Rational design of MoS₂-supported Cu single-atom catalysts by machine learning potential for enhanced peroxidase-like activity

Abstract

Two-dimensional molybdenum disulfide (2D-MoS2) supported single atom nanomaterials with enhanced enzyme-like activities bring new insights into the substitution of natural enzymes for huge specific surface area, ease of decoration, high...

2D-MoS2-supported copper peroxide nanodots with enhanced nanozyme activity: application in antibacterial activity

“…They have also performed theoretical calculations which suggest that the copper-loaded MoS 2 can donate more electrons, which further enhances the POD-like activity. 46 In this case the increase in the POD-like activity could be due to the involvement of the Cu 2+ ion in the MoS 2 redox catalytic system. From the XPS analysis, the peaks at 932.5 and 952.5 eV support the presence of copper in the 2+ state in the MoS 2 @CP (Fig.…”

“…MoS 2 -supported Cu single-atom catalysts with sulfur vacancies under acidic conditions supported this finding. 46 However, copper peroxide-decorated MoS 2 nanozymes have not been studied yet. CP-nanodots with a positive charge can contribute to the stabilization of MoS 2 and impart catalytic properties.…”

Machine learning in nanozymes: from design to application

“…Xu et al employed the random surface walk method combined with a neural network (SSW-NN) to simulate the reaction system of nanozymes. 47 They obtained a series of adsorption configurations after the decomposition of H 2 O 2 stabilized on a 2D MoS 2 surface. Utilizing the double end-surface walk (DESW) method for localizing transition states and finding reaction pathways, they identified a critical rate-determining step in the decomposition of H 2 O 2 on the material surface, specifically the homogenization of H 2 O 2 on the material surface.…”

Machine learning facilitating the rational design of nanozymes

“…44 Using the combination of stochastic surface walking (SSW) global optimization with the neural network (NN) method (SSW-NN) invented by Liu's Group in 2017, 45 the stable structures and their transition states of the MoS 2 -supported Cu single-atom nanozyme with sulfur vacancies (Cu@MoS 2 -Vs) with robust POD-like activity were successfully explored. Based on the simulation results, it is also proved that the increase of Cu loading and sulfur vacancies and the decrease of the microenvironment pH value can significantly improve the performance of Cu@MoS 2 -Vs. 46…”

“…For example, SWWS and similar methods can assist researchers in the automatic exploration of nanozymes' optimal structures. 46 GA, an evolving method that finds optimal solutions based on evaluation, is often combined with ML algorithms such as NN to help researchers to find the best-performing materials. 49,72 In addition, through manual labeling and filtering of data points and thus continuous cycle training of the model, the active learning method, which could reduce the dependence on data and enhance ML performance, is also increasingly common.…”