As science and technology advance toward a quantum revolution, quantum materials and quantum computing are widely recognized as key drivers of disruptive breakthroughs. Materials underpin all technologies by determining electronic structures and physical properties, while decades of research have revealed the unique behaviors of quantum materials. At the same time, quantum computing is accelerating the discovery and design of novel materials, creating a mutually reinforcing relationship between computation and materials science.
Quantum Material Properties and Qubit Implementation Approaches
Quantum materials exhibit quantum-mechanical characteristics that give rise to behaviors beyond the explanatory scope of classical physics. For example, superconducting materials exhibit zero electrical resistance and the Meissner effect at low temperatures, while topological insulators remain electrically insulating in the bulk yet conductive and robust at the surface. Strongly correlated electron systems display phenomena such as Mott insulating behavior arising from electron–electron interactions. Meanwhile, quantum entanglement, characterized by non‑local correlations, forms the theoretical foundation of quantum computing and quantum communication, enabling the development of novel technological applications.
At present, superconducting qubits represent the most extensively adopted qubit platform, with organizations such as IBM, Google, and Academia Sinica employing this approach. These qubits are based on Josephson junctions composed of aluminum/aluminum‑ oxide/ aluminum structures, operating at ultra‑low temperatures of approximately 10 mK. When coupled with capacitive elements, they form artificial atoms whose two energy levels are defined as the quantum states |0〉and |1〉.
By contrast, IonQ utilizes trapped‑ion qubits, in which individual atoms are confined using electric or magnetic fields and manipulated via laser‑induced electronic transitions. Intel has developed quantum dot qubits, fabricated using CMOS processes to create nanoscale electron confinement structures, with electron spin or charge states serving as quantum states. All such approaches require cryogenic environments to maintain qubit stability.
Quantum Computing as a Catalyst for Innovation in Materials Science
Quantum computing is no longer limited to the development of qubits themselves; it is increasingly emerging as a powerful tool for materials research and development. By simulating complex molecular behavior and reaction mechanisms, quantum computing can accelerate catalyst discovery and the design of novel materials, while improving the efficiency of defect analysis, thermal transport modeling, and molecular stability assessment. Through advanced quantum algorithms, large-scale chemical systems can be addressed more effectively, avoiding the exponential growth in computational resources required by classical simulations and significantly enhancing computational capabilities in materials science.
Case Study I: Quantum Simulation of High-Temperature Superconductors
Google has employed quantum processors to simulate the Hubbard model, while the University of Science and Technology of China (USTC) has applied the fermionic Hubbard model (FHM) to investigate the mechanisms of cuprate superconductivity. Together, these efforts provide a foundational basis for using quantum computing to study high‑temperature superconductors.
Case Study II: Molecular Stability Simulation for Lithium–Sulfur Batteries
Lithium batteries employing sulfide‑based solid electrolytes are regarded as a safer next‑generation energy storage solution. IBM and Mercedes-Benz have applied variational quantum algorithms to calculate the energy and dipole moments of lithium hydride and hydrogen sulfide materials, enabling detailed analysis of chemical bond dissociation processes. These quantum simulations provide critical insights that support the development of next‑generation solid‑state lithium batteries.
Case Study III: Nitrogen-Vacancy Center Magnetometry
Nitrogen‑vacancy (NV) center magnetometry exploits the spin states of diamond lattice defects in the diamond lattice to achieve highly sensitive magnetic field measurements, with the added advantage of room-temperature operation. The Tokyo Institute of Technology has applied diamond‑based quantum sensors to monitor electrical currents during battery operation, enabling charging processes to more closely approach true battery capacity. This, in turn, contributes to extended battery lifespan and reduced overall costs.
Case Study IV: Simulation of the FeMo Cofactor Macromolecule
Industrial nitrogen fertilizer production relies on ammonia synthesized through the Haber–Bosch process, which requires high temperatures and pressures and is highly energy intensive. In nature, nitrogen fixation is catalyzed by nitrogen-fixing bacteria containing the iron–molybdenum (FeMo) cofactor, a complex macromolecular structure that is extremely difficult to simulate using classical computing methods. According to estimates by Google, simulating this system would require approximately four million qubits and four days of computation, offering the potential to substantially reduce energy consumption and carbon emissions in ammonia production.
Case Study V: Photocatalytic Water-Splitting Simulation
Hydrogen energy is widely regarded as a key pillar of sustainable energy systems. If photocatalysts can efficiently split water using solar energy, they could make a substantial contribution to net-zero objectives. Toyota Motor Europe, in collaboration with the Quantum Application Lab (QAL), has simulated photocatalytic water‑splitting mechanisms using the State‑Averaged Orbital‑Optimized Variational Quantum Eigensolver (SA‑OO‑VQE) algorithm.
By modeling interactions in both ground and excited states, the research successfully resolved complex reaction pathways involved in water splitting and improved the efficiency of hydrogen-related materials development.
Three Key Future Trends in the Application of Quantum Computing to Materials Chemistry
Trend 1: Transition from Theoretical Models to Product-Oriented Applications
Quantum simulations are expanding from single atoms and simple molecules to large-scale systems such as the FeMo cofactor. This transition signals a shift in quantum computing from theoretical exploration toward practical materials design, delivering microscopic insights that directly support product development.
Trend 2: Algorithmic Breakthroughs Accelerating Practical Deployment
While the development of general‑purpose quantum computers remains constrained by qubit counts and the challenges of error correction, quantum annealing has already demonstrated early practical applications in materials screening and optimization workflows. Ongoing advances in algorithms are expected to significantly accelerate the broader deployment of quantum chemistry applications.
Trend 3: Convergence of Artificial Intelligence and Quantum Computing
Quantum simulation excels at high‑precision analysis of electronic behavior, while artificial intelligence is well suited to large‑scale data-driven prediction. Their integration is expected to transform materials research and development processes, with applications spanning battery material screening, formulation optimization, and lifetime prediction.
Conclusion: Advancing the Integration of Quantum Technologies and Materials Research in Taiwan
Taiwan possesses strong capabilities in semiconductor and materials research. In 2021, the national quantum technology program formally established a cross‑ministerial task force, selecting 17 industry–academia–research teams to advance key technologies, including superconducting qubits, cesium-atom qubits, and germanium- and silicon-based quantum dots. In parallel, materials research initiatives have utilized the IBM Quantum Platform to simulate energy transfer processes in photosynthesis, demonstrating early applications of quantum computation in complex materials systems. The convergence of quantum materials and quantum computing represents a critical transformation in next‑generation technologies. Although still at an early stage, this convergence holds substantial potential for advancing materials science. With sustained investment in research and development and strengthened international collaboration, Taiwan is well positioned to play a leading role in the global competition surrounding quantum materials and technologies.
