First published in the March/April 2024 magazine, then online on September 5, 2024. Interviewees’ roles, the software offering and the projects described reflect the context of that interview.
Remember our discussion of the role of materials in a successful application? As additive manufacturing (AM) advances, new opportunities continue to emerge. Here, I am interested in how design methods and AM can combine to target specific functions and mechanical behaviors. Alongside academic research, a Swiss startup is exploring the transition of these architectures into industrial applications.
When I first heard about metamaterials, their possibilities sounded remarkable. This feature focuses mainly on mechanical metamaterials: their behavior depends on their architecture as well as the material from which they are made. Lattices are one possible structural family, but the terms are not interchangeable; other architectures, including continuous surfaces, can also be investigated.
The challenge is therefore not just selecting a feedstock, but designing a geometry that delivers a target response. Industrial adoption also depends on the manufacturing process, its cost and validation of the resulting properties.
Additive manufacturing makes complex architectures accessible for investigation. This opens possibilities for new applications, without by itself guaranteeing their industrial feasibility.
At the intersection of software and materials
Developing metamaterials calls for expertise across several disciplines, beyond feedstock production alone. After speaking with Daniel Bachmann, then Chief Innovation Officer of Swiss startup Spherene Ltd., I am tempted to place these developers at the intersection of software design and materials development.
Bachmann explains that in 2018, the Spherene team explored new surfaces using a paper model. It developed an Adaptive Density Minimal Surface (ADMS) algorithm accessible through a cloud API. According to the company, the method uses inverted spherical surfaces to fill a design volume with an open architecture whose geometry and apparent density can be adapted.
Bachmann particularly highlights the distribution of loads within that volume. This property needs to be assessed for the specific geometry, material, process and loading case; describing it as “ideal” does not establish universal performance.
“Our technology enables us to apply forces in any direction of the sphere. These isotropic and surface conformal capabilities help for instance to make a piece of steel as light as aluminum and to save a lot of energy to produce the end material”, Bachmann outlines.
The lightweighting claim concerns reducing a component’s mass through its architecture; it does not mean changing the density of steel itself to that of aluminum.
According to Bachmann, Spherene’s solution can be used to design metamaterials based on plastics (filaments), metals, or even resins. Despite these varieties of materials, the Chief Innovation Officer says the solution is most advanced to produce parts in powder-based materials. “It does not matter if it is plastic or metal. Resin comes in 2nd position while FDM might take a longer time to print new materials developed with our technology”, he adds.
At the time of the interview, Spherene offered software licenses and a design service for organizations wishing to commission these structures.
Inverse design: research by Rayne Zheng’s team
Another research direction is AI-based inverse design. In October 2023, Berkeley Engineering reported on the work of Rayne Zheng’s team; he was then an associate professor of materials science and engineering. This approach is separate from Spherene’s commercial algorithm.
Zheng and his colleagues used machine learning to search for an architecture matching a desired mechanical response, then manufacture and test examples using 3D printing.
“With our method, a user can input the desired mechanical behavior described by a curve, and this data is then fed into the machine learning code to generate a design — a process that takes only a few seconds. And once that design is 3D printed, it will replicate the desired mechanical behavior,” said Zheng. “While still in its early stages, our machine learning-based design method can produce almost any type of material behavior with nearly 90% accuracy.”
To create their AI-based design approach, the researchers first had to develop and implement an integrated machine learning framework, which consists of an inverse prediction module and a forward validation module.
“The inverse module uses the desired mechanical behaviors to design the micro-structure of the material, and the designed material is passed to the forward module for the evaluation of its mechanical behaviors,” said Chansoo Ha, co-lead author of this study and formerly a postdoctoral researcher at Virginia Tech in Zheng’s lab. “This helps ensure that the desired properties are accurately reflected in the finished product.”
The work examines a family of cubic-symmetric, strut-based cells, using their configurations and tests to train and evaluate the model. Zheng’s quoted accuracy figure belongs to this study; it does not guarantee reproduction of every property with any material or process.
Conditions for industrial implementation
As with any new technology, the use of the Spherene API will require a learning curve. First and foremost, since “our technology is relatively new in the market. It’s crucial for the engineer to operate a shift from traditional engineering to modern engineering”, the Chief Innovation Officer says. The same argument was uttered multiple times when AM was not mature enough. Exploring the development of metamaterials requires a shift in mindset.
Second, integration with the existing workflow needs to be assessed. An API can facilitate exchanges between tools, but the geometry still needs to be prepared for the chosen process, manufactured and checked.
Third, licensing costs should be weighed against demonstrated savings. Bachmann points to several potential benefits, which need to be verified for each application:
- Design time: for one satellite application, Bachmann describes five minutes of computation avoiding twenty hours of engineering. This is a company-reported example; no detailed comparative protocol is supplied in this feature.
- Print supports: some geometries can avoid internal supports. This does not imply support-free printing in every respect: the titanium specimens in the bone-substitute study required supports connecting them to the build plate.
- Lightweighting: replacing part of a solid volume with an open architecture can reduce component mass, while still requiring its performance to be verified.
- Customization: combining solid sections, voids and gradients of apparent density can help adjust geometry, center of gravity or the desired mechanical response.
Applications and medical research
Metamaterials are being investigated in electronics, communications and defense. During the interview, Spherene cited an ESA satellite bracket, a waveguide and experimental bioceramic implants. The company also described tests of structures for footwear intended for people with diabetes; this feature does not provide evidence of clinical effectiveness for that application.
The study by Maevskaia and colleagues on hydroxyapatite bone substitutes compares ADMS architectures with a reference lattice. Its bone ingrowth experiments used a rabbit animal model. The most suitable ADMS architecture was similarly osteoconductive to the lattice, with greater compression strength and structural integrity under the conditions investigated. These preclinical results do not, on their own, demonstrate safety or effectiveness in humans, or establish market authorization.
This feature was first published in the March – April 2024 edition of 3D ADEPT Mag.
Review note: metamaterial terminology, the scope of performance claims and the preclinical nature of medical tests have been clarified. Interview quotations retain their historical context. An undated future product-release announcement has been removed.
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