On the importance of dislocation flow in continuum plasticity models for semiconductor materials

Nguyen, Binh Duong; Rausch, Alexander M.; Steiner, Johannes; Wellmann, Peter J.; Sandfeld, Stefan

doi:10.1016/j.jcrysgro.2019.125414

Cited by 9 publications

(8 citation statements)

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“…For this reason, numerical modeling is used to further characterize the hot zone during and after crystal growth, considering temperature fields of the crystal and source powder [ 24 , 25 , 26 ], mass transport [ 27 , 28 , 29 ], stress and growth kinetics [ 30 , 31 ], or dislocation dynamics [ 32 , 33 ]. However, to the knowledge of the authors, the impact of the change in CTE caused by nitrogen doping on stress was not yet investigated numerically.…”

Section: Introductionmentioning

confidence: 99%

Impact of Mechanical Stress and Nitrogen Doping on the Defect Distribution in the Initial Stage of the 4H-SiC PVT Growth Process

Steiner

Wellmann

2022

Materials

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Nitrogen incorporation changes the lattice spacing of SiC and can therefore lead to stress during physical vapor transport (PVT). The impact of the nitrogen-doping concentration during the initial phase of PVT growth of 4H-SiC was investigated using molten potassium hydroxide (KOH) etching, and the doping concentration and stress was detected by Raman spectroscopy. The change in the coefficient of thermal expansion (CTE) caused by the variation of nitrogen doping was implemented into a numerical model to quantitatively determine the stress induced during and after the crystal growth. Furthermore, the influence of mechanical stress related to the seed-mounting method was studied. To achieve this, four 100 mm diameter 4H-SiC crystals were grown with different nitrogen-doping distributions and seed-mounting strategies. It was found that the altered CTE plays a major role in the types and density of defect present in the grown crystal. While the mounting method led to increased stress in the initial seeding phase, the overall stress induced by inhomogeneous nitrogen doping is orders of magnitude higher.

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Section: Introductionmentioning

confidence: 99%

Impact of Mechanical Stress and Nitrogen Doping on the Defect Distribution in the Initial Stage of the 4H-SiC PVT Growth Process

Steiner

Wellmann

2022

Materials

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“…In case of SiC or Si a penetration depth of only some µm remain instead of 750 µm wafer thickness. As shown in Figure 3c all the different types of dislocations become distinguishable: [90] A low number of micropipes but many threading screw dislocations which are connected by a network of basal plane edge dislocations.…”

Section: Characterization Of Dislocations and Extended Defects In Sicmentioning

confidence: 99%

“…Such information about meso-and macroscopic strain distribution combined with numerical simulations is key to optimize the growth conditions and to improve the crystal quality as demonstrated by Wellmann's group. [90] The transmission topography integrates over the full transmitted volume of a sample and at high dislocation density it becomes hard to distinguish single dislocations as shown in Figure 3b. In back-reflection mode the diffracting volume decreases in general with decreasing energy of the X-rays and increasing absorption of the crystals.…”

Section: Characterization Of Dislocations and Extended Defects In Sicmentioning

confidence: 99%

“…This behavior explains the initially surprising result, that after growth process of SiC the fast cooling down ends with a lower dislocation density than a slow cooling. [89,90] Up to here the movie may be regarded as "nice pictures," only displaying the well accepted theory of Frank-Read multiplication, [98] even though a really double ended Frank-Read source is shown for the first time. But it has to be taken into account that this high number of dislocations is originating and moving within the (0001) glide planes only.…”

Section: Dislocation Dynamics In Sic and Simentioning

confidence: 99%

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X‐Ray Topography—More than Nice Pictures

Danilewsky

2020

Crystal Research and Technology

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X‐ray topography—a well‐known diffraction imaging method—is widely used for the characterization of extended crystal defects like dislocations. Herein, the progress toward the quantification besides the number and nature of dislocations is given. The diffracted images include additional information about tilt and strain, which can be measured in real‐time, thanks to the improved digital detection systems. This allows not only the fast mapping of huge samples like 450 mm diameter Si wafers, the in situ observation of the dislocation, or crack dynamics at high temperatures, but also the stress analysis in electronic devices in operando. In addition to typical white X‐ray beam methods like stacks of section topographs, the monochromatic diffraction laminography allows a 3D representation of the dislocation arrays. The merits and limitations of X‐ray topography are demonstrated by semiconductor materials as an example.

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“…Understanding and controlling defects and their behavior is an essential task in semiconductor research and production, reducing the negative influence on electronic devices [1]. Furthermore, the predictive quality of simulations strongly depends on well-characterized defect structures, e.g., as initial values [2][3][4][5][6]. Many approaches have been performed to observe defects (e.g., micropipes (MPs) which are screw dislocations (SDs) with Burgers vector magnitude b ≥ 3c , threading screw dislocations (TSDs)) in these materials.…”

Section: Introductionmentioning

confidence: 99%

Automated analysis of X-ray topography of 4H-SiC wafers: Image analysis, numerical computations, and artificial intelligence approaches for locating and characterizing screw dislocations

Nguyen

Roder

Danilewsky

et al. 2023

Journal of Materials Research

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The physical vapor transport (PVT) crystal growth process of 4H-SiC wafers is typically accompanied by the occurrence of a large variety of defect types such as screw or edge dislocations, and basal plane dislocations. In particular, screw dislocations may have a strong negative influence on the performance of electronic devices due to the large, distorted or even hollow core of such dislocations. Therefore, analyzing and understanding these types of defects is crucial also for the production of high-quality semiconductor materials. This work uses automated image analysis to provide dislocation information for computing the stresses and strain energy of the wafer. Together with using a genetic algorithm this allows us to predict the dislocation positions, the Burgers vector magnitudes, and the most likely configuration of Burgers vector signs for the dislocations in the wafer. Graphical abstract

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On the importance of dislocation flow in continuum plasticity models for semiconductor materials

Cited by 9 publications

References 51 publications

Impact of Mechanical Stress and Nitrogen Doping on the Defect Distribution in the Initial Stage of the 4H-SiC PVT Growth Process

Impact of Mechanical Stress and Nitrogen Doping on the Defect Distribution in the Initial Stage of the 4H-SiC PVT Growth Process

X‐Ray Topography—More than Nice Pictures

Automated analysis of X-ray topography of 4H-SiC wafers: Image analysis, numerical computations, and artificial intelligence approaches for locating and characterizing screw dislocations

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