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School of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong 518055, China. Electronic address:
Active colloids driven out of thermal equilibrium serve as building blocks for smart materials with tunable structures and functions. Using chemical energy to drive colloids is advantageous but requires precise control over chemical release. To address this, we developed colloidal ionogels-polymer microspheres infused with ionic liquids-that show controlled assembly and self-propulsion upon tunable swelling.
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The pursuit of boron-based organic compounds with multiresonance (MR)-induced thermally activated delayed fluorescence (TADF) is propelled by their potential as narrowband blue emitters for wide-gamut displays. Although boron-doped polycyclic aromatic hydrocarbons in MR compounds share common structural features, their molecular design traditionally involves iterative approaches with repeated attempts until success. To address this, we implemented machine learning algorithms to establish quantitative structure-property relationship models, predicting key optoelectronic characteristics, such as full width at half maximum (FWHM) and main peak wavelength, for deep-blue MR candidates.
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