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Agent Mira

Material Innovation by Reactive Agent

Automating chemical materials research through  intelligent search, AI-powered scientific models and computational workflows

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Realize Cross-scale R&D

Application Areas

Molecular Design

Structural Design

Computational Validation

Property Prediction

High-throughput Screening

Reaction Prediction

Condition Recommendations

Catalyst Design

Synthetic Route Planning

By-product Predic

Molecular Design

Material Property Prediction

Interpretable Model Iteration

Multi-Objective Optimization
Experiment Recommendation

Application Fields

Basic Chemical
Industry

Fine Chemicals

C1 Chemicals

Advanced Materials

Master Professional R&D with Ease

Research-grade Interaction

Multimodal Input Methods
Full-process Visibility and Control
Flexible File Browsing and Download Mmethods

Multimodal Input Methods

  • Search molecular databases
  • Upload structural files for automated parsing
  • Built-in sketching tools for freehand molecular design

Full-process Visibility and Control

  • Full-process visibility and control
  • Instant planning with real-time flexibility
  • Card-style task interface with full version history

Flexible File Browsing and Download Mmethods

  • Diverse navigation options for rapid browsing
  • Interactive result visualization for multiple file types
  • One-click download for end-to-end files and reports
Multi-agent Framework and Tool Matrix

Technology Foundation

User Interaction Layer Details

Professional Q&A

Basic Tool Invocation

Analysis, Summary, and Visualization

Complex Tasks

Intent Understanding

Task Orchestration

Task Execution

Analysis and Summary

Receive the orchestrated execution workflow

Workflow Orchestration Layer Details

Scenario Capabilities

Molecular Screening

Reaction Analysis

Design of Experiments (DoE)

Condition Optimization

Workflow Paradigms

Experience-driven: Deep Research Workflow

Mechanism-driven: Scientific Computing Workflow

Data-driven: Machine Learning Workflow

Receive specific instructions for tool invocation

ReactiveAI Platform - 6 Core Functional Modules

ReactGen

AI-driven Generative Design for Molecules & Reactions

Reactify

Computational Method Recommendation

ReactControl

AI-powered Real-Time Decision Model

ReactBO

Accelerator for Materials and Formulation Optimization

ReactNet

Autonomous Reaction Network Exploration

ReactHTE

Model-Guided High-Throughput Experimentation

Open-source Databases

PubChem

CCDC

USPTO

Material Project

Open Catalysts

OMol25

Open-source Databases

3 million-reaction database covering 11 common elements

2 million-Hessian matrix database

LLM-SDE

Self-developed Models

React-OT

OA-ReactDiff

LLM-EO

AlphaNet

T5Chem

Computational Tools

RDKit

Auto3D

CREST

xtb

GPU4PySCF

ORCA

Quantum Espresso

ABACUS

Agent Mira is Continuously Evolving

Capability Roadmap

Deep research on domain literature and patent

Enrichment of high-value datasets and knowledge bases

Upgrades to generative models and reaction-network algorithms

Visualization and analysis of scientific figures and charts

Integration with high-throughput automated workcells

Broader support for open-source ecosystem

Deep Principle is a global leader in AI for Materials, dedicated to accelerating innovation in materials through artificial intelligence. The name embodies the fusion of deep learning and first principles, aiming to deeply reconstruct the fundamental operating principles of the microscopic world (the particle world).
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