Accommodation of lattice mismatch in Ge_(x)Si_(1−x)/Si superlattices

We present evidence that the critical thickness for the appearance of misfit defects in a given material and heteroepitaxial structure is not simply a function of lattice mismatch. We report substantial differences in the relaxation of mismatch stress in Ge_(0.5)Si_(0.5)/Si superlattices grown at different temperatures on (100) Si substrates. Samples have been analyzed by x‐ray diffraction, channeled Rutherford backscattering, and transmission electron microscopy. While a superlattice grown at 365 °C demonstrates a high degree of elastic strain, with a dislocation density <10^5 cm^(−2) , structures grown at higher temperatures show increasing numbers of structural defects, with densities reaching 2×10^(10) cm^(−2) at a growth temperature of 530 °C. Our results suggest that it is possible to freeze a lattice‐mismatched structure in a highly strained metastable state. Thus it is not surprising that experimentally observed critical thicknesses are rarely in agreement with those predicted by equilibrium theories

Strain relaxation kinetics in Si1–xGex/Si heterostructures

Strain relaxation in Si1–xGex/Si superlattices and alloy films is studied as a function of ex situ anneal treatment with the use of x-ray diffraction and Raman spectroscopy. Samples are grown by molecular-beam epitaxy at an unusually low temperature (≈365 °C). This results in metastably strained alloy and superlattice films significantly in excess of critical thicknesses previously reported for such structures. Significant strain relaxation is observed upon anneal at temperatures as low as 390 °C. After a 700 °C, 2 h anneal, superlattices are observed to relax less fully (~43% of coherent strain) than corresponding alloys (~84% of coherent strain). Also, the strain relaxation kinetics of a Si1–xGex alloy layer is studied quantitatively. Alloy strain relaxation is approximately described by a single, thermally activated, first order kinetic process having activation energy Ea=2.0 eV. The relevance of our results to the microscopic mechanisms responsible for strain relaxation in lattice-mismatched semiconductor heterostructures is discussed

Laser Calibration System for Time of Flight Scintillator Arrays

A laser calibration system was developed for monitoring and calibrating time of flight (TOF) scintillating detector arrays. The system includes setups for both small- and large-scale scintillator arrays. Following test-bench characterization, the laser system was recently commissioned in experimental Hall B at the Thomas Jefferson National Accelerator Facility for use on the new Backward Angle Neutron Detector (BAND) scintillator array. The system successfully provided time walk corrections, absolute time calibration, and TOF drift correction for the scintillators in BAND. This showcases the general applicability of the system for use on high-precision TOF detectors.Comment: 11 pages, 11 figure

Schottky-based band lineups for refractory semiconductors

An overview is presented of band alignments for small-lattice parameter, refractory semiconductors. The band alignments are estimated empirically through the use of available Schottky barrier height data, and are compared to theoretically predicted values. Results for tetrahedrally bonded semiconductors with lattice constant values in the range from C through ZnSe are presented. Based on the estimated band alignments and the recently demonstrated p-type dopability of GaN, we propose three novel heterojunction schemes which seek to address inherent difficulties in doping or electrical contact to wide-gap semiconductors such as ZnO, ZnSe, and ZnS

Short-Range Correlations and the Nuclear EMC Effect in Deuterium and Helium-3

The EMC effect in deuterium and helium-3 is studied using a convolution formalism that allows isolating the impact of high-momentum nucleons in short-ranged correlated (SRC) pairs. We assume that the modification of the structure function of bound nucleons is given by a universal (i.e. nucleus independent) function of their virtuality, and find that the effect of such modifications is dominated by nucleons in SRC pairs. This SRC-dominance of nucleon modifications is observed despite the fact that the bulk of the nuclear inelastic scattering cross-section comes from interacting with low-momentum nucleons. These findings are found to be robust to model details including nucleon modification function parametrization, free nucleon structure function and treatment of nucleon motion effects. While existing data cannot discriminate between such model details, we present predictions for measured, but not yet published, tritium EMC effect and tagged nucleon structure functions in deuterium that are sensitive to the neutron structure functions and bound nucleon modification functions.Comment: 9 pages, 9 figures, 1 table, and online supplementary material

Measuring Recoiling Nucleons From the Nucleus with the Future Electron Ion Collider

Short range correlated nucleon-nucleon (NN) pairs are an important part of the nuclear ground state. They are typically studied by scattering an electron from one nucleon in the pair and detecting its spectator correlated partner (“spectator-nucleon tagging”). The Electron Ion Collider (EIC) should be able to detect these nucleons, since they are boosted to high momentum in the laboratory frame by the momentum of the ion beam. To determine the feasibility of these studies with the planned EIC detector configuration, we have simulated quasielastic scattering for two electron and ion beam energy configurations: 5 GeV e− and 41 GeV/A ions, and 10 GeV e− and 110 GeV/A ions. We show that the knocked-out and recoiling nucleons can be detected over a wide range of initial nucleon momenta. We also show that these measurements can achieve much larger momentum transfers than current fixed target experiments. By detecting both low and high initial-momentum nucleons, the planned EIC has the potential to provide the data that should allow scientists to definitively show if the European Muon Collaboration effect and short-range correlation are connected, and to improve our understanding of color transparency

On the SigmaN cusp in the pp -> pK+Lambda reaction

Measurements of the $pp \to pK^+\Lambda$ reaction at $T_p$ = 2.28 GeV have been carried out at COSY-TOF. In addition to the $\Lambda p$ FSI and $N^*$ resonance excitation effects a pronounced narrow structure is observed in the Dalitz plot and in its projection on the $p\Lambda$-invariant mass. The structure appears at the $pp \to$N$K^+\Sigma$ threshold and is interpreted as $\Sigma$N cusp effect. The observed width of 20 MeV/$c^2$ is substantially broader than anticipated from previous inclusive measurements. Angular distributions of this cusp structure are shown to be dissimilar to those in the residual $pK^+\Lambda$ channel, but similar to those observed in the $pK^+\Sigma^0$ channel

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample