Editorial Feature

Paragraf's Graphene Sensor Stays Cool for Quantum Computing

Paragraf is a Cambridge-based startup that was spun out of Cambridge University's Department of Materials Engineering. Paragraf has created a patented graphene deposition technique on silicon, SiO2, sapphire, and other semiconducting substrates.

Paragraf

Image Credit:  Kirill Volkov/Shutterstock.com

This method is flexible and compatible with current production procedures for electrical devices. Their initial product, a graphene Hall-effect sensor for detecting magnetic fields in harsh conditions, was developed and commercialized. Galanis and Allan are the product owners of the graphene Hall sensor and the graphene fabrication and device manufacturing lead at Paragraf, respectively.

Why Graphene?

For the last decade, graphene has been the most thoroughly investigated 2D material and with good reason.

As graphene is just one atom thick, its use could lead to a day when electronics will be flexible, transparent, and resistant to the impacts of stray magnetic fields, all of which are critical for developing elevated Hall effect sensors.

Benefits of Graphene Sensors

Excellent quality graphene with extremely high mobility may be incorporated into sensing technologies thanks to Paragraf's contamination-free direct-to-wafer deposition method. Resistance to in-plane stray fields resulting in substantially lower insulating requirements, high sensitivity and low distortion, reliability with no oscillation and no saturation in yield, and implementation at mK with relatively low heat input are all advantages of graphene Hall effect sensors.

GHS-C, A Graphene-Based Hall Sensor for Quantum Computing

The GHS-C, a graphene-based Hall sensor designed for high field observations while functioning at extremely low temperatures, has reached volume production at Paragraf. It does this with almost negligible heat dissipation.

The cryogenic sensor also enables cold bore measurements without room temperature inserts, resulting in high-quality data and significant time savings. One of the major obstacles that scientists and developers working at very low temperatures encounter when striving for high sensitivity is the instability created by the heat wasted by traditional sensors.

When working with low - temperature applications, such as quantum computing, this is very important. Instead of mWs, GHS-C dissipates nW of heat. This has a far lower influence on the instrument, enabling researchers to take more precise and reproducible measurements.

More precise analysis of material characteristics at temperature extremes and magnetic forces is one of the advantages of the GHS-C sensor. 

The GHS-C also has a very low power consumption, which keeps the heat load on the frigid fingers to a minimum. The GHS-C seems to be the only Hall sensor in mass production today that can achieve this performance level at temperatures lower than 3 K.

The technology involved can operate at much lower temperatures without losing performance. This is made feasible by graphene's absence of a planar Hall Effect, a distinctive property that Paragraf has exploited.

The GHS-C sensor allows commercial organizations to precisely detect high strong magnetic strengths at extremely low temperatures, allowing them to increase production throughput by replacing traditional NMR probe mapping procedures with faster magnet imaging. The cryogenic sensors also permit measurements in cold bore, eliminating the requirement for ambient temperature inserts and enabling faster data collecting.

Applications of GHS-C, Paragraf's New Graphene Sensor

The GHS-C employs graphene that has been optimized and tailored for high-field applications such as superconduction, quantum computing, high-energy thermodynamics, low-temperature physics, fusion, and space exploration.

Furthermore, since the next era of particle accelerators will depend on magnets with field strengths greater than 16 T, the GHS-C is already attracting attention from industry experts.

Market Overview

The already sizable worldwide magnetic sensor industry (of which Hall-Effect sensors account for the bulk) is continuously rising. Despite their extensive use, there is still room to expand the use of Hall-Effect sensor applications, especially with higher-performance devices, and there is a clear chance for graphene to demonstrate its worth.

The Verdict

As we have seen, typical Hall-Effect sensor devices have several limitations in terms of sensitivity, precision, and the impact of temperature on their performance. Paragraf's new graphene-based GHS series sensors will be capable of supporting operating parameters that are well above what can be achieved by traditional devices.

Because graphene is a two-dimensional material (with a subatomic particle thickness), it does not suffer from the typical planar Hall-Effect problems, with the sensor element simply registering the perpendicular magnetic field.

Continue reading: Ultra-Sensitive Graphene-Based Sensors for Next-Generation Surgical Robotics

References and Further Reading

Paragraf (2020) Paragraf partners with CERN to demonstrate unique properties of Paragraf's new Graphene Hall Effect Sensor. [online​​​​​​​]. Available at: https://www.paragraf.com/news/paragraf-partners-with-cern-to-demonstrate-unique-properties-of-paragrafs-new-graphene-hall-effect-sensor/

Tibbetts, J., (2019) Quantum computing and cryptography: Analysis, risks, and recommendations for decisionmakers. United States​​​. [online] Available at: https://doi.org/10.2172/1566798​​​​​​​​​​

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.

Shaheer Rehan

Written by

Shaheer Rehan

Shaheer is a graduate of Aerospace Engineering from the Institute of Space Technology, Islamabad. He has carried out research on a wide range of subjects including Aerospace Instruments and Sensors, Computational Dynamics, Aerospace Structures and Materials, Optimization Techniques, Robotics, and Clean Energy. He has been working as a freelance consultant in Aerospace Engineering for the past year. Technical Writing has always been a strong suit of Shaheer's. He has excelled at whatever he has attempted, from winning accolades on the international stage in match competitions to winning local writing competitions. Shaheer loves cars. From following Formula 1 and reading up on automotive journalism to racing in go-karts himself, his life revolves around cars. He is passionate about his sports and makes sure to always spare time for them. Squash, football, cricket, tennis, and racing are the hobbies he loves to spend his time in.

Citations

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

  • APA

    Rehan, Shaheer. (2022, February 10). Paragraf's Graphene Sensor Stays Cool for Quantum Computing. AZoSensors. Retrieved on October 30, 2024 from https://www.azosensors.com/article.aspx?ArticleID=2454.

  • MLA

    Rehan, Shaheer. "Paragraf's Graphene Sensor Stays Cool for Quantum Computing". AZoSensors. 30 October 2024. <https://www.azosensors.com/article.aspx?ArticleID=2454>.

  • Chicago

    Rehan, Shaheer. "Paragraf's Graphene Sensor Stays Cool for Quantum Computing". AZoSensors. https://www.azosensors.com/article.aspx?ArticleID=2454. (accessed October 30, 2024).

  • Harvard

    Rehan, Shaheer. 2022. Paragraf's Graphene Sensor Stays Cool for Quantum Computing. AZoSensors, viewed 30 October 2024, https://www.azosensors.com/article.aspx?ArticleID=2454.

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.