chemical looping reforming (TCLR) process for pyrolysis tar, a biomass pyrolysis-gasification-hydrogen generation combined cycle system (namely, BPGH-TCLR) is constructed. Then, Aspen plus software is used to analyze the influence of process parameters including oxygen carrier/biomass ratio, gasification temperature, water steam/biomass ratio, reforming temperature, and explore the corresponding optimal parameter values. Also, mass, energy and exergy balances of the system are investigated whereas the system performance is evaluated. The calculation results show that 100 kg/h biomass as the BPGH-TCLR feed can produce 8.03 kg/h hydrogen and 35.51 kW net electric power with energy and exergy efficiencies of 59.35% and 49.24%, respectively, and a biomass conversion efficiency of 52.49%. Compared with the other processes for hydrogen production, this proposed BPGH-TCLR system shows better hydrogen generation efficiency as well as higher biomass conversion efficiency. • A novel system for hydrogen production from biomass is proposed and simulated. • The system consists of chemical looping process/tar chemical looping reforming. • The system has relatively higher energy utilization efficiency and exergy efficiency. • The system has higher hydrogen generation efficiency and biomass conversion rate. [ABSTRACT FROM AUTHOR]

Compared to conventional monoethanolamine (MEA), alternative solvents are expected to substantially contribute to reduce the energy demand of postcombustion CO2 capture from flue gases. This study presents a comprehensive techno-economic analysis of a 27wt% 2-amino-2-methyl-1- propanol (AMP) + 13wt% piperazine (PZ) aqueous solution for CO2 capture, compared to a 30 wt% MEA solution. The study addresses the retrofit of a carbon capture unit to a biomass-fired combined heat and power (CHP) plant, effectively making it a bioenergy with a carbon capture and storage (BECCS) system. The treated flue gas has a flow rate of 23 tons/hour (t/h) with 11.54 vol% CO2 and a 90% capture rate is aimed for. Aspen Plus V14 was employed for process simulations. Initially, binary interaction parameters for AMP/PZ, AMP/H2O, and PZ/H2O are regressed using vapor-liquid equilibrium (VLE) data, which were retrieved from literature along with reaction kinetics. Validation of parameters from available experimental literature yields an average absolute relative deviation (AARD) of only 5.9%. Afterwards, a process simulation model is developed and validated against experimental data from a reference pilot plant, using a similar AMP/PZ blend, resulting in 5% AARD. Next, a sensitivity analysis optimizes operating conditions, including solvent rate, absorber/stripper packing heights, and stripper pressure, based on regeneration energy impact. Optimized results, compared to MEA, reveal that AMP/PZ reduces the energy consumption from 3.61 to 2.86 GJ/tCO2. The retrofitting of the capture unit onto the selected CHP plant is examined through the development of a dedicated model. Two control strategies are compared to address energy unavailability for supplying the capture unit. The analysis spans 4 months, selected to account for seasonal variations. At nominal capacity, CO2 emissions, rendered negative by biomass combustion and CO2 capture, reach a maximum of -3.4 tCO2/h compared to 0.36 tCO2/h before retrofitting. Depending on the control strategy and CHP plant operating point, the Specific Primary Energy Consumption for CO2 Avoided (SPECCA) ranges from 4.91 MJ/kgCO2 to 1.76 MJ/kgCO2. Finally, an economic comparison based on systematic methodology reveals a 7.87% reduction in capture cost favoring the AMP/PZ blend. Together, these findings highlight AMP/PZ as a highly favorable alternative solvent. [ABSTRACT FROM AUTHOR]

A technological process for hot forging of two-layer forgings with deep cavities and an inverted cone has been developed. A hot forging process flow chart has been analyzed. Digital simulation using QForm software was employed to study the effect of the process parameters on the force characteristics of the metal-forming process, stress-strain condition, and temperature fields of the forging and tooling after each pass. A new design of the die tooling has been proposed. [ABSTRACT FROM AUTHOR]

In the summer of 2016, an incidental discovery of a bronze star-shaped mace head was made in a forest situated in the territory of the village of Niebieszczany, South-eastern Poland. Its form and available parallels indicate that it could have been used during 12th–13th c., most likely in the 13th c. In previous studies on mace heads not much attention was paid to technological issues. It was assumed that they were manufactured during the 12th and 13th c. in the territory of Rus’, and have been exported from these territories to neighbouring areas. The comprehensive analysis of the bronze star-shaped mace head from Niebieszczany provided new conclusions concerning the manufacture of such artefacts. This mace head was most likely made in a multi-part wax model with two runners and a pouring basin that were joined on a clay core and then covered with clay in order to make a mould. In order to extract a ready artefact, such a mould had to have been destroyed after the casting. A simulation of filling and solidification using MAGMA software showed the process of filling the casting cavity of the mould and clarified defects that were recorded on the surface of the casting. Metallographic analyses (ED-XRF) revealed that the mace head from Niebieszczany was cast using a leaded tin-bronze of good quality, remarkable for its high resistance to heavy loads as well as to corrosion and abrasion. Meticulous observations showed that it was repaired using a bronze alloy with much higher contents of tin and lead. [ABSTRACT FROM AUTHOR]

Sustainable hydrogen generation is preferred over production from fossil sources in the context of a carbon‐neutral economy. As a result, production costs for CO2‐based products are estimated to be much higher than those of their fossil equivalents. Hence, it is essential to optimize process chains regarding their hydrogen efficiency. In this study, a concept for the directly coupled production of CO2‐based methanol and formaldehyde in a modified silver catalyst process is evaluated regarding the utilization of H2. Detailed simulations in Aspen Plus allow the comparison to the separately operated synthesis of green methanol and formaldehyde. By directly connecting both production steps, utilization ratios of introduced H2 and CO2 could be improved, reaching values of 98 % and 99 %, respectively. [ABSTRACT FROM AUTHOR]

A model-based investigation of the interplay between furnace setup and spatio-temporal evolution of particles' state variables is also presented. The effect of feed size distribution and processing of ultrafine ore are discussed. The process is controlled primarily by the wall temperature and secondarily the air feeding rate; an increase of furnace wall temperature from 900 to 1200°C reduced the final density to 484, 979, and 1262 kg/m3 for feed size of 150 μm, 250 μm, and 350 μm. Model predictions are in good agreement with the experimental measurements possessing differences below 10% in most cases. [ABSTRACT FROM AUTHOR]

Software process simulation models (SPSMs) that are based on descriptive process models offer the executability that can demonstrate dynamic changes of software processes over time. Verification and validation (V&V) is critical in SPSMs for guaranteeing the quality and reliability of models. V&V of dynamic software process models is more complex and challenging than for static software process models. This work systematically summarizes and maps V&V studies in SPSM to provide guidelines for future research and practice. Specifically, this study aims at identifying the focus of research on V&V, the methods used for V&V, and how to implement V&V of SPSMs in software engineering research. We conducted a systematic mapping study on studies of SPSMs that report on their V&V activities. Under the guidance of a V&V meta‐model for SPSMs, we study four research questions about V&V process. We identified 107 primary studies from a pool of 313 papers on SPSMs until 2021. There are two main results of our study. The first one presents the relationship between quality aspects of SPSMs and the V&V methods to assure them. The second result reveals the relationships among the modeling process, three modeling steps, five quality aspects, and 10 V&V methods. Generally, researchers do not pay sufficient attention to V&V, as 65.8% ((313−107)/313) failed to mention or elaborate on their V&V process. We systematically summarize and map the state‐of‐the‐art V&V research in software process modeling field to support modelers' practice and improve their V&V process. [ABSTRACT FROM AUTHOR]

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Prospective environmental and technological assessment of emerging chemical processes is necessary to identify, analyze and evaluate the technologies that are highly imperative in the transition towards climate neutrality. The investigation of the environmental impacts and material and energy requirements of the processes at the low technology readiness level (TRL) is important in making early decisions about the feasibility of adapting and upscaling the process to the industrial level. However, the upscaling of new chemical processes has always been a major challenge; and in this context, there is no general methodological guidance available in the literature. Hence, a new comprehensive methodological framework for upscaling of novel chemical processes is designed and presented based on thermodynamic process modeling and simulation. The practical implementation of the proposed methodology is extensively discussed by developing a scaled-up novel carbon capture and utilization (CCU) process comprised of sequestration of carbon dioxide (CO2) from blast furnace gas with a capacity of 1000 liter per hour (L/h) using methanol and its utilization as a precursor to produce methane (CH4). It was found that thermodynamic process modeling and simulations based on the perturbed-chain statistical associating (PC-SAFT) equation of state (EOS) can precisely estimate the CO2 solubility in methanol and conversion to CH4 at various temperature and pressure conditions. The achieved thermophysical property and kinetics parameters can be employed in process simulations to estimate scaled-up environmental flows and material and energy requirements of the process. [ABSTRACT FROM AUTHOR]

Sustainable hydrogen generation is preferred over production from fossil sources in the context of a carbon‐neutral economy. As a result, production costs for CO2‐based products are estimated to be much higher than those of their fossil equivalents. Hence, it is essential to optimize process chains regarding their hydrogen efficiency. In this study, a concept for the directly coupled production of CO2‐based methanol and formaldehyde in a modified silver catalyst process is evaluated regarding the utilization of H2. Detailed simulations in Aspen Plus allow the comparison to the separately operated synthesis of green methanol and formaldehyde. By directly connecting both production steps, utilization ratios of introduced H2 and CO2 could be improved, reaching values of 98 % and 99 %, respectively. [ABSTRACT FROM AUTHOR]

This paper presents the first integrated techno-economic and life cycle assessment of microemulsion systems being applied for rhodium-catalyzed hydroformylation of long-chain alkenes at industrial scale. The case study describes a projected 150 kt/a production of tridecanal (US gulf coast, 2019). The industrial success of the hydroformylation of short-chain alkenes lies in the continuous recycling of the rhodium-containing water phase. Microemulsion systems can be applied to transfer this concept to long-chain alkenes by overcoming the miscibility gap between the aqueous catalyst phase and the unipolar alkene phase and, moreover, by generating a temperature-induced multi-phase system enabling the immobilization of the catalyst and its continuous recycling, as demonstrated in miniplant operations with dodecene and rhodium/SulfoXantPhos. Customizable simulation models have been developed for scale-up and assessment of the miniplant data. Surprisingly, a profitability-driven sensitivity study indicates a base case optimum at low residence time with low alkene conversion leading to large throughput streams and high raw material purge rates. The comparison to the industrial cobalt-based benchmark system shows an economic advantage regarding net present value (Rh: 68 M$; Co: 62 M$), while about half of the environmental indicators are in favor or equivalent. In a best-case scenario considering zero leaching of expensive rhodium the net present value increases by almost 40% accompanied by a shift to overall lower environmental impacts than the benchmark. In conclusion, the investigated miniplant data suggest microemulsion systems to be competitive when applied in continuous processes at a large scale. [ABSTRACT FROM AUTHOR]

A novel reactor concept for ammonia decomposition utilizing tail gas from a purification unit as heat supply is presented. The designed micro‐structured reactor integrates both endothermic ammonia decomposition and exothermic tail gas combustion. The reactor and corresponding process are simulated using a mathematical multi‐scale model, which combines the results of multiple detailed computational fluid dynamics simulations into a fast surrogate model. The latter is coupled with a process simulation software via a so‐called container to simulate the entire process. The efficiency of the presented reactor concept is determined and benefits over alternative approaches are highlighted. [ABSTRACT FROM AUTHOR]