Unprecedented Speed for Atomic InnovationThe AI simulation platform that accelerates new materials discovery

Matlantis transforms the research process for both computational and experimental chemists.
For computational chemists, it broadens application range and helps tackle complex challenges with greater speed and precision.
For experimental chemists, it provides instant access to predictive insights that guide and accelerate lab work. By integrating simulation and experimentation, Matlantis enables a next-generation workflow powered by your expertise.

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  • Hokkaido University logo
  • HYUNDAI logo
  • Nagoya Institute of Technology logo
  • Panasonic logo
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  • Preferred Networks

Breaking the "Rules" of Conventional Simulation
Do these limitations sound familiar?

  • "Calculations take too much time."
  • "Large-scale systems
    are tricky."
  • "When you want higher accuracy, 
    computational costs rise."

Matlantis Overturns That Premise

Unprecedented Calculation Speed

Instant inference on systems with tens of thousands of atoms

Simulate large-scale systems and long-term phenomena at previously unimaginable speeds, dramatically accelerating the trial-and-error cycle to deliver new discoveries in a fraction of the time.

True Versatility for
a Wide Variety of Materials

Perfect for a wide range of 
materials and structures

Our platform supports materials discovery across all elements in nature, and is designed to simulate a wide variety of structures—from bulk crystals and surfaces to interfaces and amorphous systems—offering powerful support for the search for unknown materials.

AI Models with
Quantum-Mechanical Accuracy

No data preparation or additional learning required

Our software features state-of-the-art AI models, pre-trained on a meticulously curated quantum mechanical dataset. Predict physical properties with high accuracy from the start—no specialized knowledge or additional training needed.

Secure and
Hassle-Free Computation on the Cloud

No infrastructure setup 
or management required

Access our platform instantly from any web browser—no environment to build or hardware to maintain. We manage all infrastructure, delivering a seamless, zero-maintenance experience so you can focus entirely on research and development.

Functions and Features

Accelerating R&D Enables Next-Generation Materials Discovery

Matlantis, equipped with a proprietary AI model, can perform simulations tens of millions of times faster than conventional electronic structure methods while maintaining high accuracy. Supporting a total of 96 elements—including all that occur naturally—Matlantis enables complex calculations that were not previously possible. By predicting atomic-level phenomena that cannot be captured by experiments alone, Matlantis contributes to new material design, advanced property prediction, and shortened development cycles.

 Features Tailored to Each User

Matlantis
 Portable Guide

Everything You Need to Know — Features, Benefits, and More
Download Now

Powered by World-Class AI Technology

Machine learning interatomic potentials: AI models that capture atomic behavior
We set out to create a general-purpose machine learning interatomic potential capable of predicting the properties of any material; once considered "too difficult to achieve," we have now succeeded.
Using cutting edge AI technology, we have developed a unique model called the PFP (PreFerred Potential).

Core Technology

PFP-Based Applied Technology

New Feature LightPFP

NEW

For users who require even larger-scale calculations, we’re introducing a feature that allows you to build custom potentials using PFP.

ReactionString/RestScan

We’re introducing two features: ReactionString, for optimizing reaction paths, and RestScan, for generating new ones.

Calculation Cases

Matlantis is applicable across a wide range of areas explored in modern materials science, including energy, electronics and polymer chemistry.

semiconductor

SiO₂ Dry Etching Simulation Using LightPFP

ALD

semiconductor

Analysis of Surface Reaction Mechanism between ALD Precursor and Substrate

Catalysts

Catalyst screening for Ammonia Synthesis Catalyst

Adsorbent

MOF

Analysis of CO2 adsorption dynamics of MOF using NEB method

Hildebrand solubility parameters

SP value

Calculation of Hildebrand solubility parameters

Ready to unlock your next discovery? Let's explore how Matlantis can transform your research.

Trusted by Industry and Academia

Matlantis has a proven track record helping customers across a range of industries with their material exploration.

Corporate and Research Institute Customers

100+

We support materials discovery at over 100 companies and research institutes worldwide.

Matlantis Users

900+

Matlantis is used not only by computational chemists but also by experimental researchers.

Number of Research Papers Using Matlantis

60+

Since starting operations in 2021, we have built a solid track record in materials science.

Information as of July 2025

Environment and Onboarding Process

Matlantis provides an optimal environment tailored to your needs,
along with comprehensive support to ensure long-term, successful use.

Product FAQ

Functionality & Usage

Can Matlantis be used for resin and polymer research?

Yes. Matlantis is accurate and flexible enough to simulate monomer reactivity and polymer substructures. It also supports systems containing both organic and inorganic elements.

What simulation environments are supported in Matlantis?

Matlantis supports integration with ASE and LAMMPS*. We provide detailed tutorials and documentation to help you implement them within the Matlantis environment.

*Available as a trial version

How are interatomic potentials selected in Matlantis?

In Matlantis, simulations are configured by writing Python code in a JupyterLab environment.

Technical & Computational

How many atoms can Matlantis handle in a single simulation?

Matlantis can typically handle systems ranging from a few thousand to several tens of thousands of atoms, depending on the computational requirements. For example, in the case of Pt (fcc), up to 44,000 atoms can be processed in a single simulation.

How does Matlantis handle van der Waals interactions?

Matlantis incorporates Grimme’s DFT-D3 dispersion corrections to accurately model van der Waals and other non-covalent interactions.

 What is the cutoff distance currently used in Matlantis simulations?

Since the release of PFP v6.0.0, the maximum cutoff distance has been increased to 9 Å, but the cutoff is adjusted depending on the density of the system.

Pricing, Access, & Support

What are the hardware requirements for Matlantis?

Matlantis runs entirely in the cloud, so there are no specific hardware requirements for users. You can access your tenant environment from any standard device—such as a laptop—with a Google account or Azure AD authentication and a standard network connection.

How can I get pricing and licensing information for Matlantis? Are there pay-per-use options?

Please contact our sales team to learn more about Matlantis pricing plans.

In which countries and regions is Matlantis available?

Matlantis is currently available in select regions across North America, Europe, and Asia Pacific. If you would like to check availability in your specific country or region, please contact our sales team.