Decoding the chemistry of 2D MXenes for hydrogen generation through machine learning Bokinala Moses Abraham 1 , Priyanka Sinha 2 ,Prosun Halder 2 ,Jayant K Singh 2 1 Departament de Ciència de Materials i Química Física, Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, Spain 2 Department of Chemical Engineering, Indian Institute of Technology Kanpur, India Discovery and optimiation of novel catalysts are emerging as a highly attractive research topics, particularly in the field of sustainable energy. However, developing new catalysts for a target reaction is challenging because of their complicated catalytic process. To this end, we establish a robust and more broadly applicable multistep workflow from the toolbox of supervised machine learning (ML) algorithms for predicting the hydrogen evolution reaction (HER) activity over 4,500 MM′XT 2 -type MXenes, where 25% of the material space (1125 systems) is randomly selected to evaluate the HER performance using density functional theory (DFT) calculations. As the most desirable ML model, the random forest regression method with recursive feature elimination and hyperparameter optimization accurately and rapidly predicts the Gibbs free energy of hydrogen adsorption (ΔGH) with a low predictive mean absolute error of 0.374 eV. Based on these observations, the H-atom adsorbed directly on top of the outermost metal atomic layer of the MM′XT 2 -type MXenes (site-2) with Nb, V, Mo, Cr and Ti metals composed of carbon-based O-functionalization are discovered to be highly stable and active catalysts, surpassing that of commercially available platinum-based counterparts. Overall, the physically meaningful predictions and insights of the developed ML/DFT-based multistep workflow will open new avenues for accelerated screening, rational design, and discovery of potential HER catalysts. References 1. Roger, I., Shipman, M. A. & Symes, M. D. Earthabundant catalysts for electrochemical and photoelectrochemical water splitting. Nat. Rev. Chem. 1,0003 (2017). 2. She, Z. W. et al. Two-Dimensional MolybdenumCarbide (MXene) as an Efficient Electrocatalyst for Hydrogen Evolution. ACS Energy Lett. 1, 589–594(2016). 3. Hui, X., Ge, X., Zhao, R., Li, Z. & Yin, L. InterfaceChemistry on MXene-Based Materials for Enhanced 4. Energy Storage and Conversion Performance. Advanced Functional Materials 30, 2005190 (2020). 5. Lopez, M., Garcia, A. M., Vines, F. & Illas, F. Thermodynamics and Kinetics of Molecular Hydrogen 6. Adsorption and Dissociation on MXenes: Relevanceto Heterogeneously Catalyzed Hydrogenation Reactions. ACS Catal. 11, 12850-12857 (2021). 7. Naguib, M. et al. New Two-Dimensional Niobiumand Vanadium Carbides as Promising Materials for 8. Li-Ion Batteries. ACS Nano 6, 1322–31 (2012).
P199E
Made with FlippingBook Learn more on our blog