Chung-Ang University Team Unveils Breakthrough Theory on Nanoparticle Growth
A team of researchers in South Korea has unveiled a groundbreaking model that reshapes the century-old understanding of how nanoparticles form, grow, and shrink. The discovery, led by Professor Jaeyoung Sung of Chung-Ang University’s Department of Chemistry and Global Science Research Center for Systems Chemistry, offers a new framework that could transform fields ranging from electronics to medicine.
Nanoparticles are the foundation of many modern technologies, from quantum-dot displays and advanced catalysts to drug delivery systems. Their unique properties arise from their size and shape, yet the process by which nanoparticles reach uniform dimensions has remained a puzzle. For more than a century, scientists have relied on the Gibbs-Thomson equation and classical nucleation theory (CNT) to explain these dynamics. While useful, those models failed to account for why nanoparticle systems stabilize at particular size ranges.
In a study published June 10, 2025, in Proceedings of the National Academy of Sciences (PNAS), Professor Sung’s team, working with Professor Jungwon Park of Seoul National University and Distinguished Professor Taeghwan Hyeon of the IBS Center for Nanoparticle Research, introduced a new theory that captures the complex, multiphasic dynamics of nanoparticle ensembles. By employing liquid-phase transmission electron microscopy (TEM), the researchers directly observed hundreds of nanoparticles in real time. These experiments revealed that growth occurs in distinct phases, with surprising findings such as smaller particles expanding while larger ones dissolve—contradicting the long-accepted Ostwald ripening model.
The new framework accounts for six fundamental factors, including particle energy, shape, molecular diffusion, and surface interactions, as well as nanoparticle motion and configurational degeneracy—elements neglected in earlier theories. The result is the first quantitative explanation that aligns with experimental data across diverse materials, from platinum nanoparticles to semiconductors and metal oxides.
“This work makes it possible to understand the time evolution of nanoparticle size distributions from fundamental principles,” said Professor Sung. “It not only advances physics and chemistry but also opens new avenues in biology, where similar processes underlie neurodegenerative diseases like Alzheimer’s.”
The implications stretch far beyond basic science. With predictive power enhanced by computational chemistry and artificial intelligence, this new theory could guide the design of tailored nanoparticles for applications in semiconductor fabrication, energy storage, catalysis, and medicine.
As Professor Hyeon noted, the work represents a “fundamental shift” in how researchers think about nanoparticle growth. For the first time in over a century, the field has a new compass—one that may chart the course for decades of innovation ahead.
