scholarly journals Machine-Learned Free Energy Surfaces for Capillary Condensation and Evaporation in Mesopores

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 97
Author(s):  
Caroline Desgranges ◽  
Jerome Delhommelle
Keyword(s):  
Phase Transition ◽  
Free Energy ◽  
Capillary Condensation ◽  
Molecular Simulations ◽  
Condensation Process ◽  
Free Energy Barrier ◽  
Enhanced Sampling ◽  
Machine Learning Model ◽  
Capillary Evaporation ◽  
Energy Surfaces

Using molecular simulations, we study the processes of capillary condensation and capillary evaporation in model mesopores. To determine the phase transition pathway, as well as the corresponding free energy profile, we carry out enhanced sampling molecular simulations using entropy as a reaction coordinate to map the onset of order during the condensation process and of disorder during the evaporation process. The structural analysis shows the role played by intermediate states, characterized by the onset of capillary liquid bridges and bubbles. We also analyze the dependence of the free energy barrier on the pore width. Furthermore, we propose a method to build a machine learning model for the prediction of the free energy surfaces underlying capillary phase transition processes in mesopores.

scholarly journals Two-step crystallization and solid–solid transitions in binary colloidal mixtures

2020 ◽  
Vol 117 (45) ◽  
pp. 27927-27933
Author(s):  
Huang Fang ◽  
Michael F. Hagan ◽  
W. Benjamin Rogers
Keyword(s):  
Free Energy ◽  
Self Assembly ◽  
Materials Science ◽  
Protein Structures ◽  
Free Energy Barrier ◽  
Enhanced Sampling ◽  
Homogeneous Fluid ◽  
Metastable Structures ◽  
One Step ◽  
Crystal Phases

Crystallization is fundamental to materials science and is central to a variety of applications, ranging from the fabrication of silicon wafers for microelectronics to the determination of protein structures. The basic picture is that a crystal nucleates from a homogeneous fluid by a spontaneous fluctuation that kicks the system over a single free-energy barrier. However, it is becoming apparent that nucleation is often more complicated than this simple picture and, instead, can proceed via multiple transformations of metastable structures along the pathway to the thermodynamic minimum. In this article, we observe, characterize, and model crystallization pathways using DNA-coated colloids. We use optical microscopy to investigate the crystallization of a binary colloidal mixture with single-particle resolution. We observe classical one-step pathways and nonclassical two-step pathways that proceed via a solid–solid transformation of a crystal intermediate. We also use enhanced sampling to compute the free-energy landscapes corresponding to our experiments and show that both one- and two-step pathways are driven by thermodynamics alone. Specifically, the two-step solid–solid transition is governed by a competition between two different crystal phases with free energies that depend on the crystal size. These results extend our understanding of available pathways to crystallization, by showing that size-dependent thermodynamic forces can produce pathways with multiple crystal phases that interconvert without free-energy barriers and could provide approaches to controlling the self-assembly of materials made from colloids.

scholarly journals Neural networks-based variationally enhanced sampling

2019 ◽  
Vol 116 (36) ◽  
pp. 17641-17647 ◽  
Author(s):  
Luigi Bonati ◽  
Yue-Yu Zhang ◽  
Michele Parrinello
Keyword(s):  
Neural Networks ◽  
Free Energy ◽  
Atomistic Simulation ◽  
Sampling Method ◽  
Machine Learning Techniques ◽  
Enhanced Sampling ◽  
Collective Variables ◽  
Learning Techniques ◽  
Minimization Technique ◽  
Energy Surfaces

Sampling complex free-energy surfaces is one of the main challenges of modern atomistic simulation methods. The presence of kinetic bottlenecks in such surfaces often renders a direct approach useless. A popular strategy is to identify a small number of key collective variables and to introduce a bias potential that is able to favor their fluctuations in order to accelerate sampling. Here, we propose to use machine-learning techniques in conjunction with the recent variationally enhanced sampling method [O. Valsson, M. Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] in order to determine such potential. This is achieved by expressing the bias as a neural network. The parameters are determined in a variational learning scheme aimed at minimizing an appropriate functional. This required the development of a more efficient minimization technique. The expressivity of neural networks allows representing rapidly varying free-energy surfaces, removes boundary effects artifacts, and allows several collective variables to be handled.

scholarly journals How does curvature affect the free-energy barrier of stalk formation? Small vesicles vs apposing, planar membranes

2021 ◽  
Author(s):  
Y. G. Smirnova ◽  
M. Müller
Keyword(s):  
Free Energy ◽  
Thermodynamic Stability ◽  
Energy Barrier ◽  
Molecular Simulations ◽  
Minimum Free Energy ◽  
Membrane Curvature ◽  
Free Energy Barrier ◽  
Planar Membranes ◽  
Strong Curvature

AbstractUsing molecular simulations of POPC lipids in conjunction with the calculation of the Minimum Free-Energy Path (MFEP), we study the effect of strong membrane curvature on the formation of the first fusion intermediate—the stalk between a vesicle and its periodic image. We find that the thermodynamic stability of this hourglass-shaped, hydrophobic connection between two vesicles is largely increased by the strong curvature of small vesicles, whereas the intrinsic barrier to form a stalk, i.e., associated with dimple formation and lipid tails protrusions, is similar to the case of two, apposing, planar membranes. A significant reduction of the barrier of stalk formation, however, stems from the lower dehydration free energy that is required to bring highly curved vesicle into a distance, at which stalk formation may occur, compared to the case of apposing, planar membranes.

Enhanced sampling of cylindrical microphase separation via a shell-averaged bond-orientational order parameter

Soft Matter ◽  
2020 ◽  
Vol 16 (3) ◽  
pp. 659-667
Author(s):  
Bumjoon Seo ◽  
Min Young Ha ◽  
Ji Woong Yu ◽  
Won Bo Lee
Keyword(s):  
Free Energy ◽  
Order Parameter ◽  
Microphase Separation ◽  
Orientational Order ◽  
Orientational Order Parameter ◽  
Enhanced Sampling ◽  
Disorder Transition ◽  
Bond Orientational Order ◽  
Energy Surfaces

The underlying free energy surfaces for the order–disorder transition of hexagonal mesophase were identified along with the metstable state.

scholarly journals Enhanced, targeted sampling of high-dimensional free-energy landscapes using variationally enhanced sampling, with an application to chignolin

2016 ◽  
Vol 113 (5) ◽  
pp. 1150-1155 ◽  
Author(s):  
Patrick Shaffer ◽  
Omar Valsson ◽  
Michele Parrinello
Keyword(s):  
Free Energy ◽  
Sampling Methods ◽  
Molecular Simulations ◽  
High Dimensionality ◽  
High Dimensional ◽  
Energy Landscapes ◽  
Enhanced Sampling ◽  
Collective Variables ◽  
Targeted Sampling ◽  
Free Energy Landscapes

The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin.

scholarly journals Free Energy Surfaces and Barriers for Vacancy Diffusion on Al(100), Al(110), Al(111) Reconstructed Surfaces

Nanomaterials ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 76
Author(s):  
Junais Habeeb Mokkath ◽  
Mufasila Mumthaz Muhammed ◽  
Ali J. Chamkha
Keyword(s):  
Free Energy ◽  
Energy Barrier ◽  
Computational Study ◽  
Metastable States ◽  
Vacancy Diffusion ◽  
Enhanced Sampling ◽  
Free Energy Surface ◽  
Collective Variables ◽  
Surface Vacancy ◽  
Energy Surfaces

Metadynamics is a popular enhanced sampling method based on the recurrent application of a history-dependent adaptive bias potential that is a function of a selected number of appropriately chosen collective variables. In this work, using metadynamics simulations, we performed a computational study for the diffusion of vacancies on three different Al surfaces [reconstructed Al(100), Al(110), and Al(111) surfaces]. We explored the free energy landscape of diffusion and estimated the barriers associated with this process on each surface. It is found that the surfaces are unique regarding vacancy diffusion. More specically, the reconstructed Al(110) surface presents four metastable states on the free energy surface having sizable and connected passage-ways with an energy barrier of height 0.55 eV. On the other hand, the reconstructed Al(100)/Al(111) surfaces exhibit two/three metastable states, respectively, with an energy barrier of height 0.33 eV. The findings in this study can help to understand surface vacancy diffusion in technologically relevant Al surfaces.

Molecular Basis of Glucose Transport Mechanism in Plants

2019 ◽  
Author(s):  
Balaji Selvam ◽  
Ya-Chi Yu ◽  
Liqing Chen ◽  
Diwakar Shukla
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Conformational Changes ◽  
Transport Mechanism ◽  
Conformational Dynamics ◽  
Site Directed Mutagenesis ◽  
Free Energy Barrier ◽  
Transport Cycle ◽  
Dynamics Simulations

<p>The SWEET family belongs to a class of transporters in plants that undergoes large conformational changes to facilitate transport of sugar molecules across the cell membrane. However, the structures of their functionally relevant conformational states in the transport cycle have not been reported. In this study, we have characterized the conformational dynamics and complete transport cycle of glucose in OsSWEET2b transporter using extensive molecular dynamics simulations. Using Markov state models, we estimated the free energy barrier associated with different states as well as 1 for the glucose the transport mechanism. SWEETs undergoes structural transition to outward-facing (OF), Occluded (OC) and inward-facing (IF) and strongly support alternate access transport mechanism. The glucose diffuses freely from outside to inside the cell without causing major conformational changes which means that the conformations of glucose unbound and bound snapshots are exactly same for OF, OC and IF states. We identified a network of hydrophobic core residues at the center of the transporter that restricts the glucose entry to the cytoplasmic side and act as an intracellular hydrophobic gate. The mechanistic predictions from molecular dynamics simulations are validated using site-directed mutagenesis experiments. Our simulation also revealed hourglass like intermediate states making the pore radius narrower at the center. This work provides new fundamental insights into how substrate-transporter interactions actively change the free energy landscape of the transport cycle to facilitate enhanced transport activity.</p>

DFT study on the hydrolysis of metsulfuron-methyl: A sulfonylurea herbicide

2018 ◽  
Vol 17 (08) ◽  
pp. 1850050 ◽  
Author(s):  
Qiuhan Luo ◽  
Gang Li ◽  
Junping Xiao ◽  
Chunhui Yin ◽  
Yahui He ◽  
...  
Keyword(s):  
Free Energy ◽  
Water Molecule ◽  
Carbonyl Group ◽  
Energy Barrier ◽  
Density Functional ◽  
Free Energy Barrier ◽  
Functional Theory ◽  
Metsulfuron Methyl ◽  
Catalytic Role ◽  
Hydrolysis Of

Sulfonylureas are an important group of herbicides widely used for a range of weeds and grasses control particularly in cereals. However, some of them tend to persist for years in environments. Hydrolysis is the primary pathway for their degradation. To understand the hydrolysis behavior of sulfonylurea herbicides, the hydrolysis mechanism of metsulfuron-methyl, a typical sulfonylurea, was investigated using density functional theory (DFT) at the B3LYP/6-31[Formula: see text]G(d,p) level. The hydrolysis of metsulfuron-methyl resembles nucleophilic substitution by a water molecule attacking the carbonyl group from aryl side (pathway a) or from heterocycle side (pathway b). In the direct hydrolysis, the carbonyl group is directly attacked by one water molecule to form benzene sulfonamide or heterocyclic amine; the free energy barrier is about 52–58[Formula: see text]kcal[Formula: see text]mol[Formula: see text]. In the autocatalytic hydrolysis, with the second water molecule acting as a catalyst, the free energy barrier, which is about 43–45[Formula: see text]kcal[Formula: see text]mol[Formula: see text], is remarkably reduced by about 11[Formula: see text]kcal[Formula: see text]mol[Formula: see text]. It is obvious that water molecules play a significant catalytic role during the hydrolysis of sulfonylureas.

scholarly journals The Dynamics of Subunit Rotation in a Eukaryotic Ribosome

Biophysica ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 204-221
Author(s):  
Frederico Campos Freitas ◽  
Gabriele Fuchs ◽  
Ronaldo Junio de Oliveira ◽  
Paul Charles Whitford
Keyword(s):  
Free Energy ◽  
Large Scale ◽  
Small Subunit ◽  
Free Energy Barrier ◽  
Temperature Dependent ◽  
Molecular Flexibility ◽  
Subunit Rotation ◽  
Biological Kinetics ◽  
Rate Limiting ◽  
Reversible Rotation

Protein synthesis by the ribosome is coordinated by an intricate series of large-scale conformational rearrangements. Structural studies can provide information about long-lived states, however biological kinetics are controlled by the intervening free-energy barriers. While there has been progress describing the energy landscapes of bacterial ribosomes, very little is known about the energetics of large-scale rearrangements in eukaryotic systems. To address this topic, we constructed an all-atom model with simplified energetics and performed simulations of subunit rotation in the yeast ribosome. In these simulations, the small subunit (SSU; ∼1 MDa) undergoes spontaneous and reversible rotation events (∼8∘). By enabling the simulation of this rearrangement under equilibrium conditions, these calculations provide initial insights into the molecular factors that control dynamics in eukaryotic ribosomes. Through this, we are able to identify specific inter-subunit interactions that have a pronounced influence on the rate-limiting free-energy barrier. We also show that, as a result of changes in molecular flexibility, the thermodynamic balance between the rotated and unrotated states is temperature-dependent. This effect may be interpreted in terms of differential molecular flexibility within the rotated and unrotated states. Together, these calculations provide a foundation, upon which the field may begin to dissect the energetics of these complex molecular machines.

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