Mechanoluminescence(ML)is bringing a paradigm-shifting for next-generation lightbased human–robot interaction.However,the overlooked character of ML temporal dynamic response remains a critical barrier to overcoming ...Mechanoluminescence(ML)is bringing a paradigm-shifting for next-generation lightbased human–robot interaction.However,the overlooked character of ML temporal dynamic response remains a critical barrier to overcoming the limitation of mechanooptical conversion efficiency.Here,by resolving the dynamic interplay among stimuli rate,interfacial charge accumulation and ML performance of three typical materials,like ZnS:Cu^(2+),SrAl_(2)O_(4):Eu^(2+),Dy^(3+),Y_(3)Al_(5)O_(12):Ce^(3+),the cognition of ML has been deeply understand.Obviously,the ML performance is predominantly governed by the crosscoupling of stimuli rate and stimuli time rather than absolute stress magnitude.For the first time,the optimal stretching stimulation rate for commercial ZnS:Cu^(2+),SrAl_(2)O_(4):Eu^(2+),Dy^(3+)and Y_(3)Al_(5)O_(12):Ce^(3+)are respectively determined as~10.3 Mpa/s,~11.0 Mpa/s,~31.9 Mpa/s,which is of great significance for obtaining high-performance ML behavior,and an ubiquitous ML hysteresis phenomenon is demonstrated originating from a time-consuming mechano-electro-optical conversion process even existing in trap-controlled SrAl_(2)O_(4):Eu^(2+),Dy^(3+).Moreover,a qualitative relationship for ML brightness(MLB),stimuli rate(sr),stimuli time(st),inherent interfacial triboelectricity coefficient(iitre)and relative interfacial triboelectricity coefficient(ritre)is established as ML B=f(sr)*g(st)*p(iitre)*q(ritre)for guiding the design of ML elastomers.For instance,based on this equation,a topology-optimized Y_(3)Al_(5)O_(12):Ce^(3+)@polydimethylsiloxane(PDMS)elastomer is engineered,achieving unprecedented 693 times brighter emission,78%lower stress threshold and 20%lighter weight,which is successfully applied in remote control(~450 m)of quadruped robot.Three main contributions of this work include:(i)demonstrating the influence law of temporal dynamic stimulation on ML performance.(ii)resolving long-standing mechano-optical asynchrony debates.(iii)establishing a universal guideline for designing high-performance ML platforms.展开更多
基金financially supported by National Natural Science Foundation of China(U24A20307,12304460).
文摘Mechanoluminescence(ML)is bringing a paradigm-shifting for next-generation lightbased human–robot interaction.However,the overlooked character of ML temporal dynamic response remains a critical barrier to overcoming the limitation of mechanooptical conversion efficiency.Here,by resolving the dynamic interplay among stimuli rate,interfacial charge accumulation and ML performance of three typical materials,like ZnS:Cu^(2+),SrAl_(2)O_(4):Eu^(2+),Dy^(3+),Y_(3)Al_(5)O_(12):Ce^(3+),the cognition of ML has been deeply understand.Obviously,the ML performance is predominantly governed by the crosscoupling of stimuli rate and stimuli time rather than absolute stress magnitude.For the first time,the optimal stretching stimulation rate for commercial ZnS:Cu^(2+),SrAl_(2)O_(4):Eu^(2+),Dy^(3+)and Y_(3)Al_(5)O_(12):Ce^(3+)are respectively determined as~10.3 Mpa/s,~11.0 Mpa/s,~31.9 Mpa/s,which is of great significance for obtaining high-performance ML behavior,and an ubiquitous ML hysteresis phenomenon is demonstrated originating from a time-consuming mechano-electro-optical conversion process even existing in trap-controlled SrAl_(2)O_(4):Eu^(2+),Dy^(3+).Moreover,a qualitative relationship for ML brightness(MLB),stimuli rate(sr),stimuli time(st),inherent interfacial triboelectricity coefficient(iitre)and relative interfacial triboelectricity coefficient(ritre)is established as ML B=f(sr)*g(st)*p(iitre)*q(ritre)for guiding the design of ML elastomers.For instance,based on this equation,a topology-optimized Y_(3)Al_(5)O_(12):Ce^(3+)@polydimethylsiloxane(PDMS)elastomer is engineered,achieving unprecedented 693 times brighter emission,78%lower stress threshold and 20%lighter weight,which is successfully applied in remote control(~450 m)of quadruped robot.Three main contributions of this work include:(i)demonstrating the influence law of temporal dynamic stimulation on ML performance.(ii)resolving long-standing mechano-optical asynchrony debates.(iii)establishing a universal guideline for designing high-performance ML platforms.
