Janus microcylinders composed of different polymers were prepared through coaxial co-jetting with dual-core flows, followed by cross-linking, microsectioning, and shell removal. Uniquely shaped building blocks can be fabricated by photo-patterning of one hemisphere of the microcylinders.
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http://dx.doi.org/10.1021/la4009416 | DOI Listing |
ACS Nano
April 2024
Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, People's Republic of China.
Langmuir
October 2023
Department of Chemical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran.
Controlling the morphology of polymeric particles is vital for their diverse applications. In this study, we explored how solvent composition influences the morphology of poly(styrene)/poly(lactic acid) (PS/PLA) particles prepared via the emulsion solvent evaporation method. We used toluene, dichloromethane (DCM), and various mixtures to prepare these particles.
View Article and Find Full Text PDFSmall
July 2023
School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China.
Photocatalytic oxygen reduction reaction (ORR) for H O production in the absence of sacrificing agents is a green approach and of great significance, where the design of photocatalysts with high performance is the central task. Herein, a spatial specific S-scheme heterojunction design by introducing a novel semiconducting pair with a S-scheme mechanism in a purpose-designed Janus core-shell-structured hollow morphology is reported. In this design, TiO nanocrystals are grown inside the inner wall of resorcinol-formaldehyde (RF) resin hollow nanocakes with a reverse bumpy ball morphology (TiO @RF).
View Article and Find Full Text PDFLangmuir
April 2023
Integrated Engineering Major, Department of Environmental Science and Engineering, Kyung Hee University, Seocheon-dong 1, Giheung-gu, Yongin-Si, Gyeonggi-Do 446-701, South Korea.
The majority of research on Janus particles prepared by solvent evaporation-induced phase separation technique uses models based on interfacial tension or free energy to predict Janus/core-shell morphology. Data-driven predictions, in contrast, utilize multiple samples to identify patterns and outliers. Using machine-learning algorithms and explainable artificial intelligence (XAI) analysis, we developed a model based on a 200-instance data set to predict particle morphology.
View Article and Find Full Text PDFNanoscale Adv
November 2022
Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha, Onna-Son Okinawa 904-0495 Japan
Among the properties that distinguish nanoparticles (NPs) from their bulk counterparts is their lower melting points. It is also common knowledge that relatively low melting points enhance the coalescence of (usually) nascent nanoclusters toward larger NPs. Finally, it is well established that the chemical ordering of bi- (or multi-) metallic NPs can have a profound effect on their physical and chemical properties, dictating their potential applications.
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