Search arXivSearch

arXiv · 1910.13996

Revealing the Atomic Structure of Silicate Glasses by Force-Enhanced Atomic Refinement

Abstract

Although experiments can offer some fingerprints of the atomic structure of glasses (coordination numbers, pair distribution function, etc.), atomistic simulations are often required to directly access the structure itself (i.e., the positions of the atoms). On the one hand, molecular dynamics (MD) simulations can be used to generate by quenching a liquid - but MD simulations remain plagued by extremely high cooling rates. On the other hand, reverse Monte Carlo (RMC) modeling bypasses the melt-quenching route - but RMC often yields non-unique glass structures. Here, we adopt the force-enhanced atomic refinement (FEAR) method to overcome these limitations and decipher the atomic structure of a sodium silicate glass. We show that FEAR offers an unprecedented description of the atomic structure of sodium silicate. The FEAR-generated glass structure simultaneously exhibits (i) enhanced agreement with experimental neutron diffraction data and (ii) higher energetic stability as compared to those generated by MD or RMC. This result allows us to reveal new insights into the atomic structure of sodium silicate glasses. Specifically, we show that sodium silicate glasses exhibit a more ordered medium-range order structure than previously suggested by MD simulations. These results pave the way toward an increased ability to accurately describe the atomic structure of glasses.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Qi Zhou, Tao Du, Lijie Guo, Morten M. Smedskjaer, Mathieu Bauchy. 2019-10-30. Revealing the Atomic Structure of Silicate Glasses by Force-Enhanced Atomic Refinement. https://doi.org/10.1016/j.jnoncrysol.2020.120006

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

A hierarchy of thermodynamics learning frameworks for inelastic constitutive modeling

Recent advances in physics-augmented neural networks have enabled thermodynamically consistent data-driven constitutive modeling of complex inelastic materials. Most existing approaches, however, implicitly adopt a specific thermodynamic framework and embed structural assumptions such as normality, dual dissipation potentials, or other structure from manually constructed models directly into the learning architecture. Consequently, differences in predictive performance may arise not only from data or network design, but also from the underlying theoretical assumptions. In this work, we present a unified comparison of several thermodynamically consistent inelastic modeling frameworks from a machine learning perspective. We consider internal-variable formulations with dissipation potential, generalized standard materials, and metriplectic structures, and we analyze their structural assumptions, admissible dependencies, convexity requirements, and implications for dissipation and evolution. Each framework is implemented within a common neural potential architecture based on invariant representations and neural ordinary differential equations. This unified setting ensures that performance differences can be attributed to thermodynamic structure rather than architectural variation. The models are trained and evaluated on three representative inelastic datasets generated from high-fidelity representative volume element simulations: an elastoplastic alloy, a viscoelastic composite, and a rate-dependent crystal plasticity polycrystal. By isolating the role of thermodynamic structure, we assess how restrictions such as duality, normality, operator-based evolution, and convexity influence learnability, expressiveness, stability, and generalization.

cond-mat.mtrl-sci

Berry Curvature Driven Transport in Silicon-Compatible Altermagnetic $α$-MnTe Thin Films

Integrating spin-dependent functionality with mainstream semiconductor technology is a central goal of modern spintronics, yet most candidate materials remain incompatible with silicon-based platforms. Here, we report the direct epitaxial integration of $α$-MnTe thin films on Si(111) via molecular beam epitaxy and demonstrate a robust anomalous Hall effect (AHE) in this silicon-compatible altermagnetic system. Despite the absence of net bulk magnetization, the films exhibit a pronounced hysteretic Hall response, providing transport evidence consistent with finite Berry curvature generated by symmetry breaking in the thin-film geometry. High-resolution structural and spectroscopic characterization confirms phase-pure, epitaxial growth with hexagonal NiAs-type symmetry, while magnetotransport measurements reveal correlated hysteresis in both transverse and longitudinal channels with systematic temperature evolution. First-principles calculations reveal substantial uncompensated Berry curvature arising from the spin-split band structure, consistent with altermagnetic symmetry and the origin of the observed Hall response. These results establish MnTe/Si(111) as a silicon-compatible altermagnetic platform and chart a concrete pathway for embedding Berry-phase-driven functionalities into scalable semiconductor device architectures.

cond-mat.mtrl-sci

All-Optical Control of Interfacial Polarization in MoS$_2$/WSe$_2$ Heterobilayers

All-optical tuning of van der Waals heterostructures with coherent radiation offers a promising path toward ultrafast memory and optoelectronic devices. In the first-principles framework of real-time time-dependent density functional theory, we predict the induction of a persistent, long-lived out-of-plane polarization in MoS$_2$/WSe$_2$ heterobilayers, resonantly driven by intense ultrafast pulses. While weak fields preserve the intrinsic type-II band alignment, intermediate intensities trigger a four-fold enhancement of interlayer charge transfer. By analyzing the high-harmonic generation spectrum, we identify a transition from the perturbative to the strong-field regime inducing photoinduced interfacial polarity. We additionally show that lattice strain, ubiquitously present in heterobilayers, can be used as additional knob to adjust the resonant condition without compromising the permanent dipole induction. Our findings provide a theoretical blueprint for the all-optical manipulation of polar phases in low-dimensional heterostructures at the femtosecond scale.

cond-mat.mtrl-sci