## 5 Conclusions  
Firstly, we simulated the adsorption and diffusion properties of CO2, N2, and O2 in 6013 CoRE-MOFs using high-throughput MC + MD. Then, we investigated the correlation among adsorption selectivity and diffusion selectivity for CO2 and MOF descriptors by the univariate analysis. The \(Q_{\text{st}}\) and PLD were considered to be the most important for \(S_{\text{ads (CO2/N2+O2)}}\) and \(S_{\text{diff (CO2/N2+O2)}}\), respectively. In conjunction with multivariate analysis, a comparison of 4 ML algorithms revealed that the RF had the best prediction results for adsorption selectivity, with an \(R\) value of 0.982. This indicated that the RF method was the most suitable for the predictions of the capture of low CO2 concentrations in MOF. The relative importance analysis of the RF algorithm quantitatively indicated that the relative importance of the MOF descriptors on adsorption selectivity is \(Q_{\text{st}}>\rho>\text{LCD}>\text{VSA}\geq\phi>\text{PLD}\). It was also confirmed that \(Q_{\text{st}}\) is the most important parameter, while the VSA and \(\phi\) are relatively less important. Through this high-throughput screening, 14 types of MOFs with optimal adsorption selectivity and diffusion selectivity were obtained. After comparison, it was found that their adsorption selectivity was generally higher than their diffusion selectivity. The diffusion separation performance of CO2 is the key property in determining the performance of MOFs on low concentrations of CO2 during \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**No**} & **CSD** & \multirow{2}{*}{**LCD b**} & \multirow{2}{*}{\(\phi\)} & **VSA c** & **PLD d** & \multirow{2}{*}{\(P\)} & **Q\({}_{\text{st,CO2}}\)** & **S\({}_{\text{diffCO2/N2+O2)}}\)** & **S\({}_{\text{adsCO2/(N2+O2)}}\)** \\  & **Code a** & & & & **(m\({}^{2}\)/cm\({}^{3}\))** & **(Å)** & **(kg/m\({}^{3}\))** & **(UJ/mol)** & **S\({}_{\text{diffCO2/(N2+O2)}}\)** & **S\({}_{\text{adsCO2/(N2+O2)}}\)** \\ \hline
1 & REYCEF & 3.75 & 0.08 & 0 & 2.83 & 1646.40 & 26.02 & 8.21 & 6.25 \\
2 & JAHNEM & 3.50 & 0.05 & 0 & 2.66 & 1714.62 & 27.01 & 6.18 & 6.77 \\
3 & HOJLEY & 3.63 & 0.14 & 0 & 2.83 & 1410.99 & 32.65 & 5.00 & 7.45 \\
4 & KASPOL & 4.04 & 0.19 & 16.26 & 2.93 & 1665.95 & 34.05 & 36.55 & 7.68 \\
5 & XUNJOG & 3.25 & 0.07 & 0 & 2.67 & 1737.75 & 26.41 & 5.31 & 11.12 \\
6 & HIQPI & 3.87 & 0.15 & 9.46 & 3.12 & 1472.40 & 35.20 & 55.67 & 11.24 \\
7 & YUBICX & 4.58 & 0.16 & 98.56 & 3.64 & 1786.84 & 30.52 & 5.79 & 11.51 \\
8 & HIQPE & 3.84 & 0.15 & 7.68 & 3.12 & 1440.14 & 35.31 & 62.27 & 12.39 \\
9 & FEJKEM & 3.46 & 0.09 & 0.33 & 3.09 & 2132.02 & 30.00 & 15.01 & 15.72 \\
10 & FALQIU & 5.08 & 0.12 & 82.58 & 3.14 & 1977.64 & 34.40 & 5.38 & 22.97 \\
11 & FALQOA & 6.06 & 0.12 & 83.34 & 3.07 & 2004.41 & 35.03 & 6.76 & 24.10 \\
12 & TONANAX & 3.80 & 0.28 & 4.42 & 2.83 & 1346.52 & 42.65 & 5.02 & 25.15 \\
13 & OFIWIK & 4.20 & 0.05 & 5.99 & 3.14 & 1866.86 & 39.64 & 27.42 & 25.66 \\
14 & NORGOS & 4.95 & 0.13 & 45.40 & 3.43 & 1728.90 & 51.67 & 12.92 & 4712.33 \\ \hline \hline \end{tabular}  
* CSD Code is the code of MOFs in the Cambridge Structure Database; b LCD: largest cavity diameter; c VSA: volumetric surface area; d PLD: pore-limiting diameter.  
\end{table} 
Table 2: Best computation-ready, experimental metal-organic frameworks (CoRE-MOFs). the kinetic adsorption process. This study provides experimental guidance for the determination of MOFs that effectively capture CO\({}_{2}\) from the air, and indicates that advanced ML algorithms can accelerate the research and development of new materials.