HomeNewsPreferred Computational Chemistry Celebrates Second Anniversary

Preferred Computational Chemistry Celebrates Second Anniversary

Preferred ComPreferred Computational Chemistry (PFCC) marked its second anniversary on July 1, 2023. Thanks to Matlantis’s valued clients and all parties concerned, the Matlantis™ business has steadily grown with an increasing number of academic papers and case studies published by them.

Below are the two-year anniversary message from PFCC CEO Daisuke Okanohara and the latest list of academic papers and case studies published by Matlantis clients.

Message from Daisuke Okanohara, CEO:

“As PFCC celebrates its second year anniversary, I’d like to take this opportunity to express my sincerest gratitude to our clients and all those who have worked with us to achieve this milestone.

The past two years have been full of new challenges but thanks to everyone’s support and collaboration, our business has grown significantly. The client base for Matlantis has expanded to over 60 companies and academic institutions, and we could officially launch the service in the US in April 2023. Going forward, we will continue on our mission to support discovery of innovative materials for a sustainable future by working diligently to meet client needs.

As we renew our commitment on our two-year anniversary, we would like to thank all of our clients for their continued support, and we look forward to evolving further towards a sustainable future.”

Our Clients’ Research Papers related to Matlantis

Calculations of Real-System Nanoparticles Using Universal Neural Network Potential PFP

Gerardo Valadez Huerta, Yusuke Nanba, Iori Kurata, Kosuke Nakago, So Takamoto, Chikashi Shinagawa, Michihisa Koyama

Cyber Catalysis: N2 Dissociation over Ruthenium Catalyst with Strong Metal-Support Interaction

Gerardo Valadez Huerta, Kaoru Hisama, Katsutoshi Sato, Katsutoshi Nagaoka, Michihisa Koyama

Molecular dynamics of electric-field driven ionic systems using a universal neural-network potential

Kaoru Hisama, Gerardo Valadez Huerta, Michihisa Koyama

Comparison of Matlantis and VASP bulk formation and surface energies in metal hydrides, carbides, nitrides, oxides, and sulfides

Shinya Mine, Takashi Toyao, Ken-ichi Shimizu, Yoyo Hinuma

Innovation in Molecular Simulation Technologies for Tribology Using Artificial Intelligence

Tasuku Onodera

Effect of HFO Refrigerants on Lubrication Characteristics (Part 1)

Yuji SHITARA, Shigeyuki MORI

Effect of HFO Refrigerants on Lubrication Characteristics (Part 2)

Yuji SHITARA, Tasuku ONODERA, Shigeyuki MORI

Quantum Annealing Boosts Prediction of Multimolecular Adsorption on Solid Surfaces Avoiding Combinatorial Explosion

Hiroshi Sampei, Koki Saegusa, Kenshin Chishima, Takuma Higo, Shu Tanaka, Yoshihiro Yayama, Makoto Nakamura, Koichi Kimura, and Yasushi Sekine

Assessing the Reactivity of the Na3PS4 Solid-State Electrolyte with the Sodium Metal Negative Electrode Using Total Trajectory Analysis with Neural-Network Potential Molecular Dynamics

Lieven Bekaert, Suzuno Akatsuka, Naoto Tanibata, Frank De Proft, Annick Hubin, Mesfin Haile Mamme, and Masanobu Nakayama

On the Thermodynamic Stability of Alloys: Combination of Neural Network Potential and Wang-Landau Sampling

Tien Quang Nguyen, Yusuke Nanba, and Michihisa Koyama

Using GPT-4 in Parameter Selection of Materials Informatics: Improving Predictive Accuracy Amidst Data Scarcity and ‘Ugly Duckling’ Dilemma

Kan Hatakeyama-Sato, Seigo Watanabe, Naoki Yamane, Yasuhiko Igarashi, Kenichi Oyaizu

CO Adsorption on Ternary Nanoalloys by Universal Neural Network Potential

Ayako TAMURA, Gerardo VALADEZ HUERTA, Yusuke NANBA, Kaoru HISAMA, Michihisa KOYAMA