Finding a new electronic material can mean searching through an almost limitless number of possible chemical combinations. Researchers at Seoul National University have used artificial intelligence to make that search more manageable, pulling together data scattered across hundreds of scientific papers and using it to identify lead-free dielectric materials that remain stable at high temperatures.
The Seoul National University College of Engineering research team was led by Professor Ho Won Jang of the Department of Materials Science and Engineering. The researchers combined information extracted from published studies with physics-informed machine learning to design new lead-free dielectric compositions. Integrated M.S./Ph.D. student Kwanwoo Song was first author and led the overall project, with integrated M.S./Ph.D. student Youngmin Kim and postdoctoral researcher Jaehyun Kim also contributing.
Dielectrics are insulating materials that block the direct flow of electricity while storing electrical charge. They are essential to multilayer ceramic capacitors (MLCCs) found in smartphones, electric vehicles, and other electronics. A higher dielectric constant allows a component of the same size to store more electrical energy, but useful materials must also preserve that performance as temperatures rise.
To search for promising compositions, the researchers combined multimodal literature mining, which extracts information from text, tables, and graphs, with physics-informed machine learning. Their inverse design strategy began with desired performance targets and worked backward to identify compositions likely to meet them.
The researchers assembled 1,202 records of dielectric properties from 448 scientific papers, then screened a virtual chemical space containing approximately 150 million possible compositions. That process reduced the field to 37 candidates. Two were synthesized and tested experimentally, and both showed high dielectric constants along with strong stability at elevated temperatures.
The findings were published in Nature Communications.
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