Formation of functional groups on graphite during oxygen plasma treatment

Improved sample wettability was obtained by oxygen plasma functionalization of pyrolytic graphite. The samples were exposed to highly dissociated oxygen plasma with the density of 1 × 10¹⁶ m⁻³, the electron temperature of about 5.5 eV and the density of neutral oxygen atoms of 8 × 10²¹ m⁻³ for 20 s. The surface wettability was measured by a contact angle of water drop. The contact angle dropped from original 112° down to about 1°. The functional groups were detected by XPS analyses. The survey spectrum showed a substantial increase of oxygen concentration on the surface, while high-resolution analyses showed additional oxygen was bonded onto the graphite surface in the form of C-O polar functional group responsible for the increase of the surface energy.     

Positive solutions and eigenvalue regions of two-delay singular systems with a twin parameter

The paper is concerned with a two-delay singular differential system with a twin parameter. Applying fixed-point index theory, we show the relationship between the asymptotic behaviors of nonlinearities (at zero and infinity) and the open regions (eigenvalue regions) of parameters, which are correlated with delays, such that the system has zero, one and two positive solution(s).     

MORPHOLOGY OF BLACK CARBON AEROSOLS AND UBIQUITY OF 50-NANOMETER BLACK CARBON AEROSOLS IN THE ATMOSPHERE

Different-sized aerosols were collected by an Andersen air sampler to observe the detailed morphology of the black carbon （BC） aerosols which were separated chemically from the other accompanying aerosols, using a Scanning Electron Microscope equipped with an Energy Dispersive X-ray Spectrometer （SEM-EDX）. The results indicate that most BC aerosols are spherical particles of about 50 nm in diameter and with a homogeneous surface. Results also show that these particles aggregate with other aerosols or with themselves to form larger agglomerates in the micrometer range. The shape of these 50-nm BC spherical particles was found to be very similar to that of BC particles released from petroleum-powered vehicular internal combustion engines. These spherical BC particles were shown to be different from the previously reported fullerenes found using Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry （MALDI-TOF-MS）.     

System dependence of the correlation function of IMFs in Ar + Sn at 35 MeV/u

The inclusive reduced velocity correlation functions of the intermediate mass fragments were measured in the reactions of ³⁶Ar + ^112,124Sn at 35 MeV/u. The anti-correlation is observed to be stronger in ³⁶Ar + ¹²⁴Sn system than that in ³⁶Ar + ¹¹²Sn. The difference of the correlation functions between the two reactions is mainly contributed by the particle pairs with high momenta. A three body Coulomb repulsive trajectory model is employed to calculate the emission time scale of the IMFs for the two systems. The time scale is 150 fm/c in ³⁶Ar + ¹¹²Sn and 120 fm/c in the ³⁶Ar + ¹²⁴Sn, respectively.     

Students’ Reasoning About One-Object Stochastic Phenomena in an ICT-Environment

This paper focuses on the different ways in which students in lower secondary school (14–16 year olds) experience compound random events, presented to them in the form of combined junctions. A carefully designed ICT environment was developed enabling the students to interact with different representations of such structures. Data for the analysis was gathered from two interview sessions. The analysis of the interaction is based on constructivist principles on learning; i.e. we adopted a student-oriented perspective, taking into consideration the different ways students try to make sense of chance encounters. Our results show how some students give priority to geometrical and physical concerns, and we discuss how seeking causal explanations of random phenomena may have encouraged this. With respect to numerically oriented models a division strategy appears to stand out as the preferred one.     

Mixed Elastico-Plasticity Problems with Partially Unknown Boundaries

In this paper,we study mixed elastico-plasticity problems in which part of the boundary is known,while the other part of the boundary is unknown and is a free boundary.Under certain conditions,this problemcan be transformed into a Riemann-Hilbert boundary value problem for analytic functions and a mixed boundaryvalue problem for complex equations.Using the theory of generalized analytic functions,the solvability of theproblem is discussed.     

The energy and structure of (0 0 1) twist grain boundary in noble metals

The relaxed energy and structure of (0 0 1) twist grain boundary (GB) in noble metals Au, Ag and Cu are simulated by the MAEAM. In-boundary translation between two adjacent grains results in a periodic energy variation and the period is a square with the side length L_Σ/Σ. The lowest energy appears when the two grains are translated relatively to either corner or center of the periodic square. The relaxed GB energy increases smoothly for low-angle boundaries and levels off for larger-angle boundaries except a cusp appeared at θ = 36.87° (Σ = 5). After relaxation, the symmetry of the GB structure is not changed but the displacement of the atoms parallel to the GB plane decreases with increasing the distance of the atoms from the GB plane.     

On the genericity of chaos

Let M be a compact manifold with dimM?2. We prove that some iteration of the generic homeomorphism on M is semiconjugated to the shift map and has infinite topological entropy (Theorem 1.1).     

Estimates of covering numbers of convex sets with slowly decaying orthogonal subsets

Covering numbers of precompact symmetric convex subsets of Hilbert spaces are investigated. Lower bounds are derived for sets containing orthogonal subsets with norms of their elements converging to zero sufficiently slowly. When these sets are convex hulls of sets with power-type covering numbers, the bounds are tight. The arguments exploit properties of generalized Hadamard matrices. The results are illustrated by examples from machine learning, neurocomputing, and nonlinear approximation.