This talk shows how integrating p-type NiO to form NiO/Ga_₂O_₃ heterojunction rectifiers overcomes that barrier, enabling record-class breakdown and Ampere-class operation. It will cover device structure/process optimization, thermal stability to high temperatures, and radiation response – with direct ties to today’s priorities: EV fast charging, AI data‑center power systems, and aerospace/space‑qualified power electronics.

An interactive Q&A session follows the presentation.

Jian-Sian Li received the PhD in chemical engineering from the University of Florida in 2024, where his research focused on NiO/β-Ga_₂O_₃ heterojunction power rectifiers, includes device design, process optimization, fast switching, high-temperature stability, and radiation tolerance (γ, neutron, proton). His work includes extensive electrical characterization and microscopy/TCAD analysis supporting device physics and reliability in harsh environments. Previously, he completed his BS and MS at National Taiwan University (2015, 2018), with research spanning phoretic/electrokinetic colloids, polymers for OFETs/PSCs, and solid-state polymer electrolytes for Li-ion batteries. He has since transitioned to industry at Micron Technology.

The post Fabrication and device performance of Ni0/Ga₂O₃ heterojunction power rectifiers appeared first on Physics World.

A new integrated “snapshot spectroscopy” system developed in China can determine the spectral and spatial composition of light from an object with much better precision than other existing systems. The instrument uses randomly textured lithium niobate and its developers have used it for astronomical imaging and materials analysis – and they say that other applications are possible.

Spectroscopy is crucial to analysis of all kinds of objects in science and engineering, from studying the radiation emitted by stars to identifying potential food contaminants. Conventional spectrometers – such as those used on telescopes – rely on diffractive optics to separate incoming light into its constituent wavelengths. This makes them inherently large, expensive and inefficient at rapid image acquisition as the light from each point source has to be spatially separated to resolve the wavelength components.

In recent years researchers have combined computational methods with advanced optical sensors to create computational spectrometers with the potential to rival conventional instruments. One such approach is hyperspectral snapshot imaging, which captures both spectral and spatial information in the same image. There are currently two main snapshot-imaging techniques available. Narrowband-filtered snapshot spectral imagers comprise a mosaic pattern of narrowband filters and acquire an image by taking repeated snapshots at different wavelengths. However, these trade spectral resolution with spatial resolution, as each extra band requires its own tile within the mosaic. A more complex alternative design – the broadband-modulated snapshot spectral imager – uses a single, broadband detector covered with a spatially varying element such as a metasurface that interacts with the light and imprints spectral encoding information onto each pixel. However, these are complex to manufacture and their spectral resolution is limited to the nanometre scale.

Random thicknesses

In the new work, researchers led by Lu Fang at Tsinghua University in Beijing unveil a spectroscopy technique that utilizes the nonlinear optical properties of lithium niobate to achieve sub-Ångström spectral resolution in a simply fabricated, integrated snapshot detector they call RAFAEL. A lithium niobate layer with random, sub-wavelength thickness variations is surrounded by distributed Bragg reflectors, forming optical cavities. These are integrated into a stack with a set of electrodes. Each cavity corresponds to a single pixel. Incident light enters  from one side of a cavity, interacting with the lithium niobate repeatedly before exiting and being detected. Because lithium niobate is nonlinear, its response varies with the wavelength of the light.

The researchers then applied a bias voltage using the electrodes. The nonlinear optical response of lithium niobate means that this bias alters its response to light differently at different wavelengths. Moreover, the random variation of the lithium niobate’s thickness around the surface means that the wavelength variation is spatially specific.

The researchers designed a machine learning algorithm and trained it to use this variation of applied bias voltage with resulting wavelength detected at each point to reconstruct the incident wavelengths on the detector at each point in space.

“The randomness is useful for making the equations independent,” explains Fang; “We want to have uncorrelated equations so we can solve them.”

Thousands of stars

The researchers showed that they could achieve 88 Hz snapshot spectroscopy on a grid of 2048×2048 pixels with a spectral resolution of 0.5 Å (0.05 nm) between wavelengths of 400–1000 nm. They demonstrated this by capturing the full atomic absorption spectra of up to 5600 stars in a single snapshot. This is a two to four orders of magnitude improvement in observational efficiency over world-class astronomical spectrometers. They also demonstrated other applications, including a materials analysis challenge involving the distinction of a real leaf from a fake one. The two looked identical at optical wavelengths, but, using its broader range of wavelengths, RAFAEL was able to distinguish between the two.

The researchers are now attempting to improve the device further: “I still think that sub-Ångstrom is not the ending – it’s just the starting point,” says Fu. “We want to push the limit of our resolution to the picometre.” In addition, she says, they are working on further integration of the device – which requires no specialized lithography – for easier use in the field. “We’ve already put this technology on a drone platform,” she reveals. The team is also working with astronomical observatories such as Gran Telescopio Canarias in La Palma, Spain.

The research is described in Nature.

Computational imaging expert David Brady of Duke University in North Carolina is impressed by the instrument. “It’s a compact package with extremely high spectral resolution,” he says; “Typically an optical instrument, like a CMOS sensor that’s used here, is going to have between 10,000 and 100,000 photo-electrons per pixel.  That’s way too many photons for getting one measurement…I think you’ll see that with spectral imaging as is done here, but also with temporal imaging. People are saying you don’t need to go at 30 frames second, you can go at a million frames per second and push closer to the single photon limit, and then that would require you to do computation to figure out what it all means.”

The post Randomly textured lithium niobate gives snapshot spectrometer a boost appeared first on Physics World.

A research team headed up at Wayne State University School of Medicine in the US has developed a novel treatment for glioblastoma, based on exposure to low levels of radiofrequency electromagnetic fields (RF EMF). The researchers demonstrated that the new therapy slows the growth of glioblastoma cells in vitro and, for the first time, showed its feasibility and clinical impact in patients with brain tumours.

The study, led by Hugo Jimenez and reported in Oncotarget, uses a device developed by TheraBionic that delivers amplitude-modulated 27.12 MHz RF EMF throughout the entire body, via a spoon-shaped antenna placed on the tongue. Using tumour-specific modulation frequencies, the device has already received US FDA approval for treating patients with advanced hepatocellular carcinoma (HCC, a liver cancer), while its safety and effectiveness are currently being assessed in clinical trials in patients with pancreatic, colorectal and breast cancer.

In this latest work, the team investigated its use in glioblastoma, an aggressive and difficult to treat brain tumour.

To identify the particular frequencies needed to treat glioblastoma, the team used a non-invasive biofeedback method developed previously to study patients with various types of cancer. The process involves measuring variations in skin electrical resistance, pulse amplitude and blood pressure while individuals are exposed to low levels of amplitude-modulated frequencies. The approach can identify the frequencies, usually between 1 Hz and 100 kHz, specific to a single tumour type.

Jimenez and colleagues first examined the impact of glioblastoma-specific amplitude-modulated RF EMF (GBMF) on glioblastoma cells, exposing various cell lines to GBMF for 3 h per day at the exposure level used for patient treatments. After one week, GBMF decreased the proliferation of three glioblastoma cell lines (U251, BTCOE-4765 and BTCOE-4795) by 34.19%, 15.03% and 14.52%, respectively.

The team note that the level of this inhibitive effect (15–34%) is similar to that observed in HCC cell lines (19–47%) and breast cancer cell lines (10–20%) treated with tumour-specific frequencies. A fourth glioblastoma cell line (BTCOE-4536) was not inhibited by GBMF, for reasons currently unknown.

Next, the researchers examined the effect of GBMF on cancer stem cells, which are responsible for treatment resistance and cancer recurrence. The treatment decreased the tumour sphere-forming ability of U251 and BTCOE-4795 cells by 36.16% and 30.16%, respectively – also a comparable range to that seen in HCC and breast cancer cells.

Notably, these effects were only induced by frequencies associated with glioblastoma. Exposing glioblastoma cells to HCC-specific modulation frequencies had no measurable impact and was indistinguishable from sham exposure.

Looking into the underlying treatment mechanisms, the researchers hypothesized that – as seen in breast cancer and HCC – glioblastoma cell proliferation is mediated by T-type voltage-gated calcium channels (VGCC). In the presence of a VGCC blocker, GBMF did not inhibit cell proliferation, confirming that GBMF inhibition of cell proliferation depends on T-type VGCCs, in particular, a calcium channel known as CACNA1H.

The team also found that GBMF blocks the growth of glioblastoma cells by modulating the “Mitotic Roles of Polo-Like Kinase” signalling pathway, leading to disruption of the cells’ mitotic spindles, critical structures in cell replication.

A clinical first

Finally, the researchers used the TheraBionic device to treat two patients: a 38-year-old patient with recurrent glioblastoma and a 47-year-old patient with the rare brain tumour oligodendroglioma. The first patient showed signs of clinical and radiological benefit following treatment; the second exhibited stable disease and tolerated the treatment well.

“This is the first report showing feasibility and clinical activity in patients with brain tumour,” the authors write. “Similarly to what has been observed in patients with breast cancer and hepatocellular carcinoma, this report shows feasibility of this treatment approach in patients with malignant glioma and provides evidence of anticancer activity in one of them.”

The researchers add that a previous dosimetric analysis of this technique measured a whole-body specific absorption rate (SAR, the rate of energy absorbed by the body when exposed to RF EMF) of 1.35 mW/kg and a peak spatial SAR (over 1 g of tissue) of 146–352 mW/kg. These values are well within the safety limits set by the ICNIRP (whole-body SAR of 80 mW/kg; peak spatial SAR of 2000 mW/kg). Organ-specific values for grey matter, white matter and the midbrain also had mean SAR ranges well within the safety limits.

The team concludes that the results justify future preclinical and clinical studies of the TheraBionic device in this patient population. “We are currently in the process of designing clinical studies in patients with brain tumors,” Jimenez tells Physics World.

The post Tumour-specific radiofrequency fields suppress brain cancer growth appeared first on Physics World.

Physicists at the Technical University of Denmark have demonstrated what they describe as a “strong and unconditional” quantum advantage in a photonic platform for the first time. Using entangled light, they were able to reduce the number of measurements required to characterize their system by a factor of 10¹¹, with a correspondingly huge saving in time.

“We reduced the time it would take from 20 million years with a conventional scheme to 15 minutes using entanglement,” says Romain Brunel, who co-led the research together with colleagues Zheng-Hao Liu and Ulrik Lund Andersen.

Although the research, which is described in Science, is still at a preliminary stage, Brunel says it shows that major improvements are achievable with current photonic technologies. In his view, this makes it an important step towards practical quantum-based protocols for metrology and machine learning.

From individual to collective measurement

Quantum devices are hard to isolate from their environment and extremely sensitive to external perturbations. That makes it a challenge to learn about their behaviour.

To get around this problem, researchers have tried various “quantum learning” strategies that replace individual measurements with collective, algorithmic ones. These strategies have already been shown to reduce the number of measurements required to characterize certain quantum systems, such as superconducting electronic platforms containing tens of quantum bits (qubits), by as much as a factor of 10⁵.

A photonic platform

In the new study, Brunel, Liu, Andersen and colleagues obtained a quantum advantage in an alternative “continuous-variable” photonic platform. The researchers note that such platforms are far easier to scale up than superconducting qubits, which they say makes them a more natural architecture for quantum information processing. Indeed, photonic platforms have already been crucial to advances in boson sampling, quantum communication, computation and sensing.

The team’s experiment works with conventional, “imperfect” optical components and consists of a channel containing multiple light pulses that share the same pattern, or signature, of noise. The researchers began by performing a procedure known as quantum squeezing on two beams of light in their system. This caused the beams to become entangled – a quantum phenomenon that creates such a strong linkage that measuring the properties of one instantly affects the properties of the other.

The team then measured the properties of one of the beams (the “probe” beam) in an experiment known as a 100-mode bosonic displacement process. According to Brunel, one can imagine this experiment as being like tweaking the properties of 100 independent light modes, which are packets or beams of light. “A ‘bosonic displacement process’ means you slightly shift the amplitude and phase of each mode, like nudging each one’s brightness and timing,” he explains. “So, you then have 100 separate light modes, and each one is shifted in phase space according to a specific rule or pattern.”

By comparing the probe beam to the second (“reference”) beam in a single joint measurement, Brunel explains that he and his colleagues were able to cancel out much of the uncertainties in these measurements. This meant they could extract more information per trial than they could have by characterizing the probe beam alone. This information boost, in turn, allowed them to significantly reduce the number of measurements – in this case, by a factor of 10¹¹.

While the DTU researchers acknowledge that they have not yet studied a practical, real-world system, they emphasize that their platform is capable of “doing something that no classical system will ever be able to do”, which is the definition of a quantum advantage. “Our next step will therefore be to study a more practical system in which we can demonstrate a quantum advantage,” Brunel tells Physics World.

The post Entangled light leads to quantum advantage appeared first on Physics World.

This episode of Physics World Stories features an interview with Jessica Esquivel and Emily Esquivel – the creative duo behind Queer Quest. The event created a shared space for 2SLGBTQIA+ Black and Brown people working in science, technology, engineering, arts and mathematics (STEAM).

Mental health professionals also joined Queer Quest, which was officially recognized by UNESCO as part of the International Year of Quantum Science and Technology (IYQ). Over two days in Chicago this October, the event brought science, identity and wellbeing into powerful conversation.

Jessica Esquivel, a particle physicist and associate scientist at Fermilab, is part of the Muon g-2 experiment, pushing the limits of the Standard Model. Emily Esquivel is a licensed clinical professional counsellor. Together, they run Oyanova, an organization empowering Black and Brown communities through science and wellness.

Quantum metaphors and resilience through connection

Queer Quest blended keynote talks, with collective conversations, alongside meditation and other wellbeing activities. Panellists drew on quantum metaphors – such as entanglement – to explore identity, community and mental health.

In a wide-ranging conversation with podcast host Andrew Glester, Jessica and Emily speak about the inspiration for the event, and the personal challenges they have faced within academia. They speak about the importance of building resilience through community connections, especially given the social tensions in the US right now.

Hear more from Jessica Esquivel in her 2021 Physics World Stories appearance on the latest developments in muon science.

The post Queer Quest: a quantum-inspired journey of self-discovery appeared first on Physics World.

Physicists have developed a novel imaging technique for detecting and characterizing objects hidden within opaque, highly scattering material. The researchers, from France and Austria, showed that their new mathematical approach, which utilizes the fact that hidden objects generate their own complex scattering pattern, or “fingerprint”, can work on biological tissue.

Viewing the inside of the human body is challenging due to the scattering nature of tissue. With ultrasound, when waves propagate through tissue they are reflected, bounce around and scatter chaotically, creating noise that obscures the signal from the object that the medical practitioner is trying to see. The further you delve into the body the more incoherent the image becomes.

There are techniques for overcoming these issues, but as scattering increases – in more complex media or as you push deeper through tissue – they struggle and unpicking the required signal becomes too complex.

The scientists behind the latest research, from the Institut Langevin in Paris, France and TU Wien in Vienna, Austria, say that rather than compensating for scattering, their technique instead relies on detecting signals from the hidden object in the disorder.

Objects buried in a material create their own complex scattering pattern, and the researchers found that if you know an object’s specific acoustic signal it’s possible to find it in the noise created by the surrounding environment.

“We cannot see the object, but the backscattered ultrasonic wave that hits the microphones of the measuring device still carries information about the fact that it has come into contact with the object we are looking for,” explains Stefan Rotter, a theoretical physicist at TU Wien.

Rotter and his colleagues examined how a series of objects scattered ultrasound waves in an interference-free environment. This created what they refer to as fingerprint matrices: measurements of the specific, characteristic way in which each object scattered the waves.

The team then developed a mathematical method that allowed them to calculate the position of each object when hidden in a scattering medium, based on its fingerprint matrix.

“From the correlations between the measured reflected wave and the unaltered fingerprint matrix, it is possible to deduce where the object is most likely to be located, even if the object is buried,” explains Rotter.

The team tested the technique in three different scenarios. The first experiment trialled the ultrasound imaging of metal spheres in a dense suspension of glass beads in water. Conventional ultrasound failed in this setup and the spheres were completely invisible, but with their novel fingerprint method the researchers were able to accurately detect them.

Next, to examine a medical application for the technique, the researchers embedded lesion markers often used to monitor breast tumours in a foam designed to mimic the ultrasound scattering of soft tissue. These markers can be challenging to detect due to scatterers randomly distributed in human tissue. With the fingerprint matrix, however, the researchers say that the markers were easy to locate.

Finally, the team successfully mapped muscle fibres in a human calf using the technique. They claim this could be useful for diagnosing and monitoring neuromuscular diseases.

According to Rotter and his colleagues, their fingerprint matrix method is a versatile and universal technique that could be applied beyond ultrasound to all fields of wave physics. They highlight radar and sonar as examples of sensing techniques where target identification and detection in noisy environments are long-standing challenges.

“The concept of the fingerprint matrix is very generally applicable – not only for ultrasound, but also for detection with light,” Rotter says. “It opens up important new possibilities in all areas of science where a reflection matrix can be measured.”

The researchers report their findings in Nature Physics.

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What skills do you use every day in your job?

Obviously, I write: I wouldn’t be a very good science writer if I couldn’t. So communication skills are vital. Recently, for example, Qruise launched a new magnetic-resonance product for which I had to write a press release, create a new webpage and do social-media posts. That meant co-ordinating with lots of different people, finding out the key features to advertise, identifying the claims we wanted to make – and if we have the data to back those claims up. I’m not an expert in quantum computing or magnetic-resonance imagining or even marketing so I have to pick things up fast and then translate technically complex ideas from physics and software into simple messages for a broader audience. Thankfully, my colleagues are always happy to help. Science writing is a difficult task but I think I’m getting better at it.

What do you like best and least about your job?

I love the variety and the fact that I’m doing so many different things all the time. If there’s a day I feel I want something a little bit lighter, I can do some social media or the website, which is more creative. On the other hand, if I feel I could really focus in detail on something then I can write some documentation that is a little bit more technical. I also love the flexibility of remote working, but I do miss going to the office and socialising with my colleagues on a regular basis. You can’t get to know someone as well online, it’s nicer to have time with them in person.

What do you know today, that you wish you knew when you were starting out in your career?

That’s a hard one. It would be easy to say I wish I’d known earlier that I could combine science and writing and make a career out of that. On the other hand, if I’d known that, I might not have done my PhD – and if I’d gone into writing straight after my undergraduate degree, I perhaps wouldn’t be where I am now. My point is, it’s okay not to have a clear plan in life. As children, we’re always asked what we want to be – in my case, my dream from about the age of four was to be a vet. But then I did some work experience in a veterinary practice and I realized I’m really squeamish. It was only when I was 15 or 16 that I discovered I wanted to do physics because I liked it and was good at it. So just follow the things you love. You might end up doing something you never even thought was an option.

The post Ask me anything: Kirsty McGhee – ‘Follow what you love: you might end up doing something you never thought was an option’ appeared first on Physics World.

Future versions of the Laser Interferometer Gravitational Wave Observatory (LIGO) will be able to run at much higher laser powers thanks to a sophisticated new system that compensates for temperature changes in optical components. Known as FROSTI (for FROnt Surface Type Irradiator) and developed by physicists at the University of California Riverside, US, the system will enable next-generation machines to detect gravitational waves emitted when the universe was just 0.1% of its current age, before the first stars had even formed.

Gravitational waves are distortions in spacetime that occur when massive astronomical objects accelerate and collide. When these distortions pass through the four-kilometre-long arms of the two LIGO detectors, they create a tiny difference in the (otherwise identical) distance that light travels between the centre of the observatory and the mirrors located at the end of each arm. The problem is that detecting and studying gravitational waves requires these differences in distance to be measured with an accuracy of 10^-19 m, which is 1/10 000^th the size of a proton.

Extending the frequency range

LIGO overcame this barrier 10 years ago when it detected the gravitational waves produced when two black holes located roughly 1.3 billion light–years from Earth merged. Since then, it and two smaller facilities, KAGRA and VIRGO, have observed many other gravitational waves at frequencies ranging from 30–2000 Hz.

Observing waves at lower and higher frequencies in the gravitational wave spectrum remains challenging, however. At lower frequencies (around 10–30 Hz), the problem stems from vibrational noise in the mirrors. Although these mirrors are hefty objects – each one measures 34 cm across, is 20 cm thick and has a mass of around 40 kg – the incredible precision required to detect gravitational waves at these frequencies means that even the minute amount of energy they absorb from the laser beam is enough to knock them out of whack.

At higher frequencies (150 – 2000 Hz), measurements are instead limited by quantum shot noise. This is caused by the random arrival time of photons at LIGO’s output photodetectors and is a fundamental consequence of the fact that the laser field is quantized.

A novel adaptive optics device

Jonathan Richardson, the physicist who led this latest study, explains that FROSTI is designed to reduce quantum shot noise by allowing the mirrors to cope with much higher levels of laser power. At its heart is a novel adaptive optics device that is designed to precisely reshape the surfaces of LIGO’s main mirrors under laser powers exceeding 1 megawatt (MW), which is nearly five times the power used at LIGO today.

Though its name implies cooling, FROSTI actually uses heat to restore the mirror’s surface to its original shape. It does this by projecting infrared radiation onto test masses in the interferometer to create a custom heat pattern that “smooths out” distortions and so allows for fine-tuned, higher-order corrections.

The single most challenging aspect of FROSTI’s design, and one that Richardson says shaped its entire concept, is the requirement that it cannot introduce even more noise into the LIGO interferometer. “To meet this stringent requirement, we had to use the most intensity-stable radiation source available – that is, an internal blackbody emitter with a long thermal time constant,” he tells Physics World. “Our task, from there, was to develop new non-imaging optics capable of reshaping the blackbody thermal radiation into a complex spatial profile, similar to one that could be created with a laser beam.”

Richardson anticipates that FROSTI will be a critical component for future LIGO upgrades – upgrades that will themselves serve as blueprints for even more sensitive next-generation observatories like the proposed Cosmic Explorer in the US and the Einstein Telescope in Europe. “The current prototype has been tested on a 40-kg LIGO mirror, but the technology is scalable and will eventually be adapted to the 440-kg mirrors envisioned for Cosmic Explorer,” he says.

Jan Harms, a physicist at Italy’s Gran Sasso Science Institute who was not involved in this work, describes FROSTI as “an ingenious concept to apply higher-order corrections to the mirror profile.” Though it still needs to pass the final test of being integrated into the actual LIGO detectors, Harms notes that “the results from the prototype are very promising”.

Richardson and colleagues are continuing to develop extensions to their technology, building on the successful demonstration of their first prototype. “In the future, beyond the next upgrade of LIGO (A+), the FROSTI radiation will need to be shaped into an even more complex spatial profile to enable the highest levels of laser power (1.5 MW) ultimately targeted,” explains Richardson. “We believe this can be achieved by nesting two or more FROSTI actuators together in a single composite, with each targeting a different radial zone of the test mass surfaces. This will allow us to generate extremely finely-matched optical wavefront corrections.”

The present study is detailed in Optica.

The post New adaptive optics technology boosts the power of gravitational wave detectors appeared first on Physics World.

Radiation treatment for patients with lung cancer represents a balancing act, particularly if malignant lesions are centrally located near to critical structures. The radiation may destroy the tumour, but vital organs may be seriously damaged as well.

The standard treatment for non-small cell lung cancer (NSCLC) is stereotactic ablative body radiotherapy (SABR), which delivers intense radiation doses in just a few treatment sessions and achieves excellent local control. For ultracentral lung legions, however – defined as having a planning target volume (PTV) that abuts or overlaps the proximal bronchial tree, oesophagus or pulmonary vessels – the high risk of severe radiation toxicity makes SABR highly challenging.

A research team at GenesisCare UK, an independent cancer care provider operating nine treatment centres in the UK, has now demonstrated that stereotactic MR-guided adaptive radiotherapy (SMART)-based SABR may be a safer and more effective option for treating ultracentral metastatic lesions in patients with histologically confirmed NSCLC. They report their findings in Advances in Radiation Oncology.

SMART uses diagnostic-quality MR scans to provide real-time imaging, 3D multiplanar soft-tissue tracking and automated beam control of an advanced linear accelerator. The idea is to use daily online volume adaptation and plan re-optimization to account for any changes in tumour size and position relative to organs-at-risk (OAR). Real-time imaging enables treatment in breath-hold with gated beam delivery (automatically pausing delivery if the target moves outside a defined boundary), eliminating the need for an internal target volume and enabling smaller PTV margins.

The approach offers potential to enhance treatment precision and target coverage while improving sparing of adjacent organs compared with conventional SABR, first author Elena Moreno-Olmedo and colleagues contend.

A safer treatment option

The team conducted a study to assess the incidence of SABR-related toxicities in patients with histologically confirmed NSCLC undergoing SMART-based SABR. The study included 11 patients with 18 ultracentral lesions, the majority of whom had oligometastatic or olioprogressive disease.

Patients received five to eight treatment fractions, to a median dose of 40 Gy (ranging from 30 to 60 Gy). The researchers generated fixed-field SABR plans with dosimetric aims including a PTV V_100% (the volume receiving at least 100% of the prescription dose) of 95% or above, a PTV V_95% of 98% or above and a maximum dose of between110% and 140%. PTV coverage was compromised where necessary to meet OAR constraints, with a minimum PTV V_100% of at least 70%.

SABR was performed using a 6 MV 0.35 T MRIdian linac with gated delivery during repeated breath-holds, under continuous MR guidance. Based on daily MRI scans, online plan adaptation was performed for all of the 78 delivered fractions.

The researchers report that both the PTV volume and PTV overlap with ultracentral OARs were reduced in SMART treatments compared with conventional SABR. The median SMART PTV was 10.1 cc, compared with 30.4 cc for the simulated SABR PTV, while the median PTV overlap with OARs was 0.85 cc for SMART (8.4% of the PTV) and 4.7 cc for conventional SABR.

In terms of treatment-related side effects for SMART, the rates of acute and late grade 1–2 toxicities were 54% and 18%, respectively, with no grade 3–5 toxicities observed. This demonstrates the technique’s increased safety compared with non-adaptive SABR treatments, which have exhibited severe rates of toxicity, including treatment-related deaths, in ultracentral tumours.

Two-thirds of patients were alive at the median follow-up point of 28 months, and 93% were free from local progression at 12 months. The median progression-free survival was 5.8 months and median overall survival was 20 months.

Acknowledging the short follow-up time frame, the researchers note that additional late toxicities may occur. However, they are hopeful that SMART will be considered as a favourable treatment option for patients with ultracentral NSCLC lesions.

“Our analysis demonstrates that hypofractionated SMART with daily online adaptation for ultracentral NSCLC achieved comparable local control to conventional non-adaptive SABR, with a safer toxicity profile,” they write. “These findings support the consideration of SMART as a safer and effective treatment option for this challenging subgroup of thoracic tumours.”

The post A SMART approach to treating lung cancers in challenging locations appeared first on Physics World.

Researchers in the United Arab Emirates have designed a new catheter that can deliver drugs to entire regions of the brain. Developed by Batoul Khlaifat and colleagues at New York University Abu Dhabi, the catheter’s helical structure and multiple outflow ports could make it both safer and more effective for treating a wide range of neurological disorders.

Modern treatments for brain-related conditions including Parkinson’s disease, epilepsy, and tumours often involve implanting microfluidic catheters that deliver controlled doses of drug-infused fluids to highly localized regions of the brain. Today, these implants are made from highly flexible materials that closely mimic the soft tissue of the brain. This makes them far less invasive than previous designs.

However, there is still much room for improvement, as Khlaifat explains. “Catheter design and function have long been limited by the neuroinflammatory response after implantation, as well as the unequal drug distribution across the catheter’s outlets,” she says.

A key challenge with this approach is that each of the brain’s distinct regions has highly irregular shapes, which makes it incredibly difficult to target via single drug doses. Instead, doses must be delivered either through repeated insertions from a single port at the end of a catheter, or through single insertions across multiple co-implanted catheters. Either way, the approach is highly invasive, and runs the risk of further trauma to the brain.

Multiple ports

In their study, Khlaifat’s team explored how many of these problems stem from existing catheter designs. They tend to be simple tubes with single input and output ports at either end. Using fluid dynamics simulations, they started by investigating how drug outflow would change when multiple output ports are positioned along the length of the catheter.

To ensure this outflow is delivered evenly, they carefully adjusted the diameter of each port to account for the change in fluid pressure along the catheter’s length – so that four evenly spaced ports could each deliver roughly one quarter of the total flow. Building on this innovation, the researchers then explored how the shape of the catheter itself could be adjusted to optimize delivery even further.

“We varied the catheter design from a straight catheter to a helix of the same small diameter, allowing for a larger area of drug distribution in the target implantation region with minimal invasiveness,” explains team member Khalil Ramadi. “This helical shape also allows us to resist buckling on insertion, which is a major problem for miniaturized straight catheters.”

Helical catheter

Based on their simulations, the team fabricated a helical catheter the call Strategic Precision Infusion for Regional Administration of Liquid, or SPIRAL. In their first set of experiments, they tested their simulations in controlled lab conditions. They verified their prediction of even outflow rates across the catheter’s outlets.

“Our helical device was also tested in mouse models alongside its straight counterpart to study its neuroinflammatory response,” Khlaifat says. “There were no significant differences between the two designs.”

Having validated the safety of their approach, the researchers are now hopeful that SPIRAL could pave the way for new and improved methods for targeted drug delivery within the brain. With the ability to target entire regions of the brain with smaller, more controlled doses, this future generation of implanted catheters could ultimately prove to be both safer and more effective than existing designs.

“These catheters could be optimized for each patient through our computational framework to ensure only regions that require dosing are exposed to therapy, all through a single insertion point in the skull,” describes team member Mahmoud Elbeh. “This tailored approach could improve therapies for brain disorders such as epilepsy and glioblastomas.”

The research is described in the Journal of Neural Engineering.

The post Spiral catheter optimizes drug delivery to the brain appeared first on Physics World.

From quantum utility today to quantum advantage tomorrow: incumbent technology companies – among them Google, Amazon, IBM and Microsoft – and a wave of ambitious start-ups are on a mission to transform quantum computing from applied research endeavour to mainstream commercial opportunity. The end-game: quantum computers that can be deployed at-scale to perform computations significantly faster than classical machines while addressing scientific, industrial and commercial problems beyond the reach of today’s high-performance computing systems.

Meanwhile, as technology translation gathers pace across the quantum supply chain, government laboratories and academic scientists must maintain their focus on the “hard yards” of precompetitive research. That means prioritizing foundational quantum hardware and software technologies, underpinned by theoretical understanding, experimental systems, device design and fabrication – and pushing out along all these R&D pathways simultaneously.

Bringing order to disorder

Equally important is the requirement to understand and quantify the relative performance of quantum computers from different manufacturers as well as across the myriad platform technologies – among them superconducting circuits, trapped ions, neutral atoms as well as photonic and semiconductor processors. A case study in this regard is a broad-scope UK research collaboration that, for the past four years, has been reviewing, collecting and organizing a holistic taxonomy of metrics and benchmarks to evaluate the performance of quantum computers against their classical counterparts as well as the relative performance of competing quantum platforms.

Funded by the National Quantum Computing Centre (NQCC), which is part of the UK National Quantum Technologies Programme (NQTP), and led by scientists at the National Physical Laboratory (NPL), the UK’s National Metrology Institute, the cross-disciplinary consortium has taken on an endeavour that is as sprawling as it is complex. The challenge lies in the diversity of quantum hardware platforms in the mix; also the emergence of two different approaches to quantum computing – one being a gate-based framework for universal quantum computation, the other an analogue approach tailored to outperforming classical computers on specific tasks.

“Given the ambition of this undertaking, we tapped into a deep pool of specialist domain knowledge and expertise provided by university colleagues at Edinburgh, Durham, Warwick and several other centres-of-excellence in quantum,” explains Ivan Rungger, a principal scientist at NPL, professor in computer science at Royal Holloway, University of London, and lead scientist on the quantum benchmarking project. That core group consulted widely within the research community and with quantum technology companies across the nascent supply chain. “The resulting study,” adds Rungger, “positions transparent and objective benchmarking as a critical enabler for trust, comparability and commercial adoption of quantum technologies, aligning closely with NPL’s mission in quantum metrology and standards.”

Not all metrics are equal – or mature

For context, a number of performance metrics used to benchmark classical computers can also be applied directly to quantum computers, such as the speed of operations, the number of processing units, as well as the probability of errors to occur in the computation. That only goes so far, though, with all manner of dedicated metrics emerging in the past decade to benchmark the performance of quantum computers – ranging from their individual hardware components to entire applications.

Complexity reigns, it seems, and navigating the extensive literature can prove overwhelming, while the levels of maturity for different metrics varies significantly. Objective comparisons aren’t straightforward either – not least because variations of the same metric are commonly deployed; also the data disclosed together with a reported metric value is often not sufficient to reproduce the results.

“Many of the approaches provide similar overall qualitative performance values,” Rungger notes, “but the divergence in the technical implementation makes quantitative comparisons difficult and, by extension, slows progress of the field towards quantum advantage.”

The task then is to rationalize the metrics used to evaluate the performance for a given quantum hardware platform to a minimal yet representative set agreed across manufacturers, algorithm developers and end-users. These benchmarks also need to follow some agreed common approaches to fairly and objectively evaluate quantum computers from different equipment vendors.

With these objectives in mind, Rungger and colleagues conducted a deep-dive review that has yielded a comprehensive collection of metrics and benchmarks to allow holistic comparisons of quantum computers, assessing the quality of hardware components all the way to system-level performance and application-level metrics.

Drill down further and there’s a consistent format for each metric that includes its definition, a description of the methodology, the main assumptions and limitations, and a linked open-source software package implementing the methodology. The software transparently demonstrates the methodology and can also be used in practical, reproducible evaluations of all metrics.

“As research on metrics and benchmarks progresses, our collection of metrics and the associated software for performance evaluation are expected to evolve,” says Rungger. “Ultimately, the repository we have put together will provide a ‘living’ online resource, updated at regular intervals to account for community-driven developments in the field.”

From benchmarking to standards

Innovation being what it is, those developments are well under way. For starters, the importance of objective and relevant performance benchmarks for quantum computers has led several international standards bodies to initiate work on specific areas that are ready for standardization – work that, in turn, will give manufacturers, end-users and investors an informed evaluation of the performance of a range of quantum computing components, subsystems and full-stack platforms.

What’s evident is that the UK’s voice on metrics and benchmarking is already informing the collective conversation around standards development. “The quantum computing community and international standardization bodies are adopting a number of concepts from our approach to benchmarking standards,” notes Deep Lall, a quantum scientist in Rungger’s team at NPL and lead author of the study. “I was invited to present our work to a number of international standardization meetings and scientific workshops, opening up widespread international engagement with our research and discussions with colleagues across the benchmarking community.”

He continues: “We want the UK effort on benchmarking and metrics to shape the broader international effort. The hope is that the collection of metrics we have pulled together, along with the associated open-source software provided to evaluate them, will guide the development of standardized benchmarks for quantum computers and speed up the progress of the field towards practical quantum advantage.”

That’s a view echoed – and amplified – by Cyrus Larijani, NPL’s head of quantum programme. “As we move into the next phase of NPL’s quantum strategy, the importance of evidence-based decision making becomes ever-more critical,” he concludes. “By grounding our strategic choices in robust measurement science and real-world data, we ensure that our innovations not only push the boundaries of quantum technology but also deliver meaningful impact across industry and society.”

Further reading

Deep Lall et al. 2025 A  review and collection of metrics and benchmarks for quantum computers: definitions, methodologies and software https://arxiv.org/abs/2502.06717

End note: NPL retains copyright on this article.

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This episode of the Physics World Weekly podcast explores how quantum computing and artificial intelligence can be combined to help physicists search for rare interactions in data from an upgraded Large Hadron Collider.

My guest is Javier Toledo-Marín, and we spoke at the Perimeter Institute in Waterloo, Canada. As well as having an appointment at Perimeter, Toledo-Marín is also associated with the TRIUMF accelerator centre in Vancouver.

Toledo-Marín and colleagues have recently published a paper called “Conditioned quantum-assisted deep generative surrogate for particle–calorimeter interactions”.

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The microelectronics sector is known for its relentless drive for innovation, continually delivering performance and efficiency gains within ever more compact form factors. Anyone aspiring to build a career in this fast-moving field needs not just a thorough grounding in current tools and techniques, but also an understanding of the next-generation materials and structures that will propel future progress.

That’s the premise behind a Master’s programme in microelectronics technology and materials at the Hong Kong Polytechnic University (PolyU). Delivered by the Department for Applied Physics, globally recognized for its pioneering research in technologies such as two-dimensional materials, nanoelectronics and artificial intelligence, the aim is to provide students with both the fundamental knowledge and practical skills they need to kickstart their professional future – whether they choose to pursue further research or to find a job in industry.

“The programme provides students with all the key skills they need to work in microelectronics, such as circuit design, materials processing and failure analysis,” says programme leader Professor Zhao Jiong, who research focuses on 2D ferroelectrics. “But they also have direct access to more than 20 faculty members who are actively investigating novel materials and structures that go beyond silicon-based technologies.”

The course in also unusual in providing a combined focus on electronics engineering and materials science, providing students with a thorough understanding of the underlying semiconductors and device structures as well as their use in mass-produced integrated circuits. That fundamental knowledge is reinforced through regular experimental work, providing the students with hands-on experience of fabricating and testing electronic devices. “Our cleanroom laboratory is equipped with many different instruments for microfabrication, including thin-film deposition, etching and photolithography, as well as advanced characterization tools for understanding their operating mechanisms and evaluating their performance,” adds Zhao.

In a module focusing on thin-film materials, for example, students gain valuable experience from practical sessions that enable them to operate the equipment for different growth techniques, such as sputtering, molecular beam epitaxy, and both physical and chemical vapour deposition. In another module on materials analysis and characterization, the students are tasked with analysing the layered structure of a standard computer chip by making cross-sections that can be studied with a scanning electron microscope.

That practical experience extends to circuit design, with students learning how to use state-of-the-art software tools for configuring, simulating and analysing complex electronic layouts. “Through this experimental work students gain the technical skills they need to design and fabricate integrated circuits, and to optimize their performance and reliability through techniques like failure analysis,” says Professor Dai Jiyan, PolyU Associate Dean of Students, who also teaches the module on thin-film materials. “This hands-on experience helps to prepare them for working in a manufacturing facility or for continuing their studies at the PhD level.”

Also integrated into the teaching programme is the use of artificial intelligence to assist key tasks, such as defect analysis, materials selection and image processing. Indeed, PolyU has established a joint laboratory with Huawei to investigate possible applications of AI tools in electronic design, providing the students with early exposure to emerging computational methods that are likely to shape the future of the microelectronics industry. “One of our key characteristics is that we embed AI into our teaching and laboratory work,” says Dai. “Two of the modules are directly related to AI, while the joint lab with Huawei helps students to experiment with using AI in circuit design.”

Now in its third year, the Master’s programme was designed in collaboration with Hong Kong’s Applied Science and Technology Research Institute (ASTRI), established in 2000 to enhance the competitiveness of the region through the use of advanced technologies. Researchers at PolyU already pursue joint projects with ASTRI in areas like chip design, microfabrication and failure analysis. As part of the programme, these collaborators are often invited to give guest lectures or to guide the laboratory work. “Sometimes they even provide some specialized instruments for the students to use in their experiments,” says Zhao. “We really benefit from this collaboration.”

Once primed with the knowledge and experience from the taught modules, the students have the opportunity to work alongside one of the faculty members on a short research project. They can choose whether to focus on a topic that is relevant to present-day manufacturing, such as materials processing or advanced packaging technologies, or to explore the potential of emerging materials and devices across applications ranging from solar cells and microfluidics to next-generation memories and neuromorphic computing.

“It’s very interesting for the students to get involved in these projects,” says Zhao. “They learn more about the research process, which can make them more confident to take their studies to the next level. All of our faculty members are engaged in important work, and we can guide the students towards a future research field if that’s what they are interested in.”

There are also plenty of progression opportunities for those who are more interested in pursuing a career in industry. As well as providing support and advice through its joint lab in AI, Huawei arranges visits to its manufacturing facilities and offers some internships to interested students. PolyU also organizes visits to Hong Kong’s Science Park, home to multinational companies such as Infineon as well as a large number of start-up companies in the microelectronics sector. Some of these might support a student’s research project, or offer an internship in areas such as circuit design or microfabrication.

The international outlook offered by PolyU has made the Master’s programme particularly appealing to students from mainland China, but Zhao and Dai believe that the forward-looking ethos of the course should make it an appealing option for graduates across Asia and beyond. “Through the programme, the students gain knowledge about all aspects of the microelectronics industry, and how it is likely to evolve in the future,” says Dai. “The knowledge and technical skills gained by the students offer them a competitive edge for building their future career, whether they want to find a job in industry or to continue their research studies.”

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Pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer, is an aggressive tumour with a poor prognosis. Surgery remains the only potential cure, but is feasible in just 10–15% of cases. A team headed up at Sichuan University in China has now developed a selective laser ablation technique designed to target PDAC while leaving healthy pancreatic tissue intact.

Thermal ablation techniques, such as radiofrequency, microwave or laser ablation, could provide a treatment option for patients with locally advanced PDAC, but existing methods risk damaging surrounding blood vessels and healthy pancreatic tissues. The new approach, described in Optica, uses the molecular fingerprint of pancreatic tumours to enable selective ablation.

The technique exploits the fact that PDAC tissue contains a large amount of collagen compared with healthy pancreatic tissue. Amide-I collagen fibres exhibit a strong absorption peak at 6.1 µm, thus the researchers surmised that tuning the treatment laser to this resonant wavelength could enable efficient tumour ablation with minimal collateral thermal damage. As such, they designed a femtosecond pulsed laser that can deliver 6.1 µm pulses with a power of more than 1 W.

“We developed a mid-infrared femtosecond laser system for the selective tissue ablation experiment,” says team leader Houkun Liang. “The system is tunable in the wavelength range of 5 to 11 µm, aligning with various molecular fingerprint absorption peaks such as amide proteins, cholesteryl ester, hydroxyapatite and so on.”

Liang and colleagues first examined the ablation efficiency of three different laser wavelengths on two types of pancreatic cancer cells. Compared with non-resonant wavelengths of 1 and 3 µm, the collagen-resonant 6.1 µm laser was far more effective in killing pancreatic cancer cells, reducing cell viability to ranges of 0.27–0.32 and 0.37–0.38, at 0 and 24 h, respectively.

The team observed similar results in experiments on ectopic PDAC tumours cultured on the backs of mice. Irradiation at 6.1 µm led to five to 10 times deeper tumour ablation than seen for the non-resonant wavelengths (despite using a laser power of 5 W for 1 µm ablation and just 500 mW for 6.1 and 3 µm), indicating that 6.1 µm is the optimal wavelength for PDAC ablation surgery.

To validate the feasibility and safety of 6.1 µm laser irradiation, the team used the technique to treat PDAC tumours on live mice. Nine days after ablation, the tumour growth rate in treated mice was significantly suppressed, with an average tumour volume of 35.3 mm³. In contrast, tumour volume in a control group of untreated mice reached an average of 292.7 mm³, roughly eight times the size of the ablated tumours. No adverse symptoms were observed following the treatment.

Clinical potential

The researchers also used 6.1 µm laser irradiation to ablate pancreatic tissue samples (including normal tissue and PDAC) from 13 patients undergoing surgical resection. They used a laser power of 1 W and four scanning speeds (0.5, 1, 2 and 3 mm/s) with 10 ablation passes, examining 20 to 40 samples for each parameter.

At the slower scanning speeds, excessive energy accumulation resulted in comparable ablation depths. At speeds of 2 or 3 mm/s, however, the average ablation depths in PDAC samples were 2.30 and 2.57 times greater than in normal pancreatic tissue, respectively, demonstrating the sought-after selective ablation. At 3 mm/s, for example, the ablation depth in tumour was 1659.09±405.97 µm, compared with 702.5±298.32 µm in normal pancreas.

The findings show that by carefully controlling the laser power, scanning speed and number of passes, near-complete ablation of PDACs can be achieved, with minimal damage to surrounding healthy tissues.

To further investigate the clinical potential of this technique, the researchers developed an anti-resonant hollow-core fibre (AR-HCF) that can deliver high-power 6.1 µm laser pulses deep inside the human body. The fibre has a core diameter of approximately 113 µm and low bending losses at radii under 10 cm. The researchers used the AR-HCF to perform 6.1 µm laser ablation of PDAC and normal pancreas samples. The ablation depth in PDAC was greater than in normal pancreas, confirming the selective ablation properties.

“We are working together with a company to make a medical-grade fibre system to deliver the mid-infrared femtosecond laser. It consists of AR-HCF to transmit mid-infrared femtosecond pulses, a puncture needle and a fibre lens to focus the light and prevent liquid tissue getting into the fibre,” explains Liang. “We are also making efforts to integrate an imaging unit into the fibre delivery system, which will enable real-time monitoring and precise surgical guidance.”

Next, the researchers aim to further optimize the laser parameters and delivery systems to improve ablation efficiency and stability. They also plan to explore the applicability of selective laser ablation to other tumour types with distinct molecular signatures, and to conduct larger-scale animal studies to verify long-term safety and therapeutic outcomes.

“Before this technology can be used for clinical applications, highly comprehensive biological safety assessments are necessary,” Liang emphasizes. “Designing well-structured clinical trials to assess efficacy and risks, as well as navigating regulatory and ethical approvals, will be critical steps toward translation. There is a long way to go.”

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Low-energy electrons escape from some materials via distinct “doorway” states, according to a study done by physicists at Austria’s Vienna Institute of Technology. The team studied graphene-based materials and found that the nature of the doorway states depended on the number of graphene layers in the sample.

Low-energy electron (LEE) emission from solids is used across a range of materials analysis and processing applications including scanning electron microscopy and electron-beam induced deposition. However, the precise physics of the emission process is not well understood.

Electrons are ejected from a material when a beam of electrons is fired at its surface. Some of these incident electrons will impart energy to electrons residing in the material, causing some resident electrons to be emitted from the surface. In the simplest model, the minimum energy needed for this LEE emission is the electron binding energy of the material.

Frog in a box

In this new study, however, researchers have shown that exceeding the binding energy is not enough for LEE emission from graphene-based materials. Not only does the electron need this minimum energy, it must also be in a specific doorway state or it is unlikely to escape. The team compare this phenomenon to the predicament of a frog in a cardboard box with a window. Not only must the frog hop a certain height to escape the box, it must also begin its hop from a position that will result in it travelling through the hole (see figure).

For most materials, the energy spectrum of LEE electrons is featureless. However, it was known that graphite’s spectrum has an “X state” at about 3.3 eV, where emission is enhanced. This state could be related to doorway states.

To search for doorway states, the Vienna team studied LEE emission from graphite as well as from single-layer and bi-layer graphene. Graphene is a sheet of carbon just one atom thick. Sheets can stick together via the relatively weak Van der Waals force to create multilayer graphene – and ultimately graphite, which comprises a large number of layers.

Because electrons are mostly confined within the graphene layers, the electronic states of single-layer, bi-layer and multi-layer graphene are broadly similar. As a result, it was expected that these materials would have similar LEE emission spectra . However, the Vienna team found a surprising difference.

Emission and reflection

The team made their discovery by firing a beam of relatively low energy electrons (173 eV) incident at 60° to the surface of single-layer and bi-layer graphene as well as graphite. The scattered electrons are then detected at the same angle of reflection. Meanwhile, a second detector is pointed normal to the surface to capture any emitted electrons. In quantum mechanics electrons are indistinguishable, so the modifiers scattered and emitted are illustrative, rather than precise.

The team looked for coincident signals in both detectors and plotted their results as a function of energy in 2D “heat maps”. These plots revealed that bi-layer graphene and graphite each had doorway states – but at different energies. However, single-layer graphene did not appear to have any doorway states. By combining experiments with calculations, the team showed that doorway states emerge above a certain number of layers. As a result the researchers showed that graphite’s X state can be attributed in part to a doorway state that appears at about five layers of graphene.

“For the first time, we’ve shown that the shape of the electron spectrum depends not only on the material itself, but crucially on whether and where such resonant doorway states exist,” explains Anna Niggas at the Vienna Institute of Technology.

As well as providing important insights in how the electronic properties of graphene morph into the properties of graphite, the team says that their research could also shed light on the properties of other layered materials.

The research is described in Physical Review Letters.

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