Dendritic carbon architectures formed by nanotube core-directed diffusion-limited aggregation of nanoparticles
Literature Information
Zhenyu Liu
A regular array of fractal patterns with macroscopic dendritic carbon architecture was prepared by catalytic chemical vapor deposition (CVD). The dendritic carbon architectures have micrometre-sized stems and hyperbranches evolved by lateral growth, and they are formed by diffusion-limited aggregation of carbon-encapsulated iron nanoparticle building blocks generated from catalytic pyrolysis of toluene, which is directed by carbon nanotube cores, and followed by subsequent restructuring from surface to bulk. Incorporation of such proposed processes in Monte Carlo simulations generates dendritic architectures similar to the morphologies observed from the experiments. The findings provide direct information to the time resolved evolution of the morphology and microstructure of the dendritic carbon architecture, which mimic the nature behavior as snowflake attaching on the tree branches. Those will be important to understand the growth of vapor grown carbon fibers and carbon filamentous structures, and further possibility to control branching out of vapor grown carbon fibers.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.










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