Search results for "binary"
showing 10 items of 833 documents
Partial molar enthalpies and reaction enthalpies from equilibrium molecular dynamics simulation
2014
We present a new molecular simulation technique for determining partial molar enthalpies in mixtures of gases and liquids from single simulations, without relying on particle insertions, deletions, or identity changes. The method can also be applied to systems with chemical reactions. We demonstrate our method for binary mixtures of Weeks-Chandler-Anderson particles by comparing with conventional simulation techniques, as well as for a simple model that mimics a chemical reaction. The method considers small subsystems inside a large reservoir (i.e., the simulation box), and uses the construction of Hill to compute properties in the thermodynamic limit from small-scale fluctuations. Results …
Nucleation of quasicrystals by rapid cooling of a binary melt: A molecular-dynamics study.
1995
A binary Lennard-Jones fluid was cooled in an NPT ensemble by molecular-dynamics simulations. Depending on the cooling rate, we find a sharp transition from the melt either into a disordered structure or into a phase of icosahedral long-range order. We also observed a decagonal phase.
Single Particle Jumps in a Binary Lennard-Jones Glass
2002
ABSTRACTWe study a binary Lennard-Jones mixture below the glass transition with molecular dynamics (MD) simulations. To investigate the dynamics of the system we define single particle jumps via their single particle trajectories. We find two kinds of jumps: metastable jumps, where a particle jumps back and forth between two or more states, and real jumps, where a particle does not return to any of its former states. For both the real and metastable jumps we present as a function of temperature the number of jumps, jump size, time between jumps, and energy.
Molecular Dynamics Computer Simulation of Cooling Rate Effects in a Lennard-Jones Glass
1995
We present the results of a molecular dynamics computer simulation of a binary Lennard-Jones mixture. We simulate a quench of the system from a liquid state at high temperatures to a glass state at zero temperature by coupling the system to a heat bath that has a temperature that decreases linearly (with slope -γ) with time. We investigate how the residual density of the system varies as a function of the cooling rate γ and rationalize our results by means of the dependence of the coordination number of the particles on the cooling rate.
Dynamics of a Supercooled Lennard-Jones System: Qualitative and Quantitative Tests of Mode-Coupling Theory
1996
We present the results of a molecular dynamics computer simulation of a supercooled binary Lennard-Jones mixture. By investigating the temperature dependence of the diffusion constant and of the intermediate scattering function, we show that the ideal version of the mode-coupling theory of the glass transition is able to give a good qualitative description of the dynamics of this system. Using the partial structure factors, as determined from the simulation, as input, we solve the mode-coupling equations in the long time limit. From the comparison of the prediction of the theory for the critical temperature, the exponent parameter, the wave-vector dependence of the nonergodicity parameters …
Ion-ion correlation and charge reversal at titrating solid interfaces
2009
Confronting grand canonical titration Monte Carlo simulations (MC) with recently published titration and charge reversal (CR) experiments on silica surfaces by Dove et al. and van der Heyden it et al, we show that ion-ion correlations quantitatively explain why divalent counterions strongly promote surface charge which, in turn, eventually causes a charge reversal (CR). Titration and CR results from simulations and experiments are in excellent agreement without any fitting parameters. This is the first unambiguous evidence that ion-ion correlations are instrumental in the creation of highly charged surfaces and responsible for their CR. Finally, we show that charge correlations result in "a…
Avoiding patterns in irreducible permutations
2016
We explore the classical pattern avoidance question in the case of irreducible permutations, <i>i.e.</i>, those in which there is no index $i$ such that $\sigma (i+1) - \sigma (i)=1$. The problem is addressed completely in the case of avoiding one or two patterns of length three, and several well known sequences are encountered in the process, such as Catalan, Motzkin, Fibonacci, Tribonacci, Padovan and Binary numbers. Also, we present constructive bijections between the set of Motzkin paths of length $n-1$ and the sets of irreducible permutations of length $n$ (respectively fixed point free irreducible involutions of length $2n$) avoiding a pattern $\alpha$ for $\alpha \in \{13…
A Nonlinear Label Compression and Transformation Method for Multi-label Classification Using Autoencoders
2016
Multi-label classification targets the prediction of multiple interdependent and non-exclusive binary target variables. Transformation-based algorithms transform the data set such that regular single-label algorithms can be applied to the problem. A special type of transformation-based classifiers are label compression methods, which compress the labels and then mostly use single label classifiers to predict the compressed labels. So far, there are no compression-based algorithms that follow a problem transformation approach and address non-linear dependencies in the labels. In this paper, we propose a new algorithm, called Maniac (Multi-lAbel classificatioN usIng AutoenCoders), which extra…
Deep 3D Convolution Neural Network for Alzheimer’s Detection
2020
One of the most well-known and complex applications of artificial intelligence (AI) is Alzheimer’s detection, which lies in the field of medical imaging. The complexity in this task lies in the three-dimensional structure of the MRI scan images. In this paper, we propose to use 3D Convolutional Neural Networks (3D-CNN) for Alzheimer’s detection. 3D-CNNs have been a popular choice for this task. The novelty in our paper lies in the fact that we use a deeper 3D-CNN consisting of 10 layers. Also, with effectively training our model consisting of Batch Normalization layers that provide a regularizing effect, we don’t have to use any transfer learning. We also use the simple data augmentation te…
Evaluation of debris flow susceptibility in El Salvador (CA): a comparison between Multivariate Adaptive Regression Splines (MARS) and Binary Logisti…
2018
In the studies of landslide susceptibility assessment, which have been developed in recent years, statistical methods have increasingly been applied. Among all, the BLR (Binary Logistic Regression) certainly finds a more extensive application while MARS (Multivariate Adaptive Regression Splines), despite the good performance and the innovation of the strategies of analysis, only recently began to be employed as a statistical tool for predicting landslide occurrence. The purpose of this research was to evaluate the predictive performance and identify possible drawbacks of the two statistical techniques mentioned above, focusing in particular on the prediction of debris flows. To this aim, an…