Accelerated development of CO₂ reduction materials and devices by utilizing AI and experimental data

Research outline

The objective of this research is to accelerate the development of materials and devices that enable carbon dioxide to be converted into a resource by utilizing AI and experimental data. A next-generation proton-conducting solid oxide-type electrolytic cell using carbon dioxide-tolerant Sc-substituted barium zirconate (Adv. Energy Mater. 2020), which has been successfully developed by the representative, as an electrolyte will be constructed to achieve carbon dioxide recycling and selective production of olefin, a high value-added resin material. For efficient development, the machine learning model for proton conductors (ACS Energy Lett. 2021) will be extended to the other materials and their hetero interfaces. Taking advantage of the broad perspectives of the Kyushu University Platform of Inter-/Transdisciplinary Energy Research, the reactions will be evaluated based on the nano-level to device systems and economics. The project is expected to contribute significantly to the realization of “decarbonization” and the “carbon neutral society of 2050” that Japan is aiming for.

Schematic image of the research concept

Research originality

The originality of this research lies in the accelerated development of material devices that enable carbon dioxide to be recycled and propylene to be produced simultaneously through the utilization of AI and experimental data. It is also unique that the research is not limited to scientific and technological development but also considers the socioeconomic aspects of the technology.

Module members

(PI) YAMAZAKI Yoshihiro

Professor

Q-PIT

Accelerated development of CO₂ reduction materials and devices by utilizing AI and experimental data

TADA Tomofumi

Professor

Q-PIT

Evaluation of interfacial reaction field based on quantum chemistry

MATSUZAKI Yoshio

Professor

Q-PIT

System evaluation of chemical conversion devices

HYODO Junji

Assistant professor

Q-PIT

Surface design and evaluation using operando infrared absorption spectroscopy

CHAPMAN Andrew

Associate professor

I²CNER

Economic evaluation of CO₂ reduction materials and devices

KIMURA Takashi

Professor

Department of Physics

Spin utilization for high functionality in materials and devices

KAWAE Tatsuya

Associate professor

Department of Applied Quantum Physics and Nuclear Engineering

Spin utilization for high functionality in materials and devices at low temperatures

KANEKO Kenji

Professor

Department of Materials

Evaluation of materials surfaces using transmission electron microscopy

MURAKAMI Yasukazu

Professor

The Ultramicroscopy Research Center

In-situ transmission electron microscopy and evaluation of reaction sites using machine learning

HATA Satoshi

Professor

Interdisciplinary Graduate School of Engineering Science

Nanostructure characterization using transmission electron microscopy and machine learning

Expected results and outcomes of the collaboration

We will demonstrate CO₂ reduction and propane(C₃H₈) dehydrogenation (propylene(C₃H₆) production) with high selectivity beyond the equilibrium yield of conventional heterogeneous catalysts by combining an electrochemical cell using a proton-conducting electrolyte (Adv. Energy Mater. 2020), catalysts, and the electrochemical potential. This module will contribute to solving the social issue of achieving Japan’s CO₂ emission reduction target (46% of the FY2013 level by FY2030) by integrating the comprehensive knowledge of the researchers at Kyushu university.

Research results

1. Probe where the protons go to develop better fuel cells

(PRESS RELEASE、Kyushu University HP)、Research paper in Chemistry of Materials (ACS)

Probing Local Environments of Oxygen Vacancies Responsible for Hydration in Sc-doped Barium Zirconates at Elevated Temperatures: In Situ X-ray Absorption Spectroscopy, Thermogravimetry, and Active Learning Ab Initio Replica Exchange Monte Carlo Simulations

Kenta Hoshino, Shusuke Kasamatsu, Junji Hyodo, Kentaro Yamamoto, Hiroyuki Setoyama, Toshihiro Okajima, Yoshihiro Yamazaki*
Chemistry of Materials, 35, 6, 2289–2301, 2023
DOI: 10.1021/acs.chemmater.2c02116

Research result was selected for the Journal cover art!

Accelerated development of CO₂ reduction materials and devices by utilizing AI and experimental data

Research outline

Schematic image of the research concept

Research originality

Module members

(PI) YAMAZAKI Yoshihiro

TADA Tomofumi

MATSUZAKI Yoshio

HYODO Junji

CHAPMAN Andrew

KIMURA Takashi

KAWAE Tatsuya

KANEKO Kenji

MURAKAMI Yasukazu

HATA Satoshi

Expected results and outcomes of the collaboration

Research results

Probing Local Environments of Oxygen Vacancies Responsible for Hydration in Sc-doped Barium Zirconates at Elevated Temperatures: In Situ X-ray Absorption Spectroscopy, Thermogravimetry, and Active Learning Ab Initio Replica Exchange Monte Carlo Simulations

Representative research papers and achievements

Quantitative Evaluation of Biaxial Compressive Strain and its Impact on Proton Conduction and Diffusion in Yttrium-doped Barium Zirconate Epitaxial Thin Films

Accelerated Discovery of Proton-Conducting Perovskite Oxide by Capturing Physicochemical Fundamentals of Hydration

Oxygen Affinity: The Missing Link Enabling Prediction of Proton Conductivities in Doped Barium Zirconates

Fast and Stable Proton Conduction in Heavily Scandium-Doped Polycrystalline Barium Zirconate at Intermediate Temperatures

Accelerated development of CO2 reduction materials and devices by utilizing AI and experimental data

Research outline

Schematic image of the research concept

Research originality

Module members

Expected results and outcomes of the collaboration

Research results

Representative research papers and achievements

Accelerated development of CO₂ reduction materials and devices by utilizing AI and experimental data