Generative adversarial networks (GANs) are deep generative models (GMs) that have
recently attracted attention owing to their impressive performance in generating completely …

The present perspective review focuses on the role of the precursor state, controlling the
dynamical evolution of elementary processes, whose structure and stability are often difficult …

We study the global asymptotic stability problem with respect to the fractional-order
quaternion-valued bidirectional associative memory neural network (FQVBAMNN) models in …

Genetic algorithms (GAs) are stochastic global search methods inspired by biological
evolution. They have been used extensively in chemistry and materials science coupled with …

New algorithms for the optimization of alloy nanoparticles (nanoalloys) are presented. The
new algorithms are based on the concept of multiple basin‐hopping walkers running in …

Prediction of the lowest energy structure for transition metal clusters and related systems is
fundamental in cluster science. Advances in the structure search methods have reduced the …

The Particle Swarm Optimization (PSO) method is a global optimization technique based on
the gradual evolution of a population of solutions called particles. The method evolves the …

We present a generalization of the transition state search using chemical dynamics
simulations (TSSCDS) methodology (discussed in a previous study) which allows the …

Locating the global minimum of a potential energy surface is an arduous task. The
complexity of the potential energy surface increases as the number of degrees of freedom of …

Coronene is one of the basic polycyclic aromatic hydrocarbons (PAHs) used to test the
reliabilty of a multidimensional potential energy surface (PES) and to assess its influence on …