Related papers: Recent Advances in Metallic Glasses
The low-temperature quasi-universal behavior of amorphous solids has been attributed to the existence of spatially-localized tunneling defects found in the low-energy regions of the potential energy landscape. Computational models of…
During the past decade, metal additive manufacturing (MAM) has experienced significant developments and gained much attention due to its ability to fabricate complex parts, manufacture products with functionally graded materials, minimize…
Laser machining is a highly flexible non-contact manufacturing technique that has been employed widely across academia and industry. Due to nonlinear interactions between light and matter, simulation methods are extremely crucial, as they…
We use coherent X-rays to probe the aging dynamics of a metallic glass directly on the atomic level. Contrary to the common assumption of a steady slowing down of the dynamics usually observed in macroscopic studies, we show that the…
The field of machine learning has rapidly advanced the state of the art in many fields of science and engineering, including experimental fluid dynamics, which is one of the original big-data disciplines. This perspective will highlight…
The ability of metallic nanostructures to confine light at the sub-wavelength scale enables new perspectives and opportunities in the field of nanotechnology. Making use of this unique advantage, nano-optical trapping techniques have been…
Bulk metallic glass (BMG) materials are hot topics in recent years, not to mention BMG matrix composites, which further improve the magnetic and mechanical properties of BMG materials. BMG and BMG matrix materials are fast developing and…
Over the past decade inter-atomic potentials based on machine-learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure…
We report a metadynamics simulation study of crystallization in a deep undercooled metallic glass-forming liquid by developing appropriate collective variables. Through a combined analysis of free energy surface (FES) and atomic-level…
Materials informatics offers a promising pathway towards rational materials design, replacing the current trial-and-error approach and accelerating the development of new functional materials. Through the use of sophisticated data analysis…
The understanding of glassy dynamics above the devitrification temperature of a glass remains poorly understood. Here, we use real-time AFM imaging to build a spatio-temporal map of the relaxation dynamics of a highly stable glass into its…
Machine learning offers promising tools to develop surrogate models for polymer structure-property relations. Surrogate models can be built upon existing polymer data and are useful for rapidly predicting the properties of unknown polymers.…
New metallic glasses containing La or Ce have been introduced that have dynamic properties bordering on extremes of conventional metallic glasses. This provides opportunity to test trends or correlations established before in molecular and…
Here we highlight recent progress in the field of computational chemistry of nanoporous materials, focusing on methods and studies that address the extraordinary dynamic nature of these systems: the high flexibility of their frameworks, the…
Additive manufacturing of a single crystalline metallic column is studied using molecular dynamics simulations. In the model, a melt pool is incrementally added and cooled to a target temperature under isobaric conditions to build a…
Microscopic description in the study of immiscibility and segregating properties of liquid metallic binary alloys has gained a renewed scientific and technological interests during the last eight years for the physicists, metallurgists and…
We will review some of the theoretical progresses that have been recently done in the study of slow dynamics of glassy systems: the general techniques used for studying the dynamics in the mean field approximation and the emergence of a…
Synthesis of advanced inorganic materials with minimum number of trials is of paramount importance towards the acceleration of inorganic materials development. The enormous complexity involved in existing multi-variable synthesis methods…
We introduce GlassMLP, a machine learning framework using physics-inspired structural input to predict the long-time dynamics in deeply supercooled liquids. We apply this deep neural network to atomistic models in 2D and 3D. Its performance…
Existence and growth of amorphous order in supercooled liquids approaching glass transition is a subject of intense research. Even after decades of work, there is still no clear consensus on the molecular mechanisms that lead to a rapid…