DataVXnpj Computational MaterialsPaper
journal article·2021-05-20Open access

Applications of quantum computing for investigations of electronic transitions in phenylsulfonyl-carbazole TADF emitters

Qi Gao, Gavin O. Jones, Mario Motta, Michihiko Sugawara, Hiroshi C. Watanabe, Takao Kobayashi, Eriko Watanabe, Yu-ya Ohnishi, Hajime Nakamura, Naoki Yamamoto

npj Computational Materials· Volume 7· Issue 1
Publisher pageOpen full text
Source abstract

Abstract

Abstract A quantum chemistry study of the first singlet (S1) and triplet (T1) excited states of phenylsulfonyl-carbazole compounds, proposed as useful thermally activated delayed fluorescence (TADF) emitters for organic light emitting diode (OLED) applications, was performed with the quantum Equation-Of-Motion Variational Quantum Eigensolver (qEOM-VQE) and Variational Quantum Deflation (VQD) algorithms on quantum simulators and devices. These quantum simulations were performed with double zeta quality basis sets on an active space comprising the highest occupied and lowest unoccupied molecular orbitals (HOMO, LUMO) of the TADF molecules. The differences in energy separations between S1 and T1 (ΔEST) predicted by calculations on quantum simulators were found to be in excellent agreement with experimental data. Differences of 17 and 88 mHa with respect to exact energies were found for excited states by using the qEOM-VQE and VQD algorithms, respectively, to perform simulations on quantum devices without error mitigation. By utilizing state tomography to purify the quantum states and correct energy values, the large errors found for unmitigated results could be improved to differences of, at most, 4 mHa with respect to exact values. Consequently, excellent agreement could be found between values of ΔEST predicted by quantum simulations and those found in experiments.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Quantum Information and Cryptography · Quantum Computing Algorithms and Architecture · Optical Network Technologies

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

References (42)

Show source-provided references
1. Kühn, M., Zanker, S., Deglmann, P., Marthaler, M. & Weiß, H. Accuracy and resource estimations for quantum chemistry on a near-term quantum computer. J. Chem. Theory Comput. 15, 4764–4780 (2019).10.1021/acs.jctc.9b00236 ↗
2. Abrams, D. S. & Lloyd, S. Quantum algorithm providing exponential speed increase for finding eigenvalues and eigenvectors. Phys. Rev. Lett. 83, 5162 (1999).10.1103/PhysRevLett.83.5162 ↗
3. Aspuru-Guzik, A., Dutoi, A. D., Love, P. J. & Head-Gordon, M. Simulated quantum computation of molecular energies. Science 309, 1704–1707 (2005).10.1126/science.1113479 ↗
4. Peruzzo, A. et al. A variational eigenvalue solver on a photonic quantum processor. Nat. Commun. 5, 1–7 (2014).10.1038/ncomms5213 ↗
5. Kandala, A. et al. Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets. Nature 549, 242–246 (2017).10.1038/nature23879 ↗
6. Gao, Q. et al. Computational investigations of the lithium superoxide dimer rearrangement on noisy quantum devices. J. Phys. Chem. A 125, 1827–1836 (2021).10.1021/acs.jpca.0c09530 ↗
7. Ollitrault, P. J. et al. Quantum equation of motion for computing molecular excitation energies on a noisy quantum processor. Phys. Rev. Res. 2, 043140 (2020).10.1103/PhysRevResearch.2.043140 ↗
8. Higgott, O., Wang, D. & Brierley, S. Variational quantum computation of excited states. Quantum 3, 156 (2019).10.22331/q-2019-07-01-156 ↗
9. Uoyama, H., Goushi, K., Shizu, K., Nomura, H. & Adachi, C. Highly efficient organic light-emitting diodes from delayed fluorescence. Nature 492, 234–238 (2012).10.1038/nature11687 ↗
10. Zhang, Q. et al. Design of efficient thermally activated delayed fluorescence materials for pure blue organic light emitting diodes. J. Am. Chem. Soc. 134, 14706–14709 (2012).10.1021/ja306538w ↗
11. Lee, S. Y., Yasuda, T., Yang, Y. S., Zhang, Q. & Adachi, C. Luminous butterflies: efficient exciton harvesting by benzophenone derivatives for full-color delayed fluorescence OLEDs. Angew. Chem. Int. 53, 6402–6406 (2014).10.1002/anie.201402992 ↗
12. Zhang, Q. et al. Efficient blue organic light-emitting diodes employing thermally activated delayed fluorescence. Nat. Photonics 8, 326–332 (2014).10.1038/nphoton.2014.12 ↗
13. Wong, M. Y. & Zysman-Colman, E. Purely organic thermally activated delayed fluorescence materials for organic light-emitting diodes. Adv. Mater. 29, 1605444 (2017).10.1002/adma.201605444 ↗
14. Liu, Y., Li, C., Ren, Z., Yan, S. & Bryce, M. R. All-organic thermally activated delayed fluorescence materials for organic light-emitting diodes. Nat. Rev. Mater. 3, 1–20 (2018).10.1038/natrevmats.2018.20 ↗
15. Olivier, Y., Moral, M., Muccioli, L. & Sancho-García, J.-C. Dynamic nature of excited states of donor–acceptor TADF materials for OLEDs: how theory can reveal structure–property relationships. J. Mater. Chem. C 5, 5718–5729 (2017).10.1039/C6TC05075A ↗
16. de Silva, P., Kim, C. A., Zhu, T. & Van Voorhis, T. Extracting design principles for efficient thermally activated delayed fluorescence (TADF) from a simple four-state model. Chem. Mater. 31, 6995–7006 (2019).10.1021/acs.chemmater.9b01601 ↗
17. Hait, D., Zhu, T., McMahon, D. P. & Van Voorhis, T. Prediction of excited-state energies and singlet–triplet gaps of charge-transfer states using a restricted open-shell Kohn–Sham approach. J. Chem. Theory Comput. 12, 3353–3359 (2016).10.1021/acs.jctc.6b00426 ↗
18. Shao, S. et al. Blue thermally activated delayed fluorescence polymers with nonconjugated backbone and through-space charge transfer effect. J. Am. Chem. Soc. 139, 17739–17742 (2017).10.1021/jacs.7b10257 ↗
19. Sanz-Rodrigo, J., Olivier, Y. & Sancho-García, J.-C. Computational studies of molecular materials for unconventional energy conversion: the challenge of light emission by thermally activated delayed fluorescence. Molecules 25, 1006 (2020).10.3390/molecules25041006 ↗
20. Oki, K. O. et al. Composition for forming OLED element, and OLED element. Patent WO/2019/009307 (2019).
21. Endo, A. et al. Efficient up-conversion of triplet excitons into a singlet state and its application for organic light emitting diodes. Appl. Phys. Lett. 98, 42 (2011).10.1063/1.3558906 ↗
22. Nakanishi, K. M., Mitarai, K. & Fujii, K. Subspace-search variational quantum eigensolver for excited states. Phys. Rev. Res. 1, 033062 (2019).10.1103/PhysRevResearch.1.033062 ↗
23. Parrish, R. M., Hohenstein, E. G., McMahon, P. L. & Martínez, T. J. Quantum computation of electronic transitions using a variational quantum eigensolver. Phys. Rev. Lett. 122, 230401 (2019).10.1103/PhysRevLett.122.230401 ↗
24. McWeeny, R. Some recent advances in density matrix theory. Rev. Mod. Phys. 32, 335 (1960).10.1103/RevModPhys.32.335 ↗
25. Lloyd, S., Mohseni, M. & Rebentrost, P. Quantum principal component analysis. Nat. Phys. 10, 631–633 (2014).10.1038/nphys3029 ↗
26. LaRose, R., Tikku, A., O’Neel-Judy, É., Cincio, L. & Coles, P. J. Variational quantum state diagonalization. npj Quantum Inf. 5, 1–10 (2019).10.1038/s41534-019-0167-6 ↗
27. Koch, H. & Jørgensen, P. Coupled cluster response functions. J. Chem. Phys. 93, 3333–3344 (1990).10.1063/1.458814 ↗
28. Bravyi, S., Sheldon, S., Kandala, A., Mckay, D. C. & Gambetta, J. M. Mitigating measurement errors in multi-qubit experiments. Phys. Rev. A 103, 042605 (2021).10.1103/PhysRevA.103.042605 ↗
29. Huang, H.-Y., Kueng, R. & Preskill, J. Predicting many properties of a quantum system from very few measurements. Nat. Phys. 16, 1050–1057 (2020).10.1038/s41567-020-0932-7 ↗
30. Smart, S. E. & Mazziotti, D. A. Lowering tomography costs in quantum simulation with a symmetry projected operator basis. Phys. Rev. A 103, 012420 (2021).10.1103/PhysRevA.103.012420 ↗
31. Frisch, M. et al. Gaussian 16, revision C. 01 (2016).
32. Trani, F. et al. Time-dependent density functional tight binding: new formulation and benchmark of excited states. J. Chem. Theory Comput. 7, 3304–3313 (2011).10.1021/ct200461y ↗
33. Savin, A., Umrigar, C. J. & Gonze, X. Relationship of Kohn–Sham eigenvalues to excitation energies. Chem. Phys. Lett 288, 391–395 (1998).10.1016/S0009-2614(98)00316-9 ↗
34. Peach, M. J., Williamson, M. J. & Tozer, D. J. Influence of triplet instabilities in TDDFT. J. Chem. Theory Comput. 7, 3578–3585 (2011).10.1021/ct200651r ↗
35. Bravyi, S. B. & Kitaev, A. Y. Fermionic quantum computation. Ann. Phys. 298, 210–226 (2002).10.1006/aphy.2002.6254 ↗
36. Aleksandrowicz, G. et al. Qiskit: An open-source framework for quantum computing. Zenodo (2019) https://doi.org/10.5281/zenodo.2562111.10.5281/zenodo.2562111 ↗
37. Sun, Q. et al. PySCF: the Python-based simulations of chemistry framework. WIRES Comput. Mol. Sci 8, e1340 (2018).10.1002/wcms.1340 ↗
38. Kraft, D. et al. A software package for sequential quadratic programming (Wiss. Berichtswesen d. DFVLR, 1988).
39. Ibe, Y. et al. Calculating transition amplitudes by variational quantum eigensolvers. Preprint at arXiv:2002.11724 (2020).
40. Spall, J. C. An overview of the simultaneous perturbation method for efficient optimization. Johns Hopkins APL Tech. Dig. 19, 482–492 (1998).
41. Spall, J. C. Adaptive stochastic approximation by the simultaneous perturbation method. In Proceedings of the IEEE Conference on Decision and Control, 4, 3872–3879 (1998).10.1109/CDC.1998.761833 ↗
42. Kandala, A. et al. Error mitigation extends the computational reach of a noisy quantum processor. Nature 567, 491–495 (2019).10.1038/s41586-019-1040-7 ↗