Non-equilibrium structures in monolayers of fatty alcohols

2007 ◽  
pp. 269-270
Author(s):  
S. Siegel ◽  
S. Siegel
Keyword(s):  
Fatty Alcohols ◽  
Equilibrium Structures ◽  
Non Equilibrium

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.

Non-equilibrium structures and geometry relaxation in polyoctylthiophene

1990 ◽  
Vol 172 (2) ◽  
pp. 143-146 ◽  
Author(s):  
G. Zerbi ◽  
L. Castellani ◽  
B. Chierichetti ◽  
C. Gallazzi ◽  
O. Ingänas
Keyword(s):  
Equilibrium Structures ◽  
Non Equilibrium

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.

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