56016 research outputs found
Sort by
Oily waste to biosurfactant: A path towards carbon neutrality and environmental sustainability
No full textTons of oily waste accumulating worldwide has led to severe environmental problems and an increase in carbon footprint. The oily waste is rich in carbon and therefore its utilization as a substrate for the production of value-added products can aid in the concept of carbon neutrality. Oils can be directly utilized as substrate and microorgan-isms can catabolize them to produce biosurfactants. Biosurfactants being biodegradable and less toxic than synthetic surfactants are the molecules of the 21st century and are preferred candidates. Also, several fungal species can bio-transform oils to produce biosurfactants. Therefore, this study comprehensively summarizes different categories of oily waste generated worldwide, their sources, and environmental toxicity. The microbial efficiency towards oily waste utilization for the production of biosurfactants is reviewed. Following this, advance techniques including metabolic engineering, and omics approaches for biosurfactant production from this waste have been presented. Their global market and future perspective have been discussed to further emphasize the requirement for biosurfactants. The state-of-the-art information provided in various sections of this manuscript may aid the researchers to understand the relationship of oily waste utilization with carbon footprint generation. This directs attention and warrants future research towards the development of improved pathways/processes in oil waste based biorefineries.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Seedless electrodeposition of Cu thin films on ALD Ru diffusion barriers with different electrical properties
No full textSeedless Cu electrodeposition was performed directly on 10 nm atomic-layer-deposited (ALD) Ru diffusion barrier layer for Cu interconnect application in microelectronic devices. N2 gas flow rate ratio of Ru ALD process was varied between 0.24 and 0.86 to manipulate the electrical property of resultant ALD Ru layers. The nucleation and growth characteristic of Cu on ALD Ru changed depending on the electrical resistivity of ALD Ru layer under the potentiostatic deposition of Cu in an additive-free Cu-ammonia-citrate (Cu-NH3-Cit) electrolyte. As a result, a less resistive ALD Ru layer, which was formed at a lower N2 gas flow rate ratio, led to a lower electrical resistivity of Cu thin film
A Review on Flame Stabilization Technologies for UAV Engine Micro-Meso Scale Combustors: Progress and Challenges
No full text<jats:p>Unmanned aerial vehicles (UAV)s have unique requirements that demand engines with high power-to-weight ratios, fuel efficiency, and reliability. As such, combustion engines used in UAVs are specialized to meet these requirements. There are several types of combustion engines used in UAVs, including reciprocating engines, turbine engines, and Wankel engines. Recent advancements in engine design, such as the use of ceramic materials and microscale combustion, have the potential to enhance engine performance and durability. This article explores the potential use of combustion-based engines, particularly microjet engines, as an alternative to electrically powered unmanned aerial vehicle (UAV) systems. It provides a review of recent developments in UAV engines and micro combustors, as well as studies on flame stabilization techniques aimed at enhancing engine performance. Heat recirculation methods have been proposed to minimize heat loss to the combustor walls. It has been demonstrated that employing both bluff-body stabilization and heat recirculation methods in narrow channels can significantly improve combustion efficiency. The combination of flame stabilization and heat recirculation methods has been observed to significantly improve the performance of micro and mesoscale combustors. As a result, these technologies hold great promise for enhancing the performance of UAV engines.</jats:p>
Study on biophysical properties and R-loop collision of Phi29 DNA polymerase using a novel single-molecule imaging technique
No full textIonic Ir(iii) complex-interfacial layer for efficient carrier collection via induced electric dipole
No full textThe power conversion efficiency (PCE) of polymer solar cells (PSCs) has recently reached >19% through the development of photoactive materials, particularly non-fullerene acceptors. Interfacial layers (ILs) have been another essential factor in optimizing device charge extraction. In this study, we propose a series of ILs, in which ionic iridium(iii) (Ir(iii)) complexes of different alkali metal cations (Li+, Na+, and K+) enhance the charge collection efficiency between zinc oxide and active layers through an induced internal electric field. The anionic coordinate sphere and counter-cations of the Ir(iii) complexes are distributed according to the operating voltage of the PSCs, causing electric dipoles that enhance the internal electric field and charge collection efficiency. Ion species migration in the ILs is confirmed using electrochemical impedance spectroscopy. The PCE of the PM6:Y6-based PSCs was improved from 14.0% to 15.6% by introducing an IL (Ir-K+). Furthermore, the stability of PSCs containing ionic Ir(iii) complexes is enhanced significantly under ultraviolet (UV) light and AM 1.5 G one-sun irradiation owing to the intense UV absorption capacity and photo durability of the ILs. A device containing the Ir(iii) complex-based ILs retained similar to 60% of its initial PCE after UV irradiation, whereas the control device retained only similar to 20%
Crystal graph convolution neural networks for fast and accurate prediction of adsorption ability of Nb2CTx towards Pb(ii) and Cd(ii) ions
No full textPrecisely measuring the adsorption capability of materials towards toxic heavy metal ions in aqueous solution is essential for the synthesis of effective novel adsorbents. Nonetheless, no such technology is available that can accurately measure the adsorption capability at arbitrary adsorption sites. In the present study, we employed an artificial intelligence route to predict the adsorption capability of two-dimensional niobium carbide (Nb2CTx) at arbitrary adsorption sites for lead (Pb(ii)) and cadmium (Cd(ii)) ions. A crystal graph convolution neural network (CGCNN) model was applied to predict the adsorption capability of Nb2CTx with the results indicating that Pb(ii) ions had a higher adsorption energy than Cd(ii) ions with a mean absolute error and root-mean-squared error less than 0.09 eV and 0.16 eV, respectively. The proposed CGCNN model has a similar prediction to the ab initio DFT calculations, yet significantly fast and economical. Finally, the adsorption capability of Nb2CTx synthesized using a fluorine-free route was also experimentally verified, and the results were consistent with DFT calculations and CGCNN predictions. In addition, the synthesized Nb2CTx exhibited a higher recycling potential over five successive runs. Collectively, these findings indicated that the proposed technique is highly efficient in investigating the adsorption performance of materials and can be further extended for use in the removal of other hazardous pollutants from aqueous environments
Origin of Higher CO Oxidation Activity of Pt/Rutile than That of Pt/ Anatase
No full textHerein, we show that the weak interaction of CO with Pt/TiO2 under the CO oxidation condition is the origin of higher CO oxidation activity of Pt/rutile than that of Pt/anatase. The results of CO temperature-programmed desorption (TPD) and in situ diffuse reflectance infrared Fourier transform spectros-copy (DRIFTS) indicate that the onset temperatures of CO desorption on freshly prepared Pt/rutile and Pt/anatase are the same. However, the CO-TPD curves of Pt/rutile after the reaction test show that the desorption temperature of CO shifts to a lower temperature, while that for Pt/anatase does not change. The in situ pulse reaction using DRIFTS reveals that CO on Pt/rutile reacted with oxygen faster than CO on Pt/anatase. IR spectra with peak deconvolution of adsorbed CO on Pt/rutile exhibit that CO adsorbed on the terrace sites of Pt clusters on rutile (2089 cm-1) reacts readily with O2. These results indicate that the higher low-temperature activity of Pt/rutile is related to its weaker interaction with CO compared with Pt/anatase under the reaction conditions. Our findings deepen the fundamental understanding of metal-support interaction and CO oxidation on Pt/TiO2 catalysts
Intertwining porous silicon with conducting polymer for high-efficiency stable Li-ion battery anodes
No full textPorous silicon anodes have been extensively investigated for the high-performance lithium-ion battery, owing to their high capacity and structural robustness as dominantly incorporated with conductive carbon sheath. However, the typical high-temperature annealing process for carbon coating induces the collapse of pre-engineered pores and limits the full utilization of porous structures. In this work, porous silicon flake intertwined with doped polyaniline was prepared via redox-transmetalation reaction followed by a wet coating process of conducting polymer. The proposed method eliminates the risk of pore collapse and utilizes the conductive network without compromising the porous structure. As a result, the prepared composite consisting of porous silicon flake and doped polyaniline shows an extended battery cycle life, reduced electrode swelling, and increased efficiency
Precipitation nowcasting using ground radar data and simpler yet better video prediction deep learning
No full textSkillful quantitative precipitation nowcasting (QPN) is important for predicting precipitation in the upcoming few hours and thus avoiding significant socioeconomic damage. Recent QPN studies have actively adopted deep learning (DL) to generate precipitation maps using sequences of ground radar data. Although high skill scores in forecasting precipitation areas of weak intensity (similar to 1 mm/h) have been achieved, the horizontal movement of precipitation areas could not be accurately simulated, exhibiting poor forecasting skills for stronger intensities. For lead times up to 120 min, this study suggests using an improved radar-based QPN model that utilizes a state-of-the-art DL model termed simpler yet better video prediction (SimVP). An independent evaluation using ground radar data in South Korea from June to September 2022 demonstrated that the proposed model outperformed the existing DL models in terms of critical score index (CSI) with a lead time of 120 min (0.46, 0.23, and 0.09 for 1, 5, and 10 mm/h thresholds, respectively). Three case analyses were conducted to reflect various precipitation conditions: heavy rainfall, typhoons, and fast-moving narrow convection events. The proposed SimVP-based QPN model yielded robust performance for all cases, producing a comparable or highest CSI at the lead time of 120 min with a 1 mm/h threshold (0.49, 0.69, and 0.29 for heavy rainfall, typhoon, and narrow convection, respectively). Qualitative evaluation of the model indicated better results in terms of displacement movement and reduced underestimation than other models under the high variability of precipitation patterns of the three cases. A comparison of model complexity among DL-QPN models was conducted, taking into consideration operational applications across various study areas and environments. The proposed approach is expected to provide a new baseline for DL-based QPN, and the improved prediction using the proposed model can lead to reduced socioeconomic damage incurred as a result of short-term intense precipitation