scholarly journals Collective motion of active Brownian particles with polar alignment

Soft Matter ◽  
2018 ◽  
Vol 14 (14) ◽  
pp. 2610-2618 ◽  
Author(s):  
Aitor Martín-Gómez ◽  
Demian Levis ◽  
Albert Díaz-Guilera ◽  
Ignacio Pagonabarraga
Keyword(s):  
Collective Motion ◽  
Excluded Volume ◽  
Brownian Particles ◽  
Equilibrium Structures ◽  
Non Equilibrium

The competition between self-propulsion, alignment and excluded volume gives rise to richer non-equilibrium structures than the Vicsek and the ABP models.

BAND NN: A Deep Learning Framework For Energy Prediction and Geometry Optimization of Organic Small Molecules

2019 ◽  
Author(s):  
Siddhartha Laghuvarapu ◽  
Yashaswi Pathak ◽  
U. Deva Priyakumar
Keyword(s):  
Machine Learning ◽  
Density Functional ◽  
Computational Cost ◽  
Geometry Optimization ◽  
Dft Methods ◽  
Energy Prediction ◽  
Machine Learning Model ◽  
Equilibrium Structures ◽  
High Level ◽  
Non Equilibrium

Recent advances in artificial intelligence along with development of large datasets of energies calculated using quantum mechanical (QM)/density functional theory (DFT) methods have enabled prediction of accurate molecular energies at reasonably low computational cost. However, machine learning models that have been reported so far requires the atomic positions obtained from geometry optimizations using high level QM/DFT methods as input in order to predict the energies, and do not allow for geometry optimization. In this paper, a transferable and molecule-size independent machine learning model (BAND NN) based on a chemically intuitive representation inspired by molecular mechanics force fields is presented. The model predicts the atomization energies of equilibrium and non-equilibrium structures as sum of energy contributions from bonds (B), angles (A), nonbonds (N) and dihedrals (D) at remarkable accuracy. The robustness of the proposed model is further validated by calculations that span over the conformational, configurational and reaction space. The transferability of this model on systems larger than the ones in the dataset is demonstrated by performing calculations on select large molecules. Importantly, employing the BAND NN model, it is possible to perform geometry optimizations starting from non-equilibrium structures along with predicting their energies.

scholarly journals Tunable thermo-reversible bicontinuous nanoparticle gel driven by the binary solvent segregation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yuyin Xi ◽  
Ronald S. Lankone ◽  
Li-Piin Sung ◽  
Yun Liu
Keyword(s):  
Phase Separation ◽  
Domain Size ◽  
Binary Solvent ◽  
Colloidal Systems ◽  
Colloidal Assembly ◽  
Structures And Properties ◽  
Wide Range ◽  
Equilibrium Process ◽  
Equilibrium Structures ◽  
Non Equilibrium

AbstractBicontinuous porous structures through colloidal assembly realized by non-equilibrium process is crucial to various applications, including water treatment, catalysis and energy storage. However, as non-equilibrium structures are process-dependent, it is very challenging to simultaneously achieve reversibility, reproducibility, scalability, and tunability over material structures and properties. Here, a novel solvent segregation driven gel (SeedGel) is proposed and demonstrated to arrest bicontinuous structures with excellent thermal structural reversibility and reproducibility, tunable domain size, adjustable gel transition temperature, and amazing optical properties. It is achieved by trapping nanoparticles into one of the solvent domains upon the phase separation of the binary solvent. Due to the universality of the solvent driven particle phase separation, SeedGel is thus potentially a generic method for a wide range of colloidal systems.

scholarly journals Distinguishing between Clausius, Boltzmann and Pauling Entropies of Frozen Non-Equilibrium States

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 799 ◽  
Author(s):  
Rainer Feistel
Keyword(s):  
Heat Capacity ◽  
Historical Review ◽  
Zero Point ◽  
Quantum States ◽  
Boltzmann Entropy ◽  
Nernst Theorem ◽  
Symbolic Information ◽  
Equilibrium Structures ◽  
Physical Quantities ◽  
Non Equilibrium

In conventional textbook thermodynamics, entropy is a quantity that may be calculated by different methods, for example experimentally from heat capacities (following Clausius) or statistically from numbers of microscopic quantum states (following Boltzmann and Planck). It had turned out that these methods do not necessarily provide mutually consistent results, and for equilibrium systems their difference was explained by introducing a residual zero-point entropy (following Pauling), apparently violating the Nernst theorem. At finite temperatures, associated statistical entropies which count microstates that do not contribute to a body’s heat capacity, differ systematically from Clausius entropy, and are of particular relevance as measures for metastable, frozen-in non-equilibrium structures and for symbolic information processing (following Shannon). In this paper, it is suggested to consider Clausius, Boltzmann, Pauling and Shannon entropies as distinct, though related, physical quantities with different key properties, in order to avoid confusion by loosely speaking about just “entropy” while actually referring to different kinds of it. For instance, zero-point entropy exclusively belongs to Boltzmann rather than Clausius entropy, while the Nernst theorem holds rigorously for Clausius rather than Boltzmann entropy. The discussion of those terms is underpinned by a brief historical review of the emergence of corresponding fundamental thermodynamic concepts.

scholarly journals GPU parallel simulation algorithm of Brownian particles with excluded volume using Delaunay triangulations

2018 ◽  
Vol 229 ◽  
pp. 148-161 ◽  
Author(s):  
Francisco Carter ◽  
Nancy Hitschfeld ◽  
Cristóbal A. Navarro ◽  
Rodrigo Soto
Keyword(s):  
Parallel Simulation ◽  
Excluded Volume ◽  
Simulation Algorithm ◽  
Delaunay Triangulations ◽  
Brownian Particles

Scaling behavior of non-equilibrium phase transitions in spontaneously ordered motion of self-propelled particles

2016 ◽  
Vol 30 (24) ◽  
pp. 1650304 ◽  
Author(s):  
R. Bakir ◽  
I. Tarras ◽  
A. Hader ◽  
H. Sbiaai ◽  
M. Mazroui ◽  
...  
Keyword(s):  
Phase Transitions ◽  
Collective Motion ◽  
Equilibrium Phase ◽  
Deposition Process ◽  
Scaling Behavior ◽  
Scaling Exponents ◽  
Vicsek Model ◽  
Self Similar ◽  
Ordered Motion ◽  
Non Equilibrium

Many animal groups, such as bird flocks, clearly present structural order and appear to move as a single coherent entity. In interest to understand the complex behavior of these systems, many models have been proposed and tested so far. The aim of this work is to study and discuss numerically the scaling behavior in the 2D non-equilibrium phase transitions in spontaneously ordered motion of self-propelled particles in the framework of Vicsek model. This model is an important tool to study the behavior of collective motion of live biological and physical organisms. The calculation of the scaling exponents is effected by using the scaling dynamic method. However, the time evolution of the particles velocity present two different regimes separated by a cross-over time which increases linearly with both applied noise and radius of repulsive zone, but it decreases exponentially with the radius of orientation zone. The results show that the obtained exponents are similar to the growth and roughness ones used in the interfaces growth and to the submonolayer deposition process. The obtained values of these exponents are not dependent on the noises value, which proves their universality characters. Hence the kinetic evolution of the spontaneously ordered motion of self-propelled particles is self-similar. Implications of these findings are discussed.

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