Carbon nanotubes have many material properties that make them attractive for applications. In the context of nanoelectronics, interest has focused on single-walled carbon nanotubes (SWNTs) because slight changes in tube diameter and wrapping angle, defined by the chirality indices (n, m), will shift their electrical conductivity from one characteristic of a metallic state to one characteristic of a semiconducting state, and will also change the bandgap. However, this structure-function relationship can be fully exploited only with structurally pure SWNTs. Solution-based separation methods yield tubes within a narrow structure range, but the ultimate goal of producing just one type of SWNT by controlling its structure during growth has proved to be a considerable challenge over the last two decades. Such efforts aim to optimize the composition or shape of the catalyst particles that are used in the chemical vapour deposition synthesis process to decompose the carbon feedstock and influence SWNT nucleation and growth. This approach resulted in the highest reported proportion, 55 per cent, of single-chirality SWNTs in an as-grown sample. Here we show that SWNTs of a single chirality, (12, 6), can be produced directly with an abundance higher than 92 per cent when using tungsten-based bimetallic alloy nanocrystals as catalysts. These, unlike other catalysts used so far, have such high melting points that they maintain their crystalline structure during the chemical vapour deposition process. This feature seems crucial because experiment and simulation both suggest that the highly selective growth of (12, 6) SWNTs is the result of a good structural match between the carbon atom arrangement around the nanotube circumference and the arrangement of the catalytically active atoms in one of the planes of the nanocrystal catalyst. We anticipate that using high-melting-point alloy nanocrystals with optimized structures as catalysts paves the way for total chirality control in SWNT growth and will thus promote the development of SWNT applications.

Summary Discrete molecular dynamics (DMD) is a rapid sampling method used in protein folding and aggregation studies. Until now, DMD was used to perform simulations of simplified protein models in conjunction with structure-based force fields. Here, we develop an all-atom protein model and a transferable force field featuring packing, solvation, and environment-dependent hydrogen bond interactions. Using the replica exchange method, we perform folding simulations of six small proteins (20–60 residues) with distinct native structures. In all cases, native or near-native states are reached in simulations. For three small proteins, multiple folding transitions are observed and the computationally-characterized thermodynamics are in quantitative agreement with experiments. The predictive power of all-atom DMD highlights the importance of environment-dependent hydrogen bond interactions in modeling protein folding. The developed approach can be used for accurate and rapid sampling of conformational spaces of proteins and protein-protein complexes, and applied to protein engineering and design of protein-protein interactions.

RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 Å deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNA Phe , pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting nonhierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses.

A foundation of the modern technology that uses single-crystal silicon has been the growth of high-quality single-crystal Si ingots with diameters up to 12 inches or larger. For many applications of graphene, large-area high-quality (ideally of single-crystal) material will be enabling. Since the first growth on copper foil a decade ago, inch-sized single-crystal graphene has been achieved. We present here the growth, in 20 minutes, of a graphene film of 5 50 cm 2 dimension with > 99% ultra-highly oriented grains. This growth was achieved by: (i) synthesis of sub-metre-sized single-crystal Cu (111) foil as substrate; (ii) epitaxial growth of graphene islands on the Cu(111) surface; (iii) seamless merging of such graphene islands into a graphene film with high single crystallinity and (iv) the ultrafast growth of graphene film. These achievements were realized by a temperature-driven annealing technique to produce single-crystal Cu(111) from industrial polycrystalline Cu foil and the marvellous effects of a continuous oxygen supply from an adjacent oxide. The as-synthesized graphene film, with very few misoriented grains (if any), has a mobility up to ~ 23,000 cm 2 V -1 s -1 at 4 K and room temperature sheet resistance of ~ 230 □ ⁄ . It is very likely that this approach can be scaled up to achieve exceptionally large and highquality graphene films with single crystallinity, and thus realize various industrial-level applications at a low cost.

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Graphene has a range of unique physical properties and could be of use in the development of a variety of electronic, photonic and photovoltaic devices. For most applications, large-area high-quality graphene films are required and chemical vapour deposition (CVD) synthesis of graphene on copper surfaces has been of particular interest due to its simplicity and cost effectiveness. However, the rates of growth for graphene by CVD on copper are less than 0.4 μm s, and therefore the synthesis of large, single-crystal graphene domains takes at least a few hours. Here, we show that single-crystal graphene can be grown on copper foils with a growth rate of 60 μm s. Our high growth rate is achieved by placing the copper foil above an oxide substrate with a gap of ∼15 μm between them. The oxide substrate provides a continuous supply of oxygen to the surface of the copper catalyst during the CVD growth, which significantly lowers the energy barrier to the decomposition of the carbon feedstock and increases the growth rate. With this approach, we are able to grow single-crystal graphene domains with a lateral size of 0.3 mm in just 5 s.

The aggregation of alpha-helix-rich proteins into beta-sheet-rich amyloid fibrils is associated with fatal diseases, such as Alzheimer's disease and prion disease. During an aggregation process, protein secondary structure elements-alpha-helices-undergo conformational changes to beta-sheets. The fact that proteins with different sequences and structures undergo a similar transition on aggregation suggests that the sequence nonspecific hydrogen bond interaction among protein backbones is an important factor. We perform molecular dynamics simulations of a polyalanine model, which is an alpha-helix in its native state and observe a metastable beta-hairpin intermediate. Although a beta-hairpin has larger potential energy than an alpha-helix, the entropy of a beta-hairpin is larger because of fewer constraints imposed by the hydrogen bonds. In the vicinity of the transition temperature, we observe the interconversion of the alpha-helix and beta-sheet states via a random coil state. We also study the effect of the environment by varying the relative strength of side-chain interactions for a designed peptide-an alpha-helix in its native state. For a certain range of side-chain interaction strengths, we find that the intermediate beta-hairpin state is destabilized and even disappears, suggesting an important role of the environment in the aggregation propensity of a peptide.

Neurodegenerative disorders and type 2 diabetes are global epidemics compromising the quality of life of millions worldwide, with profound social and economic implications. Despite the significant differences in pathology – much of which are poorly understood – these diseases are commonly characterized by the presence of cross-β amyloid fibrils as well as the loss of neuronal or pancreatic β-cells. In this review, we document research progress on the molecular and mesoscopic self-assembly of amyloid-beta, alpha synuclein, human islet amyloid polypeptide and prions, the peptides and proteins associated with Alzheimer’s, Parkinson’s, type 2 diabetes and prions diseases. In addition, we discuss the toxicities of these amyloid proteins based on their self-assembly as well as their interactions with membranes, metal ions, small molecules and engineered nanoparticles. Through this presentation we show the remarkable similarities and differences in the structural transitions of the amyloid proteins through primary and secondary nucleation, the common evolution from disordered monomers to alpha-helices and then to β-sheets when the proteins encounter the cell membrane, and, the consensus (with a few exceptions) that off-pathway oligomers, rather than amyloid fibrils, are the toxic species regardless of the pathogenic protein sequence or physicochemical properties. In addition, we highlight the crucial role of molecular self-assembly in eliciting the biological and pathological consequences of the amyloid proteins within the context of their cellular environments and their spreading between cells and organs. Exploiting such structure-function-toxicity relationship may prove pivotal for the detection and mitigation of amyloid diseases.