How origami inspires world-changing technology

While styles of origami can be incredibly diverse, the art is rooted in mathematical principles that make it applicable to science and industry.

The ability to fold two-dimensional structures into complex, yet compact three-dimensional shapes is especially valuable to space sciences and missions, where it pays to keep payloads small.

Panel arrays on satellites must be folded down into compact forms in order to pack them into a relatively narrow rocket, and only unfurled to form large flat surfaces once the rocket has blasted into outer space. It’s thought that the first origami solar array was packed into a Japanese spacecraft that launched in 1995. This was accomplished using the Miura fold, which is a method of folding a flat surface into a smaller area and named after astrophysicist Koryo Miura. A form of rigid origami, where a material only bends at pre-specified fold lines, the crease patterns of the Miura fold form a tessellation of the surface by parallelograms.

Scientists at Nasa’s Jet Propulsion Laboratory are putting origami to a similar use to help capture images of planets outside our solar system by developing ‘Starshade’, a shield for use on space telescopes.

Starlight can prevent space telescopes from imaging the low-intensity light reflected off exoplanets. In the same way as we shield our eyes from the glare of the Sun by placing our hand at arm’s length in front of our face, this new device could shield a telescope’s camera from the light of a distant star. The concept is known as the Hybrid Observatory for Earth-like Exoplanets. Flying tens of thousands of kilometres in front of a space telescope, Starshade’s precise design would block light from a star so the telescope might be able to capture an image of the planets around the star.

The sunflower-shaped shade of the proposed Starshade is designed to be 36m in diameter but must fold down to less than 2.5m in diameter when stowed for launch. Origami concepts have been used to help work out the stow pattern. Experts developed algorithms allowing them to input specs, press enter and create a new pattern instead of having to make models and refold them over and over again.

Starshade is still in development and details are far from finalised, but you can make your own paper origami model of Starshade’s inner disc optical shield by following instructions on the Jet Propulsion Laboratory website.

Concepts from origami are shaping medical research and the creation of medical devices. Researchers at the University of Cambridge’s Centre for Misfolding Diseases, including Ryan Geiser, a PhD candidate who lost his grandfather to Alzheimer’s, are using artificial intelligence (AI) to better understand the folding and misfolding of proteins that could unlock secrets about Alzheimer’s disease.

The debilitating disease affects around 57 million people worldwide. According to a leading hypothesis, it is caused by the abnormal misfolding or the build-up of proteins in and around brain cells. This build-up leads to a decrease in neurotransmitters that, over time, causes different areas of the brain to shrink, with devastating results.

Geiser finds it helpful to compare folding proteins to origami. “Just as paper must be folded into a particular structure to make a specific origami shape, in a cell, proteins are supposed to fold in a specific way, so each protein can carry out a certain function, with sticky spots within the protein holding the structure in place,” he explains. Alzheimer’s disease develops after some proteins in the brain fold incorrectly so that sticky spots are exposed outside of a protein. These toxic species can impair cell walls and create a cascade that recruits other proteins to clump together, causing a build-up that stops nutrients from reaching neurons. “Without these nutrients, along with subsequent issues, the brain cells are destroyed.”

Geiser is using study data and AI to identify existing drugs that might be able to slow or stop the progression of Alzheimer’s disease. So far, his team has identified four calcium-channel blocker drugs that may have potential to be repurposed for treating dementia, and this is just the beginning.

“Many computational models are trying to understand ‘origami’ structures and, as computational power increases, this may become more achievable,” Geiser says. Coupled with advances such as DeepMind – a subsidiary of Alphabet – releasing the AlphaFold Protein Structure Database, which shares predicted structures for nearly all catalogued proteins known to science with researchers, it’s likely that many more mysteries behind diseases will soon be revealed.

Concepts from origami can also be used to develop medical devices. Designs that start in a compact form and then morph into a functional form enable less invasive methods of treatment delivery, in which medical devices travel through the body to previously unreachable areas. For example, researchers at the University of Oxford developed a novel aortic heart stent to treat aneurisms that was reportedly inspired by an origami water bomb. Origami’s influence can be seen in a wide range of medical devices, from an X-ray shroud to tetherless microgrippers.

Using the DNA origami method, scientists at the Centre for Structural Biology at the University of Montpellier have constructed a tiny robot to study mechanical forces applied at microscopic levels, which are crucial for many biological and pathological processes. The method enables the self-assembly of 3D nanostructures in a pre-defined form using the DNA molecule as construction material.

The researchers designed a ‘nano-robot’ approximately the size of a human cell composed of three DNA origami structures, making it possible for the first time to apply and control a force with a resolution of one piconewton, which is one-trillionth of a newton, or approximately one-trillionth of the force of a finger clicking on a pen. The team began by coupling the robot with a molecule that recognises a mechanoreceptor, which made it possible to direct the robot to some of the cells and apply forces to targeted mechanoreceptors on the surface of the cells in order to activate them.

This is the first time that a human-made, self-assembled DNA-based object can apply force with this accuracy. The tool is valuable for research as it could be used to better understand the molecular mechanisms involved in cell mechanosensitivity, the dysfunction of which is involved in many diseases, including cancer.

Origami could also be used for large objects from furniture to buildings and infrastructure. Researchers from Georgia Tech, the University of Illinois at Urbana-Champaign and the University of Tokyo have developed a ‘zippered tube’ origami configuration that makes paper structures stiff enough to hold weight while still being able to fold flat for easy shipping and storage. The researchers used Miura-Ori folding to make precise, zigzag-folded strips of paper, then glued two strips together to make a tube. While the single strip of paper is highly flexible, the tube is stiffer and does not fold in as many directions. They hope their method will be applied to other thin materials, such as plastic or metal, to create furniture or buildings.

Ichiro Ario of Hiroshima University tested an origami-inspired Mobile Bridge Version 4.0 (MB4.0) in 2015 that he designed to assist the transport of aid to disaster zones where permanent infrastructure had been destroyed. Its scissor design relies on ‘X’ shapes to retain strength while being quickly deployed in areas where existing bridges and access points have been damaged. Tests showed it could be assembled in one hour, with the actual bridge extension taking just five minutes.

Researchers at Georgia Tech are exploring whether a new class of origami- and kirigami-inspired flexible, lightweight structures could adapt to changing environmental conditions. (Kirigami is when paper is cut as well as folded.) They hope these will one day be used in a range of applications, from multifunctional robots and collapsible antennas to rapidly assembled bridges and temporary structures such as inflatable shelters.

Engineers have also drawn inspiration from the art of origami to create programmable surfaces so their dimensions and corresponding properties can shift as needed. Their technique could one day be applied to aerospace and architecture, for example.

To create the structures, an international team of researchers began with cells of four kite-shaped figures, or rhombuses. Each rhombus is connected to two others along two sides, with a tail end of each rhombus free. The connecting sides are hinged in special ways, so each cell can click through a variety of forms, from a wide basket to thin folds. This means they can be combined to make a wide range of surfaces and, when the cells are adjusted, the compressibility, flexibility and density of the surface can be changed.

The technique takes advantage of a phenomenon that physicists call ‘frustration’. In geometry, frustration is a feature that stops a pattern from propagating across a wide space, like a jagged rock in a snowfield. With the adjustable cells, the researchers can introduce frustration into structures. They use this to change the properties of the surface. They can do so over wide areas and small spots.

The researchers can use these engineered frustrations to precisely change the patterns of the surface and, by doing so, they can adjust the surface’s properties. “Usually, a single origami pattern has one specific mechanical property,” says Tomohiro Tachi, one of the researchers and a professor at the University of Tokyo. “This structure can switch between multiple states that have distinct properties. It is a universal module for programming and reprogramming materials with versatile properties.”

Origami is already transforming space travel and medicine, but applying artificial intelligence to the art form could lead to more breakthroughs.

While computers are already used to help develop folding structures, it is hard to predict whether a 3D origami design can be flattened effectively and without any damage simply by looking at it. But new work from the UvA Institute of Physics and research institute AMOLF has demonstrated that machine-learning algorithms can accurately do this, or in more technical terms, whether it can predict the properties of combinatorial mechanical metamaterials.

AI should make designing new metamaterials slightly easier by reducing the need for time-consuming trial and error. The team found that even when given only a relatively small set of examples to learn from, so-called convolutional neural networks are able to accurately predict the metamaterial properties of any configuration of building blocks down to the finest detail.

“This far exceeded our expectations,” says PhD student Ryan van Mastrigt, who led the study. “The accuracy of the predictions shows us that the neural networks have actually learned the mathematical rules underlying the metamaterial properties, even when we don’t know all the rules ourselves.”

This suggests that engineers could use AI to design new complex metamaterials with useful properties, which could make everything from tiny folding medical devices, to enormous easy-to-assemble temporary infrastructure a reality.

We’ll just have to wait to see what unfolds.