Single-molecule junctions sensitive to binary solvent mixtures
Source abstract
Abstract
We propose a quantum-mechanical model to calculate the nonlinear differential conductance of a single molecular junction immersed in a solvent, either in pure form or as a binary mixture with varying volume fraction. The solvent mixture is captured by a dielectric continuum model for which the resulting spectral density is determined within the Gladstone-Dale approach. The conductance of the molecular junction is calculated by a real-time diagrammatic technique. We find a strong variation of the conductance maximum for varying volume fraction of the solvent mixture. Importantly, the calculated molecular nonlinear conductance shows a very good agreement with experimentally measured data for common molecular junctions in various polar solvent mixtures.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Molecular Junctions and Nanostructures · Nanowire Synthesis and Applications · Quantum and electron transport phenomena
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (38)
Show source-provided references
1. 10.1103/RevModPhys.92.03500110.1103/RevModPhys.92.035001 ↗
2. 10.1016/0009-2614(74)85031-110.1016/0009-2614(74)85031-1 ↗
3. 10.1016/S1369-7021(02)05227-610.1016/S1369-7021(02)05227-6 ↗
4. L. Wang · 2019
5. 10.1038/3502403110.1038/35024031 ↗
6. 10.1002/anie.20130839810.1002/anie.201308398 ↗
7. 10.1021/acs.jpcc.8b1216310.1021/acs.jpcc.8b12163 ↗
8. 10.1088/0953-8984/28/18/18300210.1088/0953-8984/28/18/183002 ↗
9. 10.1038/nnano.2014.20910.1038/nnano.2014.209 ↗
10. 10.1039/C4CS00231H10.1039/C4CS00231H ↗
11. 10.1016/j.scib.2020.03.01210.1016/j.scib.2020.03.012 ↗
12. 10.1021/ja073096710.1021/ja0730967 ↗
13. 10.1021/cr068073+10.1021/cr068073+ ↗
14. A. Nitzan · 200610.1093/oso/9780198529798.001.0001 ↗
15. V. May · 201110.1002/9783527633791 ↗
16. 10.1021/ja01299a05010.1021/ja01299a050 ↗
17. 10.1088/0953-8984/17/10/02810.1088/0953-8984/17/10/028 ↗
18. 10.1021/jp049236610.1021/jp0492366 ↗
19. 10.1016/j.commatsci.2006.09.01010.1016/j.commatsci.2006.09.010 ↗
20. 10.1016/j.comptc.2012.06.02510.1016/j.comptc.2012.06.025 ↗
21. 10.1038/ncomms1023310.1038/ncomms10233 ↗
22. 10.3762/bjnano.6.15910.3762/bjnano.6.159 ↗
23. 10.1098/rstl.1863.001410.1098/rstl.1863.0014 ↗
24. 10.1039/D0CP02994G10.1039/D0CP02994G ↗
25. 10.1103/PhysRevLett.76.171510.1103/PhysRevLett.76.1715 ↗
26. 10.1103/PhysRevB.54.1682010.1103/PhysRevB.54.16820 ↗
27. 10.1021/jp970731u10.1021/jp970731u ↗
28. 10.1021/je00058a00110.1021/je00058a001 ↗
29. C. Reichardt · 2011
30. 10.1103/PhysRevB.68.20532410.1103/PhysRevB.68.205324 ↗
31. 10.1021/ar500393910.1021/ar5003939 ↗
32. H. Kirchberg · J. Chem. Phys. · 2018 · 148 · 16430110.1063/1.5019876 ↗
33. 10.1063/5.003932810.1063/5.0039328 ↗
34. 10.1139/v68-14610.1139/v68-146 ↗
35. S. Vaish · Indian J. Pure Appl. Math. · 1999 · 37 · 881
36. 10.1016/S0167-7322(99)00102-610.1016/S0167-7322(99)00102-6 ↗
37. 10.1007/BF0097304510.1007/BF00973045 ↗
38. G. D. Mahan · 2013