Halide-free catalytic carbon dioxide fixation of epoxides to cyclic carbonates under atmospheric pressure

Epoxides to cyclic carbonates conversion utilizing CO2 is one of the efficient approaches for CO2 fixation. Atmospheric fixation of CO2 generally required the use of halogen containing catalysts or additionally...

para-Aminobenzoic acid-capped Hematite as an Efficient Nanocatalyst for Solvent-free CO2 Fixation under Atmospheric Pressure

Utilization of carbon dioxide by converting it into value-added chemicals is a sustainable remedy approach which stipulates abundant, cheap, non-toxic and efficient catalytic materials. In this study, we have demonstrated...

A versatile active learning workflow for optimization of genetic and metabolic networks

The study, engineering and application of biological networks require practical and efficient approaches. Current optimization efforts of these systems are often limited by wet lab labor and cost, as well as the lack of convenient, easily adoptable computational tools. Aimed at democratization and standardization, we describe METIS, a modular and versatile active machine learning workflow with a simple online interface for the optimization of biological target functions with minimal experimental datasets. We demonstrate our workflow for various applications, from simple to complex gene circuits and metabolic networks, including several cell-free transcription and translation systems, a LacI-based multi-level controller and a 27-variable synthetic CO2-fixation cycle (CETCH cycle). Using METIS, we could improve above systems between one and two orders of magnitude compared to their original setup with minimal experimental efforts. For the CETCH cycle, we explored the combinatorial space of ~1025 conditions with only 1,000 experiments to yield the most efficient CO2-fixation cascade described to date. Beyond optimization, our workflow also quantifies the relative importance of individual factors to the performance of a system. This allows to identify so far unknown interactions and bottlenecks in complex systems, which paves the way for their hypothesis-driven improvement, which we demonstrate for the LacI multi-level controller that we were able to improve by 100-fold after having identified resource competition as limiting factor. Overall, our workflow opens the way for convenient optimization and prototyping of genetic and metabolic networks with customizable adjustments according to user experience, experimental setup, and laboratory facilities.

Effect of TiO2 Nanoparticles on the Yield and Photophysiological Responses of Cherry Tomatoes during the Rainy Season

The rainy season occurs mainly from June to July in Korea, and this season causes insufficient ambient light intensity for the growth of cherry tomato in a greenhouse. Titanium dioxide (TiO2), as a photocatalyst, is known to affect photosynthesis in plants. This study was carried out to investigate the influence of TiO2 foliar spray application on the yield and photophysiological responses of cherry tomato under low ambient light intensity during the rainy season in a greenhouse. Cherry tomato plants were treated with 100 mg·L−1 TiO2 (T1) or 200 mg·L−1 TiO2 (T2) nanoparticle suspension on 26 June. The control group was not treated with TiO2. In the O–J phase of the OJIP transient under a cloudy day (2 July), the slope in the control and T1 groups rose more sharply than that in the T2 group. Conversely, on a clear day (10 July), the J–I phase of the T2 group sharply increased compared to that of the control and T1 groups. On a cloudy day with low ambient light intensity, the rate of electron transport flux from QA to QB per photosystem II reaction center (ET0/RC) and carbon dioxide (CO2) fixation of TiO2-treated plants were increased compared to those of the control. However, on a clear day of high light intensity, the ET0/RC and CO2 fixation of the T2 group were lower than those of the control and Tl groups. The yield of fruit was increased in the T1 group over that in other treatments. TiO2 treatment reduced the size of the fruit and delayed the ripening time, but greatly increased the fruit hardness. These results suggest that setting the concentration and supply amount of TiO2 nanoparticles suitable for various environmental conditions should be prioritized in order to improve the effect of TiO2 nanoparticles in tomato cultivation.

Cultivation and Biorefinery of Microalgae (Chlorella sp.) for Producing Biofuels and Other Byproducts: A Review

Microalgae-based carbon dioxide (CO2) biofixation and biorefinery are the most efficient methods of biological CO2 reduction and reutilization. The diversification and high-value byproducts of microalgal biomass, known as microalgae-based biorefinery, are considered the most promising platforms for the sustainable development of energy and the environment, in addition to the improvement and integration of microalgal cultivation, scale-up, harvest, and extraction technologies. In this review, the factors influencing CO2 biofixation by microalgae, including microalgal strains, flue gas, wastewater, light, pH, temperature, and microalgae cultivation systems are summarized. Moreover, the biorefinery of Chlorella biomass for producing biofuels and its byproducts, such as fine chemicals, feed additives, and high-value products, are also discussed. The technical and economic assessments (TEAs) and life cycle assessments (LCAs) are introduced to evaluate the sustainability of microalgae CO2 fixation technology. This review provides detailed insights on the adjusted factors of microalgal cultivation to establish sustainable biological CO2 fixation technology, and the diversified applications of microalgal biomass in biorefinery. The economic and environmental sustainability, and the limitations and needs of microalgal CO2 fixation, are discussed. Finally, future research directions are provided for CO2 reduction by microalgae.