HomeCasesHigh-speed atomistic simulator revolutionizes catalyst development
High-speed atomistic simulator revolutionizes catalyst development:imageFrom left to right: Yukihiro Sugiura, Ph.D., Chief Researcher, Renewable Technology Group, Central Technical Research Laboratory / Yuichiro Fujiyama, Ph.D., General Manager of Central Technical Research Laboratory/ Yoshihiro Yayama, Senior Staff, Data Science Group, Central Technical Research Laboratory

High-speed atomistic simulator revolutionizes catalyst development

By using Matlantis, simulation tasks that would have taken 20 years with a conventional method was completed in only a week. This has shortened our catalyst development process to one-tenth of the previously required time. Matlantis has unlimited potential throughout the materials industry.

ENEOS Corporation

Industry:
Oil and gas
Business:
Refining and marketing of petroleum and petrochemical products
Electric powerEnergyGas

“The long process time was a big issue with the conventional molecular simulation methods. Matlantis’s calculation speed is overwhelmingly fast and allowed me to provide immediate feedback to my colleauges doing the experiments. For example, a calculations task that would take around 20 years was completed in only one week. We can quickly test a variety of elements and the results often surprise our experiment team.”

—Yoshihiro Yayama, computational chemistry specialist

“When we develop new catalysts, we have to prepare dozens of combinations of metals and catalyst carriers and evaluate them, which can take over a year. Matlantis suggests specific metals to aim for, and we’ve reduced the time required to a tenth or maybe less.”

—Yukihiro Sugiura, Ph.D., catalyst engineer

“In a sense, Matlantis has no limit to how it can be used as it can simulate all kinds of materials such as metals as well as catalysts. As the materials and substances that the world needs change dramatically, it is my hope that Matlantis can be used as a tool to accelerate this change.”

—Yuichiro Fujiyama, Ph.D., Executive Officer

Yoshihiro Yayama, Senior Staff, Data Science Group, Central Technical Research Laboratory
Molecular simulation on Matlantis is overwhelmingly faster than conventional techniques.

Q. How does Matlantis differ from existing molecular simulation techniques?

Conventional molecular simulation methods required a lot of calculation time—a single calculation might take up to a week. What was overwhelmingly different about Matlantis was the calculation speed. What used to take one or two days now finish in an instant, allowing me to provide immediate feedback to my colleagues doing the experiments.

Matlantis can simulate this chemical reaction in which hydrogen and carbon monoxide combine to form hydrocarbon fuel, for example. The simulation of the activated energy proceeds rapidly.

Normally this kind of calculation would take several days, but with Matlantis we only need about 10 minutes. With calculation this fast we were able to perform around 10,000 simulations. Calculation tasks that would take around 20 years were completed in only one week. We performed brute-force simulations with all kinds of elements, and found out some combination of elements can accelerate chemical reactions. We presented the results to our experiment team.

The results surprised the experiment team because some of the combinations of elements are quite unexpected.

Yukihiro Sugiura, Ph.D., Chief Researcher, Renewable Technology Group, Central Technical Research Laboratory
Catalyst development may take years but Matlantis reduced the time to a tenth.

Q. How did Matlantis help your catalyst development process?

I am responsible for the development of energy-related catalysts for refining oil and producing synthetic fuels. When we develop new catalysts we have to prepare dozens of combinations of metals and catalyst carriers to evaluate them.

We must repeat this process of trial and error, which takes a large amount of time. We have built up experience, but this method can still take over a year.

Matlantis suggests specific metals to aim for, which can greatly reduce the number of trials and errors to prepare and evaluate catalysts. I think we’ve reduced the time required to a tenth, or maybe less. There were some combinations we avoided,but Matlantis sometimes suggests them and they tested well.

To me, the great thing about Matlantis is how it suggests combinations of metals and catalyst carriers that we would never have imagined based on our own intuition and experience.

Yuichiro Fujiyama, Ph.D., General Manager of Central Technical Research Laboratory
Fujiyama says there is no limit to how Matlantis can be used in any industry working with materials and substances.

Q. What does it mean for ENEOS to search for new materials using Matlantis?

We are, after all, an energy company, and have always worked with oil and fossil fuels thus far.

But with the coming move to a low-carbon society, energy will take on a whole new form. What kind of substance will we base that energy on, and what kind of processes will we use to convert one form of energy into another?
I believe that we can use Matlantis to improve efficiency in such chemical reactions, and in many other areas.

We can also use it for other materials such as metal. Behavior of all kinds of materials can be simulated with Matlantis.

I think that for amy industry working with materials and substances, there is—in a sense—no limit to how it can be used.
As the materials and substances that the world needs change dramatically, it is my hope that Matlantis can be used as a tool to accelerate this change.

Published: July 1, 2021
All trademarks are trademarks or registered trademarks of their respective owners.
This information is current as of the published date and subject to change without notice.

Contact Us
Go to List of Cases
Features
Features

Matlantis: 3 Key Features

Matlantis supports companies exploring innovative materials for a sustainable future.

Versatility

汎用性 / Versatile イメージ
Supports a wide range of elements and structures

Matlantis can simulate properties of molecules and crystal systems, including unknown materials. Any combinations of 55 elements are currently supported, and more elements will be added.

Speed

高速 / High Speed イメージ
Over 10,000x faster than conventional methods

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

User-Friendliness

使いやすさ / Easy to Use イメージ
Just open your browser to run simulations

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. Unlike conventional machine learning potentials, Matlantis requires no data collection or training by users.

Go to Product Detail