Asymmetric diffusion at the interfaces in multilayers

Nanoscale diffusion at the interfaces in multilayers plays a vital role in controlling their physical properties for a variety of applications. In the present work depth-dependent interdiffusion in a Si/Fe/Si trilayer has been studied with sub-nanometer depth resolution, using x ray standing waves. High depth-selectivity of the present technique allows one to measure diffusion at the two interfaces of Fe namely, Fe-on-Si and Si-on-Fe, independently, yielding an intriguing result that Fe diffusivity at the two interfaces is not symmetric. It is faster at the Fe-on-Si interface. While the values of activation energy at the two interfaces are comparable, the main difference is found in the pre-exponent factor suggesting different mechanisms of diffusion at the two interfaces. This apparently counter-intuitive result has been understood in terms of an asymmetric structure of the interfaces as revealed by depth selective conversion electron Mossbauer spectroscopy. A difference in the surface free energies of Fe and Si can lead to such differences in the structure of the two interfaces.Comment: 4 pages, 5 figure

Computational models of the human visual cortex: on individual differences and ecologically valid input statistics

Perception relies on cortical processes in response to sensory stimuli. Visual input entering the eyes ascends a cascade of processing steps from the retina to high-level regions of the cortex. Vision science investigates these transformations that give rise to high-level processing of visual objects, such as object recognition. In this thesis I investigate computational models of the human visual cortex with regard to their ability to predict cortical responses to visual objects. In particular, I describe two factors playing an important role in using deep neural networks (DNNs) to better understand cortical functioning: the initial weight state and ecologically more valid input statistics. In Chapter 1 of this thesis I will introduce relevant literature pertaining to deep neural networks as a modeling framework for the visual cortex. Next, I will lay out the motivation for the research questions investigated in this thesis and described in detail in Chapters 2, 3, and 4. Chapter 2 focuses on the impact of the initial weight state of a model on its ability to predict cortical representations. I describe work in which we demonstrate that two DNN instances identical in every aspect but their initial weights, yield very dissimilar representations. Relying on single network instances to predict cortical activation patterns in response to sensory stimuli poses a problem for computational neuroscience: depending on the initial set of weights the ability to mirror the cortical representations of these stimuli might vary. Thus, results based on single (“off-the-shelf”) model instances - as commonly used in computational neuroscience - may not generalize. In contrast, using multiple DNN instances might alleviate this problem as they allow insights in the variability of a given model architecture to predict cortical representations. These individual differences between model instances suggest that to allow results to generalize more easily the model instances should be treated similar to human experimental participants. In Chapter 3 I focus on ecologically more valid input statistics (in the form of training images) aiming to improve a model’s ability to predict cortical representations. The most successful models of the human visual cortex to date are DNNs trained on object recognition tasks designed with machine learning goals in mind. However, the image sets used for training these DNNs are often not ecologically realistic. For example, training on the most-widely used image set in computational neuroscience (ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2012) requires the fine-grained distinction of 120 dog breeds, but does not contain visual object categories encountered frequently in everyday human life (e.g. woman, man, or child). This suggests that taking into account the human visual experience when training models of the human visual cortex on a categorization task might help to predict cortical representations. In this Chapter I describe the creation of a set of images aimed at mimicking the human visual diet: ecoset. Ecoset contains more than 1.5 million images from 565 basic level categories and is the largest image set specifically designed for computational neuroscience to date. Ecoset is freely available to allow the community to test their own hypotheses of models trained with input statistics matched to the human visual environment. In Chapter 4 we build on the results from the previous two Chapters. Using multiple DNN instances I investigate whether a brain-inspired model architecture (vNet) trained on ecologically more valid input statistics (ecoset) might improve its ability to predict cortical representations. I first demonstrate that ecoset might improve an architecture’s ability to mirror cortical representations. Furthermore, ecoset-trained vNet also outperforms state-ofthe- art computer vision and computational neuroscience models in terms of mirroring cortical representations in the human brain. Thus, incorporating biological and ecological aspects, such as brain-inspired architectural features and ecologically more valid input statistics, into computational models may yield better predictions of response patterns in the human visual cortex. Treating DNN instances similar to human experimental participants and considering ecological and biological factors for building these DNNs may be an important step towards better models of the human visual cortex. Such models might allow a better understanding of the cortical processes underlying high-level vision in the human brain.Cambridge Trust - Vice Chancellor's Award 2015 Cambridge Philosophical Society MRC Cognition and Brain Sciences Uni

Diffusion in Metals and Intermetallics: an Overview

After a few remarks about the history of diffusion in solids we remind the reader to some basics of diffusion such as tracer diffusion, interdiffusion, high- diffusivity paths, and basic diffusion mechanism in solids. We then summarize self-diffusion in cubic, hexagonal metals and metals with phase transformations. Then we summarize diffusion of substitutional impurities (solutes) in metals and remind the reader to the phenomena of slow solute diffusion in aluminium and of fast solute diffusion in polyvalent metals. We finish the part on solute diffusion with some remarks on interstitial impurities We start the part on intermetallic alloys by reminding the reader to some of the more frequent structures. We consider examples of the influence of order-disorder transformation on diffusion. We then discuss diffusion in cubic B2-structured phases and in B2-, L12 - and DO 3- intermetallics, We then discuss uniaxial L1 0 -intermetallics and C11 b-structured molybdenum disilicide. We finish with some remarks diffusion in the cubic Laves phase Co2 Nb.:1. Introduction – some historical remarks 2. Some basics 2.1 Tracer diffusion 2.2 Interdiffusion 2.2.2 The ‘random alloy’ approximation for interdiffusion 2.2.1 Boltzmann-Matano method 2.3 High-diffusivity paths in solids 2.4 Diffusion mechanisms in solids 3. Self-diffusion in metals 3.1 Cubic metals 3.2 Uniaxial metals 3.3 Metals with phase transitions 4, Impurity diffusion in metals 4.1 Diffusion of substitutional impurities 4.2 Slow impurity diffusion in aluminium 4.3 Fast impurity diffusion in polyvalent metals 4.4 Diffusion of fast diffusing interstitial impurities and of hydrogen 5. Diffusion in Intermetallics 5.1 Some structures of intermetallics 5.2 Influence of order-disorder transitions on diffusionThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/1 5.3 Diffusion in B2 phases and B2-intermetallics 5.4 Diffusion in L12-intermetallics 5.5 Diffusion in DO3-intermetallics 5.5 Diffusion in L10-intermetallics 5.6 Diffusion in C11b-structured molybdenum disilicide 5.6 Diffusion in the Laves phase Co 2N

Some aspects of Reproduction in Captive Mountain Lions Felis Concolor, Bobcats Lynx Rufus and Lynx Lynx Canadensis

More than 1500 vaginal smears and 75 0 urine samples were collected from 18 captive mountain lions, Felis concolor Linnaeus, 17 bobcats, Lynx rufus (Schreber), and 9 Canadian lynx, Lynx canadensis Kerr, from 1973-1974. Four types of epithelial cells were observed in the vaginal smears: parabasal, intermediate, cuboidal superficial and nivi- cuiar superficial. The smears were classified as anestrus , proestrus , estrus or metestrus on the basis of the four cell types and other smear characteristics . The reproductive behavior in captive mountain lions, bobcats, and lynx was also analyzed and the relationship between vagi- nal smear types and reproductive behavior patterns was determined. The reproductive behavior patterns of the three species were similar to each other and to patterns in the domestic cat, Felis catus Linnaeus , and included stages of anestrus, proestrus, estrus and metestrus. There was a highly significant association (P^. 0.001) between behavioral patterns and cytological appearance of the vaginal smear at every stage of the estrus cycle for each species. The change in type of vaginal smear, total urinary estrogen excretion and overt behavior were used to monitor seasonal variation in the reproductive cycle of two mountain lions and three bobcats from January 5, 1973 to December 31, 1974 . One mountain lion had seven the other s ix estrus periods over the two years . These e^rus periods occurred in seven separate months from March through November. However, eight (61%) of the estrus periods occurred from March through June indicating a seasonal influence on reproduction. The estrus periods averaged 8.1 days in length. Total estrogen excretion during the estrus perio- s averaged 49.82 xg/12 hr urine sample. The estrus cycle averaged 37.6 days and the estrous cycle averaged 5 9.5 days in length. Bobcats were observed to be seasonally polyestrus . Over a scan of two years, each of the three bobcats had five estrus periods from late March through early August. The estrus periods averaged 7.6 days in length. Total estrogen excretion during the estrus periods averaged 21.41 jjg/12 hr urine sample. The estrus cycle averaged 37.3 days in 1. * • » :’j§? \u27 • \u27 length and the estrous cycle averaged 46.4 days. Mountain lions, bobcats and lynx were injected daily with varying amounts of estradiol benzoate (EB) or pregnant mares serum gonadotrophin (PMSG) for up to 15 days to determine the utility of these hormones in inducing estrus and physiological levels of total estrogen excretion. The change in vaginal smear type and total estrogen excretion over the course of gestation also was determined in three mountain lions. Daily injections of 75-90 jjg EB or 80-125 IU PMSG for 15 days were effective in inducing estrus and physiological levels of total estrogen excretion in mountain lions. Daily injections of 20-30 jup EB or 70- 90 IU PMSG for 15 days were effective in bobcats. Daily injections of 20 i^g EB or 60-100 IU PMSG for 15 days were effective in lynx. The number of copulations and amount of total estrogen excretion appeared to be important in determining whether bleedings resulted in pregnancy. The vaginal smears of the three pregnant mountain lions contained predominantly parabasal cells from the second through the thirteenth week of gestation, except for one week when superficial cells were predominant. Total estrogen excretion was less than 11.0 mg/12 hr urine sample during the first week of gestation and gradually increased to an average of 44.28 mg/12 hr urine during the thirteenth week of gestation. There were minor peaks in total estrogen excretion during the same weeks that superficial cells were predominant. The vaginal smear was not useful in diagnosing pregnancy in the mountain lions

The Effects of Intrauterine Shock on the Emotionality of the Offspring in the Albino Rat

Recent research with animals indicates that stress applied during pregnancy can influence the emotionality of the offspring (Thompson, 1957; Fazzaro, 1971). The present study x^as designed to investigate the effects of escapable versus inescapable electric shock, administered during pregnancy, on the behavior of the offspring. Female Sprague-Dawley albino rats were mated and placed into three groups. Group I females were given daily sessions of twenty-five, escapable, 0.6mA shocks from Day 10 through Day 16 of pregnancy. Group II females were given the same amount of inescapable shock. Control subjects were placed in the shock apparatus for an equivalent amount of time but shock was never administered. The offspring were tested for ambulation in an open-field for three consecutive days at 60-80 days of age. They were also tested for avoidance acquisition in a two-way shuttlebox for three consecutive days at 66-93 days of age. The primary data for the latter test consisted of number of avoidances and number of intertrial responses (ITRs). The overall results suggest that the Group II (N=30) offspring were less emotional than either the Group I (N-25) or Control (N=22) offspring. This was inferred from their superior performance in the avoidance acquisition test (also increased ITRs) and their increased activity in the open-field. The Group I offspring were intermediate between the Group II and Control JSs in shuttlebox performance and open-field activity

Point defects in silicon after zinc diffusion - a deep level transient spectroscopy and spreading-resistance profiling study

We present results from spreading-resistance profiling and deep level transient spectroscopy on Si after Zn diffusion at 1294 K. Concentration profiles of substitutional in dislocation-free and highly dislocated Si are described by a diffusion mechanism involving interstitial-substitutional exchange. Additional annealing at 873 K following quenching from the diffusion temperature is required in the case of dislocation-free Si to electrically activate . The formation of complexes of with unwanted impurities upon quenching is discussed. Additional Ni diffusion experiments as well as total energy calculations suggest that Ni is a likely candidate for the passivation of Zns. From total energy calculations we find that the formation of complexes involving Zn and Ni depends on the position of the Fermi level. This explains differences in results from spreading-resistance profiling and deep level transient spectroscopy on near-intrinsic and p-type Si, respectively

Entropy and Entropy Production in Some Applications

By using entropy and entropy production, we calculate the steady flux of some phenomena. The method we use is a competition method, $S_S/\tau+\sigma={\it maximum}$, where $S_S$ is system entropy, $\sigma$ is entropy production and $\tau$ is microscopic interaction time. System entropy is calculated from the equilibrium state by studying the flux fluctuations. The phenomena we study include ionic conduction, atomic diffusion, thermal conduction and viscosity of a dilute gas