Crystal structure prediction using the minima hopping method

A structure prediction method is presented based on the minima hopping method. To escape local minima, moves on the configurational enthalpy surface are performed by variable cell shape molecular dynamics. To optimize the escape steps the initial atomic and cell velocities are aligned to low curvature directions of the current local minimum. The method is applied to both silicon crystals and well-studied binary Lennard-Jones mixtures. For the latter new putative ground state structures are presented. It is shown that a high success rate is achieved and a reliable prediction of unknown ground state structures is possible.     

Particle rearrangements during transitions between local minima of the potential energy landscape of a binary Lennard-Jones liquid

The potential energy landscape (PEL) of binary Lennard-Jones (BLJ) mixtures exhibits local minima, or inherent structures (IS), which are organized into metabasins (MBs). We study the particle rearrangements related to transitions between both successive IS and successive MB for a small 80:20 BLJ system near the mode-coupling temperature TMCT. The analysis includes the displacements of individual particles, the localization of the rearrangements, and the relevance of string-like motion. We find that the particle rearrangements during IS and MB transitions do not change significantly at TMCT. In particular, an onset of single particle hopping on the length scale of the interparticle distance is not observed. Further, it is demonstrated that IS and MB dynamics are spatially heterogeneous and facilitated by string-like motion. To investigate the mechanism of string-like motion, we follow the particle rearrangements during suitable sequences of IS transitions. We find that most strings observed after a series of transitions do not move coherently during a single transition, but subunits of different sizes are active at different times. Several findings suggest that, though string-like motion is of comparable relevance when the system explores a MB and when it moves from one MB to another, the occurrence of a successful string enables the system to exit a MB. Moreover, we show that the particle rearrangements during two consecutive MB transitions are basically uncorrelated. In particular, different groups of particles are highly mobile. We further find the positions of strings during successive MB transitions weakly but positively correlated, supporting the idea of dynamic facilitation. Finally, the relation between the features of the potential energy landscape and the relaxation processes in supercooled liquids is discussed.     

Many-body optimization using an ab initio monte carlo method

Advances in computing power have made it possible to study solvated molecules using ab initio quantum chemistry. Inclusion of discrete solvent molecules is required to determine geometric information about solute/solvent clusters. Monte Carlo methods are well suited to finding minima in many-body systems, and ab initio methods are applicable to the widest range of systems. A first principles Monte Carlo (FPMC) method was developed to find minima in many-body systems, and emphasis was placed on implementing moves that increase the likelihood of finding minimum energy structures. Partial optimization and molecular interchange moves aid in finding minima and overcome the incomplete sampling that is unavoidable when using ab initio methods. FPMC was validated by studying the boron trifluoride-water system, and then the method was used to examine the methyl carbenium ion in water to demonstrate its application to solvation problems.     

ChemInform Abstract: Identification of Novel Cu,Ag, and Au Ternary Oxides from Global Structural Prediction.

Ab initio global structural prediction and specifically, the minima hopping method combined with high‐throughput calculations are used to explore the periodic table in search of novel oxide phases.     

Minima hopping: an efficient search method for the global minimum of the potential energy surface of complex molecular systems

A method is presented that can find the global minimum of very complex condensed matter systems. It is based on the simple principle of exploring the configurational space as fast as possible and of avoiding revisiting known parts of this space. Even though it is not a genetic algorithm, it is not based on thermodynamics. The efficiency of the method depends strongly on the type of moves that are used to hop into new local minima. Moves that find low-barrier escape-paths out of the present minimum generally lead into low energy minima.     

Monte Carlo temperature basin paving with effective fragment potential: an efficient and fast method for finding low-energy structures of water clusters (H2O)20 and (H2O)25

Determining low-energy structures of large water clusters is a challenge for any optimization algorithm. In this work, we have developed a new Monte Carlo (MC)-based method, temperature basin paving (TBP), which is related to the well-known basin hopping method. In the TBP method, the Boltzmann weight factor used in MC methods is dynamically modified based on the history of the simulation. The states that are visited more are given a lower probability by increasing their temperatures and vice versa. This allows faster escapes from the states frequently visited in the simulation. We have used the TBP method to find a large number of low-energy minima of water clusters of size 20 and 25. We have found structures energetically same to the global minimum structures known for these two clusters. We have compared the efficiency of this method to the basin-hopping method and found that it can locate the minima faster. Statistical efficiency of the new method has been investigated by running a large number of trajectories. The new method can locate low-energy structures of both the clusters faster than some of the reported algorithms for water clusters and can switch between high energy and low-energy structures multiple times in a simulation illustrating its efficiency. The large number of minima obtained from the simulations is used to get both general and specific features of the minima. The distribution of minima for these two clusters based on the similarity of their oxygen frames shows that the (H(2)O)(20) can have different variety of structures, but for (H(2)O)(25), low-energy structures are mostly cagelike. Several (H(2)O)(25) structures are found with similar energy but with different cage architectures. Noncage structures of (H(2)O)(25) are also found but they are 6-7 kcal/mol higher in energy from the global minimum. The TBP method is likely to play an important role for exploring the complex energy landscape of large molecules.     

Sampling small-scale and large-scale conformational changes in proteins and molecular complexes

Sampling of small-scale and large-scale motions is important in various computational tasks, such as protein-protein docking and ligand binding. Here, we report further development and applications of the activation-relaxation technique for internal coordinate space trajectories (ARTIST). This method generates conformational moves of any complexity and size by identifying and crossing well-defined saddle points connecting energy minima. Simulations on two all-atom proteins and three protein complexes containing between 70 and 300 amino acids indicate that ARTIST opens the door to the full treatment of all degrees of freedom in dense systems such as protein-protein complexes.     

Growth and structural properties of Mg(N) (N = 10-56) clusters: density functional theory study

Using the minima hopping global geometry optimization method on density functional potential energy surface, we have studied the structural and electronic properties of magnesium clusters for a size range of Mg(N) where N = 10-56. Our exhaustive search reveals that most of our global minima are nonsymmetric in the size range above N = 20. We elucidate the evolutionary trend of the entire series and present more details about the peculiar growth of the clusters. For N > 20, it is possible to divide the cluster into two regions: the core region and the surface region. It turns out that the growth follows a peculiar cyclic pattern where the core and surface grow alternatively. The surface energy, as a function of number of atoms shows a clear signature as the number of atoms in the core increases by one. We have also carried out stability analysis and the stable sizes(magic numbers) agree very well with the experimental magic numbers reported by Diederich [J. Chem. Phys. 2011, 134, 124302]. We point out the similarities and differences between our results and sodium clusters.     

Hybridizing rapidly exploring random trees and basin hopping yields an improved exploration of energy landscapes

The number of local minima of the potential energy landscape (PEL) of molecular systems generally grows exponentially with the number of degrees of freedom, so that a crucial property of PEL exploration algorithms is their ability to identify local minima, which are low lying and diverse. In this work, we present a new exploration algorithm, retaining the ability of basin hopping (BH) to identify local minima, and that of transition based rapidly exploring random trees (T‐RRT) to foster the exploration of yet unexplored regions. This ability is obtained by interleaving calls to the extension procedures of BH and T‐RRT, and we show tuning the balance between these two types of calls allows the algorithm to focus on low lying regions. Computational efficiency is obtained using state‐of‐the art data structures, in particular for searching approximate nearest neighbors in metric spaces. We present results for the BLN69, a protein model whose conformational space has dimension 207 and whose PEL has been studied exhaustively. On this system, we show that the propensity of our algorithm to explore low lying regions of the landscape significantly outperforms those of BH and T‐RRT. © 2015 Wiley Periodicals, Inc.     

Global optimization of binary Lennard-Jones clusters using three perturbation operators

Global optimization of binary Lennard-Jones clusters is a challenging problem in computational chemistry. The difficulty lies in not only that there are enormous local minima on the potential energy surface but also that we must determine both the coordinate position and the atom type for each atom and thus have to deal with both continuous and combinatorial optimization. This paper presents a heuristic algorithm (denoted by 3OP) which makes extensive use of three perturbation operators. With these operators, the proposed 3OP algorithm can efficiently move from a poor local minimum to another better local minimum and detect the global minimum through a sequence of local minima with decreasing energy. The proposed 3OP algorithm has been evaluated on a set of 96 × 6 instances with up to 100 atoms. We have found most putative global minima listed in the Cambridge Cluster Database as well as discovering 12 new global minima missed in previous research.     

Novel Monte Carlo scheme for systems with short-ranged interactions

We propose a Monte Carlo (MC) sampling algorithm to simulate systems of particles interacting via very short-ranged discontinuous potentials. Such models are often used to describe protein solutions or colloidal suspensions. Most normal MC algorithms fail for such systems because, at low temperatures, they tend to get trapped in local potential-energy local minima due to the short range of the pair potential. To circumvent this problem, we have devised a scheme that changes the construction of trial moves in such a way that the potential-energy difference between initial and final states drops out of the acceptance rule for the Monte Carlo trial moves. This approach allows us to simulate systems with short-ranged attraction under conditions that were unreachable up to now.     

Accelerating molecular simulations by reversible mapping between local minima

A new framework is presented for performing Monte Carlo simulations of condensed matter based on a recently developed bijective mapping between local energy minima. The framework is used to implement a range of new multiparticle Monte Carlo moves, which are investigated by simulating atomic Lennard-Jones fluids in the canonical and grand canonical ensembles. Important aspects of the simulation protocol and their effect on performance are analyzed in detail. Using the mapping accelerates the simulations by many orders of magnitude when compared to the equivalent moves without the mapping, and leads to particularly efficient configurational sampling at low temperatures and high densities. The method appears to be suitable for adapting to quantitative simulations of more complex molecular systems over long effective time scales.     

Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules

Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution.     

Geometric thermodynamic description of the congruent-melting points of solid solutions in binary and ternary systems

The congruent-melting points of solid solutions are analyzed in binary systems (minima, maxima, and shunts on the melting curves) and ternary systems (minima, maxima, saddles, and saddle-nodes on melting surfaces).     

The analysis of volatile liquid mixtures by thermal conductivity measurements on their vapors

The composition of solutions of volatile liquids can be determined by volatilization into a stream of inert gas and measurement of the thermal conductivity of the resulting gas mixture. The method is directly applicable to binary liquid mixtures which do not show maxima or minima in the conductivity-composition curve and, with modification, it may be applied to the analysis of other mixtures.The observed and calculated thermal conductivities for the acetone— water— nitrogen system showed good agreement that was typical of a number of systems     

Theoretical model based on the memory effect for the strange photoisomerization kinetics of diarylethene derivatives dispersed on polymer films

In the present paper the authors present a theoretical model to explain the kinetics involving the induction period observed by Irie et al. [Nature (London) 420, 759 (2002)] for photoisomerization of diarylethene derivatives dispersed on polymer films at a single molecular level. In the model we assume that both ground state and excited state free energy landscapes which result from the interaction between the photochromic molecule and the surrounding polymer are rugged and have several local minima along the pathway to the critical point at which isomerization actually occurs. We assume that after one photoexcitation a fraction of the photochromic molecule moves to a new local minimum and stays there, although the other fraction returns to the original local minimum. The former effect is referred to as the memory effect. After repeated photoexcitations the photochromic molecule moves gradually from one local minimum to another in the pathway to the isomerization point. It finally reaches the isomerization point, where isomerization occurs. Their model successfully reproduces the kinetics of photoisomerization of diarylethene derivatives dispersed on polymer films observed experimentally.     

Nuclear magnetic resonance investigation of dynamics in poly(ethylene oxide)-based lithium polyether-ester-sulfonate ionomers

Nuclear magnetic resonance spectroscopy has been utilized to investigate the dynamics of poly(ethylene oxide)-based lithium sulfonate ionomer samples that have low glass transition temperatures. (1)H and (7)Li spin-lattice relaxation times (T(1)) of the bulk polymer and lithium ions, respectively, were measured and analyzed in samples with a range of ion contents. The temperature dependence of T(1) values along with the presence of minima in T(1) as a function of temperature enabled correlation times and activation energies to be obtained for both the segmental motion of the polymer backbone and the hopping motion of lithium cations. Similar activation energies for motion of both the polymer and lithium ions in the samples with lower ion content indicate that the polymer segmental motion and lithium ion hopping motion are correlated in these samples, even though lithium hopping is about ten times slower than the segmental motion. A divergent trend is observed for correlation times and activation energies of the highest ion content sample with 100% lithium sulfonation due to the presence of ionic aggregation. Details of the polymer and cation dynamics on the nanosecond timescale are discussed and complement the findings of X-ray scattering and quasi-elastic neutron scattering experiments.     

Monomeric adenine decay dynamics influenced by the DNA environment

We report on‐the‐fly surface‐hopping dynamics simulations of single adenine embedded in solvated DNA oligomers, (dA)₁₀ and (dA)₁₀·(dT)₁₀. Both model systems are found to decay from the S₁ to the S₀ state via distinct monomeric channels, on account of the strong hydrogen‐bonding interactions between the Watson–Crick pair in the double‐stranded oligomer. Surprisingly, the decay times (several picoseconds) for the current models are 10 times longer than those of adenine in the gas or aqueous phase, while matching one of the time constants observed experimentally. We discuss possible reasons for these longer decay times, including steric hindrance in the DNA strands, electronic effects of the environment, and the presence of other local excited‐state minima. We present optimized geometries and relative energies for representative S₀ and S₁ minima as well as conical intersections related to the hopping events. We have also computed steady‐state and time‐dependent fluorescence spectra that may help understand the experimental observations. © 2012 Wiley Periodicals, Inc.     

Surveying a potential energy surface by eigenvector-following

We have developed a method to search potential energy surfaces which avoids some of the difficulties associated with trapping in local minima. Steps are directly taken between minima using eigenvector-following. Exploration of this space by low temperature Metropolis Monte Carlo is a useful global optimisation tool. This method successfully finds the lowest energy icosahedral minima of Lennard- Jones clusters from random starting configurations, but cannot find the global minimum in a reasonable time for difficult cases such as the 38-atom Lennard-Jones cluster where the face-centred-cubic truncated octahedron is lowest in energy. However, by performing searches at higher temperatures, we have found a pathway between the truncated octahedron and the lowest energy icosahedral minima. Such a pathway may be illustrative of some of the structural transformations that are observed for supported metal clusters by electron microscopy.     

Automatic estimation of varying continuum background emission in laser-induced breakdown spectroscopy

In laser-induced breakdown spectroscopy (LIBS), plasma emission is extremely unstable because of many factors, such as the fluctuation of laser energy, inhomogeneity of sample surfaces, and variable distance between lens and samples. Therefore, the detection and correction of varying continuum background emission are not easily accomplished. The aim of this work is to present a method that can automatically estimate and correct varying continuum background emission, which is representative in laser-induced plasma. In this method, we first find all minima on a spectrum, and then deduct the unreasonable minima by a proper threshold. Finally, we use one or multiple polynomial functions through the minima left to approximate the continuum backgrounds. The validity of this method was evaluated by using several spectra with different complexities and wavelength ranges. We also applied this method to optimize the measurement time delays of detectors. In addition, for five aluminum alloy samples, we compared their elemental calibration cures between original spectra and background-corrected spectra. Experimental results proved that the method proposed in this paper can well estimate varying continuum backgrounds over a wide range of wavelengths.