Atomic-Level Semiconductor Simulation for Implantation Damage and Annealing

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current TCAD tools lack the capability to accurately simulate the distribution of damage caused by ion implantation and thermal annealing processes in semiconductor manufacturing, particularly in predicting structural defects and dislocations, and fail to integrate these processes into a unified simulation flow.

Innovation Solution

A TCAD-based simulation method that includes an amorphization model to simulate ion implantation-induced atomic displacement and a thermal diffusion model using a time-stamped force-bias Monte Carlo algorithm to predict the structural changes during ion implantation and thermal annealing, providing atomic-level detail on vacancies and interstitials.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If current TCAD tools are used to simulate ion implantation and thermal annealing processes, then the simulation can be performed, but the accuracy of predicting structural defects and dislocations is insufficient

Engineering Contradiction:

Improveprediction accuracy of structural defectsVSAvoidcapability to predict structural changes

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The simulation process is segmented into distinct stages: ion implantation simulation followed by thermal annealing simulation. Each stage uses specialized algorithms (amorphization model for implantation, kinetic Monte Carlo for annealing) to accurately capture the specific physics of that stage, thereby improving overall prediction accuracy of structural defects and dislocations

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary amorphization model that bridges the ion implantation process and the thermal annealing process. This intermediary representation of the damaged crystal structure enables accurate coupling between the two processes, allowing the simulation to predict structural changes that neither model could capture alone

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If separate simulations are performed for ion implantation and thermal annealing, then each process can be modeled, but they cannot be integrated into a unified simulation flow

Engineering Contradiction:

Improveintegration capability of simulation processesVSAvoidcomplexity of simulation framework

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent merges the ion implantation simulation and thermal annealing simulation into a unified TCAD framework. The amorphization model output from implantation simulation directly feeds into the kinetic Monte Carlo annealing simulation, creating an integrated workflow that can predict the combined effect of both processes on semiconductor structures

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The simulation framework is designed with universal interfaces that can handle multiple simulation types (ion implantation, thermal annealing) within a single unified system. This multi-functional approach allows the same TCAD tool to perform both simulations sequentially, improving adaptability while managing complexity through standardized data structures

Inventive Principle:

Principle #6Universality (Multi-functionality)

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

Enables accurate prediction of structural changes in semiconductor manufacturing processes, reducing the need for experimental validation and saving time and resources by simulating the entire process without empirical data, thus improving the precision of semiconductor device design.

Implementation Method 1

an amorphization model to simulate ion implantation-induced atomic displacement

Methodology Applied

Scientific EffectIon implantation: Ion Implantation

Implementation Method 2

a thermal diffusion model using a time-stamped force-bias Monte Carlo algorithm to predict the structural changes during ion implantation and thermal annealing

Methodology Applied

Scientific EffectThermal diffusion: Diffusion

Data Source

PatentUS20250307510A1Methods for simulating atomic structures in semiconductor manufacturing process

Publication Date: 2025.10.02 TAIWAN SEMICONDUCTOR MANUFACTURING CO LTD

AI summary

A method for simulating atomic structures in semiconductor manufacturing process is provided. The method includes the following operations. A first semiconductor structure data is received. The first semiconductor structure data comprises an atomic level information of each atom in a semiconductor structure. A second semiconductor structure data is generated by processing the first semiconductor structure data to obtain an expect atomic displacement of each atom in the semiconductor structure in a simulated ion implantation process. A third semiconductor structure data is generated by processing the second semiconductor structure data to obtain an expect atomic diffusion of each atom in the semiconductor structure in a simulated thermal annealing process.