In order to exploit the outstanding physical properties of one-dimensional （1D） nanostructures such as carbon nanotubes and semiconducting nanowires and nanorods in future technological applications, it will be nece...In order to exploit the outstanding physical properties of one-dimensional （1D） nanostructures such as carbon nanotubes and semiconducting nanowires and nanorods in future technological applications, it will be necessary to organize them on surfaces with precise control over both position and orientation. Here, we use a 1D rigid DNA motif as a model for studying directed assembly at the molecular scale to lithographically patterned nanodot anchors. By matching the inter-nanodot spacing to the length of the DNA nanostructure, we are able to achieve nearly 100% placement yield. By varying the length of single-stranded DNA linkers bound covalently to the nanodots, we are able to study the binding selectivity as a function of the strength of the binding interactions. We analyze the binding in terms of a thermodynamic model which provides insight into the bivalent nature of the binding, a scheme that has general applicability for the controlled assembly of a broad range of functional nanostructures.展开更多
In nature,various animal groups like bird flocks display proficient collective navigation achieved by maintaining high consistency and cohesion simultaneously.Both metric and topological interactions have been explore...In nature,various animal groups like bird flocks display proficient collective navigation achieved by maintaining high consistency and cohesion simultaneously.Both metric and topological interactions have been explored to ensure high consistency among groups.The topological interactions found in bird flocks are more cohesive than metric in-teractions against external perturbations,especially the spatially balanced topological interaction(SBTI).However,it is revealed that in complex environments,pursuing cohesion via existing interactions compromises consistency.The authors introduce an innovative solution,assemble topological interaction,to address this challenge.Con-trasting with static interaction rules,the new interaction empowers individuals with self-awareness to adapt to the complex environment by switching between interactions through visual cues.Most individuals employ high-consistency k-nearest topological interaction when not facing splitting threats.In the presence of such threats,some switch to the high-cohesion SBTI to avert splitting.The assemble topological interaction thus transcends the limit of the trade-off between consistency and cohesion.In addition,by comparing groups with varying degrees of these two features,the authors demonstrate that group effects are vital for efficient navigation led by a minority of informed agents.Finally,the real-world drone-swarm experiments validate the applicability of the proposed interaction to artificial robotic collectives.展开更多
文摘In order to exploit the outstanding physical properties of one-dimensional （1D） nanostructures such as carbon nanotubes and semiconducting nanowires and nanorods in future technological applications, it will be necessary to organize them on surfaces with precise control over both position and orientation. Here, we use a 1D rigid DNA motif as a model for studying directed assembly at the molecular scale to lithographically patterned nanodot anchors. By matching the inter-nanodot spacing to the length of the DNA nanostructure, we are able to achieve nearly 100% placement yield. By varying the length of single-stranded DNA linkers bound covalently to the nanodots, we are able to study the binding selectivity as a function of the strength of the binding interactions. We analyze the binding in terms of a thermodynamic model which provides insight into the bivalent nature of the binding, a scheme that has general applicability for the controlled assembly of a broad range of functional nanostructures.
基金This research was supported by the National Natural Science Foundation of China,Grant/Award Number:61973327.
文摘In nature,various animal groups like bird flocks display proficient collective navigation achieved by maintaining high consistency and cohesion simultaneously.Both metric and topological interactions have been explored to ensure high consistency among groups.The topological interactions found in bird flocks are more cohesive than metric in-teractions against external perturbations,especially the spatially balanced topological interaction(SBTI).However,it is revealed that in complex environments,pursuing cohesion via existing interactions compromises consistency.The authors introduce an innovative solution,assemble topological interaction,to address this challenge.Con-trasting with static interaction rules,the new interaction empowers individuals with self-awareness to adapt to the complex environment by switching between interactions through visual cues.Most individuals employ high-consistency k-nearest topological interaction when not facing splitting threats.In the presence of such threats,some switch to the high-cohesion SBTI to avert splitting.The assemble topological interaction thus transcends the limit of the trade-off between consistency and cohesion.In addition,by comparing groups with varying degrees of these two features,the authors demonstrate that group effects are vital for efficient navigation led by a minority of informed agents.Finally,the real-world drone-swarm experiments validate the applicability of the proposed interaction to artificial robotic collectives.
