̽��ֱ�� of Cambridge - graphene

̽��ֱ�� spin-out secures funding to improve AI energy efficiency and bandwidth

Anonymous — Mon, 24 Mar 2025 14:24:15 +0000

CamGraPhIC - co-founded Professor Andrea Ferrari, Director of the Cambridge Graphene Centre, and Dr Marco Romagnoli of CNIT in Italy - is developing new types of photonic circuits for energy-efficient, high-bandwidth, optical interconnect technology.

̽��ֱ��investment will support continued innovation in graphene photonics transceivers, a technology that could improve energy efficiency, reduce latency, and increase bandwidth for artificial intelligence (AI) and cellular data transmission.

With the investment, CamGraPhIC will enhance its research and development capabilities and establish a pilot manufacturing line. ̽��ֱ��facility will demonstrate a scalable mass production process compatible with commercial semiconductor and photonics foundries.

̽��ֱ��funding round was co-led by CDP Venture Capital, NATO Innovation Fund, Sony Innovation Fund, and Join Capital, with participation from Bosch Ventures, Frontier IP Group plc, and Indaco Ventures.

CamGraPhIC’s graphene-based transceivers provide a viable, stable, and scalable alternative to current silicon-based photonics. These transceivers deliver higher bandwidth density, and exceptional latency performance, while consuming 80% less energy than traditional pluggable data centre optical transceivers.

̽��ֱ��company say their innovation is particularly effective for transferring large volumes of data between graphic processing units (GPUs) and high bandwidth memory (HBM), which are fundamental to generative AI and high-performance computing.

̽��ֱ��transceivers operate efficiently across a broad temperature range, eliminating the need for complex and costly cooling systems. Thanks to a simplified device architecture enabled by the integration of graphene into the photonic structure, these transceivers are also more cost-effective to manufacture.

Thanks to this funding, CamGraPhIC will expand to applications in avionics, automotive advanced driver-assistance systems (ADAS), and space, where rugged, high-performance transceivers offer significant technical and commercial advantages over existing technologies.

“We are thrilled for this new phase in the journey towards commercialisation of CamGraPhIC groundbreaking and energy efficient devices, to speed up development of AI hardware, without impacting global emissions,” said Ferrari. “Having Sony, Bosch and NATO as shareholders and board members will help focus the work towards the most relevant applications, including defence and security.”

“With the backing of renowned investors, we are excited to propel towards commercialisation the Graphene Photonics technology to overcome the interconnection bottleneck of regenerative AI processing systems and driving the next leap in scaling bandwidth and reducing energy consumption for the future of optical data communications, ” said Romagnoli, former Head of Research Sector - Advanced Technologies for Photonic Integration of the Pisa National Inter- ̽��ֱ�� Consortium for Telecommunications (CNIT), and now Chief Scientific Officer of CamGraPhIC.

A ̽��ֱ�� of Cambridge spin-out company working to improve AI efficiency and bandwidth has raised €25 million in new funding.

CamGraPhIC

Marco Romagnoli (L) and Andrea Ferrari (R)

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Scientists develop ‘smart pyjamas’ to monitor sleep disorders

sc604 — Tue, 18 Feb 2025 11:06:44 +0000

̽��ֱ��team, led by the ̽��ֱ�� of Cambridge, developed printed fabric sensors that can monitor breathing by detecting tiny movements in the skin, even when the pyjamas are worn loosely around the neck and chest.

̽��ֱ��sensors embedded in the smart pyjamas were trained using a ‘lightweight’ AI algorithm and can identify six different sleep states with 98.6% accuracy, while ignoring regular sleep movements such as tossing and turning. ̽��ֱ��energy-efficient sensors only require a handful of examples of sleep patterns to successfully identify the difference between regular and disordered sleep.

̽��ֱ��researchers say that their smart pyjamas could be useful for the millions of people in the UK who struggle with disordered sleep to monitor their sleep, and how it might be affected by lifestyle changes. ̽��ֱ��results are reported in the Proceedings of the National Academy of Sciences (PNAS).

Sleep is vital for human health, yet more than 60% of adults experience poor sleep quality, leading to the loss of between 44 and 54 annual working days, and an estimated one percent reduction in global GDP. Sleep behaviours such as mouth breathing, sleep apnoea and snoring are major contributors to poor sleep quality, and can lead to chronic conditions such as cardiovascular disease, diabetes and depression.

“Poor sleep has huge effects on our physical and mental health, which is why proper sleep monitoring is vital,” said Professor Luigi Occhipinti from the Cambridge Graphene Centre, who led the research. “However, the current gold standard for sleep monitoring, polysomnography or PSG, is expensive, complicated and isn’t suitable for long-term use at home.”

Home devices that are simpler than PSG, such as home sleep tests, typically focus on a single condition and are bulky or uncomfortable. Wearable devices such as smartwatches, while more comfortable to wear, can only infer sleep quality, and are not effective for accurately monitoring disordered sleep.

“We need something that is comfortable and easy to use every night, but is accurate enough to provide meaningful information about sleep quality,” said Occhipinti.

To develop the smart pyjamas, Occhipinti and his colleagues built on their earlier work on a smart choker for people with speech impairments. ̽��ֱ��team re-designed the graphene-based sensors for breath analysis during sleep, and made several design improvements to increase sensitivity.

“Thanks to the design changes we made, the sensors are able to detect different sleep states, while ignoring regular tossing and turning,” said Occhinpinti. “ ̽��ֱ��improved sensitivity also means that the smart garment does not need to be worn tightly around the neck, which many people would find uncomfortable. As long as the sensors are in contact with the skin, they provide highly accurate readings.”

̽��ֱ��researchers designed a machine learning model, called SleepNet, that uses the signals captured by the sensors to identify sleep states including nasal breathing, mouth breathing, snoring, teeth grinding, central sleep apnoea (CSA), and obstructive sleep apnoea (OSA). SleepNet is a ‘lightweight’ AI network, that reduces computational complexity to the point where it can be run on portable devices, without the need to connect to computers or servers.

“We pruned the AI model to the point where we could get the lowest computational cost with the highest degree of accuracy,” said Occhinpinti. “This way we are able to embed the main data processors in the sensors directly.”

̽��ֱ��smart pyjamas were tested on healthy patients and those with sleep apnoea, and were able to detect a range of sleep states with an accuracy of 98.6%. By treating the smart pyjamas with a special starching step, they were able to improve the durability of the sensors so they can be run through a regular washing machine.

̽��ֱ��most recent version of the smart pyjamas are also capable of wireless data transfer, meaning the sleep data can be securely transferred to a smartphone or computer.

“Sleep is so important to health, and reliable sleep monitoring can be key in preventative care,” said Occhipinti. “Since this garment can be used at home, rather than in a hospital or clinic, it can alert users to changes in their sleep that they can then discuss with their doctor. Sleep behaviours such as nasal versus mouth breathing are not typically picked up in an NHS sleep analysis, but it can be an indicator of disordered sleep.”

̽��ֱ��researchers are hoping to adapt the sensors for a range of health conditions or home uses, such as baby monitoring, and have been in discussions with different patient groups. They are also working to improve the durability of the sensors for long-term use.

̽��ֱ��research was supported in part by the EU Graphene Flagship, Haleon, and the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).

Reference:
Chenyu Tang, Wentian Yi et al. ‘A deep learning-enabled smart garment for accurate and versatile monitoring of sleep conditions in daily life.’ PNAS (2025). DOI: 10.1073/pnas.2420498122

Researchers have developed comfortable, washable ‘smart pyjamas’ that can monitor sleep disorders such as sleep apnoea at home, without the need for sticky patches, cumbersome equipment or a visit to a specialist sleep clinic.

We need something that is comfortable and easy to use every night, but is accurate enough to provide meaningful information about sleep quality

Luigi Occhipinti

Illustration and photograph of 'smart pyjamas'

Yes

‘Smart choker’ uses AI to help people with speech impairment to communicate

sc604 — Fri, 13 Sep 2024 13:40:19 +0000

̽��ֱ��smart choker, developed by researchers at the ̽��ֱ�� of Cambridge, incorporates electronic sensors in a soft, stretchable fabric, and is comfortable to wear. ̽��ֱ��device could be useful for people who have temporary or permanent speech impairments, whether due to laryngeal surgery, or conditions such as Parkinson’s, stroke or cerebral palsy.

By incorporating machine learning techniques, the smart choker can also successfully recognise differences in pronunciation, accent and vocabulary between users, reducing the amount of training required.

̽��ֱ��choker is a type of technology known as a silent speech interface, which analyses non-vocal signals to decode speech in silent conditions – the user only needs to mouth the words in order for them to be captured. ̽��ֱ��captured speech signals can then be transferred to a computer or speaker to facilitate conversation.

Tests of the smart choker showed it could recognise words with over 95% accuracy, while using 90% less computational energy than existing state-of-the art technologies. ̽��ֱ��results are reported in the journal npj Flexible Electronics.

“Current solutions for people with speech impairments often fail to capture words and require a lot of training,” said Dr Luigi Occhipinti from the Cambridge Graphene Centre, who led the research. “They are also rigid, bulky and sometimes require invasive surgery to the throat.”

̽��ֱ��smart choker developed by Occhipinti and his colleagues outperforms current technologies on accuracy, requires less computing power, is comfortable for users to wear, and can be removed whenever it’s not needed. ̽��ֱ��choker is made from a sustainable bamboo-based textile, with strain sensors based on graphene ink incorporated in the fabric. When the sensors detect any strain, tiny, controllable cracks form in the graphene. ̽��ֱ��sensitivity of the sensors is more than four times higher than existing state of the art.

“These sensors can detect tiny vibrations, such as those formed in the throat when whispering or even silently mouthing words, which makes them ideal for speech detection,” said Occhipinti. “By combining the ultra-high sensitivity of the sensors with highly efficient machine learning, we’ve come up with a device we think could help a lot of people who struggle with their speech.”

Vocal signals are incredibly complex, so associating a specific signal with a specific word requires a high level of computational processing. “On top of that, every person is different in terms of the way they speak, and machine learning gives us the tools we need to learn and adapt the interpretation of signals from person to person,” said Occhipinti.

̽��ֱ��researchers trained their machine learning model on a database of the most frequently used words in English, and selected words which are frequently confused with each other, such as ‘book’ and ‘look’. ̽��ֱ��model was trained with a variety of users, including different genders, native and non-native English speakers, as well as people with different accents and different speaking speeds.

Thanks to the device’s ability to capture rich dynamic signal characteristics, the researchers found it possible to use lightweight neural network architectures with simplified depth and signal dimensions to extract and enhance the speech information features. This resulted in a machine learning model with high computational and energy efficiency, ideal for integration in battery-operated wearable devices with real-time AI processing capabilities.

“We chose to train the model with lots of different English speakers, so we could show it was capable of learning,” said Occhipinti. “Machine learning has the capability to learn quickly and efficiently from one user to the next, so the retraining process is quick.”

Tests of the smart choker showed it was 95.25% accurate in decoding speech. “I was surprised at just how sensitive the device is,” said Occhipinti. “We couldn’t capture all the signals and complexity of human speech before, but now that we can, it unlocks a whole new set of potential applications.”

Although the choker will have to undergo extensive testing and clinical trials before it is approved for use in patients with speech impairments, the researchers say that their smart choker could also be used in other health monitoring applications, or for improving communication in noisy or secure environments.

̽��ֱ��research was supported in part by the EU Graphene Flagship and the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).

Reference:
Chenyu Tang et al. ‘Ultrasensitive textile strain sensors redefine wearable silent speech interfaces with high machine learning efficiency.’ npj Flexible Electronics (2024). DOI: 10.1038/s41528-024-00315-1

Researchers have developed a wearable ‘smart choker’ that uses a combination of flexible electronics and artificial intelligence techniques to allow people with speech impairments to communicate by detecting tiny movements in the throat.

Luigi Occhipinti

Smart Choker

Yes

Graphene heads to the moon

sc604 — Wed, 30 Nov 2022 15:35:21 +0000

Cambridge researchers are part of a European project testing graphene’s ability to protect spacecraft against the sticky, sharp dust on the moon’s surface – a challenge for lunar missions since the Apollo era.

Artificial intelligence powers record-breaking all-in-one miniature spectrometers

sc604 — Thu, 20 Oct 2022 18:00:00 +0000

We see light and colours around us every day. However, to analyse the information it carries, we must analyse light using spectrometers, in the lab. These devices detect sparkles and substances that our eyes would otherwise not notice.

Now, an international team of researchers, including the ̽��ֱ�� of Cambridge, have designed a miniaturised spectrometer that breaks all current resolution records, and does so in a much smaller package, thanks to computational programmes and artificial intelligence.

̽��ֱ��new miniaturised devices could be used in a broad range of sectors, from checking the quality of food to analysing starlight or detecting faint clues of life in outer space. ̽��ֱ��results are reported in the journal Science.

Traditionally, spectrometers rely on bulky components to filter and disperse light. Modern approaches simplify these components to shrink footprints, but still suffer from limited resolution and bandwidth. Additionally, traditional spectrometers are heavy and take up extraordinary amounts of space, which limits their applications in portable and mobile devices.

To tackle these problems, and shrink the size of the system, researchers have coupled layered materials with artificial intelligence algorithms. ̽��ֱ��result is an all-in-one spectrometer thousands of times smaller than current commercial systems. At the same time, it offers performance comparable to benchtop systems. In other words, these new spectrometers will provide portable alternatives to uncover otherwise invisible information, without even going into the lab.

“We eliminate the need for detector arrays, dispersive components, and filters. It’s an all-in-one, miniaturised device that could revolutionise this field,” said Dr Hoon Hahn Yoon, from Aalto ̽��ֱ�� in Finland, first author of the paper. This spectrometer-on-chip technology is expected to offer high performance and new usability across science and industry.

̽��ֱ��detector uses van der Waals heterostructures – a ‘sandwich’ of different ingredients, including graphene, molybdenum disulfide, and tungsten diselenide. Different combinations of material components enable light detection beyond the visible spectrum, as far as the near-infrared region. This means the spectrometer detects more than just colour, enabling applications such as chemical analysis and night vision.

“We detect a continuum spectrum of light, opening a world of possibilities in a myriad of markets,” said Yoon. “Exploring other material combinations could uncover further functionalities, including even broader hyperspectral detection and improved resolution.”

Artificial intelligence is a key aspect of these devices, commonly called ‘computational’ spectrometers. This technology compensates for the inherent noise increase that inevitably occurs when the optical component is wholly removed.

“We were able to use mathematical algorithms to successfully reconstruct the signals and spectra, it’s a profound and transformative technological leap,” said lead author Professor Zhipei Sun, also from Aalto ̽��ֱ��, and a former member of Cambridge’s Department of Engineering. “ ̽��ֱ��current design is just a proof-of-concept. More advanced algorithms, as well as different combinations of materials, could soon provide even better miniaturised spectrometers.”

Spectrometers are used for toxin detection in food and cosmetics, cancer imaging, and in spacecraft – including the James Webb Space Telescope. And they will soon become more common thanks to the development and advancement of technologies such as the Internet of Things and Industry 4.0.

̽��ֱ��detection of light – and the full analysis of spectroscopic information – has applications in sensing, surveillance, smart agriculture, and more. Among the most promising applications for miniaturised spectrometers are chemical and biochemical analysis, thanks to the capabilities of the devices to detect light in the infrared wavelength range.

̽��ֱ��new devices could be incorporated into instruments like drones, mobile phones, and lab-on-a-chip platforms, which can carry out several experiments in a single integrated circuit. ̽��ֱ��latter also opens up opportunities in healthcare. In this field, spectrometers and light-detectors are already key components of imaging and diagnostic systems – the new miniaturised devices could enable the simultaneous visualisation and detection of ‘chemical fingerprints’, leading to possibilities in the biomedical area.

“Our miniaturised spectrometers offer high spatial and spectral resolution at the micrometre and nanometre scales, which is particularly exciting for responsive bio-implants and innovative imaging techniques,” said co-author Professor Tawfique Hasan, from the Cambridge Graphene Centre.

This technology has huge potential for scalability and integration, thanks to its compatibility with well-established industrial processes. It could open up the future for the next generation of smartphone cameras that evolve into hyperspectral cameras that conventional colour cameras cannot do. Researchers hope their contribution is a stepping stone towards the development of more advanced computational spectrometers, with record-breaking accuracy and resolution. This example, they say, is just the first of many.

Reference:
Hoon Hahn Yoon et al. ‘Miniaturized Spectrometers with a Tunable van der Waals Junction.’ Science (2022). DOI: 10.1126/science.add8544.

Using Artificial Intelligence (AI) to replace optical and mechanical components, researchers have designed a tiny spectrometer that breaks all current resolution records.

Suvi-Tuuli Akkanen, Mikko Turunen, Vincent Pelgrin. Aalto ̽��ֱ��.

On-chip spectrometer on a fingertip

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Cambridge spin-out receives European Innovation Council grant to develop cancer imaging technologies

Anonymous — Mon, 21 Feb 2022 16:19:52 +0000

̽��ֱ��European Innovation Council (EIC) has awarded the first Transition Grant to Cambridge’s Department of Engineering. ̽��ֱ��project CHARM (chemometric histopathology via coherent Raman imaging for precision medicine) has received over €3.2 million to develop new medical imaging technologies. EIC funding will help the transition to industrial applications of graphene-enabled ultrafast lasers of the Cambridge Graphene Centre.

̽��ֱ��EIC is Europe’s leading innovation programme to identify, develop and scale up breakthrough technologies and game-changing innovations. ̽��ֱ��Transition scheme is designed to further advance research results generated by other EU-funded initiatives, such as the European Research Council (ERC) Proof of Concept projects.

CHARM will develop a medical device based on high-speed, low-cost Raman digital imaging and artificial intelligence, to transform cancer diagnosis and treatment. Raman spectroscopy is a non-destructive technique used to investigate materials through their vibrational modes. It allows high speed, label-free imaging. ̽��ֱ��CHARM technology will analyse the molecular composition of patient tissue samples to distinguish cancerous from healthy cells, without the need for chemical staining.

CHARM is a European collaboration between the Cambridge Graphene Centre at the ̽��ֱ�� of Cambridge, its spin-off Cambridge Raman Imaging, Politecnico Di Milano, Consiglio Nazionale Delle Ricerche ans INsociety in Italy, Jena ̽��ֱ�� Hospital in Germany, and Inspiralia in Spain.

CHARM builds on the results of the ERC Proof of Concept grant GYNCOR, led by Professor Andrea Ferrari, Director of the Cambridge Graphene Centre. Within this ERC project, Cambridge researchers developed and patented a graphene-enabled laser technology that CHARM will transition to a medical device.

̽��ֱ��EIC funding will help mature and validate the technology, as well as build a strong business case to accelerate the way towards commercialisation. On top of funding research and innovation, the EIC offers awardees business advancement services, including coaching, mentoring, and partnering events. CHARM will also have fast-track access to the EIC Accelerator programme, which financially supports later phases, such as commercialisation and scale-up.

“Funding from the European Union is an integral part of the Cambridge Graphene Centre’s success,” said Ferrari. “ ̽��ֱ��European Research Council and the European Innovation Council are two of the most prestigious funding programmes worldwide. ̽��ֱ�� ̽��ֱ�� of Cambridge has a very strong track record in receiving ERC funds. I am sure this first EIC transition grant will pave the way for many more to follow. We all need to join the call to ‘stick to science’ and ensure that open and barrier-free collaboration among Europe’s research and innovation actors, who all share the same values, continues without unnecessary delays and interruptions.”

Originally published on the Cambridge Graphene Centre website.

Spin-off company Cambridge Raman Imaging Ltd. and the Cambridge Graphene Centre will lead ‘CHARM’ project, recently awarded with €3.2 million

Funding from the European Union is an integral part of the Cambridge Graphene Centre’s success

Andrea Ferrari

NICHD

Bone cancer cell (nucleus in light blue)

Yes

Licence type:

Attribution

Ultra-high-density hard drives made with graphene store ten times more data

fg375 — Fri, 04 Jun 2021 13:19:14 +0000

̽��ֱ��study, published in Nature Communications, was carried out in collaboration with teams at the ̽��ֱ�� of Exeter, India, Switzerland, Singapore, and the US.

HDDs first appeared in the 1950s, but their use as storage devices in personal computers only took off from the mid-1980s. They have become ever smaller in size, and denser in terms of the number of stored bytes. While solid state drives are popular for mobile devices, HDDs continue to be used to store files in desktop computers, largely due to their favourable cost to produce and purchase.

HDDs contain two major components: platters and a head. Data are written on the platters using a magnetic head, which moves rapidly above them as they spin. ̽��ֱ��space between head and platter is continually decreasing to enable higher densities.

Currently, carbon-based overcoats (COCs) – layers used to protect platters from mechanical damages and corrosion – occupy a significant part of this spacing. ̽��ֱ��data density of HDDs has quadrupled since 1990, and the COC thickness has reduced from 12.5nm to around 3nm, which corresponds to one terabyte per square inch. Now, graphene has enabled researchers to multiply this by ten.

̽��ֱ��Cambridge researchers have replaced commercial COCs with one to four layers of graphene, and tested friction, wear, corrosion, thermal stability, and lubricant compatibility. Beyond its unbeatable thinness, graphene fulfills all the ideal properties of an HDD overcoat in terms of corrosion protection, low friction, wear resistance, hardness, lubricant compatibility, and surface smoothness.

Graphene enables two-fold reduction in friction and provides better corrosion and wear than state-of-the-art solutions. In fact, one single graphene layer reduces corrosion by 2.5 times.

Cambridge scientists transferred graphene onto hard disks made of iron-platinum as the magnetic recording layer, and tested Heat-Assisted Magnetic Recording (HAMR) – a new technology that enables an increase in storage density by heating the recording layer to high temperatures. Current COCs do not perform at these high temperatures, but graphene does. Thus, graphene, coupled with HAMR, can outperform current HDDs, providing an unprecedented data density, higher than 10 terabytes per square inch.

“Demonstrating that graphene can serve as protective coating for conventional hard disk drives and that it is able to withstand HAMR conditions is a very important result. This will further push the development of novel high areal density hard disk drives,” said Dr Anna Ott from the Cambridge Graphene Centre, one of the co-authors of this study.

A jump in HDDs’ data density by a factor of ten and a significant reduction in wear rate are critical to achieving more sustainable and durable magnetic data recording. Graphene based technological developments are progressing along the right track towards a more sustainable world.

Professor Andrea C. Ferrari, Director of the Cambridge Graphene Centre, added: “This work showcases the excellent mechanical, corrosion and wear resistance properties of graphene for ultra-high storage density magnetic media. Considering that in 2020, around 1 billion terabytes of fresh HDD storage was produced, these results indicate a route for mass application of graphene in cutting-edge technologies.”

Reference
Dwivedi et al. Graphene Overcoats for Ultra-High Storage Density Magnetic Media. Nature Communications 12, 2854 (2021), DOI: 10.1038/s41467-021-22687-y.

Adapted from a release from the Cambridge Graphene Centre.

Graphene can be used for ultra-high density hard disk drives (HDD), with up to a tenfold jump compared to current technologies, researchers at the Cambridge Graphene Centre have shown.

Considering that in 2020, around 1 billion terabytes of fresh HDD storage was produced, these results indicate a route for mass application of graphene in cutting-edge technologies

Andrea Ferrari

bohed

Hard disk drive

Yes

Licence type:

Public Domain

‘Magnetic graphene’ forms a new kind of magnetism

sc604 — Mon, 08 Feb 2021 15:21:53 +0000

̽��ֱ��researchers, led by the ̽��ֱ�� of Cambridge, were able to control the conductivity and magnetism of iron thiophosphate (FePS₃), a two-dimensional material which undergoes a transition from an insulator to a metal when compressed. This class of magnetic materials offers new routes to understanding the physics of new magnetic states and superconductivity.

Using new high-pressure techniques, the researchers have shown what happens to magnetic graphene during the transition from insulator to conductor and into its unconventional metallic state, realised only under ultra-high pressure conditions. When the material becomes metallic, it remains magnetic, which is contrary to previous results and provides clues as to how the electrical conduction in the metallic phase works. ̽��ֱ��newly discovered high-pressure magnetic phase likely forms a precursor to superconductivity so understanding its mechanisms is vital.

Their results, published in the journal Physical Review X, also suggest a way that new materials could be engineered to have combined conduction and magnetic properties, which could be useful in the development of new technologies such as spintronics, which could transform the way in which computers process information.

Properties of matter can alter dramatically with changing dimensionality. For example, graphene, carbon nanotubes, graphite and diamond are all made of carbon atoms, but have very different properties due to their different structure and dimensionality.

“But imagine if you were also able to change all of these properties by adding magnetism,” said first author Dr Matthew Coak, who is jointly based at Cambridge’s Cavendish Laboratory and the ̽��ֱ�� of Warwick. “A material which could be mechanically flexible and form a new kind of circuit to store information and perform computation. This is why these materials are so interesting, and because they drastically change their properties when put under pressure so we can control their behaviour.”

In a previous study by Sebastian Haines of the Cavendish Laboratory and the Department of Earth Sciences, researchers established that the material becomes a metal at high pressure, and outlined how the crystal structure and arrangement of atoms in the layers of this 2D material change through the transition.

“ ̽��ֱ��missing piece has remained however, the magnetism,” said Coak. “With no experimental techniques able to probe the signatures of magnetism in this material at pressures this high, our international team had to develop and test our own new techniques to make it possible.”

̽��ֱ��researchers used new techniques to measure the magnetic structure up to record-breaking high pressures, using specially designed diamond anvils and neutrons to act as the probe of magnetism. They were then able to follow the evolution of the magnetism into the metallic state.

“To our surprise, we found that the magnetism survives and is in some ways strengthened,” co-author Dr Siddharth Saxena, group leader at the Cavendish Laboratory. “This is unexpected, as the newly-freely-roaming electrons in a newly conducting material can no longer be locked to their parent iron atoms, generating magnetic moments there - unless the conduction is coming from an unexpected source.”

In their previous paper, the researchers showed these electrons were ‘frozen’ in a sense. But when they made them flow or move, they started interacting more and more. ̽��ֱ��magnetism survives, but gets modified into new forms, giving rise to new quantum properties in a new type of magnetic metal.

How a material behaves, whether conductor or insulator, is mostly based on how the electrons, or charge, move around. However, the ‘spin’ of the electrons has been shown to be the source of magnetism. Spin makes electrons behave a bit like tiny bar magnets and point a certain way. Magnetism from the arrangement of electron spins is used in most memory devices: harnessing and controlling it is important for developing new technologies such as spintronics, which could transform the way in which computers process information.

“ ̽��ֱ��combination of the two, the charge and the spin, is key to how this material behaves,” said co-author Dr David Jarvis from the Institut Laue-Langevin, France, who carried out this work as the basis of his PhD studies at the Cavendish Laboratory. “Finding this sort of quantum multi-functionality is another leap forward in the study of these materials.”

“We don’t know exactly what’s happening at the quantum level, but at the same time, we can manipulate it,” said Saxena. “It’s like those famous ‘unknown unknowns’: we’ve opened up a new door to properties of quantum information, but we don’t yet know what those properties might be.”

There are more potential chemical compounds to synthesise than could ever be fully explored and characterised. But by carefully selecting and tuning materials with special properties, it is possible to show the way towards the creation of compounds and systems, but without having to apply huge amounts of pressure.

Additionally, gaining fundamental understanding of phenomena such as low-dimensional magnetism and superconductivity allows researchers to make the next leaps in materials science and engineering, with particular potential in energy efficiency, generation and storage.

As for the case of magnetic graphene, the researchers next plan to continue the search for superconductivity within this unique material. “Now that we have some idea what happens to this material at high pressure, we can make some predictions about what might happen if we try to tune its properties through adding free electrons by compressing it further,” said Coak.

“ ̽��ֱ��thing we’re chasing is superconductivity,” said Saxena. “If we can find a type of superconductivity that’s related to magnetism in a two-dimensional material, it could give us a shot at solving a problem that’s gone back decades.”

Reference:
Matthew J. Coak et al. ‘Emergent Magnetic Phases in Pressure-Tuned van der Waals Antiferromagnet FePS3.’ Physical Review X (2021). DOI: 10.1103/PhysRevX.11.011024

Researchers have identified a new form of magnetism in so-called magnetic graphene, which could point the way toward understanding superconductivity in this unusual type of material.

Cavendish Laboratory

Illustration of the magnetic structure of FePS3

Yes