56,128 research outputs found
Temperature dependent friction and wear of magnetron sputtered coating TiAlN/VN
In this paper, a magnetron sputtered nano-structured multilayer coating TiAlN/VN, grown on hardened tool steel substrate, has been investigated in un-lubricated ball-on-disk sliding tests against an alumina counterface, to study the friction and wear behaviours at a broad range of testing temperatures from 25 to 700 â—¦C, followed by comprehensive analysis of the worn samples using FEG-SEM, cross-sectional TEM, EDX, as well as micro/nano indentations. The experiment results indicated significant temperature dependent friction and wear properties of the coating investigated. Below 100 â—¦C, the coating showed
low friction coefficient at �≤0.6 and low wear rate in the scale of 10−17m3 N−1m−1 dominated by mild oxidation wear. From 100 to 200 ◦C, a progressive transition to higher friction coefficient occurred. After that, the coating exhibited high friction of �= 0.9 at temperatures between 200 and 400 ◦C, and simultaneously higher wear rates of (10−16 to 10−15) m3 N−1m−1. The associated wear mechanism changed to severe wear dominated by cracking and spalling. From 500 ◦C and so on, accelerated oxidation of the TiAlN/VN became the controlling process. This led first to the massive generation of oxide debris and maximum friction of �= 1.1 at 500 ◦C, and then to fast deterioration of the coating despite the lowest friction coefficient of �< 0.3 at 700 ◦C
On the Hecke Eigenvalues of Maass Forms
Let denote a primitive Hecke-Maass cusp form for with
the Laplacian eigenvalue . In this work we show
that there exists a prime such that , , and , where are the
Satake parameters of at , and is an absolute constant with
. In fact, can be taken as . In addition, we prove that the
natural density of such primes ( and ) is at least .Comment: Version 2: typos corrected and a new section on natural density adde
Multi-consensus Decentralized Accelerated Gradient Descent
This paper considers the decentralized optimization problem, which has
applications in large scale machine learning, sensor networks, and control
theory. We propose a novel algorithm that can achieve near optimal
communication complexity, matching the known lower bound up to a logarithmic
factor of the condition number of the problem. Our theoretical results give
affirmative answers to the open problem on whether there exists an algorithm
that can achieve a communication complexity (nearly) matching the lower bound
depending on the global condition number instead of the local one. Moreover,
the proposed algorithm achieves the optimal computation complexity matching the
lower bound up to universal constants. Furthermore, to achieve a linear
convergence rate, our algorithm \emph{doesn't} require the individual functions
to be (strongly) convex. Our method relies on a novel combination of known
techniques including Nesterov's accelerated gradient descent, multi-consensus
and gradient-tracking. The analysis is new, and may be applied to other related
problems. Empirical studies demonstrate the effectiveness of our method for
machine learning applications
Estimate for the glueball mass in QCD
We obtain accurate result for the lightest glueball mass of QCD in 3
dimensions from lattice Hamiltonian field theory. Using the dimensional
reduction argument, a good approximation for confining theories, we suggest
that the glueball mass in 3+1 dimensional QCD be about GeV.Comment: 10 Latex page
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