Introduction to EMOS
What is EMOS?
EMOS (Electronic Materials Optimization System) is a comprehensive web-based platform designed for materials scientists and researchers working in electronic materials research. It provides a unified interface to access multiple databases, utilize various generation algorithms, and apply prediction models for materials discovery and optimization.
Key Concepts
Information Units
EMOS is built around three core types of Information Units:
Databases: Access to multiple materials databases including ICSD, COD, OQMD, AFLOWLIB, Materials Project, Alexandria, NOMAD, and JARVIS
Generators: AI-powered materials generation tools including MatterGen, GNoME, iMatGen, MatGAN, MolGAN, and others
Predictors: Property prediction models such as MatterSim, M3GNet, PFP, DeepMD, SynthNN, and eSEN
Features
Features are high-level workflows that combine multiple Information Units to solve specific research problems. They are organized into two main categories:
Materials Exploration: Tools for discovering, generating, and analyzing new materials
Electronics Application: Specialized features for electronic device development and optimization
System Architecture
EMOS follows a modular architecture where:
Each Information Unit has a standardized interface
Features combine multiple Information Units to solve specific problems
The system is designed for easy extension with new components
All components follow factory patterns for registration and instantiation
Core Workflow
The typical EMOS workflow follows these steps:
Select a Feature: Choose from Materials Exploration or Electronics Application categories
Configure Information Units: Select which databases, generators, and predictors to use
Provide Inputs: Enter the necessary parameters for your specific use case
Execute and Analyze: Run the feature and analyze the results
Benefits
Unified Access: Single interface to multiple tools and databases
Modular Design: Easy to extend and customize
Comprehensive Coverage: From basic material search to complex device optimization
Research-Focused: Designed specifically for materials science workflows
Scalable: Can handle both simple queries and complex multi-step workflows