This study developed six machine learning models to predict the biochar properties from the dry torrefaction of lignocellulosic biomass by using biomass characteristics and torrefaction conditions as input variables. After optimization, gradient boosting machines were the optimal model, with the highest coefficient of determination ranging from 0.89 to 0.94. Torrefaction conditions exhibited a higher relative contribution to the yield and higher heating value (HHV) of biochar than biomass characteristics. Temperature was the dominant contributor to the elemental and proximate composition and the yield and HHV of biochar. Feature importance and SHapley Additive exPlanations revealed the effect of each influential factor on the target variables and the interactions between these factors in torrefaction. Software that can accurately predict the element, yield, and HHV of biochar was developed. These findings provide a comprehensive understanding of the key factors and their interactions influencing the torrefaction process and biochar properties.
Remediating inorganic pollutants is an important part of protecting coastal ecosystems, which are especially at risk from the effects of climate change. Different Phragmites karka (Retz) Trin. ex Steud ecotypes were gathered from a variety of environments, and their abilities to remove inorganic contaminants from coastal wetlands were assessed. The goal is to learn how these ecotypes process innovation might help reduce the negative impacts of climate change on coastal environments. The Phragmites karka ecotype E1, found in a coastal environment in Ichkera that was impacted by residential wastewater, has higher biomass production and photosynthetic pigment content than the Phragmites karka ecotypes E2 (Kalsh) and E3 (Gatwala). Osmoprotectant accumulation was similar across ecotypes, suggesting that all were able to successfully adapt to polluted marine environments. The levels of both total soluble sugars and proteins were highest in E2. The amount of glycine betaine (GB) rose across the board, with the highest levels being found in the E3 ecotype. The study also demonstrated that differing coastal habitats significantly influenced the antioxidant activity of all ecotypes, with E1 displaying the lowest superoxide dismutase (SOD) activity, while E2 exhibited the lowest peroxidase (POD) and catalase (CAT) activities. Significant morphological changes were evident in E3, such as an expansion of the phloem, vascular bundle, and metaxylem cell areas. When compared to the E3 ecotype, the E1 and E2 ecotypes showed striking improvements across the board in leaf anatomy. Mechanistic links between architectural and physio-biochemical alterations are crucial to the ecological survival of different ecotypes of Phragmites karka in coastal environments affected by climate change. Their robustness and capacity to reduce pollution can help coastal ecosystems endure in the face of persistent climate change.
Extraction of lignin via green methods is a crucial step in promoting the bioconversion of lignocellulosic biomasses. In the present study, utilisation of natural deep eutectic solvent for the pretreatment of kenaf fibres biomass is performed. Furthermore, extracted lignin from natural deep eutectic solvent pretreated kenaf biomass was carried out and its comparative study with commercial lignin was studied. The extracted lignin was characterized and investigated through Infrared Fourier transform spectroscopy, X-ray Diffraction, thermogravimetric analysis, UV-Vis spectroscopy, and scanning electron microscopy. FTIR Spectra shows that all samples have almost same set of absorption bands with slight difference in frequencies. CHNS analysis of natural deep eutectic solvent pretreated kenaf fibre showed a slight increase in carbon % from 42.36 to 43.17% and an increase in nitrogen % from - 0.0939 to - 0.1377%. Morphological analysis of commercial lignin shows irregular/uneven surfaces whereas natural deep eutectic solvent extracted lignin shows smooth and wavy surface. EDX analysis indicated noticeable peaks for oxygen and carbon elements which are present in lignocellulosic biomass. Thermal properties showed that lignin is constant at higher temperatures due to more branching and production of extremely condensed aromatic structures. In UV-VIS spectroscopy, commercial lignin shows slightly broad peak between 300 and 400 nm due to presence of carbonyl bond whereas, natural deep eutectic solvent extracted lignin does not show up any peak in this range. XRD results showed that the crystallinity index percentage for kenaf and natural deep eutectic solvent treated kenaf was 70.33 and 69.5% respectively. Therefore, these innovative solvents will undoubtedly have significant impact on the development of clean, green, and sustainable products for biocatalysts, extraction, electrochemistry, adsorption applications.
The development of algae is seen as a potential and ecologically sound approach to address the increasing demands in multiple sectors. However, successful implementation of processes is highly dependent on effective growing and harvesting methods. The present study provides a complete examination of contemporary techniques employed in the production and harvesting of algae, with a particular emphasis on their sustainability. The review begins by examining several culture strategies, encompassing open ponds, closed photobioreactors, and raceway ponds. The analysis of each method is conducted in a systematic manner, with a particular focus on highlighting their advantages, limitations, and potential for expansion. This approach ensures that the conversation is in line with the objectives of sustainability. Moreover, this study explores essential elements of algae harvesting, including the processes of cell separation, dewatering, and biomass extraction. Traditional methods such as centrifugation, filtration, and sedimentation are examined in conjunction with novel, environmentally concerned strategies including flocculation, electro-coagulation, and membrane filtration. It evaluates the impacts on the environment that are caused by the cultivation process, including the usage of water and land, the use of energy, the production of carbon dioxide, and the runoff of nutrients. Furthermore, this study presents a thorough examination of the current body of research pertaining to Life Cycle Analysis (LCA) studies, presenting a perspective that emphasizes sustainability in the context of algae harvesting systems. In conclusion, the analysis ends up with an examination ahead at potential areas for future study in the cultivation and harvesting of algae. This review is an essential guide for scientists, policymakers, and industry experts associated with the advancement and implementation of algae-based technologies.
The study explores co-gasification of palm oil decanter cake and alum sludge, investigating the correlation between input variables and syngas production. Operating variables, including temperature (700-900 °C), air flow rate (10-30 mL/min), and particle size (0.25-2 mm), were optimized to maximize syngas production using air as the gasification agent in a fixed bed horizontal tube furnace reactor. Response Surface Methodology with the Box-Behnken design was used employed for optimization. Fourier Transformed Infra-Red (FTIR) and Field Emission Scanning Electron Microscopic (FESEM) analyses were used to analyze the char residue. The results showed that temperature and particle size have positive effects, while air flow rate has a negative effect on the syngas yield. The optimal CO + H2 composition of 39.48 vol% was achieved at 900 °C, 10 mL/min air flow rate, and 2 mm particle size. FTIR analysis confirmed the absence of C─Cl bonds and the emergence of Si─O bonds in the optimized char residue, distinguishing it from the raw sample. FESEM analysis revealed a rich porous structure in the optimized char residue, with the presence of calcium carbonate (CaCO3) and aluminosilicates. These findings provide valuable insights for sustainable energy production from biomass wastes.
Municipal wastewater is ubiquitously laden with myriad pollutants discharged primarily from a combination of domestic and industrial activities. These heterogeneous pollutants are threating the natural environments when the traditional activated sludge system fails sporadically to reduce the pollutants' toxicities. Besides, the activated sludge system is very energy intensive, bringing conundrums for decarbonization. This research endeavoured to employ Chlorella vulgaris sp. In converting pollutants from municipal wastewater into hydrogen via alternate light and dark fermentative process. The microalgae in attached form onto 1 cm3 of polyurethane foam cubes were adopted in optimizing light intensity and photoperiod during the light exposure duration. The highest hydrogen production was recorded at 52 mL amidst the synergistic light intensity and photoperiod of 200 μmolm-2s-1 and 12:12 h (light:dark h), respectively. At this lighting condition, the removals of chemical oxygen demand (COD) and ammoniacal nitrogen were both achieved at about 80%. The sustainability of microalgal fermentative performances was verified in recyclability study using similar immobilization support material. There were negligible diminishments of hydrogen production as well as both COD and ammoniacal nitrogen removals after five cycles, heralding inconsequential microalgal cells' washout from the polyurethane support when replacing the municipal wastewater medium at each cycle. The collected dataset was finally modelled into enhanced Monod equation aided by Python software tool of machine learning. The derived model was capable to predict the performances of microalgae to execute the fermentative process in producing hydrogen while subsisting municipal wastewater at arbitrary photoperiod. The enhanced model had a best fitting of R2 of 0.9857 as validated using an independent dataset. Concisely, the outcomes had contributed towards the advancement of municipal wastewater treatment via microalgal fermentative process in producing green hydrogen as a clean energy source to decarbonize the wastewater treatment facilities.
The study investigates the potential of utilizing banana trunk-derived porous activated biochar enriched with SO3H- as a catalyst for eco-friendly biodiesel production from the microalga Chlorella vulgaris. An extensive analysis, employing advanced techniques such as XRD, FTIR, TGA, XPS, NH3-TPD, BET, SEM-EDX, and TEM, was conducted to elucidate the physicochemical properties of BT-SO3H catalysts. The synthesized catalyst demonstrated its efficiency in converting the total lipids of Chlorella vulgaris into biodiesel, with varying concentrations of 3%, 5%, and 7%. Notably, using a 5% BT-SO3H concentration resulted in remarkably higher biodiesel production about 58.29%. Additionally, the fatty acid profile of C. vulgaris biodiesel indicated that C16:0 was the predominant fatty acid at 24.31%, followed by C18:1 (19.68%), C18:3 (11.45%), and C16:1 (7.56%). Furthermore, the biodiesel produced via 5% BT-SO3H was estimated to have higher levels of saturated fatty acids (SFAs) at 34.28%, monounsaturated fatty acids (MUFAs) at 30.70%, and polyunsaturated fatty acids (PUFAs) at 24.24%. These findings highlight the promising potential of BT-SO3H catalysts for efficient and environmentally friendly biodiesel production from microalgal species.
Employing biomass for environmental conservation is regarded as a successful and environmentally friendly technique since they are cost-effective, renewable, and abundant. Biochar (BC), a thermochemically converted biomass, has a considerably lower production cost than the other conventional activated carbons. This material's distinctive properties, including a high carbon content, good electrical conductivity (EC), high stability, and a large surface area, can be utilized in various research fields. BC is feasible as a renewable source for potential applications that may achieve a comprehensive economic niche. Despite being an inexpensive and environmentally sustainable product, research has indicated that pristine BC possesses restricted properties that prevent it from fulfilling the intended remediation objectives. Consequently, modifications must be made to BC to strengthen its physicochemical properties and, thereby, its efficacy in decontaminating the environment. Modified BC, an enhanced iteration of BC, has garnered considerable interest within academia. Many modification techniques have been suggested to augment BC's functionality, including its adsorption and immobilization reliability. Modified BC is overviewed in its production, functionality, applications, and regeneration. This work provides a holistic review of the recent advances in synthesizing modified BC through physical, chemical, or biological methods to achieve enhanced performance in a specific application, which has generated considerable research interest. Surface chemistry modifications require the initiation of surface functional groups, which can be accomplished through various techniques. Therefore, the fundamental objective of these modification techniques is to improve the efficacy of BC contaminant removal, typically through adjustments in its physical or chemical characteristics, including surface area or functionality. In addition, this article summarized and discussed the applications and related mechanisms of modified BC in environmental decontamination, focusing on applying it as an ideal adsorbent, soil amendment, catalyst, electrochemical device, and anaerobic digestion (AD) promoter. Current research trends, future directions, and academic demands were available in this study.
In contemporary wastewater treatment industry, advanced oxidation techniques, membrane filtration, ion exchange, and reverse osmosis are used to treat chemically loaded wastewater. All these methods required highly toxic oxidizing chemicals, high capital investment in membrane/filter materials, and the installation of sophisticated equipment. Wastewater treatment through an adsorption process using biomass-based adsorbent is economical, user-friendly, and sustainable. Neem tree waste has been explored as an adsorbent for wastewater treatment. The chemical components in the neem biomass include carbohydrates, fat, fiber, cellulose, hemicellulose, and lignin, which support the functionalization of neem biomass. Moreover, adsorbent preparation from renewable resources is not only cost-effective and environmentally friendly but also helps in waste management for sustainable growth. Contemporary researchers explored the pre- and post-surface-modified neem biomass adsorbents in scavenging the pollutants from contaminated water. This review extensively explores the activation process of neem biomass, physical and chemical methods of surface modification mechanism, and the factors affecting surface modification. The pollutant removal through pre and post-surface-modified neem biomass adsorbents was also summarized. Furthermore, it also provides a comprehensive summary of the factors that affect the adsorption performance of the neem biomass-derived adsorbents against dyes, metal ions, and other emerging pollutants. Understanding the surface-modification mechanisms and the adsorption efficiency factor of adsorbents will help in harnessing their potential for more efficiently combatting environmental pollution and making strides toward a greener and more sustainable future.
Duckweed, a floating macrophyte, has attracted interest in various fields such as animal feedstocks and bioenergy productions. Its enriched nutritional content and rapid growth rate make it particularly promising. However, common laboratory cultures of duckweed often experience fronds layering, diminishing the efficiency of sunlight capturing due to limited surface area on conventional cultivation platforms. In this work, we aimed to address the issue of fronds layering by introducing a novel cultivation platform - a superhydrophobic coated acrylic sheet. The sheet was prepared by spray-coating a suspension of beeswax and ethanol, and its effectiveness was evaluated by comparing the growth performance of giant duckweed, Spirodela polyrhiza, on this platform with that on a modified version. The superhydrophobic coated acrylic sheet (SHPA) and its variant with a metal mesh added (SHPAM) were employed as growing platforms, with a glass jar serving as the control. The plantlets were grown for 7 days with similar growth conditions under low light stress (25 μmol/m2/s). SHPAM demonstrated superior growth performance, achieving a mass gain of 102.12 ± 17.18 %, surpassing both SHPA (89.67 ± 14.97 %) and the control (39.26 ± 8.94 %). For biochemical compositions, SHPAM outperformed in chlorophyll content, protein content and lipid content. The values obtained were 1.021 ± 0.076 mg/g FW, 14.59 ± 0.58 % DW and 6.21 ± 0.75 % DW respectively. Therefore, this work proved that incorporation of superhydrophobic coatings on a novel cultivation platform significantly enhanced the biomass production of S. polyrhiza. Simultaneously, the biochemical compositions of the duckweeds were well-maintained, showcasing the potential of this approach for optimized duckweed cultivation.
Durian peel, an abundant waste in Malaysia could be a potential substrate for fermentable sugar recovery for value-added biochemical production. Common pretreatment such as acid or alkaline pretreatment resulted in the need for extensive solid washing which generated wastewater. Herein, this study aims to introduce sonication on top of chemical pretreatment to destruct lignin and reduce the chemical usage during the durian peel pretreatment process. In this study, the morphology and the chemical composition of the pretreated durian peels were studied. The sugar yield produced from the chemical pretreatment and the combined ultrasound and chemical pretreatment were compared. The morphology and chemical structure of durian peels were investigated by Scanning Electron Microscope (SEM), Fourier Transform Infrared (FTIR) analysis and X-ray diffraction (XRD). The SEM images showed that the structural change became more significant when sonication was introduced. Second, XRD profile indicated a relatively higher crystallinity index and FTIR spectra displayed a lower intensity of lignin and hemicellulose for ultrasound plus alkaline (UB) pretreatment as compared to acid, alkaline and ultrasound plus acid (UA) pretreatment. UB and UA pretreatment portrayed higher yield (376.60 ± 12.14 and 237.38 ± 3.96 mg reducing sugar/g dry biomass, respectively) than their controls without the application of ultrasound. Therefore, it could be concluded that ultrasound was able to intensify the fermentable sugar recovery from durian peel by inducing physical and chemical effect of cavitation to alter the morphology of durian peel. Fermentation of UB treated durian peel resulted in 2.68 mol hydrogen/mol consumed sugar and 131.56 mL/Lmedium/h of hydrogen productivity. This study is important because it will shed light on a way to handle durian waste disposal problems and generate fermentable sugars for the production of high value-added products.
This study investigated an innovative strategy of incorporating surfactants into alkaline-catalyzed glycerol pretreatment and enzymatic hydrolysis to improve lignocellulosic biomass (LCB) conversion efficiency. Results revealed that adding 40 mg/g PEG 4000 to the pretreatment at 195 °C obtained the highest glucose yield (84.6%). This yield was comparable to that achieved without surfactants at a higher temperature (240 °C), indicating a reduction of 18.8% in the required heat input. Subsequently, Triton X-100 addition during enzymatic hydrolysis of PEG 4000-assisted pretreated substrate increased glucose yields to 92.1% at 6 FPU/g enzyme loading. High-solid fed-batch semi-simultaneous saccharification and co-fermentation using this dual surfactant strategy gave 56.4 g/L ethanol and a positive net energy gain of 1.4 MJ/kg. Significantly, dual assistance with surfactants rendered 56.3% enzyme cost savings compared to controls without surfactants. Therefore, the proposed surfactant dual-assisted promising approach opens the gateway to economically viable enzyme-mediated LCB biorefinery.
This research explicitly investigates the utilization of Chlorella Vulgaris sp. microalgae as a renewable source for lipid production, focusing on its application in bioplastic manufacturing. This study employed the supercritical fluid extraction technique employing supercritical CO2 (sCO2) as a green technology to selectively extract and produce PHA's precursor utilizing CO2 solvent as a cleaner solvent compared to conventional extraction method. The study assessed the effects of three extraction parameters, namely temperature (40-60 °C), pressure (15-35 MPa), and solvent flow rate (4-8 ml/min). The pressure, flowrate, and temperature were found to be the most significant parameters affecting the sCO2 extraction. Through Taguchi optimization, the optimal parameters were determined as 60 °C, 35 MPa, and 4 ml/min with the highest lipid yield of 46.74 wt%; above-average findings were reported. Furthermore, the pretreatment process involved significant effects such as crumpled and exhaustive structure, facilitating the efficient extraction of total lipids from the microalgae matrix. This study investigated the microstructure of microalgae biomatrix before and after extraction using scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). Fourier-transform infrared spectroscopy (FTIR) was utilized to assess the potential of the extracted material as a precursor for biodegradable plastic production, with a focus on reduced heavy metal content through inductively coupled plasma-optical emission spectrometry (ICP-OES) analysis. The lipid extracted from Chlorella Vulgaris sp. microalgae was analysed using gas chromatography-mass spectrometry (GC-MS), identifying key constituents, including oleic acid (C18H34O2), n-Hexadecanoic acid (C16H32O2), and octadecanoic acid (C18H36O2), essential for polyhydroxyalkanoate (PHA) formation.
A facile and cost-effective hydrothermal followed by precipitation method is employed to synthesize visible light-driven ZnS-Ag ternary composites supported on carbon aerogel (CA). Extensive studies were conducted on the structural, morphological, and optical properties, confirming the successful formation of ternary nanocomposites. The obtained results evidently demonstrate the successful loading of ZnS and Ag onto the surface of the CA. High-resolution transmission electron microscopy analysis revealed that ZnS and Ag nanoparticles (AgNPs) were uniformly distributed on the surface of the CA with an average diameter of 18 nm. The biomass-derived CA, containing a hierarchical porous nano-architecture and an abundant number of -NH2 functional groups on the surface, can greatly prevent the agglomeration, stability and reduce particle size. Brunauer-Emmett-Teller analysis results indicated specific surface areas of 4.62 m2 g-1 for the CA, 48.50 m2 g-1 for the CA/ZnS composite, and 62.62 m2 g-1 for the CA/ZnS-Ag composite. These values demonstrate an increase in surface area upon the incorporation of ZnS and Ag into the CA matrix. Under visible light irradiation, the synthesized CA/ZnS-Ag composites displayed remarkably improved photodegradation efficiency of methylene blue (MB). Among the tested samples, the CA/ZnS-Ag composites exhibited the highest percentage of photodegradation efficiency, surpassing ZnS, CA, and CA/ZnS. The obtained percentages of degradation efficiency for CA, ZnS, CA/ZnS, and CA/ZnS-Ag composites were determined as 26.60%, 52.12%, 68.39%, and 98.64%, respectively. These results highlight the superior photocatalytic performance of the CA/ZnS-Ag composites in the degradation of MB under visible light conditions. The superior efficiency of the CA/ZnS-Ag composite can be attributed to multiple factors, including its elevated specific surface area, inhibition of electron-hole pair recombination, and enhanced photon absorption within the visible light spectrum. The CA/ZnS-Ag composites displayed consistent efficiency over multiple cycles, confirming their stable performance, reusability, and enduring durability, thereby showcasing the robust nature of this composite material.
Cultivation of microalgae in wastewater stream has been extensively reported, especially for simultaneous production of biolipid and wastewater treatment process. This study aimed to derive the research trend and focus on biolipid production from microalgae cultivated in wastewater by using bibliometric approach. The search strategy used in Scopus database resulted in 1339 research articles from 1990 to November 2023. Majority of publications (46%) were affiliated to China and India, showing their predominance in this field. Keywords related to the center of attention included biodiesel, biofuel, biomass and nutrient removal. Meanwhile, keyword with recent publication year, indicating the emerging research trends, revolved around the cultivation techniques and application of the system. Co-culture involving more than one microalgae species, bacteria and yeast showed promising results, while addition of nanoparticles was also found to be beneficial. Increasing exploration on the application of microalgae for treatment of saline wastewater was also reported and the carbon fixation mechanism by microalgae has been widely investigated to promote less environmental impact. Future research on these topics were suggested based on the findings of the bibliometric analyses.
The pursuit of carbon neutrality confronts the twofold challenge of meeting energy demands and reducing pollution. This review article examines the potential of gasifying plastic waste and biomass as innovative, sustainable sources for hydrogen production, a critical element in achieving environmental reform. Addressing the problem of greenhouse gas emissions, the work highlights how the co-gasification of these feedstocks could contribute to environmental preservation by reducing waste and generating clean energy. Through an analysis of current technologies, the potential for machine learning to refine gasification for optimal hydrogen production is revealed. Additionally, hydrogen storage solutions are evaluated for their importance in creating a viable, sustainable energy infrastructure. The economic viability of these production methods is critically assessed, providing insights into both their cost-effectiveness and ecological benefits. Findings indicate that machine learning can significantly improve process efficiencies, thereby influencing the economic and environmental aspects of hydrogen production. Furthermore, the study presents the advancements in these technologies and their role in promoting a transition to a green economy and circular energy practices. Ultimately, the review delineates how integrating hydrogen production from unconventional feedstocks, bolstered by machine learning and advanced storage, can contribute to a sustainable and pollution-free future.
Microalgal lipids are promising and sustainable sources for the production of third-generation biofuels, foods, and medicines. A high lipid yield during the extraction process in microalgae could be influenced by the suitable pretreatment and lipid extraction methods. The extraction method itself could be attributed to the economic and environmental impacts on the industry. This review summarizes the pretreatment methods including mechanical and non-mechanical techniques for cell lysis strategy before lipid extraction in microalgae biomass. The multiple strategies to achieve high lipid yields via cell disruption techniques are discussed. These strategies include mechanical (shear forces, pulse electric forces, waves, and temperature shock) and non-mechanical (chemicals, osmotic pressure, and biological) methods. At present, two techniques of the pretreatment method can be combined to increase lipid extraction from microalgae. Therefore, the extraction strategy for a large-scale application could be further strengthened to optimize lipid recovery by microalgae.
The practice of aquaculture is associated with the generation of a substantial quantity of effluent. Microalgae must effectively assimilate nitrogen and phosphorus from their surrounding environment for growth. This study modeled the algal biomass film, NO3-N concentration, and pH in the membrane bioreactor using the response surface methodology (RSM) and an artificial neural network (ANN). Furthermore, it was suggested that the optimal condition for each parameter be determined. The results of ANN modeling showed that ANN with a structure of 5-3 and employing the transfer functions tansig-logsig demonstrated the highest level of accuracy. This was evidenced by the obtained values of coefficient (R2) = 0.998, R = 0.999, mean squared error (MAE) = 0.0856, and mean square error (MSE) = 0.143. The ANN model, characterized by a 5-5 structure and employing the tansig-logsig transfer function, demonstrates superior accuracy when predicting the concentration of NO3-N and pH. This is evidenced by the high values of R2 (0.996), R (0.998), MAE (0.00162), and MSE (0.0262). The RSM was afterward employed to maximize the performance of algal film biomass, pH levels, and NO3-N concentrations. The optimal conditions for the algal biomass film were a concentration of 2.884 mg/L and a duration of 6.589 days. Similarly, the most favorable conditions for the NO3-N concentration and pH were 2.984 mg/L and 6.787 days, respectively. Therefore, this research uses non-dominated sorting genetic algorithm II (NSGA II) to find the optimal NO3-N concentration, algal biomass film, and pH for product or process quality. The region has the greatest alkaline pH and lowest NO3-N content.
Microalgae's exceptional photosynthetic prowess, CO2 adaptation, and high-value bioproduct accumulation make them prime candidates for microorganism-based biorefineries. However, most microalgae research emphasizes downstream processes and applications rather than fundamental biomass and biochemical balances and kinetic under the influence of greenhouse gases such as CO2. Therefore, three distinctly different microalgae species were cultivated under 0% to 20% CO2 treatments to examine their biochemical responses, biomass production and metabolite accumulations. Using a machine learning approach, it was found that Chlorella sorokiniana showed a positive relationship between biomass and chl a, chl b, carotenoids, and carbohydrates under increasing CO2 treatments, while Chlamydomonas angulosa too displayed positive relationships between biomass and all studied biochemical contents, with minimal trade-offs. Meanwhile, Nostoc sp. exhibited a negative correlation between biomass and lipid contents under increasing CO2 treatment. The study showed the potential of Chlorella, Chlamydomonas and Nostoc for commercialization in biorefineries and carbon capture systems where their trade-offs were identified for different CO2 treatments and could be prioritized based on commercial objectives. This study highlighted the importance of understanding trade-offs between biomass production and biochemical yields for informed decision-making in microalgae cultivation, in the direction of mass carbon capture for climate change mitigation.
Microalgae is a sustainable alternative source to traditional proteins. Existing pretreatment methods for protein extraction from microalgae still lack scalability, are uneconomical and inefficient. Herein, high shear mixing (HSM) was applied to disrupt the rigid cell walls and was found to assist in protein release from microalgae. This study integrates HSM in liquid biphasic system with seven parameters being investigated on extraction efficiency (EE) and protein yield (Y). The highest EE and Y obtained are 96.83 ± 0.47 % and 40.98 ± 1.27 %, respectively, using 30% w/v K3PO4 salt, 60 % v/v alcohol, volume ratio of 1:1 and 0.5 % w/v biomass loading under shearing rate of 16,000 rpm for 1 min.