journal article·2026-02-19Open access

Liquid‐Processed 2D Aromatic Amorphous Carbon: Defect Engineering and Universal Transport Scaling

Fabiola Liscio, Andrea Fondacaro, Gaetana Petrone, Federico Chianese, Jasper Rikkert Plaisier, Sara Fiori, Orlando Castellano, Alice Apponi, Nicolò Galvani, Verónica Montes García, Veronica Valentini, Stefano Iacobucci, Damiano Ricciarelli, Giuseppe Fisicaro, Antonino Lamagna, Giovanni Maria Vinai, Ernesto Placidi, Alessandro Bellucci, Daniele Maria Trucchi, Paolo Samorì, Alessandro Ruocco, Samuel Lara Avila, Andrea Liscio

Abstract

ABSTRACT Liquid‐processed 2D aromatic amorphous carbons are emerging as a new materials platform in which distorted sp 2 networks combine scalability with unconventional electronic transport. Here, we report a deterministic pathway to produce graphene‐derived amorphous 2D carbon thin films by combining the water processability of graphene oxide with rapid thermal quenching. During heating, the stepwise removal of oxygen groups generates vacancies and topological defects; rapid traversal of this regime prevents structural recovery and yields a kinetically trapped quasi‐amorphous phase, termed quenched reduced graphene oxide (qRGO). XPS and UPS confirm that qRGO maintains predominantly sp 2 bonding, indicating a distorted aromatic network rather than a transition to sp 3 ‐rich amorphous carbon. Correlative structural and spectroscopic analyses reveal suppressed long‐range order and boundary‐like defect character in qRGO, contrasting with the vacancy‐type defects of nanocrystalline reduced graphene oxide (RGO). Transport measurements show that RGO retains partial coherence and weak localization, whereas qRGO evolves into a strongly disordered regime governed by variable‐range hopping. Despite these differences, both systems collapse onto a universal power‐law scaling of resistivity. These results demonstrate that thermal‐kinetic control of oxygen‐driven defect formation provides a scalable route to functional 2D amorphous carbon films.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Graphene research and applications · Covalent Organic Framework Applications · Surface Chemistry and Catalysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Consiglio Nazionale delle Ricerche Istituto per lo Studio dei Materiali Nanostrutturati (CNR‐ISMN) ‐ Bologna Unit Bologna Italy

Istituto Officina dei Materiali (IOM) CNR Trieste Italy

Consiglio Nazionale delle Ricerche Istituto per la Microelettronica e Microsistemi (CNR‐IMM) – Roma Unit Roma Italy

Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg Sweden

Elettra ‐Sincrotrone Trieste S.C.p.A. Trieste Italy

Institut Català de Nanociència i Nanotecnologia (ICN2) Barcelona Spain

Dipartimento di Scienze Università degli Studi di Roma Tre Roma Italy

INFN Sezione di Roma Tre Rome Italy

ISIS & icFRC University of Strasbourg & CNRS Strasbourg France

Consiglio Nazionale delle Ricerche (ISM‐CNR) DiaTHEMA Lab Istituto Di Struttura della Materia Roma Italy

Consiglio Nazionale delle Ricerche Istituto di Struttura della Materia (CNR‐ISM) – Roma Tor Vergata Unit Roma Italy

Consiglio Nazionale delle Ricerche Istituto per la Microelettronica e Microsistemi, (CNR‐IMM) Catania Italy

Dipartimento di Fisica Sapienza Università di Roma Roma Italy

References (52)

Show source-provided references
1. 10.1002/smll.20230323810.1002/smll.202303238 ↗
2. 10.1021/acs.nanolett.1c0388310.1021/acs.nanolett.1c03883 ↗
3. 10.1021/acsnano.0c0777110.1021/acsnano.0c07771 ↗
4. 10.1103/PhysRevLett.106.10550510.1103/PhysRevLett.106.105505 ↗
5. 10.1038/s41586‐019‐1871‐210.1038/s41586‐019‐1871‐2 ↗
6. 10.1126/sciadv.160182110.1126/sciadv.1601821 ↗
7. 10.1021/jacs.5c0054810.1021/jacs.5c00548 ↗
8. 10.1038/s41598‐019‐41231‐z10.1038/s41598‐019‐41231‐z ↗
9. 10.1016/j.nanoms.2021.03.00310.1016/j.nanoms.2021.03.003 ↗
10. 10.1088/2053‐1583/ab116910.1088/2053‐1583/ab1169 ↗
11. 10.1063/1.514462610.1063/1.5144626 ↗
12. 10.1016/j.carbon.2021.03.01810.1016/j.carbon.2021.03.018 ↗
13. 10.1016/j.carbon.2026.12124710.1016/j.carbon.2026.121247 ↗
14. 10.1088/2053‐1583/aa57ff10.1088/2053‐1583/aa57ff ↗
15. 10.1021/acs.jpcc.5b0159010.1021/acs.jpcc.5b01590 ↗
16. 10.1039/C3TC31124D10.1039/C3TC31124D ↗
17. 10.1103/PhysRevB.61.1409510.1103/PhysRevB.61.14095 ↗
18. 10.1016/j.carbon.2009.12.05710.1016/j.carbon.2009.12.057 ↗
19. 10.1021/nl300901a10.1021/nl300901a ↗
20. 10.1021/acs.jpcc.7b0623610.1021/acs.jpcc.7b06236 ↗
21. 10.1063/1.219605710.1063/1.2196057 ↗
22. 10.1088/0022‐3719/3/2/01010.1088/0022‐3719/3/2/010 ↗
23. 10.1016/j.apsusc.2020.14560510.1016/j.apsusc.2020.145605 ↗
24. 10.1021/nl500969t10.1021/nl500969t ↗
25. 10.1103/PhysRevB.77.23340610.1103/PhysRevB.77.233406 ↗
26. 10.1186/1556‐276X‐6‐63610.1186/1556‐276X‐6‐636 ↗
27. 10.1038/s41467‐024‐48614‐510.1038/s41467‐024‐48614‐5 ↗
28. 10.1103/PhysRevLett.70.293210.1103/PhysRevLett.70.2932 ↗
29. 10.1088/0953‐2048/29/1/01501510.1088/0953‐2048/29/1/015015 ↗
30. Milligan R. F. · 1985 · 231
31. 10.1080/1364281010820579610.1080/13642810108205796 ↗
32. 10.1007/978-3-662-02403-410.1007/978-3-662-02403-4 ↗
33. 10.1016/j.carbon.2015.03.01910.1016/j.carbon.2015.03.019 ↗
34. 10.1038/s41928‐021‐00684‐910.1038/s41928‐021‐00684‐9 ↗
35. 10.1103/PhysRevB.66.05443810.1103/PhysRevB.66.054438 ↗
36. 10.1016/0022‐3093(79)90033‐410.1016/0022‐3093(79)90033‐4 ↗
37. 10.1016/0022‐3093(83)90424‐610.1016/0022‐3093(83)90424‐6 ↗
38. Mott N. F. · 1979 · 590
39. 10.1080/1364281950823908810.1080/13642819508239088 ↗
40. 10.1002/andp.20210058810.1002/andp.202100588 ↗
41. 10.1103/PhysRevB.27.132610.1103/PhysRevB.27.1326 ↗
42. 10.1080/0001873860010191110.1080/00018738600101911 ↗
43. 10.1021/nl402696q10.1021/nl402696q ↗
44. 10.1103/PhysRevLett.93.18550310.1103/PhysRevLett.93.185503 ↗
45. 10.1080/1478643041000171694410.1080/14786430410001716944 ↗
46. 10.1063/5.000530210.1063/5.0005302 ↗
47. 10.1002/cphc.20120088010.1002/cphc.201200880 ↗
48. 10.1063/1.513121610.1063/1.5131216 ↗
49. 10.1016/j.carbon.2023.11850210.1016/j.carbon.2023.118502 ↗
50. 10.1002/zaac.20140016310.1002/zaac.201400163 ↗
51. I.Batatia D. P.Kovács G. N. C.Simm C.Ortner andG.Csányi “MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields ” inProceedings of the 36th International Conference on Neural Information Processing Systems(Curran Associates Inc. 2022) 830.10.52202/068431-0830 ↗
52. 10.1021/jp501237c10.1021/jp501237c ↗