Enhanced CO2 Reduction on a Cu-Decorated Single-Atom Catalyst via an Inverse Sandwich M-Graphene-Cu Structure.

The highly active and selective electrochemical CO2 reduction reaction (CO2RR) can be exploited to produce valuable chemicals and fuels and is also crucial for achieving clean energy goals and environmental remediation. Decorated single-atom catalysts (D-SACs), which feature synergistic interactions between the active metal site (M) and an axially decorated ligand, have been extensively explored for the CO2RR. Very recently, novel double-atom catalysts (DACs) featuring inverse sandwich structures were theoretically proposed and identified as promising CO2RR electrocatalysts. However, the experimental synthesis of DACs remains a challenge. To facilitate the fabrication and to realize the potential of these novel DACs, we designed a D-SAC system, denoted as M1@gra+Cuslab. This system features a graphene layer with a vacancy-anchored SAC, all stacked on a Cu(111) surface, thereby embodying a Cu slab-supported inverse sandwich M-graphene-Cu structure. Using density functional theory calculations, we evaluated the stability, selectivity, and activity of 27 M1@gra+Cuslab systems (M = Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Y, Zr, Nb, Mo, Ru, Rh, Pd, Ag, Cd, Hf, Ta, W, Re, Os, Ir, Pt, or Au) and showed five M1@gra+Cuslab (M = Co, Ni, Cu, Rh, or Pd) systems exhibit optimal characteristics for the CO2RR and can potentially outperform their SAC and DAC counterparts. This study offers a new strategy for developing highly efficient CO2RR D-SACs with an inverse sandwich structural moiety.

Mental health conditions of Chinese international students and associated predictors amidst the pandemic.

The current study aims to examine the mental health conditions and the associated predictors among Chinese international students. A sample of 256 Chinese international students aged 16 or above living primarily in Canada were asked to complete an online survey. Mental health conditions were assessed with the Depression, Anxiety, and Stress Scale-21 and the Physical and Mental Health Summary Scales. 15.3%, 20.4%, and 10.5% of respondents reported severe to extremely severe depression, anxiety, and stress levels, respectively. Univariate analysis of variance models and multiple linear regression models identified education and financial status as significant sociodemographic predictors while controlling for the effect of physical health status. Higher financial status and lower level of education were associated with better mental health conditions. These findings shed light on our understanding of mental health conditions and the risk factors among Chinese international students during the COVID-19 pandemic.

Non-Pathological Psychological Distress among Mainland Chinese in Canada and Its Sociodemographic Risk Factors amidst the Pandemic.

The COVID-19 pandemic has exacerbated health inequalities, with a potentially heightened mental health risk for Mainland Chinese in Canada, given the rising anti-Chinese discrimination, and barriers in assessing health services. In this context, this study aimed to assess non-pathological psychological distress towards COVID-19 and identify its sociodemographic risk factors among Mainland Chinese in Canada at the early stages of the pandemic. METHODS: A sample of 731 Mainland Chinese aged 16 or older completed an on-line survey to examine their attitudes, behavioural, and psychological responses towards COVID-19. Non-pathological psychological distress was assessed with a 7-item self-report scale to capture common emotional reactions towards COVID-19. RESULTS: A factor analysis revealed a single-factor structure of the 7-item COVID-19 psychological distress scale (Eigen λ = 3.79). A composite psychological distress index (PDI) score was calculated from these items and used as the outcome variable. Multivariate regression models identified age, financial satisfaction, health status, and perceived/experienced discrimination as significant predictors of psychological distress (ps ≤ 0.05). CONCLUSIONS: Mainland Chinese in Canada who were over 25, in poor financial/health status, or with perceived/experienced discrimination were at a higher risk for COVID-19-related psychological distress. The health inequity across these factors would inform the services to mitigate mental health risk in minority groups.

Lithium stabilizes square-two-dimensional metal sheets: a computational exploration.

Based on the M4-square-containing M4Li2 (M = Al, Ga, In, Tl, Ge, Sn, Pb, Sb, Bi, Cu, Ag, Au, and Hg) clusters, we computationally designed two-dimensional (2D) M2Li sheets consisting of M4-square motifs. The four M2Li-I (M = Sb, Bi, Ag, and Au) monolayers with Li square sublayer sandwiched between two M square sublayers (P4/mmm space group) were confirmed to be stable (high cohesive energies, positive vibrational frequencies, moderate Young's moduli, and structural integrity during first-principles molecular dynamics simulations at 500 K), and the particle swarm optimization (PSO) method identified these constructed monolayers as the global minima in the 2D space. The three M2Li-I (M = Sb, Bi, and Ag) monolayers demonstrated a half-auxetic behavior. Ag2Li-I could well activate CO2 and convert it into HCOOH by following the path * → *CO2 → *OCHO → *HCOOH → *+HCOOH. Particularly, Ag2Li-I shows great promise as an electrocatalyst for CO2 reduction as its limiting potential is as low as 0.40 (0.27) V without (with) considering the solvent effect. Our theoretical explorations reveal that lithium can stabilize the square metal monolayers, and the stable square binary metal sheets exhibit diverse mechanical and electrochemical properties, which can be used in the fields of mechanics and electrochemical catalysis.

Metal dimers embedded vertically in defect-graphene as gas sensors: a first-principles study.

A highly symmetric structure of metal dimers embedded in defect-graphene (M2⊥gra) in a perpendicular manner was designed. Five M2⊥gra (M = Co, Ni, Rh, Ir and Pt) monolayers were identified to be stable by density functional theory (DFT) calculations. To investigate the capability of those new structures as gas sensors, the adsorption behavior of ten gas molecules (O2, N2, CO, CO2, NO, NO2, NH3, H2O, H2S and SO2) on M2⊥gra was explored, and the charge transfer, magnetism changes, etc. of these adsorption systems were analyzed. The Ni2⊥gra can be used as a gas sensor for O2 at 500 K by the analysis of electronic and magnetic properties. At room temperature, the Pt2⊥gra is expected to be an excellent CO2 gas selector due to its high selectivity, sensitivity and short recovery time (1.04 × 10-12 s). The electronic and magnetic coupling between the metal atoms in the vertical metal dimers plays an important role in sensing gas molecules. Our work paves a new way to design metal-dimer-based nanomaterials.

Computational investigation of two-dimensional borides with planar octacoordinated main group elements.

In this communication, by means of first principles calculations, we searched stable two-dimensional borides with octacoordinated main group elements, and we found that only AlB4 monolayer is stable in the planar octacoordinate motif through our stability screenings, which can be used for electrocatalyzing the hydrogen evolution reaction.

Sociodemographic and COVID-Related Predictors for Mental Health Condition of Mainland Chinese in Canada Amidst the Pandemic.

The current study investigates the mental health condition of Mainland Chinese in Canada and identifies the associated sociodemographic and COVID-19-related predictors. A sample of 471 Mainland Chinese aged 18 or older completed an online survey that collected information on demographics, experience, cognition, and behaviours related to the COVID-19 pandemic and mental health condition. Mental health condition was assessed with the Depression, Anxiety, and Stress Scale-21 (DASS-21) for the depression, anxiety, and stress levels of Mainland Chinese during the pandemic. Moderate to severe depression, anxiety, and stress levels were respectively reported by 11.30%, 10.83%, and 5.10% of respondents. Univariate analysis of variance models (ANOVAs) were conducted to assess mental health condition variance as stratified by independent sociodemographic- or COVID-19-related explanatory variables, to identify possible predictors to be entered into the subsequent regression models. The regression models identified age, income level, health status, and perceived discrimination as significant sociodemographic predictors (absolute value of ßs = 1.19-7.11, ps < 0.05), whereas self-infection worry, attitude towards Canadian measures, information confusion, food/goods stocking, and room cleaning/sanitizing were identified as significant COVID-19-reltaed predictors (absolute value of ßs = 1.33-3.45, ps < 0.05) for mental health outcomes. The results shed light on our understanding of the major factors associated with the mental health condition of Mainland Chinese in Canada during the COVID-19 pandemic.