C60‐based thin‐film transistors are fabricated through solution processing. On rigid indium tin oxide glass, the transistors display electron mobilities as high as 0.21 cm2 V−1 s−1 and a threshold voltage of 0.7 V, only slightly lower than those of organic thin‐film transistors prepared through vacuum deposition. On ITO‐coated PET substrates, the mobilities in the flexible devices (see image) are approximately one order of magnitude lower than those of devices prepared on rigid glass substrates.

In this study we used convergent syntheses to prepare two novel acceptor-donor-acceptor (A-D-A) small molecules (BT4OT, BT6OT), each containing an electron-rich benzotrithiophene (BT) unit as the core, flanked by octylthiophene units, and end-capped with electron-deficient cyanoacetate units. The number of octylthiophene units affected the optical, electrochemical, morphological, and photovoltaic properties of BT4OT and BT6OT. Moreover, BT4OT and BT6OT possess low-energy highest occupied molecular orbitals (HOMOs), providing them with good air stability and their bulk heterojunction (BHJ) photovoltaic devices with high open-circuit voltages (V oc ). A solar cell device containing BT6OT and [6,6]-phenyl-C 71 -butyric acid methyl ester (PC 71 BM) in a 1 : 0.75 ratio (w/w) exhibited a power conversion efficiency (PCE) of 3.61% with a short-circuit current density (J sc ) of 7.39 mA cm À2 , a value of V oc of 0.88 V, and a fill factor (FF) of 56.9%. After adding 0.25 vol% of 1-chloronaphthalene (CN) as a processing additive during the formation of the blend film of BT6OT:PC 71 BM (1 : 0.75, w/w), the PCE increased significantly to 5.05% with values of J sc of 9.94 mA cm À2 , V oc of 0.86 V, and FF of 59.1% as a result of suppressed nanophase molecular aggregation.

Decomposition-based evolutionary multi-objective optimization algorithms decompose a multi-objective optimization problem into subproblems using a set of predefined reference points. The convergence is guaranteed by optimizing the single-objective or simplified multi-objective subproblems while the diversity is handled by the evenly distributed reference points. Nevertheless, studies have shown that the performance of decomposition-based algorithms is strongly dependent on the Pareto front shapes due to unadaptable reference points and subproblem formulation. In this paper, we investigate the causes from three aspects and propose a learning-to-decompose paradigm consisting of a learning module and an optimization module to address these issues. Specifically, given the current non-dominated solutions from the optimization module, which can be any decomposition-based multi-objective optimizer, the learning module learns an analytical model that characterizes the estimated PF. Thereafter, useful information are extracted from the learned model to guide the decomposition in the optimization module. In particular, we utilize the learned model to sample reference points compliant to the PF and formulate subproblems with appropriate contours and search directions according to the current status. We integrate the learning-todecompose paradigm with two most popular decompositionbased evolutionary optimizers, i.e., MOEA/D and NSGA-III, and compare them with several state-of-the-art adaptive methods. The comprehensive experiments validate the effectiveness and robustness of the proposed paradigm on 14 test problems with various Pareto front shapes.

Micro‐LEDs are regarded as ideal light sources for next‐generation display and high‐speed visible‐light communication (VLC). However, the conventional micro‐LEDs based on InGaN quantum well (QW) active region suffer from a low efficiency under small injection (below 1 A cm−2) due to the size‐dependent effect and a limited 3 dB bandwidth (hundreds of MHz) due to quantum‐confined Stark effect. Here, InGaN quantum dots (QDs) are proposed as the active region of micro‐LEDs to address these challenges for their strong localization and low‐strain features. Green InGaN QDs are self‐assembled under Stranski–Krastanov (SK) and Volmer–Weber (VW) modes by using metal organic vapor phase epitaxy. The SK QDs can shift the peak efficiency of a micro‐LED to an extremely low current density of 0.5 A cm−2 (almost two orders of magnitude lower compared to QW ones) with an external quantum efficiency of 18.2% (nearly two times higher than present green micro‐LEDs). Besides, green micro‐LEDs based on VW QDs reach a 3 dB bandwidth of 1.3 GHz. These results indicate that InGaN QDs can provide an ultimate solution to micro‐LEDs for display and VLC applications, especially since they are fully compatible with current light‐emitting diode (LED) industrial technology.

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