for Chemicals & Materials
Quantum computing promises to reduce waste and accelerate the discovery of new chemicals and materials, such as high-temperature superconductors, more efficient batteries, and new solar cell materials. Even if it only increased efficiency by a realistic 5-10%, McKinsey estimates that quantum computing could add $20 billion to $40 billion in value for the industry each year.
Building Better Batteries
The development of new battery technology will accelerate the shift to renewable energy and electric vehicles. Alternative electrolyte formulations could potentially allow lithium-ion batteries to operate at high voltages without compromising their cycle life. However, because the number of possible electrolyte formulations is extremely large, machine learning techniques could accelerate the discovery of battery materials.
Research suggests that quantum computing may be able to capture more correlations in data than classical computers, which would improve the prediction accuracy of machine learning models used to screen electrolyte additives. A hybrid quantum-classical classifier can be used to identify electrolyte additives that are likely to improve the oxidative stability of selected electrolyte formulation. The successful implementation of such an approach could reduce the marginal cost of producing electric vehicles and potentially increase their range.
Quantum-Ready Applications® for Chemicals and Materials
Supply Chain, Logistics and Shipping
Supply Chain, Logistics and Shipping
Chemical and Material Simulation
Discover and test new chemicals and materials using quantum chemical simulation, including stronger materials, lighter batteries, and more efficient catalysts.
Predict macroscopic properties of alloys and structural materials using multi-scale modeling and quantum-inspired machine learning.
Model homogenous and heterogenous catalysis using electronic structure calculations.
Excited State Property Prediction
Predict excited state properties for materials relevant to applications such as OLEDs and photovoltaics.
Chemical Dynamics Simulation
Simulate chemical dynamics and kinetics using quantum-enhanced force-field methods and electronic structure calculations.
Chemical Reaction Optimization
Optimize chemical reaction network conditions to maximize yield, reduce costs, and save time using quantum-enhanced machine learning techniques.
Plant Operations Optimization
Optimize the scheduling of machine processes and employee shifts using quantum or quantum-inspired prescriptive analytics.
Apply quantum-boosted predictive analytics to proactively predict when machinery and equipment will need maintenance.
Generate synthetic data with generative models to better train anomaly detection algorithms for quality control processes.
Supply Chain Optimization
Optimize the selection of suppliers and vendors for product quality, costs, delivery times, and demand coverage using generator-enhanced optimization (GEO).
Distribution Route Optimization
Optimize distribution routes to reduce fuel costs and delivery times using quantum or quantum-inspired prescriptive analytics.
Optimize the stocking of reactors, catalysts, and other components for chemical manufacturing as well as the stocking of distribution warehouses using GEO.
As the world’s largest chemical producer, BASF wants to know how quantum computing can be applied in the near-term to support the development of sustainable and innovative new materials.
BASF has partnered with Zapata to explore how quantum computing can boost machine learning approaches for predicting the molecular properties of new materials. Our collaboration with BASF also investigates how quantum-inspired methods can optimize operations across the value chain, from the sourcing of raw materials to the distribution of finished products.
Orquestra® Benefits for Chemicals and Materials
Orchestration Across Environments
Leverage the quantum and other heterogenous classical compute resources best suited for your tasks, without getting locked into any one hardware platform. Deploy across hybrid backends at enterprise scale.
Data Management & Velocity
Store, retrieve, and analyze large datasets. Streamline data management from ingestion to export to accelerate data velocity.
Keep what works now. Integrate existing and future solutions with a framework optimized for extensibility, interoperability, and innovation.
Workflow Development and Deployment
One unified platform to go from research to development to deployment with extensible, scalable, modular workflows.
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