Some specific features of spreading at the molecular scale: Wetting transition and molecular self-assembly

1994 ◽  
Vol 98 (3) ◽  
pp. 424-428 ◽  
Author(s):  
M. P. Valignat ◽  
A. M. Cazabat ◽  
F. Tiberg
Keyword(s):  
Self Assembly ◽  
Wetting Transition ◽  
Molecular Scale

Thermodynamics and Selectivity of Two-Dimensional Metallo-supramolecular Self-Assembly Resolved at Molecular Scale

2011 ◽  
Vol 133 (16) ◽  
pp. 6150-6153 ◽  
Author(s):  
Ziliang Shi ◽  
Jun Liu ◽  
Tao Lin ◽  
Fei Xia ◽  
Pei Nian Liu ◽  
...  
Keyword(s):  
Self Assembly ◽  
Two Dimensional ◽  
Molecular Scale

scholarly journals How faceted liquid droplets grow tails

2016 ◽  
Vol 113 (3) ◽  
pp. 493-496 ◽  
Author(s):  
Shani Guttman ◽  
Zvi Sapir ◽  
Moty Schultz ◽  
Alexander V. Butenko ◽  
Benjamin M. Ocko ◽  
...  
Keyword(s):  
Melting Point ◽  
Interfacial Tension ◽  
Everyday Life ◽  
Self Assembly ◽  
Liquid Droplets ◽  
Scale Elasticity ◽  
Dispersed Oil ◽  
Molecular Scale ◽  
Future Technologies ◽  
Shape Changes

Liquid droplets, widely encountered in everyday life, have no flat facets. Here we show that water-dispersed oil droplets can be reversibly temperature-tuned to icosahedral and other faceted shapes, hitherto unreported for liquid droplets. These shape changes are shown to originate in the interplay between interfacial tension and the elasticity of the droplet’s 2-nm-thick interfacial monolayer, which crystallizes at some T = Ts above the oil’s melting point, with the droplet’s bulk remaining liquid. Strikingly, at still-lower temperatures, this interfacial freezing (IF) effect also causes droplets to deform, split, and grow tails. Our findings provide deep insights into molecular-scale elasticity and allow formation of emulsions of tunable stability for directed self-assembly of complex-shaped particles and other future technologies.

scholarly journals RNA nanotechnology for computer design and in vivo computation

2013 ◽  
Vol 371 (2000) ◽  
pp. 20120310 ◽  
Author(s):  
Meikang Qiu ◽  
Emil Khisamutdinov ◽  
Zhengyi Zhao ◽  
Cheryl Pan ◽  
Jeong-Woo Choi ◽  
...  
Keyword(s):  
Self Assembly ◽  
Acid Resistance ◽  
Computational Design ◽  
Computer Design ◽  
Property A ◽  
Rna Sequences ◽  
Rna Nanotechnology ◽  
Molecular Scale ◽  
Computer Scientists

Molecular-scale computing has been explored since 1989 owing to the foreseeable limitation of Moore's law for silicon-based computation devices. With the potential of massive parallelism, low energy consumption and capability of working in vivo , molecular-scale computing promises a new computational paradigm. Inspired by the concepts from the electronic computer, DNA computing has realized basic Boolean functions and has progressed into multi-layered circuits. Recently, RNA nanotechnology has emerged as an alternative approach. Owing to the newly discovered thermodynamic stability of a special RNA motif (Shu et al. 2011 Nat. Nanotechnol. 6 , 658–667 ( doi:10.1038/nnano.2011.105 )), RNA nanoparticles are emerging as another promising medium for nanodevice and nanomedicine as well as molecular-scale computing. Like DNA, RNA sequences can be designed to form desired secondary structures in a straightforward manner, but RNA is structurally more versatile and more thermodynamically stable owing to its non-canonical base-pairing, tertiary interactions and base-stacking property. A 90-nucleotide RNA can exhibit 4 90 nanostructures, and its loops and tertiary architecture can serve as a mounting dovetail that eliminates the need for external linking dowels. Its enzymatic and fluorogenic activity creates diversity in computational design. Varieties of small RNA can work cooperatively, synergistically or antagonistically to carry out computational logic circuits. The riboswitch and enzymatic ribozyme activities and its special in vivo attributes offer a great potential for in vivo computation. Unique features in transcription, termination, self-assembly, self-processing and acid resistance enable in vivo production of RNA nanoparticles that harbour various regulators for intracellular manipulation. With all these advantages, RNA computation is promising, but it is still in its infancy. Many challenges still exist. Collaborations between RNA nanotechnologists and computer scientists are necessary to advance this nascent technology.

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