The efficiency droop in GaInN∕GaN multiple-quantum well (MQW) light-emitting diodes is investigated. Measurements show that the efficiency droop, occurring under high injection conditions, is unrelated to junction temperature. Furthermore, the photoluminescence output as a function of excitation power shows no droop, indicating that the droop is not related to MQW efficiency but rather to the recombination of carriers outside the MQW region. Simulations show that polarization fields in the MQW and electron blocking layer enable the escape of electrons from the MQW region and thus are the physical origin of the droop. It is shown that through the use of proper quaternary AlGaInN compositions, polarization effects are reduced, thereby minimizing droop and improving efficiency.

Maximum atom efficiency as well as distinct chemoselectivity is expected for electrocatalysis on atomically dispersed (or single site) metal centres, but its realization remains challenging so far, because carbon, as the most widely used electrocatalyst support, cannot effectively stabilize them. Here we report that a sulfur-doped zeolite-templated carbon, simultaneously exhibiting large sulfur content (17 wt% S), as well as a unique carbon structure (that is, highly curved three-dimensional networks of graphene nanoribbons), can stabilize a relatively high loading of platinum (5 wt%) in the form of highly dispersed species including site isolated atoms. In the oxygen reduction reaction, this catalyst does not follow a conventional four-electron pathway producing H2O, but selectively produces H2O2 even over extended times without significant degradation of the activity. Thus, this approach constitutes a potentially promising route for producing important fine chemical H2O2, and also offers opportunities for tuning the selectivity of other electrochemical reactions on various metal catalysts.

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Recent advances of plasmonic nanoparticles include fascinating developments in the fields of energy, catalyst chemistry, optics, biotechnology, and medicine. The plasmonic photothermal properties of metallic nanoparticles are of enormous interest in biomedical fields because of their strong and tunable optical response and the capability to manipulate the photothermal effect by an external light source. To date, most biomedical applications using photothermal nanoparticles have focused on photothermal therapy; however, to fully realize the potential of these particles for clinical and other applications, the fundamental properties of photothermal nanoparticles need to be better understood and controlled, and the photothermal effect‐based diagnosis, treatment, and theranostics should be thoroughly explored. This Progress Report summarizes recent advances in the understanding and applications of plasmonic photothermal nanoparticles, particularly for sensing, imaging, therapy, and drug delivery, and discusses the future directions of these fields.

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Hot electron chemistry has drawn tremendous attention from applications related to materials, energy, sensing, and catalysis. The plasmon‐induced generation of hot electrons and their transfer behavior are very important for understanding plasmonic‐enhanced applications and for achieving practically useful efficiency. From a plasmonic perspective, well‐designed plasmonic structures that can manipulate surface plasmons are able to enhance the efficiencies of hot electron‐based processes. This progress report summarizes the recent experimental and theoretical advances on the hot electron effect, emphasizing the crucial role of surface plasmons that are highly designable by using metal nanostructures. In particular, recent breakthroughs in the emerging fields of heterogeneous catalysis based on the hot electron effect are highlighted. Important design principles, mechanisms, and concepts, as well as challenges and perspectives, are illustrated and discussed.

Emulating the biological visual perception system typically requires a complex architecture including the integration of an artificial retina and optic nerves with various synaptic behaviors. However, self‐adaptive synaptic behaviors, which are frequently translated into visual nerves to adjust environmental light intensities, have been one of the serious challenges for the artificial visual perception system. Here, an artificial optoelectronic neuromorphic device array to emulate the light‐adaptable synaptic functions (photopic and scotopic adaptation) of the biological visual perception system is presented. By employing an artificial visual perception circuit including a metal chalcogenide photoreceptor transistor and a metal oxide synaptic transistor, the optoelectronic neuromorphic device successfully demonstrates diverse visual synaptic functions such as phototriggered short‐term plasticity, long‐term potentiation, and neural facilitation. More importantly, the environment‐adaptable perception behaviors at various levels of the light illumination are well reproduced by adjusting load transistor in the circuit, exhibiting the acts of variable dynamic ranges of biological system. This development paves a new way to fabricate an environmental‐adaptable artificial visual perception system with profound implications for the field of future neuromorphic electronics.

We model the carrier recombination mechanisms in GaInN/GaN light-emitting diodes as R=An+Bn2+Cn3+f(n), where f(n) represents carrier leakage out of the active region. The term f(n) is expanded into a power series and shown to have higher-than-third-order contributions to the recombination. The total third-order nonradiative coefficient (which may include an f(n) leakage contribution and an Auger contribution) is found to be 8×10−29 cm6 s−1. Comparison of the theoretical ABC+f(n) model with experimental data shows that a good fit requires the inclusion of the f(n) term.