Process synthesis and optimization of biorefinery configurations

Recently, there has been a growing interest in the development of cost‐effective technologies for the production of biofuels. A common approach to biofuel research is to invent or improve a biochemical or thermochemical conversion step. Subsequently, other conversion and separation steps are added to form a complete biorefinery flowsheet. Because this approach is structured around a specific conversion step, it may limit the possibilities of configuring optimal and innovative biorefineries. This article proposes a novel and systematic two‐stage approach to the synthesis and optimization of biorefinery configurations, given available feedstocks and desired products. In the synthesis stage, a systems‐based approach is developed to create a methodical way for synthesizing integrated biorefineries. This method is referred to as “forward‐backward” approach. It involves forward synthesis of biomass to possible intermediates and reverse synthesis starting with the desired products and identifying necessary species and pathways leading to them. In the optimization stage, Bellman's principle of optimality is applied to decompose the optimization problem into subproblems in which an optimal policy of available technologies is determined for every conversion step. An optimization formulation is utilized to determine the optimal configuration based on screening and connecting the optimal policies and generating the biorefinery flowsheet. A case study of alcohol‐producing pathways from lignocellulosic biomass is solved to demonstrate the merits of the proposed approach. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

Challenges and opportunities in computer-aided molecular design

In this paper, the significant development, current challenges and future opportunities in the field of chemical product design using computer-aided molecular design (CAMD) tools are highlighted. With the gaining of focus on the design of novel and improved chemical products, the traditional heuristic based approaches may not be effective in designing optimal products. This leads to the vast development and application of CAMD tools, which are methods that combine property prediction models with computer-assisted search in the design of various chemical products. The introduction and development of different classes of property prediction methods in the overall product design process is discussed. The exploration and application of CAMD tools in numerous single component product designs, mixture design, and later in the integrated process-product design are reviewed in this paper. Difficulties and possible future extension of CAMD are then discussed in detail. The highlighted challenges and opportunities are mainly about the needs for exploration and development of property models, suitable design scale and computational effort as well as sustainable chemical product design framework. In order to produce a chemical product in a sustainable way, the role of each level in a chemical product design enterprise hierarchy is discussed. In addition to process parameters and product quality, environment, health and safety performance are required to be considered in shaping a sustainable chemical product design framework. On top of these, recent developments and opportunities in the design of ionic liquids using molecular design techniques have been discussed.     

Computer-aided molecular design in the continuous-molecular targeting framework using group-contribution PC-SAFT

Computer-aided molecular design allows generating novel fluids fulfilling a set of target properties. An integrated design of fluid and process directly employs a process-based objective function. In this work, we solve the integrated process and fluid design problem using the continuous-molecular targeting computer-aided molecular design (CoMT–CAMD) framework. CoMT–CAMD exploits the molecular picture underlying the PC-SAFT equation of state. In the simultaneous optimization of process and fluid, relaxed pure component parameters allow for an efficient optimization. The result is a hypothetical optimal target fluid. In previous work, fluids showing similar performance as the target fluid were obtained from a mapping onto a database. Here, we integrate computer-aided molecular design to realize the actual design of novel fluids. The resulting method for fluid design is based on a group-contribution method for the PC-SAFT parameters (GPC-SAFT) and applied to the design of working fluids for Organic Rankine cycles and solvents for CO₂ capture.     

Synthesis of sustainable integrated biorefinery via reaction pathway synthesis: Economic,incremental enviromental burden and energy assessment with multiobjective optimization

With the increasing attention toward sustainable development, biomass has been identified as one of the most promising sources of renewable energy. To convert biomass into value‐added products and energy, an integrated processing facility, known as an integrated biorefinery is needed. To date, various biomass conversion systems such as gasification, pyrolysis, anaerobic digestion and fermentation are well established. Due to a large number of technologies available, systematic synthesis of a sustainable integrated biorefinery which simultaneously considers economic performance, environmental impact, and energy requirement is a challenging task. To address this issue, multiobjective optimization approaches are used in this work to synthesize a sustainable integrated biorefinery. In addition, a novel approach (incremental environmental burden) to assess the environmental impact for an integrated biorefinery is presented. To illustrate the proposed approach, a palm‐based biomass case study is solved. © 2014 American Institute of Chemical Engineers AIChE J, 61: 132–146, 2015     

Integrated chemo- and biocatalytic processes: a new fashion toward renewable chemicals production from lignocellulosic biomass

Concerns over climate change and environmental pollution resulting from petroleum refining has spurred the exploitation of green replacements for producing chemicals and fuels. Valorization of lignocellulosic biomass into chemicals represents a promising alternative to petroleum refining. Biological and chemical catalysis are two leading routes for lignocellulose variolization, but strategies relying simply on biological or chemical conversion have shown limitations. Integrating biocatalysts with chemocatalysts could leverage the inherent strengths of both while circumventing their respective disadvantages, benefiting product yield and selectivity, and reducing cost and waste generation. This review focuses on the coupled chemocatalytic and biocatalytic synthesis of renewable chemicals from polysaccharides and their derived platform chemicals. In addition, strategies for producing value-added products from lignin via integrated chemical depolymerization and biological conversion are highlighted. The techno-economics of integrating chemocatalysts and biocatalysts in producing chemicals in the context of biorefinery are also discussed. Finally, perspectives on designing integrated chemical and biological catalysis for renewable chemicals production are provided. © 2022 Society of Chemical Industry (SCI).     

Process synthesis and optimization of a sustainable integrated biorefinery via fuzzy optimization

Over the last decade, utilization of biomasses is highly encouraged to conserve scarce resources, reduce dependency on energy imports as well as protect the environment. Integrated biorefinery emerged as noteworthy concept to integrate several conversion technologies to have more flexibility in product generation with energy self‐sustained and reduce the overall cost of the process. Integrated biorefinery is a processing facility that converts biomass feedstocks into a wide range of value added products via multiple technologies. In this work, a systematic approach for the synthesis and optimization of a sustainable integrated biorefinery which considers economic, environmental, inherent safety, and inherent occupational health performances is presented. Fuzzy optimization approach is adapted to solve four parameters simultaneously as they are often conflicting in process synthesis and optimization of an integrated biorefinery. An integrated palm oil‐based biorefinery case study is solved to demonstrate the proposed approach. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4212–4227, 2013     

Synthesis and Structural Analysis of Branched-Chain Derivatives of Methyl Oleate

As part of a project to develop new value-added industrial applications for cottonseed oil (such as biodiesel, fuel additives, and lubricants), studies were conducted on the synthetic conversion of oleic acid to branched-chain fatty acid esters. In these studies, methyl oleate was brominated in the allylic position and subsequently treated with organocuprate reagents to produce novel branched-chain derivatives (methyl, n-butyl, phenyl). Original reaction conditions afforded only the branched methyl derivatives as major products. Modification of reaction conditions (lower temperature, less organocuprate reagent) afforded predominantly the desired n-butyl and phenyl derivatives and minimized products resulting from attack on the ester functionality. Details of the syntheses, characterization (especially by NMR), and the properties of the products (with emphasis on low-temperature properties) are discussed.     

Graph machine learning for design of high-octane fuels

Fuels with high-knock resistance enable modern spark-ignition engines to achieve high efficiency and thus low CO₂ emissions. Identification of molecules with desired autoignition properties indicated by a high research octane number and a high octane sensitivity is therefore of great practical relevance and can be supported by computer-aided molecular design (CAMD). Recent developments in the field of graph machine learning (graph-ML) provide novel, promising tools for CAMD. We propose a modular graph-ML CAMD framework that integrates generative graph-ML models with graph neural networks and optimization, enabling the design of molecules with desired ignition properties in a continuous molecular space. In particular, we explore the potential of Bayesian optimization and genetic algorithms in combination with generative graph-ML models. The graph-ML CAMD framework successfully identifies well-established high-octane components. It also suggests new candidates, one of which we experimentally investigate and use to illustrate the need for further autoignition training data.     

Valorisation of Jatropha curcas L. plant parts: Nut shell conversion to fast pyrolysis oil

The biorefinery concept is a very powerful concept to optimise the conversion of biomass resources to value-added products with a minimum loss of energy and mass and a maximum overall value of the production chain. We here report our activities on the application of this concept to valorise the Jatropha curcas L. (JCL) shrub, a (sub)-tropical plant producing a high quality plant oil that may be converted to biodiesel in good yields. Within a research consortium of Dutch and Indonesian researchers, we are exploring high added value outlets for byproducts of the JCL plant (leaves, latex) and seed processing units (press cake). As an example, we here report fast pyrolysis experiments to convert the nut shells to fast pyrolysis oil, a promising second generation biofuel. The fast pyrolysis experiments were carried out in a continuous bench scale pyrolyser at a throughput of 2.27 kg/h at 480 °C and atmospheric pressure. The nut shell pyrolysis oil was obtained in 50 wt.% yield, the remainder being char (23 wt.%), gas (17 wt.%) and ash. Relevant product properties of the oil were determined and indicate that the oil is inhomogeneous in nature.     

Separation of butanol from acetone-butanol-ethanol fermentation by a hybrid extraction-distillation process

The alternative fuel butanol can be produced via acetone-butanol-ethanol (ABE) fermentation from biomass. The high costs for the separation of ABE from the dilute fermentation broth have so far prohibited the industrial-scale production of bio-butanol. In order to facilitate an effective and energy-efficient product removal, we suggest a hybrid extraction-distillation downstream process with ABE extraction in an external column. By means of computer-aided molecular design (CAMD), mesitylene is identified as novel solvent with excellent properties for ABE extraction from the fermentation broth. An optimal flowsheet is developed by systematic process synthesis which combines shortcut and rigorous models with rigorous numerical optimization. Optimization of the flowsheet structure and the operating point, consideration of heat integration, and the evaluation of the minimum energy demands are covered. It is shown that the total annualized costs of the novel process are considerably lower compared to the costs of alternative hybrid or pure distillation processes.     

System Study on Hydrothermal Gasification Combined With a Hybrid Solid Oxide Fuel Cell Gas Turbine

The application of wet biomass in energy conversion systems is challenging, since in most conventional systems the biomass has to be dried. Drying can be very energy intensive especially when the biomass has a moisture content above 50 wt.% on a wet basis. The combination of hydrothermal biomass gasification and a solid oxide fuel cell (SOFC) gas turbine (GT) hybrid system could be an efficient way to convert very wet biomass into electricity. Therefore, thermodynamic evaluation of combined systems with hydrothermal gasification units and SOFC–GT hybrid units has been performed. Three hydrothermal gasification cases have been evaluated; one producing mainly methane, a second one producing a mixture of hydrogen and methane and the last one producing mainly hydrogen. These three gasification systems have been coupled to the same SOFC–GT hybrid system. All the integrated systems have electrical exergy efficiencies around 50%, therefore, the combination of supercritical water gasification and SOFC–GT hybrid systems seems promising. The overall system performance depends for a large part on the liquid gas separation. Further research is required for finding out the optimal separation conditions.     

Thermo-environomic optimisation strategy for fuel decarbonisation process design and analysis

To meet the CO₂ reduction targets and ensure sustainable energy supply, the development and deployment of cost-competitive innovative low-carbon energy technologies is essential. To design and evaluate the competitiveness of such complex integrated energy conversion systems, a systematic thermo-environomic optimisation strategy for the consistent modelling, comparison and optimisation of fuel decarbonisation process options is developed. The environmental benefit and the energetic and economic costs are assessed for several carbon capture process options. The performance is systematically compared and the trade-offs are assessed to support decision-making and identify optimal process configurations with regard to the polygeneration of H₂, electricity, heat and captured CO₂. The importance of process integration in the synthesis of efficient decarbonisation processes is revealed. It appears that different process options are in competition when a carbon tax is introduced. The choice of the optimal configuration is defined by the priorities given to the different thermo-environomic criteria.     

生物炼制与石油炼制一体化——促进我国生物质能源发展的有效对策之一

生物炼制是与石油炼制互补的新型工业生产模式,对我国生物质能源发展有重要作用。我国生物炼制产业发展目前处于起步阶段,面临着原料、技术等问题。针对我国国情,提出了在条件适当地区,生物炼制企业建设采取生物炼制与石油炼制一体化建设的设想。以燃料乙醇项目建设为例,通过对单独建设和一体化建设两种方案的比较,从成本、未来发展和原料供应等方面分析了一体化建设的优势。研究表明生物炼制与石油炼制一体化模式将对我国能源、化工等行业的可持续性发展起到促进作用。     

Optimal design of solvents for extractive reaction processes

It is well known that solvents can have significant effects on rates and equilibrium compositions of chemical reactions. The computer‐aided molecular design (CAMD) of solvents for heterogeneous liquid phase reactions is challenging due to multiple solvent effects on reaction and phase equilibria. In this work, we propose a CAMD methodology based on a genetic algorithm (GA) for identifying optimal solvents for liquid phase reactions where the objective is to maximize the reaction equilibrium conversion. In particular, a novel molecular encoding method is introduced to facilitate the construction and evaluation of solvent molecules in a defined structure space. The reliability of the method for fast identification of optimal reaction solvents is demonstrated for a selected biphasic esterification reaction. The proposed approach opens up new perspectives for intensifying extractive reaction processes via the purposeful design of solvent molecules. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3238–3249, 2016     

Integrated design of diesel hydrotreating processes

This work presents an integrated approach for the design of diesel hydrotreating processes employing a simulated annealing optimisation algorithm. The modelling of reactor, separation and heat recovery system for diesel hydrotreating processes is discussed, and a novel optimisation framework is developed for the design of complex refinery processes. A comparison with conventional approach to process design, i.e. sequential evolution of design, is given to illustrate the ability of proposed approach to obtain overall hydrotreating process designs with minimum total annualised costs. The proposed integrated approach takes into account the trade-offs between capital and operating costs, as well as interactions between the hydrotreater, distillation column, and the associated heat exchanger network.     

A novel synthesis of diesel fuel additives from dimethyl ether using dielectric barrier discharges

A diesel fuel additive has been synthesized from conversion of dimethyl ether (DME) using dielectric barrier discharge (DBD) plasma at atmospheric pressure and low temperatures. A high conversion of DME has been achieved. The product of such conversion is a mixture of hydrocarbons and oxygenates that can be used as high-performance diesel fuel additives. The maximum conversion of DME reached 47.2% with a selectivity of liquid product (a mixture of dimethoxy-containing hydrocarbons) more than 39.0% at 120°C and a 30 ml/min flow rate of DME.     

Mathematical approach to compute the molecular composition of hydrothermal liquefaction-derived renewable crude oil

Hydrothermal liquefaction (HTL), a thermo-chemical conversion process, uses water as a reaction medium at elevated pressure and temperature, to convert biomass to renewable liquid fuel and recovers fertilizer-rich water. To assess the techno-economic screening of HTL oils from various feedstock, it is crucial to have information on molecular composition of the feed and products. There are limitations of existing analytical methods to identify and quantify all the molecules present in the bio-fuel. Therefore, there is a need to find alternate ways to quantify the molecular composition of feed and expected products. The modeling work on bio-oil is developed and validated on mathematical approach using simple analytical results like CHNO along with structural analysis of oil like Fourier-transform infrared, nuclear magnetic resonance analysis for HTL derived oil from microalgae. This mathematical framework is further extended to predict the molecular composition of oil obtained from HTL of feedstocks like mixed plastic waste, sludge, and so on. A multi-dimensional molecular matrix is developed based on the distributions of side chains, aromatic rings, and olefinic carbon on top of core molecules. The parameters of the distributions are estimated computationally using global optimization algorithm (genetic algorithm) and local optimization algorithm to predict a mixture composition that matches closely with bulk properties of the product.     

A computer-aided molecular design framework for crystallization solvent design

One of the key decisions in designing solution crystallization processes is the selection of solvents. In this paper, we present a computer-aided molecular design (CAMD) framework for the design and selection of solvents and/or anti-solvents for solution crystallization. The CAMD problem is formulated as a mixed integer nonlinear programming (MINLP) model. Although, the model allows any combination of performance objectives and property constraints, in the case studies, potential recovery was considered as the performance objective. The latter, needs to be maximized, while other solvent property requirements such as solubility, crystal morphology, flashpoint, toxicity, viscosity, normal boiling and melting point are posed as constraints. All the properties are estimated using group contribution methods. The MINLP model is then solved using a decomposition approach to obtain optimal solvent molecules. Solvent design and selection for two types of solution crystallization processes namely cooling crystallization and drowning out crystallization are presented. In the first case study, the design of single compound solvent for crystallization of ibuprofen, which is an important pharmaceutical compound, is addressed. One of the important issues namely, the effect of solvent on the shape of ibuprofen crystals is also considered in the MINLP model. The second case study is a mixture design problem where an optimal solvent/anti-solvent mixture is designed for crystallization of ibuprofen by the drowning out technique. For both case studies the performance of the solvents are verified qualitatively through SLE diagrams.     

Efficient ant colony optimization for computer aided molecular design: Case study solvent selection problem

In this paper, we propose a novel computer-aided molecular design (CAMD) methodology for the design of optimal solvents based on an efficient ant colony optimization (EACO) algorithm. The molecular design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a solvent performance measure is maximized (solute distribution coefficient) subject to structural feasibility, property, and process constraints. In developing the EACO algorithm, the better uniformity property of Hammersley sequence sampling (HSS) is exploited. The capabilities of the proposed methodology are illustrated using a real world case study for the design of an optimal solvent for extraction of acetic acid from waste process stream using liquid–liquid extraction. The UNIFAC model based on the infinite dilution activity coefficient is used to estimate the mixture properties. New solvents with better targeted properties are proposed.     

A hybrid optimisation model for the synthesis of sustainable gasification-based integrated biorefinery

Depletion of fossil fuels and increasing public awareness of environmental issues has stimulated the search for alternative energy sources. Biofuels are recognised as one of the most promising alternatives to fossil fuels, as they can be produced from various types of feedstock. The efficiency and sustainability of biomass-based production can be maximised by producing biofuels along with other valuable coproducts in a “biorefinery”. This concept was proposed to make the production of biofuels and biochemicals more economically viable by taking advantage of opportunities for process integration and waste recovery. In this work, a novel hybrid optimisation model that combines superstructure-based optimisation approach and insight-based automated targeting for the synthesis of a sustainable integrated biorefinery is presented. In addition, fuzzy optimisation is also adapted to synthesize such integrated facility with the simultaneous consideration of both economic and environmental performance. Note that the proposed approach is a generic synthesis strategy that can be applied even without detailed modelling of individual processes.