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.



Latest Publications

Accelerated chemical science with AI

In light of the pressing need for practical materials and molecular solutions to renewable energy and health problems, to name just two examples, one wonders how to accelerate research and development in the chemical sciences, so as to address the time it takes to bring materials from initial discovery to commercialization. Artificial intelligence (AI)-based techniques, in particular, are having a transformative and accelerating impact on many if not most, technological domains. To shed light on these questions, the authors and participants gathered in person for the ASLLA Symposium on the theme of ‘Accelerated Chemical Science with AI’ at Gangneung, Republic of Korea. We present the findings, ideas, comments, and often contentious opinions expressed during four panel discussions related to the respective general topics: ‘Data’, ‘New applications’, ‘Machine learning algorithms’, and ‘Education’. All discussions were recorded, transcribed into text using Open AI’s Whisper, and summarized using LG AI Research’s EXAONE LLM, followed by revision by all authors. For the broader benefit of current researchers, educators in higher education, and academic bodies such as associations, publishers, librarians, and companies, we provide chemistry-specific recommendations and summarize the resulting conclusions.

Vanadium Selenide Nanobelt Electrocatalyst for Dopamine-Selective Detection

Electrochemical dopamine (DA) detection has been extensively studied for the practical diagnosis of neurological disorders. A major challenge in this system is to synthesize selective and sensitive DA sensing electrocatalysts in extracellular fluids, because critical interferents such as uric acid (UA) and ascorbic acid (AA) exhibit oxidation potentials similar to those of DA. Herein, we report an extremely selective and sensitive electrocatalyst for DA sensing prepared by vanadium selenide (V2Se9). A solution-based process for the first time was introduced to synthesize the V2Se9, showing unique DA-philic characteristic caused by exposure negative charge of crystal selenide. Owing to its distinctive features, the prepared V2Se9 electrode detected only DA in the presence of concentrated interferents. Furthermore, nano-structured V2Se9 electrode extremely improves DA sensing ability as low as practical detection limit with maintaining inactive interferent characteristic. More interestingly, an identical unique DA-sensing ability was also observed in a V2Se9 analogue—Nb2Se9. We believe that this finding provides new insights into the effect of the analyte-philic properties of electrode materials on the electrocatalytic response for selective analyte quantification.