Researchers Capture Nanoparticle Movements To Forge New Materials

Researchers can now observe the phonon dynamics and wave propagation in self-assembly of nanomaterials with unusual properties that rarely exist in nature. This advance will enable researchers to incorporate desired mechanical properties into reconfigurable, solution-processible metamaterials, which have wide-ranging applications — from shock absorption to devices that guide acoustic and optical energy in high-powered computer applications.

Phonons are natural phenomena that can be thought of as discrete packets of energy waves that move through the building blocks of materials, whether they are atoms, particles or 3D-printed hinges, causing them to vibrate and transfer energy. This is a quantum mechanical description of common properties observed in various contexts, including the transfer of heat, the flow of sound and even seismic waves formed by earthquakes.

 Some materials, both artificial and natural, are designed to move phonons along specific paths, imparting specific mechanical attributes. Two real-life examples of this include materials used in structures to resist seismic waves during earthquakes and the evolution of the rugged yet lightweight skeletons of deep-sea sponges, which enable them to withstand the extreme pressures of deep-water environments.

“Using the liquid-phase electron microscopy technique developed in our lab at Illinois, the new study marks the first time we’ve been able to observe phonon dynamics in nanoparticle self-assemblies, acting as a new type of mechanical metamaterials,” said Qian Chen, a professor of material science and engineering at the University of Illinois Urbana-Champaign.

The multi-institutional, multi-discipline study is the result of a four-year collaboration between Chen, who led the materials science and experimental portion; professor Xiaoming Mao at the University of Michigan, who led the mechanical metamaterials and theory portion of the study; and professor Wenxiao Pan, who led the simulation portion of the study at University of Wisconsin-Madison. Published in the journal Nature Materials, the study combines nanoparticle assembly with mechanical metamaterial principles, enabling the engineering of mechanical properties through structural design.

“Some refer to metamaterials development as mechano-logic,” Chen said. “Metamaterials design is a very active field, and most research has focused on the macroscale realm, where it is easier to control the geometry and structure, as well as measure and model the phonon properties.”

But Chen and her collaborators work in the nanoscale world, where both engineering and theoretical approaches to phonon control are tough. To address this problem, the team employed precise theoretical modeling in conjunction with experimental and observational techniques, as well as machine learning-accelerated simulations, to develop a new framework for metamaterials design.   

In the lab, using liquid-phase electron microscopy, the team examined the vibrational trajectories of gold nanoparticles to determine the phonon band structures, and then matched these structures to a discrete mechanical model to extract nanoscale springs.

Click here to view a video explaining the liquid-phase electron microscopy workload process.

“We feel we are at a great intersection between disciplines, collaboration and the need for advancement in materials science,” Chen said. “With nanoparticle assembly, we can design structures with very controlled geometry, and then with mechanical metamaterials, adapt the theoretical framework in material design.”

“This opens a new research area where nanoscale building blocks — along with their intrinsic optical, electromagnetic, and chemical properties — can be incorporated into mechanical metamaterials,” Mao said, “Enabling emerging technologies in multiple fields from robotics and mechanical engineering to information technology.”

“This work also demonstrates the potential of machine learning to advance the study of complex particle systems, making it possible to observe their self-assembly pathways governed by complex dynamics,” Pan said. “It opens new avenues for data-driven inverse design of reconfigurable colloidal metamaterials using machine learning and artificial intelligence.”

Reference: Qian C, Stanifer E, Ma Z, et al. Nanoscale phonon dynamics in self-assembled nanoparticle lattices. Nat Mater. 2025. doi: 10.1038/s41563-025-02253-3

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