- What happened: An evaluation technology for solid-state battery materials, jointly developed by Sharp and QunaSys, has been selected for Season 2 of NEDO's quantum prize program.
- Why it matters: The companies aim to extend quantum-computer calculations of ion-migration energy to more complex materials, with the goal of helping select and design candidate materials for solid-state batteries.
- What to watch next: Key details include the materials and atom counts involved, and concrete figures on accuracy and computation time compared with conventional methods. Whether the results match measurements of synthesized materials will also be important.
On October 22, 2026, Sharp and QunaSys announced that their development of an evaluation technology for solid-state battery materials using quantum computers had been selected for Season 2 of the quantum prize program run by NEDO (the New Energy and Industrial Technology Development Organization). In Season 1, the companies developed and verified a method that uses quantum computation to evaluate the energy required for ions to move through a solid electrolyte. In Season 2, they aim to apply it to more complex materials containing more atoms. Their ultimate goal is to establish a computational technology that can efficiently narrow down candidate materials for solid-state batteries and be used in material design and prototyping. How far the Season 1 method can be applied to actual materials development will be the focus going forward.
Evaluating ion-migration energy with quantum computers
Solid-state batteries replace the liquid electrolyte used in conventional lithium-ion batteries with a solid material. In materials development, it is important to accurately understand how easily ions move through a solid electrolyte. The energy required for ion migration is one key indicator for understanding a material's ion-conduction properties and comparing candidate materials. In their Season 1 research, Sharp and QunaSys developed a technology that uses quantum computers to evaluate this energy computationally.
The two companies divided roles according to their respective areas of expertise. Drawing on its knowledge of batteries and materials development, Sharp defined the items to be evaluated and the accuracy the calculations require. QunaSys, which develops software for quantum computers, was responsible for converting those evaluation items into problems that quantum computation can handle, and for building and verifying the calculation method. The effort aims to use quantum algorithms to carry out the evaluations needed in real materials development.
As a result of Season 1, the companies say they confirmed that the performance of solid-state battery materials can be evaluated more accurately and efficiently than before. However, specific figures for calculation error and processing time have not been disclosed, nor have the conventional methods used as comparison points. It is therefore difficult to judge objectively how much accuracy improved or how much computation time was reduced. Details such as the names of the materials studied, their atom counts, and the number of candidate materials evaluated have also not been provided.
The quantum computer model, the number of qubits, and the number of calculation repetitions have not been made public either. The announcement also does not make clear how actual quantum computers and simulators were used. What is clear at this point is that the companies developed and verified a calculation method and report achieving certain results in performance evaluation. The research did not involve building prototype batteries and measuring capacity or lifespan, nor did it demonstrate that introducing quantum computation improved actual battery performance. Ion-migration energy results alone cannot support conclusions about shorter charging times or longer battery life.
Season 2 targets more complex materials and higher accuracy
In Season 2, the companies will work to further improve calculation accuracy, targeting complex materials that contain more atoms than in Season 1. According to the companies' joint announcement dated October 22, 2026, they aim to evaluate more complex materials by combining conventional computers with quantum computers. The aim is to compare how easily ions move in each material through calculation, and to use the results to narrow down promising candidates and support material design. The key question is whether they can secure accuracy sufficient for materials-development decisions, rather than merely scaling up the calculations.
The plan does not involve moving all the calculations needed for materials evaluation onto quantum computers. However, it has not been disclosed which processes conventional and quantum computers will each handle. Specific targets, such as how far the number of atoms in the calculation will be increased or which materials will be evaluated, have also not been presented. Assessing the Season 2 results will require confirming how much more complex the materials that can be handled have become, as well as how calculation accuracy and required time have changed.
The initiatives the companies announced can be organized into the Season 1 results, the Season 2 development goals, and future applications, as follows.
| Stage | Initiative | Status at time of announcement |
|---|---|---|
| Season 1 | Evaluate the energy required for ion migration using quantum computation | The companies report that they built the calculation method and completed verification |
| Season 2 | Combine conventional and quantum computers to evaluate more complex materials with more atoms | Plans to expand the calculation targets and improve accuracy |
| Future applications | Reflect calculation results in material synthesis and actual performance evaluation | A concept aimed at making materials development and prototype evaluation more efficient |
Season 1 was positioned as building and verifying the calculation method, and Season 2 as applying it to more complex materials. Beyond that lies a concept of synthesizing and evaluating materials selected through calculation, leading to more efficient prototyping. However, what has been demonstrated in this announcement must be distinguished from what the companies aim to achieve in the future. The stage of using calculation results in material synthesis and measured evaluation has not yet been reached, and how much the technology can streamline the actual materials development process remains a matter for future verification.
NEDO selection is a starting point; performance demonstration is still ahead
The list of Season 2 screening selectees published by NEDO includes the team name "SHARP/QunaSys." The selected challenge is multi-objective optimization toward realizing a circular economy in the chemical and materials industries. The selection is meant to advance research and development of quantum computing technology, and does not mean that computational performance or practicality has already been demonstrated.
NEDO says it will provide participants who pass the screening review with computing environments such as the National Institute of Advanced Industrial Science and Technology's quantum computer "ABCI-Q." The official FAQ also explains that applicants need only submit a document outlining their concept at the time of application, while the subsequent results review requires research results that use actual quantum hardware or a simulator. In other words, selection recognizes participation in research and development, and actual technical results are evaluated in later reviews. Selection alone is not grounds for concluding that quantum computers outperform conventional computational methods.
Under the standard schedule for the program as a whole, the R&D period runs from early September 2026 to late June 2027. Deliverables are due in late June 2027, and an awards ceremony is planned for mid-October of that year. However, this is the schedule for NEDO's quantum prize program overall; it does not indicate when Sharp and QunaSys's technology will be put to practical use or when products containing solid-state batteries will go on sale. How concrete the evaluation results the two companies release ahead of the upcoming results review will be is a point of interest.
The main source of information on the research results available at present is the joint announcement by Sharp and QunaSys. The announcement text and its attached PDF do not list the authors, journal, DOI, or preprint identifier of any related peer-reviewed paper. As a result, the work cannot currently be confirmed as peer-reviewed research, and no information is provided on replication by independent research groups. Judging the reproducibility of the reported results, or their advantage over conventional methods, will require more detailed disclosure of calculation conditions and evaluation results.
To determine whether quantum computation will actually help in developing solid-state battery materials, it will be important to disclose the target materials and atom counts and to compare accuracy and required time with conventional methods. It will also be necessary to synthesize candidate materials chosen on the basis of the calculation results and verify how closely their measured properties match the predictions. For Sharp and QunaSys to achieve the more efficient materials development they are aiming for, they must not only make it possible to calculate more complex materials but also show that the results are useful in actual material selection. Season 2 will test how far the companies can connect technical progress in quantum computation to practical materials evaluation.