Investigation of Nanoparticles in High Resolution Scanning Electron Microscopy (SEM) and Low Voltage SEM by Digital Image-Analysis

Small particles (Cu, Ag, In, Sn, Au, also MgO and NaCl) were prepared in the diameter range from 1 nm to 100 nm on different conductive substrates by thermal evaporation in high-vacuum or in an inert gas atmosphere. Imaging of the particles was performed in a high resolution scanning electron microscope (HRSEM) that can also be operated at low beam voltages of a few hundred volts. This mode of operation is called low voltage SEM (LVSEM). Scanning electron micrographs were taken at different beam voltages VO (0.5-30 kV). The micrographs were digitally recorded and analyzed with an image processing system operated on-line to the HRSEM. Grey-value line profiles and densitometric quantities of single particles, as well as the contrast between particle and substrate, changed with VO. The results for tin-particles on a bulk carbon substrate are shown. In all cases considered, only positive contrasts, i.e., particles looking brighter than the substrate, were obtained. The main contrast producing mechanism is, therefore, assigned to effects that include the particle\u27s geometrical properties of size, shape and surface. Sn-, In-, and Ag-particles, imaged in the secondary electron (SE) mode showed significantly larger particle diameters, as did images simultaneously recorded with transmitted electrons; however, Au-particles did not show that difference. This effect may be qualitatively explained by SE resulting from decaying plasmons

Unpacking Agile Enterprise Architecture Innovation work practices: A Qualitative Case Study of a Railroad Company

Agile EA is the process for managing enterprise architecture modeling and redesign efforts with principles of agile methods. However, very little work has been done till date on how organizations adopt these methodological innovations such as integration of agile methods with enterprise architecture. This is problematic, because we know that organizations face stiff challenges in bringing new innovations that fundamentally disrupt their enterprise architecture. Hence we ask: How does agile EA get adopted in practice and what are the underlying mechanisms through which teams self-organize and adapt? To this end, we studied a large-scale agile EA development effort to modernize the legacy systems at a top railroad company referred to as “Alpha” (a pseudonym). Our qualitative analysis shows how multi-teams self-organize and adjust the pace of the development efforts by strategically (1) choosing different type of agile methods and (2) embedding resources across teams for increasing communications

Crossing the Chasm of Agile Enterprise Architecture Innovation: A Case Study of Service Modernization at a Railroad Company

Agile EA is the process for managing enterprise architecture modeling and redesign efforts with principles of agile methods such as iterations, lean thinking, pair programming etc., for faster development times. However, very little work has been done till date on how organizations adopt these methodological innovations such as integration of agile methods with enterprise architecture. This is problematic, because we know that organizations face stiff challenges in bringing new innovations that fundamentally disrupt their enterprise architecture. It is for this reason organizations rely on external consultants to internalize the concepts that are non-native to its actors. Hence we ask: What factors affect the adoption process of agile EA in organizations? If so what is the adoption rate over time? And what is the role of internal and external change agents in adoption process? To address this questions, we plan on conducting a field study in a top railroad company referred to as “Alpha” (a pseudonym) for exploring the variations in routines to understand the agile EA adoption process. Specifically, the proposed research study has two goals. First, we wish to develop a formal process theory about the adoption of agile enterprise architecture innovations using grounded theory approach. Second, through this study we would like to provide design guidelines for crossing the chasm of agile EA

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure

Investigation of the Dzyaloshinskii-Moriya interaction and room temperature skyrmions in W/CoFeB/MgO thin films and microwires

Recent studies have shown that material structures, which lack structural inversion symmetry and have high spin-orbit coupling can exhibit chiral magnetic textures and skyrmions which could be a key component for next generation storage devices. The Dzyaloshinskii-Moriya Interaction (DMI) that stabilizes skyrmions is an anti-symmetric exchange interaction favoring non-collinear orientation of neighboring spins. It has been shown that material systems with high DMI can lead to very efficient domain wall and skyrmion motion by spin-orbit torques. To engineer such devices, it is important to quantify the DMI for a given material system. Here we extract the DMI at the Heavy Metal (HM) /Ferromagnet (FM) interface using two complementary measurement schemes namely asymmetric domain wall motion and the magnetic stripe annihilation. By using the two different measurement schemes, we find for W(5 nm)/Co20Fe60B20(0.6 nm)/MgO(2 nm) the DMI to be 0.68 +/- 0.05 mJ/m2 and 0.73 +/- 0.5 mJ/m2, respectively. Furthermore, we show that this DMI stabilizes skyrmions at room temperature and that there is a strong dependence of the DMI on the relative composition of the CoFeB alloy. Finally we optimize the layers and the interfaces using different growth conditions and demonstrate that a higher deposition rate leads to a more uniform film with reduced pinning and skyrmions that can be manipulated by Spin-Orbit Torques

Tunneling magneto thermo power in magnetic tunnel junction nanopillars

We study the tunneling magneto thermo power (TMTP) in CoFeB/MgO/CoFeB magnetic tunnel junction nanopillars. Thermal gradients across the junctions are generated by a micropatterned electric heater line. Thermo power voltages up to a few tens of \muV between the top and bottom contact of the nanopillars are measured which scale linearly with the applied heating power and hence with the applied temperature gradient. The thermo power signal varies by up to 10 \muV upon reversal of the relative magnetic configuration of the two CoFeB layers from parallel to antiparallel. This signal change corresponds to a large spin-dependent Seebeck coefficient of the order of 100 \muV/K and a large TMTP change of the tunnel junction of up to 90%.Comment: Revised version containing additional data and analyis. 13 pages, 3 figure

The Effects of a Pre-Workout Energy Drink on Measures of Physical Performance

The purpose of this study was to investigate the effects of a pre-workout commercial energy drink on parameters of exercise performance, including anaerobic power, muscular endurance, speed, and reaction time. This study used a randomized, double blind, placebo controlled, parallel design. Participants visited the laboratory on two different occasions. On the first visit, participants were assessed for anaerobic power (via a vertical jump test), muscular endurance, reaction time, reactive sprint test, and aerobic power (via a 1.5 mile run). On the second visit, participants were randomly assigned to ingest four ounces of the energy drink beverage or a similar-tasting placebo beverage 30-minutes prior to engaging in these same physical performance tests. The energy drink treatment had no effect on anaerobic power (vertical jump), reaction time, reactive sprint test, or aerobic power. For the push-up to fatigue test, a significant difference (p = 0.014) was observed with the energy drink treatment enhancing performance by 12% as compared to the placebo treatment (improvement of ~ 4%). For the sit-up to fatigue test, a non-significant difference (p = 0.075) was observed with the energy drink treatment resulting in an enhancement of performance by ~13% as compared to no improvement for the placebo treatment. In light of these findings, individuals whose upper-body muscular endurance performance is part of their physical fitness assessment program may benefit from pre-workout energy drink consumption. In contrast, individuals needing to demonstrate anaerobic/aerobic power, or reactive abilities should not expect an improvement in performance from pre-workout energy drink consumption