Mechanoluminescence (ML) is the non-thermal emission of light as a response to mechanical stimuli on a solid material. While this phenomenon has been observed for a long time when breaking certain materials, it is now being extensively explored, especially since the discovery of non-destructive ML upon elastic deformation. A great number of materials have already been identified as mechanoluminescent, but novel ones with colour tunability and improved sensitivity are still urgently needed. The physical origin of the phenomenon, which mainly involves the release of trapped carriers at defects with the help of stress, still remains unclear. This in turn hinders a deeper research, either theoretically or application oriented. In this review paper, we have tabulated the known ML compounds according to their structure prototypes based on the connectivity of anion polyhedra, highlighting structural features, such as framework distortion, layered structure, elastic anisotropy and microstructures, which are very relevant to the ML process. We then review the various proposed mechanisms and corresponding mathematical models. We comment on their contribution to a clearer understanding of the ML phenomenon and on the derived guidelines for improving properties of ML phosphors. Proven and potential applications of ML in various fields, such as stress field sensing, light sources, and sensing electric (magnetic) fields, are summarized. Finally, we point out the challenges and future directions in this active and emerging field of luminescence research.

: Mechanoluminescence (ML) is the phenomenon describing the emission of light during mechanical action on a solid, leading to applications such as pressure sensing, damage detection and visualization of stress distributions. In most cases, this mechanical action releases energy that was previously stored in the crystal lattice of the phosphor by means of trapped charge carriers. A drawback is the need to record the ML emission during a pressure event. In this work, we provide a method for adding a memory function to these pressure-sensitive phosphors, allowing an optical readout of the location and intensity of a pressure event in excess of 72 h after the event. This is achieved in the BaSi₂O₂N₂:Eu²⁺ phosphor, where a broad trap depth distribution essential for the process is present. By merging optically stimulated luminescence (OSL), thermoluminescence (TL) and ML measurements, the influence of light, heat and pressure on the trap depth distribution is carefully analysed. This analysis demonstrates that mechanical action can not only lead to direct light emission but also to a reshuffling of trap occupations. This memory effect not only is expected to lead to new pressure sensing applications but also offers an approach to study charge carrier transitions in energy storage phosphors.

The performance of persistent phosphors under given charging and working conditions is determined by the properties of the traps that are responsible for these unique properties. Traps are characterized by the height of their associated barrier for thermal detrapping, and a continuous distribution of trap depths is often found in real materials. Accurately determining trap depth distributions is hence of importance for the understanding and development of persistent phosphors. However, extracting the trap depth distribution is often hindered by the presence of a thermal barrier for charging as well, which causes a temperature-dependent filling of traps. For this case, we propose a method for extracting the trap depth distribution from a set of thermoluminescence glow curves obtained at different charging temperatures. The glow curves are first transformed into electron population functions via the Tikhonov regularization, assuming first-order kinetics. Subsequently, the occupation of the traps as a function of their depth, quantified by the so-called filling function, is obtained. Finally, the underlying trap depth distribution is reconstructed from the filling functions. The proposed method provides a substantial improvement in precision and resolution for the trap depth distribution compared with existing methods. This is hence a step forward in understanding the (de)trapping behavior of persistent and storage phosphors.