Integrating density-functional theory and machine-learning to assess the stability of lateral graphene–metallene interfaces. Credit: University of Jyväskylä

Metallenes are atomically thin metals whose unique properties make them extremely promising for nanoscale applications. However, their extreme thinness makes them also flimsy.

Now, researchers at the Nanoscience Center of the University of Jyväskylä (Finland) have succeeded in identifying the principles that can maximize their stability. The solution may open up opportunities in materials design, nano‐electronics, energy production, and biomedicine.

The findings are published in the journal Nanoscale.

Metallenes possess exceptional properties that make them highly attractive for future applications in advanced electronics, high‐efficiency energy storage, sensors, and catalysis. However, their tendency to collapse due to metallic bonding has made their synthesis difficult, often requiring confinement within the pores of template materials as small patches.

"The aim of our researcher group was to use a large‐scale computational approach to conduct a systematic, microscopic analysis of metallene interfaces to discover the fundamental design principles for greater stability," explains the team leader, Professor Pekka Koskinen from the University of Jyväskylä.

Geometry determines the stability of metal parts

To tackle this challenge, researchers used a powerful computational approach that combined quantum‐mechanical modeling with advanced universal machine learning. This allowed them to analyze the stability and properties of 1,080 different graphene‐metallene interfaces.

"We found that interface stability depends on maintaining smooth, well‐aligned geometries. Such clean edges provide strong resistance to defects and mechanical strain, whereas irregular boundaries promote destabilization," says postdoctoral researcher Dr. Mohammad Bagheri from University of Jyväskylä, who conducted the theoretical simulations.

Machine learning speeds up the design of new materials

The researchers also found that metallenes made from transition metals form the most robust interfaces overall. Moreover, the research validates the use of machine‐learning models for accurately predicting atomic‐level interface behavior, establishing a powerful new tool to accelerate the design and screening of novel materials.

"This systematic understanding provides useful geometric and elemental rule‐of‐thumb requirements for stability. This way, the research offers a guideline to accelerate the synthesis of more robust, larger‐scale metallene structures," says Koskinen.

This knowledge is a critical breakthrough needed to move metallenes out of the research lab and into practical, high‐performance devices. This study marks a vital step toward enabling metallenes for applications in high‐tech fields like electronics, energy conversion and biomedicine.

More information: Mohammad Bagheri et al, Lateral graphene-metallene interfaces at the nanoscale, Nanoscale (2025). DOI: 10.1039/d5nr02770e

Citation: A geometric recipe for stabilizing atomically thin metals (2025, December 8) retrieved 8 December 2025 from https://phys.org/news/2025-12-geometric-recipe-stabilizing-atomically-thin.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.