REFERENCES
1. Lo, S.; Baird, S. G.; Schrier, J.; et al. Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept. Digit. Discover. 2024, 3, 842-68.
2. Wang, Z.; Qin, M.; Zhang, P.; et al. High throughput characterization method of electrical and phonon properties by dielectric resonant spectroscopy. Mater. Genome. Eng. Adv. 2025, 3, e70010.
3. Xiang, J.; Li, Y.; Zhang, X.; He, Y.; Sun, Q. Local large language model-assisted literature mining for on-surface reactions. Mater. Genome. Eng. Adv. 2025, 3, e88.
4. Li, Y.; Liu, X.; Wang, X.; Xie, W.; Qiu, D.; Yang, J. Effect of material properties on the thermal responses of the carbonization and pyrolysis layers of polymer matrix composites for charring-ablators. J. Mater. Inf. 2025, 5, 31.
5. Wang, W. Y.; Zhang, S.; Li, G.; et al. Artificial intelligence enabled smart design and manufacturing of advanced materials: the endless Frontier in AI+ era. Mater. Genome. Eng. Adv. 2024, 2, e56.
6. Jung, T. A.; Schlittler, R. R.; Gimzewski, J. K. Conformational identification of individual adsorbed molecules with the STM. Nature 1997, 386, 696-8.
7. Meng, T.; Lu, Y.; Lei, P.; et al. Self-assembly of triphenylamine macrocycles and co-assembly with guest molecules at the liquid-solid interface studied by STM: influence of different side chains on host-guest interaction. Langmuir 2022, 38, 3568-74.
8. Wyrick, J.; Wang, X.; Namboodiri, P.; et al. Enhanced atomic precision fabrication by adsorption of phosphine into engineered dangling bonds on H-Si using STM and DFT. ACS. Nano. 2022, 16, 19114-23.
9. Wang, L.; Xia, Y.; Ho, W. Atomic-scale quantum sensing based on the ultrafast coherence of an H2 molecule in an STM cavity. Science 2022, 376, 401-5.
10. Moreno, D.; Parreiras, S. O.; Urgel, J. I.; et al. Engineering periodic dinuclear lanthanide-directed networks featuring tunable energy level alignment and magnetic anisotropy by metal exchange. Small 2022, 18, e2107073.
11. Lyu, C. K.; Gao, Y. F.; Gao, Z. A.; et al. Synthesis of single-layer two-dimensional metal–organic frameworks M3(HAT)2 (M=Ni, Fe, Co, HAT=1,4,5,8,9,12-hexaazatriphenylene) using an on-surface reaction. Angew. Chem. Int. Ed. Engl. 2022, 61, e202204528.
12. Liu, J.; Li, J.; Xu, Z.; et al. On-surface preparation of coordinated lanthanide-transition-metal clusters. Nat. Commun. 2021, 12, 1619.
13. Di Giovannantonio, M.; Fasel, R. On-surface synthesis and atomic scale characterization of unprotected indenofluorene polymers. J. Polym. Sci. 2022, 60, 1814-26.
14. Wang, J.; Niu, K.; Xu, C.; et al. Influence of molecular configurations on the desulfonylation reactions on metal surfaces. J. Am. Chem. Soc. 2022, 144, 21596-605.
15. Kinikar, A.; Di Giovannantonio, M.; Urgel, J. I.; et al. On-surface polyarylene synthesis by cycloaromatization of isopropyl substituents. Nat. Synth. 2022, 1, 289-96.
16. Liu, L.; Klaasen, H.; Witteler, M. C.; et al. Polymerization of silanes through dehydrogenative Si-Si bond formation on metal surfaces. Nature. Chem. 2021, 13, 350-7.
17. Mallada, B.; de la Torre, B.; Mendieta-Moreno, J. I.; et al. On-surface strain-driven synthesis of nonalternant non-benzenoid aromatic compounds containing four- to eight-membered rings. J. Am. Chem. Soc. 2021, 143, 14694-702.
18. Zhu, X.; Liu, Y.; Pu, W.; et al. On-surface synthesis of C144 hexagonal coronoid with zigzag edges. ACS. Nano. 2022, 16, 10600-7.
19. Hellerstedt, J.; Cahlík, A.; Švec, M.; Stetsovych, O.; Hennen, T. Counting molecules: python based scheme for automated enumeration and categorization of molecules in scanning tunneling microscopy images. Softw. Impacts. 2022, 12, 100301.
20. Krull, A.; Hirsch, P.; Rother, C.; Schiffrin, A.; Krull, C. Artificial-intelligence-driven scanning probe microscopy. Commun. Phys. 2020, 3, 54.
21. Milošević, D.; Vodanović, M.; Galić, I.; Subašić, M. Automated estimation of chronological age from panoramic dental X-ray images using deep learning. Expert. Syst. Appl. 2022, 189, 116038.
22. Li, J.; Telychko, M.; Yin, J.; et al. Machine vision automated chiral molecule detection and classification in molecular imaging. J. Am. Chem. Soc. 2021, 143, 10177-88.
23. Gordon, O. M.; Hodgkinson, J. E. A.; Farley, S. M.; Hunsicker, E. L.; Moriarty, P. J. Automated searching and identification of self-organized nanostructures. Nano. Lett. 2020, 20, 7688-93.
24. Kang, J.; Yoo, Y. J.; Park, J. H.; et al. DeepGT: deep learning-based quantification of nanosized bioparticles in bright-field micrographs of gires-tournois biosensor. Nano. Today. 2023, 52, 101968.
25. Faraz, K.; Grenier, T.; Ducottet, C.; Epicier, T. Deep learning detection of nanoparticles and multiple object tracking of their dynamic evolution during in situ ETEM studies. Sci. Rep. 2022, 12, 2484.
26. Newby, J. M.; Schaefer, A. M.; Lee, P. T.; Forest, M. G.; Lai, S. K. Convolutional neural networks automate detection for tracking of submicron-scale particles in 2D and 3D. Proc. Natl. Acad. Sci. U. S. A. 2018, 115, 9026-31.
27. Zhu, Z.; Yuan, S.; Yang, Q.; et al. Autonomous scanning tunneling microscopy imaging via deep learning. J. Am. Chem. Soc. 2024, 146, 29199-206.
28. Seifert, T. J.; Stritzke, M.; Kasten, P.; et al. Chirality detection in scanning tunneling microscopy data using artificial intelligence. Small. Methods. 2024, 8, e2400549.
29. Wang, C. Y.; Yeh, I. H.; Liao, H. Y. M. YOLOv9: learning what you want to learn using programmable gradient information. arXiv 2024, arXiv:2402.13616. Available online: https://doi.org/10.48550/arXiv.2402.13616. (accessed 27 Mar 2026).
30. Gao, T.; Gao, J.; Zhang, J.; Song, B.; Zhang, L. Development of an accurate “composition-process-properties” dataset for SLMed Al-Si-(Mg) alloys and its application in alloy design. J. Mater. Inf. 2023, 3, 6.
31. Zhou, D. W.; Wang, Q. W.; Qi, Z. H.; Ye, H. J.; Zhan, D. C.; Liu, Z. Class-incremental learning: a survey. IEEE. Trans. Pattern. Anal. Mach. Intell. 2024, 46, 9851-73.
32. Pan, S. J.; Yang, Q. A survey on transfer learning. IEEE. Trans. Knowl. Data. Eng. 2010, 22, 1345-59.
33. Otero, R.; Gallego, J. M.; de Parga, A. L.; Martín, N.; Miranda, R. Molecular self-assembly at solid surfaces. Adv. Mater. 2011, 23, 5148-76.





