Cellulose-based MXene composite foams with enhanced oxidation stability and Janus wettability for high-performance solar evaporation and electricity generation.

Treatment of waste activated sludge and the enhancement mechanism for electron transfer in an osmotic microbial fuel cell.

Photo-driven multifunctional membrane evaporator based on Sb2Se3/MoSe2/Ag@PAM for freshwater harvesting and electricity generation

Accurately quantifying operational carbon emissions from buildings is essential to verify that decarbonization targets are met. Yet many current practices rely on overly simplified yearly average emission factors that overlook the temporal variability of the electrical grid generation. This issue becomes increasingly critical with the rising penetration of renewable energy and the adoption of demand-side strategies in buildings, such as load shifting. Existing literature on net-zero carbon buildings rarely examines how the temporal resolution of emission factors affects accounting accuracy. In this study, we evaluated a range of grid emission factors (annual, seasonal, time-of-day, season-hour, and month-hour) and quantified their impact on carbon emissions accounting accuracy for commercial buildings across 18 U.S. grid regions. These emission factors, derived from publicly available datasets, are applied to measured hourly electricity consumption profiles from over 600 real commercial buildings. By considering hourly emission factors as the benchmark reference, we then quantified the resulting errors and uncertainties due to the reduced temporal resolution of the emission factors. Additionally, we assessed how buildings' on-site solar PV generation affects avoided emissions accounting from grid exports when electricity generation exceeds demand. As a result, we found that annual and seasonal averages are unreliable and should not be used for net-zero target assessments. Instead, we recommend incentivizing the adoption of season-hour and month-hour emission factors, which consistently deliver sufficient accuracy across diverse U.S. grid regions, with median errors typically less than 10%. This is also the case when quantifying the avoided emissions when utility export is available, yet the results are more variable and dependent on the grid generation mix. In particular, when coarse emission factors such as annual or seasonal averages are used, increasing onsite solar capacity can raise the median normalized fractional error to approximately 15% for operational emissions and to more than 100% for avoided emissions. These findings highlight the need for future standards and guidelines to consider at least the use of season-hour or month-hour emission factors' resolution to achieve acceptable emissions accounting accuracy. • Annual average emission factors should not be used for assessing building operational or avoided carbon emissions. • Season-hour and month-hour average emission factors deliver sufficient accuracy with median errors typically below 10%. • The importance of temporal resolution increases significantly in grid regions with higher solar generation. • Coarse-resolution emission factors risk underestimating the true impact of efficiency and flexibility retrofits.

Iran's electricity generation relies heavily on fossil fuels, resulting in frequent power shortages and widespread blackouts in major cities. Given the high levels of solar irradiance across the country, photovoltaic (PV) and concentrating solar power (CSP) technologies could provide a sustainable alternative. Existing studies focus on specific technologies or individual regions. Currently, there is no consistent, comprehensive mapping of the scope for political decision-making in Iran. This study aims to address this issue by providing the first nationwide assessment of solar energy potential in Iran, evaluating both PV and CSP. This GIS-based assessment uses an expanded set of environmental and technical criteria and performs sensitivity analyses to ensure robust results and identify the most effective and sustainable locations for PV and CSP plants. The model incorporates specific constraints, such as protected natural areas, to exclude unsuitable sites, and assesses suitability based on criteria such as solar irradiation levels and proximity to grid infrastructure. These factors are categorised into four suitability classes, ranging from 'high' to 'very low' for both PV and CSP installations. By synthesising the constraint and suitability maps, the model identifies feasible sites and assesses their relative desirability. A sensitivity analysis, focusing on the weighting of the suitability criteria, confirms the robustness of the results. The results highlight Iran's considerable capacity for solar power generation and suggest that the country could exceed its current electricity production by a multiple through the development of solar power plants. The model applies 14 exclusion criteria, revealing that 70% of Iran’s land is unsuitable for PV and 83% for CSP. The results show that 14.5% of Iran’s land is suitable for PV and 7.5% for CSP (medium and high suitable), with central and eastern regions offering the highest potential. Additionally, the study highlights the promising prospects of GIS modeling in renewable energy siting, emphasizing improved data integration, global scalability, environmental impact assessment, and policy harmonization. • For the first time, a nationwide GIS model identifies suitable PV and CSP sites in Iran. • Suitability results remain robust across sensitivity scenarios. • Iran's solar potential could exceed its current electricity generation by a multiple.

Organic photothermal cocrystal of solar evaporators for synergistic clean water and electricity generation

Techno-economic analysis of a solar-wind hybrid system with energy storage for remote inaccessible regions of India -A case study

EmuCast is a lightweight tool for generating synthetic time-series forecasts with tuneable error levels. It is intended for researchers and engineers to test predictive control strategies without needing forecasting expertise. It uses Markov Chain Monte Carlo (MCMC) and a reshaping process to create realistic hourly to sub-hourly forecasts. It is simple with only two main parameters, and do not require any calibration to adapt to any type of data (e.g. electricity demand and generation). It is fast and realistic with errors naturally increasing along the horizon. The package includes examples and datasets for predictive management in the energy sector.

Implantable piezocatalytic enzyme hydrogel re-engineers metabolic reprogramming for ischemic stroke therapy.

Electrochemical induction of high performance electricity generation by novel marine electroactive Rossellomorea aquimaris MT01.

• Hybrid GO-MXene nanofluids cut PV thermal resistance by 41.1%. • 3D-OHP with nanofluids boosts PV output by 14.9%. • GO-MXene cools PV panels by 24°C, enhancing efficiency. • Nanofluid cooling adds 43 W/day power, improves exergy to 30.9%. • LCOE analysis confirms cost-effective PV thermal management. The efficiency and longevity of photovoltaic (PV) panels are significantly impaired by excessive operational heat accumulation, which can reduce electrical efficiency by 0.4–0.5% per °C above 25°C and lead to 20–30% annual energy losses in urban environments. This study presents an innovative passive thermal management system integrating a three-dimensional oscillating heat pipe (3D-OHP) with hybrid graphene oxide (GO)–MXene (Ti 3 C 2 T x ) nanofluids at concentrations of 0.1 wt% and 0.2 wt%, leveraging GO’s high thermal conductivity (up to 3000 W/m.K) and MXene’s low viscosity and hydrophilicity for enhanced heat transfer and stability. Experiments conducted in Mashhad, Iran, under solar irradiances of 660–1090 W/m 2 , demonstrate that the 0.2 wt% GO-MXene nanofluid reduces thermal resistance by 41.1% (compared to 35.6% for MXene and 28.2% for GO alone), lowers panel temperature by over 24°C (versus 21.2°C for MXene, 15.4°C for GO, and 6.3°C for water), and boosts electrical power output by 14.9% (peaking at 48.3 W versus 42.1 W for the uncooled panel). This results in an additional 43 W/day of electricity generation, outperforming MXene (38.4 W/day), GO (27.3 W/day), and water (16.8 W/day) coolants. First-law electrical efficiency improves to 11.51% (from 10.02% uncooled), while peak exergy efficiency reaches 30.9% (versus 27.4% for MXene, 24.6% for GO, and 22.1% for water). Thermophysical enhancements include a 6% increase in thermal conductivity (to 0.651 W/m.K) with only a 31% viscosity rise (to 1.17 mPa.s), supported by zeta potentials exceeding ± 30 mV for stability. Economic evaluation yields a Levelized Cost of Energy (LCOE) of 0.083 USD/kWh and Levelized Cost of Storage (LCOS) of 0.273 USD/kWh for GO-MXene, balancing superior performance with affordability compared to water (LCOE: 0.071 USD/kWh; LCOS: 0.09 USD/kWh) and other nanofluids (GO LCOE: 0.086 USD/kWh; MXene LCOE: 0.080 USD/kWh). This scalable, surfactant-free system advances sustainable urban solar technologies by mitigating thermal stress, enhancing efficiency, and supporting net-zero energy goals with minimal environmental impact.

Techno-Economic Assessment of Wheat-derived hybrid evaporator with energy-confinement network for high-efficiency solar water purification andCarbon-Neutral concurrent electricity generation

Optimising the operation and design of tidal range schemes is a long-standing and critical problem in their design which also affects their financial feasability. The optimisation process is very time consuming considering its complexity and the number of variables which leads to significant simplifications in the process. Enhancing the efficiency and accuracy of optimisation methods is essential for maximising their energy output. In this study, we propose an efficient tabular dynamic programming for tidal range scheme optimisation by refining the algorithm. Dynamic programming is capable of finding the global optimal solution given that the assumptions used to formulate the optimisation problem are valid. The algorithm refined in this study was tested with two different schemes, namely the West Somerset Lagoon and the North Wales Lagoon in the UK, and demonstrated accurate and efficient prediction of the scheme’s operation. The computational time required by the dynamic programming algorithm was significantly lower than the most promising optimisation approaches used for tidal range schemes, namely Genetic Algorithm, showing potential for real-time application. The refined algorithm includes provisions to simulate tidal range schemes with block formulation to account for the fact that turbines and sluice gates are usually installed in different blocks and are subjected to tidal phase differences. Results demonstrated that optimisation including the multi-block formulation lead to electricity generation up to 6% more annually. • First dynamic programming approach for multi-block tidal range scheme operations. • Operation strategy guaranteed globally optimal. • Tested on West Somerset and North Wales lagoons, with real-time potential.

Utilizing performance-based energy consumption prediction methodology according to zero energy mandate system levels: A study on greenhouse gas reduction scenarios for non-residential buildings in Goyang City, South Korea

Field testing and numerical analysis of pavement-integrated photovoltaic/thermal system (PIPVT)

Integrated evaluation of energy and water use in air-cooled and adiabatic condensers – a case study in an office building

This study presents the long-term performance of a 3.3 kWp semi-transparent photovoltaic (STPV) system using five years (2017-2021) of operational data collected in Gödöllő, Hungary. A comprehensive 4E (energy, exergy, economic, and environmental) framework is applied to quantify system performance under real climatic conditions. The system generated an average yearly electricity production of 2490 kWh, with variability driven by irradiance and temperature fluctuations. Exergy analysis based on Petela model revealed average exergy efficiencies significantly lower than energy efficiency due to spectral mismatch and the partial transmittance inherent to the STPV design. Environmental assessment was conducted using updated life-cycle emission intensities (28-100 g CO 2 eq/kWh and 40-110 g CO 2 eq/kWh), resulting in an embodied carbon range between 1.74 and 6.85 tonnes CO 2 eq across the two literature scenarios. Under three grid emission scenarios (0.35, 0.25, and 0.15 kg CO 2 eq/kWh), carbon payback time (CPT) ranges from 2.0 to 18.3 years. Economic evaluation yielded a levelized cost of electricity (LCOE) ranging from €0.095 to €0.117 per kWh, with a simple payback period of 9.5-11.7 years. The results demonstrate that STPV systems can achieve carbon neutrality within their operational lifetime under grid conditions, although environmental performance remains sensitive to future decarbonisation pathways. The proposed framework provides reproducible methodology for evaluating STPV systems using long-term empirical datasets. • Five-year operational analysis of a 3.3 kWp semi-transparent PV system. • Comprehensive 4E framework applied: energy, exergy, economic, and environmental. • Average annual electricity generation reached 2490 kWh under real climate conditions. • LCOE ranges from €0.095–0.117 kWh with a payback period of 9.5–11.7 years. • Carbon payback time varies between 2.0 and 18.3 years depending on grid emissions. • Results confirm long-term viability of STPV systems for BIPV applications.

High-efficiency evaporation induced electricity generation of wood in seawater

Hydrovoltaic technology can harvest electrical energy from water-solid interactions and has emerged as a promising power solution for wearable electronics due to its broad material compatibility and strong environmental adaptability. However, the selection of flexible substrates and the relatively low interfacial charge separation efficiency still restrict its widespread application. In this work, biomass-derived carbonized silk fabric was utilized as a conductive and flexible substrate, and ordered TiO2 nanowires were grown in situ on the fiber surface to construct an efficient evaporation-driven hydrovoltaic device. Subsequently, reduction-phosphorus doping, asymmetric electrode engineering, and photothermal enhancement were incorporated to regulate surface defect chemistry and establish additional internal fields, thereby promoting charge separation. Impressively, these synergistic optimizations significantly improved the electrical output, ultimately enabling the TiO2-x-P nanowire-based device to achieve a high open-circuit voltage of 868.5 mV and a short-circuit current of 18.6 μA. Additionally, devices encapsulated with plastic film can generate a sustained ∼962 mV output voltage for over 80 h. Furthermore, the device can also function as a self-powered sensor to detect ultraviolet radiation, demonstrating its multifunctionality for future wearable and sensing applications.

Eruptive development of wearable technology has evoked great demand for decentralized energy supplies harvesting ubiquitous environmental stimuli, such as water evaporation. Conventional hydrovoltaic power generators (HPG) collect energy through directional ion migration originating from water gradient in functional materials, while the unsatisfactory electrical output severely hinders the practical applications. Herein, we develop a liquid-induced high-performance all-fiber HPG for sustainable self-powered electronics by constructing an ion-enriched storage electrode and coincidently inducing an oxygen-involved reaction in the solid-liquid-gas interface of the functional layer. Taking advantage of the hierarchical structural configuration of HPG, we verify the dual pathway synergistic electricity generation mechanism of hydrovoltaic effect and oxygen-involved redox through in situ characterization and theoretical calculations. Significantly, the HPG exhibits an impressive power density of 164.5 µW cm-2, an extraordinary current density of 1.25mA cm-2, a high air-permeability of 428.4mm s-1, and an excellent sustainability with high output retention of 88% after 150 cycles of washing, outperforming most of the counterparts. As demonstration of applications, the as-assembled HPG power supply packs can directly drive various wearable electronics without extra energy storage devices or rectification circuits, demonstrating the great expectation for the development of evaporation energy harvesters and self-powered wearable electronics.