Exploration of Reaction Pathways and Chemical Transformation Networks

For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and automatedly. These approaches differ in their application range, the level of completeness of the exploration, as well as the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure

Searching for Stable Si\u3csub\u3en\u3c/sub\u3eC\u3csub\u3en\u3c/sub\u3e Clusters: Combination of Stochastic Potential Surface Search and Pseudopotential Plane-Wave Car-Parinello Simulated Annealing Simulations

To find low energy SinCn structures out of hundreds to thousands of isomers we have developed a general method to search for stable isomeric structures that combines Stochastic Potential Surface Search and Pseudopotential Plane-Wave Density Functional Theory Car-Parinello Molecular Dynamics simulated annealing (PSPW-CPMD-SA). We enhanced the Sunders stochastic search method to generate random cluster structures used as seed structures for PSPW-CPMD-SA simulations. This method ensures that each SA simulation samples a different potential surface region to find the regional minimum structure. By iterations of this automated, parallel process on a high performance computer we located hundreds to more than a thousand stable isomers for each SinCn cluster. Among these, five to 10 of the lowest energy isomers were further optimized using B3LYP/cc-pVTZ method. We applied this method to SinCn (n = 4–12) clusters and found the lowest energy structures, most not previously reported. By analyzing the bonding patterns of low energy structures of each SinCn cluster, we observed that carbon segregations tend to form condensed conjugated rings while Si connects to unsaturated bonds at the periphery of the carbon segregation as single atoms or clusters when n is small and when n is large a silicon network spans over the carbon segregation region

Transformation of amorphous carbon clusters to fullerenes

Transformation of amorphous carbon clusters into fullerenes under high temperature is studied using molecular dynamics simulations at microsecond times. Based on the analysis of both structure and energy of the system, it is found that fullerene formation occurs in two stages. Firstly, fast transformation of the initial amorphous structure into a hollow sp$^2$ shell with a few chains attached occurs with a considerable decrease of the potential energy and the number of atoms belonging to chains and to the amorphous domain. Then, insertion of remaining carbon chains into the sp$^2$ network takes place at the same time with the fullerene shell formation. Two types of defects remaining after the formation of the fullerene shell are revealed: 7-membered rings and single one-coordinated atoms. One of the fullerene structures obtained contains no defects at all, which demonstrates that defect-free carbon cages can be occasionally formed from amorphous precursors directly without defect healing. No structural changes are observed after the fullerene formation, suggesting that defect healing is a slow process in comparison with the fullerene shell formation. The schemes of the revealed reactions of chain atoms insertion into the fullerene shell just before its completion are presented. The results of the performed simulations are summarized within the paradigm of fullerene formation due to selforganization of the carbon system.Comment: 35 pages, 9 figure

Dimensional Strategies and the Minimization Problem: Barrier-Avoiding Algorithms

In the present paper we examine the role of dimensionality in the minimization problem. Since it has such a powerful influence on the topology of the associated potential energy landscape, we argue that it may prove useful to alter the dimensionality of the space of the original minimization problem. We explore this general idea in the context of finding the minimum energy geometries of Lennard-Jones clusters. We show that it is possible to locate barrier-free, high-dimensional pathways that connect local, three-dimensional cluster minima. The performance of the resulting, “barrier-avoiding minimization” algorithm is examined for clusters containing as many as 55 atoms

Enhancement of electronic, photophysical and optical properties of 5,5 '-Dibromo-2,2 '-bithiophene molecule: new aspect to molecular design

WOS: 000474358100002The aims of this study were to enhance electronic, photophysical and optical properties of molecular semiconductors. For this purpose, the isomers of the B-doped molecule (5,5'-Dibromo-2,2'-bithiophene) have been investigated by density functional theory (DFT) based on B3LYP/6-311++G** level of theory. The isomers were first calculated using kick algorithm. The most stable isomers of the B-doped molecule are presented depending on the binding energy, fragmentation energy, ionization potential, electron affinity, chemical hardness, refractive index, radial distribution function and HOMO-LUMO energy gap based on DFT. Ultraviolet-visible (UV-vis) spectra have been also researched by time-dependent (TD) DFT calculations. The value of a band gap for isomer with the lowest total energy decreases from 4.20 to 3.47 eV while the maximum peaks of the absorbance and emission increase from 292 to 324 nm and 392 to 440 nm with boron doped into 5,5'-Dibromo-2,2'-bithiophene. Obtained results reveal that the B-doped molecule has more desirable optoelectronic properties than the pure molecule. (C) 2019 Association of Polish Electrical Engineers (SEP). Published by Elsevier B.V. All right

Charge transfer embedded-atom potentials for atomistic simulations of amino acids and proteins

The dynamical simulation of biophysical systems requires force fields (interaction potentials) capable of describing bond formation and breaking and reactive charge transfer. Molecular motor proteins such as kinesin, dynein and myosin have the extraordinary ability of converting chemical energy to mechanical energy by the process of ATP hydrolysis used for motility. This work is motivated by the reactive force field developed recently by Valone and Atlas[1—4], the charge-transfer embedded atom method (CT-EAM). CT-EAM is based on the empirical embedded-atom method (EAM) pioneered by Daw and Baskes[5]. CT-EAM extends the EAM to re- active molecular systems, through a formal basis in density functional theory. Here we report results on the development of a database for reparameterizing the earlier CT-EAM water potential developed by Muralidharan et al.[6], and for developing a new CT-EAM potential for the amino acids that are the building blocks of all proteins. The reparametization will involve using this extensive ab initio conformational fitting database for six amino acids: glycine, alanine, cysteine, serine, proline, and lysine. These amino acids were chosen to represent canonical subclasses (polar, charged, hydrophobic, ring) of the 20 naturally-occurring amino acids, thereby incorporating varying degrees of charge transfer and solvent interactions. The conformers for each amino acid, identified using a stochastic search method adapted from the work of Saunders[7], further sample distinct structural and bonding patterns. The full database includes information on the energetics of transition states linking selected amino acid conformers, an extensive survey of local minima for each amino acid, dipole moments for each conformer and includes several hitherto uncharacterized structures including novel unsolvated zwitterionic-like structures. All electronic structure calculations were performed at a high level of theory (electron correlation and high quality basis set, MP2/6-311++G**), in order to distinguish correctly between nearly-isoenergetic conformers. The resulting CT-EAM potential fitted to this database will be assessed by comparison with ab initio results for solvated amino acids and dipeptides

Exploration of Free Energy Surface and Thermal Effects on Relative Population and Infrared Spectrum of the Be6B11− Fluxional Cluster

The starting point to understanding cluster properties is the putative global minimum and all the nearby local energy minima; however, locating them is computationally expensive and difficult. The relative populations and spectroscopic properties that are a function of temperature can be approximately computed by employing statistical thermodynamics. Here, we investigate entropy-driven isomers distribution on Be6B11− clusters and the effect of temperature on their infrared spectroscopy and relative populations. We identify the vibration modes possessed by the cluster that significantly contribute to the zero-point energy. A couple of steps are considered for computing the temperature-dependent relative population: First, using a genetic algorithm coupled to density functional theory, we performed an extensive and systematic exploration of the potential/free energy surface of Be6B11− clusters to locate the putative global minimum and elucidate the low-energy structures. Second, the relative populations’ temperature effects are determined by considering the thermodynamic properties and Boltzmann factors. The temperature-dependent relative populations show that the entropies and temperature are essential for determining the global minimum. We compute the temperature-dependent total infrared spectra employing the Boltzmann factor weighted sums of each isomer’s infrared spectrum and find that at finite temperature, the total infrared spectrum is composed of an admixture of infrared spectra that corresponds to the lowest energy structure and its isomers located at high energies. The methodology and results describe the thermal effects in the relative population and the infrared spectra