Crystal structure of fiber structured pentacene thin films

This PhD thesis presents a technique based on the grazing incidence crystal truncation rod (GI-CTR) X-ray diffraction method used to solve the crystal structure of substrate induced fiber structured organic thin films. The crystal structures of pentacene thin films grown on technologically relevant gate dielectric substrates are reported. It is widely recognized, that the intrinsic charge transport properties in organic thin film transistors (OTFTs) depend strongly on the crystal structure of the organic semiconductor layer. Pentacene, showing one of the highest charge carrier mobilities among organic semiconductors, is known to crystallize in at least four polymorphs, which can be distinguished by their layer periodicity d(001). Only two polymorphs (14.4 Å and 14.1 Å), grow as single crystals and their detailed crystal structure has been solved with standard crystallography techniques. The substrate induced 15.4 Å polymorph, the so called pentacene thin-film phase, is the most relevant for OTFT applications, since it grows at room temperature on technologically relevant gate dielectrics. However, the crystal structure of the pentacene thin-film phase has remained incomplete as it only grows as a fiber structured thin film. In this thesis, the GI-CTR X-ray diffraction technique is extended to fiber structured thin films. The X-ray diffraction experiments were carried out at the synchrotron source beamline W1 at HASYLAB in Hamburg, in order to obtain enough diffraction data for the determination of the crystal structure as pentacene thin films only grow as ultra thin films with crystal grains as small as 0.4μm. Pentacene thin films are also known to be sensitive to environmental conditions, such as light and oxygen. For this reason, the X-ray synchrotron measurements were performed in-situ. A portable ultra high vacuum growth chamber equipped with a rotatable sample holder and a beryllium window was built in order to perform X-ray measurements of up to four samples right after the thin film growth process without breaking the vacuum. Parallel to this, a versatile software package coded with Matlab in order to simulate, analyze and fit the complex data measured at the synchrotron source was developed. The complete crystal structure of the 15.4 Å pentacene thin-film polymorph grown on four model types of gate dielectric materials, amorphous silicon dioxide (a−SiO2), octadecyltrichlorosilane-treated a−SiO2 (OTS), Topas (“thermoplastic olefin polymer of amorphous structure”) and polystyrene films, was solved. It was found, that the unit cell parameters are identical within measurement precision on all measured substrates. The crystal structure belongs to the space group P-1 and was found to be triclinic with the following lattice parameters: a = 5.958 ± 0.005 Å, b = 7.596 ± 0.008 Å, c = 15.61 ± 0.01 Å, alpha = 81.25 ± 0.04°, beta = 86.56 ± 0.04° and 2 gamma = 89.80 ± 0.10°. The unit cell volume V = 697 Å^3 is the largest of all pentacene polymorphs reported so far. However, the molecular arrangement within the unit cell was found to be substrate dependent. Here, the following parameters are reported: The herringbone angle is 54.3°, 55.8°, 59.4° and 55.1° for a−SiO2, OTS, Topas and polystyrene, respectively. The tilts of the two molecular axes (theta_A, theta_B) are (5.6°, 6.0°), (6.4°,6.8°), (5.6°, 6.3°) and (5.7°, 6.0°) for a−SiO2, OTS, Topas and polystyrene, respectively. To conclude, it was shown that the molecular orientation in the unit cell differs among substrates while the unit cell dimensions of the 15.4 Å pentacene polymorph are identical. This indicates that substrate effects have to be included if one aims on understanding the molecular structure of the thin-film phase in detail. The crystal structures reported here provide a basis to apply techniques such as density functional methods to investigate intrinsic charge transport properties and optical properties of organic thin film devices on a molecular level. In previous studies it was observed that different substrates vary the charge carrier mobility in OTFTs. The substrate dependent crystal structures observed here could be one reason for this variation. This topic may lead ultimatively to a controlled finetuning of intrinsic charge transport properties. The experimental approach to determine the crystal structure developed here can be easily applied to a wide range of organic thin film systems used in organic electronic devices

From Correlation to Causation: Estimation of Effective Connectivity from Continuous Brain Signals based on Zero-Lag Covariance

Knowing brain connectivity is of great importance both in basic research and for clinical applications. We are proposing a method to infer directed connectivity from zero-lag covariances of neuronal activity recorded at multiple sites. This allows us to identify causal relations that are reflected in neuronal population activity. To derive our strategy, we assume a generic linear model of interacting continuous variables, the components of which represent the activity of local neuronal populations. The suggested method for inferring connectivity from recorded signals exploits the fact that the covariance matrix derived from the observed activity contains information about the existence, the direction and the sign of connections. Assuming a sparsely coupled network, we disambiguate the underlying causal structure via $L^1$-minimization. In general, this method is suited to infer effective connectivity from resting state data of various types. We show that our method is applicable over a broad range of structural parameters regarding network size and connection probability of the network. We also explored parameters affecting its activity dynamics, like the eigenvalue spectrum. Also, based on the simulation of suitable Ornstein-Uhlenbeck processes to model BOLD dynamics, we show that with our method it is possible to estimate directed connectivity from zero-lag covariances derived from such signals. In this study, we consider measurement noise and unobserved nodes as additional confounding factors. Furthermore, we investigate the amount of data required for a reliable estimate. Additionally, we apply the proposed method on a fMRI dataset. The resulting network exhibits a tendency for close-by areas being connected as well as inter-hemispheric connections between corresponding areas. Also, we found that a large fraction of identified connections were inhibitory.Comment: 18 pages, 10 figure

Dynamic Power Management for Neuromorphic Many-Core Systems

This work presents a dynamic power management architecture for neuromorphic many core systems such as SpiNNaker. A fast dynamic voltage and frequency scaling (DVFS) technique is presented which allows the processing elements (PE) to change their supply voltage and clock frequency individually and autonomously within less than 100 ns. This is employed by the neuromorphic simulation software flow, which defines the performance level (PL) of the PE based on the actual workload within each simulation cycle. A test chip in 28 nm SLP CMOS technology has been implemented. It includes 4 PEs which can be scaled from 0.7 V to 1.0 V with frequencies from 125 MHz to 500 MHz at three distinct PLs. By measurement of three neuromorphic benchmarks it is shown that the total PE power consumption can be reduced by 75%, with 80% baseline power reduction and a 50% reduction of energy per neuron and synapse computation, all while maintaining temporary peak system performance to achieve biological real-time operation of the system. A numerical model of this power management model is derived which allows DVFS architecture exploration for neuromorphics. The proposed technique is to be used for the second generation SpiNNaker neuromorphic many core system

VLSI Implementation of a 2.8 Gevent/s Packet-Based AER Interface with Routing and Event Sorting Functionality

State-of-the-art large-scale neuromorphic systems require sophisticated spike event communication between units of the neural network. We present a high-speed communication infrastructure for a waferscale neuromorphic system, based on application-specific neuromorphic communication ICs in an field programmable gate arrays (FPGA)-maintained environment. The ICs implement configurable axonal delays, as required for certain types of dynamic processing or for emulating spike-based learning among distant cortical areas. Measurements are presented which show the efficacy of these delays in influencing behavior of neuromorphic benchmarks. The specialized, dedicated address-event-representation communication in most current systems requires separate, low-bandwidth configuration channels. In contrast, the configuration of the waferscale neuromorphic system is also handled by the digital packet-based pulse channel, which transmits configuration data at the full bandwidth otherwise used for pulse transmission. The overall so-called pulse communication subgroup (ICs and FPGA) delivers a factor 25–50 more event transmission rate than other current neuromorphic communication infrastructures

Электропривод скипового подъемника

В работе был разработан и спроектирован электропривод главного скипового подъёмника доменной печи на основе устройства преобразования тока SIMOREG- К. В ходе проектирования были рассчитаны параметры силовой цепи привода, произведён расчёт регулировочных характеристик преобразователя, параметров оптимальной настройки и логарифмических амплитудно-частотных и фазочастотных характеристик электропривода. Также был произведён расчёт переходных характеристик регулируемого электропривода методом математического моделирования и определены показатели качества, которые полностью удовлетворяют требованиям технического задания.The electric drive of the main skip hoist of the blast furnace was designed and designed on the basis of the SIMOREG-K current conversion device. During the design, the parameters of the drive power circuit were calculated, the converter adjusting characteristics, the optimum tuning parameters and the logarithmic amplitude-frequency and phase-frequency characteristics of the drive were calculated. The calculation of the transient characteristics of the regulated electric drive by the method of mathematical modeling was also carried out, and quality indicators were determined that fully satisfy the requirements of the technical assignment

Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System

Emulating spiking neural networks on analog neuromorphic hardware offers several advantages over simulating them on conventional computers, particularly in terms of speed and energy consumption. However, this usually comes at the cost of reduced control over the dynamics of the emulated networks. In this paper, we demonstrate how iterative training of a hardware-emulated network can compensate for anomalies induced by the analog substrate. We first convert a deep neural network trained in software to a spiking network on the BrainScaleS wafer-scale neuromorphic system, thereby enabling an acceleration factor of 10 000 compared to the biological time domain. This mapping is followed by the in-the-loop training, where in each training step, the network activity is first recorded in hardware and then used to compute the parameter updates in software via backpropagation. An essential finding is that the parameter updates do not have to be precise, but only need to approximately follow the correct gradient, which simplifies the computation of updates. Using this approach, after only several tens of iterations, the spiking network shows an accuracy close to the ideal software-emulated prototype. The presented techniques show that deep spiking networks emulated on analog neuromorphic devices can attain good computational performance despite the inherent variations of the analog substrate.Comment: 8 pages, 10 figures, submitted to IJCNN 201

How should novelty be valued in science?

<p>Box plot analysis of serum concentrations of sRAGE (A), esRAGE (B), S100A9 (C) and HMGB1 (D) in patients with CTEPH (n = 26) and controls (n = 33). Independent Student’s t-test was used to compare groups. <i>RAGE</i> receptor for advanced glycation endproducts, <i>sRAGE</i> soluble RAGE, <i>esRAGE</i> endogenous secretory RAGE, <i>S100A9</i> member of S100 family of Ca+ binding proteins, <i>HMGB1</i> high mobility group box1, <i>CTEPH</i> chronic thromboembolic pulmonary hypertension.</p

Исследование свойств медных покрытий, полученных с помощью магнетрона с жидкофазной мишенью

В процессе работы проводились экспериментальные исследования структуры, шероховатости, электрического сопротивления и поверхности покрытий, полученных при разных условиях осаждения Осаждение медных покрытий из жидкой фазы с помощью МРС с испаряемой мишенью позволяет получить высокие скорости осаждения, низкое удельное электрическое сопротивление и хорошую адгезию пленок с подложкой по сравнению с осаждением из твердофазной МРС.In the course of the work, experimental studies of the structure, roughness, electrical resistance, and surface coatings obtained under different deposition conditions The deposition of copper coatings by means of an MSS with an evaporated target allows obtaining high deposition rates, low electrical resistivity, and good adhesion of the films to the substrate as compared to precipitation from the solid-state MSS

An interdisciplinary approach to data management

Many scientific issues involve interdisciplinary approaches that demand scientists with diverse skills and research fields. For the design and fabrication of new materials, this is especially true since new materials with macroscopically observable properties must be proposed based on changes at the molecular level. Research projects of this kind pose particular challenges for efficient execution and documentation, as research data management (RDM) tools usually fit very well to a specific research area, but cannot provide solutions for interdisciplinary topics. In order to guarantee consistent research and its documentation across disciplines, different tools, which may be used in several groups, must be used cooperatively. In the context of the Science Data Center MoMaF, among other things, strategies are being developed to enable research data management across scales. The RDM tools used for this are Chemotion and Kadi4Mat. The systems cover research at the molecular level (chemotion ELN) as well as simulation activities on the meso- and macroscopic scale (Kadi4Mat), and will be extended within the Science Data Center to enable cooperative use of the systems for work across scales. A first use case shows how Chemotion ELN can be used to document necessary parameters at the molecular level, in order to then be able to manage simulations of phase separation processes on their basis in a further step with the help of Kadi4Mat. For this purpose, the procedure and documentation method of already completed projects were first analysed in order to be able to propose a concept for future processes. Chemotion ELN is used in the presented procedure to document molecular descriptions, the performance of polymerization reactions and their outcome, as well as the properties obtained experimentally and from the literature. Kadi4Mat manages and transfers the parameters from the molecular description as input for mesoscopic simulations that describe the phase separation process in a time-dependent manner. Finally, by applying analysis tools on the time-dependent data via Kadi4Mat, macroscopic properties can be derived across scales as a function of the molecular composition