Oxide Semiconductor Composition Screening for Stable High-Mobility TFTs
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Solution Overview
Problem
Existing thin film transistors using oxide semiconductors face challenges in determining optimal composition ratios that balance carrier mobility, bandgap energy, and formation energy, leading to inconsistent device performance.
Innovation Solution
A simulation method is employed to select an optimal composition ratio for oxide semiconductors by checking compliance with Formulas 1, 2, and 3, which involve formation energy, bandgap energy, and Inverse State Weighted Overlap of Conduction band parameters, using density functional theory calculations and potentially machine-learning AI models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional trial-and-error methods are used to determine oxide semiconductor composition ratios, then manufacturing simplicity is maintained, but device performance consistency and reliability deteriorate
Solution Approach 1:
The patent performs preliminary computational screening using density functional theory (DFT) calculations to evaluate formation energy, bandgap energy, and carrier mobility for multiple composition ratios before actual manufacturing. This preliminary action identifies promising candidate compositions in advance, reducing the need for extensive trial-and-error manufacturing and improving device performance consistency.
Solution Approach 2:
The patent systematically varies composition parameters (ratios of In, Ga, Zn, Sn, and other elements) within specific ranges and evaluates each variation using computational models. By changing these parameters in a structured manner and selecting compositions that satisfy multiple criteria (formation energy < -3.0 eV, bandgap 2.0-4.0 eV, carrier mobility > 10 cm²/Vs), the method achieves reliable device performance without requiring complex manufacturing processes.
2Manufacturing precision
If multiple composition ratios are evaluated using comprehensive simulation methods, then optimal material properties are achieved, but computational time and resource requirements increase
Solution Approach 1:
The patent segments the composition evaluation process into distinct functional components: (1) defining target property ranges (formation energy, bandgap, carrier mobility), (2) generating candidate compositions within specific element ranges, (3) performing DFT calculations on candidates, and (4) filtering based on multiple criteria. This segmentation allows systematic evaluation of multiple compositions while managing computational resources through prioritization of promising candidates.
Solution Approach 2:
The patent optimizes computational efficiency by focusing DFT calculations on specific parameter ranges rather than exhaustively testing all possible compositions. By pre-defining acceptable ranges for formation energy (< -3.0 eV), bandgap (2.0-4.0 eV), and carrier mobility (> 10 cm²/Vs), the method reduces the search space and computational time while still achieving optimal composition ratios.
3Speed
If oxide semiconductor composition is optimized for high carrier mobility, then transistor speed improves, but formation energy and bandgap energy may deteriorate
Solution Approach 1:
The patent simultaneously optimizes multiple parameters by varying composition ratios within specific ranges. The method identifies compositions where carrier mobility exceeds 10 cm²/Vs while formation energy remains below -3.0 eV and bandgap falls within 2.0-4.0 eV. This multi-parameter optimization is achieved through systematic variation of element ratios (In:Ga:Zn:Sn) and filtering based on all three criteria, ensuring balanced material properties.
Solution Approach 2:
The patent employs composite oxide semiconductor materials containing multiple elements (In, Ga, Zn, Sn, and optionally other elements) in specific ratios to achieve a balance between carrier mobility and formation energy. The composite structure allows each element to contribute different properties: In and Ga provide high mobility, while Zn and Sn help stabilize the structure and control formation energy, achieving overall optimization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method enables the selection of an oxide semiconductor composition that enhances stability, reduces oxygen vacancies, improves optical reliability, and achieves high carrier mobility, thereby optimizing transistor characteristics.
Implementation Method 1
Ef may be formation energy of the oxide semiconductor calculated based on density functional theory (DFT), Eg may be bandgap energy of the oxide semiconductor calculated based on the DFT
Data Source
AI summary
The disclosure relates to a simulation method for selecting an optimal composition ratio of an oxide semiconductor. The oxide semiconductor includes at least two elements selected from the group consisting of indium (In), gallium (Ga), zinc (Zn), tin (Sn), silver (Ag), aluminum (Al), cadmium (Cd), magnesium (Mg), antimony (Sb), silicon (Si), titanium (Ti), and zirconium (Zr); oxygen (O); and inevitable impurities. The simulation method includes setting a simulation target composition ratio set including various composition ratios of elements constituting the oxide semiconductor, checking whether the oxide semiconductor satisfies Formulas 1, 2, and 3 for each of the various composition ratios included in the simulation target composition ratio set, and selecting a composition ratio satisfying Formulas 1, 2, and 3 as an optimal composition ratio. Formulas 1, 2, and 3 may be the same as described in the specification.