Natasha Dropka

Leibniz Institute for Crystal Growth

Germany

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Articles (25)

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2025

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Collaborators (6)

Klaus Böttcher

GERMANY

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Ta-Shun Chou

Leibniz Institute for Crystal Growth

GERMANY

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Iryna Buchovska

GERMANY

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Frank Woittennek

Full Professor

UMIT - Private Universität für Gesundheitswissenschaften, Medizinische Informatik und Technik

AUSTRIA

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Milena Petkovic

Head of Research Group

Leibniz-Institut für Kristallzüchtung

GERMANY

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Robert Menzel

Head of FZ-IV Group

Leibniz Institute for Crystal Growth

GERMANY

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Natasha Dropka

Research Interests

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Articles (25)

Toward a Universal Czochralski Growth Model Leveraging Data‐Driven Techniques

Comparative analysis of machine learning approaches for predicting and interpreting Cz-sapphire growth

Leveraging Transfer Learning to Overcome Data Limitations in Czochralski Crystal Growth

SyMO: A Hybrid Approach for Multi‐Objective Optimization of Crystal Growth Processes

Optimizing the morphology transition on MOVPE-grown (100) β-Ga2O3 film between step-flow growth and step-bunching: A machine learning-assisted approach

An Analysis of Elusive Relationships in Floating Zone Growth Using Data Mining Techniques

Data-driven feasibility study of VGF β-Ga2O3 growth under traveling magnetic fields

Unraveling conditions for W-shaped interface and undercooled melts in Cz-Si growth: A smart approach

Data‐Driven Cz–Si Scale‐Up under Conditions of Partial Similarity

Numerical modelling of Cz-β-Ga2O3 crystal growth in reactive atmosphere

Decision Tree-Supported Analysis of Gallium Arsenide Growth Using the LEC Method

Development of the VGF Crystal Growth Recipe: Intelligent Solutions of Ill‐Posed Inverse Problems using Images and Numerical Data

Development of Large‐Diameter and Very High Purity Ge Crystal Growth Technology for Devices

Toward Model-Based Control of the Vertical Gradient Freeze Crystal Growth Process

Smart Design of Cz-Ge Crystal Growth Furnace and Process

Artificial Intelligence for Crystal Growth and Characterization

Si doping mechanism in MOVPE-grown (100) β-Ga2O3 films

Adjustment of resistivity for phosphorus-doped n-type multicrystalline silicon

Machine learning supported analysis of MOVPE grown β-Ga2O3 thin films on sapphire

Toward Precise n-Type Doping Control in MOVPE-Grown β-Ga2O3 Thin Films by Deep-Learning Approach

Development and Optimization of VGF-GaAs Crystal Growth Process Using Data Mining and Machine Learning Techniques

Real Time Predictions of VGF-GaAs Growth Dynamics by LSTM Neural Networks

Application of Artificial Neural Networks in Crystal Growth of Electronic and Opto-Electronic Materials

Influence of impurities from SiC and TiC crucible cover on directionally solidified silicon

Semiconductor Crystal Growth under the Influence of Magnetic Fields

Collaborators (6)

Klaus Böttcher

Ta-Shun Chou

Iryna Buchovska

Frank Woittennek

Milena Petkovic

Robert Menzel

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