Metallic glasses reveal their secrets
A highly detailed plot that shows, for the first time, the location of all 18 356 atoms in a metallic glass nanoparticle could transform our understanding of non-crystalline materials. The feat, achieved thanks to a technique known as atomic electron tomography (AET), could also make it easier to design materials with properties suited to applications in quantum computing and gravitational wave detection.
Metallic glasses were discovered in 1960 and have properties of both metals and glasses. They contain metallic bonds, so are conducting, but their atoms are disordered like in a glass rather than ordered as in a crystal. They are produced by heating certain substances to above their melting points and then quenching them in a way that prevents them from crystallizing, and their exceptional strength makes them promising for structural engineering applications. However, their disordered nature makes it difficult to study their three-dimensional structure using crystallography techniques. While alternative methods – including X-ray and neutron diffraction, high-resolution transmission electron microscopy and nuclear magnetic resonance – are available, none of these can directly identify all the positions of the atoms in 3D.
A highly detailed plot that shows, for the first time, the location of all 18 356 atoms in a metallic glass nanoparticle could transform our understanding of non-crystalline materials. The feat, achieved thanks to a technique known as atomic electron tomography (AET), could also make it easier to design materials with properties suited to applications in quantum computing and gravitational wave detection.
Metallic glasses were discovered in 1960 and have properties of both metals and glasses. They contain metallic bonds, so are conducting, but their atoms are disordered like in a glass rather than ordered as in a crystal. They are produced by heating certain substances to above their melting points and then quenching them in a way that prevents them from crystallizing, and their exceptional strength makes them promising for structural engineering applications. However, their disordered nature makes it difficult to study their three-dimensional structure using crystallography techniques. While alternative methods – including X-ray and neutron diffraction, high-resolution transmission electron microscopy and nuclear magnetic resonance – are available, none of these can directly identify all the positions of the atoms in 3D.
Atomic electron tomography
In a paper published in Nature, Jianwei Miao of the University of California, Los Angeles, US, and colleagues note that AET can, in principle, solve this long-standing problem. The technique works by passing a beam of electrons through a sample to acquire 2D projections of its 3D atomic structure. From there, a series of 2D images is obtained by changing the orientation of the sample with respect to the beam. In a final step, the images are reconstructed into a 3D image of the entire sample.
AET has previously been used to image 3D crystal defects (such as dislocations, stacking faults, grain boundaries, chemical order/disorder and point defects) in materials at the single-atom level. Obtaining the 3D atomic structure of a metallic glass, however, required two important advances, Miao says. “We optimized our experiment to expose a sample to the lowest possible ‘dose’ of electrons needed to generate images to avoid changing the sample during the course of the measurement,” he tells Physics World. “We also developed advanced algorithms to analyse the noisy images and then stitch them together to obtain a 3D map.”
After years of pursuing their goal, Miao and colleagues say they finally succeeded in analysing a series of high-quality 2D images that capture subtle variations in contrast when the metallic glass is viewed in different orientations. They then used their advanced algorithms to map out the precise 3D position of 18 356 atoms in a metallic glass nanoparticle (see this video).
In a paper published in Nature, Jianwei Miao of the University of California, Los Angeles, US, and colleagues note that AET can, in principle, solve this long-standing problem. The technique works by passing a beam of electrons through a sample to acquire 2D projections of its 3D atomic structure. From there, a series of 2D images is obtained by changing the orientation of the sample with respect to the beam. In a final step, the images are reconstructed into a 3D image of the entire sample.
AET has previously been used to image 3D crystal defects (such as dislocations, stacking faults, grain boundaries, chemical order/disorder and point defects) in materials at the single-atom level. Obtaining the 3D atomic structure of a metallic glass, however, required two important advances, Miao says. “We optimized our experiment to expose a sample to the lowest possible ‘dose’ of electrons needed to generate images to avoid changing the sample during the course of the measurement,” he tells Physics World. “We also developed advanced algorithms to analyse the noisy images and then stitch them together to obtain a 3D map.”
After years of pursuing their goal, Miao and colleagues say they finally succeeded in analysing a series of high-quality 2D images that capture subtle variations in contrast when the metallic glass is viewed in different orientations. They then used their advanced algorithms to map out the precise 3D position of 18 356 atoms in a metallic glass nanoparticle (see this video).
Crystal-like superclusters
The team, which also includes researchers from the Lawrence Berkeley National Laboratory and the University of Maryland, studied metallic glass nanoparticles containing eight elements: cobalt, nickel, ruthenium, rhodium, palladium, silver, iridium and platinum. They classified these into three different atom types: cobalt and nickel as type 1; ruthenium, rhodium, palladium and silver as type 2; and iridium and platinum as type 3.
The researchers quantitatively characterized the short- and medium-range order of the 3D arrangement of the atoms. They observed that, although the short-range 3D atomic packing is geometrically disordered, some short-range-order structures connected with each other to form crystal-like superclusters, giving rise to medium-range order.
Miao and colleagues identified four types of crystal-like medium-range order (face-centred cubic, hexagonal close-packed, body-centred cubic and simple cubic) that coexist in the amorphous sample. These observations back up the so-called efficient cluster packing model for metallic glasses.
The team also showed that some of these clusters are densely packed, while others are looser. The loose packing might stem from the process in which the glasses were synthesized, but it might also hint at important gaps in current models.
In a related News & Views article, Paul Voyles of the University of Wisconsin, Madison, US, notes that AET could open the way to better ways of characterizing structural defects in glasses. Technologies as varied as the superconducting quantum bits used in quantum computers and certain optical coatings used at the LIGO gravitational-wave observatory could benefit as a result, as both are currently limited by glass defects known as two-level systems. These defects can be detected only by their spectroscopic signatures, not by their structure, Voyles explains, so being able to identify them more readily could make it easier to design better materials for these and other applications.
The team, which also includes researchers from the Lawrence Berkeley National Laboratory and the University of Maryland, studied metallic glass nanoparticles containing eight elements: cobalt, nickel, ruthenium, rhodium, palladium, silver, iridium and platinum. They classified these into three different atom types: cobalt and nickel as type 1; ruthenium, rhodium, palladium and silver as type 2; and iridium and platinum as type 3.
The researchers quantitatively characterized the short- and medium-range order of the 3D arrangement of the atoms. They observed that, although the short-range 3D atomic packing is geometrically disordered, some short-range-order structures connected with each other to form crystal-like superclusters, giving rise to medium-range order.
Miao and colleagues identified four types of crystal-like medium-range order (face-centred cubic, hexagonal close-packed, body-centred cubic and simple cubic) that coexist in the amorphous sample. These observations back up the so-called efficient cluster packing model for metallic glasses.
The team also showed that some of these clusters are densely packed, while others are looser. The loose packing might stem from the process in which the glasses were synthesized, but it might also hint at important gaps in current models.
In a related News & Views article, Paul Voyles of the University of Wisconsin, Madison, US, notes that AET could open the way to better ways of characterizing structural defects in glasses. Technologies as varied as the superconducting quantum bits used in quantum computers and certain optical coatings used at the LIGO gravitational-wave observatory could benefit as a result, as both are currently limited by glass defects known as two-level systems. These defects can be detected only by their spectroscopic signatures, not by their structure, Voyles explains, so being able to identify them more readily could make it easier to design better materials for these and other applications.