A Model of Silicon Nanocrystal Nucleation and Growth on SiO2 by CVD

2004 ◽  
Vol 830 ◽  
Author(s):  
M. W. Stoker ◽  
T. P. Merchant ◽  
R. Rao ◽  
R. Muralidhar ◽  
S. Straub ◽  
...  
Keyword(s):  
Crystallite Size ◽  
Flash Memory ◽  
Silicon Nanocrystals ◽  
Large Scale ◽  
Process Development ◽  
Electron Tunneling ◽  
Nucleation And Growth ◽  
Scale Model ◽  
Size Distributions ◽  
Deposition Processes

ABSTRACTSilicon nanocrystals can be used in non-volatile memory devices to reduce susceptibility to charge loss via tunnel oxide defects, allowing scaling to smaller sizes than possible with conventional Flash memory technology. In order to optimize device performance, it is desirable to maximize the nanocrystal density and surface coverage, while maintaining sufficient inter-crystallite separation to limit electron tunneling between adjacent crystallites. Ideally, crystallite densities in excess of 1012cm-2 with relatively narrow particle size distributions must be obtained, posing a significant challenge for process development and control. In order to facilitate development of such a process, a rate-expression-based model has been developed for the nucleation and growth of silicon nanocrystals on SiO2 in a CVD process. The model addresses the phenomena of nucleation, growth, and coalescence and includes the effects of exclusion zones surrounding the growing nuclei. The model uses a phenomenological expression to describe the nucleation rate and assumes that following nucleation, crystallite growth is dominated by gas-phase deposition processes, analogous to CVD of polycrystalline silicon. The model-predicted time-evolutions of crystallite densities and crystallite size distributions are consistent with experimental distributions as measured by Scanning Electron Microscopy (SEM). By coupling the model to a reactor-scale model of polysilicon CVD, it is possible to predict variations in the crystallite size distributions at various locations across a wafer as a function of reactor settings (temperature, pressure, flow rates, etc…). This in turn can be used for process control and optimization in order to ensure uniform deposition of nanocrystals in a large-scale manufacturing environment.

scholarly journals Investigating the Diurnal Evolution of the Cloud Size Distribution of Continental Cumulus Convection Using Multiday LES

2019 ◽  
Vol 76 (3) ◽  
pp. 729-747 ◽  
Author(s):  
Thirza W. van Laar ◽  
Vera Schemann ◽  
Roel A. J. Neggers
Keyword(s):  
Power Law ◽  
Cloud Cover ◽  
Large Scale ◽  
Correlation Coefficients ◽  
Scale Model ◽  
Cloud Base ◽  
Size Distributions ◽  
Total Cloud Cover ◽  
Surface Precipitation ◽  
Shallow Cumulus

Abstract The diurnal dependence of cumulus cloud size distributions over land is investigated by means of an ensemble of large-eddy simulations (LESs). A total of 146 days of transient continental shallow cumulus are selected and simulated, reflecting a low midday maximum of total cloud cover, weak synoptic forcing, and the absence of strong surface precipitation. The LESs are semi-idealized, forced by large-scale model output but using an interactive surface. This multitude of cases covers a large parameter space of environmental conditions, which is necessary for identifying any diurnal dependencies in cloud size distributions. A power-law exponential function is found to describe the shape of the cloud size distributions for these days well, with the exponential component capturing the departure from power-law scaling at the larger cloud sizes. To assess what controls the largest cloud size in the distribution, the correlation coefficients between the maximum cloud size and various candidate variables reflecting the boundary layer state are computed. The strongest correlation is found between total cloud cover and maximum cloud size. Studying the size density of the cloud area revealed that larger clouds contribute most to a larger total cloud cover, and not the smaller ones. Besides cloud cover, cloud-base and cloud-top height are also found to weakly correlate with the maximum cloud size, suggesting that the classic idea of deeper boundary layers accommodating larger convective thermals still holds for shallow cumulus. Sensitivity tests reveal that the results are only minimally affected by the representation of microphysics and the output resolution.

The Structure and Properties of MoSi2 Thin Film in Mos Process

1980 ◽  
Vol 38 ◽  
pp. 326-327
Author(s):  
C.K. Wu ◽  
P. Chang ◽  
N. Godinho
Keyword(s):  
Thin Film ◽  
Integrated Circuits ◽  
High Performance ◽  
Large Scale ◽  
Process Development ◽  
Structure And Properties ◽  
Metal Silicides ◽  
High Oxidation ◽  
Important Approach ◽  
High Oxidation Resistance

Recently, the use of refractory metal silicides as low resistivity, high temperature and high oxidation resistance gate materials in large scale integrated circuits (LSI) has become an important approach in advanced MOS process development (1). This research is a systematic study on the structure and properties of molybdenum silicide thin film and its applicability to high performance LSI fabrication.

RANCANG BANGUN PERANGKAT EKSPERIMENTASI PROSES PIROLISIS BIOMASA GELOMBANG MIKRO

2013 ◽  
Vol 14 (2) ◽  
Author(s):  
Noor Fachrizal
Keyword(s):  
Large Scale ◽  
Continuous Model ◽  
Biomass Energy ◽  
Scale Model ◽  
Small Scale ◽  
Laboratory Apparatus ◽  
Liquid Form ◽  
Large Scale Model ◽  
Bio Oil ◽  
Pyrolysis Of Biomass

Biomass such as agriculture waste and urban waste are enormous potency as energy resources instead of enviromental problem. organic waste can be converted into energy in the form of liquid fuel, solid, and syngas by using of pyrolysis technique. Pyrolysis process can yield higher liquid form when the process can be drifted into fast and flash response. It can be solved by using microwave heating method. This research is started from developing an experimentation laboratory apparatus of microwave-assisted pyrolysis of biomass energy conversion system, and conducting preliminary experiments for gaining the proof that this method can be established for driving the process properly and safely. Modifying commercial oven into laboratory apparatus has been done, it works safely, and initial experiments have been carried out, process yields bio-oil and charcoal shortly, several parameters are achieved. Some further experiments are still needed for more detail parameters. Theresults may be used to design small-scale continuous model of productionsystem, which then can be developed into large-scale model that applicable for comercial use.

scholarly journals Stator Non-Uniform Radial Ventilation Design Methodology for a 15 MW Turbo-Synchronous Generator Based on Single Ventilation Duct Subsystem

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2760
Author(s):  
Ruiye Li ◽  
Peng Cheng ◽  
Hai Lan ◽  
Weili Li ◽  
David Gerada ◽  
...  
Keyword(s):  
Finite Element ◽  
Temperature Distribution ◽  
Design Methodology ◽  
Large Scale ◽  
Synchronous Generator ◽  
Axial Direction ◽  
Scale Model ◽  
Element Analysis ◽  
Axial Temperature ◽  
Ventilation Duct

Within large turboalternators, the excessive local temperatures and spatially distributed temperature differences can accelerate the deterioration of electrical insulation as well as lead to deformation of components, which may cause major machine malfunctions. In order to homogenise the stator axial temperature distribution whilst reducing the maximum stator temperature, this paper presents a novel non-uniform radial ventilation ducts design methodology. To reduce the huge computational costs resulting from the large-scale model, the stator is decomposed into several single ventilation duct subsystems (SVDSs) along the axial direction, with each SVDS connected in series with the medium of the air gap flow rate. The calculation of electromagnetic and thermal performances within SVDS are completed by finite element method (FEM) and computational fluid dynamics (CFD), respectively. To improve the optimization efficiency, the radial basis function neural network (RBFNN) model is employed to approximate the finite element analysis, while the novel isometric sampling method (ISM) is designed to trade off the cost and accuracy of the process. It is found that the proposed methodology can provide optimal design schemes of SVDS with uniform axial temperature distribution, and the needed computation cost is markedly reduced. Finally, results based on a 15 MW turboalternator show that the peak temperature can be reduced by 7.3 ∘C (6.4%). The proposed methodology can be applied for the design and optimisation of electromagnetic-thermal coupling of other electrical machines with long axial dimensions.

scholarly journals A Lagrange Relaxation Based Decomposition Algorithm for Large-Scale Offshore Oil Production Planning Optimization

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1257
Author(s):  
Xiaoyong Gao ◽  
Yue Zhao ◽  
Yuhong Wang ◽  
Xin Zuo ◽  
Tao Chen
Keyword(s):  
Production Planning ◽  
Large Scale ◽  
Oil Production ◽  
Original Model ◽  
Decomposition Algorithm ◽  
Scale Model ◽  
Lagrange Relaxation ◽  
Planning Optimization ◽  
Offshore Oil Production ◽  
Offshore Oil

In this paper, a new Lagrange relaxation based decomposition algorithm for the integrated offshore oil production planning optimization is presented. In our previous study (Gao et al. Computers and Chemical Engineering, 2020, 133, 106674), a multiperiod mixed-integer nonlinear programming (MINLP) model considering both well operation and flow assurance simultaneously had been proposed. However, due to the large-scale nature of the problem, i.e., too many oil wells and long planning time cycle, the optimization problem makes it difficult to get a satisfactory solution in a reasonable time. As an effective method, Lagrange relaxation based decomposition algorithms can provide more compact bounds and thus result in a smaller duality gap. Specifically, Lagrange multiplier is introduced to relax coupling constraints of multi-batch units and thus some moderate scale sub-problems result. Moreover, dual problem is constructed for iteration. As a result, the original integrated large-scale model is decomposed into several single-batch subproblems and solved simultaneously by commercial solvers. Computational results show that the proposed method can reduce the solving time up to 43% or even more. Meanwhile, the planning results are close to those obtained by the original model. Moreover, the larger the problem size, the better the proposed LR algorithm is than the original model.

scholarly journals On the structural connectivity of large-scale models of brain networks at cellular level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giuseppe Giacopelli ◽  
Domenico Tegolo ◽  
Emiliano Spera ◽  
Michele Migliore
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Structural Connectivity ◽  
Network Models ◽  
Brain Regions ◽  
Cellular Level ◽  
Scale Model ◽  
Mathematical Framework ◽  
Underlying Mechanisms ◽  
Experimental Findings

AbstractThe brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the corresponding biological system. To solve this problem, we propose to use a new mathematical framework able to use sparse and limited experimental data to quantitatively reproduce the structural connectivity of biological brain networks at cellular level.

scholarly journals Trace element catalyses mineral replacement reactions and facilitates ore formation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yanlu Xing ◽  
Joël Brugger ◽  
Barbara Etschmann ◽  
Andrew G. Tomkins ◽  
Andrew J. Frierdich ◽  
...  
Keyword(s):  
Mass Transfer ◽  
Trace Elements ◽  
Fluid Flow ◽  
Large Scale ◽  
Metal Accumulation ◽  
Nucleation And Growth ◽  
Reaction Interface ◽  
Ore Formation ◽  
Key Factor ◽  
Mineral Replacement

AbstractReaction-induced porosity is a key factor enabling protracted fluid-rock interactions in the Earth’s crust, promoting large-scale mineralogical changes during diagenesis, metamorphism, and ore formation. Here, we show experimentally that the presence of trace amounts of dissolved cerium increases the porosity of hematite (Fe2O3) formed via fluid-induced, redox-independent replacement of magnetite (Fe3O4), thereby increasing the efficiency of coupled magnetite replacement, fluid flow, and element mass transfer. Cerium acts as a catalyst affecting the nucleation and growth of hematite by modifying the Fe2+(aq)/Fe3+(aq) ratio at the reaction interface. Our results demonstrate that trace elements can enhance fluid-mediated mineral replacement reactions, ultimately controlling the kinetics, texture, and composition of fluid-mineral systems. Applied to some of the world’s most valuable orebodies, these results provide new insights into how early formation of extensive magnetite alteration may have preconditioned these ore systems for later enhanced metal accumulation, contributing to their sizes and metal endowment.

Sign in / Sign up

Export Citation Format

Share Document