UEXdo/OpenDataHub huggingface dataset:
Agricultural carbon footprints, renewable energy and sustainable development in Asia
Authors: Liu, H.; Liu, Y.
Journal: Scientific Reports (2025)

Abstract
          There is a growing concern over environmental degradation and climate change in rapidly developing Asian nations. However, little research has been conducted on the impact of agricultural carbon emissions and renewable energy use on sustainable development outcomes in Asia. This research looks at the relationship between agricultural carbon footprints (ACF), renewable energy consumption (RE), and sustainable development (SD) in nine Asian nations from 2000 to 2022. The study e
A new 37- level inverter with reduced switches for renewable energy applications
Authors: Shukla, S.; Goel, V.; Dhanamjayulu, C.
Journal: Scientific Reports (2025)

Abstract
                  
                    Multilevel inverters (MLIs) are now crucial in producing high-quality output waveforms due to their modularity and efficiency. This paper presents a novel 37- level MLI topology with a reduced number of switches and sources. The proposed design offers several advantages, including lower total harmonic distortion (THD) of 1.21% in hardware and 0.8% in simulation, high efficiency of 93.26%, reduced total standing voltage of 18 V
                    D
Multi-criteria assessment of optimization methods for controlling renewable energy sources in distribution systems
Authors: Eid, A.; Alsafrani, A.
Journal: Scientific Reports (2025)

Abstract
          Numerous optimization techniques have recently been employed in the literature to enhance various electric power systems. Optimization algorithms help system operators determine the optimal location and capacity of any renewable energy source (RES) connected to a system, enabling them to achieve a specific goal and improve its performance. This study presents a novel statistical evaluation of 20 famous metaheuristic optimization techniques based on 10 performance measures. The
Seasonal forecasting of the hourly electricity demand applying machine and deep learning algorithms impact analysis of different factors
Authors: El-Azab, H.; Swief, R.; El-Amary, N.; Temraz, H.
Journal: Scientific Reports (2025)

Abstract
          The purpose of this paper is to suggest short-term Seasonal forecasting for hourly electricity demand in the New England Control Area (ISO-NE-CA). Precision improvements are also considered when creating a model. Where the whole database is split into four seasons based on demand patterns. This article’s integrated model is built on techniques for machine and deep learning methods: Adaptive Neural-based Fuzzy Inference System, Long Short-Term Memory, Gated Recurrent Units, and
An empirical analysis of electricity use and expenditure in farming households in Poland
Authors: Piwowar, A.
Journal: Scientific Reports (2025)

Abstract
                  
                    The article presents the results of empirical research into expenditure on electricity and the dependencies of the share of these expenses with regard to the features of farming households in Poland. The source material came from empirical research conducted on a random sample of 480 farming households in Poland (each exceeding 5 ha of UAA), with multiple correspondence analysis (MCA) used in the analyses. Through a combination of survey methods an
Climate-adaptive energy forecasting in green buildings via attention-enhanced Seq2Seq transfer learning
Authors: Peng, F.; Su, T.; Zeng, Q.; Han, X.
Journal: Scientific Reports (2025)

Abstract
          Energy consumption forecasting in green buildings remains challenging due to complex climate-building interactions and temporal dependencies in energy usage patterns. Existing prediction models often fail to capture long-term dependencies and adapt to diverse climatic conditions, limiting their practical applicability. This study presents an integrated forecasting framework that combines sequence-to-sequence (Seq2Seq) architecture with reinforcement learning and transfer learn
Mitigating anthropogenic climate change with aqueous green energy
Authors: Olim, S.; Nickoloff, A.; Moffat, L.; Weaver, A.; Eby, M.
Journal: Scientific Reports (2025)

AbstractReaching net zero emissions and limiting global warming to 2 °C requires the widespread introduction of technology-based solutions to draw down existing atmospheric levels and future emissions of CO2. One such approach is direct air CO2 capture and storage (DACCS), a readily available, yet energy-intensive process. The combination of DACCS and ocean thermal energy conversion (OTEC) allows for independently powered carbon capture plants to inject concentrated carbon into deep marine sedim
Solar potential assessment using machine learning and climate change projections for long-term energy planning
Authors: Reddy, B.; Gautam, K.; Pachauri, N.
Journal: Scientific Reports (2025)

Abstract
                  This work proposes a novel method for evaluating solar potential, essential for the development, installation, and operation of solar power systems. The approach forecasts solar energy potential for specific sites by utilizing integrated geospatial, meteorological, and infrastructural multidimensional data. A new application has been released to assess the solar capacity globally. The study evaluated various machine learning methods, ultimately selecting an XGBoost mod
A novel approach to wind energy modeling in the context of climate change at Zaafrana region in Egypt
Authors: Kamel, B.; Abdelaziz, A.; Attia, M.; Khamees, A.
Journal: Scientific Reports (2025)

Abstract
          Global warming, driven by the excessive emission of greenhouse gases from the combustion of fossil fuels, has emerged as a critical environmental challenge which is considered as a motivation for this research. Where, the switch to sustainable energy sources is crucial because of the pressing need to slow down climate change and lower carbon footprints. Of all the renewable energy sources, wind energy is particularly important as a means of reducing carbon emissions from the g
Optimal micro-grid battery scheduling within a comprehensive smart pricing scheme
Authors: Ali, M.; Besheer, A.; Emara, H.; Bahgat, A.
Journal: Scientific Reports (2025)

Abstract
          The challenge of optimizing battery operating revenue while mitigating aging costs remains inadequately addressed in current literature. This paper introduces a novel cost–benefit approach for scheduling battery energy storage systems (BESS) within microgrids (MGs) that features smart grid attributes. The proposed comprehensive approach accounts for fluctuations of real-time pricing, demand charge tariffs, and battery degradation cost. Using the dynamic programming technique,
Identification and suppression of low-frequency oscillations using PMU measurements based power system model in smart grid
Authors: Zuhaib, M.; Rihan, M.; Gupta, S.; Sufyan, M.
Journal: Scientific Reports (2025)

Abstract
          Low-frequency oscillations (LFO) are inherent to large interconnected power systems. Timely detection and mitigation of these oscillations is essential to maintain reliable power system operation. This paper presents a methodology to identify and mitigate low-frequency oscillations ( forced and inter-area) using a wide area monitoring system (WAMS) based power system model utilizing phasor measurement units (PMUs). These models accurately identify the behavior and location of
Resilient cybersecurity in smart grid ICS communication using BLAKE3-driven dynamic key rotation and intrusion detection
Authors: Dokku, N.; David Amar Raj, R.; Bodapati, S.; Pallakonda, A.; Reddy, Y.
Journal: Scientific Reports (2025)

Abstract
          The increasing convergence of Industrial Control Systems (ICS) with critical infrastructure, such as smart grids, has increased their exposure to advanced cyber threats, demanding advanced security frameworks to maintain security and operational integrity. This paper shows an innovative cybersecurity approach for ICS, using the IEC 60870-5-104 dataset, that combines machine learning, cryptographic resilience, and forensic analysis to predict and neutralize various attack vecto
Powertrain configuration design for two mode power split hybrid electric vehicle
Authors: Ke, T.; Nie, L.; Kecskeméthy, A.
Journal: Scientific Reports (2025)

Abstract
          Hybrid transmissions have attracted great attention in the automotive industry due to their energy-saving, low-emission properties, and have become a focus of research and development. This paper presents a new method to design the configuration of two mode power split hybrid transmission using the combination of the simple planetary gear trains (PGT). For this purpose, the hybrid transmission structure is divided into two substructures, which achieve different operation modes
Multi-objective route optimization for electric vehicle hazardous materials transportation in uncertain environments
Authors: Zhang, Q.; Zhang, Z.; Ma, C.
Journal: Scientific Reports (2025)

Abstract
                  This paper focuses on the application of electric vehicles in the transportation of Category 9 hazardous materials. Given the high requirements for safety and timeliness in hazardous materials transportation, this study first comprehensively considers the impacts of population density uncertainty and cargo volume changes on transportation risks and power consumption. Furthermore, a multi-objective path optimization model is developed. The model aims to minimize transpo
Comprehensive performance analysis of an electric vehicle using multi-mode Indian drive cycles
Authors: Kondru, J.; Obulesu, Y.
Journal: Scientific Reports (2025)

Abstract
          The constant advancements in the research and development society of vehicle manufacturing made the customer’s attention towards EV ownership due to the better economic profile in the view of maintenance and operations. Even though the vehicles have better features the performance of the EV can be estimated with the consideration of the designed drive cycle for the region. According to that the procurement of EVs should be in the approved range of drive cycles with the concern
Survival analysis of electric vehicle charging behavior and the temporal evolution of feature effects
Authors: Meža, M.; Strle, G.; Meža, M.
Journal: Scientific Reports (2025)

Abstract
          This study proposes a survival-based modeling framework that combines behavioral features with interpretable machine learning to understand and predict user churn in electric vehicle charging services. Using a dataset of 1,074 users and 107,531 charging sessions from Central European countries, we modeled time-to-churn while handling censored observations. The best-performing model, a Stacked Weibull survival model based on gradient boosting, achieved a concordance index of 0.
Machine learning-based approach for reduction of energy consumption in hybrid energy storage electric vehicle
Authors: Paulraj, T.; Obulesu, Y.
Journal: Scientific Reports (2025)

Abstract
          This research introduces a novel machine learning-based strategy for generating supercapacitor (SC) reference current to optimize energy distribution in Battery Electric Vehicles (BEV) and Hybrid Battery Electric Vehicles (HBEV). A Long Short-Term Memory (LSTM) neural network is trained using real-world drive cycle data and exported in Open Neural Network Exchange (ONNX) format for real-time deployment within a Simulink-based control environment. This enables adaptive SC curre
Smart Strategies for Improving Electric Vehicle Battery Performance and Efficiency
Authors: Tangi, S.; Vatsa, A.; Opam, A.; Bonthagorla, P.; Gaonkar, D.
Journal: Scientific Reports (2025)

Abstract
                  The increasing demand for Electric Vehicles (EVs) necessitates accurate range prediction and optimization of driving parameters to address range anxiety and improve user experience. This study proposes a machine learning-based framework for predicting EV range, optimum acceleration, and velocity using a synthetically generated dataset of 2,000 samples designed to reflect real-world driving scenarios. Four models—Random Forest (RF), Extra Trees (ET), Linear Regression (
Strategic design of wind energy and battery storage for efficient and sustainable energy systems
Authors: Eroğlu, H.; Kurtuluş, O.
Journal: Scientific Reports (2025)

Abstract
          The intermittent nature of renewable energy sources, particularly wind power, necessitates advanced energy management and storage strategies to ensure grid stability and economic viability. This study investigates the techno economic benefits of integrating Battery Energy Storage Systems (BESS) into wind power plants by developing and evaluating optimized hybrid operation strategies. Using real world Data from a 70 MW wind farm, ten distinct operational strategies were simulat
A spatial decision making framework using neutrosophic VIKOR for wind energy investment in Turkey
Authors: Eroğlu, H.
Journal: Scientific Reports (2025)

Abstract
          The growing demand for clean energy and the urgency of reducing carbon emissions have made wind power a key element of Turkey’s renewable energy strategy. However, identifying optimal regions for wind energy investment remains a complex task due to the interplay of technical, spatial, and economic factors, all of which are characterized by varying degrees of uncertainty. Although GIS-based site selection and multi-criteria decision-making (MCDM) methods are widely used, few ap
An aeroelastic wind energy harvester with continuous orbiting motion and no friction components
Authors: Denissenko, P.; Tucker Harvey, S.
Journal: Scientific Reports (2025)

Abstract
          A continuous-movement aeroelastic energy harvester with no friction parts is presented. Different from the commonly used vortex-induced vibration or galloping devices, the proposed energy harvesting system is constructed with a circular arc airfoil mounted to a flexible beam that follows a closed trajectory rather than oscillating linearly. The continuous motion of the airfoil results in the flow being fully attached, resulting in a greater efficiency than that of conventional
Design of a distributed power system using solar PV and micro turbine-based wind energy system with a flywheel energy storage
Authors: Bhavani, T.; Rajababu, D.; Irfan, M.; Rakesh, T.; Sekhar, P.
Journal: Scientific Reports (2025)

Abstract
                  As renewable energy sources gain distinction in distributed power generation, micro-grid systems integrating solar photovoltaic (PV), micro-turbine-based wind energy, and flywheel energy storage have developed as sustainable solutions. This paper presents a novel design methodology for a hybrid micro-grid system that optimally integrates these components, ensuring enhanced efficiency, resilience, and stability. In a grid outage or weak-grid scenario, a flywheel provide
Conceptual design of airborne contra rotating VAWTs for rooftop wind energy
Authors: Radhakrishnan, J.; Sridhar, S.; Zuber, M.; Ng, E.; Shenoy, B.
Journal: Scientific Reports (2025)

Abstract
          Co-rotating, counter, and contra-rotating Vertical Axis Wind Turbines (VAWTs) offer higher power yields than singular turbines due to synergetic interactions, making them ideal for rooftop applications. This study focuses on enhancing the efficiency of a Contra-Rotating VAWT (CR-VAWT) using a ducted airborne configuration. A wind gathering device (WGD), optimized via the Taguchi method, is integrated around the CR-VAWT, which is elevated using an oblate spheroid aerostat desig
Multi-timescale optimization scheduling of integrated energy systems oriented towards generalized energy storage services
Authors: Mao, Y.; Cai, Z.; Jiao, X.; Long, D.
Journal: Scientific Reports (2025)

Abstract
          This paper addresses the limitations of existing research that focuses on single-sided resources and two-timescale optimization, overlooking the coordinated response of various energy storage resources across different timescales in comprehensive energy systems. To tackle these shortcomings, the study integrates flexible demand-side resources, such as electric vehicles (EVs), hydrogen storage, and air conditioning clusters, as generalized energy storage. It explores their impa
Artificial intelligence powered intelligent energy management framework for hydrogen storage and dispatch in smart microgrids
Authors: Hassan, M.
Journal: Scientific Reports (2025)

Abstract
                  
                    Hydrogen energy storage is increasingly recognized as a key enabler for enhancing flexibility and reliability in smart microgrids with high shares of renewable energy. However, its practical deployment remains constrained by challenges such as real-time dispatch complexity, forecasting uncertainty, and nonlinear system dynamics. This study presents a novel AI-powered decision-support framework that integrates Long Short-Term Memory (LSTM) neural ne
Carbon footprint awareness scale (CFAS): validity and reliability study on university students
Authors: Pekel, A.; Yoka, K.; Turan, M.; Yoka, O.; Akyüz, O.
Journal: Scientific Reports (2025)

Abstract
          This study was designed with a mixed model to develop a valid and reliable measurement tool to measure university students’ carbon footprint awareness. A total of 1053 university students, 454 female and 599 male, were included in the study voluntarily. To provide evidence for the scale’s validity, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied to the measurement tool within the scope of construct validity. In the Exploratory Factor Analy
Carbon footprint assessment and reconstruction redesign of recycled discarded military training uniforms
Authors: Huang, G.; Shi, S.; Wang, Q.; Li, F.; Li, X.
Journal: Scientific Reports (2025)

Abstract
                  In response to the problem of resource waste and environmental pollution caused by the large amount of waste textiles in China, taking waste military training uniforms as an example, a thorough investigation was conducted to draw a life cycle diagram of military training uniforms, establish a recycling system for waste military training uniforms, and use Taiyuan University of Technology as a pilot for recycling. The carbon footprint of different recycling methods was c
Quantifying the energy and emissions implications of consumption redistribution in the UK through sustainable consumption corridors
Authors: Betts-Davies, S.; Owen, A.; Barrett, J.; Brockway, P.; Norman, J.
Journal: Scientific Reports (2025)

Abstract
          Reducing inequality to ensure decent living standards alongside climate mitigation, are frequently posited as dual goals of a just transition. Energy sufficiency has received attention as a solution to these crises, but there has been limited exploration of the impact sufficiency principles could have on energy and GHG emissions. Addressing this gap, we utilise a consumption-corridor approach to develop three redistributive scenarios of final consumption for the UK. Each scena
Study on indoor thermal environment and energy consumption of traditional dwellings of ethnic minorities in Sichuan plateau
Authors: Zhang, Y.; Wang, B.
Journal: Scientific Reports (2025)

Abstract
          In this paper, field tests, questionnaire surveys, and DesignBuilder were used to analyse the indoor thermal environment and energy consumption of traditional houses in a traditional ethnic minority village of Western Sichuan Plateau of China, The results showed that during the summer test period, the outdoor temperature range was 9.3–7.8 °C and the relative humidity range was 53.5–67.4%, while the indoor temperature range of the tested room was 13.3–2.3 °C, and the relative h
Modeling energy consumption indexes of an industrial cement ball mill for sustainable production
Authors: Chehreh Chelgani, S.; Fatahi, R.; Pournazari, A.; Nasiri, H.
Journal: Scientific Reports (2025)

Abstract
          The total cement energy consumption is around 5% of global industrial energy usage. In cement plants, mills consume half of this energy for dry grinding particles. However, grinding in tumbling mills is a random process, and a maximum of 5% of this energy would be directly devoted to particle size reduction. Thus, understanding interactions between operation variables and the mill energy consumption factors would be essential for sustainable cement production and green transit
Multiobjective distribution system operation with demand response to optimize solar hosting capacity, voltage deviation index and network loss
Authors: Loji, K.; Sharma, S.; Sharma, G.; Rawat, T.
Journal: Scientific Reports (2025)

AbstractIn this research, demand response impact on the hosting capacity of solar photovoltaic for distribution system is investigated. The suggested solution model is formulated and presented as a tri-objective optimization that consider maximization of solar PV hosting capacity (HC), minimization of network losses (Loss) and maintaining node voltage deviation (VDev) within acceptable limits. These crucial objectives are optimized simultaneously as well as individually. To assess the efficacy o
An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system
Authors: Dey, B.; Sharma, G.; Bokoro, P.; Dutta, S.
Journal: Scientific Reports (2025)

AbstractThe cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. In order to improve load factor and efficiency, load-shifting techniques are frequently used in conjunction with additional complex constraints such as PHEV scheduling and battery life assessment. Pollutant reduction, however, is rarely highlighted as a primary goal. An incentive-based demand response (IBDR) is introd
Two-stage multi-objective framework for optimal operation of modern distribution network considering demand response program
Authors: Elshenawy, M.; Mohamed, A.; Ali, A.; Mosa, M.
Journal: Scientific Reports (2025)

AbstractTo improve the inadequate reliability of the grid that has led to a worsening energy crisis and environmental issues, comprehensive research on new clean renewable energy and efficient, cost-effective, and eco-friendly energy management technologies is essential. This requires the creation of advanced energy management systems to enhance system reliability and optimize efficiency. Demand-side energy management systems are a superior solution for multiple reasons. Firstly, they empower co
Open-flask, ambient temperature direct arylation synthesis of mixed ionic-electronic conductors
Authors: Kimpel, J.; Kim, Y.; Schomaker, H.; Hinojosa, D.; Asatryan, J.
Journal: Science Advances (2025)


            Conjugated polymers are widely studied for application areas ranging from energy technology to wearable electronics and bioelectronics. To develop a truly sustainable technology, environmentally benign synthesis is essential. Here, the open-flask synthesis of a multitude of conjugated polymers at room temperature by ambient direct arylation polymerization (ADAP) is demonstrated. The batch synthesis of over 100 grams of polymer in a green solvent and continuous droplet flow synthesis
A photovoltaic-electrolysis system with high solar-to-hydrogen efficiency under practical current densities
Authors: Zhang, Q.; Shan, Y.; Pan, J.; Kumar, P.; Keevers, M.
Journal: Science Advances (2025)


            The photovoltaic-alkaline water (PV-AW) electrolysis system offers an appealing approach for large-scale green hydrogen generation. However, current PV-AW systems suffer from low solar-to-hydrogen (STH) conversion efficiencies (e.g., &lt;20%) at practical current densities (e.g., &gt;100 mA cm
            −2
            ), rendering the produced H
            2
            not economical. Here, we designed and developed a highly efficient PV-AW system that mainly consists of a custo