Researchers anticipate that 2026 could mark the beginning of practical applications for quantum computers in chemistry, leveraging their inherent quantum nature to tackle complex molecular calculations. Advances in 2025 have laid the groundwork, with larger machines expected to enable more sophisticated simulations. This progress could benefit industrial and medical fields by improving predictions of molecular structures and reactivities.
The challenge of understanding a molecule's structure, reactivity, and other chemical properties stems from the quantum behavior of its electrons. Traditional supercomputers struggle with increasingly complex molecules, but quantum computers, being quantum devices themselves, offer a natural advantage for these tasks.
In 2025, significant steps forward demonstrated this potential. Teams at IBM and Japan's RIKEN institute combined a quantum computer with a supercomputer to model several molecules. Google researchers developed and tested a quantum algorithm to determine molecular structures. Meanwhile, RIKEN collaborated with Quantinuum to create a workflow for calculating molecular energies, where the quantum system detects its own errors. Separately, Qunova Computing introduced an algorithm that uses quantum elements to compute energies about 10 times more efficiently than classical methods.
Looking to 2026, experts expect larger quantum computers to accelerate these efforts. David Muñoz Ramo at Quantinuum notes, “Upcoming bigger machines will allow us to develop more powerful versions of this [existing] workflow, and ultimately, we’ll be able to address general quantum chemistry problems.” His team has simulated a hydrogen molecule so far, with more complex targets like industrial catalysts in sight.
Other initiatives are aligning similarly. In December, Microsoft partnered with quantum software start-up Algorithmiq to speed up development of quantum chemistry algorithms. A Hyperion Research survey identifies chemistry as the top area for quantum computing progress in the coming year, up from second and fourth in prior surveys, reflecting growing interest and investment.
However, full realization depends on achieving fault-tolerance in quantum systems, a universal goal among manufacturers. As Philipp Schleich and Alán Aspuru-Guzik of the University of Toronto observe in a recent Science commentary, “The ability of a quantum computer to solve problems faster than a classical computer depends on fault-tolerant algorithm.” Until then, hybrid approaches will bridge the gap, potentially transforming chemical research in industry and medicine.
