This review provides exhaustive insights into material and process design of adsorption-based direct air capture in the past five years.

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A new splitting method designed for the numerical solutions of stochastic delay Hopfield neural networks is introduced and analysed. Under Lipschitz and linear growth conditions, this split-step -Milstein method is proved to have a strong convergence of order 1 in mean-square sense, which is higher than that of existing split-step -method. Further, mean-square stability of the proposed method is investigated. Numerical experiments and comparisons with existing methods illustrate the computational efficiency of our method.