Energy-intensive Research Articles

Intensification of the Dimethyl Sulfide Precursor Conversion Reaction: A Retrospective Analysis of Pilot-Scale Brewer’s Wort Boiling Experiments Using Hydrodynamic Cavitation

Dimethyl sulfide (DMS), a low-boiling compound generated during barley germination and wort boiling from the conversion of its main precursor S-methylmethionine (SMM), a functional biomolecule, is detrimental to beer flavor. Vigorous and prolonged boiling, a time-consuming and energy-intensive process, is required to decrease the content of SMM and remove free DMS. The standard model, further validated in this study, assumed wort temperature and pH as the limiting factors of the SMM conversion reaction. This study aimed to assess the specific effect of hydrodynamic cavitation (HC) on the SMM conversion rate in pilot-scale experiments of brewer’s wort boiling. For the first time, the SMM conversion rate was shown to be significantly affected by HC processes. The SMM half-life was reduced by up to 70% and showed remarkable sensitivity to HC regimes. The intensification of the SMM conversion reaction could be attributed to the HC-based generation of hydroxyl radicals. Other wort processes unfolded in compliance with standard specifications, such as the removal of free DMS, the isomerization of hop alpha-acids, and the change in wort color. In conclusion, evidence supported HC for a substantial saving in process time and energy consumption in the brewer’s wort boiling step.

Solar Stirling for Renewable Energy Multigeneration Systems

This study explores the feasibility and potential of integrating dish–Stirling systems (DSSs) into multigeneration energy systems, focusing on their ability to produce both thermal and electrical energy. By leveraging the concentrated solar power capabilities of DSSs, this research examines their performance relative to alternative solutions such as photovoltaic (PV) systems and solar heating. A 25 kW Stirling Energy Systems (SES) DSS served as the basis for the analysis. Simulations were performed for local 2022 weather conditions in Germany. The study employed a detailed modeling approach using the NREL System Advisor Model (SAM) to quantify the energy outputs and evaluate the system efficiencies. The results indicate that the DSS achieved an electrical efficiency of 25% and a combined efficiency of 78% when accounting for the maximum thermal energy generated. Seasonal analysis highlights the adaptability to fluctuating energy demands, with advantages in winter heating applications. Comparative evaluations revealed DSSs as a viable cogeneration alternative to standalone PV systems and solar heaters, offering reduced environmental impacts and enhanced energy efficiency. Future work will address real-world operational conditions, including thermal storage and multigeneration integration, positioning the DSS as a sustainable solution for renewable energy generation.

Numerical investigation of indirect parallel PVT solar systems using MATLAB/simulink

Abstract In this paper, an original numerical investigation of indirect parallel photovoltaic/thermal system integration using Matlab/Simulink is carried out. The added value is to evaluate the potential use of integrated PVT (Photovoltaic-Thermal) solar systems in residential applications and the possibility of controlling and investigating their performance to optimize the results under weather conditions throughout the year. A substantial number of annual simulations have been conducted to encompass the best performance using each control, with an emphasis on two configurations of cooling approaches. Results show that an optimal mass flow rate of about 0.0125 kg/s for both collector and storage tank pumps was found. For the direct cooling method, results reveal an increase in overall system efficiency of the order of 41.4%. In addition, the paper compares the PVT system with a stand-alone PVT collector, and the results indicate that integrated PVT leads to a relative improvement in electrical and thermal efficiency of about 7.89% and 24.62%, respectively.

Blockchain-Enhanced Demand-Side Management for Improved Energy Efficiency and Decentralized Control

Blockchain technology introduces significant advancements in demand-side management (DSM) by enabling decentralized, transparent, and secure data handling within energy systems. This study explores a blockchain-based approach aimed at improving electricity efficiency through enhanced DSM strategies. We present a comprehensive framework that integrates blockchain technology with real-time data analytics to optimize energy consumption, stimulate consumer participation, and support efficient energy utilization. The experimental analysis demonstrates that blockchain integration significantly strengthens DSM operations by reducing operational costs, increasing participation in demand response programs, and enhancing grid stability. The findings highlight the effectiveness and potential of the proposed approach as a forward-looking solution for energy management systems.

Hybrid LSTM-PSO optimization techniques for enhancing wind power bidding efficiency in electricity markets

Hybrid LSTM-PSO optimization techniques for enhancing wind power bidding efficiency in electricity markets

Environmental Assessment and Eco-Efficiency Analysis of the Dividing Wall Distillation Column for Separating a Benzene–Toluene–Xylene Mixture

The benzene–toluene–xylene (BTX) system represents an energy-intensive petrochemical process with various industrial applications. Global climate changes have forced modern industry to act toward environmental safety, which requires technological changes. Thus, the divided wall column (DWC) represents a significant advancement in multicomponent mixture separation. To assess the impact of the conventional BTX process and its intensification proposal based on DWC technology, it is necessary to integrate an eco-efficiency approach that jointly analyzes the economic and environmental variables influencing the system, such as water consumption, CO2 emissions, and utility costs. An auxiliary utility plant was also considered for more realistic results in terms of energy and water consumption, which was identified as a lack in many research studies that performed an overall sustainability analysis. The results showed that the DWC scheme is 37.5% more eco-efficient than the conventional counterpart, mainly due to a 15.6% and 30.3% savings on energy and water consumption, respectively, which provided a 15.5% and 16.7% reduction on CO2 emissions and utility costs, respectively. In addition, all other environmental and safety indicators based on the waste algorithm reduction (WAR) were reduced by approximately 16%. Thus, the DWC proved to be a convenient technology with economic attractiveness and environmental friendliness.

Optimal turning of a 2-DOF proportional-integral-derivative controller based on a chess algorithm for load frequency control

Load frequency control is necessary for power system management. The power system must maintain a frequency range to ensure power supply stability. System faults and demand fluctuations may cause frequencies to change quickly. System stability and integrity suffer. We are optimizing the two-degree-of-freedom (2-DOF) proportional-integral-derivative (PID) controllers chess algorithm. This article addresses electrical load frequency regulation. We employ classical control theory and current adjustment. It aims for electrical system efficiency and dependability. It checks for errors using integral absolute error (IAE), integral squared error (ISE), integral of time multiply absolute error (ITAE), and integral time squared error (ITSE). Particle swarm algorithm (PSO) compares performance. The IAE of 0.03364, nearly identical to it, shows that chess trumps other algorithms in many scenarios. The chess algorithm's ISE was 0.00035, like PSO's 0.03363. The ISE was 0.00036, indicating PSO's error-reduction capabilities. For the chess algorithm, PSO is 0.07929, and ITAE is 0.07647. This indicates the PSO responds faster to system breakdowns and load changes. Finally, the chess algorithm's ITSE is 0.00072, below the PSO 0.00076. The chess algorithm is better at managing long-term load frequency.

Life cycle assessment of anaerobic digestion coupled co-pyrolysis for treatment of food waste.

In this study, the environmental impact of anaerobic digestion (AD) coupled co-pyrolysis (PY) to dispose of food waste (FW) was assessed. Four cases (mono AD, mono PY, AD coupled PY and AD coupled co-PY) were analyzed in comparison by life cycle assessment. The results showed that coupling technology was an environmentally viable technology compared with mono AD or PY. Among them, AD coupled co-PY presented the best environmental benefit (-0.0038Pt of total environmental impact potential /t FW), and provided a potential way to treat waste plastics and digestate. Moreover, the optimization of AD technology will enhance the total environmental benefits, while the control of emission at the energy recovery stage and the improvement of electricity efficiency are crucial for sustainability. This study provides potential approaches and environmental support for the treatment of FW.

Developing Cost-Effective AI Algorithms for Resource-Constrained Devices

Resource-restrained gadgets pose sizable challenges for deploying synthetic intelligence (AI) packages, which include restricted computational power, reminiscence, and electricity resources. This research pursuits to broaden value-effective AI algorithms that cope with these limitations whilst retaining high overall performance and accuracy. The examine leverages superior optimization strategies, such as version pruning, quantization, and dynamic strength control, to layout light-weight models appropriate for low-strength environments. Experiments conducted on gadgets like the Raspberry Pi 4 and NVIDIA Jetson Nano screen giant improvements in inference time, electricity efficiency, and accuracy compared to conventional processes. The proposed algorithms acquire up to 50% reduction in energy consumption and 20% improvement in accuracy at the same time as lowering typical computational charges. These findings reveal the feasibility of deploying green AI solutions on constrained hardware without compromising on functionality or nice. The practical implications of this paintings make bigger to various applications, along with real-time healthcare monitoring, clever agriculture, and commercial IoT systems. The have a look at concludes by means of highlighting areas for destiny studies, which includes improving algorithmic adaptability and expanding trying out to embody diverse eventualities. This work gives a sturdy basis for advancing the deployment of AI in resource-restricted settings, bridging the gap between technological innovation and practical implementation.

Analysis of Energy Use and Environmental Impacts of Pistachio (Pistacia vera L.) in Conventional and Bio-friendly Production Systems

Humankind and natural ecosystems are facing global changes. There is a clear influence of human activities due to the use of contaminant energies among other factors. Therefore, it is a priority to find clean energies with less environmental impacts coming from bio-friendly production systems. Therefore, the main aim of this research is to examine energy use patterns, greenhouse gas emission (CO2, N2O, and CH4) and life cycle assessment (LCA) in pistachio (Pistacia vera L.) production systems. As experimental plots, we selected one plantation located in the North Khorasan province of Iran. Data were collected from two pistachio orchards with conventional (CPS) and with bio-friendly production systems (BPS). In 2 seasonal years, from 2020 to 2021, a functional unit of 1000 kg pistachio was used. The results indicated that total energy consumption in the conventional pistachio production system reached 58,759.86 MJ ha−1 in comparison to bio-friendly pistachio production systems with 31,149.02 MJ ha−1, accounting for 36.0% of fertilizer energy, 26% of diesel energy, and 12.7% of electricity. The energy use efficiency for the CPS and BPS was respectively 0.38 and 0.73, and also energy productivity for CPS reached 0.01 kg MJ ha−1 and BPS 0.02 kg MJ ha−1. Results indicated that the direct energy for CPS was 19.6% and for BPS 39.03%, but indirect energy inputs for CPS and BPS registered 76.4 and 60.5%, respectively. It was found that the non-renewable form of energy input for CPS was 83.8% and for BPS just 57.6%. We conclude that chemicals (pesticides, fertilizers), fuel and electricity were the most important inputs for the pistachio production system, which also influenced total CO2, N2O and CH4 emissions due to chemical inputs for CPS. In CPS and BPS, the total global warming potential (GWP) was 2445.24 and 1507.99 kg CO2eq ha−1, respectively. Compared to CPS, the application of the BPS method reduces total damage to human health, ecosystems, and resources.

Comparing Nerve Versus Muscle Wide-Pulse High-Frequency Electrical Stimulation for Maximal and Submaximal Efforts.

The effectiveness of neuromuscular electrical stimulation hinges on the evoked torque level, which can be attained through either conventional (CONV) or wide-pulse high frequency (WPHF). However, the best electrode placement is still unclear. This study adopted a crossover design to compare the effects of WPHF applied to the tibial nerve trunk (N-WPHF) or muscle (M-WPHF) with CONV in healthy participants. A total of 30 participants (age: 22.4 [4.5]) were involved in 4 sessions. During each session, participants performed: 2 maximal voluntary contractions, 2 contractions at maximal evoked torque, and 2 contractions at submaximal evoked torque at 20% maximal voluntary contraction. Neuromuscular electrical stimulation intensity-evoked torque, efficiency, and discomfort were measured in maximal and submaximal conditions. Statistical analyses were conducted using a 1-way mixed-model analysis of variance with repeated measures. N-WPHF and M-WPHF showed higher evoked torque than CONV (P = .002 and P = .036) and greater efficiency than CONV for maximal evoked torque (P = .006 and P = .002). N-WPHF induced higher efficiency than M-WPHF and CONV for submaximal evoked torque (P = .004). Higher discomfort was observed for both N-WPHF and M-WPHF for submaximal evoked torque compared with CONV (P = .003 and P < .001). Our results suggest that WPHF applied at either the nerve or muscle could be the best choice for the maximal condition, whereas nerve application is preferred for the submaximal condition.

A Simple Micro/Nano‐Porous Structure With Day‐Night Dynamic Thermal Control and High Thermal Conductivity for Enhanced Thermoelectric Power Generation

AbstractThe main challenge of an all‐weather power generation system that combines radiative cooling and thermoelectricity is to dynamically regulate the temperature sources at both ends of the thermoelectric device. Previous studies have used stacked and flipped structures, thermochromic materials, and other methods. However, the above methods have complex structures, low thermal conductivity efficiency, and difficult‐to‐prepare materials. Therefore, in this paper, a porous structure of carbon nanomaterials with simple preparation, dynamically adjustable heat source during day and night, and high thermal conductivity in combination with thermoelectric devices with ultra‐high electrical efficiency is proposed. The structure has a solar spectrum absorption of 98.6%. Graphene film is used as a substrate material to enhance the longitudinal thermal conductivity. Experiments showed that the maximum voltage during day and night can reach 847 and 106 mV, the maximum temperature difference is 12.63 and 1.42 °C, and the maximum power density is 2112.96 mW m−2 when combined with thermoelectric devices. Simulation models are used to analyze the environmental sensitivity of power generation units and to predict their power generation potential. This work provides superior photothermal/radiative cooling structures combined with thermoelectric elements for efficient all‐weather energy conversion and power output.

Efficient Recycling Processes for Lithium-Ion Batteries

Lithium-ion batteries (LIBs) are an indispensable power source for electric vehicles, portable electronics, and renewable energy storage systems due to their high energy density and long cycle life. However, the exponential growth in production and usage has necessitated highly effective recycling of end-of-life LIBs to recover valuable resources and minimize the environmental impact. Pyrometallurgical and hydrometallurgical processes are the most common recycling methods but pose considerable difficulties. The energy-intensive pyrometallurgical recycling process results in the loss of critical materials such as lithium and suffers from substantial emissions and high costs. Solvent extraction, a hydrometallurgical method, offers energy-efficient recovery for lithium, cobalt, and nickel but requires hazardous chemicals and careful waste management. Direct recycling is an alternative to traditional methods as it preserves the cathode active material (CAM) structure for quicker and cheaper regeneration. It also offers environmental advantages of lower energy intensity and chemical use. Hybrid pathways, combining hydrometallurgical and direct recycling methods, provide a cost-effective, scalable solution for LIB recycling, maximizing material recovery with minimal waste and environmental risk. The success of recycling methods depends on factors such as battery chemistry, the scalability of recovery processes, and the cost-effectiveness of waste material recovery. Though pyrometallurgical and hydrometallurgical processes have secured their position in LIB recycling, research is proceeding toward newer approaches, such as direct and hybrid methods. These alternatives are more efficient both environmentally and in terms of cost with a broader perspective into the future. In this review, we describe the current state of direct recycling as an alternative to traditional pyrometallurgical and hydrometallurgical methods for recuperating these critical materials, particularly lithium. We also highlight some significant advancements that make these objectives possible. As research progresses, direct recycling and its variations hold great potential to reshape the way LIBs are recycled, providing a sustainable pathway for battery material recovery and reuse.

Calculation and structural analysis of total factor energy efficiency in high carbon sectors

High carbon sectors (agriculture, industry, construction, and transportation) contribute nearly 85% of carbon emissions, highlighting the urgent need for transitioning towards cleaner energy structures in these sectors. This study utilizes the undesirable SBM model to assess TFEE (total factor energy efficiency) across the total sector and high carbon sectors. It decomposes TFEE from an energy structural perspective into coal, oil, natural gas, and electric heat efficiencies. Using a variance-like decomposition model, it analyzes TFEE at two levels to examine how changes in specific sectors and energy categories affect total sector TFEE. From 2010 to 2021, China’s total sector TFEE increased from 0.542 to 0.676, with electric heat and coal identified as critical factors limiting TFEE improvements. Among the four high carbon sectors, construction exhibited a significant increase in TFEE, agriculture showed a steep rise, the industry demonstrated a U-shaped trend with a turning point in 2015, and transportation experienced a slight decline. TFEE exhibits a descending order among sectors, with agriculture ranking highest, followed by construction, industry, and transportation. Similarly, the total factor efficiencies of energy types show a hierarchical structure, with oil being the most efficient, followed by electric heat, natural gas, and coal. Construction dominates TFEE changes at the sectoral level, contributing 58.87%, while coal contributes over 30% at the energy category level. The decomposition results for each province further indicate that both sectoral structure and energy structure significantly impact the changes in TFEE, and this influence also exhibits regional heterogeneity.

Optimized Enzymatic Extraction of Phenolic Compounds from Verbascum nigrum L.: A Sustainable Approach for Enhanced Extraction of Bioactive Compounds

Verbascum nigrum, commonly known as black mullein, is widely used in traditional medicine for its expectorant, mucolytic, sedative, and diuretic properties. This study aimed to develop and optimize a standardized method for extracting phenolic compounds from V. nigrum using enzymatic pretreatment followed by solvent extraction. Enzymatic treatment does not rely on harmful solvents and is a low energy-intensive process, making it a suitable green technology for the food, cosmetic, and pharmaceutical industries. The research explored the use of different lignocellulolytic enzymes, including pectinase, cellulase, α-amylase, and xylanase, to break down plant cell walls, enhancing the release and bioaccessibility of active compounds. The two-step extraction process proposed combined enzymatic pretreatment and hydroalcoholic extraction, resulting in a considerably improved yield of phenolic compounds (24 mg/g DM). Analytical characterization using a high-performance liquid chromatography (HPLC) system coupled with a diode-array-detector (DAD) and ultra-high-performance liquid chromatography (UHPLC) coupled with DAD and tandem mass spectrometry (MS/MS) revealed a higher concentration of target bioactive compounds in enzymatically treated extracts compared to traditional methods, including phenolic derivatives (e.g., caffeic acid, p-coumaric acid, and verbascoside), and flavonoids (e.g., luteolin). Up to 22 phenolic and flavonoid compounds were characterized. This study provides new insight into the potential of enzymatic extraction as a green and efficient alternative to conventional extraction methods, for the production of high-quality herbal products richer in (poly)phenolic compounds, highlighting its potential for industrial applications.

Numerical studies of the efficiency of binary geothermal power plants at the studied thermal fields of Russia

Relevance. The necessity to develop the technologies in Russia that use non-traditional energy sources. The formation of these technologies will allow providing energy resources to the population without harmful emissions into the environment. Aim. Comprehensive analysis of the operating characteristics of a binary geothermal power plants in various climatic operating conditions. Objects. Thermal diagrams of binary geothermal power plants applicable to installation in different geographic regions and operation from different geothermal sources. Methods. Numerical studies based on mathematical algorithms of binary geothermal plant systems, comparative analysis of the efficiency of binary geothermal plants based on various external parameters. Results and conclusions. Numerical studies have been conducted to determine the efficiency of geothermal power plants with a binary thermal circuit and an air-cooled condenser were conducted during their operation on various sources, for which 15 known geothermal sources located in Russia in different geographical regions were selected. Possible operating parameters of binary geothermal power plants were analyzed based on the known characteristics of the fluid at the well outlet. Since the geothermal power plant has an air-cooled condenser in its thermal circuit, its operating parameters were obtained from the average monthly ambient air temperatures in the calendar year in the region where the analyzed geothermal source is located. Numerical studies showed the impact of thermal source parameters and climatic features on the efficiency of electric energy generation by means of a binary plant. It was revealed that with the possible operation of a binary geothermal plant during a calendar year, the highest average monthly electric power is expectedly achieved in the cold period of time, in this case in January, and is 1752 kW for the Mogoysky hot spring. For the warmest month of the year – July – the binary power plant of the Mechigmen hot spring could have the greatest electric power of 930 kW. The greatest absolute electric efficiency in January reaches 15.22%, depends to a greater extent on the value of the temperature of the heat supply in the cycle and among the binary stations considered in this work, the geothermal power plants in the settlement of Chazhemto could have it.

Electricity Consumption and Efficiency Measures in Public Buildings: A Comprehensive Review

Industrialization and the expansion of service sectors have led to a significant increase in electricity consumption. This rising demand has also been observed in public buildings, which account for a considerable share of total electrical energy use. Coupled with the upward trend in energy prices, this increase has likewise escalated electricity costs in these sectors. The objective of this review is to compile studies that analyze electricity consumption in large public buildings, with a primary focus on universities, as well as works that propose or implement energy-saving measures aimed at reducing consumption. Throughout this review, it is observed that effective monitoring of consumption as well as the use of demand management systems can reduce electricity consumption by up to 15%. Additionally, the studies collected consistently highlight the need for improvements in real-time data monitoring to enhance energy management. Buildings that implement energy-saving measures achieve reductions in demand exceeding 10%, while those incorporating renewable energy systems are capable of covering between 40% and 50% of their energy needs. Of these systems, solar photovoltaic technology is that most widely adopted by public buildings, primarily due to its adaptability to the architectural characteristics and operational requirements of such facilities. This review underscores the substantial impact that optimized monitoring and renewable energy integration can have on reducing the energy footprint of large public facilities.

The scoping, design, and plasma physics optimization of the Eos neutron source stellarator

Abstract On the path to a fusion pilot plant, Thea Energy plans to build Eos, a sub-breakeven, deuterium-deuterium, beam-target fusion, stellarator neutron source facility for producing tritium and other valuable radioisotopes. In this paper, a set of 1D plasma physics models are coupled and used to design the operating point of the facility and predict performance. At this foundational stage of the design, analytic and approximate models are sufficient to capture the leading-order effects, and fast enough to run in the inner loop of an optimizer. Higher-fidelity analyses will follow. Models of 1D profile-dependent neutral beam stopping, ion beam slowing down, beam-target fusion, electron-ion classical heat transfer, energy confinement (ISS04), beam pressure, beam heating of ions and electrons, beam-beam fusion fraction, and neutral beam injection and gyrotron heating electrical efficiencies are included. A numerical optimizer is used to determine the minimum required facility electric power to generate tritium at a given rate. A potentially advantageous regime is described in which modern precisely-quasisymmetric stellarators, new high-temperature superconductors, ITER-derived neutral beam injection, and new high-frequency gyrotrons enable a suitible target plasma with hot electrons, cold ions, peaked density and temperature profiles, and high beam-injected ion density. It appears possible at this time for a facility with a medium-scale and medium-strength stellarator whose required facility electric power is less than 40 MW to produce 2.5 × 10 17 neutrons s−1 for the production of radioisotopes. With the addition of a tritium breeding blanket, such a facility could produce 0.2 grams d−1 or 70 grams yr−1 of tritium.

Tailoring molecular diffusion in core-shell zeolite imidazolate framework composites realizes efficient kinetic separation of xylene isomers.

The separation of xylene isomers is a critical and energy-intensive process in the petrochemical industry, primarily due to their closely similar molecular structures and boiling points. In this work, we report the synthesis and application of a novel core-shell zeolitic imidazolate framework (ZIF) composite, ZIF-65@ZIF-67, designed to significantly enhance the kinetic separation of xylene isomers through a synergistic "shell-gated diffusion and core-facilitated transport" strategy. The external ZIF-67 shell selectively restricts the diffusion of larger isomers (MX and OX), while the internal ZIF-65 core accelerates the diffusion of PX, thereby amplifying the diffusion differences among the isomers. This architecture yields remarkable improvements in both selectivity and diffusion rates, as demonstrated by vapor-phase adsorption studies and molecular dynamics simulations. The ZIF-65@ZIF-67 composite exhibits up to 12.5 times higher PX/OX selectivity in liquid-phase adsorption and 3.4 times higher dynamic selectivity in fixed-column breakthrough experiments compared to the individual ZIF components. Theoretical simulations further corroborate the heterogeneous diffusion control mechanism, revealing the time-dependent diffusion regulation within the core-shell architecture. This work underscores the great potential of core-shell MOF composites in optimizing molecular sieving processes for industrially significant separations and highlights a new route for enhancing kinetic separation efficiency in complex multicomponent systems.

Tunable Gas Permeation Behavior through Robust, Freestanding Self-Assembled Metal Nanoparticle Membranes.

Membrane-based gas separation offers a promising alternative route to energy-intensive industrial gas separation processes. Conventional microporous membranes often exhibit low gas selectivities for gases with similar kinetic diameters, primarily due to large pore sizes and reliance on Knudsen selectivity. In this study, we present self-assembled gold nanoparticle (Au NP) membranes that enable molecular gas separation within the kinetic diameter range of small gases such as H2, CO2, and O2. By grafting silane molecules of varying sizes onto NP ligands, the gas selectivity of these membranes becomes tunable. This strategy achieves remarkably high gas selectivities of 192 and 35 for H2/CO2 and CO2/O2 gas pairs. Moreover, the Au NP membrane demonstrates a mixed gas selectivity of up to 30 for H2/CO2 even at room temperature, establishing its potential as a novel class of gas separation membranes with high and tunable selectivity.