Lightweight glass for Cars
A new machine-learning algorithm for exploring lightweight, very stiff glass compositions can help design next-gen materials for more efficient vehicles and wind turbines. Lightweight glass reduces energy and raw material consumption, thereby saving resources. Glasses can reinforce polymers to generate composite materials that provide similar strengths as metals but with less weight. In addition, the cost of transport and storage is reduced. Bottlers, retailers, consumers, and the environment all benefit from this new lightness.
Liang Qi, a professor of materials science and engineering at the University of Michigan, answered questions about his group’s new paper in Computational Materials.
Lightweight glass saves raw materials, weight, and transport costs. The lower weight simplifies transport to the customer and the consumer. Elastic and glass don’t seem to be two words that go together. All solid materials, including glass, have a property called elastic stiffness — also known as elastic modulus. It’s a measure of how much force per unit area is needed to make the material bend or stretch. If that change is elastic, the material can totally recover its original shape and size once you stop the force.
Elastic stiffness is critical for any materials in structural applications. Higher stiffness means that you can sustain the same force loading with a thinner material. For example, the structural glass in car windshields, and in touch screens on smartphones and other screens, can be made thinner and lighter if the glasses are stiffer. Glass fiber composites are widely used lightweight materials for cars, trucks, and wind turbines, and we can make these parts even lighter.
Benefits of lightweight glass –
- Reduced transport costs (lighter, and more containers per pallet)
- No loss of performance
- Attractive to consumers, especially when green aspects are marketed
- Reduced production costs and CO2 emissions
- Increased productivity.
Lightweight glass containers offer a resource-efficient solution, with the potential to save over 150,000 tonnes of glass packaging each year. Lighter vehicles can go further on a gallon of gas — 6-8% further for a 10% reduction in weight, according to the U.S. Office of Energy Efficiency and Renewable Energy. Weight reduction can also significantly increase the range of electric vehicles.s
Lighter, stiffer glass can enable wind turbine blades to transfer wind power into electricity more efficiently because less wind power is “wasted” to make the blades rotate. It can also enable longer wind turbine blades, which can generate more electricity under the same wind speed.
The last few years have seen some important advances in lightweight glass packaging, many premium products are now offered in lightweight containers while retaining their original performance characteristic and design appeal. And as a growing body of evidence reveals, innovative weight reductions can be achieved without undermining consumer appeal.
The other problem is that we don’t have enough data about glass compositions for machine learning to be effective at predicting glass properties for new glass compositions. Machine learning algorithms are fed data, and they find patterns in the data that enable them to make predictions.
How did you overcome these barriers?
First, we used existing high-throughput computer simulations to generate data on the densities and elastic stiffnesses of various glasses. Second, we developed the machine learning model that is more suitable for a small amount of data — because we still didn’t have a lot of data by machine learning standards. We designed it so that the key thing it pays attention to is the strength of the interaction between atoms. In essence, we used physics to give it hints about what was important in the data, and that improves the quality of its predictions for new compositions. Brand owners, manufacturers, and retailers have already begun to adopt lightweight glass, with great success weight glass, with great success.
