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Hydrothermal liquefaction (HTL) is an effective way to treat solid wastes with high moisture content. The co-hydrothermal liquefaction (co-HTL) experiments of oily scum and poplar sawdust biochar at the different hydrothermal temperatures were performed in this work. The changes of the appearance and components of the liquid products were comprehensively studied. The results showed that the addition of biochar into oily scum significantly reduced the moisture content of the residue hydrochars obtained after co-HTL. As the hydrothermal temperature increased, the liquid products obtained from co-HTL turned clearer and lighter in color, and the recovery rate of the liquid products significantly increased. The co-HTL of bi-ochar and oily scum could effectively improve the liquid quality and enhance the recovery rate of hydrochars. The carbon numbers of the liquid products obtained from co-HTL were concentrated in C5-C11, which were main compositions of gas-oline. This work can provide basic data and theoretical reference for oily scum efficient treatment and engineering practice.

The regulation of catalyst activity and selectivity using a reducible support for the industrially relevant hydrogenation of 1,3-butadiene to more valuable butene products was achieved. Supported palladium and nickel–palladium catalysts on ceria were prepared and characterized with hydrogen temperature programmed reduction (H2-TPR), hydrogen temperature programmed desorption (H2-TPD), X-ray photoelectron spectroscopy (XPS), high resolution transmission electron microscopy (HR-TEM), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), temperature programmed oxidation (TPO), energy dispersive spectroscopy (EDS), and N2 adsorption–desorption to examine their chemical and physical properties. Pathways guiding the reaction were determined using the density functional theory (DFT). H2-TPR confirmed that palladium oxide was reduced, and nickel oxide species strongly interacted with the CeO2 support. The Ce3+ concentration determined by XPS showed that all catalysts surface contained the Ce reduced state. The catalysts showed a similar BET surface area, with 4Pd–Ce presenting the lowest value due to particle aggregation, which was confirmed from the EDS mapping analysis. Butadiene conversion consistently increased with temperature (40 °C–120 °C) until full conversion was reached on all the Pd catalysts while the maximum conversion on the 4Ni-Ce catalyst was 88 % at 120 °C. Product distribution revealed that 4 % Pd content directed the products toward butane when 40 °C was exceeded. Constructed mechanisms by DFT calculations featured low reaction barriers for the involved surface hydrogenation steps, and thus, they accounted for the observed low temperature of the surface hydrogenation activity. Selective formation of 1-butene partially stemmed from its relatively weak binding to Ni sites in reference to Pd sites. The mapped-out mechanisms entailed a higher reaction barrier for the formation of 2-butene, in agreement with the experimental observation pertinent to its formation at higher temperatures when compared with that of 1-butene.

This paper considers the sequential design of remedial control actions in response to system anomalies for the ultimate objective of preventing blackouts. A physics-guided reinforcement learning (RL) framework is designed to identify effective sequences of real-time remedial look-ahead decisions accounting for the long-term impact on the system's stability. The paper considers a space of control actions that involve both discrete-valued transmission line-switching decisions (line reconnections and removals) and continuous-valued generator adjustments. To identify an effective blackout mitigation policy, a physics-guided approach is designed that uses power-flow sensitivity factors associated with the power transmission network to guide the RL exploration during agent training. Comprehensive empirical evaluations using the open-source Grid2Op platform demonstrate the notable advantages of incorporating physical signals into RL decisions, establishing the gains of the proposed physics-guided approach compared to its black box counterparts. One important observation is that strategically~\emph{removing} transmission lines, in conjunction with multiple real-time generator adjustments, often renders effective long-term decisions that are likely to prevent or delay blackouts.

Globally, energy demands are massive, and environmental issues are rising against our sustainability. To maximize the use of renewable energy sources, development of efficient energy storage systems is mandatory. Lithium-ion batteries (LIBs) play an indispensable role in powering portable devices and electric vehicles, due to their high specific capacity and long cycle life. Manganese oxide (Mn3O4) is an environmentally friendly anode active material with high theoretical specific capacity of 936 mAh g−1 for applications in Li-ion cells.In the present work, Mn3O4-functionalized carbon nanotubes (FCNT) nanocomposite, coated on carbon cloth (CC) current collector and termed as Mn3O4-FCNT @CC, is used as the anode material. Li-ion coin cells based on this nanocomposite anode show discharge capacity of 1371mAhg−1 and charge capacity of 1141mAhg−1 at current density of 100 mA g−1 with initial Coulombic efficiency of 83%. After 70 cycles, the charge-discharge capacities of the cells are 953mAhg−1 and 958mAhg−1, respectively, with capacity retention of 91% at current rate of 100 mA g−1. These cells are found to deliver reversible charge capacity of 575mAhg−1 after 100 cycles at 1C (∼1 A g−1) and offer prospects of stable operation at high current rates.

This study introduces a mixed-integer linear programming (MILP) model, effectively co-optimizing patrolling, damage assessment, fault isolation, repair, and load re-energization processes. The model is designed to solve a vital operational conundrum: deciding between further network exploration to obtain more comprehensive data or addressing the repair of already identified faults. As information on the fault location and repair timelines becomes available, the model allows for dynamic adaptation of crew dispatch decisions. In addition, this study proposes a conservative power flow constraint set that considers two network loading scenarios within the final network configuration. This approach results in the determination of an upper and a lower bound for node voltage levels and an upper bound for power line flows. To underscore the practicality and scalability of the proposed model, we have demonstrated its application using IEEE 123-node and 8500-node test systems, where it delivered promising results.

This study explores the relationship between grid reliability and energy efficiency in China’s energy landscape. Findings highlight the influence of energy efficiency in the past while revealing random effects of smart grid penetration. Demand-side management and renewable energy integration significantly increase energy efficiency. Grid reliability and technology investment enhance efficiency, although consumption pattern changes show a limited impact. Implications for policy and energy strategies are discussed.

Biofuel, a sustainable fuel source, is crucial in the modern day as it reduces reliance on non-renewable energy sources and helps to reduce CO2 emissions. The manufacture of biofuels on a wide scale is a difficult process due to the numerous limitations in current technology and the subsequent rise in expenses. Moreover, the processes employed to transform diverse raw materials into the desired biofuel may differ depending on the particular methodologies and substances utilized. The global demand for bioethanol is growing as countries throughout the world enforce legislation requiring the blending of bioethanol with gasoline. Second-generation bioethanol derived from lignocellulosic biomass is rapidly gaining prominence. The biochemical conversion process has various technical, practical, and economic challenges such as pre-treatment, hydrolysis, and fermentation. Nanoparticles (NPs) offer a highly efficient solution for overcoming current challenges in utilizing biomass, thanks to their selectivity, energy efficiency, and time management capabilities, all while reducing prices. Also, the biotechnological significant advancement in revolutionized the sorghum varieties or strains to enhance the yield of ethanol. This article offers a succinct summary of bioethanol from sweet sorghum feedstock and the progress made in using nanotechnology to produce them, with a specific focus on the enzyme immobilization approach. The text offers an in-depth exploration of how nanotechnology is utilized across ethanol production, with a specific focus on comprehending the process by which enzymes immobilized on nanoparticles interact with lignocellulose to enhance the output of ethanol.

In this review, the potential role of machine learning in sustainable energy and SGDs is analyzed; energy forecasting, planning, renewable energy production and storage are covered and an extensive perspective on the future role of ML is provided.

A self-operating photothermal CO2 methanation system in solar free environments is successfully developed by integrating a homemade photothermal TiC/Cu based device with a solid solution structure of NiO and CeO2.