Nature and strength of bonding in a crystal of semiconducting nanotubes: van der Waals density functional calculations and analytical results

The dispersive interaction between nanotubes is investigated through ab initio theory calculations and in an analytical approximation. A van der Waals density functional (vdW-DF) [Phys. Rev. Lett. 92, 246401 (2004)] is used to determine and compare the binding of a pair of nanotubes as well as in a nanotube crystal. To analyze the interaction and determine the importance of morphology, we furthermore compare results of our ab initio calculations with a simple analytical result that we obtain for a pair of well-separated nanotubes. In contrast to traditional density functional theory calculations, the vdW-DF study predicts an intertube vdW bonding with a strength that is consistent with recent observations for the interlayer binding in graphitics. It also produce a nanotube wall-to-wall separation which is in very good agreement with experiments. Moreover, we find that the vdW-DF result for the nanotube-crystal binding energy can be approximated by a sum of nanotube-pair interactions when these are calculated in vdW-DF. This observation suggests a framework for an efficient implementation of quantum-physical modeling of the CNT bundling in more general nanotube bundles, including nanotube yarn and rope structures.Comment: 10 pages, 4 figure

Numerical thermo-elasto-plastic analysis of residual stresses on different scales during cooling of hot forming parts

In current research, more and more attention is paid to the understanding of residual stress states as well as the application of targeted residual stresses to extend e.g. life time or stiffness of a part. In course of that, the numerical simulation and analysis of the forming process of components, which goes along with the evolution of residual stresses, play an important role. In this contribution, we focus on the residual stresses arising from the austenite-to-martensite transformation at microscopic and mesoscopic level of a Cr-alloyed steel. A combination of a Multi-Phase-Field model and a two-scale Finite Element simulation is utilized for numerical analysis. A first microscopic simulation considers the lattice change, such that the results can be homogenized and applied on the mesoscale. Based on this result, a polycrystal consisting of a certain number of austenitic grains is built and the phase transformation from austenite to martensite is described with respect to the mesoscale. Afterwards, in a two-scale Finite Element simulation the plastic effects are considered and resulting residual stress states are computed

High-precision epsilon expansions of single-mass-scale four-loop vacuum bubbles

In this article we present a high-precision evaluation of the expansions in \e=(4-d)/2 of (up to) four-loop scalar vacuum master integrals, using the method of difference equations developed by S. Laporta. We cover the complete set of `QED-type' master integrals, i.e. those with a single mass scale only (i.e. $m_i\in\{0,m\}$) and an even number of massive lines at each vertex. Furthermore, we collect all that is known analytically about four-loop `QED-type' masters, as well as about {\em all} single-mass-scale vacuum integrals at one-, two- and three-loop order.Comment: 25 pages, uses axodraw.st

Four-Loop Decoupling Relations for the Strong Coupling

We compute the matching relation for the strong coupling constant within the framework of QCD up to four-loop order. This allows a consistent five-loop running (once the $\beta$ function is available to this order) taking into account threshold effects. As a side product we obtain the effective coupling of a Higgs boson to gluons with five-loop accuracy.Comment: 11 page

The Automorphism Conjecture for Ordered Sets of Width ≤11\leq 11 (Version 2)

We introduce a recursive method to deconstruct the automorphism group of an ordered set. By connecting this method with deep results for permutation groups, we prove the Automorphism Conjecture for ordered sets of width less than or equal to $11$. Subsequent investigations show that the method presented here could lead to a resolution of the Automorphism Conjecture.Comment: arXiv admin note: substantial text overlap with arXiv:2209.0931

Towards the Automorphism Conjecture I: Combinatorial Control and Compensation for Factorials

This paper exploits adjacencies between the orbits of an ordered set P and a consequence of the classification of finite simple groups to, in many cases, exponentially bound the number of automorphisms. Results clearly identify the structures which currently prevent the proof of such an exponential bound, or which indeed inflate the number of automorphisms beyond such a bound. This is a first step towards a possible resolution of the Automorphism Conjecture for ordered sets

Reconstruction of the Ranks of the Nonextremal Cards and of Ordered Sets with a Minmax Pair of Pseudo-Similar Points

For every ordered set, we reconstruct the deck obtained by removal of the elements of rank r that are neither minimal nor maximal. Consequently, we also reconstruct the deck obtained by removal of the extremal, that is, minimal or maximal, elements. Finally, we reconstruct the ordered sets with a minmax pair of pseudo-similar points

Matching small β\beta functions using centroid jitter and two beam position monitors

Matching to small beta functions is required to preserve emittance in plasma accelerators. The plasma wake provides strong focusing fields, which typically require beta functions on the mm-scale, comparable to those found in the final focusing of a linear collider. Such beams can be time consuming to experimentally produce and diagnose. We present a simple, fast, and noninvasive method to measure Twiss parameters in a linac using two beam position monitors only, relying on the similarity of the beam phase space and the jitter phase space. By benchmarking against conventional quadrupole scans, the viability of this technique was experimentally demonstrated at the FLASHForward plasma-accelerator facility.Comment: 8 pages, 7 figure

Multiscale 3D Shape Analysis using Spherical Wavelets

©2005 Springer. The original publication is available at www.springerlink.com: http://dx.doi.org/10.1007/11566489_57DOI: 10.1007/11566489_57Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data