Skip to main content

Reset your password

Please enter the e-mail address you used to register to reset your password

Note: The verification e-mail to change your password should arrive immediately. However, in some cases it takes longer. Don't forget to check your spam folder.

If you haven't received the e-mail in 24 hours, please contact customerservices@ioppublishing.org

Registration complete

Thank you for registering with Physics World
If you'd like to change your details at any time, please visit My account

Close
Home » Page 200

Competing pacemakers create distinctive triplets in heartbeats

A simple set of mathematical rules that accurately identifies signs of competing electrical signals in the heart has been developed by Leon Glass at McGill University and colleagues. The Canadian team did in vitro experiments that showed how abnormal beating triggered by anomalous electrical impulses can generate distinctive triplets. These triplets also appear in cardiac data from real patients and emerge from a simple mathematical model.

Our heartbeat is controlled by a cluster of specialized cells called a pacemaker. Located in the right atrium, the pacemaker broadcasts regular electrical “sinus” signals that cause heart muscle cells to contract in a regular manner. However, the heart can also contain an abnormal “ectopic” pacemaker located in a different part of the organ. This pacemaker can send out electrical signals, often at lower frequencies than the sinus pacemaker. The heart muscles can respond to both sinus and ectopic signals, leading to an irregular beating of the heart called ectopic arrhythmia.

To monitor for signs of ectopic pacemakers, scientists have developed mathematical models that predict the patterns of irregular heart activity that can emerge from this interference. In this new study, Glass’s team did experiments that put these models to the test.

Genetically modified

The team began by creating artificial pacemakers in cardiac cells taken from mice. These cells had been genetically modified so that the voltages produced by their cell membranes can be controlled using light. In thin layers of heart cells, the researchers used short light pulses to create pairs of pacemaker signals with slightly different frequencies (one sinus and the other ectopic), at spots positioned 8.5 mm apart.

In the region between the spots, they measured the number of sinus pulses detected between successive ectopic pulses – where the ectopic pulses occur at a lower frequency than the sinus pulses. Interference between the pulses causes this number to vary according to when and where in the sample the measurements are made.

Glass and colleagues discovered that the number of these intervening sinus pulses always came in distinctive triplets: such as 1, 2, 4; 1, 4, 6; or 4, 6, 11. These triplets all seemed to follow just two simple rules: that one number must be odd, and that the largest number must be one larger than the sum of the two smaller numbers.

Based on these rules, the researchers reproduced the same patterns in simple mathematical models, and also searched for the patterns in real electrocardiogram data from 47 patients. Despite the immense complexity of the heart, they detected the distinctive triplets in eight electrocardiograms.

Glass’s team hopes that the remarkable simplicity of the triplet pattern should make it easily detectable using wearable heartbeat monitors. This could strengthen the ability of cardiologists to diagnose and treat potentially life-threatening irregular heartbeats.

The research is described in Physical Review Letters.

Using radar to detect cosmic neutrinos in ice sheets, why Leo Szilard changed his mind on nuclear weapons

This episode of the Physics World Weekly podcast features Steven Prohira, who is co-leader of the Radar Echo Telescope collaboration, which aims to detect high energy cosmic neutrinos by sending radar waves through an Antarctic ice sheet. Based at the University of Kansas, Prohira explains the physics behind the project and talks about the fascinating history of previous attempts to use radar to detect particles from outer space.

Also on hand is Physics World’s Matin Durrani, who chats about the remarkable life of the Hungarian-American physicist Leo Szilard – who encouraged the US to develop nuclear weapons during the Second World War, but later opposed their use.

Robotic system uses multispectral imaging and artificial intelligence to search for earthquake victims

Robotic search system
Intelligent search: the system uses a multispectral camera (silver, top) mounted on a quadruped robot. (Courtesy: Christyan Cruz et al./2023 Mach. Learn.: Sci. Technol.)

The horrific aftermath of the recent earthquakes that struck Syria and Turkey makes it clear why a range of technologies are needed to search for survivors in the rubble of destroyed buildings. Now, researchers at the Polytechnic University of Madrid have developed an autonomous robotic system that combines artificial intelligence with multispectral imaging to search for people in dangerous and difficult to access post-disaster environments.

The system uses an Altum multispectral camera that operates at five wavelengths – red, green and blue visible light; near infrared; and red edge light. The camera is attached to a remote-controlled quadruped robot that can be deployed in dangerous environments such as a collapsed building.

Christyan Cruz Ulloa and colleagues developed multispectral indexes that can be used to identify people within rubble. An index is a way of combining images taken at different wavelengths to enhance the ability of the multispectral imaging system to identify specific objects. Such indexes are often used to identify vegetation in satellite images, but no index had existed for identifying people in a rubble environment.

Convolutional neural networks

Once the team had identified an index that was suitable for both indoor and outdoor identification of people within a background of rubble, the next step was to train several convolutional neural networks (CNNs) to identify human forms – such as a torso, head and hand – within rubble. The researchers then compared efficacy of the different CNNs. This allowed them to select the best CNN for this application – a CNN called YOLOv5m.

The researchers then compared their prototype technique with previous systems, which tend to use either red-green-blue or infrared imaging to locate victims. They conclude that their multispectral system has greater versatility when it comes to locating people in both indoor and outdoor environments.

The team describes the system in a paper that has been accepted for publication in Machine Learning: Science and Technology.

Could next-generation perovskite detectors improve clinical X-ray imaging?

Perovskite-based X-ray detectors have a lot to offer the field of diagnostic imaging: low production costs, direct conversion, high absorption efficiency and superior spatial resolution to existing detectors. But while these advantages have been demonstrated in previous studies, researchers have not yet determined whether they translate to improvements in clinical applications.

To investigate this potential in more depth, researchers in the X-ray Cancer Imaging and Therapy Experimental (XCITE) Lab at the University of Victoria in Canada have performed virtual clinical trials on next-generation perovskite detectors integrated into common X-ray imaging devices, reporting their findings in Physics in Medicine & Biology.

The team investigated the perovskite crystal methylammonium lead bromide (MAPbBr3), which combines high charge carrier mobility and long carrier lifetimes, making it extremely sensitive to incident X-ray photons. Indeed, some MAPbBr3 crystals show equivalent performance to that of cadmium zinc telluride (CZT), a promising material used in cutting edge medical imaging techniques such as photon-counting CT.

To determine which imaging applications may suit perovskite detectors, the researchers used TOPAS Monte Carlo (MC) simulations to calculate the energy deposition efficiency (EDE, the fraction of absorbed energy relative to the incident energy) of MAPbBr3, for crystal thicknesses between 40 and 15 mm and beam energies from 20 keV to 6 MeV.

They compared the results with four other detector materials: amorphous selenium (a-Se), commonly used for mammography; caesium iodide (CsI), the standard detector material for kilovoltage (kV) CT; gadolinium oxysulphide (GOS), as used in kV and megavoltage (MV) imaging; and CZT.

Due to the lead content in MAPbBr3, the perovskite exhibited the highest energy absorption of all the detectors in the mammographic energy range. For MV imaging, only CZT had superior EDE, while for kV imaging, perovskite did not generally perform as well as the others. Based on these findings, the team chose three imaging systems to study: the Koning dedicated breast CT scanner, and Varian’s Truebeam kV and MV cone-beam CT (CBCT) systems.

“The EDE simulations motivated the inclusion of breast CT, a more niche imaging system that we would not have simulated otherwise,” explains first author Jericho O’Connell. “The kV- and MV-CBCT systems would have been included regardless, as they are key parts of the radiotherapy workflow.”

Virtual clinical trials

O’Connell and colleagues used Fastcat hybrid MC simulations to optimize the perovskite detector design for each application. By maximizing the detective quantum efficiency (DQE, the efficiency of converting an input signal to an output image), they calculated the optimal thicknesses for the perovskite crystals as 0.30, 0.86 and 1.99 mm, for breast CT, kV- and MV-CBCT, respectively. They then used these device-specific detectors in a series of virtual clinical trials.

Images of phantoms using default detectors and perovskite detectors
Virtual clinical trials Images of phantoms using default detectors and perovskite detectors for breast CT (left), kV-CBCT (top right) and MV-CBCT (bottom right). The difference images show regions where perovskite has higher HU values in blue. (Courtesy: Phys. Med. Biol. 10.1088/1361-6560/acae15)

For the breast CT trial, the researchers simulated a breast phantom with microcalcifications imaged using the default CsI detector and a perovskite detector with the same pixel pitch (0.194 mm). The perovskite detector increased contrast in the microcalcifications by 87%, clearly visualizing a calcified lesion that was poorly defined using the CsI detector. This could enable more accurate identification of such structures in breast cancer screening when using a perovskite detector, which can be manufactured at lower cost than CsI.

In the kV and MV CBCT virtual trials, the researchers imaged an XCAT head phantom. In both cases, the perovskite detector dramatically improved image quality compared with the default detectors. In the kV images, spatial resolution in fine bone features and tissue contrast was improved dramatically using the perovskite detector, increasing the CNR in brain and skull by 8% and 13%, respectively, compared with the CsI detector.

The MV image focused on a skull region containing silver fillings that would generally produce large streaking artefacts in kV images. The high efficiency of the perovskite detector compared with a GOS detector resulted in dramatic improvement in CNR and enabled a metal artefact-free image of the jaw. The researchers point out that the improved contrast in MV-CBCT images with a perovskite detector could enable imaging of patients on radiotherapy machines without a kV on-board imager, as is the case for most systems in low- and middle-income countries.

Replacing the current detectors on the breast CT, kV-CBCT and MV-CBCT machines with optimized perovskite detectors improved the DQE of these systems by 12.1%, 9.5% and 86.1%, respectively. “Perovskite detectors perform better than current detectors in breast CT and kV-CBCT applications, and are far superior to current MV-CBCT detectors in terms of CNR and DQE,” the researchers conclude.

Next, the team plans to create prototype perovskite-based flat-panel detectors to experimentally verify the virtual trials. “We are excited to report that we have sent off crystals to get a prototype pixelated detector made through AY Sensors,” O’Connell tells Physics World. “Stay tuned for the experimental characterization of the prototype detector.”

Science elevated to cabinet position in UK government shake-up

Science has been elevated to a cabinet-level position in the UK government for the first time in decades. The move occurred yesterday after Conservative prime minister Rishi Sunak announced the creation of a new Department for Science, Innovation and Technology, which will be led by Chippenham MP Michelle Donelan.

The new high profile for science came as part of a reshuffle of UK government, which will see the Department for Business, Energy and Industrial Strategy (BEIS) split into three separate departments. In addition to science, there is a new Department for Energy Security and Net Zero as well as a Department for Business and Trade.

Donelan, who was previously secretary of state for digital, culture, media and sport, has been made secretary of state for science, innovation and technology. George Freeman retains his science brief, becoming minister of state in the new department. He was previously minister of state for BEIS.

According to the UK government, the new science department will “focus on positioning the UK at the forefront of global scientific and technological advancement” and “direct record levels of research and development”. In a statement, it said that a department focused on turning “scientific and technical innovations into practical, appliable solutions will help make sure the UK is the most innovative economy in the world”.

‘Good news’

Tom Grinyer, group chief executive officer of the Institute of Physics, which publishes Physics World, says that the cabinet seat for science is good news for the UK as it “puts science and innovation exactly where they should be – right at the heart of government”.

Grinyer says that Donelan must work with the scientific community and other departments to ensure the government’s plan for the UK to become a global science superpower stays on track and “that there is a genuinely joined-up approach to science across government”.

Adrian Smith, president of the Royal Society, has also welcomed the creation of the new science department. In a statement, he says it signals that “research and innovation sit at the heart of the prime minister’s productivity and growth agenda”.

Smith believes that Donelan’s first job must be for the UK to secure association to Horizon Europe and other European Union (EU) science programmes. Participation in Horizon Europe had been agreed as part of the post-Brexit trade deal between the UK and EU, but the association agreement has not yet been signed and has since become a bargaining chip in other political issues related to Brexit.

“These schemes support outstanding international collaboration and without being part of them we are undermining the prime  minister’s stated ambition for the UK to be at the forefront of science and technology globally,” Smith says.

Daniel Rathbone, assistant director of the Campaign for Science and Engineering, also highlights access to European research programmes as a key issue for the new department, along with reform of the R&D tax-relief system.

Rathbone warns, however, that it will be vital that “the practicalities of making changes in Whitehall aren’t allowed to take away from the time and resources needed to drive forward the promising [science and innovation] agenda the government has previously set out”.

  • Businesses are being held back by a lack of apprentices in key physics-related roles. That is according to a new report by the Institute of Physics, which highlights a massive shortfall in the numbers of women pursuing such apprenticeships. The report, which surveyed nearly 300 apprentices and interviewed over 90 organisations, also finds that people are concerned about the cost of living crisis while employers say they struggle to get into schools to talk to young people about their options.

Designing materials and systems for decarbonizing chemicals and water industries

Want to learn more on this subject?

Watch now

Storing cheap renewable electricity into chemical bonds (such as chemical energy storage) could be a transformative opportunity for long-duration energy storage that can address the intermittency of renewables and balance the mismatch between supply and demand at the grid.

The chemical industry primarily consumes fossil feedstock as an energy source, which has been the standard for more than a century. A paradigm shift is required to move towards a more sustainable route for chemical synthesis by electrifying and decarbonizing the modern chemical industry. As renewable electricity costs continue to decrease, there is a growing interest in fuels and chemical electrosynthesis.

This webinar focuses on developing systems, catalysts, and processes to use renewable electricity as an energetic driving force to produce high-value and high-energy molecules that can be utilized as either fuel, energy storers, and/or chemicals. Also discussed are future directions and strategies to manage the carbon, nitrogen, and water cycles, enabling a circular economy, mitigating waste, and promoting sustainability with positive social and environmental impacts through waste-water treatment and paving the way for nutrient recovery and recycling.

This research aims to develop next-generation sustainable industrial systems and processes that can aid in the transition to a net-zero-emission energy system and in meeting our world’s growing clean energy and water demands.

An interactive Q&A session follows the presentation.

Want to learn more on this subject?

Watch now
Reza Nazemi

Reza Nazemi is assistant professor in the Department of Mechanical Engineering and the School of Advanced Materials Discovery at Colorado State University (CSU). His group at CSU focuses on designing and developing systems and materials for clean-energy generation and waste-water treatment. In addition, his group leverages advanced spectroscopic and microscopic techniques to gain a mechanistic understanding of photoelectrochemical reactions for sustainable fuel and fertilizer production.

Dr Nazemi earned his PhD from the Woodruff School of Mechanical Engineering at the Georgia Institute of Technology (Georgia Tech) in 2020 followed by a postdoctoral fellowship there in the School of Chemistry and Biochemistry (2020–2021). From 2021–2022, he was a postdoctoral associate in the Department of Chemical and Environmental Engineering at Yale University. Reza’s notable recognition includes the 2022 ECS Colin Garfield Fink Fellowship, 2021 American Chemical Society Physical Chemistry Division Young Investigator Award, and 2018 Amazon Catalyst at ECS award. In 2020, he was the Georgia Tech Technology Innovation: Generating Economic Results Class of 2020 Fellow, and received the Georgia Research Alliance Award and Georgia Tech-Oak Ridge National Lab Seed Grant Award.

Practical approach to MR-guided online adaptive radiation therapy

Want to learn more on this subject?

Watch now

From Laura Bassi to Marie Curie, for centuries, women have been making important contributions to the world of physics. Now with ViewRay’s MRIdian system, women are leading the charge in bringing the latest advancement of MRI-guided radiation therapy to the forefront of radiation oncology and expanding the medical physics landscape.

MR-guided radiation therapy has stimulated a paradigm shift in external beam radiation therapy. Daily online adaptive therapy is now possible by introducing an advanced imaging modality during treatment delivery. Efforts to streamline its approach are prudent to broaden its availability and realize the clinical benefits. The implementation of a practical approach to an MRgRT online ART workflow will be discussed.

This series of five webinars will specifically highlight women physicists across the globe that are using MRIdian to transform cancer care as we know it. Jennifer Dolan of Henry Ford Health will present this webinar.

This presentation is the third in a series of Women in Medical Physics, supported by ViewRay.

Want to learn more on this subject?

Watch now
Jennifer Dolan

Jennifer Dolan is the director of MR-guided radiation therapy physics at the Henry Ford Cancer Institute in Detroit, Michigan, where she also serves on the radiosurgery physics team. Dr Dolan received her PhD in nuclear engineering and radiological sciences from the University of Michigan in 2013. Upon completion of her studies, Jennifer worked in the nuclear security and nuclear well logging fields. She returned to the University of Michigan in 2016 to obtain her certificate in medical physics and completed her residency at Henry Ford Health in 2019. Her research interests focus on MR-guided adaptive radiation therapy and innovations in novel MR-guided applications to radiation therapy.

Dose tracking during radiotherapy could enable safer cancer treatments

Real-time dose monitoring
Real-time dose monitoring Top row, left to right: dose distribution for a C-shaped treatment plan delivered to a phantom; relative dose distribution imaged with iRAI; 60% (blue) and 80% (brown) isodose lines, showing good agreement between the planned and iRAI-imaged dose. Bottom row: temporal dose accumulation imaged by iRAI. (Courtesy: CC BY 4.0/Nat. Biotechnol. 10.1038/s41587-022-01593-8)

Radiotherapy of moving lesions is challenging. Delivery of the therapeutic radiation to a planned target volume may be impacted by organ motion, while anatomical deformations and set-up uncertainties can cause targeting errors. If radiation oncologists had an accurate, real-time 3D radiation dose distribution map, they would be able to alter the level or trajectory of radiation online to achieve more effective and safer treatments.

Ionizing radiation acoustic imaging (iRAI) is a non-invasive technology that could provide this capability. By reconstructing radiation dose using acoustic waves, iRAI can map dose deposition in tumours and adjacent healthy tissues and monitor dose accumulation in real time during radiotherapy, without the need to use additional radiation sources.

A multi-speciality research team at the University of Michigan and Moffitt Cancer Center has now developed a clinical grade iRAI volumetric imaging system. The system, described in Nature Biotechnology, achieved 3D semiquantitative mapping of X-ray beam delivery deep into the body during radiotherapy of a patient with liver metastases.

The iRAI technique works via the thermoacoustic effect. When a high-energy pulsed photon beam generated by a linear accelerator strikes body tissue, it is absorbed. This absorbed energy transfers into heat, which causes localized thermal expansion and generates acoustic waves. These waves are weak, however, and usually undetectable by clinical ultrasound technology.

The new iRAI system detects the acoustic signals with a custom-designed 2D matrix array transducer and a matching multi-channel preamplifier board, driven by a commercial research ultrasound system. The amplified signal is then transferred into an ultrasound device to construct dose-related images in real time.

The researchers explain that their dual-modality system, which combines iRAI with ultrasound imaging, offers “a promising solution to solve the need for real-time monitoring of beam position and online assessment of delivering dose during radiotherapy”. The ultrasound image presents the morphological tissue structures and motion in the body, as well as functional information such as blood flow and vascular density, while the iRAI image can map and quantify the spatially distributed dose deposition in different biological tissues.

“This clinical trial was a pilot study to assess the feasibility of using iRAI in patients receiving abdominal stereotactic body radiation therapy (SBRT),” explains clinical principal investigator Kyle Cuneo from Michigan’s Rogel Cancer Center. “Its findings are enabling us to optimize the iRAI system.”

iRAI experimental setups
Experimental set-ups Schematic of the iRAI system for mapping the dose deposition in a patient during radiotherapy (a). CAD view of a 2D matrix array with an integrated preamplifier board (b). Set-up for the phantom (c) and rabbit (d, e) studies. (Courtesy: CC BY 4.0/Nat. Biotechnol. 10.1038/s41587-022-01593-8)

For their proof-of-concept study, the researchers validated the system in a cylindrical lard phantom, a rabbit and then a patient undergoing abdominal SBRT. To enhance the signal-to-noise ratio (SNR) when detecting radiation acoustic signals, they selected a central frequency of 0.35 MHz to match the power spectrum of the acoustic signals generated by the 4 µs X-ray pulse. The SNR was further enhanced by the 1024-channel preamplifier with 46 dB gain integrated with the 2D matrix array, and by displaying the iRAI images with 25 times averaging.

After verifying the system performance using the phantom, the team created and tested a clinical treatment plan to irradiate the liver of a rabbit. The iRAI measurements showed high consistency between the measured dose distribution and that generated by the treatment planning system.

The team then prepared radiotherapy plans for the study participant, with the treatment plan for each fraction divided into two parts. The first part was for iRAI imaging and comprised 2.087 and 0.877 Gy beams delivered in the superior and inferior anterior directions, respectively. This was followed by a volumetric-modulated arc therapy plan (without iRAI imaging) to ensure that the total delivered radiation dose met the clinical requirements.

Both the dose locations and the overall distributions of iRAI measurements matched well with the treatment plan. The iRAI volumetric imaging was able to map the high-dose area with high accuracy. The researchers note that they need to optimize the mapping accuracy for lower dose intensity areas, improve spatial resolution, and develop a comprehensive calibration protocol to provide absolute dose measurement, using advanced reconstruction techniques exploiting artificial intelligence.

Grant principal investigator Issam El Naqa from the Moffitt Cancer Center advises that the current system will be augmented with real-time ultrasound imaging and will also be evaluated in the context of high-risk delivery scenarios such as FLASH radiotherapy.

“One potential application of this technology in the future is real-time adaptive treatment delivery. Current adaptive treatment techniques are based mainly on anatomical changes in the tumour and organs-at-risk (OARs),” explains Cuneo. “With iRAI, we can use both anatomical information, and more importantly, dosimetric information to adapt the radiation plan. This could allow for dose escalation in the target, especially in situations where there is an adjacent OAR, and provide for safer treatments by accurately quantifying the true dose delivered to the target and OARs during each fraction.”

“The system has the unique capability of visualizing radiation deposition while monitoring organ motion, allowing better pinpointing of radiation to targeted tumours while sparing uninvolved tissue in a cost saving manner,” El Naqa adds. “This can be equally applied in both developed and developing countries where financial resources are scarce, leading to improved patient care and better outcomes in these places.”

Hydrogen-producing solar cells mimic photosynthesis

Illustration showing sun shining on an array of solar-energy-to-hydrogen devices located in shallow water. A lens system directs UV and visible light to the devices and infrared light to heat the water around them.
Using the full spectrum of sunlight contributes to the higher efficiency of the new system. (Courtesy: Z Mi)

Two independent teams have taken inspiration from nature to develop better ways of producing hydrogen with solar cells. The first team, from the University of Michigan in the US, achieved a record-breaking solar-energy-to-hydrogen efficiency of more than 9% using a solar panel containing an indium gallium nitride (InGaN) catalyst. The second team, from the EPFL in Switzerland and Toyota Motors Europe, created a new type of transparent, porous gas diffusion electrode that harvests water from the air and turns it into hydrogen when exposed to sunlight. Both technologies could, in principle, supply hydrogen for fuel cells and industrial processes in a “green” way, without the need for fossil-fuel precursors.

In photocatalytic solar water splitting, scientists use the energy from sunlight to split water into its component elements: oxygen and hydrogen. This process mimics a crucial step in natural photosynthesis and could be a clean and renewable way to produce energy. The problem is that the efficiency of the solar-to-hydrogen (STH) process is very low, making it uneconomical compared with fossil-fuel-based methods of generating the large quantities of hydrogen needed for various industrial processes.

9.2% efficiency

At Michigan, Zetian Mi and colleagues used the ultraviolet-to-visible part of the Sun’s spectrum to photoexcite the semiconductor InGaN, causing it to produce electrons and “holes” (regions of positive charge) that can split water into hydrogen and oxygen. The researchers then used the infrared portion of sunlight to heat the reaction system to around 70 °C. This heating helped to prevent the hydrogen and oxygen from recombining to form water, which is the main “backreaction” in water splitting and a major limiting factor in STH efficiency.

Using pure water, this strategy resulted in a STH efficiency of 9.2% under concentrated simulated sunlight – 10 times greater than previous such experiments. Under the same conditions, the researchers achieved an efficiency of 7.4% using tap water and 6.6% with sea water. They also obtained an efficiency of 6.2% using pure water in a large-scale prototype photocatalytic water-splitting system located outdoors.

The device, which the team describes in Nature, is also stable at high temperatures and at light intensities equivalent to 160 Suns. “In principle, this technology can supply hydrogen for fuel cell stations and any industrial processes that require hydrogen,” Mi tells Physics World. “A unique advantage of this approach is the distributed generation of hydrogen, compared to conventional centralized steam methane reforming processes, thereby significantly reducing the cost associated with hydrogen transportation.”

Like an artificial leaf

The gas diffusion electrodes made by Marina Caretti and colleagues in the EPFL team, meanwhile, are based on quartz (silicon dioxide) fibres processed into felt wafers that are then fused together at temperatures of 1350 °C. The team coated the resulting transparent porous substrates with a transparent thin film of a photoactive material, fluorine-doped tin oxide, in an atmospheric chemical vapour deposition process for 10 min at 600 °C with monobutyltin trichloride and trifluoroacetic acid.

The structure thus produced has a porosity of 90%, giving it the maximum amount of contact with water vapour in the air and a good conductivity of 20 ± 3 Ω sq−1. It is also transparent, allowing light to pass through the coated semiconductor.

When exposed to sunlight, this device behaves like an artificial leaf, harvesting water from the air and using sunlight to produce energy (in the form of hydrogen gas, in this case). The energy from the solar radiation is stored in hydrogen bonds, similar to the way that plant leaves store energy in the chemical bonds of sugars and starches produced during photosynthesis.

Technology could harvest humidity from the air

The EPFL researchers, who detail their work in Advanced Materials, acknowledge that the solar-to-hydrogen conversion efficiency of their photoelectrochemical (PEC) device is quite low. However, maximizing this efficiency was not a goal of their study, and team member Kevin Sivula points out that its maximum theoretical efficiency is around 12%. This, he says, indicates “promise for improvement”.

“The system concept will also eliminate the need for a highly acidic electrolyte, traditionally employed in PEC devices,” he tells Physics World.

The EPFL team’s prototype was only stable for about an hour under one Sun’s worth of illumination, which Sivula says will “need to be improved” to make the device practical. One possible application for it might be in PEC cells, which use incident light to stimulate a photosensitive material such as a semiconductor that is immersed in liquid solution. The goal in this case is to drive chemical reactions, but the process has some drawbacks – one being that it is complicated to make large-area PEC devices that use such a solution. The new work shows that PEC technology can be adapted to harvest humidity from the air instead.

Optimization in progress

The EPFL researchers are now seeking to optimize their system by studying different fibre and pore sizes and different semiconductor materials. They are pursuing their work in the context of the EU Project Sun-to-X, which is dedicated to advancing this technology.

The Michigan researchers, for their part, now plan to separate the pure hydrogen from mixed hydrogen and oxygen produced in their photocatalytic water splitting process using a membrane. “We will also develop a new photocatalytic approach to directly produce high-purity hydrogen from water splitting,” Mi says.

Coherent correlation imaging tracks fluctuations on the nanoscale

Using a new image reconstruction technique, physicists in Germany and the US have made clear and detailed movies of nanoscale fluctuations in a magnetic material. To capture these features, a team led by Christopher Klose at the Max Born Institute, Berlin, used an advanced algorithm to identify correlations in the spatial patterns in multiple X-ray images.

Fluctuations and phase transitions are a near-universal features of matter and X-ray and electron imaging techniques can be used to observe these phenomena on the nanoscale. However, these methods have an inherent trade-off between high spatial resolution and high temporal resolution – the latter being needed to track the dynamics of fluctuations and phase transitions.

While both temporal and spatial resolution can be improved by boosting illumination, intense beams of X-rays and electrons can damage delicate features in a sample.

To overcome this limitation, Klose’s team has developed a technique called coherent correlation imaging (CCI). Their approach relies on the fact that nanoscale fluctuations are not entirely random, but instead display distinctive spatial patterns.

Many snapshots

CCI first involves taking thousands of snapshots of samples in quick succession, using relatively low levels of illumination. While these snapshots appear to be mostly indistinct from each other, the researchers found they contain enough information to categorise each image using a hierarchical clustering algorithm. This sorts the images into groups with spatial patterns that display clear correlations. By combining the images in each group, the team was able to reconstruct clear images of the patterns in samples.

To demonstrate their approach, Klose and colleagues used CCI and X-rays to image fluctuations in a thin-film ferromagnet. This material is widely used in modern hard drives, where information is encoded into magnetic domains. These are nanoscale regions in which the magnetization can either point in one of two opposing directions. These domains are known to be highly stable at room temperature, with little information lost due to fluctuations. So far, however, researchers have not been able to confirm this stability directly by imaging the material.

Klose’s team used CCI to test the ferromagnet’s stability at 37 °C, which is above room temperature. Far from remaining static, the algorithm identified transitions between 30 distinct domain states in the film. By assessing the similarity between these states, the researchers also determined the order in which the transitions occurred. This allowed Klose and colleagues to construct clear, detailed movies of the fluctuations.

Through further improvements, CCI could soon enable researchers to answer fundamental questions surrounding the nature of phase transitions in advanced materials including high-temperature superconductors. Klose and colleagues now hope to extend their technique to electron microscopy – allowing them to reconstruct images on even smaller scales.

The technique is described in Nature.

Copyright © 2025 by IOP Publishing Ltd and individual contributors