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The continuous energy-harvesting in moisture environment is attractive for the development of clean energy source. Controlling the transport of ionized mobile charge in intelligent nanoporous membrane systems is a promising strategy to develop the moisture-enabled electric generator. However, existing designs still suffer from low output power density. Moreover, these devices can only produce short-term (mostly a few seconds or a few hours, rarely for a few days) voltage and current output in the ambient environment. Here, we show an ionic diode–type hybrid membrane capable of continuously generating energy in the ambient environment. The built-in electric field of the nanofluidic diode-type PN junction helps the selective ions separation and the steady-state one-way ion charge transfer. This directional ion migration is further converted to electron transportation at the surface of electrodes via oxidation-reduction reaction and charge adsorption, thus resulting in a continuous voltage and current with high energy conversion efficiency. Energy harvesting of humidity present in air can be used for the development of clean energy sources and self-sustained systems. The authors propose a nanofluid energy conversion system with integrated ionic diode-type hybrid membrane for energy generation in environmental moisture.

Water and ion channels are crucial for moisture energy harvesting, requiring precise pore design for mass transfer control. However, the key challenge lies in managing the localized assembly process of membrane materials to arrange them orderly, forming confined mass transfer pathways and stable solid-liquid interfaces. This is essential for exploring the interrelationship among channel morphological characteristics, mass transfer dynamics, and device power generation performance. This work proposes the use of freeze-assisted salting-out to meticulously construct hydrogel bilayer membranes with micro-meso-macroporous oriented channels and asymmetric charge characteristics. The produced polyvinyl alcohol/MXene hydrogel devices achieved a V oc × J sc of 11.4 μW cm −2 (pure hydrovoltaic effect) and 146 μW cm −2 (with active electrodes) at 25 °C, 45%RH, surpassing most moisture-based generators. In addition, the power generation performance is highly consistent with the Hofmeister series, with stronger salting-out effect to obtain more micropores and mesopores, and ice crystal growth can help obtain ordered macropores. It has faster water transport rate, higher ionic conductivity, better ionic selectivity, and stronger channel stability than traditional moisture-based power generation membranes. This relationship between pore tuning from salt ions and device power generation performance provides a design basis for the development of high-performance moisture-based power generators. The regulation of water and ion channels is crucial for moisture energy harvesting. The authors adopt a directional freezing-assisted salting-out method to finely adjust the cross-scale pore structure of ion channels, achieving efficient moisture energy harvesting.

Harvesting the energy from the interaction between hygroscopic materials and atmospheric water can generate green and clean energy. However, the ion diffusion process of moisture-induced dissociation leads to the disappearance of the ion concentration gradient gradually, and there is still a lack of moisture-based power generation devices with truly continuous operation, especially the duration of the current output still needs to be extended. Here, we propose a design for reconstructing the ion concentration gradient by coupling photocatalytic hydrogen evolution reaction with hydrovoltaic effect, to report a moisture-enabled electric generator (MEG) with continuous current output. We show that the introduction of the photocatalytic layer not only absorbs light energy to greatly increase the power generation of the MEG (500% power density enhancement), but more importantly, the photocatalytic hydrogen evolution process consumes the pre-stacked ions to restore the ion concentration gradient, allowing the MEG to continuously output current for more than 600 hours, which is 1 to 2 orders of magnitude higher than the great majority of existed MEGs in terms of the current output duration. This study designs a moisture-enabled electric generator (MEG) with a photocatalytic layer, achieving a 500% power density enhancement and continuous current output for over 600 hours, addressing the challenge of extended operation duration

Moisture-induced ion diffusion in nanostructured materials is a promising route for high-performance power generation, yet achieving the continuous ion migration necessary for long-term operation remains challenging. Here, we report a moisture-electricity conversion mechanism capable of sustained electrical output. We demonstrate that humidity fluctuations regulate the dynamic coordination between iodide ions (I - ) and iodine molecules (I 2 ), driving the oscillatory migration of I - to generate a continuous alternating ion current (AC). Crucially, this coordination process avoids charge exchange, while electricity generation is achieved through moisture-driven ion transport. The device achieves a current output of 33.2 µA cm - ² and exhibits sustainable performance recovery under natural humidity fluctuations. This mechanism remains effective even under minimal humidity gradients (13% RH), ensuring adaptability to diverse weather conditions. Our strategy, applicable to various gel materials, utilizes environmental humidity fluctuations as a power source for ion diffusion, offering a fundamental solution for long-term, autonomous energy harvesting. This study reveals a mechanism where humidity-driven dynamic coordination between iodide ions and iodine molecules enables sustained oscillatory ion migration, providing a robust solution for continuous ambient energy harvesting

Considerable efforts have recently been made to augment the power density of moisture‐enabled electric generators. However, due to the unsustainable ion/water molecule concentration gradients, the ion‐directed transport gradually diminishes, which largely affects the operating lifetime and energy efficiency of generators. This work introduces an electrode chemistry regulation strategy into the ionic diode‐type energy conversion structure, which demonstrates 1240 h power generation in ambient humidity. The electrode chemical regulation can be achieved by adding Cl−. The purpose is to destroy the passivation film on the electrode interface and provide a continuous path for ion‐electron coupling conduction. Moreover, this device simultaneously satisfies the requirements of fast trapping of moisture molecules, high rectification ratio transport of ions, and sustained ion‐to‐electron current conversion. A single device can deliver an open‐circuit voltage of about 1 V and a peak short‐circuit current density of 350 µA cm−2. Finally, the first‐principle calculations are carried out to reveal the mechanism by which the electrode surface chemistry affects the power generation performance. A moisture‐enabled electric generator for power generation at high humidity for 1240 h is presented. The device simultaneously meets the requirements of fast capture of moisture molecules, high rectification ratio transport of ions, and sustained ion‐electron current conversion, and also provides a reliable solution for ultra‐long‐time humidity power generation.

The NutriLight system presents a novel dietary approach designed to enhance health communication, promote sustainable eating habits, and address limitations in existing dietary patterns. Using a traffic light scoring system, it simplifies dietary recommendations, making them more accessible and adaptable across diverse populations. Unlike rigid diets, NutriLight categorises foods into green, yellow, and red groups, encouraging balance rather than restriction. This flexibility allows for cultural adaptations, ensuring relevance in different dietary contexts while supporting planetary health. Additionally, NutriLight mitigates the risk of nutrient deficiencies by emphasising whole, minimally processed foods and reducing overconsumption of unhealthy options. While promising, its effectiveness depends on proper implementation, localised adaptation, and long-term evaluation to confirm its health benefits. By bridging the gap between nutritional science and practical application, NutriLight has the potential to serve as an effective tool in public health nutrition, fostering healthier and more sustainable dietary choices worldwide.

Water salinity is a key characteristic of natural lakes, with its spatial and vertical variations altering water density and affecting aquatic organisms. Traditional lake water salinity monitoring, reliant on in-situ measurements, has limited the comprehensive exploration of both horizontal and vertical water salinity distribution, thereby hindering accurate characterization of volumetric water salinity and total salt content within the entire lake. To address this, our study introduces a novel framework for volumetric salinity estimation, using Pung Co, a deep endorheic lake on the Tibetan Plateau (TP), as a case study. First, we developed a model using machine learning algorithms, with remote sensing data and hydrological and topographical features, to estimate surface water salinity. Secondly, we analyzed field-surveyed vertical water salinity profiles to model the relationship between lake water depth and salinity, revealing the vertical water salinity variation characteristics. Finally, we constructed a gridded water column method to precisely estimate the lake's total salt content. Results showed that the extreme gradient boosting model (R 2  = 0.85, RMSE = 0.13 g/L, MAPE = 0.91%) effectively estimated surface water salinity. The modeled water salinity was characterized by significant horizontal and vertical variability. Horizontally, the water salinity was higher in the north and west and lower in the south and east, with a lake-wide average of 10.91 g/L. Vertically, the water salinity was strongly influenced by depth, exhibiting a sharp change near the thermocline before stabilizing. When surface water salinity was below 11.20 g/L, it increased with depth. When surface water salinity exceeded 11.20 g/L, it decreased with depth, with both converging toward a stable value of approximately 11.20 g/L. Using our gridded approach, the total dissolved salt content in Pung Co was estimated to be approximately 4.51 × 10 7 tons. This study establishes a quantitative framework that shifts salinity estimation from a two-dimensional surface assessment to a three-dimensional volumetric estimation, offering significant implications for understanding microbial diversity and the ecological effects of salinity stratification in high-altitude deep lakes.

The timing regimes of precipitation can exert profound impacts on grassland ecosystems. However, it is still unclear how the peak aboveground biomass (AGBpeak) of alpine grasslands responds to the temporal variability of growing season precipitation (GSP) on the northern Tibetan Plateau. Here, the temporal variability of precipitation was defined as the number and intensity of precipitation events as well as the time interval between consecutive precipitation events. We conducted annual field measurements of AGBpeak between 2009 and 2016 at four sites that were representative of alpine meadow, meadow-steppe, alpine steppe, and desert-steppe. Thus, an empirical model was established with the time series of the field-measured AGBpeak and the corresponding enhanced vegetation index (EVI) (R2 = 0.78), which was used to estimate grassland AGBpeak at the regional scale. The relative importance of the three indices of the temporal variability of precipitation, events, intensity, and time interval on grassland AGBpeak was quantified by principal component regression and shown in a red–green–blue (RGB) composition map. The standardized importance values were used to calculate the vegetation sensitivity index to the temporal variability of precipitation (VSIP). Our results showed that the standardized VSIP was larger than 60 for only 15% of alpine grassland pixels and that AGBpeak did not change significantly for more than 60% of alpine grassland pixels over the past decades, which was likely due to the nonsignificant changes in the temporal variability of precipitation in most pixels. However, a U-shaped relationship was found between VSIP and GSP across the four representative grassland types, indicating that the sensitivity of grassland AGBpeak to precipitation was dependent on the types of grassland communities. Moreover, we found that the temporal variability of precipitation explained more of the field-measured AGBpeak variance than did the total amount of precipitation alone at the site scale, which implies that the mechanisms underlying how the temporal variability of precipitation controls the AGBpeak of alpine grasslands should be better understood at the local scale. We hypothesize that alpine grassland plants promptly respond to the temporal variability of precipitation to keep community biomass production more stable over time, but this conclusion should be further tested. Finally, we call for a long-term experimental study that includes multiple natural and anthropogenic factors together, such as warming, nitrogen deposition, and grazing and fencing, to better understand the mechanisms of alpine grassland stability on the Tibetan Plateau.