Rodney S. Ruoff

Bio: Rodney S. Ruoff is an academic researcher from Ulsan National Institute of Science and Technology. The author has contributed to research in topics: Graphene & Graphene oxide paper. The author has an hindex of 164, co-authored 666 publications receiving 194902 citations. Previous affiliations of Rodney S. Ruoff include Texas State University & North Carolina State University.

Three-Dimensional Representation of Curved Nanostructures

Abstract: Nanostructures, such as nanowires, nanotubes, and nanocoils, can be described in many cases as quasi one-dimensional (1D) curved objects projecting in three-dimensional (3D) space. A parallax method to reconstruct the correct three-dimensional geometry of such 1D nanostructures is presented. A series of images were acquired at different view angles, and from those image pairs, 3D representations were constructed using a MATLAB program. Error analysis as a function of view-angle between the two images is discussed. As an example application, we demonstrate the importance of knowing the true 3D shape of Boron nanowires. Without precise knowledge of the nanowire's dimensions, diameter and length, mechanical resonance data cannot be properly fit to obtain an accurate estimate of the Young's modulus.

Fullerene Endohedrals of Praseodymium

Abstract: Praseodymium endohedral fullerenes have been produced in a graphite arc discharge system and shown to exist in the entire fullerene series from C60 to C100. These endohedrals prefer to be encaged in the larger fullerenes which exist in concentrations approximately equal to the concentrations of their empty counterparts. However for C60 and C70 the endohedrals are only about 5% of their counterparts. Solvent extraction with regular fullerene solvents is partially successful for Pr@C82 but completely unsuccessful for the other endohedrals. However, these Pr endohedrals appear to be stable to air and solvent exposure over long periods of time.

The rise of graphene

Abstract: 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.

Fast parallel algorithms for short-range molecular dynamics

Abstract: 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.

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

Abstract: 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。

Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene

Abstract: 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.