Related papers: Machine learning glass caging order parameters wit…
The interplay of slow dynamics and thermodynamic features of dense liquids is studied by examinining how the glass transition changes depending on the presence or absence of Lennard-Jones-like attractions. Quite different thermodynamic…
The element of metastability is incorporated in the fluctuating nonlinear hydrodynamic description of the mode coupling theory (MCT) of the liquid-glass transition. This is achieved through the introduction of the defect density variable…
Based on deep neural networks (DNNs), deep learning has been successfully applied to many problems, but its mechanism is still not well understood -- especially the reason why over-parametrized DNNs can generalize. A recent statistical…
Non-equilibrium molecular dynamics simulations are performed to investigate the dynamic behavior of three-dimensional binary glasses prepared via an instantaneous quench across the glass transition. We found that with increasing strain…
We report an experimental investigation of the caging motion in a uniformly heated granular fluid, for a wide range of filling fractions, $\phi$. At low $\phi$ the classic diffusive behavior of a fluid is observed. However, as $\phi$ is…
Understanding the nature of glass transition, as well as precise estimation of the glass transition temperature for polymeric materials, remain open questions in both experimental and theoretical polymer sciences. We propose a data-driven…
We consider the idea of bond ordering as a model for glass transition: a generic covalently bonded liquid may substantially reduce its energy through bond ordering, without undergoing significant structural order. This concept is developed…
Molecular anisotropy plays an important role in the glass transition of a liquid. Recently, a novel bulk glass state has been discovered by optical microscopy experiments on suspensions of ellipsoidal colloids. 'Liquid glass' is a…
Identifying local structural motifs and packing patterns of molecular solids is a challenging task for both simulation and experiment. We demonstrate two novel approaches to characterize local environments in different polymorphs of…
We show that the dynamics of kinetically constrained models of glass formers takes place at a first-order coexistence line between active and inactive dynamical phases. We prove this by computing the large-deviation functions of suitable…
Sorting the integers 1 through $N$ into an ordered list is a simple task that can be done rapidly. However, using an algorithm based on the thermally-activated pairwise exchanges of neighboring list elements, we find sorting can display…
When we lower the temperature of a liquid, at some point we meet a first order phase transition to the crystal. Yet, under certain conditions it is possible to keep the system in its metastable phase and to avoid crystallization. In this…
Polymer-related materials exhibit rich glassy behaviors at different length scales due to their various molecular structures and topological constraints. Recent studies have identified transient interpenetration of the long-chain rings…
We simulate the compression of a two-component Lennard-Jones liquid at a variety of constant temperatures using a molecular dynamics algorithm in an isobaric-isothermal ensemble. The viscosity of the liquid increases with pressure,…
Fine-grained categorisation has been a challenging problem due to small inter-class variation, large intra-class variation and low number of training images. We propose a learning system which first clusters visually similar classes and…
Using molecular dynamics computer simulations we investigate how the glass transition and the properties of the resulting glass depend on the cooling rate with which the sample has been quenched. This is done by studying a two component…
We present an analysis of neural network-based machine learning schemes for phases and phase transitions in theoretical condensed matter research, focusing on neural networks with a single hidden layer. Such shallow neural networks were…
We introduce a new quantity to probe the glass transition. This quantity is a linear generalized compressibility which depends solely on the positions of the particles. We have performed a molecular dynamics simulation on a glass forming…
Phase segregation, the process by which the components of a binary mixture spontaneously separate, is a key process in the evolution and design of many chemical, mechanical, and biological systems. In this work, we present a data-driven…
In recent years, machine learning has been adopted to complex networks, but most existing works concern about the structural properties. To use machine learning to detect phase transitions and accurately identify the critical transition…