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Abstract Achieving efficient and stable blue light‐emitting perovskite nanocrystals is a significant challenge for next‐generation optoelectronic devices. Here, a dual‐ligand surface engineering strategy is reported for quasi‐2D CsPbBr₃nanoplatelets (NPLs) synthesized via ligand‐assisted reprecipitation. By synergistically co‐introducing didodecyldimethylammonium bromide to passivate bromine vacancies and hexylphosphonic acid to bind undercoordinated lead ions, the NPLs achieved a remarkable photoluminescence quantum yield of 93.7% and a narrow full‐width at half‐maximum of 19.27 nm. The enhanced photoluminescence (PL) lifetime (6.35 ns), reduced crystal disorder, slower bleach recovery kinetics, and improved thermal stability suggest that the suppressed non‐radiative pathways and strong exciton confinement (Eb = 141.76 meV) result from effective surface defect passivation and enhanced radiative recombination. Additionally, surface and structural characterizations confirmed the successful dual‐ligand integration and improved crystal integrity. The treated NPLs retained ∼57% PL under 450 min of ultraviolet (UV) light and ∼55% PL under 70% relative humidity, demonstrating strong UV and moisture stability. A prototype white light‐emitting device fabricated by integrating dual‐ligand‐treated NPLs achieves a wide color gamut (121% National Television System Committee, 90.4% ITU‐R Recommendation BT.2020), demonstrating their potential for high‐performance optoelectronics. This approach promotes defect suppression in low‐dimensional perovskites, paving the way for stable and efficient blue emitters. 

Abstract This study presents the Br‐rich in situ synthesis of blue‐emitting 2D CsPbBr₃nanoplatelets (NPLs) with various Br/Pb ratios using ZnBr₂as a Br precursor to enhance Br ion adsorption significantly. This leads to effective passivation of surface defects, particularly Pb−Br bonds, by increasing the positive charge density around Pb atoms, thus creating a stable bonding environment and reducing defect formation. Consequently, the photoluminescence quantum yield (PLQY) improves from 31.15% for a Br/Pb ratio of 2 to 87.2% for a ratio of 6. NPLs with a Br/Pb ratio of 6 also exhibit longer lifetimes (16.69 ns) and slower bleach recovery dynamics, indicating fewer non‐radiative recombination pathways and effective exciton dynamics. Additionally, NPLs with the Br/Pb ratio of 6 demonstrated better thermal stability, with an activation energy of 124.3 meV, indicating stronger exciton binding. These NPLs also exhibited enhanced stability, with UV tolerance at 43.9% and water resistance at 23.8%, making them suitable for displays and lighting. Furthermore, Br‐passivated CsPbBr₃NPLs are used as blue emitters in prototype white LEDs, achieving a wide color gamut, 126.6% of the National Television Standards Committee and 94.5% of Rec. 2020, demonstrating their potential for high‐quality lighting and advanced display technologies. 

Abstract Among promising applications of metal‐halide perovskite, the most research progress is made for perovskite solar cells (PSCs). Data from myriads of research work enables leveraging machine learning (ML) to significantly expedite material and device optimization as well as potentially design novel configurations. This paper represents one of the first efforts in providing open‐source ML tools developed utilizing the Perovskite Database Project (PDP), the most comprehensive open‐source PSC database to date with over 43 000 entries from published literature. Three ML model architectures with short‐circuit current density (J_sc) as a target are trained exploiting the PDP. Using the XGBoost architecture, a root mean squared error (RMSE) of 3.58 , R²of 0.35 and a mean absolute percentage error (MAPE) of 9.49% are achieved. This performance is comparable to results reported in literature, and through further investigation can likely be improved. To overcome challenges with manual database creation, an open‐source data cleaning pipeline is created for PDP data. Through the creation of these tools, which have been published on GitHub, this research aims to make ML available to aid the design for PSC while showing the already promising performance achieved. The tools can be adapted for other applications, such as perovskite light‐emitting diodes (PeLEDs), if a sufficient database is available. 

A universal method of micro-patterning thin quantum dot films is highly desired by industry to enable integration of quantum dot materials with optoelectronic devices. Many of the methods reported so far, including specially engineered photoresist or ink-jet printing, are either of poor yield, resolution limited, difficult to scale for mass production, overly expensive or sacrifice some optical quality of the quantum dots. In our previous work, we presented a dry photolithographic lift-off method for pixelization of solution-processed materials and demonstrated its application in patterning perovskite quantum dot pixels, 10 µm in diameter, to construct a static micro-display. In this report, we present further development of this method, and demonstrate high-resolution patterning (~1 µm diameter), full-scale processing on 100 mm wafer, and multi-color integration of two different varieties of quantum dots. Perovskite and cadmium-selenide quantum dots were adopted for the experimentation, but the method can be applied to other types of solution-processed materials. We also show the viability of this method for constructing high-resolution micro-arrays of quantum dot color-convertors by fabricating patterned films directly on top of a blue gallium-nitride LED substrate. The green perovskite quantum dots used for fabrication are synthesized and prepared by our research group via room temperature ligand-assisted reprecipitation method, and these synthesized quantum dots have a photoluminescent quantum yield of 93.6% and full-width half-maximum emission linewidth less than 20 nm. Our results demonstrate the viability of this method for use in scalable manufacturing of high-resolution micro-displays. 

We report a photolithography‐based technology for patterning quantum dot color converters for micro‐LED displays. A patterning resolution of ~1 µm is achieved. The method can be applied to any color converter materials. Integration of perovskite quantum dots and CdSe/ZnS quantum dots is demonstrated to show the versatility of the technology.