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We provide easy-to-understand explanations of Matlantis terminology and the latest technology trends from an expert's perspective. We deliver information that will help you solve your problems and make new discoveries.
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Micro-Physical AI: The Atomic-Scale Frontier of Physical AI and the Future of Materials Discovery
What is Physical AI? Current LLMs (Large Language Models) learn about the world from text. Through this, they incorporate the knowledge accumulated by humans so far and are already having a major impact on the world. However, to borrow Plato's words, text is merely a "shadow" of reality. Text only records a portion of what humans have been able to verbalize, and the overwhelming majority of phenomena occurring in the physical world have not yet been turned into words.
CEO Blog
What Is the Semiconductor Front-End Process? A Materials Simulation Guide to Deposition, Lithography, Etching, and CMP
Semiconductor devices are manufactured by forming nanoscale structures on silicon wafers. This involves repeating numerous processes such as film deposition, photolithography, etching, ion implantation, and planarization to create fine circuit structures on the wafer. In these manufacturing processes, the physical properties of the materials and the reactions occurring at the surface and interface significantly impact device performance and yield. In recent years, the micro-scale of devices has been a key factor.
Explainer Computational Chemistry
From Lab to Deployment: Three Computational Trends Shaping the Future of Industry at TechConnect 2026
In early March, the Matlantis US team headed down to Raleigh, NC, for TechConnect World 2026. It’s one of the largest conferences in the country for applied innovation, covering everything from advanced materials and energy to sustainability and AI. While a conference like TMS (which we headed to right afterwards, see our report here
Conference Report
Three Computational Trends Reshaping Materials Science from TMS 2026
From March 15-19, 2026, the TMS 2026 Annual Meeting was held in San Diego under clear skies, bringing together thousands of materials scientists and engineers to share the latest research findings. Our Matlantis team also joined the circle of over 4,000 participants and presented our research results. Attending numerous sessions and directly interacting with leaders who are driving
Conference Report
AI pioneers materials development through computational chemistry
This article is a blog post based on an article written by Zhang, Customer Success Engineer Matlantis Corporation, which was published in the February 2026 issue of the technical magazine "Monthly Material Stage" in the special feature "Improving the Efficiency of Materials Development Using AI and Automated Experiments." 1. Materials Development to Date Our lives have been enriched by numerous innovative materials. However,
DFT Molecular Dynamics Machine Learning Interatomic Potentials Explainer
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Introduction to Machine Learning Interatomic Potentials (MLIPs): A Game Changer in Materials Simulation
Machine Learning Interatomic Potentials Explainer
Matlantis, an AI materials simulation that accelerates research, is taught at the University of Tokyo's SPRING GX lectures. Doctoral students experience AI-based molecular design simulations with ENEOS.
Interview
Matlantis gave a presentation at the 26th Asian Workshop
Conference Report
A new model for doctoral education pioneered through industry-academia collaboration: A "new pilot case" demonstrated by Institute of Science Tokyo and Taiyo Yuden Practice School
Interview
High-Accuracy and High-Speed MOF Calculations with Matlantis - Benchmark Results of Machine Learning Interatomic Potentials -
Explainer Computational Chemistry
Presentation given at the 86th The Japan Society of Applied Physics autumn meeting 2025
Conference Report
[Kyoto Univ. Prof. Kitagawa Wins the Nobel Prize in Chemistry]What is PCP / MOF? Explaining Their Impact and Significance
Explainer Computational Chemistry
![[Kyoto Univ. Prof. Kitagawa Wins the Nobel Prize in Chemistry]What is PCP / MOF? Explaining Their Impact and Significance](https://matlantis.com/wp-content/uploads/2025/10/ブログ_アイキャッチMOF-1-scaled.png)
The Future of Materials Science: Three Key Trends from ACS Fall 2025
Conference Report
[Event Report] Exhibited and presented at ACS Fall 2025
Conference Report
![[Event Report] Exhibited and presented at ACS Fall 2025](https://matlantis.com/wp-content/uploads/2025/08/title-image-scaled.jpg)
[For Beginners] What is Density Functional Theory (DFT)? | Basics
DFT Explainer Computational Chemistrychemistry
![[For Beginners] What is Density Functional Theory (DFT)? | Basics](https://matlantis.com/wp-content/uploads/2025/08/top_eyecatch-01-scaled.jpg)
Molecular Dynamics Simulations for Materials and Molecule Discovery - From Fundamental to Emerging Trends-
MD Explainer Computational Chemistry
How to Choose DFT Software: Representative Software by Application and Implementation Steps
DFT Explainer Computational Chemistrychemistry
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