Multidimensional Configuration Space Research Articles

Correlating Nitrate Adsorption with the Local Environments of FeCoNiCuZn High-Entropy Alloy Catalysts Using Machine Learning.

The electrocatalytic nitrate reduction to ammonia holds significant values for water remediations and energy applications, which quests for the development of highly effective catalysts with considerable stability and selectivity. Recently, high-entropy alloys (HEAs) are attracting growing attention for electrocatalytic processes. Nonetheless, studies of HEA-based nitrate reduction to ammonia are still at the early stage, and it remains unclear how the HEA compositions affect the adsorption and activation of the reaction intermediates. Herein, high-throughput density functional theory (DFT) calculations were integrated with machine learning to investigate the dependence of nitrate adsorption on the FeCoNiCuZn HEA structures. In particular, a total of 1268 different structures were sampled and constructed from the multidimensional configuration space, followed by the DFT calculations to investigate the Gibbs free energy of nitrate adsorption (i.e., ΔGNO3) on different surface microstructures. Four regression models were successfully developed, which can accurately predict ΔGNO3 using the HEA structures as the input features. Through the analysis of the feature importance, it was found that the active sites are crucial for nitrate adsorption; meanwhile, the local environments also play a considerable role. The dependence of the ΔGNO3 and adsorption geometries on the HEA compositions demonstrates that the compositional modulation of the HEA catalysts could be a promising avenue for facile adsorption and activation of reaction intermediates. Overall, this work will contribute to the probabilistic optimization of the HEA microstructures for enhanced electrochemical nitrate reduction.

Photoisomerization pathways of trans-resveratrol.

Resveratrol is well-known for promoting health benefits due to its antioxidant, anti-aging, anti-carcinogenic, and other beneficial activities. Understanding the photophysics of resveratrol is essential for determining its applicability to pharmaceutical innovations. In the present work, we used an explore-then-assess strategy to map the internal conversion pathways of trans-resveratrol. This strategy consists of exploring the multidimensional configurational space with nonadiabatic dynamics simulations based on a semiempirical multireference method, followed by a feasibility assessment of reduced-dimensionality pathways at a high ab initio theoretical level. The exploration step revealed that internal conversion to the ground state may occur near five distinct conical intersections. The assessment step showed that the main photoisomerization pathway involves a twisted-pyramidalized S1/S0 conical intersection, yielding either trans or cis isomers. However, a secondary path was identified, where cis-trans isomerization happens in the excited state and internal conversion occurs at a cyclic conical intersection, yielding a closed-ring resveratrol derivative. This derivative, which can be formed through this direct path or an indirect photoexcitation, may be connected to the production of oxygen-reactive species previously reported and have implications in photodynamic therapy.

High-Entropy Alloy for Thin Film Application: A Review

High entropy alloy (HEA) involves the addition of five or more elements into the materials system. This provides a multidimensional configuration space that is limitless in terms of its properties and functions. Some high-entropy alloys have already been shown to have superior properties over conventional alloys, especially the CoCr-based HEA materials. Better high-entropy alloy applications may be discovered, especially in micro- and nano-level structures, hence the development of thin film/coating -based HEA materials. Therefore, in this review paper, we are aiming to provide recent studies on the thin film/coating-based high-entropy alloy on fundamental issues related to methods of preparation, phase formation and mechanical properties. We found that sputtering has been extensively used to grow thin-film-based HEAs as it allowed parameters to be controlled with homogeneous growth. The evolution from bulk to thin samples can also be observed with the mechanical properties has exceeded the bulk-based HEA expectations, which are high hardness, better interfacial bonding and tribological behaviour and higher corrosion resistant.

Enantiomeric Transitions in the Chiral Cluster Au15 Studied by a Reaction Coordinate Deduced from Molecular Dynamics Simulations

A recently developed modified basin hopping (MBH) optimization algorithm, combined with an energy function calculated by the semiempirical density functional tight-binding (DFTB) theory, was applied to determine the lowest-energy structures of Aun clusters with size n = 3-20. It was predicted from the DFTB/MBH optimization algorithm calculations that clusters Au10, Au15, and Au18 exhibit chiral properties; i.e., each of these three clusters possesses the same energy value and associated with it are two nonsuperposable mirror-image clusters. In the potential energy landscape, there thus exist multidimensional barriers separating the two enantiomers, and this lowest-energy double-well morphology is surrounded by potential-energy minima of higher energies. In this paper, we have chosen to study the chiral cluster Au15 by employing an isothermal Brownian-type molecular dynamics simulation to discern in greater detail its conformational transition from one enantiomer, say left, to its right counterpart. To facilitate our analysis of the simulation data, we transpose the multidimensional configurational space description to a lower dimensional collective variable (CV) space spanned by two geometry-relevant CVs. The thermally driven progression and mechanism of enantiomeric transitions between the left and right enantiomers will be our main focus, and the strategy is to dissect the time development of the CVs collected from different sets of independent simulation runs. From simulation data, we found that an understanding of the dynamics of enantiomeric transitions needs first to seek out the left and right enantiomers through a molecular modeling and visualizing program, then to ferret out and identify between the left and right enantiomers a symmetrical structure, and finally to define from the latter a reaction coordinate. We showed in this work that this single reaction coordinate is predictive in unraveling the left ⇌ right enantiomeric transition events, providing a specific inkling of the transition time span and its associated distribution which can be checked further for its reasonableness by the autocorrelation function and a vibrational analysis, all of which shed light on the mechanisms of transition.

A "backtracking" correction for the fewest switches surface hopping algorithm.

We propose a "backtracking" mechanism within Tully's fewest switches surface hopping (FSSH) algorithm, whereby whenever one detects consecutive (double) hops during a short period of time, one simply rewinds the dynamics backward in time. In doing so, one reduces the number of hopping events and comes closer to a truly fewest switches surface hopping approach with independent trajectories. With this algorithmic change, we demonstrate that surface hopping can be reasonably accurate for nuclear dynamics in a multidimensional configuration space with a complex-valued (i.e., not real-valued) electronic Hamiltonian; without this adjustment, surface hopping often fails. The added computational cost is marginal. Future research will be needed to assess whether or not this backtracking correction can improve the accuracy of a typical FSSH calculation with a real-valued electronic Hamiltonian (that ignores spin).

Pump–Push–Probe for Ultrafast All‐Optical Switching: The Case of a Nanographene Molecule

AbstractIn the last two decades, the three‐beam pump–push–probe (PPP) technique has become a well‐established tool for investigating the multidimensional configurational space of a molecule, as it permits disclosure of precious information about the multiple and often complex deactivation pathways of the excited molecule. From the spectroscopic point of view, such a tool has revealed details about the efficiency of charge pair generation and conformational relaxation in π‐conjugated molecules and macromolecules. In addition, PPP is effectively utilized for modulating the gain signal in conjugated materials by taking advantage of the spectral overlap between stimulated emission and charge absorption in those systems. However, the relatively low stability of conjugated polymers under intense photoexcitation is a crucial limitation for their real employment in plastic optical fibers (POFs) and for signal control applications. Herein, the role of PPP for achieving ultrafast all‐optical switching in π‐conjugated systems is highlighted. Furthermore, new experimental data on optical switching of a newly synthesized nanographene molecule, namely dibenzo[hi,st]ovalene (DBOV), is reported. The superior environmental and photostability of DBOV and, in general, of graphene nanostructures can represent a great advantage for their effective applications in POFs and information and communications technology.

Nonlinear modes disentangle glassy and Goldstone modes in structural glasses

One outstanding problem in the physics of glassy solids is understanding the statistics and properties of low-energy excitations that stem from the disorder that characterizes these systems' microstructure. In this work we introduce a family of algebraic equations whose solutions represent collective displacement directions (modes) in the multi-dimensional configuration space of a structural glass. We explain why solutions of the algebraic equations, coined nonlinear glassy modes, are quasi-localized low-energy excitations. We present an iterative method to solve the algebraic equations, and use it to study the energetic and structural properties of a selected subset of their solutions constructed by starting from a normal mode analysis of the potential energy of a model glass. Our key result is that the structure and energies associated with harmonic glassy vibrational modes and their nonlinear counterparts converge in the limit of very low frequencies. As nonlinear modes never suffer hybridizations, our result implies that the presented theoretical framework constitutes a robust alternative definition of `soft glassy modes' in the thermodynamic limit, in which Goldstone modes overwhelm and destroy the identity of low-frequency harmonic glassy modes.

Extension of Configurational Polyhedra to Finite Temperature Property

Configurational polyhedora (CP) is a hyperpolyhedra on multidimensional configuration space, whose vertex (and edges) corresponds to upper or lower limit value of correlation functions for all possible atomic configuration on given lattice. In classical systems where physical property including internal energy and elastic modulus can be a linear map for structures considered, it is known that atomic configuration having highest (or lowerst) physical quantity should always locate on one of the vertices at absolute zero temperature. The present study extend the idea of CP to finite-temperature property (especially, focusing on internal energy), and successfully provides demonstration of how temperature dependence of internal energy in equilibrium state for alloys is interpreted in terms of the density of states for non-interacting system along specially selected direction on cofiguration space.

Spontaneous energy-barrier formation in entropy-driven glassy dynamics.

The description of activated relaxation of glassy systems in the multidimensional configurational space is a long-standing open problem. We develop a phenomenological description of the out-of-equilibrium dynamics of a model with a rough potential energy landscape and we analyze it both numerically and analytically. The model provides an example of dynamics where typical relaxation channels go over finite-potential energy barriers despite the presence of less-energy-demanding escaping paths in configurational space; we expect this phenomenon to be also relevant in the thermally activated regime of realistic models of glass-formers. In this case, we found that typical dynamical paths episodically reach an high-fixed-threshold energy, unexpectedly giving rise to a simple thermally activated aging phenomenology. In order to unveil this peculiar aging behavior, we introduce a novel description of the dynamics in terms of spontaneously emerging dynamical basins.

Two-dimensional macroscopic quantum tunneling in multi-gap superconductor Josephson junctions

Low-temperature characters of superconducting devices yield definite probes for different superconducting phenomena. We study the macroscopic quantum tunneling (MQT) in a Josephson junction, composed of a single-gap superconductor and a two-gap superconductor. Since this junction has two kinds to the superconducting phase differences, calculating the MQT escape rate requires the analysis of quantum tunneling in a multi-dimensional configuration space. Our approach is the semi-classical approximation along a 1D curve in a 2D potential- energy landscape, connecting two adjacent potential (local) minimums through a saddle point. We find that this system has two plausible tunneling paths; an in-phase path and an out-of-phase path. The former is characterized by the Josephson-plasma frequency, whereas the latter is by the frequency of the characteristic collective mode in a two-band superconductor, Josephson- Leggett mode. Depending on external bias current and inter-band Josephson-coupling energy, one of them mainly contributes to the MQT. Our numerical calculations show that the difference between the in-phase path and the out-of-phase path is manifest, with respect to the bias- current-dependence of the MQT escape rate. This result suggests that our MQT setting be an indicator of the Josephson-Leggett mode.

Cold fission from isomeric states of superheavy nuclei

Correlations between the potential energy surface structure and the mass distributions observed in the production of superheavy nuclei are evidenced. The isomeric states are identified by spanning the multidimensional configuration space from the contact point of the colliding nuclei up to the formation of the compound nucleus. The available degrees of freedom are the elongation, the necking, the mass asymmetry, and the deformations of the two colliding nuclei. Using the macroscopic-microscopic model based on the Woods-Saxon two-center shell model, several minima in the potential energy landscape were revealed. The fission process from these isomeric states was investigated and the probabilities of realization of possible partitions were calculated in the WKB approximation. The inertia was computed in the framework of the cranking model. The identified correlations indicate that the mass distribution attributed to quasifission in previous studies can be alternatively explained as a cold-fission process from excited states.

A Simple Coarse-Grained Model to Map the Transition Pathway Between Two Stable Conformations using the Anisotropic Elastic Network Model

Conformational transitions in biomolecules, especially proteins, play an important role in signaling and regulation of various biological processes. Here we propose a fast and simple method for constructing a transition pathway between two stable conformations of a protein. The protein is represented as a simplified coarse-grained (CG) model with a single site located at the C-alpha atom of each residue. The energy function of the two-state CG model is approximated by the anisotropic network model (ANM) harmonic energy surfaces of the end-states. The simple two-state energy surface comprises two local minima centered on the positions of the stable states and the system resides in one of these minima. There is a cusp with discontinuous first derivative in the multi-dimensional configuration space of the system, which acts as the transition state surface for the two-state potential. Given this simple prescription, two structures constrained to remain similar to one another but each residing on the opposite sides of the cusp, are optimized using energy minimization. This virtual “dumbbell” of two structures is then used as a crude approximation to the transition state. The pathway in the multi-dimensional space is constructed by letting these two structures slide down on their ANM surface using steepest descent energy minimization until the stable end-points are reached. This simple two-state ANM model was applied to explore the multi-dimensional and collective character of the conformational transition pathways in several systems of biological significance, including adenylate kinase, leucine transporter, sarcoplasmic reticulum Ca-ATPase and the glutamate transporter.

Temperature Accelerated Dynamics in Glass-Forming Materials

In this work we propose a methodology for improving dynamical sampling in molecular simulations via temperature acceleration. The proposed approach combines the novel methods of Voter for temperature-accelerated dynamics with the multiple histogram reweighting method of Ferrenberg and Swendsen, its dynamical extension by Nieto-Draghi et al., and with hazard plot analysis, allowing optimal sampling with small computational cost over time scales inaccessible to classical molecular dynamics simulations by utilizing the "inherent structure" idea. The time evolution of the system is viewed as a succession of transitions between "basins" in its potential energy landscape, each basin containing a local minimum of the energy (inherent structure). Applying the proposed algorithm to a glass-forming material consisting of a mixture of spherical atoms interacting via Lennard-Jones potentials, we show that it is possible to perform an exhaustive search and evaluate rate constants for basin-to-basin transitions that cover several orders of magnitude on the time scale, far beyond the abilities of any competitive dynamical study, revealing an extreme ruggedness of the potential energy landscape in the vicinity of the glass transition temperature. By analyzing the network of inherent structures, we find that there are characteristic distances and rate constants related to the dynamical entrapment of the system in a neighborhood of basins (a metabasin), whereas evidence to support a random energy model is provided. The multidimensional configurational space displays a self-similar character depicted by a fractal dimension around 2.7 (+/-0.5) for the set of sampled inherent structures. Only transitions with small Euclidean measure can be considered as localized.

From molecule to solid: The prediction of organic crystal structures

A method for predicting the structure of a molecular crystal based on the systematic search for a global potential energy minimum is considered. The method takes into account unequal occurrences of the structural classes of organic crystals and symmetry of the multidimensional configuration space. The programs of global minimization PMC, comparison of crystal structures CRYCOM, and approximation to the distributions of the electrostatic potentials of molecules FitMEP are presented as tools for numerically solving the problem. Examples of predicted structures substantiated experimentally and the experience of author’s participation in international tests of crystal structure prediction organized by the Cambridge Crystallographic Data Center (Cambridge, UK) are considered.

Monte Carlo method for computing density of states and quench probability of potential energy and enthalpy landscapes

The thermodynamics and kinetics of a many-body system can be described in terms of a potential energy landscape in multidimensional configuration space. The partition function of such a landscape can be written in terms of a density of states, which can be computed using a variety of Monte Carlo techniques. In this paper, a new self-consistent Monte Carlo method for computing density of states is described that uses importance sampling and a multiplicative update factor to achieve rapid convergence. The technique is then applied to compute the equilibrium quench probability of the various inherent structures (minima) in the landscape. The quench probability depends on both the potential energy of the inherent structure and the volume of its corresponding basin in configuration space. Finally, the methodology is extended to the isothermal-isobaric ensemble in order to compute inherent structure quench probabilities in an enthalpy landscape.

Frequency distribution of mechanically stable disk packings

Relative frequencies of mechanically stable (MS) packings of frictionless bidisperse disks are studied numerically in small systems. The packings are created by successively compressing or decompressing a system of soft purely repulsive disks, followed by energy minimization, until only infinitesimal particle overlaps remain. For systems of up to 14 particles, most of the MS packings were generated. We find that the packings are not equally probable as has been assumed in recent thermodynamic descriptions of granular systems. Instead, the frequency distribution, averaged over each packing-fraction interval Deltaphi , grows exponentially with increasing phi. Moreover, within each packing-fraction interval, MS packings occur with frequencies f{k} that differ by many orders of magnitude. Also, key features of the frequency distribution do not change when we significantly alter the packing-generation algorithm; for example, frequent packings remain frequent and rare ones remain rare. These results indicate that the frequency distribution of MS packings is strongly influenced by geometrical properties of the multidimensional configuration space. By adding thermal fluctuations to a set of the MS packings, we were able to examine a number of local features of configuration space near each packing. We measured the time required for a given packing to break to a distinct one, which enabled us to estimate the energy barriers that separate one packing from another. We found a gross positive correlation between the packing frequencies and the heights of the lowest energy barriers {0}; however, there is significant scatter in the data. We also examined displacement fluctuations away from the MS packings to assess the size and shape of the local basins near each packing. The displacement modes scale as d{i} approximately epsilon{0}{gamma{i}} with gamma{i} ranging from approximately 0.6 for the largest eigenvalues to 1.0 for the smallest ones. These scalings suggest that the packing frequencies are not determined by the local volume of configuration space near each packing, which would require that the dependence of f{k} on epsilon{0} is much stronger than the dependence we observe. The scatter in our data implies that in addition to epsilon{0} there are also other, as yet undetermined variables that influence the packing probabilities.

Topographical complexity of multidimensional energy landscapes

A scheme for visualizing and quantifying the complexity of multidimensional energy landscapes and multiple pathways is presented employing principal component-based disconnectivity graphs and the Shannon entropy of relative "sizes" of superbasins. The principal component-based disconnectivity graphs incorporate a metric relationship between the stationary points of the system, which enable us to capture not only the actual assignment of the superbasins but also the size of each superbasin in the multidimensional configuration space. The landscape complexity measure quantifies the degree of topographical complexity of a multidimensional energy landscape and tells us at which energy regime branching of the main path becomes significant, making the system more likely to be kinetically trapped in local minima. The path complexity measure quantifies the difficulty encountered by the system to reach a connected local minimum by the path in question, implying that the more significant the branching points along the path the more difficult it is to end up in the desired local minimum. As an illustrative example, we apply this analysis to two kinds of small model protein systems exhibiting a highly frustrated and an ideal funnel-like energy landscape.

High throughput screening of ferroelectric thin film libraries

High throughput methods can significantly speed up the search for advanced materials in a multidimensional configuration space, hence keeping innovation cycles short. In the search for improved materials, high throughput methods are wanted to optimize composition and processing of promising systems, and to find candidate compounds. Such a method is described here which is applicable to the development of ferroelectric thin films. Libraries with samples of varying chemical composition were produced via the sol-gel route on structured and metallized silicon wafers. To determine the permittivity of the films, automated measurements of film thickness and capacity were established. Furthermore, ferroelectric hysterisis measurements were performed on samples with a particularly high permittivity. This high throughput route, which allows for synthesis and characterization of over hundred samples per day, was proved and tested by means of lead zirconate titanate as a standard material. It was possible to obtain films with remarkable high permittivity and low coercive field at optimal lead zirconate/lead titanate ratio and by compensating for lead loss during processing by finding the optimal lead excess added to the precursor solutions.

Searching for transition paths in multidimensional space with a fixed repulsive bias potential

An efficient method for searching for transition paths in a multidimensional configuration space is proposed. It is based on using a fixed, locally repulsive bias potential, which forces the system to move from a given initial state to a different final state. This simple method is very effective in determining nearby configurations and possible transition paths for many-particle systems. Once the approximate transition paths are known, the corresponding activation energies can be computed using, e.g., the nudged elastic band method. The usefulness of the present method is demonstrated for both classical and quantum-mechanical systems.

Entanglement generation by the mixing property in a quantum non-linear system

To study the quantum dynamics in non-linear systems with redundant degrees of freedom that are unnecessary to cause classical chaos, we describe the dynamics as the evolution of rigid volume elements in a multi-dimensional configuration space. We show that the expansion and compression of the volume elements are driven by the non-linear potential, and that the coupling with redundant degrees of freedom induces mixing in the configuration space. We reveal that the mixing property continues generating quantum entanglement.