In quantum information theory, secret-key distillation is a crucial process for enabling secure communication across quantum networks. It works by extracting confidential bits from shared quantum states or channels using local operations and limited classical communication, ensuring privacy even over insecure links.
A bipartite quantum state is a system shared between two parties (often called Alice and Bob) that may exhibit entanglement. If they successfully distil a secret key, they can encrypt and decrypt messages securely, using the key like a shared password known only to them.
To achieve this, Alice and Bob use point-to-point quantum channels and perform local operations, meaning each can only manipulate their own part of the system. They also rely on one-way classical communication, where Alice sends messages to Bob, but Bob cannot reply. This constraint reflects realistic limitations in quantum networks and helps researchers identify the minimum requirements for secure key generation.
This paper investigates how many secret bits can be extracted under these conditions. The authors introduce a resource-theoretic framework based on unextendible entanglement which is a form of entanglement that cannot be shared with additional parties. This framework allows them to derive efficiently computable upper bounds on secret-key rates, helping determine how much security is achievable with limited resources.
Their results apply to both one-shot scenarios, where the quantum system is used only once, and asymptotic regimes, where the same system is used repeatedly and statistical patterns emerge. Notably, they extend their approach to quantum channels assisted by forward classical communication, resolving a long-standing open problem about the one-shot forward-assisted private capacity.
Finally, they show that error rates in private communication can decrease exponentially with repeated channel use, offering a scalable and practical path toward building secure quantum messaging systems.
As the Earth moves through space, it wobbles. Researchers in Germany have now directly observed this wobble with the highest precision yet thanks to a large ring laser gyroscope they developed for this purpose. The instrument, which is located in southern Germany and operates continuously, represents an important advance in the development of super-sensitive rotation sensors. If further improved, such sensors could help us better understand the interior of our planet and test predictions of relativistic effects, including the distortion of space-time due to Earth’s rotation.
The Earth rotates once every day, but there are tiny fluctuations, or wobbles, in its axis of rotation. These fluctuations are caused by several factors, including the gravitational forces of the Moon and Sun and, to a lesser extent, the neighbouring planets in our Solar System. Other, smaller fluctuations stem from the exchange of momentum between the solid Earth and the oceans, atmosphere and ice sheets. The Earth’s shape, which is not a perfect sphere but is flattened at the poles and thickened at the equator, also contributes to the wobble.
These different types of fluctuations produce effects known as precession and nutation that cause the extension of the Earth’s axis to trace a wrinkly circle in the sky. At the moment, this extended axis is aligned precisely with the North Star. In the future, it will align with other stars before returning to the North Star again in a cycle that lasts 26,000 years.
Most studies of the Earth’s rotation involve combining data from many sources. These sources include very long baseline radio-astronomy observations of quasars; global satellite navigation systems (GNSS); and GNSS observations combined with satellite laser ranging (SLR) and Doppler orbitography and radiopositioning integrated by satellite (DORIS). These techniques are based on measuring the travel time of light, and because it is difficult to combine them, only one such measurement can be made per day.
An optical interferometer that works using the Sagnac effect
The new gyroscope, which is detailed in Science Advances, is an optical interferometer that operates using the Sagnac effect. At its heart is an optical cavity that guides a light beam around a square path 16 m long. Depending on the rate of rotation it experiences, this cavity selects two different frequencies from the beam to be coherently amplified. “The two frequencies chosen are the only ones that have an integer number of waves around the cavity,” explains team leader Ulrich Schreiber of the Technische Universität München (TUM). “And because of the finite velocity of light, the co-rotating beam ‘sees’ a slightly larger cavity, while the anti-rotating beam ‘sees’ a slightly shorter one.”
The frequency shift in the interference pattern produced by the co-rotating beam is projected onto an external detector and is strictly proportional to the Earth’s rotation rate. Because the accuracy of the measurement depends, in part, on the mechanical stability of the set-up, the researchers constructed their gyroscope from a glass ceramic that does not expand much with temperature. They also set it up horizontally in an underground laboratory, the Geodetic Observatory Wettzell in southern Bavaria, to protect it as much as possible from external vibrations.
The instrument can sense the Earth’s rotation to within an accuracy of 48 parts per billion (ppb), which corresponds to picoradians per second. “This is about a factor of 100 better than any other rotation sensor,” says Schreiber, “and, importantly, is less than an order of magnitude away from the regime in which relativistic effects can be measured – but we are not quite there yet.”
An increase in the measurement accuracy and stability of the ring laser by a factor of 10 would, Schreiber adds, allow the researchers to measure the space-time distortion caused by the Earth’s rotation. For example, it would permit them to conduct a direct test for the Lense-Thirring effect — that is, the “dragging” of space by the Earth’s rotation – right at the Earth’s surface.
To reach this goal, the researchers say they would need to amend several details of their sensor design. One example is the composition of the thin-film coatings on the mirrors inside their optical interferometer. “This is neither easy nor straightforward,” explains Schreiber, “but we have some ideas to try out and hope to progress here in the near future.
“In the meantime, we are working towards implementing our measurements into a routine evaluation procedure,” he tells Physics World.
Susumu Kitagawa, Richard Robson and Omar Yaghi have been awarded the 2025 Nobel Prize for Chemistry “for developing metal-organic frameworks”.
The award includes a SEK 11m prize ($1.2m), which is shared equally by the winners. The prize will be presented at a ceremony in Stockholm on 10 December.
The prize was announced this morning by members of the Royal Swedish Academy of Science. Speaking on the phone during the press conference, Kitagawa noted that he was “deeply honoured and delighted” that his research had been recognized.
A new framework
Beginning in the late 1980s and for the next couple of decades, the trio, who are all trained chemists, developed a new form of molecular architecture in that metal ions function as cornerstones that are linked by long organic carbon-based molecules.
Together, the metal ions and molecules form crystals that contain large cavities through which gases and other chemicals can flow.
“It’s a little like Hermione’s handbag – small on the outside, but very large on the inside,” noted Heiner Linke, chair of the Nobel Committee for Chemistry.
Yet the trio had to overcome several challenges before they could be used such as making them stable and flexible, which Kitagawa noted “was very tough”.
These porous materials are now called metal-organic frameworks (MOF). By varying the building blocks used in the MOFs, researchers can design them to capture and store specific substances as well as drive chemical reactions or conduct electricity.
“Metal-organic frameworks have enormous potential, bringing previously unforeseen opportunities for custom-made materials with new functions,” added Linke.
Following the laureates’ work, chemists have built tens of thousands of different MOFs.
3D MOFs are an important class of materials that could be used in applications as diverse as sensing, gas storage, catalysis and optoelectronics.
MOFs are now able to capture water from air in the desert, sequester carbon dioxide from industry effluents, store hydrogen gas, recover rare-earth metals from waste, break down oil contamination as well as extract “forever chemicals” such as PFAS from water.
“My dream is to capture air and to separate air into CO2, oxygen and water and convert them to usable materials using renewable energy,” noted Kitagawa.
Their 2D versions might even be used as flexible material platforms to realize exotic quantum phases, such as topological and anomalous quantum Hall insulators.
Life scientific
Kitagawa was born in 1951 in Kyoto, Japan. He obtained a PhD from Kyoto University, Japan, in 1979 and then held positions at Kindai University before joining Tokyo Metropolitan University in 1992. He then joined Kyoto University in 1998 where he is currently based.
Robson was born in 1937 in Glusburn, UK. He obtained a PhD from University of Oxford in 1962. After postdoc positions at California Institute of Technology and Stanford University, in 1966 he moved to the University of Melbourne where he remained for the rest of his career.
Yaghi was born in 1965 in Amman, Jordan. He obtained a PhD from University of Illinois Urbana-Champaign, US, in 1990. He then held positions at Arizona State University, the University of Michigan and the University of California, Los Angeles, before joining the University of California, Berkeley, in 2012 where he is currently based.
Neurodegenerative diseases affect millions of people worldwide, but treatment of such conditions is limited by the blood–brain barrier (BBB), which blocks the passage of drugs to the brain. In the quest for more effective therapeutic options, a multidisciplinary research team has developed a novel machine learning-based technique to predict the behaviour of nanoparticles as drug delivery systems.
The work focuses on nanoparticles that can cross the BBB and provide a promising platform for enhancing drug transport into the brain. But designing specific nanoparticles to target specific brain regions is a complex and time-consuming task; there’s a need for improved design frameworks to identify potential candidates with desirable bioactivity profiles. For this, the team – comprising researchers from the University of the Basque Country (UPV/EHU) in Spain and Tulane University in the USA, led by the multicentre CHEMIF.PTML Lab – turned to machine learning.
Machine learning uses molecular and clinical data to detect trends that may lead to novel drug delivery strategies with improved efficiency and reduced side effects. In contrast to slow and costly trial-and-error or physical modelling approaches, machine learning could provide efficient initial screening of large combinations of nanoparticle compositions. Traditional machine learning, however, can be hindered by the lack of suitable data sets.
To address this limitation, the CHEMIF.PTML Lab team developed the IFE.PTML method – an approach that integrates information fusion, Python-based encoding and perturbation theory with machine learning algorithms, describing the model in Machine Learning: Science and Technology.
“The main advantage of our IFE.PTML method lies in its ability to handle heterogeneous nanoparticle data,” corresponding author Humberto González-Díaz explains. “Standard machine learning approaches often struggle with disperse and multi-source datasets from nanoparticle experiments. Our approach integrates information fusion to combine diverse data types – such as physicochemical properties, bioassays and so on – and applies perturbation theory to model these uncertainties as probabilistic perturbations around baseline conditions. This results in more robust, generalizable predictions of nanoparticle behaviour.”
To build the predictive models, the researchers created a database containing physicochemical and bioactivity parameters for 45 different nanoparticle systems across 41 different cell lines. They used these data to train IFE.PTML models with three machine learning algorithms – random forest, extreme gradient boosting and decision tree – to predict the drug delivery behaviour of various nanomaterials. The random forest-based model showed the best overall performance, with accuracies of 95.1% and 89.7% on training and testing data sets, respectively.
Experimental demonstration
To illustrate the real-world applicability of the random forest-based IFE.PTML model, the researchers synthetized two novel magnetite nanoparticle systems (the 31 nm-diameter Fe3O4_A and the 26 nm-diameter Fe3O4_B). Magnetite-based nanoparticles are biocompatible, can be easily functionalized and have a high surface area-to-volume ratio, making them efficient drug carriers. To make them water soluble, the nanoparticles were coated with either PMAO (poly(maleic anhydride-alt-1-octadecene)) or PMAO plus PEI (poly(ethyleneimine).
Preparation process Functionalization of Fe3O4 nanoparticles with PMAO and PEI polymers. (Courtesy: Mach. Learn.: Sci. Technol. 10.1088/2632-2153/ae038a)
The team characterized the structural, morphological and magnetic properties of the four nanoparticle systems and then used the optimized model to predict their likelihood of favourable bioactivity for drug delivery in various human brain cell lines, including models of neurodegenerative disease, brain tumour models and a cell line modelling the BBB.
As inputs for their model, the researchers used a reference function based on the bioactivity parameters for each system, plus perturbation theory operators for various nanoparticle parameters. The IFE.PTML model calculated key bioactivity parameters, focusing on indicators of toxicity, efficacy and safety. These included the 50% cytotoxic, inhibitory, lethal and toxic concentrations (at which 50% of the biological effect is observed) and the zeta potential, which affects the nanoparticles’ capacity to cross the BBB. For each parameter, the model output a binary result: “0” for undesired and “1” for desired bioactivities.
The model identified PMAO-coated nanoparticles as the most promising candidates for BBB and neuronal applications, due to their potentially favourable stability and biocompatibility. Nanoparticles with PMAO-PEI coatings, on the other hand, could prove optimal for targeting brain tumour cells.
The researchers point out that, where comparisons were possible, the trends predicted by the RF-IFE.PTML model agreed with the experimental findings, as well as with previous studies reported in the literature. As such, they conclude that their model is efficient and robust and offers valuable predictions on nanoparticle–coating combinations designed to act on specific targets.
“The present study focused on the nanoparticles as potential drug carriers. Therefore, we are currently implementing a combined machine learning and deep learning methodology with potential drug candidates for neurodegenerative diseases,” González-Díaz tells Physics World.
This year’s Q2B meeting took place at the end of last month in Paris at the Cité des Sciences et de l’Industrie, a science museum in the north-east of the city. The event brought together more than 500 attendees and 70 speakers – world-leading experts from industry, government institutions and academia. All major quantum technologies were highlighted: computing, AI, sensing, communications and security.
As was clear from the conference talks, quantum computers are undoubtedly advancing in leaps and bounds. One of their most important weak points, however, is that their fundamental building blocks (quantum bits, or qubits) are highly prone to errors. These errors are caused by interactions with the environment – also known as noise – and correcting them will require innovative software and hardware. Today’s machines are only capable of running on average a few hundred operations before an error occurs; but in the future, we will have to develop quantum computers capable of processing a million error-free quantum operations (known as a MegaQuOp) or even a trillion error-free operations (TeraQuOps).
QEC works by distributing one quantum bit of information – called a logical qubit – across several different physical qubits, such as superconducting circuits or trapped atoms. Each physical qubit is noisy, but they work together to preserve the quantum state of the logical qubit – at least for long enough to perform a calculation. It was Peter Shor who first discovered this method of formulating a quantum error correcting code by storing the information of one qubit onto a highly entangled state of nine qubits. A technique known as syndrome decoding is then used to diagnose which error was the likely source of corruption on an encoded state. The error can then be reversed by applying a corrective operation depending on the syndrome.
Computing advances A prototype quantum computer from NVIDIA that makes use of seven qubits. (Courtesy: Isabelle Dumé)
While error correction should become more effective as the number of physical qubits in a logical qubit increases, adding more physical qubits to a logical qubit also adds more noise. Much progress has been made in addressing this and other noise issues in recent years, however.
“We can say there’s a ‘fight’ when increasing the length of a code,” explains Hilaire. “Doing so allows us to correct more errors, but we also introduce more sources of errors. The goal is thus being able to correct more errors than we introduce. What I like with this picture is the clear idea of the concept of a fault-tolerant threshold below which fault-tolerant quantum computing becomes feasible.”
Developments in QEC theory
Speakers at the Q2B25 meeting shared a comprehensive overview of the most recent advancements in the field – and they are varied. First up, concatenated error correction codes. Prevalent in the early days of QEC, these fell by the wayside in favour of codes like surface code, but are making a return as recent work has shown. Concatenated codes can achieve constant encoding rates and a quantum computer operating on a linear, nearest-neighbour connectivity was recently put forward. Directional codes, the likes of which are being developed by Riverlane, are also being studied. These leverage native transmon qubit logic gates – for example, iSWAP gates – and could potentially outperform surface codes in some aspects.
The panellists then described bivariate bicycle codes, being developed by IBM, which offer better encoding rates than surface codes. While their decoding can be challenging for real-time applications, IBM’s “relay belief propagation” (relay BP) has made progress here by simplifying decoding strategies that previously involved combining BP with post-processing. The good thing is that this decoder is actually very general and works for all the “low-density parity check codes” — one of the most studied class of high performance QEC codes (these also include, for example, surface codes and directional codes).
There is also renewed interest in decoders that can be parallelized and operate locally within a system, they said. These have shown promise for codes like the 1D repetition code, which could revive the concept of self-correcting or autonomous quantum memory. Another possibility is the increased use of the graphical language ZX calculus as a tool for optimizing QEC circuits and understanding spacetime error structures.
Hardware-specific challenges
The panel stressed that to achieve robust and reliable quantum systems, we will need to move beyond so-called hero experiments. For example, the demand for real-time decoding at megahertz frequencies with microsecond latencies is an important and unprecedented challenge. Indeed, breaking down the decoding problem into smaller, manageable bits has proven difficult so far.
There are also issues with qubit platforms themselves that need to be addressed: trapped ions and neutral atoms allow for high fidelities and long coherence times, but they are roughly 1000 times slower than superconducting and photonic qubits and therefore require algorithmic or hardware speed-ups. And that is not all: solid-state qubits (such as superconducting and spin qubits) suffer from a “yield problem”, with dead qubits on manufactured chips. Improved fabrication methods will thus be crucial, said the panellists.
Collaboration between academia and industry
The discussions then moved towards the subject of collaboration between academia and industry. In the field of QEC, such collaboration is highly productive today, with joint PhD programmes and shared conferences like Q2B, for example. Large companies also now boast substantial R&D departments capable of funding high-risk, high-reward research, blurring the lines between fundamental and application-oriented research. Both sectors also use similar foundational mathematics and physics tools.
At the moment there’s an unprecedented degree of openness and cooperation in the field. This situation might change, however, as commercial competition heats up, noted the panellists. In the future, for example, researchers from both sectors might be less inclined to share experimental chip details.
Last, but certainly not least, the panellists stressed the urgent need for more PhDs trained in quantum mechanics to address the talent deficit in both academia and industry. So, if you were thinking of switching to another field, perhaps now could be the time to jump.
High performance, proven, wire scanner for transverse beam profile measurement for the latest generation of low emittance accelerators and FELs. (Courtesy: UHV Design)
A new high-performance wire scanner fork that the latest generation of free electron lasers (FELs) can use for measuring beam profiles has been developed by UK-based firm UHV Design. Produced using technology licensed from the Paul Scherrer Institute (PSI) in Switzerland, the device could be customized for different FELs and low emittance accelerators around the world. It builds on the company’s PLSM range, which allows heavy objects to be moved very smoothly and with minimal vibrations.
The project began 10 years ago when the PSI was starting to build the Swiss Free Electron Laser and equipping the facility, explains Jonty Eyres. The remit for UHV Design was to provide a stiff, very smooth, bellows sealed, ultra-high vacuum compatible linear actuator that could move a wire fork without vibrating it adversely. The fork, designed by PSI, can hold wires in two directions and can therefore scan the intensity of the beam profile in both X and Y planes using just one device as opposed to two or more as in previous such structures.
“We decided to employ an industrial integrated ball screw and linear slide assembly with a very stiff frame around it, the construction of which provides the support and super smooth motion,” he says. “This type of structure is generally not used in the ultra-high vacuum industry.”
The position of the wire fork is determined through a (radiation-hard) side mounted linear optical encoder in conjunction with the PSI’s own motor and gearbox assembly. A power off brake is also incorporated to avoid any issues with back driving under vacuum load if electrical power was to be lost to the PLSM. All electrical connections terminated with UTO style connectors to PSI specification.
Long term reliability was important to avoid costly and unnecessary down time, particularly between planned FEL maintenance shutdowns. The industrial ball screw and slide assembly by design was the perfect choice in conjunction with a bellows assembly rated for 500,000 cycles with an option to increase to 1 million cycles.
Eyres and his UHV design team began by building a prototype that the PSI tested themselves with a high-speed camera. Once validated, the UHV engineers then built a batch of 20 identical units to prove that the device could be replicated in terms of constraints and tolerances.
The real challenge in constructing this device, says Eyres, was about trying to minimize the amount of vibration on the wire, which, for PSI, is typically between 5 and 25 microns thick. This is only possible if the vibration of the wire during a scan is low compared to the cross section of the wire – that is, about a micron for a 25-micron wire. “Otherwise, you are just measuring noise,” explains Eyres. “The small vibration we achieved can be corrected for in calculations, so providing an accurate value for the beam profile intensity.”
UHV Design holds the intellectual property rights for the linear actuator and PSI the property rights of the fork. Following the success of the project and a subsequent agreement between them both, it was recently decided that UHV Design buy the licence to promote the wire fork, allowing the company to sell the device or a version of it to any institution or company operating a FEL or low-emittance accelerator. “The device is customizable and can be adapted to different types of fork, wires, motors or encoders,” says Eyres. “The heart of the design remains the same: a very stiff structure and its integrated ball screw and linear slide assembly. But, it can be tailored to meet the requirements of different beam lines in terms of stroke size, specific wiring and the components employed.”
UHV Design’s linear actuator was installed on the Swiss FEL in 2016 and has been performing very well since, says Eyres.
A final and important point to note, he adds, is that UHV Design built an identical copy of their actuator when we took on board the licence agreement, so that we could prove it could still reproduce the same performance. “We built an exact copy of the wire scanner, including the PSI fork assembly and sent it to the PSI, who then used the very same high-speed camera rig that they’d employed in 2015 to directly compare the new actuator with the original ones supplied. They reported that the results were indeed comparable, meaning that if fitted to the Swiss FEL today, it would perform in the same way.”
Silicon-based lithium-ion batteries exhibit severe time-based degradation resulting in poor calendar lives. In this webinar, we will talk about how calendar aging is measured, why the traditional measurement approaches are time intensive and there is a need for new approaches to optimize materials for next generation silicon based systems. Using this new approach we also screen multiple new electrolyte systems that can lead to calendar life improvements in Si containing batteries.
An interactive Q&A session follows the presentation.
Ankit Verma’s expertise is in physics-based and data-driven modeling of lithium-ion and next generation lithium metal batteries. His interests lie in unraveling the coupled reaction-transport-mechanics behavior in these electrochemical systems with experiment-driven validation to provide predictive insights for practical advancements. Predominantly, he’s working on improving silicon anodes energy density and calendar life as part of the Silicon Consortium Project, understanding solid-state battery limitations and upcycling of end-of-life electrodes as part of the ReCell Center.
Verma’s past works include optimization of lithium-ion battery anodes and cathodes for high-power and fast-charge applications and understanding electrodeposition stability in metal anodes.
John Clarke, Michel Devoret and John Martinis share the 2025 Nobel Prize for Physics “for the discovery of macroscopic quantum mechanical tunnelling and energy quantization in an electric circuit”.
The award includes a SEK 11m prize ($1.2m), which is shared equally by the winners. The prize will be presented at a ceremony in Stockholm on 10 December.
The prize was announced this morning by members of the Royal Swedish Academy of Science. Olle Eriksson of Uppsala University and chair of the Nobel Committee for Physics commented, “There is no advanced technology today that does not rely on quantum mechanics.”
Göran Johansson of Chalmers University of Technology explained that the three laureates took quantum tunnelling from the microscopic world and onto superconducting chips, allowing physicists to study quantum physics and ultimately create quantum computers.
Speaking on the telephone, John Clarke said of his win, “To put it mildly, it was the surprise of my life,” adding “I am completely stunned. It had never occurred to me that this might be the basis of a Nobel prize.” On the significance of the trio’s research, Clarke said, “The basis of quantum computing relies to quite an extent on our discovery.”
As well as acknowledging the contributions of Devoret and Martinis, Clarke also said that their work was made possible by the work of Anthony Leggett and Brian Josephson – who laid the groundwork for their work on tunnelling in superconducting circuits. Leggett and Josephson are previous Nobel winners.
As well as having scientific significance, the trio’s work has led to the development of nascent commercial quantum computers that employ superconducting circuits. Physicist and tech entrepreneur Ilana Wisby, who co-founded Oxford Quantum Circuits, told Physics World, “It’s such a brilliant and well-deserved recognition for the community”.
A life in science
Clarke was born in 1942 in Cambridge, UK. He received his BA in physics from the University of Cambridge in 1964 before carrying out a PhD at Cambridge in 1968. He then moved to the University of California, Berkeley, to carry out a postdoc before joining the physics faculty in 1969 where he has remained since.
Devoret was born in Paris, France in 1953. He graduated from Ecole Nationale Superieure des Telecommunications in Paris in 1975 before earning a PhD from the University of Paris, Orsay, in 1982. He then moved to the University of California, Berkeley, to work in Clarke’s group collaborating with Martinis who was a graduate student at the time. In 1984 Devoret returned to France to start his own research group at the Commissariat à l’Energie Atomique in Saclay (CEA-Saclay) before heading to the US to Yale University in 2002. In 2024 he moved to the University of California, Santa Barbara, and also became chief scientist at Google Quantum AI.
Martinis was born in the US in 1958. He received a BS in physics in 1980 and a PhD in physics both from the University of California, Berkeley. He then carried out postdocs at CEA-Saclay, France, and the National Institute of Standards and Technology in Boulder, Colorado, before moving to the University of California, Santa Barbara, in 2004. In 2014 Martinis and his team joined Google with the aim of building the first useful quantum computer before he moved to Australia in 2020 to join the start-up Silicon Quantum Computing. In 2022 he co-founded the company Qolab, of which he is currently the chief technology officer.
The trio did its prizewinning work in the mid-1980s at the University of California, Berkeley. At the time Devoret was a postdoctoral fellow and Martinis was a graduate student – both working for Clarke. They were looking for evidence of macroscopic quantum tunnelling (MQT) in a device called a Josephson junction. This comprises two pieces of superconductor that are separated by an insulating barrier. In 1962 the British physicist Brian Josephson predicted how the Cooper pairs of electrons that carry current in a superconductor can tunnel across the barrier unscathed. This Josephson effect was confirmed experimentally in 1963.
Single wavefunction
The lowest-energy (ground) state of a superconductor is a macroscopic quantum state in which all Cooper pairs are described by a single quantum-mechanical wavefunction. In the late 1970s, the British–American physicist Anthony Leggett proposed that the tunnelling of this entire macroscopic state could be observed in a Josephson junction.
The idea is to put the system into a metastable state in which electrical current flows without resistance across the junction – resulting in zero voltage across the junction. If the system is indeed a macroscopic quantum state, then it should be able to occasionally tunnel out of this metastable state, resulting in a voltage across the junction.
This tunnelling can be observed by increasing the current through the junction and measuring the current at which a voltage occurs – obtaining an average value over many such measurements. As the temperature of the device is reduced, this average current increases – something that is expected regardless of whether the system is in a macroscopic quantum state.
However, at very low temperatures the average current becomes independent of temperature, which is the signature of macroscopic quantum tunnelling that Martinis, Devoret and Clarke were seeking. Their challenge was to reduce the noise in their experimental apparatus, because noise has a similar effect as tunnelling on their measurements.
Multilevel system
As well as observing the signature of tunnelling, they were also able to show that the macroscopic quantum state exists in several different energy states. Such a multilevel system is essentially a macroscopic version of an atom or nucleus, with its own spectroscopic structure.
The noise-control techniques developed by the trio to observe MQT and the fact that a Josephson junction can function as a macroscopic multilevel quantum system have led to the development of superconducting quantum bits (qubits) that form the basis of some nascent quantum computers.
For many years, I’ve been a judge for awards and prizes linked to research and innovation in engineering and physics. It’s often said that it’s better to give than to receive, and it’s certainly true in this case. But another highlight of my involvement with awards is learning about cutting-edge innovations I either hadn’t heard of or didn’t know much about.
One area that never fails to fascinate me is the development of new and advanced materials. I’m not a materials scientist – my expertise lies in creating monitoring systems for engineering – so I apologize for any over-simplification in what follows. But I do want to give you a sense of just how impressive, challenging and rewarding the field of materials science is.
It’s all too easy to take advanced materials for granted. We are in constant contact with them in everyday life, whether it’s through applications in healthcare, electronics and computing or energy, transport, construction and process engineering. But what are the most important materials innovations right now – and what kinds of novel materials can we expect in future?
Drivers of innovation
There are several – and all equally important – drivers when it comes to materials development. One is the desire to improve the performance of products we’re already familiar with. A second is the need to develop more sustainable materials, whether that means replacing less environmentally friendly solutions or enabling new technology. Third, there’s the drive for novel developments, which is where some of the most ground-breaking work is occurring.
On the environmental front, we know that there are many products with components that could, in principle, be recycled. However, the reality is that many products end up in landfill because of how they’ve been constructed. I was recently reminded of this conundrum when I heard a research presentation about the difficulties of recycling solar panels.
Green problem Solar panels often fail to be recycled at their end of their life despite containing reusable materials. (Courtesy: iStock/Milos Muller)
Photovoltaic cells become increasingly inefficient with time and most solar panels aren’t expected to last more than about 30 years. Trouble is, solar panels are so robustly built that recycling them requires specialized equipment and processes. More often than not, solar panels just get thrown away despite mostly containing reusable materials such as glass, plastic and metals – including aluminium and silver.
It seems ironic that solar panels, which enable sustainable living, could also contribute significantly to landfill. In fact, the problem could escalate significantly if left unaddressed. There are already an estimated 1.8 million solar panels in use the UK, and potentially billions around the world, with a rapidly increasing install base. Making solar panels more sustainable is surely a grand challenge in materials science.
Waste not, want not
Another vital issue concerns our addiction to new tech, which means we rarely hang on to objects until the end of their life; I mean, who hasn’t been tempted by a shiny new smartphone even though the old one is perfectly adequate? That urge for new objects means we need more materials and designs that can be readily re-used or recycled, thereby reducing waste and resource depletion.
As someone who works in the aerospace industry, I know first-hand how companies are trying to make planes more fuel efficient by developing composite materials that are stronger and can survive higher temperatures and pressures – for example carbon fibre and composite matrix ceramics. The industry also uses “additive manufacturing” to enable more intricate component design with less resultant waste.
Plastics are another key area of development. Many products are made from single type, recyclable materials, such as polyethylene or polypropylene, which benefit from being light, durable and capable of withstanding chemicals and heat. Trouble is, while polyethene and polypropene can be recycled, they both create the tiny “microplastics” that, as we know all too well, are not good news for the environment.
Sustainable challenge Material scientists will need to find practical bio-based alternatives to conventional plastics to avoid polluting microplastics entering the seas and oceans. (Courtesy: iStock/Dmitriy Sidor)
Bio-based materials are becoming more common for everyday items. Think about polylactic acid (PLA), which is a plant-based polymer derived from renewable resources such as cornstarch or sugar cane. Typically used for food or medical packaging, it’s usually said to be “compostable”, although this is a term we need to view with caution.
Sadly, PLA does not degrade readily in natural environments or landfill. To break it down, you need high-temperature, high-moisture industrial composting facilities. So whilst PLAs come from natural plants, they are not straightforward to recycle, which is why single-use disposable items, such as plastic cutlery, drinking straws and plates, are no longer permitted to be made from it.
Thankfully, we’re also seeing greater use of more sustainable, natural fibre composites, such as flax, hemp and bamboo (have you tried bamboo socks or cutlery?). All of which brings me to an interesting urban myth, which is that in 1941 legendary US car manufacturer Henry Ford built a car apparently made entirely of a plant-based plastic – dubbed the “soybean” car (see box).
The soybean car: fact or fiction?
Crazy or credible? Soybean car frame patent signed by Henry Ford and Eugene Turenne Gregorie. (Courtesy: Image in public domain)
Henry Ford’s 1941 “soybean” car, which was built entirely of a plant-based plastic, was apparently motivated by a need to make vehicles lighter (and therefore more fuel efficient), less reliant on steel (which was in high demand during the Second World War) and safer too. The exact ingredients of the plastic are, however, not known since there were no records kept.
Speculation is that it was a combination of soybeans, wheat, hemp, flax and ramie (a kind of flowering nettle). Lowell Overly, a Ford designer who had major involvement in creating the car, said it was “soybean fibre in a phenolic resin with formaldehyde used in the impregnation”. Despite being a mix of natural and synthetic materials – and not entirely made of soybeans – the car was nonetheless a significant advancement for the automotive industry more than eight decades ago.
Avoiding the “solar-panel trap”
So what technology developments do we need to take materials to the next level? The key will be to avoid what I coin the “solar-panel trap” and find materials that are sustainable from cradle to grave. We have to create an environmentally sustainable economic system that’s based on the reuse and regeneration of materials or products – what some dub the “circular economy”.
Sustainable composites will be essential. We’ll need composites that can be easily separated, such as adhesives that dissolve in water or a specific solvent, so that we can cleanly, quickly and cheaply recover valuable materials from complex products. We’ll also need recycled composites, using recycled carbon fibre, or plastic combined with bio-based resins made from renewable sources like plant-based oils, starches and agricultural waste (rather than fossil fuels).
Vital too will be eco-friendly composites that combine sustainable composite materials (such as natural fibres) with bio-based resins. In principle, these could be used to replace traditional composite materials and to reduce waste and environmental impact.
Another important trend is developing novel metals and complex alloys. As well as enhancing traditional applications, these are addressing future requirements for what may become commonplace applications, such as wide-scale hydrogen manufacture, transportation and distribution.
Soft and stretchy
Then there are “soft composites”. These are advanced, often biocompatible materials that combine softer, rubbery polymers with reinforcing fibres or nanoparticles to create flexible, durable and functional materials that can be used for soft robotics, medical implants, prosthetics and wearable sensors. These materials can be engineered for properties like stretchability, self-healing, magnetic actuation and tissue integration, enabling innovative and patient-friendly healthcare solutions.
Medical magic Wearable electronic materials could transform how we monitor human health. (Shutterstock/Guguart)
And have you heard of e-textiles, which integrate electronic components into everyday fabrics? These materials could be game-changing for healthcare applications by offering wearable, non-invasive monitoring of physiological information such as heart rate and respiration.
Further applications could include advanced personal protective equipment (PPE), smart bandages and garments for long-term rehabilitation and remote patient care. Smart textiles could revolutionize medical diagnostics, therapy delivery and treatment by providing personalized digital healthcare solutions.
Towards “new gold”
I realize I have only scratched the surface of materials science – an amazing cauldron of ideas where physics, chemistry and engineering work hand in hand to deliver groundbreaking solutions. It’s a hugely and truly important discipline. With far greater success than the original alchemists, materials scientists are adept at creating the “new gold”.
Their discoveries and inventions are making major contributions to our planet’s sustainable economy from the design, deployment and decommission of everyday items, as well as finding novel solutions that will positively impact way we live today. Surely it’s an area we should celebrate and, as physicists, become more closely involved in.
A perovskite semiconductor that can detect and image single gamma-ray photons with both high-spatial and high-energy resolution could be used to create next-generation nuclear medicine scanners that can image faster and provide clearer results. The perovskite is also easier to grow and much cheaper than existing detector materials such as cadmium zinc telluride (CZT), say the researchers at Northwestern University in the US and Soochow University in China who developed it.
Nuclear medicine imaging techniques like single-photon emission computed tomography (SPECT) work by detecting the gamma rays emitted by a short-lived radiotracer delivered to a specific part of a patient’s body. Each gamma ray can be thought of as being a pixel of light, and after millions of these pixels have been collected, a 3D image of the region of interest can be built up by an external detector.
Such detectors are today made from either semiconductors like CZT or scintillators such as NaI:TI, CsI and LYSO, but CZT detectors are expensive – often costing hundreds of thousands to millions of dollars. CZT crystals are also brittle, making the detectors difficult to manufacture. While NaI is cheaper than CZT, detectors made of this material end up being bulky and generate blurrier images.
High-quality crystals of CsPbBr3
To overcome these problems, researchers led by Mercouri Kanatzidis and Yihui He studied the lead halide perovskite crystal CsPbBr3. They already knew that this was an efficient solar cell material and recently, they discovered that it also showed promise for detecting X-rays and gamma rays.
In the new work, detailed in Nature Communications, the team grew high-quality crystals of CsPbBr3 and fabricated them into detector devices. “When a gamma-ray photon enters the crystal, it interacts with the material and produces electron–hole pairs,” explains Kanatzidis. “These charge carriers are collected as an electrical signal that we can measure to determine both the energy of the photon and its point of interaction.”
The researchers found that their detectors could resolve individual gamma rays at the energies used in SPECT imaging with high resolution. They could also sense extremely weak signals from the medical tracer technetium-99m, which is routinely employed in hospital settings. They were thus able to produce sharp images that could distinguish features as small as 3.2 mm. This fine sensitivity means that patients would be exposed to shorter scan times or smaller doses of radiation compared with NaI or CZT detectors.
Ten years of optimization
“Importantly, a parallel study published in Advanced Materials the same week as our Nature Communications paper directly compared perovskite performance with CZT, the only commercial semiconductor material available today for SPECT, which showed that perovskites can even surpass CZT in certain aspects,” says Kanatzidis.
“The result was possible thanks to our efforts over the last 10 years in optimizing the crystal growth of CsPbBr3, improving the electrode contacts in the detectors and carrier transport and nuclear electronics therein,” adds He. “Since the first demonstration of high spectral resolution by CsPbBr3 in our previous work, it has gradually been recognized as the most promising competitor to CZT.”
Looking forward, the Northwestern–Soochow team is now busy scaling up detector fabrication and improving its long-term stability. “We are also trying to better understand the fundamental physics of how gamma rays interact in perovskites, which could help optimize future materials,” says Kanatzidis. “A few years ago, we established a new company, Actinia, with the goal of commercializing this technology and moving it toward practical use in hospitals and clinics,” he tells Physics World.
“High-quality nuclear medicine shouldn’t be limited to hospitals that can afford the most expensive equipment,” he says. “With perovskites, we can open the door to clearer, faster, safer scans for many more patients around the world. The ultimate goal is better scans, better diagnoses and better care for patients.”
