Enhanced mechanically induced red-light emitting novel mechanoluminescence materials for ultrasonic visualization and monitoring applications

Abstract

When Ca2+ is substituted with Sr2+, the optical band gap of (Ca, Sr)ZnOS:Mn2+ becomes narrower and the trap depths becomes deeper, which leads to ML enhanced. The monitoring of ultrasonic intensity was achieved by using this ML material.

Time‐Resolved Bright Red to Cyan Color Tunable Mechanoluminescence from CaZnOS: Bi3+, Mn2+ for Anti‐Counterfeiting Device and Stress Sensor

“…After that the energy is released through non‐radiatively recombine with the holes (process 1), or the energy is directly transferred to luminescent center through the tunneling effect (process 2). [ 52 ] Finally, the cyan emission and red emission were observed owing to the 3 P 1, 0 → 1 S 0 transition of Bi 3+ and the 4 T 1 ( 4 G) → 6 A 1 ( 6 S) transition of Mn 2+ . For Mn Zn 2+ doping in CaZnOS, there is the electronic level stays at 3.522 eV near the bottom of the conduction band.…”

Optical temperature sensing properties and thermoluminescence behavior in Er-modified potassium sodium niobate-based multifunctional ferroelectric ceramics

“…This can be ascribed to the fact that the exchange interaction and nonradiative transition between Er 3+ ions become stronger at high Er 3+ concentrations. 43 Also, the electrons at the 4 F 7/2 level non-radiatively relax to 4 S 3/2 and 4 F 9/2 levels via MPR, and some electrons of the 4 S 3/2 level are filled to the 2 H 11/2 level via thermal agitation (TAG). Finally, electrons relax to the ground state, resulting in green and red radiation.…”

Digital Image Correlation Compatible Mechanoluminescent Skin for Structural Health Monitoring

“…Different classes of ML materials have been discovered and applied in several domains since then, such as displays, mapping of personalized handwriting, pressure memory, ultrasound visualization, and heartbeat monitoring. [ 11–15 ] In the field of fracture mechanics, the potential of ML technology in crack‐tip position identification, crack‐tip effective stress, and strain field visualization in elastic and plastic fields, crack path prediction based on the crack‐tip effective stress field, and hidden crack identification in pressurized hydrogen fuel cells has been demonstrated. [ 16–20 ] However, the problem of calibrating the ML intensity and strain must be addressed before ML technology can be considered a reliable and robust method for structural health monitoring of megastructures and their components.…”