PFCC Launches Matlantis Atomistic Simulator as Cloud-Based Service

Preferred Networks, Inc. (PFN), ENEOS Corporation (ENEOS) and their joint venture Preferred Computational Chemistry (PFCC) announced today that PFCC has launched Matlantis™, a cloud-based atomistic simulator that significantly accelerates discovery and development of new materials.

PFCC’s Matlantis supports large-scale materials discovery by quickly simulating the atomic-scale behavior of various materials. PFN and ENEOS have incorporated a deep learning model into a conventional physical simulator to increase the simulation speed by tens of thousands of times and to support a wide variety of materials. The deep learning model for Matlantis has been trained with a vast amount of atomic structure data generated by physical simulation on PFN’s supercomputers.

Key Features of Matlantis

1. Versatility

The atomistic simulation tasks that take hours to months using conventional DFT (density functional theory) methods on a high-performance computer can be finished in only a few seconds using Matlantis.

2. Speed

The atomistic simulation tasks that take hours to months using conventional DFT (density functional theory) methods on a high-performance computer can be finished in only a few seconds using Matlantis.

3. User-Friendliness

Thanks to the pre-trained deep learning model, physical property calculation library and high-performance computing environment, no hardware or software installations are required for performing simulations.

Origin of the name Matlantis

The product name Matlantis is a combination of “material” and “Atlantis,” a mythical continent appearing in Plato’s works that inspired adventurers worldwide. Out of 1060 theoretically possible functional molecules, mankind has discovered only a handful of useful materials. The name represents PFCC’s commitment to help companies discover innovative materials in the vast ocean of unknown molecules.

Comment from Daisuke Okanohara, CEO of PFCC

PFCC’s mission is to contribute to a sustainable future by enabling companies to create innovative materials,” said Daisuke Okanohara, Chief Executive Officer of PFCC. “To achieve this, we have combined Preferred Networks’ artificial intelligence expertise and computing infrastructure with ENEOS’s expertise in chemistry to build Matlantis. We look forward to providing powerful tools to help researchers worldwide discover game-changing materials that give a positive impact on our future.

About Preferred Computational Chemistry, Inc. (PFCC)

Japan Office	Otemachi Building, 1-6-1 Otemachi, Chiyoda-ku, Tokyo
Date of Establishment	June 1, 2021
Representative	Daisuke Okanohara, Chief Executive Officer
Capital	310 million yen (investment ratio: PFN 51%, ENEOS Corporation 49%)
Business Overview	Sales and consulting for Matlantis, a versatile atomistic simulation cloud service
URL	https://matlantis.com