REFERENCES

1. Liu, Z.; Liu, Y.; Zhang, Y.; et al. Universal catalyst design framework for electrochemical hydrogen peroxide synthesis facilitated by local atomic environment descriptors. Angew. Chem. Int. Ed. 2025, 65, e18027.

2. Cai, S.; Lai, C.; Li, L.; Sun, H.; Ma, M. Toward dual-electrode full-cell production: a review on electrosynthesis of H2O2 via 2e- ORR and 2e- WOR. Adv. Sustain. Syst. 2026, 10, e01632.

3. Shi, X.; Siahrostami, S.; Li, G.; et al. Understanding activity trends in electrochemical water oxidation to form hydrogen peroxide. Nat. Commun. 2017, 8, 701.

4. Baek, J.; Jin, Q.; Johnson, N. S.; et al. Discovery of LaAlO3 as an efficient catalyst for two-electron water electrolysis towards hydrogen peroxide. Nat. Commun. 2022, 13, 7256.

5. Zhang, D.; Bao, Z.; Chu, Y.; et al. Digital Catalysis Platform (DigCat): a gateway to big data and AI-powered innovations in catalysis. ChemRxiv 2024. Available online: https://doi.org/10.26434/chemrxiv-2024-9lpb9 (accessed 26 May 2026).

6. Zhang, D.; Wang, Z.; Liu, F.; et al. Unraveling the pH-dependent oxygen reduction performance on single-atom catalysts: from single- to dual-sabatier optima. J. Am. Chem. Soc. 2024, 146, 3210-9.

7. Dickens, C. F.; Kirk, C.; Nørskov, J. K. Insights into the electrochemical oxygen evolution reaction with ab initio calculations and microkinetic modeling: beyond the limiting potential volcano. J. Phys. Chem. C. 2019, 123, 18960-77.

8. Li, H. AI Agent - defining the next era of intelligent agents. AI. Agent. 2025, 1, 1.

9. Seifrid, M.; Pollice, R.; Aguilar-granda, A.; et al. Autonomous chemical experiments: challenges and perspectives on establishing a self-driving lab. Acc. Chem. Res. 2022, 55, 2454-66.

10. Chowdhury, P. R.; Medhi, H.; Bhattacharyya, K. G.; Hussain, C. M. Revolutionizing layered double hydroxides for adsorption, catalysis and energy storage through artificial intelligence and machine learning: a critical review. Coord. Chem. Rev. 2026, 560, 217886.