Graphene is a rapidly rising star on the horizon of materials science and condensed-matter physics. This strictly two-dimensional material exhibits exceptionally high crystal and electronic quality, and, despite its short history, has already revealed a cornucopia of new physics and potential applications, which are briefly discussed here. Whereas one can be certain of the realness of applications only when commercial products appear, graphene no longer requires any further proof of its importance in terms of fundamental physics. Owing to its unusual electronic spectrum, graphene has led to the emergence of a new paradigm of 'relativistic' condensed-matter physics, where quantum relativistic phenomena, some of which are unobservable in high-energy physics, can now be mimicked and tested in table-top experiments. More generally, graphene represents a conceptually new class of materials that are only one atom thick, and, on this basis, offers new inroads into low-dimensional physics that has never ceased to surprise and continues to provide a fertile ground for applications.

The rise of graphene

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

We measured the elastic properties and intrinsic breaking strength of free-standing monolayer graphene membranes by nanoindentation in an atomic force microscope. The force-displacement behavior is interpreted within a framework of nonlinear elastic stress-strain response, and yields second- and third-order elastic stiffnesses of 340 newtons per meter (N m(-1)) and -690 Nm(-1), respectively. The breaking strength is 42 N m(-1) and represents the intrinsic strength of a defect-free sheet. These quantities correspond to a Young's modulus of E = 1.0 terapascals, third-order elastic stiffness of D = -2.0 terapascals, and intrinsic strength of sigma(int) = 130 gigapascals for bulk graphite. These experiments establish graphene as the strongest material ever measured, and show that atomically perfect nanoscale materials can be mechanically tested to deformations well beyond the linear regime.

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Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene

Graphene has demonstrated broad applications due to its prominent properties. Its molecular structure makes graphene achiral. Here, we propose a direct way to prepare chiral graphene by transferring chiral structural conformation from chiral conjugated amino acids onto graphene basal plane through π–π interaction followed by thermal fusion. Using atomic resolution transmission electron microscopy, we estimated an areal coverage of the molecular imprints (chiral regions) up to 64 % on the basal plane of graphene (grown by chemical vapor deposition). The high concentration of molecular imprints in their single layer points to a close packing of the deposited amino acid molecules prior to “thermal fusion”. Such “molecular chirality-encoded graphene” was tested as an electrode in electrochemical enantioselective recognition. The chirality-encoded graphene might find use for other chirality-related studies and the encoding procedure might be extended to other two-dimensional materials. 

Encoding Enantiomeric Molecular Chiralities on Graphene Basal Planes

We have designed and fabricated a TEM (transmission electron microscopy) liquid cell with hundreds of graphene nanocapsules arranged in a stack of two Si3N4-x membranes. These graphene nanocapsules are formed on arrays of nanoholes patterned on the Si3N4-x membrane by focused ion beam milling, allowing for better resolution than for the conventional graphene liquid cells, which enables the observation of light elements, such as atomic structures of silicon. We suggest that multiple nanocapsules provide opportunities for consecutive imaging under the same conditions in a single liquid cell. The use of single-crystal graphene windows offers an excellent signal-to-noise ratio and high spatial resolution. The motion of silicon nanoparticles (a low atomic number (Z) material) interacting with nanobubbles was observed, and analyzed, in detail. Our approach will help advance liquid-phase TEM observations by providing a straightforward method to encapsulate liquid between monolayers of various 2-dimensional materials.

Using Single-Crystal Graphene to Form Arrays of Nanocapsules Enabling the Observation of Light Elements in Liquid Cell Transmission Electron Microscopy.

A new energy-based theory, Quantized Fracture Mechanics (QFM), is presented that modifies continuum-based fracture mechanics. The differentials in Griffith’s criterion are substituted with finite differences; the implications are remarkable. Fracture of tiny systems with a given geometry and type of loading occurs at quantized stresses that are well predicted by QFM. QFM is self-consistent, agreeing to first-order with linear elastic fracture mechanics (LEFM), and to second-order with non-linear fracture mechanics (NLFM): the equation of the R-curve is consequently derived. For vanishing crack length QFM predicts a finite ideal strength in agreement with Orowan’s prediction. The different fracture Modes (opening I, sliding II and tearing III), and the stability of the fracture propagations, are treated in a simple way. In contrast to LEFM, QFM has no restrictions on treating defect size and shape. As an example, strengths predicted by QFM are compared with experimental and numerical results on carbon nanotubes containing defects of different size and shape.

Quantized fracture mechanics and related applications for predicting the strength of defective nanotubes

Crystalline boron (B) nanowires (NWs) have been synthesized by the CVD method with preformed metal catalyst particles. We have experimentally investigated their dynamical resonance (i) and mechanical strength (ii). Both the two independent methods suggest the possible presence of nanocracks in the tested B NWs. Nanocrack detection can in principle be achieved by analytical calculations quantifying crack position and depth.

Rodney S. Ruoff

Papers

Encoding Enantiomeric Molecular Chiralities on Graphene Basal Planes

Using Single-Crystal Graphene to Form Arrays of Nanocapsules Enabling the Observation of Light Elements in Liquid Cell Transmission Electron Microscopy.

Quantized fracture mechanics and related applications for predicting the strength of defective nanotubes

Nanocrack Detection in Vibrating Nanowires

Electrochemical polymerization of polyhydrocarbons by reductive dehalogenation of chlorinated methanes