Understanding How Atomic Sulfur Controls the Selectivity of the Electroreduction of CO₂ to Formic Acid on Metallic Cu Surfaces

Electrochemical conversion of CO2 with renewable energy has recently gained increasing attention for its potential to offset its dramatic exponential increase. Sulfur (S)-modified Cu electrodes were reported to selectively reduce CO2 into formic acid and fully quench the original CO production on clean Cu surfaces, yet the actual mechanism is still unsolved. To further understand this critical issue, herein, an integrated structure–selectivity investigation on the role of sulfur upon CO2 electroreduction was carried out. DFT calculations in combination with relevant experimental observations from the literature were utilized to identify the existing forms of sulfur and their impact of the reaction selectivity of CO2 to HCOOH under realistic conditions. Interestingly, most residual sulfur atoms were found to exist in relatively unstable forms during the reaction, which plays a dominant role in altering the reaction pathway by enhancing CO adsorption. In turn, these strongly adsorbed CO stabilize the unstable sulfur, and a synergetic effect between CO and S is proposed. These findings unravel a groundbreaking comprehensive understanding for the rational development of highly selective CO2 reduction electrocatalysts

Age distribution of population in Yangzhou City.

Human-to-human contact plays a leading role in the transmission of infectious diseases, and the contact pattern between individuals has an important influence on the intensity and trend of disease transmission. In this paper, we define regular contacts and random contacts. Then, taking the COVID-19 outbreak in Yangzhou City, China as an example, we consider age heterogeneity, household structure and two contact patterns to establish discrete dynamic models with switching between daytime and nighttime to depict the transmission mechanism of COVID-19 in population. We studied the changes in the reproduction number with different age groups and household sizes at different stages. The effects of the proportion of two contacts patterns on reproduction number were also studied. Furthermore, taking the final size, the peak value of infected individuals in community and the peak value of quarantine infected individuals and nucleic acid test positive individuals as indicators, we evaluate the impact of the number of random contacts, the duration of the free transmission stage and summer vacation on the spread of the disease. The results show that a series of prevention and control measures taken by the Chinese government in response to the epidemic situation are reasonable and effective, and the young and middle-aged adults (aged 18-59) with household size of 6 have the strongest transmission ability. In addition, the results also indicate that increasing the proportion of random contact is beneficial to the control of the infectious disease in the phase with interventions. This work enriches the content of infectious disease modeling and provides theoretical guidance for the prevention and control of follow-up major infectious diseases.</div

Distribution of the number of regular contacts in the workplace.

Distribution of the number of regular contacts in the workplace.</p

Fig 7 -

(A) The number of daily new test positive cases and cumulative test positive cases for all age groups. (B) The number of daily new test positive cases for age group-ai, i = 2, 3, 4.</p

The flowchart of COVID-19 transmission with intervention measures.

The flowchart of COVID-19 transmission with intervention measures.</p

(A) The proportion of cumulative infected cases of all age groups. (B) The number of infected individuals in society.

The initial values are set as Table 2 and parameter values are set as Table 3. The red line corresponds to the absence of any NPIs. The green line indicates that the NPIs implemented are the same as those in stage 2 (weak NPIs). The green line indicates the actual implementation of NPIs (strong NPIs).</p

The proportion of cumulative test positive cases with household size <i>k</i> in the population with the same household size, i.e. .

The initial values are set as Table 2 and parameter values are set as Table 3.</p

The influence of summer vacation on the spread of COVID-19.

Initial values are set as Table 2 and parameters are set as Table 3. and the horizontal axis represents the number of regular contacts between students among age group-a2 at school during daytime.</p

Effects of the proportion of random contacts on the basic reproduction number and control reproduction number.

Effects of the proportion of random contacts on the basic reproduction number and control reproduction number.</p