116 research outputs found
Multiskalensimulation des Ladungstransports in Silizium-Nanodraht-Transistoren: Evaluation der Grenzen des Simulationsmodells: Ist die Bestimmung von physikalischen Parameten aus gemessenem Strom-Spannungs-Kennlinien möglich?
Durch Multiskalensimulationen wird der Ladungstransport in nanodrahtbasierten Schottky-Barrieren-Feldeffekt-Transistoren im Materialsystem Ni2Si/Si untersucht. Die Bedingungen an die Genauigkeit der verwendeten Eingangsparameter werden bestimmt und Vorhersagen über optimale Material- und Geräteparameter werden getroffen. Es wird die Frage beantwortet, ob die Bestimmung von physikalischen Parametern aus einzelnen gemessenen Strom-Spannungs-Kennlinie möglich ist. Der Feldeffekt wird durch Berechnungen auf Basis der Finiten-Elemente-Methode und die resultierenden Stromflüsse durch ein quantenmechanisches Transportmodell ermittelt. In der Untersuchung der geometrischen Eingangsparameter wird gezeigt, dass bis auf den Radius des Nanodrahtes die in einem Experiment zu erwartenden Messfehler keinen drastischen Einfluss auf die Strom-Spannungs-Kennlinie haben. Signifikant ist hingegen der Einfluss der Temperatur, der effektiven Ladungsträgermassen und der Höhe der Schottky-Barriere. Da diese drei Eingangsparameter des betrachteten Systems mit relativ großen Ungenauigkeiten behaftet sind, ist die Bestimmung von physikalischen Parametern aus einzelnen gemessenen Strom-Spannungs-Kennlinien auf die erhoffte Weise nicht möglich. Die Arbeit zeigt auch, dass bereits moderate Veränderungen der Arbeitstemperatur einen bedeutenden Einfluss auf die Strom-Spannungs-Kennlinie haben. Für die Konstruktion von Transistoren mit hoher Stromdichte kann anhand der ermittelten Daten die Verkleinerung der aktiven Region durch Oxidation vorgeschlagen werden.:Kurzfassung/Abstract I
Verwendete Symbole IV
Verwendete Parameter VI
Verwendete Abkürzungen VII
1 Motivation 8
2 Grundlagen 9
2.1 Modellbildung und Simulation 9
2.2 Schottky-Diode 10
2.3 Feldeffekt-Transistor 12
2.4 Feldeffekt-Transistor auf der Basis von Silizium-Nanodrähten 13
3 Methoden 17
3.1 Simulationsmodell 17
3.2 Finite-Elemente-Methode 20
3.3 Landauer-Büttiker-Formalismus 21
3.4 Hamiltonoperator 22
3.5 Transmissionsfunktion 23
3.6 Büttiker Sonde 24
4 Ergebnisse und Diskussion 26
4.1 Implementierung des Simulationsprogrammes 26
4.2 Berechnung der Basis-Strom-Spannungs-Kennlinie 31
4.3 Wahl der Simulationsparameter 35
4.4 Abhängigkeit von geometrischen Parametern 41
4.5 Abhängigkeit von physikalischen Parametern 49
5 Zusammenfassung, Schlussfolgerungen und Ausblick 55
Abbildungsverzeichnis 59
Literatur 62Charge transport in nanowire-based Schottky-barrier field-effect transistors in the material system Ni2Si/Si is examined by multi-scale simulations. The requirements for the accuracy of the input parameters are determined and predictions about optimum material and device parameters are made. The question is answered, whether the determination of physical parameters from individual measured current-voltage curves is possible? The field effect is described by calculations based on the finite element method and the resulting currents are calculated with a quantum mechanical transport model. In the study of the geometric input parameters it is shown that experimental uncertainties do not drastically affect the current-voltage characteristic, except from the nanowire radius. However, significant is the influence of the temperature, the effective charge carrier mass and the height of the Schottky-barrier. Since these three input parameters are known only with low experimental accuracy for the considered system, the determination of physical parameters from individual measured current-voltage curves is not possible in the expected way. The results also show that moderate changes of the working temperature have a significant influence on the current-voltage characteristic. For the construction of transistors with high current density the reduction of the active region by oxidation is proposed.:Kurzfassung/Abstract I
Verwendete Symbole IV
Verwendete Parameter VI
Verwendete Abkürzungen VII
1 Motivation 8
2 Grundlagen 9
2.1 Modellbildung und Simulation 9
2.2 Schottky-Diode 10
2.3 Feldeffekt-Transistor 12
2.4 Feldeffekt-Transistor auf der Basis von Silizium-Nanodrähten 13
3 Methoden 17
3.1 Simulationsmodell 17
3.2 Finite-Elemente-Methode 20
3.3 Landauer-Büttiker-Formalismus 21
3.4 Hamiltonoperator 22
3.5 Transmissionsfunktion 23
3.6 Büttiker Sonde 24
4 Ergebnisse und Diskussion 26
4.1 Implementierung des Simulationsprogrammes 26
4.2 Berechnung der Basis-Strom-Spannungs-Kennlinie 31
4.3 Wahl der Simulationsparameter 35
4.4 Abhängigkeit von geometrischen Parametern 41
4.5 Abhängigkeit von physikalischen Parametern 49
5 Zusammenfassung, Schlussfolgerungen und Ausblick 55
Abbildungsverzeichnis 59
Literatur 6
Phytoene Desaturase Is Localized Exclusively in the Chloroplast and Up-Regulated at the mRNA Level during Accumulation of Secondary Carotenoids in Haematococcus pluvialis
How Ordinary Elimination Became Gaussian Elimination
Newton, in notes that he would rather not have seen published, described a
process for solving simultaneous equations that later authors applied
specifically to linear equations. This method that Euler did not recommend,
that Legendre called "ordinary," and that Gauss called "common" - is now named
after Gauss: "Gaussian" elimination. Gauss's name became associated with
elimination through the adoption, by professional computers, of a specialized
notation that Gauss devised for his own least squares calculations. The
notation allowed elimination to be viewed as a sequence of arithmetic
operations that were repeatedly optimized for hand computing and eventually
were described by matrices.Comment: 56 pages, 21 figures, 1 tabl
Disordered enthalpy–entropy descriptor for high-entropy ceramics discovery
The need for improved functionalities in extreme environments is fuelling interest in high-entropy ceramics1,2,3. Except for the computational discovery of high-entropy carbides, performed with the entropy-forming-ability descriptor4, most innovation has been slowly driven by experimental means1,2,3. Hence, advancement in the field needs more theoretical contributions. Here we introduce disordered enthalpy–entropy descriptor (DEED), a descriptor that captures the balance between entropy gains and enthalpy costs, allowing the correct classification of functional synthesizability of multicomponent ceramics, regardless of chemistry and structure. To make our calculations possible, we have developed a convolutional algorithm that drastically reduces computational resources. Moreover, DEED guides the experimental discovery of new single-phase high-entropy carbonitrides and borides. This work, integrated into the AFLOW computational ecosystem, provides an array of potential new candidates, ripe for experimental discoveries
Engineering improved ethylene production: Leveraging systems Biology and adaptive laboratory evolution
Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including E. coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate limiting steps in biological ethylene production. We employed a combination of genome scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to the EFE enzyme (WT vs mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges
Congenital microcephaly: Case definition & guidelines for data collection, analysis, and presentation of safety data after maternal immunisation.
Need for developing case definitions and guidelines for data collection, analysis, and presentation for congenital microcephaly as an adverse event following maternal immunisation
Congenital microcephaly, also referred to as primary microcephaly due to its presence in utero or at birth, is a descriptive term for a structural defect in which a fetus or infant’s head (cranium) circumference is smaller than expected when compared to other fetuses or infants of the same gestational age, sex and ethnic background
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the upcoming v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development
Engineering improved ethylene production: Leveraging systems Biology and adaptive laboratory evolution
Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including E. coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate limiting steps in biological ethylene production. We employed a combination of genome scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to the EFE enzyme (WT vs mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges
- …