Deep reinforcement learning was employed to optimize chemical reactions. Our model iteratively records the results of a chemical reaction and chooses new experimental conditions to improve the reaction outcome. This model outperformed a state-of-the-art blackbox optimization algorithm by using 71% fewer steps on both simulations and real reactions. Furthermore, we introduced an efficient explor...

We study the effect of the variation of reaction efficiency in binary reactions. We use the well-known A + B → 0 model, which has been extensively studied in the past. We perform simulations on this model where we vary the efficiency of reaction, i.e., when two particles meet they do not instantly react, as has been assumed in previous studies, but they react with a probability γ, where γ is in...

In this study we explore the strategies that undergraduate and graduate chemistry students use when engaged in classification tasks involving symbolic and microscopic (particulate) representations of different chemical reactions. We were specifically interested in characterizing the basic features to which students pay attention when classifying chemical reactions at the symbolic and microscopi...

In this thesis, density functional theory (DFT) is used to investigate the mechanisms and reactivities of electrophilic and nucleophilic aromatic substitution reactions (SEAr and SNAr respectively). For SEAr, the σ-complex intermediate is preceded by one (halogenation) or two (nitration) π-complex intermediates. Whereas the rate-determining transition state (TS) for nitration resembles the seco...

In various biochemical systems, discrete and stochastic approaches are more appropriate than continuous and deterministic approaches when the system has small numbers of molecules. Before the emergence of the stochastic simulation algorithm (SSA) by Gillespie, chemical master equations were used to stochastically model. Solving the master equations is often mathematically intractable. Therefore...

Systems biology uses large networks of biochemical reactions to model the functioning of biological cells from the molecular to the cellular scale. The dynamics of dissipative reaction networks with many well separated time scales can be described as a sequence of successive equilibrations of different subsets of variables of the system. Polynomial systems with separation are equilibrated when ...

For many years, researchers have been developing theoretical methods of estimating reaction rates and energetics when experimental measurements are not available. Recent advances have led to composite energy methods with near chemical accuracy. The performance of these new methods for predicting activation energies and rate constants have not been evaluated for large hydrocarbon cracking reacti...

The chemical reactions are very complex, and include oscillation, condensation, catalyst and self-organization, etc. In these case changes of entropy may increase or decrease. The second law of thermodynamics is based on an isolated system and statistical independence. If fluctuations magnified due to internal interactions exist in the system, entropy will decrease possibly. In chemical reactio...

INTRODUCTION Three major areas of work present themselves to a chemist who is concerned with polymer materials namely: synthesis and degradation of polymers; structure analysis of natural and synthetic polymers; and chemical transformations of polymers. Although these three fields are very closely related,. I wish to concern myself only with the last of them. Reactions with natural or synthetic...

We study the limit of high activation energy of a special Fokker–Planck equation known as the Kramers–Smoluchowski equation (KS). This equation governs the time evolution of the probability density of a particle performing a Brownian motion under the influence of a chemical potential H/ε. We choose H having two wells corresponding to two chemical states A and B. We prove that after a suitable r...