Important Energy Research Articles

Research on internal leakage detection of the ball valves based on stacking ensemble learning

Abstract Natural gas is an important clean energy source that is mainly transported through pipelines. The ball valve is a crucial piece of control equipment for the pipeline transportation system for natural gas, and the failure of internal leakage of the ball valve will seriously affect the natural gas transmission and increase the risk of sudden safety accidents. In response to the problems of the limitations of a single machine learning model in the traditional ball valve internal leakage rate prediction methods and failure to qualitatively analyze unilateral and bilateral internal leakage recognition of ball valve, a study of ball valve internal leakage detection based on Stacking ensemble learning is proposed. A total of 15 time and frequency domain feature parameters were obtained by feature extraction of 125 and 96 sets of raw acoustic emission signals from the ball valve; the parameters of a single machine learning model were adjusted by Bayesian optimization grid search. An internal leakage rate prediction model and an internal leakage recognition model are constructed, and the proposed model is compared and analyzed with a single model through a field ball valve internal leakage test. The results indicate that the Stacking ensemble learning model outperforms each single machine learning model in terms of SMAPE (17.2583), RMSE (1.1009), and MAE (0.9375) for internal leakage rate prediction. The Stacking ensemble learning model outperformed the single machine learning model in terms of accuracy (1), recall (1), precision (1), FAR(0), and F1-score (1) for internal leakage recognition. Stacking ensemble learning significantly enhances the model's ability to detect internal ball valve leaks.

Differential Mechanisms of Microbial As(III) and Sb(III) Oxidation and Their Contribution to Tailings Reclamation.

Mine tailings are extremely oligotrophic environments frequently contaminated with elevated As and Sb, making As(III) and Sb(III) oxidation potentially important energy sources for the tailing microbiome. Although they have been proposed to share similar metabolic pathways, a systemic comparison of the As(III) and Sb(III) oxidation mechanisms and energy utilization efficiencies requires further elucidation. In this study, we employed a combination of physicochemical, molecular, and bioinformatic analyses to compare the kinetic and genetic mechanisms of As(III) and Sb(III) oxidation as well as their respective energy efficiencies for fueling the key nutrient acquisition metabolisms. Thiobacillus and Rhizobium spp. were identified as functional populations for both As(III) and Sb(III) oxidation in mine tailings by DNA-stable isotope probing. However, these microorganisms mediated As(III) and Sb(III) oxidation via different metabolic pathways, resulting in preferential oxidation of Sb(III) over As(III). Notably, both As(III) and Sb(III) oxidation can facilitate nitrogen fixation and phosphate solubilization in mine tailings, with Sb(III) oxidation being more efficient in powering these processes. Thus, this study provided novel insights into the microbial As(III) and Sb(III) oxidation mechanisms and their respective nutrient acquisition efficiencies, which may be critical for the reclamation of mine tailings.

A statistical study for the impact of REMS and nuclear energy on carbon dioxide emissions reductions in G20 countries

Renewable and nuclear energy are seen as clean and eco-friendly substitutes for energy derived from fossil fuels. Which of the two is better, though, is still up for debate. In order to meet their combined global energy objectives and perhaps become carbon neutral or even carbon negative in the near future, a shift to additional renewable energy sources and nuclear energy will be necessary. One such method of improving energy usage through the implementation of a renewable energy management system (REMS) that will help attain a continuous and reliable source of energy, allowing for the proactive and effective management of renewable assets and dependable supply. This article investigates attitudes and opinions about nuclear and renewable energy production technologies by analyzing the dependence of carbon dioxide (CO2) emissions on non-renewable energy sources, renewable energy sources, and nuclear energy in the group of twenty (G20) countries, over the period from 2000 to 2021. This study employs advanced panel data econometric techniques in the presence of outliers in the G20 dataset, utilizing a robust random coefficient regression (RRCR) model via the M-estimation approach to study the impacts of non-renewable, renewable, and nuclear energy use with respect to CO2 emission mitigation in G20 countries. The overall conclusions of the econometric analysis confirm renewable and nuclear energy's importance in reducing CO2 emissions. We can conclude that the robust M-estimate approach is the best estimation technique for the G20 dataset, as compared to the classical estimation methods in the presence of outliers. The results show that for every percentage point of energy consumption that falls into the category of non-renewable energy, CO2 emissions will increase by 2.5737% for all G20 countries. Also, A 1% rise in renewable energy consumption reduces CO2 emissions by 1.0566% for all G20 countries. Similarly, a 1% increase in nuclear energy consumption will reduce CO2 emissions by 5.5703% for all G20 countries. Therefore, we can conclude that energy derived from renewable sources and nuclear energy greatly cuts CO2 emissions in all G20 countries. Total energy consumption, on the other hand, increases CO2 emissions in the long run. According to these findings, it is pivotal for the G20 countries to increase nuclear energy use and employ REMS to reduce the majority of G20 country's reliance on fossil fuels in order to minimize CO2 emissions. These findings are vital for understanding the relationship between these variables and the implementation of new or revised policies and initiatives supporting carbon neutrality at the G20 countries and national levels.

Exploring chemical disposal options for non-condensable gasses in geothermal power plants: A case study of Kızıldere geothermal field (Türkiye)

Geothermal power plants are among the most important renewable energy power plants owing to their high-capacity factors and integrated utilization possibilities. Currently, these power plants utilize geothermal fluid to generate electricity. Although their emissions are lower than those of conventional power plants, gasses such as CO2 and H2S are released into the air from the cooling towers, particularly in flash-type geothermal power plantsTo reduce the emission of CO2 gas released from geothermal power plants, reinjection studies have mainly been carried out around the world. These types of studies require extensive analysis of underground fracture systems, detailed geosciences, and the reservoir studies. However, these studies are considered risky and expensive for most plant operators because possible changes in underground fracture systems may affect the productivity of geothermal production zones. In terms of the environmental impact, hydrogen sulfide is a more harmful gas than CO2. Effective H2S removal methods cannot be widely used, except in areas with extremely high concentrations, because they commonly incur significant costs for plant operators. Effective H2S removal methods are not widely available except for geothermal sites with high concentrations. The fact that local limit values can be exceeded in geothermal power plants with relatively low H2S concentrations, such as geothermal power plants in Türkiye, pushes plant operators to find new low-cost solutions due to high operation costs. For this reason, a treatment method that can be applied at every site and whose cost is not too high has not yet been put forward. However, NaOH is used for this purpose in geothermal fields such as steam-dominated Geyser field to increase the pH values in geothermal wells, which has been producing for a long time.In this study, field tests were carried out with five different chemicals and pure water to examine the reduction of non-condensable gasses in a geothermal power plant located in the Kızıldere (Denizli, Türkiye) geothermal field, one of the most important geothermal fields in the world. According to this, the capture of these gasses is technically possible using chemical methods, with a performance of up to 70 % observed in CO2 gas capture.However, although it is possible to capture 70 % of non-condensable gasses with such chemical methods, the consumable cost of the operation is quite high.

Quantifying soil moisture and evapotranspiration heterogeneity within a solar farm: Implications for stormwater management

As solar energy becomes a cheap source of renewable energy, the number of major utility-scale ground solar panel installations, often called ‘solar farms,’ are growing. With these solar farms often covering hundreds of acres, there is potential for impacts on natural hydrologic processes, including runoff generation and erosion. There is still limited research in this area, and best management practices to address these impacts are variable and not well understood. To fill this gap, we conducted a field investigation of soil moisture patterns, solar radiation, and vegetation at two solar farms in central Pennsylvania, USA that are representative of the complex terrain in the region (e.g., high or variable slopes). Both solar farms also included engineered infiltration basins or trenches that were investigated. Analysis of soil moisture patterns reveals redistribution of water relative to panels, with dripline soil moisture 19 % higher than the reference, and underpanel moisture 25 % lower than the reference, on average at both solar farms over a year. There are also the greatest periods of saturation and runoff generation at the panel driplines. However, an open interspace between panel rows and existing infiltration basins and trenches are playing a critical role in managing runoff. Micrometeorological monitoring indicates reduced evapotranspiration (ET) under panels, with potential underpanel ET 37–67 % lower in summer, and minimal difference in winter. However, a survey of vegetation revealed almost complete ground coverage under panels, which is critical for supporting infiltration and reducing erosion. As solar farms expand to meet important renewable energy goals, it is essential that care be taken to design the landscape to minimize runoff generation and erosion. This work demonstrates that healthy vegetation and well-draining soils can help manage runoff on solar farms; where necessary on more challenging landscapes, engineered stormwater controls can manage any unmitigated runoff.

Integration analysis of transcriptome and proteome profiles brings new insights of somatic embryogenesis of two eucalyptus species

BackgroundSomatic embryogenesis (SE) is recognized as a promising technology for plant vegetative propagation. Although previous studies have identified some key regulators involved in the SE process in plant, our knowledge about the molecular changes in the SE process and key regulators associated with high embryogenic potential is still poor, especially in the important fiber and energy source tree – eucalyptus.ResultsIn this study, we analyzed the transcriptome and proteome profiles of E. camaldulensis (with high embryogenic potential) and E. grandis x urophylla (with low embryogenic potential) in SE process: callus induction and development. A total of 12,121 differentially expressed genes (DEGs) and 3,922 differentially expressed proteins (DEPs) were identified in the SE of the two eucalyptus species. Integration analysis identified 1,353 (131 to 546) DEGs/DEPs shared by the two eucalyptus species in the SE process, including 142, 13 and 186 DEGs/DEPs commonly upregulated in the callus induction, maturation and development, respectively. Further, we found that the trihelix transcription factor ASR3 isoform X2 was commonly upregulated in the callus induction of the two eucalyptus species. The SOX30 and WRKY40 TFs were specifically upregulated in the callus induction of E. camaldulensis. Three TFs (bHLH62, bHLH35 isoform X2, RAP2-1) were specifically downregulated in the callus induction of E. grandis x urophylla. WGCNA identified 125 and 26 genes/proteins with high correlation (Pearson correlation > 0.8 or < -0.8) with ASR3 TF in the SE of E. camaldulensis and E. grandis x urophylla, respectively. The potential target gene expression patterns of ASR3 TF were then validated using qRT-PCR in the material.ConclusionsThis is the first time to integrate multiple omics technologies to study the SE of eucalyptus. The findings will enhance our understanding of molecular regulation mechanisms of SE in eucalyptus. The output will also benefit the eucalyptus breeding program.

Advancing Sustainable Energy Development: A Study of the Factors Influencing Distributed Photovoltaic Industry in Heilongjiang Province

In today’s energy industry, the development of clean energy has become a global concern. As an important clean energy technology, photovoltaic power generation (PV) is widely used in various countries and regions, helping to reduce the dependence on traditional fossil energy sources and to reduce greenhouse gas emissions. Existing studies have some shortcomings in terms of factors affecting distributed PV grid-connected capacity. First, previous studies tend to focus on the influence of a single factor on the grid-connected capacity of distributed PV, ignoring the interaction effects among multiple factors. Second, the sample scope in existing studies is relatively narrow, often limited to specific regions or countries, and lacks comprehensive regional comparative analysis. In addition, previous studies often do not fully consider the moderating effect of carbon emission intensity on the influencing factors. Based on the above deficiencies, this study aims to build a regression model by analyzing panel data of central municipalities and provinces including Heilongjiang, Shandong and Beijing over the past three years, and construct an interaction model based on the interaction term. The empirical results show that effective sunshine hours, average feed-in tariff and annual electricity consumption are the main factors affecting the grid-connected capacity of distributed PV with a positive effect. The regional heterogeneity analysis also finds that carbon emission intensity enhances the impact of each factor on distributed PV grid-connected capacity. The regulation effect analysis confirms that the average feed-in tariff and annual electricity consumption have a regulation effect. With the results of this study, we fill the knowledge gaps left by previous studies and provide a new perspective to explore the influencing factors of distributed PV. A deeper understanding of the impact of these factors on distributed PV capacity helps us to better understand and optimize the potential of PV generation. In addition, our findings provide policy makers with recommendations and guidance on how to promote distributed PV generation, thereby contributing to the sustainable development of the clean energy sector.

A scientometric review of knowledge domains on nuclear radiation

Nuclear energy is an important energy component to achieve the goal of “carbon peak and carbon neutrality”. Nuclear radiation is one of the hot spots in the development and utilization of nuclear energy. This study used bibliometric methods to gain a preliminary understanding of the knowledge system in the field of nuclear radiation and explored the network relationships of cooperation in the field of nuclear radiation. The literature data for the study were obtained from the Web of Science core collection database. All literature from 2008 to 2023 was downloaded, totalling 1602 articles. VOSviewer and CiteSpace were used to analyze several aspects such as article volume, keyword clustering and collaborative network relationships. The research showed that the years 2011–2014 and 2017–2020 were periods of vigorous literature development, with a sharp increase in the number of literature. In the collaborative network, the author collaborative network was divided into five different clusters, mainly dominated by Tsubokura, Masaharu and Yasumura, Seijiz. Research and development in various countries were uneven, and cooperation between underdeveloped national institutions in this field was even more limited. In the keyword clustering, five cluster models have been established, including the investigation and related treatment of nuclear radiation hazards, the Fukushima nuclear accident in Japan, research on nuclear radiation products, optical properties of nuclear radiation, and research on shielding materials. Recently, radiation shielding materials, photons and neutrons have become research hotspots. Through this study, we can gain a deeper understanding of the development status, cooperation networks, and cutting-edge research information in the nuclear field, which can serve as a reference for researchers.

Strategies for the Preparation of Single-Atom Catalysts Using Low-Dimensional Metal-Organic Frameworks.

As single-atom catalysts are important energy materials, their preparation and synthesis methods have become particularly important. The unique structures of low-dimensional metal-organic frameworks and their derivatives provide various strategies for preparing single-atom catalysts. This paper summarizes various strategies for the preparation of single-atom catalysts based on low-dimensional metal-organic frameworks and their derivatives.

An Assessment Methodology for International Hydrogen Competitiveness: Seven Case Studies Compared

Currently, the global energy structure is undergoing a transition from fossil fuels to renewable energy sources, with the hydrogen economy playing a pivotal role. Hydrogen is not only an important energy carrier needed to achieve the global goal of energy conservation and emission reduction, it represents a key object of the future international energy trade. As hydrogen trade expands, nations are increasingly allocating resources to enhance the international competitiveness of their respective hydrogen industries. This paper introduces an index that can be used to evaluate international hydrogen competitiveness and elucidate the most competitive countries in the hydrogen trade. To calculate the competitiveness scores of seven major prospective hydrogen market participants, we employed the entropy weight method. This method considers five essential factors: potential resources, economic and financial base, infrastructure, government support and institutional environment, and technological feasibility. The results indicate that the USA and Australia exhibit the highest composite indices. These findings can serve as a guide for countries in formulating suitable policies and strategies to bolster the development and international competitiveness of their respective hydrogen industries.

A Cu/MnOx Composite with Copper-Doping-Induced Oxygen Vacancies as a Cathode for Aqueous Zinc-Ion Batteries.

Aqueous zinc-ion batteries are anticipated to be the next generation of important energy storage devices to replace lithium-ion batteries due to the ongoing use of lithium resources and the safety hazards associated with organic electrolytes in lithium-ion batteries. Manganese-based compounds, including MnOx materials, have prominent places among the many zinc-ion battery cathode materials. Additionally, Cu doping can cause the creation of an oxygen vacancy, which increases the material's internal electric field and enhances cycle stability. MnOx also has great cyclic stability and promotes ion transport. At a current density of 0.2 A g-1, the Cu/MnOx nanocomposite obtained a high specific capacitance of 304.4 mAh g-1. In addition, Cu/MnOx nanocomposites showed A high specific capacity of 198.9 mAh g-1 after 1000 cycles at a current density of 0.5 A g-1. Therefore, Cu/MnOx nanocomposites are expected to be a strong contender for the next generation of zinc-ion battery cathode materials in high energy density storage systems.

High vs. low glycaemic index pre-exercise feeding

Carbohydrates are proven to be the most important energy source to skeletal muscle during endurance exercise. However, the glucose that carbohydrates provide the muscle with can differ in how quickly they are digested and released into the bloodstream. High glycaemic index (GI) carbohydrates are released into the bloodstream in a rapid burst following digestion whereas low GI carbohydrates are released into the bloodstream at a constant rate after consumption. The effects of low and high GI carbohydrate consumption pre-exercise on endurance exercise performance are not comprehensively understood. Therefore, the aim of this study is to identify the impact of low vs high GI pre-exercise feeding on maximal effort endurance exercise performance. With institutional ethics approval, twelve physically active, healthy males aged 18-40 years attended the laboratory on four separate occasions. On the first occasion, participants underwent a V̇O2max test to identify their maximal aerobic capacity. The final three lab visits consisted of the participants undergoing trials under three differing conditions upon arrival in the fasted state (participants were instructed to not consume food or drink other than water 6 h before arrival). The trial entailed of 20 km cycling followed by 5 km running with 2 min rest in between. Upon arrival, the participants received a carbohydrate beverage, either 40 g high GI, 40 g low GI, or a placebo, 15 min before exercising. Before consumption of the beverage, before the onset of exercise, after each 5 km during the cycle and following the run, heart rate and RPE were recorded, and a finger prick blood sample was taken to analyse for blood glucose and blood lactate concentrations throughout the exercise bout. However, the primary performance indicator was the overall time to complete the trial (bike and run minus 2 min rest). The final order of mean completion time across conditions from fastest to slowest went low GI, high GI, placebo. There was no significant difference between the mean time to completion in the low GI and high GI conditions. However, the low GI condition resulted in a faster time to completion than the placebo condition (P = 0.02) as well as the high GI condition resulting in a faster time to completion than the placebo condition (P = 0.043). Therefore, this could demonstrate that the presence of any carbohydrate type is more influential on endurance exercise performance rather than the glycaemic index of such carbohydrates.

Targeting pyruvate kinase M2 for the treatment of kidney disease.

Pyruvate kinase M2 (PKM2), a rate limiting enzyme in glycolysis, is a cellular regulator that has received extensive attention and regards as a metabolic regulator of cellular metabolism and energy. Kidney is a highly metabolically active organ, and glycolysis is the important energy resource for kidney. The accumulated evidences indicates that the enzymatic activity of PKM2 is disturbed in kidney disease progression and treatment, especially diabetic kidney disease and acute kidney injury. Modulating PKM2 post-translational modification determines its enzymatic activity and nuclear translocation that serves as an important interventional approach to regulate PKM2. Emerging evidences show that PKM2 and its post-translational modification participate in kidney disease progression and treatment through modulating metabolism regulation, podocyte injury, fibroblast activation and proliferation, macrophage polarization, and T cell regulation. Interestingly, PKM2 activators (TEPP-46, DASA-58, mitapivat, and TP-1454) and PKM2 inhibitors (shikonin, alkannin, compound 3k and compound 3h) have exhibited potential therapeutic property in kidney disease, which indicates the pleiotropic effects of PKM2 in kidney. In the future, the deep investigation of PKM2 pleiotropic effects in kidney is urgently needed to determine the therapeutic effect of PKM2 activator/inhibitor to benefit patients. The information in this review highlights that PKM2 functions as a potential biomarker and therapeutic target for kidney diseases.

Dynamic interactions among new energy metals and price adjustment strategies: A cross-industry chain perspective

Lithium, Cobalt, Nickel are the most important new energy metals for energy transition. Their rapid increasing demand drives significant prices fluctuations, often causing simultaneous extensive price spikes in several products among their industry chains, reflecting their interaction nature. This paper first reconstructs products price interaction network among the Lithium–Cobalt–Nickel cross-industry chains to analyze their dynamic interactions. By applying network structural control theory, we then simulate three price reduction scenarios under high price volatility. Product price adjustment difficulties are quantified and distinct adjustment patterns are identified. Our results demonstrate substantial intra-chain and cross-chain dynamic interactions among products, particularly within the nickel chain. Products like the midstream product electrolytic nickel, downstream products Nickel Plate and Nickel exhibit intense interactions with others. Adjusting the prices of 17 key products proves effective in stabilizing the entire system. Electrolytic cobalt and lithium cobaltate always require significant adjustment efforts for most products during high-levels, expect for the nickel ore and some products in lithium chain where they are not critical. Lithium cobaltate always follows a U-shape adjustment pattern, while electrolytic cobalt follows a ∩-shape pattern. When the entire nickel industry chain experiences sharp price increases, the largest adjustment efforts are required to turn down prices.

ABHD5 regulates midgut-specific lipid homeostasis in Bombyx mori.

Lipids are an important energy source and are utilized as substrates for various physiological processes in insects. Comparative gene identification58 (CGI-58), also known as α/β hydrolase domain-containing5 (ABHD5), is a highly conserved and multifunctional gene involved in regulating lipid metabolism and cellular energy balance in many organisms. However, the biological functions of ABHD5 in insects are poorly understood. In the current study, we describe the identification and characterization of the ABHD5 gene in the lepidopteran model insect, Bombyx mori. The tissue expression profile investigated using quantitative reverse transcription polymerase chain reaction (RT-qPCR) reveals that BmABHD5 is widely expressed in all tissues, with particularly high levels found in the midgut and testis. A binary transgenic CRISPR/Cas9 system was employed to conduct a functional analysis of BmABHD5, with the mutation of BmABHD5 leading to the dysregulation of lipid metabolism and excessive lipid accumulation in the larval midgut. Histological and physiological analysis further reveals a significant accumulation of lipid droplets in the midgut of mutant larvae. RNA-seq and RT-qPCR analysis showed that genes related to metabolic pathways were significantly affected by the absence of BmABHD5. Altogether, our data prove that BmABHD5 plays an important role in regulating tissue-specific lipid metabolism in the silkworm midgut.

A novel seasonal grey prediction model with time-lag and interactive effects for forecasting the photovoltaic power generation

Electricity is one of the most important energy sources for the progress of human society. Photovoltaic power generation (PPG) has great potential as a renewable energy source to support sustainable development. However, the unpredictability of photovoltaics because of the uncertain weather conditions, time lags and the complex interactions among related factors may result in instabilities in PPG, which limits its applications in the electric power system. Therefore, accurately identifying the related factors and representing the interactions are the key issues in predicting PPG. For this purpose, a novel seasonal grey prediction model with time-lag and interactive effects, denoted as SGMLI(1,n), is developed to predict the capacity of photovoltaic power generation. More specifically, a time-lag driving term, a periodic driving term, and an interaction driving term are proposed to represent the lag relationship, periodicity, and the interactive effects between two factors, respectively. Utilizing the least square method and the Whale Optimization Algorithm (WOA), the optimal solution to the nonlinear programming problem is estimated. For elaboration and verification, six grey forecasting models, two statistical techniques, and two machine learning models, are employed for comparison with the SGMLI(1,n) model. Experimental results reveal that the SGMLI(1,n) outperforms benchmark models in forecasting PPG.

Multiscale-simulation method for the wear behaviour of planetary journal bearings in wind turbine gearboxes

Wind energy is one of the most important renewable energy sources. To maintain competitiveness wind energy needs to be cost effective. Increasing the performance of wind turbines can help to reduce the total cost of wind energy. The power output can be increased by an increase in turbine rotor size since the power increases disproportionately with the rotor diameter. The increase in rotor size inherently comes with an increase in overall wind turbine size to cope with the increasing loads. Since the nacelle weight cannot be increased without limitation, e.g. due to the effect on the tower and costs, an increase in power density is necessary. The usage of journal bearings instead of rolling bearings for the application in planetary gearboxes in wind turbines is one way to increase the power density and reliability of the drivetrain. When designed and operated correctly, journal bearings have a longer service lifetime than rolling bearings. Wear simulations aid in the design of journal bearings. This work presents a simulation method for the wear prediction of planetary journal bearings in wind turbine gearboxes. The method is validated with measurements on a component test rig. The transfer to the wind turbine gearbox is shown by means of simulation.

Hydrogen production from chemical hydrogen storage materials over copper‐based catalysts

AbstractHydrogen, as a clean and efficient energy source, is one of the important energy carriers in the future. However, the safe storage and delivery of hydrogen is still a bottleneck in its practical applications. Chemical hydrides (such as NaBH4, NH3BH3, N2H4·H2O, N2H4BH3, and HCOOH) are considered as potential chemical hydrogen storage materials that can achieve rapid on‐site hydrogen production. At present, the most critical issue for them is to develop economic catalysts to achieve efficient hydrogen production from chemical hydrides. Copper (Cu) is considered as a promising catalyst that is one of the most reactive metals among the first‐row transition metals and economically cheap. In this review, we outline the recent advancements of Cu‐based catalysts in catalyzing hydrogen production from chemical hydrides. Moreover, the synthesis methods, characterization techniques, and hydrogen production catalytic activity of Cu‐based catalysts were also introduced. Finally, a brief conclusion and outlook are given for the application of Cu‐based catalysts in the dehydrogenation of chemical hydrides. We hope that this review will stimulate interest in the promising research area of Cu‐based catalysts for the dehydrogenation of chemical hydrides.

Equitable charging infrastructure for electric vehicles: access and experience

The shift toward electric vehicles (EVs) as a decarbonisation strategy in transportation raises important energy justice concerns, particularly regarding fair access to charging infrastructure. This perspective synthesizes evidence on how access to, and experience of, charging infrastructure may differ across socio-economic groups across North America. We present a framework for assessing charging infrastructure equity that includes: (i) accessibility—proximity, reliability, visibility, affordability; and (ii) user experiences—safety, payment ease, and co-located other services. The framework helps characterize the varied impacts across socio-demographic groups, including on low-income and marginalized communities. We explore how the direct and indirect effects of accessibility and user experience might influence the distribution and design of EV charging stations. Considerations of socio-economic diversity in the deployment of charging infrastructure are critical to ensure equitable benefits from electric mobility. We conclude that targeted actions from manufacturers, charging operators, and governments are needed to alleviate the disparities in access and experiences with public EV charging.

Describing the microwave heating performances of the main constitutes of biomass

Biomass is abundant, environmentally friendly, and an important renewable energy source, and it is mainly composed of cellulose, hemicellulose, and lignin. The microwave heating performances of the main constitutes of biomass is fundamental for the further applications of microwave-assisted technologies, i.e., pyrolysis, gasification, etc. In this study, the effects of reactor volume (50, 150, and 250 mL), material mass (5, 10, and 15 g), and microwave power (450, 550, and 650 W) on the microwave heating performances of biomass main constitutes (cellulose, hemicellulose, and lignin) were investigated. For cellulose, hemicellulose, and lignin, the average heating rates varied in the ranges of 1.14–10.50, 1.00–4.03, and 0.44–14.34 oC/s, respectively. Relationships with R2 values of 0.945–1.000 were proposed for forecasting and regulating the real-time temperatures of biomass main constitutes during the heating process.