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Built with ❤️ by the quantum computing community

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    Materials Science

    Applications of quantum computing in materials discovery, analysis, design, and optimization for advanced applications.

    57 Case Studies
    8 Target Roles

    The materials science field faces fundamental computational limitations in modeling, predicting, and designing advanced materials that impact discovery timelines, development costs, and innovation capabilities. Quantum computing offers transformative solutions to these challenges through several key applications that address specific computational bottlenecks in materials research.

    Materials discovery represents the most promising application, where quantum algorithms can model electron behaviour and molecular interactions with greater accuracy than classical approximations. This capability enables more precise prediction of material properties before synthesis, potentially accelerating the discovery of novel materials with specific performance characteristics. Several research institutions and materials companies have established quantum initiatives specifically targeting the discovery of superconductors, semiconductors, battery materials, and structural compounds.

    Quantum material simulation applications leverage quantum computing to model materials that exhibit quantum mechanical properties such as superconductivity, topological states, and quantum magnetism. These materials are particularly challenging to simulate with classical computers but may be more naturally represented on quantum systems, potentially leading to breakthroughs in understanding and designing quantum materials for advanced technologies.

    Properties prediction applications use quantum chemistry algorithms to calculate structural, electronic, optical, and mechanical properties of materials with greater accuracy than classical methods. Improved prediction capabilities directly impact material selection and optimization for specific applications across industries from electronics to aerospace.

    Catalyst design benefits from quantum computing through more accurate modeling of reaction mechanisms, transition states, and surface interactions. These capabilities can accelerate the development of more efficient catalysts for chemical processes, energy conversion, and environmental applications—addressing critical sustainability challenges.

    Material defect analysis applications leverage quantum simulation to understand how atomic-scale defects impact macro-scale material properties. These insights can lead to improved manufacturing processes, more durable materials, and novel defect-based functionalities in engineered materials.

    Implementation strategies for materials research organisations should focus on identifying specific computational bottlenecks in current discovery processes, developing hybrid quantum-classical workflows, establishing partnerships with quantum technology providers, and creating proof-of-concept implementations for high-value material discovery challenges.


    Related Case Studies

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    D-Wave and Airbus explore aerospace manufacturing

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    IBM and Boeing Quantum Computing Partnership for Aerospace Innovation

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    IBM and Daimler AG Strategic Partnership for Automotive Quantum Computing Applications

    IBM Quantum and Daimler AG formed a strategic partnership to explore quantum computing applications in automotive manufacturing, materials science, and logistics optimization. The collaboration focuses on leveraging quantum algorithms to solve complex computational challenges in vehicle design, battery technology, and supply chain management.

    Quantinuum and Mitsui & Co. evaluate broad quantum utility

    Quantinuum and Mitsui & Co. trading company explore quantum computing potential across a range of its portfolio of activities.

    Quantum Computing Partnership for Advanced Materials and Drug Discovery

    Algorithmiq, IBM Quantum, and Trinity College Dublin have formed a strategic partnership to leverage quantum computing for molecular simulation and drug discovery applications. This collaboration combines Algorithmiq's quantum algorithms for chemistry, IBM's quantum hardware and cloud infrastructure, and Trinity College Dublin's expertise in quantum information science to accelerate pharmaceutical research and materials development.

    IBM and ExxonMobil: Advancing Energy and Materials Science through Quantum Computing

    IBM Quantum and ExxonMobil partnered to explore quantum computing applications for solving complex computational challenges in energy and chemical research. This collaboration focuses on developing quantum algorithms for molecular simulation, materials discovery, and optimization problems critical to the energy sector.

    Microsoft and Ford explore traffic flow optimisation

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    Amazon Web Services and BMW Group: Quantum Computing for Industrial Challenges

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    Atos Quantum and Total: Advancing Energy Sector Optimization Through Quantum Computing

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    IBM and Daimler AG Quantum Computing Partnership for Battery Development and Optimization

    IBM and Daimler AG partnered to explore quantum computing applications in automotive research, focusing on battery chemistry simulation, fleet logistics optimization, and materials science. This collaboration aimed to leverage IBM's quantum computing expertise with Daimler's automotive innovation to solve complex computational challenges in the automotive industry.

    IBM and ExxonMobil Quantum Computing Partnership for Energy and Chemical Research

    IBM and ExxonMobil partnered in 2019 to explore quantum computing applications in energy sector challenges, focusing on molecular simulation, optimization problems, and materials discovery. The collaboration leverages IBM's quantum computing expertise and ExxonMobil's domain knowledge to address complex computational challenges in petrochemicals, carbon capture, and energy optimization.

    IBM and Mercedes-Benz Partnership: Quantum Computing for Automotive Innovation

    IBM and Mercedes-Benz (formerly Daimler) have collaborated since 2018 to explore quantum computing applications in automotive manufacturing, battery research, and logistics optimization. The partnership leverages IBM's quantum computing expertise and Mercedes-Benz's automotive domain knowledge to solve complex optimization problems that are computationally intractable for classical computers.

    ZZZZ QSimulate-Bosch Partnership: Quantum Computing for Materials Discovery and Chemical Simulation

    QSimulate, a quantum software company specializing in chemical simulations, partnered with Bosch to leverage quantum computing for accelerating materials discovery and molecular modeling. This collaboration aims to enhance Bosch's R&D capabilities in developing advanced materials for automotive, industrial, and consumer applications through quantum-enhanced computational chemistry.

    Intel-AIST Quantum Computing Research Collaboration for Advanced Materials and Device Development

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    IonQ and Airbus Partnership for Quantum Computing in Aerospace Applications

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    Silicon Quantum Computing: Australia's National Quantum Computing Commercialization Partnership

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    Zapata Computing and BP: Quantum Computing for Energy Optimization

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    ZZZ IBM and Mitsubishi Chemical: Advancing Materials Discovery Through Quantum Computing

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    IBM and Daimler Partnership: Advancing Automotive Innovation through Quantum Computing

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    ZZZ IBM and Quantum Network Partnership with Major Tech Companies

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    CQC and Nippon Steel explore materials science

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    Honeywell Quantum Solutions and BMW Group advancing supply chain optimisation

    Applying trapped-ion quantum computing to complex supply chain optimisation and logistics problems.

    ZZZ CQC and Honeywell Quantum Solutions: Mer DELETE

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    IBM Quantum Network Partnership with RIKEN and Cleveland Clinic

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    IonQ and US Air Force Research Laboratory

    Focusing on developing quantum algorithms for optimization problems, secure communications, and advanced modeling capabilities critical to military operations.

    Amazon AWS Braket and BMW explore automotive solutions

    A partnership to run a series of quantum computing innovation challenges for automotive applications.

    Industry Details

    Target Roles

    Systems Integration Engineer
    Quantum Cloud and Platform Provider
    Quantum Chemist
    Quantum Solutions Provider
    Quantum Algorithm Developer
    Software Engineer
    Quantum Hardware Engineer
    Domain Expert