Words by Jesse Silverberg, PhD

I once asked a company for some product information and they sent back a giant spreadsheet that’s denser than the McMaster-Carr catalog. My only thought was, “that’s not great.”

Choose a metamaterial - The McMaster-Carr catalog

Image: The very thorough McMaster-Carr catalog.

Choice paralysis is a problem

How do you navigate a landscape with hundreds of dimensions? How do you make decisions when the answer to every question is “it depends”? This type of problem arises everywhere from airline booking websites to modern data science. When offered a massive menu of possibilities, thoughtful creative solutions are required to overcome the burden of choice.

Trying to choose your metamaterial solution that’s best suited for a specific problem is a prime example of this challenge. Mechanical metamaterials are defined by their geometry, and each geometry can have a dozen or more parameters.

At Multiscale Systems, we’ve mapped out the relationships between these parameters and the resulting material properties. We’ve compiled this data and made it available in our interactive Metamaterial Selector, an easy-to-use interface that takes the guesswork out of finding the best option. By doing the hard work ahead of time, we’ve created a tool that allows you to quickly choose a metamaterial solution best suited to your needs.

Case study: Choose a metamaterial solution for lightweight vehicle impact protection

Suppose you’re responsible for designing a vehicle safety system to mitigate risk of injury in a crash. As the first layer of defense, you want some kind of lightweight protective shield, the goal of which is to absorb as much energy as possible without adding significant weight.

You’ve spoken with your team and they’ve voiced concern that the safety system can’t interfere with certain critical aspects of the vehicle’s design due to cost and time constraints, so you’ve opted to choose a metamaterial as it’s an impact absorbing material that requires no power source and can be shaped to fit within the existing vehicle envelope.

Already, we have three distinct performance metrics to consider:

1. Density

Density is a common measure of how much weight per unit volume of impact-absorbing material is required. Reducing the total solution weight is important for efficiency, but a lower-density material may require more total material to achieve impact protection and therefore result in a higher total weight.

This trade-off is why a foam would be an inappropriate solution – yes, foams absorb energy and are very low-density, but the amount of foam required to protect passengers in a vehicle collision would be astronomically impractical. Reducing density independent of performance is therefore insufficient.

2. Specific Energy Absorption (SEA)

SEA is a measure of how much impact energy will be absorbed per unit mass of material. Generally, a high SEA is great, but some high SEA materials like honeycomb and crush tubes only function for impacts coming from a very narrow range of directions.

Solutions that function in one direction are considered anisotropic, whereas solutions that function in all directions are considered isotropic. The MetaCORE family of lightweight impact absorbers have been engineered to promote isotropic energy absorption and therefore offer protection regardless of the impact direction. This characteristic means no special engineering is required to shape the material or form it with a specific orientation.

(Actually, MetaCORE’s SEA is 30x higher performing than popular comparative materials – check out this white paper (PDF) to learn more).

3. Crush Force Efficiency (CFE)

CFE is another key metric for designing impact protection systems. It quantifies the potential for harmful shocks and sudden decelerations. Yes, you read that right. Simply absorbing impact energy is not enough, because the impact energy needs to be absorbed at a smooth rate.

Low CFE solutions for passenger vehicles translate to whiplash and neck injury. High CFE solutions activate at a threshold equal to their strength, and then smoothly dissipate energy at a rate equal to their strength multiplied by their CFE.

Other factors

The density, SEA, and CFE, are the three metrics that immediately arise from the problem statement. Several more factors can be teased out by further considering the operational conditions.

For example, vehicles routinely experience extreme outdoor temperatures, and in colder climates with snow, exposure to punishingly corrosive salt. As a result, commodity materials with the potential for impact absorption will soften at high temperatures, become brittle at low temperatures, or undergo accelerated degradation from corrosion. Cross-referencing the various performance metrics against these considerations is therefore critical for success.

Having identified just a few factors in our case study, we’ve exposed the issue our Metamaterial Selector was designed to solve: too many options make it difficult to narrow down a choice.

Putting it all together with the Metamaterial Selector

Let’s use the factors we discussed above and input them into the Metamaterial Selector in order to choose a metamaterial solution.

Choose a metamaterial family

We know MetaCORE metamaterials are already engineered for lightweight impact protection so we’ll select that as our general metamaterial family. But let’s drill down further by selecting from the left drop-down menu whether we’re working in metric or imperial units (in this case, we’ll select metric).

Choose a metamaterial - selecting the metamaterial solution.

Image: Selecting Metric for our chosen metamaterial solution.

Selecting for high SEA and CFE solutions

Next, let’s have a look at the main data visualization graph, which should be pre-populated with the MetaCORE (metric) data set. We know we want high SEA and CFE solutions, so let’s set the -axis to SEA and the y-axis to CFE.

By default, the axes are on a logarithmic scale, which makes it easier to understand data across a broad range of values. But CFE is better visualized on a linear scale, so let’s change the y-axis from “logarithmic” to “linear.”

Choose a metamaterial - changing the y-axis scale

Image: Changing the Y-Axis Variable to a linear scale.

Navigate trade-offs: narrow the ranges for CFE and SEA

We now have a scatter plot where the highest performing solutions jump to the upper-right area of the pack. These look good, but what are the trade-offs and how much mass will they add? To answer these questions, we simply need to filter the data using sliders from the left-hand menu. Open up CFE and narrow the range to only show values greater than 65%.

Choose a metamaterial - selecting the CFE

Image: Narrowing the CFE range to values above 65%.

Next, open up SEA and narrow the range to remove a good amount of the remaining data points.

Choose a metamaterial - selecting the SEA

Narrow options for lower density solutions

We’re making progress. Let’s bring in considerations about added weight.

Keep the x-axis at SEA and change the y-axis to display density. Set both axes to logarithmic to get the clearest sense of the data’s spread.

Select density from the left-hand menu and make adjustments to narrow the focus to lower density solutions.

Choose a metamaterial - selecting the density.

Image: Selecting for lower density.

Choose your base material

Finally, expand the option for the base material used to fabricate the metamaterial and use the checkboxes to exclude materials from the visualizer. The default is to show your more rather than fewer, but the thermoplastic materials listed by default are all generally appropriate for the use case.

Choose a metamaterial - selecting the material

Image: Excluding base materials.

Access the data card for your selected solution(s)

Finally, cross reference the data table below the visualizer to get complete information on specific performance information about metamaterial solutions and their material properties. Click on any row in the table to pull up its material card and copy-paste (or print to PDF) for your convenience.

Choose a metamaterial - Metamaterial Selector data card screenshot

Image: The data card for the selected metamaterial solution.

Solve your problem without the guesswork

Now that you have the metamaterial data, you’re all set to design the impact protector.

You’ll be able to answer the critical questions of how much metamaterial you’ll need to dissipate an impact and how much it will weigh.

We have an already published case study (PDF, see page 3) that shows how to get the most use from the information at your fingertips, which is especially helpful if you’re designing for specific safety regulations or trying to reverse engineer your design for a specific crash scenario.

Once you choose a metamaterial solution and you’re happy with the technical performance, contact us to request a quote.

What if I want a solution not found in the selector?

No worries – we regularly update the data selector with measurements coming out of our skunkworks. If you don’t see the solution you want in the material you want it in, that doesn’t mean it won’t work – it just means we haven’t tested that permutation of variables yet. Contact us to let us know what you want and we’ll work with you to help you get the answers you need.

Try the Metamaterial Selector

This interactive data selector was created with support from the New England Business Association matching grant program.

headshot Jesse Silverberg

Jesse Silverberg, PhD, is the CEO and Research Director at Multiscale Systems. With more than 15 years’ experience in physics research and technology development, Jesse now leads Multiscale Systems toward sustainable commercial success.

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