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Molecular volcano plots, which facilitate the rapid prediction of the activity and selectivity of prospective catalysts, have emerged as powerful tools for computational catalysis. Here, we integrate microkinetic modeling into the volcano plot framework to ...
In recent years, there has been a surge of interest in predicting computed activation barriers, to enable the acceleration of the automated exploration of reaction networks. Consequently, various predictive approaches have emerged, ranging from graph-based ...
A hybrid photothermal catalytic system, which combines both the photochemical (light) and thermal (heat) activation pathways over a bifunctional catalyst, has demonstrated remarkable levels of reaction activity and selectivity when compared with individual ...
The emergence of mycelium-bonded biocomposites has been stimulated in the quest for sustainable development. These biocomposites exhibit enhanced mechanical properties through hot pressing, with mycelium playing a crucial role as both the adhesive and rein ...
The constant urge to construct new molecules in an economical and sustainable fashion led to the development of numerous metal-catalyzed transformations. Organocatalysts consisting of abundant and more sustainable elements offer an elegant solution to over ...
On-surface synthesis has become a prominent method for growing low-dimensional carbon-based nanomaterials on metal surfaces. However, the necessity of decoupling organic nanostructures from metal substrates to exploit their properties requires either trans ...
This publication summarizes my journey in the field of chemical oxidation processes for water treatment over the last 30+ years. Initially, the efficiency of the application of chemical oxidants for micropollutant abatement was assessed by the abatement of ...
The spatially resolved identification of active sites on the heterogeneous catalyst surface is an essential step toward directly visualizing a catalytic reaction with atomic scale. To date, ferrous centers on platinum group metals have shown promising pote ...
Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...
Metal-porphyrins are studied intensively due their potential applications, deriving from the variety of electronic and chemical properties, tunable by selecting metal centers and functional groups. Metalation, de- and trans-metalation processes are fundame ...
