Photo by Charlie Larkman on Unsplash
Modeling of complex systems such as materials, batteries, and medicines is extremely difficult for existing computers. The next generation of computing devices, which are quantum computers, will be able to solve such problems more efficiently. As a result, the business will be able to find practical solutions such as modeling of new materials, production of devices of a new class from such materials, and selection of optimal characteristics or reactions inside these materials, which are necessary for increasing the subsequent efficiency. One of the real challenges for the industry and business is the modeling of chemical compounds used in the batteries manufacturing process.
“As part of the project, we are developing quantum chemistry methods using machine learning and quantum optimization. We plan to integrate the developed methods into the material design system, which is used today in Nissan. This will allow Nissan to unlock the huge potential of quantum computing for its tasks, and in the future, to achieve technological leadership,” said Alexey Fedorov, Head of the Group Quantum Information Technologies RQC, Ph.D. in Theoretical Physics.
“Quantum technologies are promising for solving many industrial challenges. The materials that can be created with quantum chemistry will significantly increase the power and capacity of batteries. As a result, we will get the opportunity to create highly efficient and environmentally-friendly transport, as well as new solutions. The future is behind these technologies and, together with our partner, Russian Quantum Center, we are striving to become a pioneer in this industry,” said Shigeo Ibuka, Head of Nissan R&D center in Russia, Ph.D. in Physics.
In the long term, the use of quantum technologies will significantly reduce the time for the development of new materials, as well as predict their compliance with the requirements of industry and business. The RQC team will conduct research using both existing quantum computers and their own-developed quantum-inspired algorithms.
“As part of the project, we are developing quantum chemistry methods using machine learning and quantum optimization. We plan to integrate the developed methods into the material design system, which is used today in Nissan. This will allow Nissan to unlock the huge potential of quantum computing for its tasks, and in the future, to achieve technological leadership,” said Alexey Fedorov, Head of the Group Quantum Information Technologies RQC, Ph.D. in Theoretical Physics.
“Quantum technologies are promising for solving many industrial challenges. The materials that can be created with quantum chemistry will significantly increase the power and capacity of batteries. As a result, we will get the opportunity to create highly efficient and environmentally-friendly transport, as well as new solutions. The future is behind these technologies and, together with our partner, Russian Quantum Center, we are striving to become a pioneer in this industry,” said Shigeo Ibuka, Head of Nissan R&D center in Russia, Ph.D. in Physics.
In the long term, the use of quantum technologies will significantly reduce the time for the development of new materials, as well as predict their compliance with the requirements of industry and business. The RQC team will conduct research using both existing quantum computers and their own-developed quantum-inspired algorithms.