To accelerate the transition to a renewable energy society by discovering new materials, chemicals, and processes through multi-scale simulation and data science.
We interface multi-scale materials simulation and data science. Specifically, we develop innovative methods that accelerate materials design.


An automated rapid microkinetic simulation is invaluable in predicting the products of chemical reactions ahead of experiments. Although existing models perform well in their focused domains, a dedicated comprehensive framework for the bond exchange reaction kinetics is absent. To address this, we present an integrated algorithm for the rapid kinetic simulation of bond exchange reaction networks. We introduce a scalable matrix-based enumeration method that allows economic exploration of all plausible reaction products without resorting to reaction templates. Our model primarily uses machine learning, which achieves a mean absolute error of 4.55 kcal/mol for activation energies, to more efficiently predict reaction properties, without relying on stored chemical reaction databases or expensive electronic structure calculations. The framework was validated by successfully reproducing two reactions.

Visible light-driven photocatalysis is a sustainable approach for air purification, but full mineralization of aromatic volatile organic compounds (VOCs) such as toluene to carbon dioxide (CO2) remains elusive due to their chemical stability and weak surface affinity. Here, we report a platinum-loaded, surface-fluorinated tungsten trioxide (F-WO3/Pt) that achieves mineralization of toluene under visible-light irradiation, markedly outperforming conventional Pt/WO3, which cannot degrade toluene at all under the same condition. Mechanistic studies reveal that the surface fluorination of Pt/WO3 promotes the formation of mobile hydroxyl radicals (·OH). These radicals diffuse into the gas phase, extending the active reaction zone beyond the catalyst surface. This fluorination-driven ·OH mobility compensates for WO3’s inherently low photocatalytic oxidation (PCO) activity, low surface area, and weak toluene adsorption. Remote PCO experiments, scavenger tests, and ESR analyses collectively demonstrate the generation and active role of mobile radicals, whereas DFT calculations reveal an additional effect arising from the enhanced affinity of toluene with the fluorinated surface. The synergy between radical mobility and surface affinity establishes a new conceptual framework for the design of highly efficient photocatalysts for air pollutant degradation. These results present a scalable approach to modulating radical dynamics for enhanced visible-light-driven VOC removal and underscore the broad potential of this strategy for developing advanced materials for air purification.

Integrated capture and conversion of low-concentration CO2 is a critical step toward carbon neutrality. Here, we demonstrate a gas diffusion electrode (GDE) modified with oxygen- and nitrogen-functionalized porous graphitic carbon (ONC) that enables efficient electroreduction of dilute CO2. Under 15% CO2 gas (without O2), the ONC-modified GDE achieved a CO2-to-formic acid conversion rate of 250 μmol/h·cm2, 2.5 times higher than that of the bare GDE, with a Faradaic efficiency (FE) of 98%. Even in flue gas containing 8% O2, the modified GDE achieved 22 μmol/h·cm2 formic acid production (8% FE) at −1.4 VRHE. Mechanistic and simulation studies revealed that the oxygen functional groups in ONC enhance CO2 adsorption while suppressing O2 permeation, imparting strong oxygen tolerance. In particular, the ONC-modified GDE remains active at a CO2 concentration as low as 1% and 400 ppm, suggesting potential applicability in integrated capture–conversion systems that utilize dilute CO2 streams from flue gas and ambient air.


