UEXdo/OpenDataHub huggingface dataset:
Microstructure &amp; physicochemical properties dataset of NaCl-based salt mixtures for concentrating solar power
Authors: Feng, Y.; Wu, Y.; Wang, W.
Journal: Scientific Data (2026)

Abstract
                  Concentrating solar power is a pivotal technology in global transition toward renewable energy, providing a viable pathway for dispatchable and base-load electricity generation. An important component of the concentrating solar power system is molten salts, particularly NaCl-based mixtures, which serve as both efficient heat transfer fluids and high-capacity thermal energy storage media. The influence mechanisms of micro-ionic interactions and microstructure on physico
An electronic product carbon footprint dataset for question answering
Authors: Zhao, K.; Koyatan Chathoth, A.; Balaji, B.; Lee, S.
Journal: Scientific Data (2026)

Abstract
                  The embodied carbon of computing systems constitutes a significant portion of their greenhouse gas (GHG) emissions. To support environmental initiatives and meet evolving standards, many companies now disclose product carbon footprints in sustainability reports, often with detailed breakdowns. Yet these reports appear in diverse and unstructured formats—text, tables, and graphs embedded in PDFs—creating major challenges for extracting and analyzing component-specific e
Carbon footprint dataset of concrete based on field surveys at commercial mixing plants in Shandong, China
Authors: Niu, D.; Zhou, J.; Guo, B.
Journal: Scientific Data (2026)

Abstract
                  
                    Carbon dioxide (CO
                    2
                    ) emissions from concrete have grown rapidly, ranking second after the power sector. Current emission factors often overlook regional heterogeneity. To bridge this knowledge gap, this study takes Shandong Province, a typical region in China, as a case study. Considering the difference in geography, history, culture, and economic development, Shandong is divided into five subregions: Easte
Global 0.05° Grid-Based Dataset of Keyhole Imagery with Spatio-Temporal Indicators (1960–1984)
Authors: Wang, T.; Zhang, X.; Shan, M.; Deng, M.; Wang, J.
Journal: Scientific Data (2026)

Abstract
                  The American satellite reconnaissance program (Keyhole imagery) is serving as a significant data source for geoscience research because of its high-resolution and early temporal coverage, while lack of spatial and temporal description of its uneven distribution could hinder researchers from selecting/accessing appropriate the Keyhole images. Here we introduce a global grid–based dataset that organizes declassified U.S. Keyhole imagery (1960–1984) for direct reuse, buil
A dynamic meshing transmission dataset for manufacturing quality inspection of electric vehicle reducer gears
Authors: Guo, D.; Yang, J.; Li, H.; Huang, Y.; Long, X.
Journal: Scientific Data (2026)

Abstract
                  The NVH (Noise, Vibration, Harshness) performance of electric vehicle reducer gears directly affects the NVH level of the whole vehicle. However, the existing single gear quality detection methods based on tooth surface waviness are faced with two major challenges, which are unable to detect quickly and cannot fully characterize the real performance. This work introduces the first real industrial dataset for manufacturing quality inspection of electric vehicle reducer
Bounding the costs of electric vehicle managed charging—supply curves for scenarios from 2025 to 2050
Authors: Matsuda-Dunn, R.; Hale, E.; Estreich, E.; Lavin, L.; Konar-Steenberg, G.
Journal: Scientific Data (2026)

Abstract
                  As electric vehicle (EV) adoption increases, the resulting EV battery charging will increase demand on the electric power grid. Through EV managed charging (EVMC) programs, charging can be shifted in time to support electric grid reliability and reduce electricity costs. EVMC can offer an alternative to additional supply-side generation, but the costs of EVMC implementation must be understood to evaluate the cost-benefits of EVMC. This paper presents bottom-up, forward
Mapping Europe’s rooftop photovoltaic potential with a building-level database
Authors: Kakoulaki, G.; Kenny, R.; Taylor, N.; Gracia-Amillo, A.; Szabo, S.
Journal: Nature Energy (2026)

Abstract
                  
                    Individual building-level approaches are needed to understand the full potential of rooftop photovoltaics (PV) at national and regional scale. Here we use the European Digital Building Stock Model R2025, an open-access building-level database, to assess rooftop solar potential for each of the 271 million buildings in the European Union. The results show that potential capacity could reach 2.3 TWp (1,822 GWp residential, 519 GWp non-residential), wi
Heterogeneity in public attitudes and preferences for the deployment of aquifer thermal energy storage
Authors: Liu, T.; Hanna, R.; Kountouris, Y.
Journal: Nature Energy (2026)

Abstract
                  
                    Aquifer thermal energy storage (ATES) can contribute to heating and cooling decarbonization by utilizing the thermal capacity of natural aquifers. Securing acceptance and support for deploying ATES at scale requires acknowledging public perceptions and designing systems compatible with public preferences. Here we characterize attitudinal stances and preferences for the deployment of ATES in public buildings in the UK. Using data from a social surve
The electric vehicle transition and vanishing fuel tax revenues
Authors: Noll, B.; Schmidt, T.; Egli, F.
Journal: Nature Sustainability (2026)

Abstract
                  As electric vehicle adoption accelerates globally, fuel tax revenues decline, exposing government budgets without a proposed replacement tax on electric vehicles. We estimate fuel tax transition exposure across 168 countries, demonstrating that relative exposure, in percentage of total government revenues, varies substantially by income level. Our analysis finds that global public revenues from fuel taxes totalled approximately US$900 billion in 2023. Crucially, we sho
Probabilistic day-ahead forecasting of system-level renewable energy and electricity demand
Authors: Terrén-Serrano, G.; Deshmukh, R.; Martínez-Ramón, M.
Journal: Nature Communications (2026)

Abstract
                  Increasing shares of wind and solar generation, together with rising electricity demand, introduce growing uncertainty into power system operations. Accurate day-ahead forecasts of electricity demand and renewable generation are essential for system operators to coordinate electricity markets and maintain reliability at low cost. Here, we show that forecasting based on joint probability distributions of demand and renewable supply can substantially improve system-level
Balancing land use for conservation, agriculture, and renewable energy
Authors: Brock, C.; Roehrdanz, P.; Beringer, T.; Chaplin-Kramer, R.; Enquist, B.
Journal: Nature Communications (2026)

Abstract
                  
                    Growing demand for food coupled with climate commitments to reduce emissions will result in more land development for agriculture and renewable energy. Simultaneously, conserving land for biodiversity and nature’s contributions to people (NCP) is imperative for achieving international climate, sustainable development, and biodiversity goals. Meeting these interconnected objectives requires efficient land allocation across sectors. Here, we present
Charting net-zero pathways for ASEAN's energy sector
Authors: Zhong, S.; Su, B.; Papageorgiou, D.; Yeung, F.; Ng, T.
Journal: npj Clean Energy (2026)

Abstract
                  The Association of Southeast Asian Nations (ASEAN) is at a turning point to drive an energy transition toward a low-carbon future. Investigating ASEAN's decarbonization strategies is timely. We present a capacity expansion model with hourly resolution for ASEAN to meet net-zero emissions by 2050, integrating electricity generation and hydrogen production. The results show two “bookend” pathways. ASEAN can decarbonize its power sector through an accelerated expansion in
From local production to global consumption: Assessing the carbon footprints of Chinese cities in global value chains
Authors: Wang, S.; Liang, J.; Shan, Y.; Fang, C.; Bai, X.
Journal: npj Clean Energy (2026)

Abstract
                  As cities take on increasingly specialized roles in global value chains (GVCs), the spatial disconnect between where emissions occur and where responsibility lies continues to widen. However, city-level carbon flows across GVCs remain largely underexamined, hindering the design of effective climate policies. Here, we develop a GVC-oriented carbon accounting framework by nesting a multiregional input–output (MRIO) model of 313 Chinese cities within a global MRIO system.
Interaction effect of courtyard building form and orientation on energy performance of hospitals in warm humid climate
Authors: Harshalatha, .; Patil, S.
Journal: Scientific Reports (2026)

Abstract
                  The built environment plays a crucial role in optimizing energy consumption within hospital buildings. Enhancing its efficiency is vital for sustainable development. The form, shape and orientation of hospital buildings significantly impact their energy performance, leading to energy savings, improved indoor air quality, and enhanced thermal comfort. This research focuses on assessing the interactive effect of courtyard building forms and orientation on energy performa
Predicting energy prices and renewable energy adoption through an optimized tree-based learning framework with explainable artificial intelligence
Authors: Tang, T.
Journal: Scientific Reports (2026)

Abstract
                  This research offers a comprehensive analysis of global energy consumption, focusing on predicting two key metrics: the Energy Price Index and the Renewable Energy Share. The study employs advanced Machine Learning (ML) regression techniques, all further optimized using metaheuristic algorithms. In addition, a primary objective of this study is to determine which variables most significantly affect model performance and predictive accuracy. Through SHAP (SHapley Additi
A multi strategy optimization framework using AI digital twins for smart grid carbon emission reduction
Authors: Sakthivel, S.; Arivukarasi, M.; Charulatha, G.; Nithisha, J.; Abirami, B.
Journal: Scientific Reports (2026)

Abstract
                  This research presents an AI-enabled digital twin framework to achieve carbon neutrality in smart grids through optimal management of heterogeneous energy storage systems. The proposed structure integrates battery, thermal, and hydrogen storage technologies with AI-driven forecasting models to address the challenge of renewable integration, while maintaining grid stability and economic viability. This paper presents a comparative analysis of three distinct optimization
A multi-dimensional feature aggregation network for electric vehicle charging demand prediction
Authors: Yu, Y.; He, L.; Yu, Z.; Tu, Y.; Jing, X.
Journal: Scientific Reports (2026)

Abstract
                  
                    Accurate prediction of urban electric vehicle (EV) charging demand is critical for infrastructure planning and dynamic pricing strategies. Although various methods have been developed, most existing studies focus primarily on spatiotemporal dependencies, paying limited attention to interactions among multivariate features. Furthermore, conventional serial spatiotemporal architectures typically extract features dimension-by-dimension, which may impe
Optimized scheduling of integrated energy systems considering waste-to-power plants and advanced adiabatic air compression energy storage machines
Authors: Wang, W.; Liu, M.; Zhao, H.; Wu, Y.; Tian, Y.
Journal: Scientific Reports (2026)

Abstract
                  To achieve carbon peaking and carbon neutrality goals, improve energy utilization efficiency, and accelerate the decarbonization of energy structure, this paper proposes a model that integrates Waste Incineration Power Plant (WIP) and Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) to reduce carbon emissions and enhance system economics. First, based on the coupled WIP and Power-to-Gas (P2G) model, a waste heat recovery unit is introduced to recover exhaust
Large terahertz photovoltaic effect enhanced by phonon excitations in ferroelectric semiconductor SbSI
Authors: Okamura, Y.; Guo, G.; Kaneko, Y.; Nakamura, M.; Sotome, M.
Journal: Science Advances (2026)

Quantum geometry of Bloch electron in crystalline solids produces various exotic quantum phenomena. The shift current photovoltaic effect driven by the photo creation of quasiparticle is one such emerging example that enables the conversion from terahertz photon into dc charge current with absence of dissipative photocarrier. Despite wide-ranging potential applications, however, the fundamental nature of terahertz photovoltaic response has remained elusive. Here, we show the large photocurrent g
Bulk and interface engineering of 1.7 eV–bandgap chalcogenide solar cells enabling record efficiency
Authors: Ishizuka, S.; Taguchi, N.
Journal: Science Advances (2026)


                    Wide-bandgap chalcogenide photovoltaics offer strong potential for tandem solar cells and solar-driven hydrogen generation via water splitting, yet their performance remains limited by persistent interfacial and bulk defects. Here, we demonstrate enhanced efficiency in 1.7–electron volt CuGaSe
                    2
                    thin-film solar cells through aluminum (Al) alloying and rubidium (Rb) incorporation. The Al- and Rb-modified CuGaSe
                    2
Unpacking the growth of global agricultural greenhouse gas emissions
Authors: Ortiz-Bobea, A.; Pieralli, S.
Journal: Science Advances (2026)


                    Agriculture, forestry, and other land use contribute about a fifth of total anthropogenic greenhouse gas (GHG) emissions. Mitigation efforts have emphasized “decoupling” that sustains production while lowering emissions per unit of output. However, the underlying decoupling mechanisms have not been fully characterized. We rely on a mathematical identity to decompose agricultural GHG emission growth (
Reassessing boreal wildfire drivers enables high-resolution mapping of emissions for climate adaptation
Authors: Eckdahl, J.; Nieradzik, L.; Rütting, L.
Journal: Science Advances (2026)

The expansive carbon reservoirs of the boreal region are becoming some of the most rapidly growing sources of greenhouse gasses under a positive feedback between intensifying fire activity and climate change. However, current regional-scale methods lack the spatial precision needed to improve understanding of the drivers of these fluxes to inform strategies aimed at maximizing landscape carbon storage. Here, we develop an alternative and highly constrained procedure for estimating wildfire emiss
Electroluminescent perovskite QD–based neural networks for energy-efficient and accelerate multitasking learning
Authors: Park, Y.; Wang, G.
Journal: Science Advances (2026)


                    The ability of multitasking (MT) learning in neuro-inspired artificial intelligence (AI) systems offers promise for energy-efficient deployment in robotics, health care, and autonomous vehicles. Here, an MT learning framework is established using a dual-output electroluminescent synaptic device array based on a mixed-dimensional stacked configuration with Cs
                    
                      1−
                      x
                    
                    FA
On-demand cancer immunotherapy via single-cell encapsulation of synthetic circuit–engineered cells
Authors: Zhao, Y.; Li, R.; Han, Y.; Shi, C.; Lee, K.
Journal: Science Advances (2026)


                    Despite the therapeutic potential of engineered immune cell therapy against metastases, it faces challenges including cytokine-driven systemic toxicity, off-target biodistribution, and host rejection. Here, we develop red/far-red light-regulated individually encapsulated (RL/FRL-EnE) cells, integrating optogenetics with biomaterial encapsulation for precise immunomodulation. This system uses a phytochrome A–based photoswitch (ΔPhyA-PCB) that enables bidirectional control. RL
Programmable electric tweezers
Authors: Chen, Y.; Tan, H.; Zhuang, J.; Xu, Y.; Zhang, C.
Journal: Science Advances (2026)

The interaction between a single microscopic object such as a cell or a molecule and electromagnetic field is fundamental in single-object manipulation such as optical trap and magnetic trap. Function-on-demand, single-object manipulation requires local high-freedom control of electromagnetic field, which remains challenging. Here, we propose a manipulation concept: programmable single-object manipulation, based on programming the electromagnetic field in a multibit electrode system realized on
Chang’E-6 reveals solar wind–dependent H
                    <sup>−</sup>
                    ions on the Moon
Authors: Zhong, T.; Xie, L.; Zhang, A.; Wieser, M.; Wang, W.
Journal: Science Advances (2026)


                    Apart from positive ions and electrons, negative ions are expected in various astrophysical environments. However, they have never been detected on the Moon until the Chang’E-6 mission. The NILS instrument onboard Chang’E-6 lander is the first dedicated instrument for detecting negative ions beyond Earth and has successfully obtained H
                    −
                    spectra on the lunar surface, providing an unprecedented opportunity to investigate their origin an
Boosting capacitive energy storage in relaxor ferroelectrics through polymorphic phase engineering
Authors: Zhang, Y.; Liang, H.; Liu, Y.; Li, D.; Dong, S.
Journal: Science Advances (2026)


                    Relaxor ferroelectric materials are promising for next-generation capacitors due to their high energy storage capacity. Polymorphic phase engineering, where different ferroelectric phases coexist, has been widely demonstrated as an effective approach to further boost capacitive energy storage performance of relaxor ferroelectrics, but the reasons for these improvements and how they compare to single-phase systems remain unclear. Here, taking dendrite-like PbZr
Rigid-flexible heptazine-biguanide frameworks enable fast electron delocalization and low-steric-hindrance ammonium-ion storage
Authors: Du, W.; Zhang, Y.; Duan, H.; Lv, Y.; Song, Z.
Journal: Science Advances (2026)


                    Polymer anodes solve the solubility issue of small molecules while offering structure-function merits compared with inorganics for superior ammonium-ion batteries (AIBs), but current research focuses either on rigid polymers for rapid ion transport or flexible ones for high active-site utilization. Here, we design polymeric heptazine-biguanide frameworks (HBFs) via integrating planar three-electron meleme and rotated four-electron chlorhexidine linkers, which harness the adv
Global dataset combining open-source hydropower plant and reservoir data
Authors: Shah, J.; Hu, J.; Edelenbosch, O.; van Vliet, M.
Journal: Scientific Data (2025)

Abstract
          Hydropower is a crucial renewable source that depends heavily on water availability. Analyzing drought and climate change impacts on hydropower potential requires detailed data on both hydropower plant attributes (e.g. plant type and head) and reservoir characteristics (e.g. area, depth and volume). However, existing open-source datasets are poorly integrated: hydropower plant datasets often lack reservoir information, while reservoir datasets commonly miss hydropower plant in
Global photovoltaic solar panel dataset from 2019 to 2022
Authors: Li, A.; Liu, L.; Li, S.; Cui, X.; Chen, X.
Journal: Scientific Data (2025)

Abstract
          Solar photovoltaic (PV) power generation, known for its affordability and environmental benefits, is a key component of the global energy supply. However, the lack of comprehensive, timely, and precise global PV datasets has limited spatial analysis of PV potential. We developed a new method to identify PV panels globally, producing an annual 20-meter resolution dataset for 2019–2022. This dataset offers unprecedented detail and accuracy for future research and policy-making.
Longitudinal Dataset of Net-load, PV Production and Solar Irradiation from Madeira Island, Portugal
Authors: Pereira, L.; Monteiro, D.; Apina, F.; Scuri, S.; Barreto, M.
Journal: Scientific Data (2025)

Abstract
                  This paper presents the PTProsumer dataset, a high-resolution dataset of photovoltaic (PV) production and net-load measurements collected from 24 prosumers - entities that both produce and consume electricity, including households and small commercial buildings - on Madeira Island, Portugal. The dataset covers monitoring periods ranging from 3 months to 5 years, with measurements sampled at a 1-second resolution, resulting in approximately 3.89 billion data points. PV
From Footprints to Functions: A Comprehensive Global and Semantic Building Footprint Dataset
Authors: Oostwegel, L.; Schorlemmer, D.; Guéguen, P.
Journal: Scientific Data (2025)

Abstract
                  
                    Buildings play a critical role in understanding settlement patterns and are essential for crisis management, urban planning, energy efficiency, and multi-hazard risk assessment. To address the need for accessible global building data, we introduce a dataset containing 2.7 billion building footprints classified using the building taxonomy of the Global Earthquake Model. By conflating the AI-derived
                    Google Open Buildings
A global urban tree leaf area index dataset for urban climate modeling
Authors: Dong, W.; Yuan, H.; Lin, W.; Liu, Z.; Xiang, J.
Journal: Scientific Data (2025)

Abstract
          Urban trees are recognized for mitigating urban thermal stress, therefore incorporating their effects is crucial for urban climate research. However, due to the limitation of remote sensing, the LAI in urban areas is generally masked (e.g., MODIS), which in turn limits its application in Urban Canopy Models (UCMs). To address this gap, we developed a high-resolution (500 m) and long-time-series (2000–2022) urban tree LAI dataset derived through the Random Forest model trained
A dataset of emissions and removals from scenarios and pathways within long-term national climate strategies – the LTS-SP dataset
Authors: Smith, H.; Vaughan, N.; Forster, J.
Journal: Scientific Data (2025)

Abstract
          Long-term low emission development strategies (LT-LEDS), supported by Article 4, paragraph 19, of the Paris Agreement, present scenarios and pathways aligned with national long-term climate targets. There is a growing interest in understanding whether the collective effort of national climate plans align with the goals of the Paris Agreement, alongside the feasibility, sectoral focus, and the balance of emissions and removals seen in national scenarios. Here we introduce the l
China’s product-level CO2 emissions dataset aligned with national input-output tables from 1997 to 2020
Authors: Li, X.; Liu, Y.; Zhang, J.; Zhou, M.; Meng, B.
Journal: Scientific Data (2025)

AbstractCarbon emission research based on input-output tables (IOTs) has received attention, but data quality issues persist due to inconsistencies between the sectoral scopes of energy statistics and IOTs. Specifically, China’s official energy data are reported at the industry level, whereas IOTs are organized by product sectors. Valid IOT-based environmental models require consistent transformation from industry-level to product-level emissions. However, most existing studies overlook this nec