From Graphene constrictions to single carbon chains

We present an atomic-resolution observation and analysis of graphene constrictions and ribbons with sub-nanometer width. Graphene membranes are studied by imaging side spherical aberration-corrected transmission electron microscopy at 80 kV. Holes are formed in the honeycomb-like structure due to radiation damage. As the holes grow and two holes approach each other, the hexagonal structure that lies between them narrows down. Transitions and deviations from the hexagonal structure in this graphene ribbon occur as its width shrinks below one nanometer. Some reconstructions, involving more pentagons and heptagons than hexagons, turn out to be surprisingly stable. Finally, single carbon atom chain bridges between graphene contacts are observed. The dynamics are observed in real time at atomic resolution with enough sensitivity to detect every carbon atom that remains stable for a sufficient amount of time. The carbon chains appear reproducibly and in various configurations from graphene bridges, between adsorbates, or at open edges and seem to represent one of the most stable configurations that a few-atomic carbon system accomodates in the presence of continuous energy input from the electron beam.Comment: 12 pages, 4 figure

The transition between hole-pairs and four-hole clusters in four-leg tJ ladders

Holes weakly doped into a four-leg \tj ladder bind in pairs. At dopings exceeding a critical doping of $\delta_c\simeq {1/8}$ four hole clusters are observed to form in DMRG calculations. The symmetry of the ground state wavefunction does not change and we are able to reproduce this behavior qualitatively with an effective bosonic model in which the four-leg ladder is represented as two coupled two-leg ladders and hole-pairs are mapped on hard core bosons moving along and between these ladders. At lower dopings, $\delta<\delta_c$, a one dimensional bosonic representation for hole-pairs works and allows us to calculate accurately the Luttinger liquid parameter \krho, which takes the universal value \krho=1 as half-filling is approached

Development of a rapid screen for the endodermal differentiation potential of human pluripotent stem cell lines.

A challenge facing the human pluripotent stem cell (hPSC) field is the variability observed in differentiation potential of hPSCs. Variability can lead to time consuming and costly optimisation to yield the cell type of interest. This is especially relevant for the differentiation of hPSCs towards the endodermal lineages. Endodermal cells have the potential to yield promising new knowledge and therapies for diseases affecting multiple organ systems, including lung, thymus, intestine, pancreas and liver, as well as applications in regenerative medicine and toxicology. Providing a means to rapidly, cheaply and efficiently assess the differentiation potential of multiple hPSCs is of great interest. To this end, we have developed a rapid small molecule based screen to assess the endodermal potential (EP) of hPSCs, based solely on definitive endoderm (DE) morphology. This drastically reduces the cost and time to identify lines suitable for use in deriving endodermal lineages. We demonstrate the efficacy of this screen using 10 different hPSCs, including 4 human embryonic stem cell lines (hESCs) and 6 human induced pluripotent stem cell lines (hiPSCs). The screen clearly revealed lines amenable to endodermal differentiation, and only lines that passed our morphological assessment were capable of further differentiation to hepatocyte like cells (HLCs)

Adaptive Control Optimization of Cutting Parameters for High Quality Machining Operations Based on Neural Networks and Search Algorithms

This book chapter presents an Adaptive Control with Optimization (ACO) system for optimising a multi-objective function based on material removal rate, quality loss function related to surface roughness, and cutting-tool life subjected to surface roughness specifications constraint

Adaptive control optimization in micro-milling of hardened steels-evaluation of optimization approaches

Nowadays, the miniaturization of many consumer products is extending the use of micro-milling operations with high-quality requirements. However, the impacts of cutting-tool wear on part dimensions, form and surface integrity are not negligible and part quality assurance for a minimum production cost is a challenging task. In fact, industrial practices usually set conservative cutting parameters and early cutting replacement policies in order to minimize the impact of cutting-tool wear on part quality. Although these practices may ensure part integrity, the production cost is far away to be minimized, especially in highly tool-consuming operations like mold and die micro-manufacturing. In this paper, an adaptive control optimization (ACO) system is proposed to estimate cutting-tool wear in terms of part quality and adapt the cutting conditions accordingly in order to minimize the production cost, ensuring quality specifications in hardened steel micro-parts. The ACO system is based on: (1) a monitoring sensor system composed of a dynamometer, (2) an estimation module with Artificial Neural Networks models, (3) an optimization module with evolutionary optimization algorithms, and (4) a CNC interface module. In order to operate in a nearly real-time basis and facilitate the implementation of the ACO system, different evolutionary optimization algorithms are evaluated such as particle swarm optimization (PSO), genetic algorithms (GA), and simulated annealing (SA) in terms of accuracy, precision, and robustness. The results for a given micro-milling operation showed that PSO algorithm performs better than GA and SA algorithms under computing time constraints. Furthermore, the implementation of the final ACO system reported a decrease in the production cost of 12.3 and 29 % in comparison with conservative and high-production strategies, respectively

Superconductivity and antiferromagnetism in a hard-core boson spin-1 model in two dimensions

A model of hard-core bosons and spin-1 sites with single-ion anisotropy is proposed to approximately describe hole pairs moving in a background of singlets and triplets with the aim of exploring the relationship between superconductivity and antiferromagnetism. The properties of this model at zero temperature were investigated using quantum Monte Carlo techniques. The most important feature found is the suppression of superconductivity, as long range coherence of preformed pairs, due to the presence of both antiferromagnetism and $S^z=\pm 1$ excitations. Indications of charge ordered and other phases are also discussed.Comment: One figure, one reference, adde