Flexible positive pressure sensors have been studied extensively and have been used in a lot of scenarios. However, negative pressure detection is also in demand in some scenarios, such as fluid mechanics analysis, air pressure sensing, and so on. Flexible wearable sensors that can detect both positive and negative pressures will greatly broaden the application field. In this paper, we report a flexible highly sensitive ionic gel (IG) pressure sensor, which is simple and of low cost to prepare and can reliably detect a large pressure range from -98 to 100 kPa under an atmospheric pressure of about 982 hPa. The IG dielectric layer is composed of polyvinyl alcohol and phosphoric acid with a random microstructure of sandpaper inversion. The sensor exhibits flexibility, cycling stability, and high sensitivity under both negative and positive pressures (S = 84.45 nF/kPa for the negative pressure section, S = 25.61 nF/kPa for the positive pressure section). These sensors could be worn on the body not only to test breathing and pulse but also to measure air pressure for estimating the altitude, showing that the flexible full-pressure sensors have a wider application range in wearable electronics.

Ubiquitous moisture is of particular attraction for sustainable power generation. However, rigorous assembly procedures limit the effi-cient large-scale integration for moisture-enabled electric genera-tors (MEGs). Herein, we develop fully printed planar MEG (PMEG) arrays using modulated polycation and polyanion inks, which maxi-mize access to moisture and make it free of strict assembly and de-vice packaging. Thus, a PMEG unit (only 0.3 cm2) generates an open -circuit voltage of up to 1.1 V, along with a power density of 2.6 mW cm -2. A small piece of sheet with 200 PMEG units offers a maximum voltage of 200 V and a current of 1.3 mA. A standard power module is constructed to meet the on-demand power supply requirements of compact electronics. Furthermore, scalable and customizable PMEG arrays can be compatibly integrated with flexible circuits, as demonstrated by a fully printed self-powered functional system including PMEG arrays and energy-storage and electrochromic devices.

Simultaneous multimodal monitoring can greatly perceive intricately multiple stimuli, which is important for the understanding and development of a future human-machine fusion world. However, the integrated multisensor networks with cumbersome structure, huge power consumption, and complex preparation process have heavily restricted practical applications. Herein, a graphene oxide single-component multimodal sensor (GO-MS) is developed, which enables simultaneous monitoring of multiple environmental stimuli by a single unit with unique moist-electric self-power supply. This GO-MS can generate a sustainable moist-electric potential by spontaneously adsorbing water molecules in air, which has a characteristic response behavior when exposed to different stimuli. As a result, the simultaneous monitoring and decoupling of the changes of temperature, humidity, pressure, and light intensity are achieved by this single GO-MS with machine-learning (ML) assistance. Of practical importance, a moist-electric-powered human-machine interaction wristband based on GO-MS is constructed to monitor pulse signals, body temperature, and sweating in a multidimensional manner, as well as gestures and sign language commanding communication. This ML-empowered moist-electric GO-MS provides a new platform for the development of self-powered single-component multimodal sensors, showing great potential for applications in the fields of health detection, artificial electronic skin, and the Internet-of-Things.

Harvesting energy from spontaneous water flow within artificial nanochannels is a promising route to meet sustainable power requirements of the fast-growing human society. However, large-scale nanochannel integration and the multi-parameter coupling restrictive influence on electric generation are still big challenges for macroscale applications. In this regard, long-range (1 to 20 cm) ordered graphene oxide assembled framework with integrated 2D nanochannels have been fabricated by a rotational freeze-casting method. The structure can promote spontaneous absorption and directional transmission of water inside the channels to generate considerable electric energy. A transfer learning strategy is implemented to address the complicated multi-parameters coupling problem under limited experimental data, which provides highly accurate performance optimization and efficiently guides the design of 2D water flow enabled generators. A generator unit can produce ~2.9 V voltage or ~16.8 μA current in a controllable manner. High electric output of ~12 V or ~83 μA is realized by connecting several devices in series or parallel. Different water enabled electricity generation systems have been developed to directly power commercial electronics like LED arrays and display screens, demonstrating the material's potential for development of water enabled clean energy.

Simulation of the dynamics of physical systems is essential to the development of both science and engineering. Recently there is an increasing interest in learning to simulate the dynamics of physical systems using neural networks. However, existing approaches fail to generalize to physical substances not in the training set, such as liquids with different viscosities or elastomers with different elasticities. Here we present a machine learning method embedded with physical priors and material parameters, which we term as "Graph-based Physics Engine" (GPE), to efficiently model the physical dynamics of different substances in a wide variety of scenarios. We demonstrate that GPE can generalize to materials with different properties not seen in the training set and perform well from single-step predictions to multi-step roll-out simulations. In addition, introducing the law of momentum conservation in the model significantly improves the efficiency and stability of learning, allowing convergence to better models with fewer training steps.

Ultralight, ultrastrong, and supertough graphene aerogel metamaterials combining with multi-functionalities are promising for future military and domestic applications. However, the unsatisfactory mechanical performances and lack of the multiscale structural regulation still impede the development of graphene aerogels. Herein, we demonstrate a laser-engraving strategy toward graphene meta-aerogels (GmAs) with unusual characters. As the prerequisite, the nanofiber-reinforced networks convert the graphene walls’ deformation from the microscopic buckling to the bulk deformation during the compression process, ensuring the highly elastic, robust, and stiff nature. Accordingly, laser-engraving enables arbitrary regulation on the macro-configurations of GmAs with rich geometries and appealing characteristics such as large stretchability of 5400% reversible elongation, ultralight specific weight as small as 0.1 mg cm −3 , and ultrawide Poisson’s ratio range from −0.95 to 1.64. Additionally, incorporating specific components into the pre-designed meta-structures could further achieve diversified functionalities.

Island-bridge architectures represent a widely used structural design in stretchable inorganic electronics, where deformable interconnects that form the bridge provide system stretchability, and functional components that reside on the islands undergo negligible deformations. These device systems usually experience a common strain concentration phenomenon, i.e., "island effect", because of the modulus mismatch between the soft elastomer substrate and its on-top rigid components. Such an island effect can significantly raise the surrounding local strain, therefore increasing the risk of material failure for the interconnects in the vicinity of the islands. In this work, a systematic study of such an island effect through combined theoretical analysis, numerical simulations and experimental measurements is presented. To relieve the island effect, a buffer layer strategy is proposed as a generic route to enhanced stretchabilities of deformable interconnects. Both experimental and numerical results illustrate the applicability of this strategy to 2D serpentine and 3D helical interconnects, as evidenced by the increased stretchabilities (e.g., by 1.5 times with a simple buffer layer, and 2 times with a ring buffer layer, both for serpentine interconnects). The application of the patterned buffer layer strategy in a stretchable light emitting diodes system suggests promising potentials for uses in other functional device systems.

This study demonstrates an all-region-applicable moist-electric generator (MEG) based on a highly hydrophilic graphene oxide composite, delivering considerable electric energy over a wide temperature (−25 °C to 50 °C) and relative humidity range (RH, 5–95%).

Water shortage is a serious, long-standing global issue that urgently needs to be solved. Recently, various kinds of techniques have been developed for the treatment of wastewater. Among them, solar thermal conversion of steam generation is a green and sustainable approach for regeneration of clean water. Herein, we develop the solar steam generator based on the defect-abundant graphene sheets for highly efficient production of clean water with high rejection of ions, organic media, and bacteria. The thermal conductivity of defect-abundant graphene aerogel is as low as 0.0075 W m(-1) K-1 with a record surface temperature of up to ca 90 degrees C under only 1 sun, which thus promotes a high water evaporation rate of 1.78 k gm(-2) h(-1). Efficient production of clean water with high rejection of ions, oil and bacteria is demonstrated, which proved the possibility for a one-step production of drinkable water from the water sources of the sea, lake, and emulsified oil/water mixtures.

Three-dimensional water evaporation is proposed based on highly vertically ordered pillar array of graphene-assembled framework (HOPGF). A high evaporation rate of 2.10 kg m−2 h−1 is achieved (1 sun). This efficient SSG system has been applied to wastewater purification, solar water heater and housing self-supply water system.

Low modulus, compliant systems of sensors, circuits and radios designed to intimately interface with the soft tissues of the human body are of growing interest, due to their emerging applications in continuous, clinical-quality health monitors and advanced, bioelectronic therapeutics. Although recent research establishes various materials and mechanics concepts for such technologies, all existing approaches involve simple, two-dimensional (2D) layouts in the constituent micro-components and interconnects. Here we introduce concepts in three-dimensional (3D) architectures that bypass important engineering constraints and performance limitations set by traditional, 2D designs. Specifically, open-mesh, 3D interconnect networks of helical microcoils formed by deterministic compressive buckling establish the basis for systems that can offer exceptional low modulus, elastic mechanics, in compact geometries, with active components and sophisticated levels of functionality. Coupled mechanical and electrical design approaches enable layout optimization, assembly processes and encapsulation schemes to yield 3D configurations that satisfy requirements in demanding, complex systems, such as wireless, skin-compatible electronic sensors.