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Programmable matter

Programmable matter is a engineering topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Programmable matter rather than just read about it. In short: Programmable matter is matter which has the ability to change its physical properties (shape, density, moduli, conductivity, optical properties, etc.) in a programmable fashion, based upon user input or autonomous sensing. Programmable matter is thus linked to the concept of a material which inherently has the ability to perform information processing.

Programmable matter — main illustration
Programmable matter — illustration

Key takeaways

  • Programmable matter belongs to engineering; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Programmable matter to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Programmable matter from memory before moving on to harder problems.

Reference excerpt

Programmable matter is matter which has the ability to change its physical properties (shape, density, moduli, conductivity, optical properties, etc.) in a programmable fashion, based upon user input or autonomous sensing. Programmable matter is thus linked to the concept of a material which inherently has the ability to perform information processing.

History Programmable matter is a term originally coined in 1991 by Toffoli and Margolus to refer to an ensemble of fine-grained computing elements arranged in space. Their paper describes a computing substrate that is composed of fine-grained compute nodes distributed throughout space which communicate using only nearest neighbor interactions. In this context, programmable matter refers to compute models similar to cellular automata and lattice gas automata. The CAM-8 architecture is an example hardware realization of this model. This function is also known as "digital referenced areas" (DRA) in some forms of self-replicating machine science. In the early 1990s, there was a significant amount of work in reconfigurable modular robotics with a philosophy similar to programmable matter. As semiconductor technology, nanotechnology, and self-replicating machine technology have advanced, the use of the term programmable matter has changed to reflect the fact that it is possible to build an ensemble of elements which can be "programmed" to change their physical properties in reality, not just in simulation. Thus, programmable matter has come to mean "any bulk substance which can be programmed to change its physical properties." In the summer of 1998, in a discussion on artificial atoms and programmable matter, Wil McCarthy and G. Snyder coined the term "quantum wellstone" (or simply "wellstone") to describe this hypothetical but plausible form of programmable matter. McCarthy has used the term in his fiction. In 2002, Seth Goldstein and Todd Mowry started the claytronics project at Carnegie Mellon University to investigate the underlying hardware and software mechanisms necessary to realize programmable matter. In 2004, the DARPA Information Science and Technology group (ISAT) examined the potential of programmable matter. This resulted in the 2005–2006 study "Realizing Programmable Matter", which laid out a multi-year program for the research and development of programmable matter. In 2007, programmable matter was the subject of a DARPA research solicitation and subsequent program. From 2016 to 2022, the ANR has funded several research programs coordinated by Julien Bourgeois and Benoit Piranda at the FEMTO-ST Institute, which is taking the lead in the Claytronics project initiated by Intel and Carnegie Mellon University. In 2025 as an extension to Programmable Matter, the term Programmable Quantum Matter was coined by a team at Massachusetts Institute of Technology led by Dirk Englund, proposing a scalable architecture to construct large-scale quantum cluster states using solid-state qubits. Programmable Quantum Matter is also being developed using neutral atoms to create a quantum simulator. The connection between a cellular automata based programmable matter and cluster state based quantum computing is deeply connected via graph states and an interesting research direction.

Approaches In one school of thought, the programming could be external to the material and might be achieved by the "application of light, voltage, electric or magnetic fields, etc." (McCarthy 2006). For example, a liquid crystal display is a form of programmable matter. A second school of thought is that the individual units of the ensemble can compute and the result of their computation is a change in the ensemble's physical properties. An example of this more ambitious form of programmable matter is claytronics. There are many proposed implementations of programmable matter. Scale is one key differentiator between different forms of programmable matter. At one end of the spectrum, reconfigurable modular robotics pursues a form of programmable matter where the individual units are in the centimeter size range. At the nanoscale end of the spectrum, there are a tremendous number of different bases for programmable matter, ranging from shape changing molecules to quantum dots. Quantum dots are in fact often referred to as artificial atoms. In the micrometer to sub-millimeter range examples include MEMS-based units, cells created using synthetic biology, and the utility fog concept. An important sub-group of programmable matter are robotic materials, which combine the structural aspects of a composite with the affordances offered by tight integration of sensors, actuators, computation, and communication, while foregoing reconfiguration by particle motion.

Examples There are many conceptions of programmable matter, and thus many discrete avenues of research using the name. Below are some specific examples of programmable matter.

"Solid-liquid phase-change pumping" Shape-changing and locomotion of solid objects are possible with solid-liquid phase change pumping. This approach allows deforming objects into any intended shape with sub-millimetre resolution and freely changing their topology.

"Simple" These include materials that can change their properties based on some input, but do not have the ability to do complex computation by themselves.

Complex fluids

The physical properties of several complex fluids can be modified by applying a current or voltage, as is the case with liquid crystals.

Metamaterials

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Programmable matter

Start with the simplest possible case. Write down what Programmable matter claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In engineering, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Programmable matter before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Programmable matter ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Programmable matter

In research
Programmable matter appears in engineering research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Programmable matter in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Programmable matter is common in secondary-school and first-year university syllabi. It links to neighbouring topics Robotics engineering, Smart materials, Synthetic biology, so understanding it makes those chapters shorter.
In everyday life
Look for Programmable matter outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Programmable matter in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Programmable matter means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Programmable matter out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Programmable matter in simple terms?

Programmable matter is matter which has the ability to change its physical properties (shape, density, moduli, conductivity, optical properties, etc.) in a programmable fashion, based upon user input or autonomous sensing. Programmable matter is thus linked to the concept of a material which inhere…

Why does Programmable matter matter?

Because it connects several engineering ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Programmable matter?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Programmable matter.

Tags

  • Robotics engineering
  • Smart materials
  • Synthetic biology

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