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Graphene is a new generation material, which finds potential and practical applications in a vast range of research areas. It has unrivalled characteristics, chiefly in terms of electronic conductivity, mechanical robustness and large surface area, which allow the attainment of outstanding performances in the material science field. Some unneglectable issues, such as the high cost of production at high quality and corresponding scarce availability in large amounts necessary for mass scale distribution, slow down graphene widespread utilization; however, in the last decade both basic academic and applied industrial materials research have achieved remarkable breakthroughs thanks to the implementation of graphene and related 1D derivatives. In this work, after briefly recalling the main characteristics of graphene, we present an extensive overview of the most recent advances in the development of the Li-ion battery anodes granted by the use of neat and engineered graphene and related 1D materials. Being far from totally exhaustive, due to the immense scientific production in the field yearly, we chiefly focus here on the role of graphene in materials modification for performance enhancement in both half and full lithium-based cells and give some insights on related promising perspectives.

Electricity is indispensable and of strategic importance to national economies. Consequently, electric utilities make an effort to balance power generation and demand in order to offer a good service at a competitive price. For this purpose, these utilities need electric load forecasts to be as accurate as possible. However, electric load depends on many factors (day of the week, month of the year, etc.), which makes load forecasting quite a complex process requiring something other than statistical methods. This study presents an electric load forecast architectural model based on an Artificial Neural Network (ANN) that performs Short-Term Load Forecasting (STLF). In this study, we present the excellent results obtained, and highlight the simplicity of the proposed model. Load forecasting was performed in a geographic location of the size of a potential microgrid, as microgrids appear to be the future of electric power supply.

This article describes the results of a study of Ecuador’s energy status, using the system dynamics methodology to model supply, demand and CO2 emissions scenarios for the year 2030. Primary energy production increased in the different projected scenarios, with oil as the most important source of energy. The increase observed in final energy consumption was mainly associated with the transport and industry sectors. A reduction in energy intensity was projected for the different scenarios, which could be associated with the projected economic growth. The results obtained were used to build a proposal for energy policies aimed at mitigating emissions. The proposed changes to the national energy matrix could be the factors that will contribute most to the achievement of carbon emission reductions projected by the different scenarios; changes in the energy matrix are mainly associated with the development of projects to replace fossil fuels with renewable energies, mainly hydropower.

Linear switched reluctance motors are a focus of study for many applications because of their simple and sturdy electromagnetic structure, despite their lower thrust force density when compared with linear permanent magnet synchronous motors. This study presents a novel linear switched reluctance structure enhanced by the use of permanent magnets. The proposed structure preserves the main advantages of the reluctance machines, that is, mechanical and thermal robustness, fault tolerant, and easy assembly in spite of the permanent magnets. The linear hybrid reluctance motor is analyzed by finite element analysis and the results are validated by experimental results. The main findings show a significant increase in the thrust force when compared with the former reluctance structure, with a low detent force.

The aim of this study is to characterise the changes in mechanical properties and to provide a comprehensive micro-structural analysis of Harcourt granite over different pre-heating temperatures under two cooling treatments (1) rapid and (2) slow cooling. A series of uniaxial compression tests was conducted to evaluate the mechanical properties of granite specimens subjected to pre-heating to temperatures ranging from 25–1000 °C under both cooling conditions. An acoustic emission (AE) system was incorporated to identify the fracture propagation stress thresholds. Furthermore, the effect of loading and unloading behaviour on the elastic properties of Harcourt granite was evaluated at two locations prior to failure: (1) crack initiation and (2) crack damage. Scanning electron microscopy (SEM) analyses were conducted on heat-treated thin rock slices to observe the crack/fracture patterns and to quantify the extent of micro-cracking during intense heating followed by cooling. The results revealed that the thermal field induced in the Harcourt granite pore structure during heating up to 100 °C followed by cooling causes cracks to close, resulting in increased mechanical characteristics, in particular, material stiffness and strength. Thereafter, a decline in mechanical properties occurs with the increase of pre-heating temperatures from 100 °C to 800 °C. However, the thermal deterioration under rapid cooling is much higher than that under slow cooling, because rapid cooling appears to produce a significant amount of micro-cracking due to the irreversible thermal shock induced. Multiple stages of loading and unloading prior to failure degrade the elastic properties of Harcourt granite due to the damage accumulated through the coalescence of micro-cracks induced during compression loading. However, this degradation is insignificant for pre-heating temperatures over 400 °C, since the specimens are already damaged due to excessive thermal deterioration. Moreover, unloading after crack initiation tends to cause insignificant irreversible strains, whereas significant permanent strains occur during unloading after crack damage, and this appears to increase with the increase of pre-heating temperature over 400 °C.

Increasing biogas production in the Three Seas Initiative countries (3SI) is a good way to reduce greenhouse gas emissions and to increase energy self-sufficiency by replacing some of the fossil energy sources. An assessment of the biogas production potential carried out for the 3SI at the NUTS 1 and NUTS 2 level shows that the potential of this energy carrier was stable for the period (from 2010–2021). The results showed that it can cover from approximately 10% (Hungary, Slovakia) to more than 34% (Estonia, Slovenia) of natural gas consumption; moreover, there is strong variation in the value of potential at the regional level (NUTS 2) in most of the countries studied. The biogas production forecast was carried out with the ARIMA model using four regressors, which are GDP, biogas potential utilisation, natural gas consumption and investments in RES (renewable energy sources) infrastructure, including changes in the EU energy policy after 24 February 2022. In the most promising scenario (four regressors), the results obtained for the period from 2022–2030 predict a rapid increase in biogas production in the 3SI countries, from 32.4 ± 11.3% for the Czech Republic to 138.7 ± 27.5% for Estonia (relative to 2021). However, in the case of six countries (Bulgaria, Lithuania, Hungary, Austria, Poland and Romania) the utilisation of 50% of the potential will most likely occur in the fifth decade of the 21st century. The above results differ significantly for those obtained for three regressors, where the highest rise is predicted for Bulgaria at 33.5 ± 16.1% and the lowest for Slovenia, at only 2.8 ± 14.4% (relative to 2021).