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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

Amphibious robots, which are expected to move agilely in both land and water environments with huge differences in medium density, have always been a hot spot in the field of robotics. However, limited by the simple structure and drive system, the existing mini‐robots have a relatively single‐movement mode, which limits their ability to move in complex environments. This article fuses two different biomimetic morphological features to create an amphibious mini‐robot: mimicking the body shape and gait of a terrestrial inchworm, and mimicking the superhydrophobic leg shape and gait of an aquatic water strider. The light‐driven approach also brings the advantage of remote wireless manipulation. The mass of the robot is only 8 mg, and it has fast land movement speed (≈0.05 times body length s−1), water surface movement speed (≈0.5 times body length s−1), and some obstacle‐crossing ability (over obstacles of ≈64% of the robot's height). Moreover, the robot can quickly switch from land to water locomotion, which is expected to facilitate emerging applications in various industrial and biomedical settings. An amphibious mini‐robot, which fuses two different biomimetic morphological features, has been proposed and is able to move agilely in both land and water environments. The mini‐robot brings the advantages of remote wireless manipulation, light mass, fast movement speed, and can quickly switch from land to water locomotion, demonstrating its ability to move in complex environments.

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.

In digital pathology, deep learning has been shown to have a wide range of applications, from cancer grading to segmenting structures like glomeruli. One of the main hurdles for digital pathology to be truly effective is the size of the dataset needed for generalization to address the spectrum of possible morphologies. Small datasets limit classifiers’ ability to generalize. Yet, when we move to larger datasets of whole slide images (WSIs) of tissue, these datasets may cause network bottlenecks as each WSI at its original magnification can be upwards of 100 000 by 100 000 pixels, and over a gigabyte in file size. Compounding this problem, high quality pathologist annotations are difficult to obtain, as the volume of necessary annotations to create a classifier that can generalize would be extremely costly in terms of pathologist-hours. In this work, we use Active Learning (AL), a process for iterative interactive training, to create a modified U-net classifier on the region of interest (ROI) scale. We then compare this to Random Learning (RL), where images for addition to the dataset for retraining are randomly selected. Our hypothesis is that AL shows benefits for generating segmentation results versus randomly selecting images to annotate. We show that after 3 iterations, that AL, with an average Dice coefficient of 0.461, outperforms RL, with an average Dice Coefficient of 0.375, by 0.086.

Intense femtosecond laser-plasma interactions can produce high power terahertz radiations. In our experiment, the polished copper target was irradiated by a p-polarized laser with intensity of more than 1018 W/cm2 at an incident angle of 67.5° from the target normal. The THz energy from three different detection angles is measured. The maximum emission is found in the direction at an angle of 45° to the laser backward direction, which is more than one order of magnitude higher than in the other two directions. A simple theoretical model has been established to explain the measurements.

Metabolic diseases are the most common and rapidly growing health issues worldwide. The massive population-based human genetics is crucial for the precise prevention and intervention of metabolic disorders. The China Metabolic Analytics Project (ChinaMAP) is based on cohort studies across diverse regions and ethnic groups with metabolic phenotypic data in China. Here, we describe the centralized analysis of the deep whole genome sequencing data and the genetic bases of metabolic traits in 10,588 individuals from the ChinaMAP. The frequency spectrum of variants, population structure, pathogenic variants and novel genomic characteristics were analyzed. The individual genetic evaluations of Mendelian diseases, nutrition and drug metabolism, and traits of blood glucose and BMI were integrated. Our study establishes a large-scale and deep resource for the genetics of East Asians and provides opportunities for novel genetic discoveries of metabolic characteristics and disorders.

The paper has studied the influence of target material and thickness on energy and angular distributions of the protons generated by using an 800 rim, 60 fs, 0.24 J laser pulse to irradiate solid target foils. The results show that the initial density and thickness of the targets will affect the formation of the acceleration sheath fields in the target normal direction. For the same target thickness, using lower density target materials can obtain a higher proton maximum energy. However, lower density targets tend to be deformed due to the shock waves launched by the laser pulses, making the proton spatial distribution more divergent.