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Transfer printing is a key technology in the fabrication of flexible electronics. Transfer printing method based on curvature provides a simple and effective way to transfer films onto weakly adhesive or even adhesiveless surfaces, overcoming the shortage of traditional transfer printing methods that it is difficult to print functional materials from strong interface to weak interface and can only be applicable to surfaces with certain interfacial strength. So far, the theoretical principle of the curvature‐based transfer printing method has not yet been developed. In this article, a dual‐interface competitive fracture model is established to analyze the mechanism of printing and picking up processes and quantitatively provide the critical transfer printing radius in terms of material and geometric properties of the transfer printing system. This model is verified to be both correct and widely applicable by rich experimental results, providing a new and reliable theory for the fabrication of inorganic flexible electronics. [ABSTRACT FROM AUTHOR]

This paper introduces a class of ferromagnetic, folded, soft composite material for skin-interfaced electrodes with releasable interfaces to stretchable, wireless electronic measurement systems. These electrodes establish intimate, adhesive contacts to the skin, in dimensionally stable formats compatible with multiple days of continuous operation, with several key advantages over conventional hydrogel based alternatives. The reported studies focus on aspects ranging from ferromagnetic and mechanical behavior of the materials systems, to electrical properties associated with their skin interface, to system-level integration for advanced electrophysiological monitoring applications. The work combines experimental measurement and theoretical modeling to establish the key design considerations. These concepts have potential uses across a diverse set of skin-integrated electronic technologies.

The problem that the thermal safety of flexible electronic devices is difficult to evaluate in real time is addressed in this study by establishing a BP neural network (GA-BPNN) temperature prediction model based on genetic algorithm optimisation. The model uses a BP neural network to fit the functional relationship between the input condition and the steady-state temperature of the equipment and uses a genetic algorithm to optimise the parameter initialisation problem of the BP neural network. To overcome the challenge of the high cost of obtaining experimental data, finite element analysis software is used to simulate the temperature results of the equipment under different working conditions. The prediction variance of the GA-BPNN model does not exceed 0.57 °C and has good robustness, as the model is trained according to the simulation data. The study conducted thermal validation experiments on the temperature prediction model for this flexible electronic device. The device reached steady state after 1200 s of operation at rated power. The error between the predicted and experimental results was less than 0.9 °C, verifying the validity of the model's predictions. Compared with traditional thermal simulation and experimental methods, this model can quickly predict the temperature with a certain accuracy and has outstanding advantages in computational efficiency and integrated application of hardware and software. [ABSTRACT FROM AUTHOR]

Vascular disease poses a significant threat to human health. Effective detection methods for quantifying noninvasive arterial wall stiffness enable the early identification of populations exhibiting arteriosclerosis tendencies, providing substantial value for vascular disease prevention and treatment. However, current methods for evaluating arterial stiffness rely on simple tangent stiffness, which is affected by blood pressure fluctuations. This study utilizes a collapse model to investigate arterial deformation and pulse wave propagation under transmural pressure with different arterial wall thicknesses and material properties. Based on the pressure–area relationship of collapsed blood vessels, the relationship between pulse wave velocity and initial bending stiffness at the collapsed state is derived. A method is, then, proposed to evaluate the arterial wall bending stiffness incorporating cuff and photoplethysmography technology for assessing arteriosclerosis. This method is verified through a collapse experiment with a rubber tube and employed in measuring the initial bending stiffness of a human radial artery in vivo. The implementation of this measurement method facilitates vascular stiffness measurements beyond the restriction of tangent modulus and blood pressure changes, offering a quantitative evaluation of arterial wall stiffness. The technique can, therefore, amplify the precision and dependability of preliminary arteriosclerosis lesion diagnostic procedures. [ABSTRACT FROM AUTHOR]