Transfer learning has been highlighted as a promising framework to increase the accuracy of the data-driven model in the case of data sparsity, specifically by leveraging pretrained knowledge to the training of the target model. The objective of this study is to evaluate whether the number of requisite training samples can be reduced with the use of various transfer learning models for predicting, for example, the chemical source terms of the data-driven reduced-order modeling (ROM) that represents the homogeneous ignition of a hydrogen/air mixture. Principal component analysis is applied to reduce the dimensionality of the hydrogen/air mixture in composition space. Artificial neural networks (ANNs) are used to regress the reaction rates of principal components, and subsequently, a system of ordinary differential equations is solved. As the number of training samples decreases in the target task, the ROM fails to predict the ignition evolution of a hydrogen/air mixture. Three transfer learning strategies are then applied to the training of the ANN model with a sparse dataset. The performance of the ROM with a sparse dataset is remarkably enhanced if the training of the ANN model is restricted by a regularization term that controls the degree of knowledge transfer from source to target tasks. To this end, a novel transfer learning method is introduced, Parameter control via Partial Initialization and Regularization (PaPIR), whereby the amount of knowledge transferred is systemically adjusted in terms of the initialization and regularization schemes of the ANN model in the target task.

Phosphorus nitride (PN) is believed to be one of the major reservoirs of phosphorus in the interstellar medium (ISM). For this reason, understanding which reactions produce PN in space and predicting their rate coefficients is important for modelling the relative abundances of P-bearing species and clarifying the role of phosphorus in astrochemistry. In this work, we explore the potential energy surfaces of the $\textrm{P}(^4\textrm{S}) + \textrm{NH}(^3\Sigma^-)$ and $\textrm{N}(^4\textrm{S}) + \textrm{PH}(^3\Sigma^-)$ reactions and the formation of $\textrm{H}(^2\textrm{S}) + \textrm{PN}(^1\Sigma^+)$ through high accuracy ab initio calculations and the variable reaction coordinate transition state theory (VRC-TST). We found that both reactions proceed without an activation barrier and with similar rate coefficients that can be described by a modified Arrhenius equation ($k(T)=\alpha\!\left( T/300 \right)^{\beta} \exp\!{(\!-\!\gamma/T)})$ with $\alpha=0.93\times 10^{-10}\rm cm^3\,s^{-1}$, $\beta=-0.18$ and $\gamma=0.24\, \rm K$ for the $\textrm{P} + \textrm{NH} \longrightarrow \textrm{H} + \textrm{PN}$ reaction and $\alpha=0.88\times 10^{-10}\rm cm^3\,s^{-1}$, $\beta=-0.18$ and $\gamma=1.01\, \rm K$ for the $\textrm{N} + \textrm{PH} \longrightarrow \textrm{H} + \textrm{PN}$ one. Both reactions are expected to be relevant for modelling PN abundances even in the cold environments of the ISM. Given the abundance of hydrogen in space, we have also predicted rate coefficients for the destruction of PN via H + PN collisions.

We numerically study a thermal-diffusive model for smouldering combustion under microgravity with convective heat losses. In accordance with previous experimental observations, it is well known that porous materials burning against a gaseous oxidiser under microgravity exhibit various finger-like char patterns due to the destabilising effect of oxidiser transport. There is a close resemblance between the pattern-forming dynamics observed in the experiments with the mechanism of thermal-diffusive instability, similar to that occurring in low Lewis number premixtures. At large values of the Lewis number, the finger-like pattern coalesces and propagates as a stable front reminiscent of the pattern behaviour at large Péclet numbers in diffusion-limited systems. The significance of the order of the chemical kinetics for the coexistence of both upstream and downstream smoulder waves is also considered.

We have studied dynamic thermo-mechano-chemical responses of reactive metallic systems, both in clouds of small oxygen-free particles (∼1–10 μm in diameter) produced by fracturing Zr-rich bulk metallic glass and in pure Zr metal foils (∼25 μm thin), under thermal (laser ablation or pulse electrical heating) and mechanical loadings. The mechanical fracture/fragmentation and fragments reactions were time resolved using an integrated set of fast six-channel optical pyrometer, high-speed microphotographic camera, and time- and angle-resolved synchrotron x-ray diffraction. These small-scale tabletop real-time experiments performed on or near surfaces of reactive metals provide fundamental data, in atomistic scales or of particle clouds, regarding fragmentation mechanics, combustion mechanisms and kinetics, and dynamics of energy release under thermal and mechanical loadings. We present the results of pure Zr and Zr-rich amorphous metals, not only signifying diversified combustion mechanisms depending on microstructures, particle sizes, oxygen pressure, and ignition conditions but also providing fundamental data that can be used to develop and validate thermochemical and mechanochemical models for reactive materials.

It is shown that the method of deriving bounds on the rate of convergence for birth–death processes developed by Zeifman can be effectively applied to stochastic models of chemical reactions.

Several stochastic models have been proposed to describe the kinetic theory of reversible chemical reactions. However, in macroscopic systems the effects of stochastic variability are often outweighed by mean effects. In the present paper we show that some observed phenomena can be explained quite adequately by a stochastic model in which the stochastic variability is not negligible in comparison with mean effects. Our argument involves approximations to a stochastic model for competing chemical reactions.

In the chemistry of some chain molecules, adjacent monomeric side groups can form dimers. Here a Markov chain model is developed for irreversible formation of dimers. Closed form expressions for the finite time expected numbers of sequences of unreacted monomers of various lengths (number of monomers) are given. The relation between this model and the parking problem is discussed.