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Biological cells routinely reconfigure their shape using dynamic signalling and regulatory networks that direct self-assembly processes in time and space, through molecular components that sense, process and transmit information from the environment. A similar strategy could be used to enable life-like behaviours in synthetic materials. Nucleic acid nanotechnology offers a promising route towards this goal through a variety of sensors, logic and dynamic components and self-assembling structures. Here, by harnessing both dynamic and structural DNA nanotechnology, we demonstrate dynamic control of the self-assembly of DNA nanotubes—a well-known class of programmable DNA nanostructures. Nanotube assembly and disassembly is controlled with minimal synthetic gene systems, including an autonomous molecular oscillator. We use a coarse-grained computational model to capture nanotube length distribution dynamics in response to inputs from nucleic acid circuits. We hope that these results may find use for the development of responsive nucleic acid materials, with potential applications in biomaterials science, nanofabrication and drug delivery. Nucleic acid nanotechnology offers a promising route towards the design and synthesis of reconfigurable biomolecular materials. Now, the combination of dynamic and structural DNA nanotechnology has enabled the dynamic control of the assembly and disassembly of DNA nanotubes. The process involves minimal synthetic gene systems, including an autonomous molecular oscillator.

In this communication, the (2+1)-dimensional Broer-Kaup-Kupershmidt (BKK) system is studied. With the aid of Painlevé Bäcklund transformation method, we have obtained a special class of solution consisting of only one arbitrary function. Consequently, we derive exact wave solutions, including dromion, dromion triplet pairs and multi-rogue waves. To realize dynamics of the wave patterns, we have created 3D plots with the use of symbolic software Mathematica. The obtained solutions are very significant to explore the qualitative interpretations, especially for the civil and coastal engineers in a coastal and harbor design.

An accurate and computationally efficient molecular level description of mesoscopic behavior of ice-water systems remains a major challenge. Here, we introduce a set of machine-learned coarse-grained (CG) models (ML-BOP, ML-BOP dih , and ML-mW) that accurately describe the structure and thermodynamic anomalies of both water and ice at mesoscopic scales, all at two orders of magnitude cheaper computational cost than existing atomistic models. In a significant departure from conventional force-field fitting, we use a multilevel evolutionary strategy that trains CG models against not just energetics from first-principles and experiments but also temperature-dependent properties inferred from on-the-fly molecular dynamics (~ 10’s of milliseconds of overall trajectories). Our ML BOP models predict both the correct experimental melting point of ice and the temperature of maximum density of liquid water that remained elusive to-date. Our ML workflow navigates efficiently through the high-dimensional parameter space to even improve upon existing high-quality CG models (e.g. mW model). A computationally efficient description of ice-water systems at the mesoscopic scale is challenging due to system size and timescale limitations. Here the authors develop a machine-learned coarse-grained water model to elucidate the ice nucleation process much more efficiently than previous models.

Stress-induced reactions at the sliding interface during relative movement are known to cause structural or chemical modifications in contacting materials. The nature of these modifications at the atomic level and formation of byproducts in an oil-free environment, however, remain poorly understood and pose uncertainties in predicting the tribological performance of the complete tribosystem. Here, we demonstrate that tribochemical reactions occur even in dry conditions when hydrogenated diamond-like carbon (H-DLC) surface is slid against two-dimensional (2D) molybdenum disulfide along with nanodiamonds in dry nitrogen atmosphere. Detailed experimental studies coupled with reactive molecular dynamics simulations reveal that at high contact pressures, diffusion of sulfur from the dissociated molybdenum disulfide led to amorphization of nanodiamond and subsequent transformation to onion-like carbon structures (OLCs). The in situ formation of OLCs at the sliding interface provide reduced contact area as well as incommensurate contact with respect to the H-DLC surface, thus enabling successful demonstration of superlubricity Stress-induced tribochemical reactions that reduce friction at sliding interfaces typically require liquid lubricants. Here, the authors discover the nanoscale tribocatalytic formation of onion-like carbon from 2D MoS 2 and nanodiamond under dry and oil-free conditions, providing superlubricity at the macroscale.

Friction and wear remain as the primary modes of mechanical energy dissipation in moving mechanical assemblies; thus, it is desirable to minimize friction in a number of applications. We demonstrate that superlubricity can be realized at engineering scale when graphene is used in combination with nanodiamond particles and diamondlike carbon (DLC). Macroscopic superlubricity originates because graphene patches at a sliding interface wrap around nanodiamonds to form nanoscrolls with reduced contact area that slide against the DLC surface, achieving an incommensurate contact and substantially reduced coefficient of friction (∼0.004). Atomistic simulations elucidate the overall mechanism and mesoscopic link bridging the nanoscale mechanics and macroscopic experimental observations.

Moving mechanical interfaces need to be lubricated to ensure long life and easy slippage; here, a new type of coating is described—comprising nitrides of either molybdenum or vanadium, together with a copper or nickel catalyst—that generates protective tribofilms from lubricating oils. Low-friction tribofilms created in situ This paper describes a novel approach to lubrication between moving mechanical interfaces that relies on the extraction of carbon tribofilms in situ directly from the base-oil molecules on catalytically active, sliding nanometre-scale crystalline surfaces. The newly developed coatings — comprising molybdenum or vanadium nitrides plus a copper or nickel catalyst — deposited on steel substrates generate protective tribofilms from lubricating oils that virtually eliminate wear and provide lower friction than films produced from formulated lubricants. Moving mechanical interfaces are commonly lubricated and separated by a combination of fluid films and solid ‘tribofilms’, which together ensure easy slippage and long wear life 1 . The efficacy of the fluid film is governed by the viscosity of the base oil in the lubricant; the efficacy of the solid tribofilm, which is produced as a result of sliding contact between moving parts, relies upon the effectiveness of the lubricant’s anti-wear additive (typically zinc dialkyldithiophosphate) 2 . Minimizing friction and wear continues to be a challenge, and recent efforts have focused on enhancing the anti-friction and anti-wear properties of lubricants by incorporating inorganic nanoparticles and ionic liquids 3 , 4 . Here, we describe the in operando formation of carbon-based tribofilms via dissociative extraction from base-oil molecules on catalytically active, sliding nanometre-scale crystalline surfaces, enabling base oils to provide not only the fluid but also the solid tribofilm. We study nanocrystalline catalytic coatings composed of nitrides of either molybdenum or vanadium, containing either copper or nickel catalysts, respectively. Structurally, the resulting tribofilms are similar to diamond-like carbon 5 . Ball-on-disk tests at contact pressures of 1.3 gigapascals reveal that these tribofilms nearly eliminate wear, and provide lower friction than tribofilms formed with zinc dialkyldithiophosphate. Reactive and ab initio molecular-dynamics simulations show that the catalytic action of the coatings facilitates dehydrogenation of linear olefins in the lubricating oil and random scission of their carbon–carbon backbones; the products recombine to nucleate and grow a compact, amorphous lubricating tribofilm.

Real-time tracking of the three-dimensional (3D) evolution of colloidal nanoparticles in solution is essential for understanding complex mechanisms involved in nanoparticle growth and transformation. We used time-resolved small-angle and wide-angle x-ray scattering simultaneously to monitor oxidation of highly uniform colloidal iron nanoparticles, enabling the reconstruction of intermediate 3D morphologies of the nanoparticles with a spatial resolution of ~5 angstroms. The in situ observations, combined with large-scale reactive molecular dynamics simulations, reveal the details of the transformation from solid metal nanoparticles to hollow metal oxide nanoshells via a nanoscale Kirkendall process—for example, coalescence of voids as they grow and reversal of mass diffusion direction depending on crystallinity. Our results highlight the complex interplay between defect chemistry and defect dynamics in determining nanoparticle transformation and formation.