S in Figure and predicted by the microkinetic computational model (described in in our experiments,

S in Figure and predicted by the microkinetic computational model (described in in our experiments, as Azoxymethane web literature, 8. Comparison amongst the NH3 TOF values obtained detail elsewhere [43]). literature, and predicted by the N binding power around the metal terrace sites. TOFs are showcased as a function of themicrokinetic computational model (described in detailWe choose to highlight that catalyst activities are anticipated to differ by various orders of magnitude in thermal catalysis and in plasma catalysis, if they are governed by vibrational The Even so, the outcomes presented right here along with the be largely independent excitations.fact that the NH3 concentrations appear toresults reported in prior from th transition metal showcase muchbe explained by We compiled the results from experimental functions utilized might smaller deviations. the contributions of plasma-ge other experimental performs, together with our surface [43]. compare vibrational excitations o radicals interacting using the metal own data, and Whilst them together with the trends predicted computationally [43], as shown in Figure 8. We plottedas Co and with(that are anticipated to improve the overall performance of catalysts, such the outcomes Ni the 1:3 H2 :N2 ratio from our experiments since it compares ideal together with the data from other a lot more noble than the thermally optimal Ru), they cannot clarify a simil functions which made use of higher N2 contents. In any case, the difference between the results obtained performance in between them in our perform is catalyst, nor the a and Ru with the 3:1, 1:1, and 1:3 H2 :N2 ratiosand the Cu incredibly modest when put onFelogarithmic cataly computational two functions by Wang that radical adsorption reactions could sign scale. Apart from the outcomes recommended et al. [38] and Mehta et al. [42] describing the functionality ofnoble catalysts metals Cu), whilst ER we also added a dataset obtained activate the diverse catalytic (e.g., in DBD reactors, reactions are anticipated to activate by Shah et al. within a low-pressure radiofrequency plasma [63], which interestingly exhibited noble catalysts (e.g., Fe). Hence, below such conditions, the thermally o the exact same properties (i.e., the absence of your “volcano” trend), therefore indirectly suggesting that “volcano” behaviour will be cancelled and stress plasma metals the implications of our model may attain beyond atmospheric the transition circumstances. would similarly. At thenote thattime, the equal aimed merely at with the unique transition We especially very same this comparison is performance highlighting the qualitative trends of TOFs as by homogeneous plasma reactions, reactions at the Thromboxane B2 Cancer reactor w can’t be explained a function of the catalyst material. A quantitative comparison in between observedsupport simply because the beyond the degree of detail that computational activity with the and calculated TOFs is empty reactor along with the reactor filled with pu modelling can give. We acknowledge that a DBD can perform both in a filamentary and uniform regime [28,38]. Having said that, it truly is most frequently filamentary (i.e., consisting of microdischarges and their afterflows). Therefore, the modelling final results in Figure eight are shown for each the microdischarges and their afterglows of a filamentary plasma. For each circumstances, benefits were calculated for a plasma phase containing vibrationally excited N2 and plasma-generated radicals, at the same time as a plasma phase containing only vibrationally excited N2 (denoted “vib. only” inside the legend of Figure 8). The comparison with the experimental trends and the mod.