Journal of environmental chemical engineering, Год журнала: 2025, Номер unknown, С. 115653 - 115653
Опубликована: Янв. 1, 2025
Язык: Английский
Journal of environmental chemical engineering, Год журнала: 2025, Номер unknown, С. 115653 - 115653
Опубликована: Янв. 1, 2025
Язык: Английский
Phytochemistry Reviews, Год журнала: 2022, Номер 22(4), С. 1089 - 1126
Опубликована: Май 2, 2022
Язык: Английский
Процитировано
174International Journal of Hydrogen Energy, Год журнала: 2023, Номер 54, С. 127 - 160
Опубликована: Май 21, 2023
Язык: Английский
Процитировано
119International Journal of Hydrogen Energy, Год журнала: 2022, Номер 48(18), С. 6738 - 6760
Опубликована: Май 8, 2022
Язык: Английский
Процитировано
92Bioresource Technology, Год журнала: 2022, Номер 367, С. 128255 - 128255
Опубликована: Ноя. 5, 2022
Pine needles (PNs) are one of the largest bio-polymer produced worldwide. Its waste, i.e., fallen PNs, is mostly responsible for forest fires and a major challenge. In present article, we have reviewed differenteffortsmadeto tackle this situation. PNs been used in various fields such asin composite, water purification industries,electronic devices, etc. Gasification appealing processes turning into bio-energy; pyrolysis technique has employed to create carbon-based materials; saccharification combined with fermentation good yields bio-ethanol; Pd or Ni/PNs biocatalyst showed catalytic properties variousreactionsand without catalyst an alluring prepare bio-fuel. Nano cellulose extracted from thermal mechanical strength. The air quality nearbyenvironment was examinedby studying magnetic PNs. Packing materials made exceptional ethylene scavenging abilities.
Язык: Английский
Процитировано
83Bioresource Technology, Год журнала: 2022, Номер 363, С. 127958 - 127958
Опубликована: Сен. 13, 2022
Язык: Английский
Процитировано
76Carbon, Год журнала: 2023, Номер 211, С. 118105 - 118105
Опубликована: Май 11, 2023
Язык: Английский
Процитировано
72Energy & Fuels, Год журнала: 2024, Номер 38(4), С. 2654 - 2689
Опубликована: Фев. 2, 2024
The rapid depletion of fossil-derived fuels along with rising environmental pollution have motivated academics and manufacturers to pursue more environmentally friendly sustainable energy options in today's globe. Biodiesel has developed as an ecologically favorable alternative. However, the mass manufacturing biodiesel on industrial scale confronts substantial cost pricing challenges. To address this issue, high-efficiency catalysts a large number active sites are needed, resulting increased output quality. Metal–organic frameworks (MOFs) received lot interest catalyst for converting oils/fats or fatty acids into biodiesel. MOFs polyporous materials that can alter pore size well topological structure. They serve versatile foundation designing satisfy unique needs catalytic reactions conversion pathways. purpose current work is shed light underlying mechanisms essential properties MOF-based used synthesis. In addition, several methods connecting inside scrutinized, while usability production process completely compared other catalysts. More importantly, limits future research directions about utilization synthesis route also critically presented. general, review contributes improved awareness potential sector by investigating primary mechanism characteristics
Язык: Английский
Процитировано
20International Journal of Hydrogen Energy, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
4Case Studies in Thermal Engineering, Год журнала: 2022, Номер 40, С. 102448 - 102448
Опубликована: Сен. 24, 2022
The thermal performance of a flat plate solar collector using MWCNT + Fe3O4/Water hybrid nanofluids was examined in this research. tested different nanofluid concentrations and flow rates an arid environment. A significant enhancement coefficient heat transfer (26.3%) with marginal loss on pressure drop due to friction factor (18.9%). data collected during experimental testing utilized develop novel prediction models for efficient transfer, Nusselt's number, factor, efficiency. modern ensemble machine learning techniques Boosted Regression Tree (BRT) Extreme Gradient Boosting (XGBoost) were used prognostic each parameter. battery statistical methods Taylor's graphs compare the these two ML techniques. value R2 BRT-based 0.9619 - 0.9994 0.9914 0.9997 XGBoost-based models. mean squared error quite low all (0.000081 9.11), while absolute percentage negligible from 0.0025 0.3114. comprehensive analysis model complemented improved comparison paradigm, reveal superiority XGBoost over BRT.
Язык: Английский
Процитировано
64Fuel, Год журнала: 2022, Номер 329, С. 125362 - 125362
Опубликована: Июль 27, 2022
Язык: Английский
Процитировано
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