Modeling B clustering in Si and SiGe

2004 ◽  
Vol 810 ◽  
Author(s):  
Ljubo Radic ◽  
Aaron D. Lilak ◽  
Mark E. Law
Keyword(s):  
Thermal Processing ◽  
Control Sample ◽  
Amorphous Layer ◽  
Dissolution Time ◽  
Uphill Diffusion ◽  
Physically Based Model ◽  
Diffusion Behavior ◽  
Clustering Model ◽  
Physically Based ◽  
First Time

ABSTRACTOur experiments show boron-interstitial cluster dissolution is reduced during oxidation, a behavior not predicted by the current models. Both our experiments and others on the time dependence indicate the reactivation is coming from more than one cluster. Since oxidation induced interstitial injection reduces reactivation, one of the significant clusters has to release an interstitial release during dissolution. Recent ab-initio calculations provide a qualitatively different B clustering model, with two significant cluster species. Based on these energetics, we have developed a new physically based model that for the first time accounts for the experimentally observed cluster dissolution time and ambient dependence.Anomalous B diffusion behavior is also observed in an investigation of Ge influence on B diffusion. Silicon wafers were subjected to a Si preamorphization implant (PAI), followed by Ge and B implants contained within the existing amorphous layer. The control sample received only Si PAI and B implant. Upon annealing, the peak of the B profile shifts towards the surface and increases in magnitude, exhibiting uphill diffusion. The control samples subjected to the same thermal processing exhibit TED, but no uphill diffusion behavior. This is consistent with the model of B diffusion in Si1−xGex, accounting for trapping of B at Ge sites through formation of GeB complex.

Modeling of Damage Evolution During Ion Implantation Into Silicon: A Monte Carlo Approach

1996 ◽  
Vol 439 ◽  
Author(s):  
S. Tian ◽  
M. Morris ◽  
S. J. Morris ◽  
B. Obradovic ◽  
A. F. Tasch
Keyword(s):  
Ion Implantation ◽  
Damage Evolution ◽  
Damage Model ◽  
Amorphous Layer ◽  
High Dose ◽  
Defect Production ◽  
Implantation Damage ◽  
Wide Range ◽  
Physically Based ◽  
First Time

AbstractWe present for the first time a physically based ion implantation damage model which successfully predicts both the as-implanted impurity range profiles and the damage profiles for a wide range of implant conditions for arsenic, boron, phosphorus, and BF2 implants into single-crystal (100) silicon. In addition, the amorphous layer thicknesses predicted by this damage model for high dose implants are also generally in excellent agreement with experiments. This damage model explicitly simulates the defect production and its subsequent evolution into the experimentally observable profiles for the first time. The microscopic mechanisms for damage evolution are further discussed.

Modeling of Damage Evolution During Ion Implantation into Silicon: a Monte Carlo Approach

1996 ◽  
Vol 438 ◽  
Author(s):  
S. Tian ◽  
M. Morris ◽  
S. J. Morris ◽  
B. Obradovic ◽  
A. F. Tasch
Keyword(s):  
Ion Implantation ◽  
Damage Evolution ◽  
Damage Model ◽  
Amorphous Layer ◽  
High Dose ◽  
Defect Production ◽  
Implantation Damage ◽  
Wide Range ◽  
Physically Based ◽  
First Time

AbstractWe present for the first time a physically based ion implantation damage model which successfully predicts both the as-implanted impurity range profiles and the damage profiles for a wide range of implant conditions for arsenic, boron, phosphorus, and BF2 implants into single-crystal (100) silicon. In addition, the amorphous layer thicknesses predicted by this damage model for high dose implants are also generally in excellent agreement with experiments. This damage model explicitly simulates the defect production and its subsequent evolution into the experimentally observable profiles for the first time. The microscopic mechanisms for damage evolution are further discussed.

scholarly journals A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA

2019 ◽  
Vol 19 (11) ◽  
pp. 2477-2495
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel
Keyword(s):  
Statistical Approach ◽  
Joint Probability ◽  
North Cascades ◽  
Physically Based Model ◽  
New Approach ◽  
The North ◽  
Debris Avalanches ◽  
Landslide Hazards ◽  
Infinite Slope Stability Model ◽  
Physically Based

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.

Precursor engineering for high-quality Cs2AgBiBr6 films toward efficient lead-free double perovskite solar cells

2021 ◽  
Author(s):  
Ping Hou ◽  
Wenxiang Yang ◽  
Ning Wan ◽  
Zhi Fang ◽  
Jinju Zheng ◽  
...  
Keyword(s):  
Solar Cells ◽  
Perovskite Solar Cells ◽  
Control Sample ◽  
Double Perovskite ◽  
Lead Free ◽  
High Quality ◽  
Precursor Engineering ◽  
First Time

We report a facile BiBr3(DMSO)2 adduct process to produce high-quality Cs2AgBiBr6 films with large grains for the first time, which leads to an enhancement of over 40% on the PCE of Cs2AgBiBr6-based solar cells compared to that of the control sample.

New physically based model for thermal induced initial stress in 3D for silicon germanium films after deposition

2014 ◽  
Vol 33 (6) ◽  
pp. 2121-2138 ◽  
Author(s):  
Abderrazzak El Boukili
Keyword(s):  
Thermal Expansion ◽  
Initial Stress ◽  
Silicon Germanium ◽  
Rate Of Change ◽  
Thermal Mismatch ◽  
Electronic Band ◽  
Physically Based Model ◽  
Content Type ◽  
Physically Based ◽  
Pmos Transistor

Purpose – The purpose of this paper is to provide a new three dimension physically based model to calculate the initial stress in silicon germanium (SiGe) film due to thermal mismatch after deposition. We should note that there are many other sources of initial stress in SiGe films or in the substrate. Here, the author is focussing only on how to model the initial stress arising from thermal mismatch in SiGe film. The author uses this initial stress to calculate numerically the resulting extrinsic stress distribution in a nanoscale PMOS transistor. This extrinsic stress is used by industrials and manufacturers as Intel or IBM to boost the performances of the nanoscale PMOS and NMOS transistors. It is now admitted that compressive stress enhances the mobility of holes and tensile stress enhances the mobility of electrons in the channel. Design/methodology/approach – During thermal processing, thin film materials like polysilicon, silicon nitride, silicon dioxide, or SiGe expand or contract at different rates compared to the silicon substrate according to their thermal expansion coefficients. The author defines the thermal expansion coefficient as the rate of change of strain with respect to temperature. Findings – Several numerical experiments have been used for different temperatures ranging from 30 to 1,000°C. These experiments did show that the temperature affects strongly the extrinsic stress in the channel of a 45 nm PMOS transistor. On the other hand, the author has compared the extrinsic stress due to lattice mismatch with the extrinsic stress due to thermal mismatch. The author found that these two types of stress have the same order (see the numerical results on Figures 4 and 12). And, these are great findings for semiconductor industry. Practical implications – Front-end process induced extrinsic stress is used by manufacturers of nanoscale transistors as the new scaling vector for the 90 nm node technology and below. The extrinsic stress has the advantage of improving the performances of PMOSFETs and NMOSFETs transistors by enhancing mobility. This mobility enhancement fundamentally results from alteration of electronic band structure of silicon due to extrinsic stress. Then, the results are of great importance to manufacturers and industrials. The evidence is that these results show that the extrinsic stress in the channel depends also on the thermal mismatch between materials and not only on the material mismatch. Originality/value – The model the author is proposing to calculate the initial stress due to thermal mismatch is novel and original. The author validated the values of the initial stress with those obtained by experiments in Al-Bayati et al. (2005). Using the uniaxial stress generation technique of Intel (see Figure 2). Al-Bayati et al. (2005) found experimentally that for 17 percent germanium concentration, a compressive initial stress of 1.4 GPa is generated inside the SiGe layer.

A physically based model to simulate maxillo-facial surgery from 3D CT images

1999 ◽  
Vol 15 (2) ◽  
pp. 217-221 ◽  
Author(s):  
Alessandro Sarti ◽  
Roberto Gori ◽  
Claudio Lamberti
Keyword(s):  
Ct Images ◽  
3D Ct ◽  
Physically Based Model ◽  
Facial Surgery ◽  
Physically Based

scholarly journals Development of a statistical tool for the estimation of riverbank erosion probability

SOIL ◽  
2016 ◽  
Vol 2 (1) ◽  
pp. 1-11 ◽  
Author(s):  
E. A. Varouchakis ◽  
G. V. Giannakis ◽  
M. A. Lilli ◽  
E. Ioannidou ◽  
N. P. Nikolaidis ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Statistical Methodology ◽  
Land Loss ◽  
Statistical Tool ◽  
Physically Based Model ◽  
Stream Management ◽  
Tool Performance ◽  
Riverbank Erosion ◽  
Physically Based ◽  
Local Habitat

Abstract. Riverbank erosion affects river morphology and local habitat, and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict areas vulnerable to erosion is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a statistical methodology is proposed to predict the probability of the presence or absence of erosion in a river section. A physically based model determines the locations vulnerable to erosion by quantifying the potential eroded area. The derived results are used to determine validation locations for the evaluation of the statistical tool performance. The statistical tool is based on a series of independent local variables and employs the logistic regression methodology. It is developed in two forms, logistic regression and locally weighted logistic regression, which both deliver useful and accurate results. The second form, though, provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed tool is easy to use and accurate and can be applied to any region and river.

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