Bio-based Processes Research Articles

Ozone delivery on food materials incorporating some bio-based processes: A succinct synopsis

This paper reviews succinctly ozone delivery on food materials incorporating some bio-based processes. Particularly, ozone treatment is among existent bio-based process technologies applicable to wide range of food materials. Since declared 'Generally Recognized As Safe (GRAS)’, the global technological progress of ozone has had its discharge settings to-date range between laboratory/domestic and industrial scales. Based on medium properties and probably owed to its unstable nature, whilst the chemistry and physics of ozone substantiates not only its efficacy, but also the delivery processes, incorporating both direct/indirect oxidation and ozonolysis contributes to its diversity. Ozone is widely under investigation as sanitizing agent for the food industry. So when it is applied to food materials, key variables of interest can include amount/quantity of concentration and exposure time/periods. Now and on-going into the future, it remains imperative that makers of ozone equipment continually search for 'best' safe applications that would cater for both consumer and industrial needs. Copyright © 2017 VBRI Press.

Digitizing sustainable process development: From ex-post to ex-ante LCA using machine-learning to evaluate bio-based process technologies ahead of detailed design

Life Cycle Assessment is a data-intensive process holding great promise to benefit from advanced analytics and machine learning technologies. The present research aims at the development of a data-science based framework with capabilities to estimate LCA metrics of bio-based and biorefinery processes in early design phases. Life cycle inventories may combine experimental (pilot and lab scale) data, property and thermodynamic databases, and model-derived data from simulations and design studies. The framework applies advanced analytics such as classification trees and artificial neural networks (ANN) with a scope to produce input–output relationships through predictor variables that refer to the molecular structure of bio-chemical or bio-fuel products of interest, the feedstocks used, and the process technologies characteristics. The combined use of ANNs and trees demonstrates a coordinated level of complementarity between the approaches, while it improves robustness and streamlines LCA estimations in the early-stage design.

Bacterial Nanocellulose Derived from Banana Leaf Extract: Yield and Variation Factors

Bananas are one of the most important crops worldwide. However, a large amount of residual lignocellulosic biomass is generated during its production and is currently undervalued. These residues have the potential to be used as feedstock in bio-based processes with a biorefinery approach. This work is based on the valorization of banana leaf and has the following objectives (i) to determine the effect of certain physical and environmental factors on the concentration of glucose present in banana leaf extract (BLE), using a statistical regression model; (ii) to obtain Bacterial Nanocellulose (BNC), using BLE (70% v/v) and kombucha tea as fermentation medium. In addition, the physicochemical properties of BNC were evaluated by X-ray diffraction (XRD), Fourier transform infrared (FTIR), and thermogravimetric analysis (TGA). The results indicate that storage time, location, leaf color, and petiole type are factors related to BLE concentration, which is reduced by approximately 28.82% and 64.32% during storage times of five days. Regarding BNC biosynthesis, the results indicate that the highest yield, 0.031 g/g, was obtained at 21 days. Furthermore, it was determined that the highest production rate was 0.11 gL−1h−1 at 11 days of fermentation. By FTIR, it was determined that the purification step with NaOH (3M) should be carried out for approximately two hours. This research supports the development of a circular bioeconomy around the banana value chain, as it presents a way of bioprocessing residual biomass that can be used to produce bioproducts.

Multipurpose Processing Additives for Silica/Rubber Composites: Synthesis, Characterization, and Application.

Processing additives are a special group of chemicals included in rubber formulations to facilitate the flowability of the resultant compounds. Their addition generally affects the cured properties of the subsequent rubber composites, and fine-tuning of the compound formulation is therefore required. In this work, an attempt has been made to address this issue through the preparation of new bio-based processing additives capable of promoting the mixing of the rubber compound while at the same time enhancing mechanical properties following curing. A significant decrease in the mixing energy at the first stage of mixing (~10%) has been observed by substituting only a small percentage of the conventional petroleum-derived process oil with aminated epoxidized soybean oil. Concomitantly, it is found that this aminated epoxidized soybean oil promotes rubber curing and increases the tensile strength of the final composite by ~20% compared to the control.

Challenges in Optimization and Control of Biobased Process Systems: An Industrial-Academic Perspective

Biobased slurry processes and large-scale continuous chemical production share many similarities. These concern not only process technologies and equipment but also staffing (positions/educations) and plant operations, including methods and technologies for planning, scheduling, and control. Process Systems Engineering (PSE) approaches have been applied successfully in large-scale chemical production to optimize processes of high complexity. By replacing rules-of-thumb and oversimplified calculations with rigorous quantification and automation, PSE increases the profitability of a wide range of processes. Such improvement potential also exists in the bioindustry, which traditionally comprises many small-scale and batch plants deployed in food or pharmaceutical production. The article elucidates the most important operational challenges of such processes. It brings together academic research and industrial perspectives by contrasting a careful revision of literature with a survey of personnel working in industrial biobased production settings in Denmark. This analysis allows showing the existence of a gap between academic research focus and industrial need, for instance, concerning production processes with humans-in-the-loop. Furthermore, differences between chemical and biobased processes are pointed out, highlighting some limitations of applying PSE to biobased processes. A deeper understanding of these limitations is fundamental to assessing risks when identifying process improvement potential. Finally, the article suggests a possible roadmap for the development of frameworks for the optimization of industrial biobased processes based on existing works in chemical processing.

The potential use of Chlamydomonas reinhardtii and Chlorella sorokiniana as biostimulants on maize plants

Nitrogen deficiency and drought stress are among the major stresses faced by plants with negative consequence on crop production. The use of plant biostimulants is a very promising application in agriculture to improve crop yield, but especially to prevent the effect of abiotic stresses. Algae-derived biostimulants represent an efficient tool to stimulate the root development: while macroalgae have already been widely adopted as a source of biostimulants to improve plants growth and resilience, far less information is available for microalgae. The objective of this work is to investigate the stimulant ability on maize roots of two green algae species, Chlamydomonas reinhardtii and Chlorella sorokiniana, being respectively the model organism for Chlorophyta and one of the most promising species for microalgae cultivation at industrial scale. The results obtained demonstrate that both C. reinhardtii and C. sorokiniana cells promoted the development of maize root system compared to the untreated negative control. C. sorokiniana specifically increased the number of secondary roots, while improved micro-nutrients accumulation on roots and shoots was measured in the case of C. reinhardtii treated plants. When these microalgae-derived biostimulants were applied on plants grown in stress conditions as nitrogen deficiency, improved development of the root system was measured in the case of plants treated with C. sorokiniana biomass. Microalgae cultivation for biostimulant production can thus be considered as a bio-based process providing solutions for improving plant resilience toward stress conditions.

Mechanical, chemical, biological: Moving towards closed-loop bio-based recycling in a circular economy of sustainable textiles

The textile industry is facing increasing criticism because of its intensive use of resources –both natural and fossil derived– and the negative environmental and societal impacts associated with the manufacturing, use and disposal of clothes. This has led to a desire to move towards a circular economy for textiles that will implement recycling concepts and technologies to protect resources, the environment and people. So far, recycling processes have been focused on the chemical and mechanical reuse of textile fibres. In contrast, bio-based processes for textile production and recycling have received little attention, beyond end-of-life composting. However, the selectivity and benign processing conditions associated with bio-based technologies hold great promise for circularising the textile life cycle and reducing the environmental impacts of textile production and processing. Developing circular and sustainable systems for textile production requires a revolutionary system approach that encompasses the choice of material and finishes being designed for recycling at the end of life, and in this context bio-based processes can help provide the means to maintain materials in a closed loop. This paper reviews established methods in mechanical and chemical recycling processes in closed-loop textile recycling of all fibre types, as well as bio-based processes that demonstrate open-loop textile recycling. Fermentation and enzymatic processes have been demonstrated for the production of all types of textiles, which in combination with enzymatic deconstruction of end of life cellulosic textiles could allow them to be recycled indefinitely. Within the context of the circular economy, bio-based processes could extend mechanical and chemical textile recycling mechanisms in the technical cycle, enabling greater circularity of textiles in the biological cycle before composting takes place.

Bio-based process for the catalytic production of ethyl levulinate from cellulose

This paper presents a bio-based process for the catalytic conversion of cellulose to ethyl levulinate and an analysis of its techno-economic feasibility. The said bio-based process relies as major feedstock on cellulose, which can be derived from lignocellulosic biomass. cellulose is converted to ethyl levulinate via a homogeneous catalytic reaction whereby dilute sulfuric acid in combination with Al salts is the catalyst and ethanol is the solvent and reactant. This approach affords high ethyl levulinate yields but requires complex procedures for used catalyst and solvent recycling. Based on experimental results on the homogeneous catalytic reaction and vapor–liquid equilibrium separation in the previous studies, a simulation was conducted that included process design, energy integration, and economic analysis. Results from this simulation indicated the proposed bio-based process to afford a minimum selling price of US$ 2,830 per ton of ethyl levulinate, which was highly dependent on an off-site supply of heating energy required for ethanol purification.11The short version of the paper was presented at ICAE2020, Dec 1–10, 2020. This paper is a substantial extension of the short version of the conference paper.

Enzymes, In Vivo Biocatalysis, and Metabolic Engineering for Enabling a Circular Economy and Sustainability.

Since the industrial revolution, the rapid growth and development of global industries have depended largely upon the utilization of coal-derived chemicals, and more recently, the utilization of petroleum-based chemicals. These developments have followed a linear economy model (produce, consume, and dispose). As the world is facing a serious threat from the climate change crisis, a more sustainable solution for manufacturing, i.e., circular economy in which waste from the same or different industries can be used as feedstocks or resources for production offers an attractive industrial/business model. In nature, biological systems, i.e., microorganisms routinely use their enzymes and metabolic pathways to convert organic and inorganic wastes to synthesize biochemicals and energy required for their growth. Therefore, an understanding of how selected enzymes convert biobased feedstocks into special (bio)chemicals serves as an important basis from which to build on for applications in biocatalysis, metabolic engineering, and synthetic biology to enable biobased processes that are greener and cleaner for the environment. This review article highlights the current state of knowledge regarding the enzymatic reactions used in converting biobased wastes (lignocellulosic biomass, sugar, phenolic acid, triglyceride, fatty acid, and glycerol) and greenhouse gases (CO2 and CH4) into value-added products and discusses the current progress made in their metabolic engineering. The commercial aspects and life cycle assessment of products from enzymatic and metabolic engineering are also discussed. Continued development in the field of metabolic engineering would offer diversified solutions which are sustainable and renewable for manufacturing valuable chemicals.

Engineering of Yarrowia lipolytica transporters for high-efficient production of biobased succinic acid from glucose

BackgroundSuccinic acid (SA) is a crucial metabolic intermediate and platform chemical. Development of biobased processes to achieve sustainable SA production has attracted more and more attention in biotechnology industry. Yarrowia lipolytica has a strong tricarboxylic acid cycle and tolerates low pH conditions, thus making it a potential platform for SA production. However, its SA titers in glucose media remain low.ResultsIn this study, we screened mitochondrial carriers and C4-dicarboxylic acid transporters to enhance SA secretion in Y. lipolytica. PGC62-SYF-Mae strain with efficient growth and SA production was constructed by optimizing SA biosynthetic pathways and expressing the transporter SpMae1. In fed-batch fermentation, this strain produced 101.4 g/L SA with a productivity of 0.70 g/L/h and a yield of 0.37 g/g glucose, which is the highest SA titer achieved using yeast, with glucose as the sole carbon resource.ConclusionOur results indicated that transporter engineering is a powerful strategy to achieve the efficient secretion of SA in Y. lipolytica, which will promote the industrial production of bio-based SA.

OSiD: opening the conceptual design of biobased processes to a context‐sensitive sustainability analysis

AbstractBiobased production has been promoted as an alternative to fossil‐based production to mitigate climate change. However, emerging concerns over the sustainability of biobased products have shown that tensions can emerge between different objectives and concerns, like emission reduction targets and food security, and that these are dependent on local contexts. Here we present the Open Sustainability‐in‐Design (OSiD) framework, the aim of which is to integrate a context‐sensitive sustainability analysis in the conceptual design of biobased processes. The framework is illustrated, taking as an example the production of sustainable aviation fuel in southeast Brazil. The OSiD framework is a novel concept that brings the perspectives of stakeholders and considerations of the regional context to an ex ante sustainability analysis of biobased production. This work also illustrates a way to integrate methods from different scientific disciplines supporting the analysis of sustainability and the identification of tensions between different sustainability aspects. Making these tensions explicit early in the development of biobased production can make them more responsive to emerging sustainability concerns. Considering the global pressure to reduce carbon emissions, situating sustainability analyses in their socio‐technical contexts as presented here can help to explain and improve the impacts of biobased production in the transition away from fossil resources. © 2021 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

Machine learning applied for metabolic flux-based control of micro-aerated fermentations in bioreactors.

Various bio-based processes depend on controlled micro-aerobic conditions to achieve a satisfactory product yield. However, the limiting oxygen concentration varies according to the micro-organism employed, while for industrial applications, there is no cost-effective way of measuring it at low levels. This study proposes a machine learning procedure within a metabolic flux-based control strategy (SUPERSYS_MCU) to address this issue. The control strategy used simulations of a genome-scale metabolic model to generate a surrogate model in the form of an artificial neural network, to be used in a micro-aerobic fermentation strategy (MF-ANN). The meta-model provided setpoints to the controller, allowing adjustment of the inlet air flow to control the oxygen uptake rate. The strategy was evaluated in micro-aerobic batch cultures employing industrial Saccharomyces cerevisiae yeast, with defined medium and glucose as the carbon source, as a case study. The performance of the proposed control scheme was compared with a conventional fermentation and with three previously reported micro-aeration strategies, including respiratory quotient-based control and constant air flow rate. Due to maintenance of the oxidative balance at the anaerobiosis threshold, the MF-ANN provided volumetric ethanol productivity of 4.16 g·L-1 ·h-1 and a yield of 0.48 gethanol .gsubstrate-1 , which were higher than the values achieved for the other conditions studied (maximum of 3.4 g·L-1 ·h-1 and 0.35-0.40 gethanol ·gsubstrate-1 , respectively). Due to its modular character, the MF-ANN strategy could be adapted to other micro-aerated bioprocesses.

Modelling of ozone multiphase flow behaviour in an ozonolysis pretreatment reactor

Ozonolysis pretreatment of lignocellulosic biomass (LB) is envisaged as a green and effective method to selectively remove lignin for subsequent bio-based processing. Herein, this study investigates the ozone multiphase flow behaviour of an ozonolysis pretreatment reactor for lignin degradation of oil palm empty fruit bunch (EFB). A coupled transport-reaction model is simulated using Computational Fluid Dynamic (CFD) via COMSOL Multiphysics® software to visualize the ozone multiphase flow behaviour in non-porous and porous bed regions. Numerical findings indicate the pressure drop across porous bed linearly increases with superficial ozone velocity. Simulation results also reveal that the relative pressure across the biomass bed reduces by reducing the biomass bed length. The present work provides preliminary insights for ozonolysis reactor design and optimum operations of biomass pretreatment for up-scaling and commercialization purposes.

Evaluating the efficacy of a newly developed palm-based process aid on nitrile rubber composites

The exploration of bio-based process aid is still ongoing in the effort to replace petroleum-based process oil. In this study, the efficacy of a newly developed palm-based process aid (Bio) on nitrile rubber (NBR) composites was investigated by varying its concentration from 0.0 to 10.0 phr. A comparison was made against a commercial oil (CO), i.e. naphthenic oil in terms of Mooney viscosity, cure characteristics, morphology, physical, and chemical properties. Results revealed that the use of Bio as process aid improves the processability of rubber by lowering the Mooney viscosity, enhancing filler dispersion, and lowering loss tangent values. Tensile properties and compression sets of CO-NBR composites were slightly better compared to Bio-NBR composites. Interestingly, Bio-NBR composites showed better ageing properties, especially at higher process aid content. Higher retentions of tensile strength and elongation at break and lower compression sets of aged Bio-NBR compared to CO-NBR composites were observed, which are possibly contributed by the good compatibility of Bio with aged rubber. Thermogravimetric analysis showed that the thermal stability of Bio-NBR composites were slightly better than CO-NBR composites. Based on these findings, the use of Bio (≥ 7.5 phr) as process aid significantly improved the processability of rubber with some enhancement in ageing properties of composites that is desirable and ideal for various applications such as for the production of automotive components.

How does business model redesign foster resilience in emerging circular value chains?

This paper aims to elucidate how companies can innovate their business model to strengthen their resilience and timely respond to current ecosystem challenges, like the emergence of new cross-industry value chains in the circular economy. The adoption of new sustainable technologies leads to the disruption of current linear settings and to the need of business model innovation. This study draws upon a case study from the circular economy rooted in by-product valorisation and presents an innovative bio-based process enabling phosphate recovery from rapeseed oil press-cakes. Incumbent actors of established (linear) value chains have been interviewed to highlight potential business model innovation. To this end, an inductive theory-building case study approach has been applied. Results reveal that a business model redesign is needed in order to build novel circular value chains, but it depends on chain actors’ capacity to adapt to change, namely to be resilient. The new value proposition needs to reach new customer targets more sensitive to sustainability issues and/or to enhance the awareness towards bio-based technological solutions into extant customers. Value creation and capture highly depend on the coordinating role of the chain actor willing to invest in the new bio-based technology, which becomes the focal company within the emergent value chain. Two scenarios are open, according to who is playing this role: if the new recovery and release process is carried out by an incumbent, the new process requires exploratory, transformative and exploitative learning together with extra investments in highly specific assets and the establishment of new cross-industry relationships to complement missing assets and knowledge about such technological breakthroughs available on the market. If a new actor enters the emerging value chain, business model innovation is mediated and moderated by a company owning both tangible and intangible resources, thus catalysing technology implementation. • Business model innovation is evaluated in its interplay with emerging value chains. • The valorisation of agri-food by-products to recover scarce resources has been used as a case study. • Four types of potential new value chains are identified as emerging from cascading usage of agri-food by-products. • Elements which companies need to change in their current business model to implement sustainable innovations are outlined. • Cross-industry relationships are fundamental to redesign business models for a successful sustainable transition.

Towards aromatics from biomass: Prospective Life Cycle Assessment of bio-based aniline

Bio-based chemicals are seen as a potential stepping-stone towards a more sustainable chemical industry. However, while bio-based routes are already available for various organic alcohols and acids, the direct bio-based production of aromatic compounds has been difficult so far. Recently, the first bio-based process for the production of the important aromatic aniline has been realized. The process produces bio-based aniline via two-stages: first, sugar is fermented by Corynebacterium Glutamicum to aminobenzoic acid, which is then catalytically decarboxylated to aniline. In this study, we present a prospective Life Cycle Assessment for bio-based aniline production to evaluate the environmental potential compared to fossil-based aniline production. Our results suggest that the bio-based production could reduce the global warming impacts of aniline from cradle-to-grave by 35–69% relative to fossil-based production, depending on the type of biomass feedstock. However, bio-based aniline could also substantially increase eutrophication and acidification, a trade-off commonly observed for bio-based processes. Thus, the novel production route is promising and expands the scope of bio-based chemicals towards aromatics. • First Life Cycle Assessment of bio-based aniline production. • Bio-based production chain in three world regions considering four feedstocks. • Significantly lower global warming impacts possible by bio-based aniline. • Reduced global warming impacts robust regarding indirect land-use change. • Feedstock demand for global aniline demand could be satisfied.

DERIVATIZATION OF SOYBEAN OIL TO ENHANCE PERFORMANCE AS A PROCESSING OIL IN SBR-BASED RUBBER COMPOUNDS

ABSTRACTAlthough soybean oil (SBO) has been used as a bio-based processing oil (PO) for rubber compounds, direct replacement of a conventional petroleum-based PO with SBO often results in a reduction of some important properties. As a result, it was of interest to investigate two higher molecular weight SBO-derived materials as POs, namely, sucrose octasoyate (SS) and poly(2-vinyloxyethyl)soyate (P2VOES). When these compounds were used in carbon black (CB)-filled SBR, mechanical properties were significantly improved. This result was mainly attributed to higher crosslink densities resulting from their higher degree of unsaturation per molecule as compared with SBO. Higher unsaturation per molecule increases the probability that the PO will be incorporated into the crosslinked network as elastically effective crosslinks as opposed to dangling chain ends. With regard to tire tread performance, both SS and P2VOES-based vulcanizates showed a lower predicted rolling resistance than the SBO-based control, and the P2VOES vulcanizate showed a better balance between rolling resistance and wet traction. Vulcanizates derived from SS and P2VOES showed a small tangent delta peak between −13 and 35 °C that might be associated with relatively highly crosslinked domains rich in SS or P2VOES.

Closing the loop: the power of microbial biotransformations from traditional bioprocesses to biorefineries, and beyond.

The power of microorganisms in manipulating diverse matrices and in favouring the flux of elements and molecules through biogeochemical cycles developed in the natural environment, but they also managed to take advantage of some niches created by humans. Therefore, inspired by learning these lessons from nature, we can implement biobased processes at industrial level, for diminishing our dependency on fossil resources and to return molecules to their turnover in a compatible timeframe and with reduced environmental impact.

Bioprocess intensification: Cases that (don’t) work

Development of affordable and low carbon biobased manufacturing depends critically on strategies that reduce cost and emission profiles. This paper indicates that efforts around the reduction of capital costs by intensification of process equipment need to be carefully weighed against the inherently fast increasing financial and climate costs of driving forces used for the intensification. The fundamental relation between capital expenditures (CAPEX) and operational expenditures (OPEX) of intensified and non-intensified biobased processes and their financial and climatic impacts are emphasized and provisionally explored for a few industrial processes. General learnings flag the importance in particular of OPEX minimisation for sustainable bio-economic development.

Enhancing mechanistic models with neural differential equations to predict electrodialysis fouling

Fouling of the ion-exchange membranes by colloidal substances present in bio-based process streams is an important hurdle for electrodialysis. The development of a model is challenged by the limited availability of experimental data and the complexity of the underlying physics. This research addresses this challenge by combining a mechanistic description of the transport processes with a machine learning model to describe the complex phenomena of colloidal aggregation and attachment to the surface of ion-exchange membranes. After validation with fouling experiments using acrylamide as colloidal foulant, it was found that this hybrid model improves the predictive power of the model while reducing the need for experimental data. An analysis of both mechanistic and machine learning models showed that the attachment probability of anion polyacrylamide (APAM) is influenced by the current density and the size of the fouling layer in a non-linear manner. An increase in current density leads to an increase in the attachment probability while the opposite holds for the size of the fouling layer. This research shows that machine learning can complement mechanistic models where fundamental knowledge is lacking or computational resources are limiting. The combination maintains the interpretability and generalisability of mechanistic models while harnessing the accuracy of machine learning.