Water drops sliding over insulating and hydrophobic surfaces can accumulate electric charge. Consequently, the solid surfaces underneath a drop acquire opposite charges, a process referred to as slide1,2 or contact electrification, analogous to triboelectricity between solids3. It is not clear how charges are transferred, given that bringing a unit charge from the solid–water interface to the free solid surface is highly energetically unfavourable. Unlike solid tribocharging, where high shear stresses easily break chemical bonds at asperities4,5, the contact line of a drop is soft. While the charging of drops has been recognized for over a century6,7, quantitative experiments have been scarce until recently. In the past decade protocols have emerged to quantify this charging of sliding drops8,9,10,11. Understanding the mechanisms behind water drop electrification is essential to understanding dynamic wetting and has major implications for many areas related to condensation, energy generation, printing and desalination12,13,14. Despite extensive efforts, the microscopic origin of charge transfer in slide electrification remains debated15,16,17. For liquid water, the prevailing view attributes charging primarily to surface charges, which form spontaneously at the water–solid interface. The bound surface charges are usually formed by the dissociation of surface groups such as amino groups18 or the adsorption of ions...

Japanese researchers have turned ordinary laser-printed toner and plastic into a touch-sensitive interface that can recognize finger movements, commands, and even individual users.

Static electricity secrets may explain planet formation

Water-solid friction produces clean and durable electricity upon environmental excitation. By revealing and overcoming the fundamental limitations of liquid-solid triboelectricity, a switch-enhanced generator achieves high energy output, good load adaptability, and can harvest energy from multiple scenarios to power electronics.

#solarpunksunday #solarpunk #solar Researchers “created a hybrid device that can generate energy from both sunlight and rainfall at the same time.” The rain actually hitting the solar panels generates electricity. 🫨 https://scitechdaily.com/this-breakthrough-solar-panel-generates-power-from-both-sunlight-and-raindrops/

This familiar phenomenon has puzzled researchers for centuries, but experiments are finally making sense of its unruly behaviors

We propose a microphysical theory of the triboelectric effect by which mechanical rubbing separates charges across the interface between two surfaces. Surface electrons are treated as an open system, ...

Human skin inherently forms a body-coupled triboelectric circuit that enables the generation of triboelectric charges through contact between the skin surface and various materials. Integrated with an on-finger, substrate-free microfiber electrode, the material-specific and personalized triboelectric signals can be imperceptibly collected for machine learning-based material identification, advancing the paradigm for human tactile augmentation. Abstract Harnessing intrinsic triboelectric signals from human skin holds promise for enhancing tactile perception. However, collecting these signals without disrupting normal skin functions and convoluting motion artifacts remains challenging. Additionally, person-to-person signal variance complicates data processing. In this study, it is demonstrated that triboelectric signals generated from touch can be imperceptibly collected and processed using a machine learning model to achieve tactile augmentation. When one hand contacts and rubs against a target object, charge transfer occurs between the skin and the object's surface. By placing a substrate-less microfiber electrode on the finger of the other hand, a body-coupled triboelectric circuit is formed to collect these signals, which contain material-specific features such as amplitude and peak ratio. A machine learning technique is developed to process the triboelectric signals, enabling the classification of six different materials with a prediction accuracy of ≈95%. The material differentiation model is further validated across different users, achieving an overall accuracy of ≈88 %, illustrating the potential of utilizing the body-coupled triboelectric circuit for tactile augmentation.

Publication date: Available online 15 May 2025 Source: Advanced Powder Materials Author(s): Mandar Vasant Paranjape, Punnarao Manchi, Harishkumarreddy Patnam, Anand Kurakula, Venkata Siva Kavarthapu, Jae Su Yu