Editorial Feature

Nanotechnology in Quantum Computing

By shrinking control to the atomic scale, scientists are unlocking new ways to build stable, scalable qubits, bringing real-world quantum computing a step closer. 

Image Credits: welcomia /shutterstock.com

Quantum computing uses qubits - quantum bits - to perform calculations that go far beyond what classical computers can handle. Nanotechnology plays a central role by making it possible to build and control these qubits with incredible precision. 

What is a Quantum Computer?

Quantum computing is a way of processing information that's based on the sometimes strange rules of quantum mechanics. Unlike traditional bits, which are either 0 or 1, quantum bits, or qubits, can be in both states at once, thanks to a property called superposition.

They can also become entangled, meaning the state of one qubit is linked to another, no matter the distance between them. These features give quantum computers the potential to solve problems that would take classical machines millions of years. 

But these quantum effects only appear at extremely small scales, typically a few nanometers, where materials behave very differently from their bulk counterparts. This is where nanotechnology comes in. It offers the tools to build and tweak materials at these tiny scales, allowing researchers to create qubits that are more stable and less prone to losing their quantum state.

Nanotech is also helping scientists design better layouts for quantum chips, improve gate performance, and experiment with early versions of error correction, key steps toward building quantum systems that actually work in practice.1,2 

Quantum Computers Explained: How Quantum Computing Works

Video Credit: Science ABC/YouTube.com

Controlled Realization of Heisenberg Spin Chains

Heisenberg spin chains are one-dimensional quantum systems where neighboring spins interact with each other. They're an important model for studying quantum magnetism and how qubits might interact one day. 

But building these chains in the lab, and controlling them at the atomic level, is difficult. Getting individual spins to stay put within just a few nanometers takes serious precision. 

Now, researchers at the Swiss Federal Laboratories for Materials Science and Technology (EMPA) have devised a way to do so. They used nanographene molecules known as Clar's Goblet to create linear spin chains on a gold surface.

Each molecule has unpaired electrons at either end, acting like tiny magnetic moments that can be linked into chains. 

By controlling the length of the chain and how each spin behaves, the team was able to directly observe spin interactions using tools with atomic-scale resolution. 

This offers a promising way to explore how qubits might communicate through spin-based systems, though in its current stage, it is still only for use in study and is not ready for real-world devices.3 

Fault-Tolerant Quantum Computing with Majorana Zero Modes 

Qubits are incredibly fragile. Even the slightest disturbance from their environment can throw them off, which is why so much of quantum research focuses on error correction. 

However, using particles like Majorana zero modes (MZMz), which are naturally less fragile because of their topology, could be a workaround. The challenge here is how to form MZMs cleanly and ensure they maintain stability in actual hardware.

In a study in Nature Nanotechnology, a team built a simple three-site Kitaev chain using InSb/Al nanowires and quantum dots linked by superconductors. This setup allowed them to better isolate and control the MZMs and showed improved stability compared to earlier designs. 

The project is still a long way from a topological quantum computer, but its work is solid proof of concept that nanostructures could play an integral role.4 

Precision Engineering of Silicon Carbide Qubits

At Argonne and Sandia National Laboratories, scientists are working with silicon carbide (SiC) to make qubits that are easier to control and read.

The researchers used ion implantation with sub-25 nm precision to create optically readable divacancy qubits in SiC. They then used advanced X-ray and nanoscale imaging to see how those defects formed and behaved at the atomic level.

Their findings confirmed that SiC can host stable qubits and that its properties can be finely tuned using existing fabrication methods.

It’s a promising step for building scalable quantum devices, though more work is needed to test how well these qubits hold up under longer use and more complex operations.5

Germanium-Based Quantum Circuits 

Materials like silicon and gallium arsenide have been the go-to for quantum experiments, but they still have limitations. Their weak spin-orbit coupling and sensitivity to noise make it harder to manipulate qubits quickly and reliably.

So a team at QuTech has turned to germanium. With strong spin-orbit coupling and low charge noise, it could offer improved performance in key areas.

Using advanced nanolithography and ultra-precise fabrication, the researchers built a 2×4 grid of quantum dots that housed four singlet–triplet qubits. They achieved high-fidelity one- and two-qubit operations and even managed entanglement swapping between qubits that weren’t directly connected, an important milestone for quantum networking and error correction.

These results show that germanium has real potential for building faster, more scalable quantum processors. However, singlet-triplet qubits are still one of several types being explored, and the field is far from settled.6

Industry-Compatible Silicon Spin Qubits

One of the biggest challenges in quantum tech has been the gap between lab-made qubits and mass-produced ones. It’s one thing to build a delicate quantum device by hand, another to make millions of them on a chip using industry tools.

A recent study indicates that gap may be narrowing. Published in Nature, researchers built two-qubit silicon devices using standard CMOS processes in a 300-mm foundry, usually used to make commercial computer chips. The devices achieved gate fidelities above 99 %, and coherence times as long as 9.5 seconds.

This is a major milestone. It shows that qubits with high stability and accuracy can be produced in volume using today's semiconductor tech. There’s still a lot to figure out before these chips can power a full quantum computer, but it’s a step toward bringing the hardware side of the field into the real world.7

Download to Learn More About Quantum Computing and Nanotechnology

Challenges and Future Outlooks

Even with these exciting advances, building a practical quantum computer is far from solved.

Qubits still suffer from noise and instability, often caused by fluctuations in charge or magnetic fields. And scaling things up adds a new set of problems: more qubits means more wiring, more control signals, and more chances for interference.

On top of that, quantum devices don’t yet have a common fabrication standard, making it harder to reproduce results or scale production efficiently.

Tackling these issues will require further collaboration between materials scientists, quantum physicists, and chip engineers. It’s not just about improving one part of the system; the whole computer should be designed together, from atoms to algorithms.

References and Further Reading

  1. Schneider, J., & Smalley, I. (2025). What is quantum computing? https://www.ibm.com/think/topics/quantum-computing
  2. Arne Laucht, Hohls, F., Niels Ubbelohde, M Fernando Gonzalez-Zalba, Reilly, D. J., Stobbe, S., Schröder, T., Scarlino, P., Koski, J. V., Dzurak, A., Yang, C.-H., Yoneda, J., Kuemmeth, F., Bluhm, H., Pla, J., Hill, C., Salfi, J., Akira Oiwa, Muhonen, J. T., & Verhagen, E. (2021). Roadmap on quantum nanotechnologies. Nanotechnology, 32(16), 162003–162003. https://doi.org/10.1088/1361-6528/abb333
  3. Zhao, C., Catarina, G., Zhang, J., Henriques, J. C., Yang, L., Ma, J., Feng, X., Gröning, O., Ruffieux, P., & Fasel, R. (2024). Tunable topological phases in nanographene-based spin-1/2 alternating-exchange Heisenberg chains. Nature Nanotechnology, 19(12), 1789-1795. https://doi.org/10.1038/s41565-024-01805-z
  4. Bordin, A., Liu, C., Dvir, T., Zatelli, F., Ten Haaf, S. L., Van Driel, D., Wang, G., Van Loo, N., Zhang, Y., Wolff, J. C., Van Caekenberghe, T., Badawy, G., Gazibegovic, S., Bakkers, E. P., Wimmer, M., Kouwenhoven, L. P., & Mazur, G. P. (2025). Enhanced Majorana stability in a three-site Kitaev chain. Nature Nanotechnology, 20(6), 726-731. https://doi.org/10.1038/s41565-025-01894-4
  5. Hesla, L. (2024). Argonne, Sandia scientists create qubits using precision tools of nanotechnology. https://www.anl.gov/article/argonne-sandia-scientists-create-qubits-using-precision-tools-of-nanotechnology
  6. Zhang, X., Morozova, E., Jirovec, D., Hsiao, T., Fariña, P. C., Wang, C., Oosterhout, S. D., Sammak, A., Scappucci, G., Veldhorst, M., & Vandersypen, L. M. (2025). Universal control of four singlet–triplet qubits. Nature Nanotechnology, 20(2), 209-215. https://doi.org/10.1038/s41565-024-01817-9
  7. Steinacker, P., Dumoulin Stuyck, N., Lim, W. H., Tanttu, T., Feng, M., Serrano, S., Nickl, A., Candido, M., Cifuentes, J. D., Vahapoglu, E., Bartee, S. K., Hudson, F. E., Chan, K. W., Kubicek, S., Jussot, J., Canvel, Y., Beyne, S., Shimura, Y., Loo, R., . . .  Dzurak, A. S. (2025). Industry-compatible silicon spin-qubit unit cells exceeding 99% fidelity. Nature, 646(8083), 81-87. https://doi.org/10.1038/s41586-025-09531-9

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Article Revisions

  • Oct 13 2025 - Adding content to engage readers and in depth explainers.
  • Oct 13 2025 - Updating the article to in line with the changes/advances that have occurred over the last decade.
Owais Ali

Written by

Owais Ali

NEBOSH certified Mechanical Engineer with 3 years of experience as a technical writer and editor. Owais is interested in occupational health and safety, computer hardware, industrial and mobile robotics. During his academic career, Owais worked on several research projects regarding mobile robots, notably the Autonomous Fire Fighting Mobile Robot. The designed mobile robot could navigate, detect and extinguish fire autonomously. Arduino Uno was used as the microcontroller to control the flame sensors' input and output of the flame extinguisher. Apart from his professional life, Owais is an avid book reader and a huge computer technology enthusiast and likes to keep himself updated regarding developments in the computer industry.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Ali, Owais. (2025, October 14). Nanotechnology in Quantum Computing. AZoNano. Retrieved on November 25, 2025 from https://www.azonano.com/article.aspx?ArticleID=3251.

  • MLA

    Ali, Owais. "Nanotechnology in Quantum Computing". AZoNano. 25 November 2025. <https://www.azonano.com/article.aspx?ArticleID=3251>.

  • Chicago

    Ali, Owais. "Nanotechnology in Quantum Computing". AZoNano. https://www.azonano.com/article.aspx?ArticleID=3251. (accessed November 25, 2025).

  • Harvard

    Ali, Owais. 2025. Nanotechnology in Quantum Computing. AZoNano, viewed 25 November 2025, https://www.azonano.com/article.aspx?ArticleID=3251.

Comments

  1. Joseph Conner Joseph Conner United States says:

    What an interesting and I formative article about quantum computing.

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoNano.com.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this article?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.