OxideTFT-Studio: High-Fidelity IGZO TFT Simulation

OxideTFT-Studio is a high-precision, interactive physics simulation tool for Amorphous Oxide Semiconductor Thin-Film Transistors (AOS-TFTs), specifically focused on IGZO technology.

It uses the Finite Difference Method (FDM) to solve the 2D Poisson equation self-consistently with carrier statistics, allowing researchers and engineers to visualize potential distribution, carrier concentration, and electric fields in real-time.

🛠️ Usage

website：https://oxide-tft-simulation-z3wjys5v3czfmapanua62v.streamlit.app

🌟 Key Features

• Multi-Structure Support: Simulate various device architectures:
  • Double Gate
  • Single Gate (Top/Bottom)
  • Source-Gated Transistor
• Advanced Stacked Buffer Model:
  • Support for composite dielectric layers: SiN (Nitride) + SiO (Oxide) buffer stacks.
  • Configurable thickness and permittivity for all layers (Buffer, Active IGZO, GI).
• High-Precision Mesh:
  • User-defined mesh density (up to 1000+ points in the active region).
  • Physics-aware sub-sampling for high-definition rendering of the thin active channel (50nm typical).
• Interactive Visualization:
  • Heatmaps for Carrier Concentration ($n$) and Electric Field ($E$).
  • Vertical 1D cut-lines for profile analysis.
  • Powered by Plotly for interactive zooming and inspection.

🛠️ Installation

1. Clone the repository

   git clone [https://github.com/your-username/oxide-tft-simulation.git](https://github.com/your-username/oxide-tft-simulation.git)
   cd oxide-tft-simulation

2. Install dependencies It is recommended to use a virtual environment.

   pip install -r requirements.txt

3. Run the Simulation

   streamlit run app.py

   The tool will open automatically in your web browser at http://localhost:8501.

📐 Physics Engine

The core solver (solver.py) implements a numerical solution for the Poisson equation:

$$ \nabla \cdot (\epsilon \nabla \phi) = -q (N_{d}^{+} - n) $$

Where:

• $n$ is the electron density calculated using Fermi-Dirac statistics (approximated for oxide semiconductors).
• $\phi$ is the electrostatic potential.
• $\epsilon$ is the position-dependent permittivity (SiN, SiO, IGZO).

The non-linear system is solved using a Newton-Raphson iteration loop until convergence is achieved.

📂 Project Structure

• app.py: The Streamlit frontend interface. Handles user input, calls the solver, and renders Plotly charts.
• solver.py: The physics engine. Contains the TFTPoissonSolver class, mesh generation logic, and the finite difference matrix builder.
• requirements.txt: List of Python dependencies (numpy, scipy, streamlit, plotly).

OxideTFT-Studio: 高精度 IGZO TFT 物理仿真工具

OxideTFT-Studio 是一款专为非晶氧化物半导体薄膜晶体管（AOS-TFTs）开发的高精度交互式物理仿真工具，重点针对 IGZO 技术进行了优化。

该项目使用有限差分法 (FDM) 对二维泊松方程进行自洽求解，结合载流子统计模型，允许研究人员和工程师实时可视化器件内部的电势分布、载流子浓度以及电场强度。

🛠️ Usage

传送门：https://oxide-tft-simulation-z3wjys5v3czfmapanua62v.streamlit.app

🌟 核心功能

• 多结构支持 (Multi-Structure Support):
  • 支持模拟多种器件架构：双栅 (Double Gate)、单栅 (顶栅/底栅)、源控晶体管 (Source-Gated)。
• 高级叠层 Buffer 模型 (Stacked Buffer Model):
  • 支持复合介质层模拟：SiN (氮化硅) + SiO (氧化硅) 叠层结构。
  • 支持自定义所有层（Buffer, 有源层 IGZO, GI）的厚度和介电常数。
• 高精度网格 (High-Precision Mesh):
  • 用户可自定义网格密度（有源区支持 1000+ 网格点）。
  • 针对超薄沟道（典型值 50nm）内置了物理感知的子采样算法，实现高清渲染。
• 交互式可视化 (Interactive Visualization):
  • 提供载流子浓度 ($n$) 和电场 ($E$) 的高分辨率热力图。
  • 支持垂直方向的 1D 切面分析 (Cut-line profile)。
  • 基于 Plotly 引擎，支持图表的实时交互、缩放和数据探查。

🛠️ 安装指南

1. 克隆仓库

   git clone [https://github.com/your-username/oxide-tft-simulation.git](https://github.com/your-username/oxide-tft-simulation.git)
   cd oxide-tft-simulation

2. 安装依赖 建议在 Python 虚拟环境中运行。

   pip install -r requirements.txt

3. 运行仿真

   streamlit run app.py

   启动后，工具将自动在你的默认浏览器中打开，地址通常为 http://localhost:8501。

📐 物理引擎说明

核心求解器 (solver.py) 实现了泊松方程的数值解：

$$ \nabla \cdot (\epsilon \nabla \phi) = -q (N_{d}^{+} - n) $$

其中：

• $n$ 为电子浓度，由费米-狄拉克统计计算（针对氧化物半导体进行了近似）。
• $\phi$ 为静电势。
• $\epsilon$ 为位置相关的介电常数（分别对应 SiN, SiO, IGZO 等区域）。

该非线性系统通过牛顿-拉夫逊 (Newton-Raphson) 迭代法求解，直至达到收敛标准。

📂 项目结构

• app.py: Streamlit 前端界面。负责处理用户输入、调用求解器并渲染 Plotly 图表。
• solver.py: 物理引擎后端。包含 TFTPoissonSolver 类、自适应网格生成逻辑以及有限差分矩阵构建算法。
• requirements.txt: 项目所需的 Python 依赖库列表 (numpy, scipy, streamlit, plotly)。