Price Tags, Smartphones, Large-Scale Screens,…

Display technology continues to evolve rapidly, powering everything from mobile devices to high-resolution monitors and emerging flexible screens. Thin-Film Transistors (TFTs) form the backbone of modern displays, with technologies ranging from amorphous silicon to advanced oxide semiconductors like IGZO and organic materials. As pixel densities increase and new form factors emerge, developing reliable, efficient TFT structures requires sophisticated simulation capabilities that can predict device behavior across different materials, architectures, and operating conditions.

Thin-Film Transistors for Display Applications

Display TFTs present unique challenges compared to conventional silicon devices, including amorphous and polycrystalline material structures, large-area fabrication requirements, and performance optimization across varying temperature and illumination conditions.

  • a-Si (Amorphous Silicon) offers mature, cost-effective manufacturing for mainstream displays.
  • LTPS (Low-Temperature Polysilicon) provides higher carrier mobility for high-performance displays.
  • IGZO and Oxide Semiconductors deliver excellent uniformity over large areas, low off-state current, and transparency for emerging applications.
  • Organic Materials enable flexible and lightweight displays with unique optical properties.

GTS Minimos-NT provides the comprehensive simulation framework needed to analyze and optimize display TFTs from device level to integrated pixel circuits.

 

TFT display / amorphous silicon, bottom-gated half corbino – top view of the layout
3D simulation of a-Si TFT: corner section
3D simulation of a-Si TFT: straight section
Parameter variation, validation of 2D simulation accuracy by 3D
Anisotopic grid (detail)

From Classical to Modern TFT Generations

Modern TFT designs leverage three-dimensional structures to optimize performance within area constraints. Key structural elements include:

  • Gate electrode and dielectric layers
  • Active semiconductor channel (a-Si, LTPS, IGZO, or organic)
  • Source and drain contacts with appropriate barrier materials
  • Passivation and protective layers

GTS Framework enables rapid exploration of design variants, including bottom-gated, top-gated, and double-gated configurations.

Analyzing Display TFTs: From Structure to Performance

Process Emulation and Device Simulation

Device models can be efficiently generated based on layouts and process emulation flows yielding realistic conformal TFT topographies. Automated anisotropic mesh generation optimizes computational efficiency while maintaining accuracy in critical regions.

The workflow supports both full three-dimensional device simulation and efficient sectional approaches. Validation between 2D and 3D simulations ensures efficient analysis while maintaining predictive accuracy.

Materials Modeling and Physical Effects

Display TFTs require specialized materials models that capture the physics of amorphous and disordered semiconductors:

Effective Mobility Modeling accurately reproduces experimental gate bias dependency of mobility over large temperature ranges. Detailed microscopic models scale to the 100 nanometer range, while efficient effective models calibrated to measurement data optimize micrometer-scale devices typical in displays.

Amorphous Materials Physics employs stochastic modeling of spatially varying band-edge landscapes, accounting for non-conducting band-tail states. This intrinsically captures material variability and applies to any disordered amorphous material.

Contact Modeling with Schottky-barrier contacts ensures realistic current-voltage characteristics, particularly for different contact metals like molybdenum and titanium used in display fabrication.

IGZO TFT Reliability: Illumination stress – Ion reaction and diffusion modeling
IGZO TFT Reliability: ID / VGS
Amorphous Materials / Oxide Mobility Modeling
A schematic representation of the band-edge landscape and its concrete elements along a 1D cross-section. Gridding along the x-axis represents the Voronoi volumes associated with each mesh point along the cross-sectional line (squares), the orange line represents the band-edge at each point, and the dotted blue line is the Fermi level. The gridding along the y-axis represents energy ranges and corresponds to the histogram on the right showing the total number of mesh points with band-edges falling in the range between any given y-grid lines. Note that the histogram is representative of a much larger set of points than is shown in the figure, which is too small a sample for clear statistics. Finally, at any and all mesh points, we imagine a density-of-states (DOS) that includes the free and bound carriers centered around the band-edge energy at that mesh point.
TCAD versus experimental results from Germs et al. for the mobility as a function of voltage for different temperatures from 150 K to 350 K.
TCAD versus experimental results from Germs et al. for the mobility as a function of voltage for different temperatures from 150 K to 350 K plotted as a function of the inverse temperature for a fixed gate voltage, VG.
Variability (mean and standard deviation) in threshold voltage (Vth), subthreshold swing (SS) and ION as a function of IGZO spatial correlation length, λ. For λ less than the channel thickness (i.e. 5 nm) heavy variability is observed. λ = 10 nm (which corresponding to the channel thickness) is used for later simulations.

Comprehensive TFT Analysis and Optimization

GTS Framework enables multiple levels of analysis to address different aspects of TFT development:

Design of Experiments and Parameter Variation

The DOE (Design of Experiments) workflow efficiently explores critical parameter spaces including density-of-states distribution, interface trap characteristics, material composition, and geometric dimensions.

Computational Efficiency for Large-Area Devices

Anisotropic mesh capabilities and efficient numerical methods enable practical simulation times even for three-dimensional structures. Validation of two-dimensional simulation accuracy through selective three-dimensional analysis allows optimal resource allocation.

Reliability Analysis Under Operating Conditions

Illumination stress represents a critical reliability concern for transparent oxide semiconductors. The reliability modeling framework includes carrier generation based on input light spectrum and material absorption. A chemical module handles ion reaction and diffusion mechanisms, with photogenerated carriers accelerating chemical reactions and degradation processes.

IGZO TFT: Top and bottom gate
IGZO TFT: Effective Mobility
IGZO TFT: ID/VG, effective mobility

Advanced Solutions for Display Technology Development

Versatility across material systems and solid foundation in physics make GTS Framework ideal for display TFT analysis and optimization. The comprehensive material database includes specialized models for amorphous silicon, LTPS, IGZO, oxide semiconductors, and organic materials.

Whether developing next-generation IGZO backplanes, optimizing LTPS circuits, or exploring organic TFT architectures, GTS Minimos-NT delivers the predictive accuracy needed for confident design decisions. The Python API allows customization of simulation flows for particular applications.

Product Callout Box: GTS Minimos-NT – Simulate semiconductor devices and circuits: Run steady-state, transient, and small-signal analysis of arbitrary 2D and 3D device geometries. Advanced materials models for amorphous and disordered semiconductors. Integrated reliability simulation with illumination stress and chemical degradation.

icon_ToolMinimos-Name

GTS Minimos NT – simulate semiconductor devices and circuits: Run steady-state, transient, and small-signal analysis of arbitrary 2D and 3D device geometries. Combine multiple devices in a circuit with compact models. Run thermal analysys of devices and circuits.

icon_Framework-FW-Name

GTS Framework – the solid base of all GTS products and your working environment. Includes device editing, file management, distributed job execution, visualization, post-processing, a Python interface, etc.