Abstract Birds have developed near-perfect structures and functionality over millions of years of natural evolution. To improve the efficiency of fixed-wing vehicles in different environments, researchers have developed deformable wings inspired by the wing structures of birds. Shape Memory Alloy (SMA) is applied as a smart material to the deformable wing. Compared with other drive methods, SMA actuators have the advantages of high drive capacity and a simple structure for driving wing deformation. According to the shape memory effect, SMA actuators are classified as single-range and dual-range actuators. The wing structure designed for each SMA drive is unique. By comparing and analyzing the structures of airfoils, airfoils with similar drive forms and deformation structures are put together for review and discussion. The deformable wings are categorized into out-of-face deformation, in-face deformation, airfoil curvature deformation, and combined deformation with multiple degrees of freedom based on the structure and location of the wing that produces the deformation. An overview of the deformed wing is introduced by telling the bionic theory of seagulls. The principles of deformation of the wing, the mechanics of the SMA actuator mechanism, and the aerodynamic characteristics of the deformable wing are presented. The structure and working principle of SMA actuators for each type of deformable wing are explained in detail. Methods and approaches to study the deformability of deformable wings are analyzed and summarized. This work provides comprehensive insights and perspectives for future studies of SMA-driven deformable airfoils.

Abstract Detecting and distinguishing infrared radiation for non-invasive medical diagnostic purposes has been attempted for basic surface temperature assessment since the middle of the 20th century. However, the long wavelength and low energy of infrared radiation impede the detection of signals from deeper tissue layers, significantly limiting its use in diagnostics. To overcome these limitations, a novel approach was developed by combining a semiconductor gallium arsenide chip and prism-based optics that enabled the detection of signals in the infrared and terahertz spectrum. Challenges related to penetration depth and thermal noises were addressed by neural network modelling.