February 03, 2025
Material discovery reborn: Applications of quantum computing in quantum dynamics
The quantum computing community has long framed ground energy estimation as the central problem in quantum chemistry, serving as a layer of abstraction to decouple algorithmic developments from concrete applications. As a result, one might come away from the literature with the impression that ground-state energy estimation is all there is to quantum chemistry. This perception, however, is not accurate.
Problems in quantum chemistry can be categorized as either static or dynamic. Static problems focus on properties of the eigenstates of a system such as ground- or excited-state energies. Eigenstates are stationary states, and their expectation value doesn’t change for any observable under time evolution. This makes static problems inherently time-independent, greatly reducing their difficulty. Dynamical problems on the other hand focus on non-stationary properties, necessitating a time-dependent treatment.
When it comes to understanding and designing functional materials, many critical processes are dynamical, rendering a static description of the system inadequate. For instance, while static calculations can indicate whether a process is thermodynamically favorable, they provide little insight into the timescales or competing pathways that determine whether the process actually happens. However, quantum dynamics are notoriously hard to simulate on classical hardware. In contrast, quantum computers seem naturally suited for simulating time dynamics, but surprisingly, little attention has been given to exploring the applications of quantum computers in dynamics. So we decided to do it in our recent paper Quantum Algorithm for Vibronic Dynamics: Case Study on Singlet Fission Solar Cell Design!
Contents
Simulation-Driven Discovery
Traditional experimental approaches in material discovery often involve synthesizing molecules, setting up complex testing environments, and maintaining a team of experts to operate and interpret the experiments. All of this is time-consuming and expensive. Accurate quantum simulations can bypass many of these hurdles by offering a way to predict material behavior at a fundamental level without the need for physical prototypes or intricate experimental setups. By replacing physical testing with simulations that have true predictive power, researchers can significantly reduce not only the time required to discover and optimize new materials but also the associated costs and resources. This can transform the process of material discovery from one that is laborious, time-consuming, and expensive into a streamlined, cost-effective, computationally-driven endeavor. Moreover, it opens the door to exploring molecular configurations or extreme conditions that might be difficult, dangerous, or inaccessible experimentally.
However, many key functional properties of material like charge and energy transfer are inherently time-dependent, requiring a dynamical description. Classical methods often fall short in capturing the complexity of quantum dynamics, with accurate simulations quickly becoming intractable as system size increases. This is where quantum computers show immense promise, but first, we need a quantum algorithm!
In our work, we develop a highly optimized quantum algorithm based on product formulas to implement time evolution under a general vibronic Hamiltonian. The word vibronic is derived from the combination of the words vibrational and electronic, reflecting its connection to the interaction between vibrational (nuclear motion) and electronic (electronic energy states) degrees of freedom in molecules. Our algorithm is the first in its ability to treat an arbitrary number of electronic states and vibrational modes. Moreover, we develop various algorithmic innovations to reduce the cost of the algorithm, achieving some of the lowest number of qubits and gates required for a useful application of quantum computers.
Next, we’ll analyze an industrially relevant application of our algorithm for probing and optimizing rates of vibronically-driven energy and charge transfer processes in organic solar cells based on singlet fission, a form of multiple exciton generation process.
Case Study on Singlet Fission Solar Cell Design
Vibronic effects play a crucial role in the accurate modeling of photochemistry, providing insights into processes such as charge and energy transfer, non-radiative relaxation, and reaction pathways. These have a wide range of applications, including the design of advanced materials for optoelectronic and photovoltaic technologies [1, 2, 3, 4], the study of molecular photomagnets for ultradense memory storage [5, 6, 7], and the advancement of photodynamic therapies for cancer treatment [8, 9].
In the following, we focus on an application in photovoltaics—specifically, designing next-generation organic solar cells that utilize the quantum phenomena of singlet fission that achieve a theoretical internal quantum efficiency of 200%: two electrons for one photon! And, of course, all made possible by the ability to simulate various key processes on a quantum computer.
Singlet fission is a quantum process that can increase the efficiency of solar cells by generating two excitons from a single absorbed photon. This effectively doubles the energy conversion potential of the absorbed light since each exciton can independently contribute to the generation of charge carriers. Singlet fission begins when a photoexcited molecule in its low-spin (singlet) state transfers energy to a neighboring molecule, creating a pair of high-spin (triplet) excited states.
However, generating these triplets isn’t enough—for singlet fission to improve solar cell efficiency, the triplets must separate efficiently in order to migrate to an acceptor interface.
Following the migration of a separated triplet exciton to the donor-acceptor interface, a charge transfer must occur between the excited molecule, and an electron acceptor to produce free charge carriers (electricity!).
All of these steps—from singlet fission to charge transfer—are inherently dynamical processes driven by vibronic interactions, where nuclear motion plays a key role in mediating electronic transitions. Existing computational approaches focus mostly on static energetic criteria, which are insufficient to capture these dynamics. For instance, while static calculations can indicate whether singlet fission is energetically allowed, they provide little insight into the timescales or competing pathways that determine whether the process actually happens.
Our algorithm addresses this gap by enabling fully quantum simulations of non-adiabatic dynamics. Starting from a vibronic Hamiltonian, our algorithm models how populations shift between different states over time, providing insights into the singlet fission rate and downstream processes like triplet separation and charge transfer. These vibronic effects are essential for modeling singlet fission solar cells and optimizing their performance — and are precisely what our quantum algorithm targets!
Outro
There are simply too many exciting results to distill into a blog post, so we strongly encourage you to read our paper on Quantum Algorithm for Vibronic Dynamics: Case Study on Singlet Fission Solar Cell Design! There we provide a detailed explanation of the algorithm, the innovations we developed to optimize its performance, and a proof-of-concept materials discovery pipeline tailored to designing more efficient singlet fission–based organic solar cells. We also present concrete resource estimates for implementing the algorithm across a wide range of system sizes and parameter regimes, achieving some of the lowest numbers yet for a practical application of quantum computers.
References
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[2] T. Nelson, S. Fernandez-Alberti, A. E. Roitberg, and S. Tretiak, Nonadiabatic excited-state molecular dynamics: Modeling photophysics in organic conjugated materials, Acc. Chem. Res. 47, 1155 (2014).
[3] A. Endo, K. Sato, K. Yoshimura, T. Kai, A. Kawada, H. Miyazaki, and C. Adachi, Efficient up-conversion of triplet excitons into a singlet state and its application for organic light emitting diodes, Appl. Phys. Lett. 98, 083302 (2011).
[4] J. Gibson, A. P. Monkman, T. J. Penfold, The importance of vibronic coupling for efficient reverse intersystem crossing in thermally activated delayed fluorescence molecules. Chemphyschem. 17, 2956 (2016).
[5] J. K. Staab and N. F. Chilton, Analytic linear vibronic coupling method for first-principles spin-dynamics calculations in single-molecule magnets, J. Chem. Theory Comput. 18, 6588 (2022).
[6] T. J. Penfold, J. O. Johansson, and J. Eng, Towards understanding and controlling ultrafast dynamics in molecular photomagnets, Coord. Chem. Rev. 494, 215346 (2023).
[7] A. Mattioni, J. K. Staab, W. J. Blackmore, D. Reta, J. Iles-Smith, A. Nazir, and N. F. Chilton, Vibronic effects on the quantum tunnelling of magnetisation in kramers single-molecule magnets, Nat. Commun. 15, 485 (2024).
[8] G. Cui and W.-h. Fang, State-specific heavy-atom effect on intersystem crossing processes in 2-thiothymine: A potential photodynamic therapy photosensitizer, J. Chem. Phys. 138, 044315 (2013).
[9] F. Ponte, D. M. Scopelliti, N. Sanna, E. Sicilia, and G. Mazzone, How computations can assist the rational design of drugs for photodynamic therapy: photosensitizing activity assessment of a Ru (II)-BODIPY assembly, Molecules 27, 5635 (2022).
About the author
Danial Motlagh
Searching for real world applications of quantum computers.