Desalination is used to produce fresh drinking water from seawater, but it also generates a highly concentrated waste stream known as brine. Disposing of this brine is a major challenge and is often achieved through deep-well injection, in which the waste is pumped underground, an approach that can be expensive. Oil and gas production creates similarly saline wastewater, which is often managed in the same way.

In this work, the researchers developed a modelling platform to evaluate different strategies for managing these waste streams and to determine whether it is more cost effective to dispose of brine or to treat it further and recover additional water using solar-powered technologies. They applied the framework to two case studies: the Kay Bailey Hutchison Desalination Plant in Texas, a large inland desalination facility, and produced water from the Permian Basin, one of the most productive oil-producing regions in the United States.

The study compared a range of desalination technologies, including reverse osmosis, which uses membranes to separate water from dissolved salts, and thermal desalination methods that use heat to evaporate and recover water. Solar technologies included photovoltaic panels that generate electricity and solar thermal systems that provide heat. The researchers found that for desalination brine, the most cost-effective solar-powered option was photovoltaic combined with reverse osmosis, while solar-thermal desalination remained relatively expensive because of the cost of solar collectors and heat storage. For highly saline oilfield wastewater, zero-liquid-discharge systems, which recover almost all of the water and leave behind solid salts, could be economically attractive because they reduce or eliminate costly brine disposal.

More broadly, the findings suggest that renewable energy could help make desalination and wastewater treatment more sustainable, particularly in water-stressed regions. By identifying cost-effective ways to increase water recovery and reduce brine disposal, the work could support wider water reuse and potentially enable valuable minerals to be recovered from waste streams rather than discarded.

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Energy efficiency and renewable energy utilization in desalination systems by Veera Gnaneswar Gude and Vasilis Fthenakis (2020)

The post When is solar desalination worth it? appeared first on Physics World.

When a material does not have inversion symmetry, particles within it will move in different directions when they have different spin states. This is because the asymmetry of the material creates an effective electric field that couples the particles’ spin and momentum. The behaviour is called the Rashba effect, and it allows researchers to manipulate electron spins without requiring a magnetic field.

Surface plasmons are waves of oscillating electrons that travel along a metal surface when it interacts with light. In this work, the researchers investigated surface plasmons to see if they could create something like the Rashba effect but in a completely symmetrical material. To do this, they shone polarized light onto a periodic gold nanostructure (a plasmonic crystal) and measured how the resulting plasmon modes behaved, comparing what happened for left- and right-circularly polarized light.

They observed that differently polarized light caused the plasmon modes to split according to the light’s spin (polarization), mimicking Rashba spin splitting. Instead of being caused by the lack of symmetry in the material, the tightly focused light interacts with the anisotropic gold grating. The gold grating has lines running in one direction, meaning that light polarized along the grating lines behaves differently from light polarized across them. When light is tightly focused, its polarization is no longer identical everywhere, so the light experiences different combinations of birefringence and dichroism depending on its propagation direction. This creates a geometric phase gradient that gives left- and right-circularly polarized light opposite momentum shifts, causing the observed spin splitting. The researchers describe this mechanism as a geometric linear birefringence-linear dichroism effect.

The findings show that Rashba-like spin splitting does not necessarily require structural asymmetry and suggest that researchers may be able to achieve spin-controlled optical behaviour using simpler symmetric metasurfaces rather than increasingly complex asymmetric nanostructures.

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Quantum transport in Rashba spin–orbit materials: a review by Dario Bercioux and Procolo Lucignano (2015)

The post A new route to spin-controlled photonics appeared first on Physics World.

When waves travel through complex environments (such as acoustics), repeated scattering is usually a problem because it scrambles wavefronts and distorts the information they carry. As a result, most approaches seek to suppress or compensate for scattering. In this work, however, the researchers take the opposite approach and show that scattering itself can be harnessed to manipulate waves.

The challenge is to design a disordered medium so that multiple scattering produces a desired outcome. This is difficult because the scattering matrix, which describes how waves are transformed by the medium, depends sensitively on the positions of many individual scatterers. Finding a configuration that performs a target operation can therefore be like searching for a destination in a vast landscape. The researchers used a mathematical tool known as the generalized Wigner-Smith operator, which reveals how small changes in scatterer positions modify the scattering matrix. In effect, it acts as a local map of the design landscape, guiding the system toward target unitary transformations while maintaining near-perfect transmission.

The team demonstrated the concept using an acoustic waveguide containing eighty metallic cylinders. By carefully arranging the scatterers, they controlled how different waveguide modes were converted into one another, enabling operations known as braiding. Similar to weaving strands in a braid, braiding exchanges modes in a prescribed sequence. A particularly striking example is non-Abelian braiding, where changing the order of those exchanges produces different outcomes. Such order-dependent operations are of great interest in topological quantum computing and can also manipulate information encoded in classical waves. The researchers demonstrated this behavior experimentally using a compact multiple-scattering medium only a few wavelengths thick, avoiding the long structures required in previous wave-based braiding schemes.

The significance of the work extends well beyond braiding. The same design principle can realize a broad range of unitary transformations, suggesting that complex media can be programmed to process information carried by waves rather than simply transmit it. Although practical implementations will still face challenges such as loss, bandwidth, and fabrication constraints, the work offers a new way of thinking about disorder. Instead of treating scattering as an obstacle to overcome, researchers may be able to harness it as a resource to build compact, reconfigurable devices for communications, imaging, signal processing, and wave-based computation.

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Non-local and non-Hermitian acoustic metasurfaces by Xu Wang, Ruizhi Dong, Yong Li and Yun Jing (2023)

The post Turning disorder into a resource for wave control appeared first on Physics World.

Protonic ceramic electrochemical cells (PCECs) function as fuel cells, converting hydrogen into electricity, or as electrolysers, where electricity is used to split water into hydrogen and oxygen. This makes them useful in hydrogen energy systems because surplus electricity from integrated energy sources like nuclear, hydropower and geothermal can be converted into hydrogen, stored, and later converted back into electricity. Inside PCECs, two electrodes are separated by a ceramic electrolyte that controls the movement of hydrogen ions, which are protons.

Unfortunately, manufacturing the proton-conducting ceramic electrolyte layer is cumbersome. Long processing times involve multiple steps, including intensive ball-milling and high-temperature sintering, making protonic ceramics expensive to produce. In this work, the researchers investigated how PCECs could be manufactured more affordably, more rapidly and with better performance.

Instead of using larger precursor particles and grinding them for many hours, they started with nano-sized precursor powders. This enabled them to remove the ball-milling step entirely and reduce production time from 85 hours to 33 hours. In addition, it produced a finer electrolyte powder whose smaller particles packed together and sintered more easily, allowing the ceramic to become dense at temperatures around 100 °C lower than those required by the conventional method. The resulting electrolytes had lower electrical resistance, improving cell performance.

Compared with cells made using the conventional synthesis method, the new cells delivered up to 32% higher peak power density in fuel cell mode and 40% higher electrolysis current density at 600 °C, while maintaining stable operation for more than 500 hours. The process also reduced estimated electrolyte-powder fabrication costs by 25-29% and was successfully demonstrated in larger-area cells. This work could help accelerate the deployment of protonic ceramic electrochemical technologies for hydrogen production and energy conversion.

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Focus on Protonic Ceramics: A Promising Class of Materials for Energy Conversion and Storage – Guest Editors: Sandrine Ricote and Aayan Banerjee

The post Faster fabrication, better performance for PCECs appeared first on Physics World.

A quark is a fundamental building block of matter. There are six types known as flavours of quark: up, down, strange, charm, bottom, and top. Quarks combine to form particles known as hadrons. Most ordinary matter is made from up and down quarks, for example, a proton consists of two up quarks and one down quark, while a neutron consists of one up quark and two down quarks. Electrons belong to a different family of particles called leptons and are not made of quarks.

Particle physicists continuously test the Standard Model of particle physics to search for signs of new phenomena. One possibility is that quarks possess anomalous magnetic or electric dipole moments, which would indicate physics beyond the Standard Model. However, quarks are never observed in isolation because they are confined inside particles such as protons and neutrons.

In this work, the authors study electron-positron collisions, which can produce quark-antiquark pairs. These quarks subsequently fragment into hadrons. By analysing the directions in which the hadrons emerge, information about the spins of the original quarks can be reconstructed. The authors show that anomalous magnetic or electric dipole interactions would modify the quantum-entangled spin state of the quark-antiquark pair in a characteristic way, producing either a spin-triplet state (for magnetic dipole interactions) or a spin-singlet state (for electric dipole interactions). These changes lead to measurable signatures in the angular distributions of the resulting hadrons. Rather than searching for an excess of events, the method probes changes in the spin-correlation structure of the quark-antiquark system.

The work introduces a new entanglement-based approach for probing the electromagnetic properties of light quarks. By connecting quantum spin correlations in hadron production with possible quark dipole interactions, it provides a complementary method for searching for physics beyond the Standard Model using collider data.

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The sea of quarks and antiquarks in the nucleon by D F Geesaman and P E Reimer (2019)

The post Using quantum entanglement to probe hidden properties of quarks appeared first on Physics World.

In magnets, the magnetic moments of electrons, known as spins, usually align in an ordered pattern. However, in a spin liquid, the spins never settle into a fixed arrangement. Instead, they continue to fluctuate collectively even at very low temperatures. In a chiral spin liquid, these fluctuations have a preferred handedness, similar to the difference between left and right hands or clockwise and anticlockwise rotation.

This research focuses on the pyrochlore lattice, a three-dimensional structure made of interconnected tetrahedra. Because of this geometry, the spins cannot all simultaneously satisfy their preferred interactions, making the system “frustrated”. This frustration can prevent conventional magnetic order and create the conditions needed for spin-liquid behaviour.

The researchers classified all possible chiral spin-liquid states allowed by the symmetries of the pyrochlore lattice. They then built theoretical models and performed simulations to predict how these states would appear in experiments. One unusual feature of spin liquids is that the collective motion of the spins can behave as if it creates emergent gauge fields, which resemble electromagnetic fields. The researchers found that some chiral spin liquids are dominated by these emergent gauge fields, while others are influenced more strongly by the spin-like excitations themselves.

The researchers showed that different chiral spin liquids have distinct signatures, providing a way to distinguish them experimentally. Their results offer a roadmap for identifying and classifying elusive three-dimensional chiral spin liquids in real materials.

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Dynamical quantum phase transitions: a review by Markus Heyl (2018)

The post Finding the signatures of chiral spin liquids appeared first on Physics World.

An important low-carbon technology is the hydrogen fuel cell, which can be used in vehicles, backup power systems and other applications. Fuel cells convert hydrogen into electricity, producing only water as a by-product. A key process inside the cell is the oxygen reduction reaction, in which oxygen from the air is reduced at the cathode. This reaction is relatively slow and is one of the main factors limiting fuel-cell performance.

To speed up this step, platinum catalysts are used. While highly effective, platinum is expensive and gradually degrades during operation. Much research therefore focuses on reducing the amount of platinum required while improving performance and catalyst lifetime. One approach is to use platinum alloys, where a cheaper metal is mixed with platinum to improve efficiency. However, these alloying metals can gradually leach out, causing the catalyst to lose activity over time.

In this work, the researchers aimed to address the trade off between catalytic activity and long-term durability by investigating two alloy catalysts, platinum-copper (PtCu) and platinum-iron (PtFe). These were attached to a two-dimensional material, similar to graphene, called a MXene, which can improve performance while helping to hold the nanoparticles in place and enhance their stability. PtCu/MXene showed the highest catalytic activity, as copper modifies the platinum surface to improve oxygen reduction and accelerate the reaction. PtFe/MXene was less active but more durable, with strong Fe-O-MXene interactions helping to stabilise the catalyst during long-term operation.

By using in-situ X-ray spectroscopy, the researchers were able to observe the catalysts during operation and identify the structural and electronic changes responsible for their performance. This revealed how alloy composition and catalyst supports influence activity and durability, the study provides a roadmap for developing improved catalysts for future fuel cells.

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Catalyst designing strategies for electrochemical CO2 reduction: a perspective by Shreya Sarkar and Sebastian C Peter (2022)

The post Exploring efficiency and durability in fuel cell catalysts appeared first on Physics World.

In some materials, when many electrons interact very strongly, they behave collectively like a quantum fluid with unusual properties. One example is a Fractional Quantum Hall state, which occurs in a two-dimensional system under a strong magnetic field. In this state, the electrons form a topologically ordered quantum fluid that supports unusual collective excitations.

A Fractional Chern Insulator aims to recreate the same type of physics without requiring such a strong magnetic field. Instead, the crystal lattice and electronic band structure are engineered to mimic the effects of the magnetic field.

The electron fluid has an internal geometric structure that describes how electrons are correlated with one another. When this internal geometry oscillates collectively, it produces a special excitation known as a graviton mode.

In this work, the authors developed new mathematical tools and performed large-scale computer simulations to search for graviton modes in lattice-based systems. They then smoothly transformed a known Fractional Quantum Hall state into a Fractional Chern Insulator and showed that the graviton mode persists throughout the transition.

Graviton modes were already known to exist in Fractional Quantum Hall systems and have recently been observed experimentally. However, it was unclear whether they could survive in a Fractional Chern Insulator because the crystal lattice breaks some of the symmetries that are thought to protect these excitations.

The authors found that graviton modes do survive on the lattice. They showed that the Fractional Chern Insulator graviton is not a completely new excitation, but is continuously connected to the graviton found in Fractional Quantum Hall systems. They also found that the graviton decays much more slowly than many researchers expected, meaning it remains a well-defined excitation. Finally, the work suggests that graviton modes could provide a valuable experimental signature for identifying exotic topological phases such as Fractional Chern Insulators.

“It is remarkable how geometric excitations can govern the behavior of inherently discrete lattices, demonstrating unexpected universal features of topological quantum matter.“ – Zi Yang Meng, The University of Hong Kong, and Marcello Dalmonte, Università di Bologna.

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Fractional charge and fractional statistics in the quantum Hall effects by D E Feldman and Bertrand I Halperin (2020)

The post Graviton modes survive on the lattice appeared first on Physics World.

The Higgs boson is associated with the Higgs field, which gives many fundamental particles their mass. Although it was predicted in the 1960s, it was not discovered until 2012. Since then, researchers have been studying whether the Higgs behaves exactly as predicted by the Standard Model of particle physics or whether it shows signs of physics beyond the Standard Model. This involves measuring how often Higgs bosons are produced, how they are produced, what they decay into, and how they interact with other particles.

In this work, the researchers combined measurements from proton-proton collisions recorded between 2016 and 2018 by the CMS experiment. These collisions can produce Higgs bosons, but such events are rare, so a huge dataset was needed. The study used 138 fb-1 of data, representing an enormous sample of proton-proton collisions on which to perform measurements of the Higgs. The researchers examined many Higgs decay channels, including decays into photons, bosons, and leptons. They also searched for invisible Higgs decays, in which the Higgs would produce undetectable particles such as dark matter candidates, and studied rare off-shell Higgs production, where the Higgs is produced as a virtual state with a mass different from its physical mass.

The researchers found that, with the current experimental precision, the Higgs boson behaves as predicted by the Standard Model. They measured an overall Higgs signal strength of 1.01 ± 0.05, where a value of 1 represents perfect agreement with the Standard Model. The result is therefore fully consistent with theoretical expectations. Many theories that extend the Standard Model predict that undiscovered particles or forces could subtly alter how the Higgs boson is produced or how it decays. Because the CMS measurements agree with Standard Model predictions, there is currently little evidence for such effects, significantly constraining many proposed theories of new physics.

This study provides the most comprehensive test of the Higgs boson to date using data from the CMS experiment. By narrowing the range of possible deviations from the Standard Model, it helps guide future searches for new physics at the Large Hadron Collider and other particle physics experiments.

“It is amazing to see how far we have come in just over a decade since discovery. We are now able to measure the Higgs boson production rate at the LHC with a 5% precision, confirming our theories regarding the origin of mass in the Universe.” –  Dr Jonathon Langford from Imperial College London, a lead analyst for this paper.

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Prospects for Higgs physics at energies up to 100 TeV by Julien Baglio, Abdelhak Djouadi and Jérémie Quevillon (2016)

The post Most comprehensive study yet of the Higgs boson at CMS appeared first on Physics World.

The majority of hydrogen comes from natural gas, produced in a process called Steam Methane Reforming. Even though this process is relatively cheap, it has the downside of producing significant amounts of the greenhouse gas carbon dioxide. Alternatively, hydrogen can be made by splitting water, a process that requires electricity for electrolysis and therefore another energy source, as well as large supplies of water. There is an ongoing desire for low-carbon electricity, clean hydrogen for industry (e.g. steel manufacturing, fertiliser manufacturing and heavy transport), and greater freshwater supplies, particularly in water-stressed regions.

In this work, the researchers investigate how a small nuclear reactor can be used to produce all three: hydrogen, clean electricity, and freshwater through seawater desalination. A small modular reactor produces 200 MW of thermal power. The heat creates steam that drives turbines and generates electricity. Part of the steam is diverted to a process called High-Temperature Steam Electrolysis, which splits water into hydrogen and oxygen. Because the steam is already hot, less electricity is needed than in conventional electrolysis. After the hydrogen production process, the steam is cooler but still contains useful heat, which is then used in a desalination plant to convert seawater into freshwater.

The integrated system was able to simultaneously produce around 90 MW of electricity, 0.6 kg/s of hydrogen (~52 tonnes/day), and 612 m³/day of freshwater from a single reactor module. By reusing waste heat from hydrogen production to drive desalination, the overall energy utilisation increased from 48% for electricity generation alone to 53% in the full tri-generation system.

The researchers evaluated two operating modes: a self-sufficient option, where desalinated water is used internally for hydrogen production, and a market-led option, where freshwater is sold externally. The market-led scenario achieved lower hydrogen production costs ($2.93-3.19/kg compared with $3.49-3.88/kg for the self-sufficient scenario) due to the additional revenue from water sales.

Overall, the study demonstrates that a small modular nuclear reactor could be used to produce clean electricity, hydrogen, and freshwater, offering an efficient and potentially attractive solution for water scarce regions seeking low carbon energy and industrial hydrogen supplies.

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Energy storage in long-term system models: a review of considerations, best practices, and research needs by John Bistline et al. (2020)

The post Producing hydrogen, electricity and freshwater with one reactor appeared first on Physics World.

Information can be transported using electrons, for example in conventional computing, or using light in photonic devices. A third option that researchers are exploring is the use of excitons, which are bound electron-hole pairs created when a material is excited by light. Excitons can be thought of as an intermediate state between light and electrical charge carriers. However, excitons typically recombine quickly and emit light or undergo non-radiative recombination, limiting how far they can travel. One way to extend their lifetime is to separate the electron and hole across two different material layers, creating an interlayer exciton that can transport energy over longer distances.

Previous studies have used stacked transition-metal dichalcogenides such as MoSe₂/WSe₂ or WS₂/WSe₂, which require extremely precise rotational alignment between layers to form prominent interlayer exciton emission. In this work, however, the researchers use a hybrid perovskite-WS₂ heterostructure that does not require such careful twist-angle engineering. They demonstrate a device in which an applied voltage switches between two different exciton states—interlayer excitons and intralayer excitons, allowing them to control whether excitons can move through the material or remain localised.

Valley polarisation describes how strongly carriers favour one of two equivalent energy minima, known as valleys. The researchers used voltage to switch the device between low and high valley-polarisation states between these two different exciton states, allowing them to electrically control a form of information carried by excitons. This capability is an important step toward future valleytronic devices, which aim to use valley states for information processing.

More broadly, the research demonstrates a practical way to electrically control both energy transport and information states in a 2D material system, bringing excitonic and valleytronic circuits a step closer to reality.

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Valley manipulation in monolayer transition metal dichalcogenides and their hybrid systems: status and challenges by Siwen Zhao et al. (2021)

The post Voltage switches exciton transport in 2D hybrid material appeared first on Physics World.

In Texas, US, electricity demand is expected to grow because of rapid population growth, increased adoption of electric vehicles, expansion of AI data centres, and other societal and industrial developments. Most of Texas’ electricity system is managed by the Electric Reliability Council of Texas (ERCOT), which operates a grid that is largely independent from the rest of the United States. Combined with the state’s rapidly changing demand patterns, this makes Texas an important test case for exploring future energy scenarios.

In this work, the researchers developed a framework to model how different sources of electricity demand growth could affect the Texas grid through to 2050. They separately examined the impacts of population growth, electrified heating, electric vehicles, large industrial loads such as data centres, and electrification of oil and gas operations.

The study found that electric vehicles have the greatest impact on peak electricity demand because charging tends to occur at similar times of day, creating sharp increases in demand. In contrast, large industrial loads, including data centres, cryptocurrency mining, hydrogen production and manufacturing facilities, have the greatest impact on overall electricity consumption because they often operate continuously. Electrification of heating had a smaller net effect because heat pumps increase winter electricity demand while simultaneously reducing summer electricity demand through more efficient cooling.

The findings suggest that different types of demand growth require different grid solutions. Battery storage is particularly effective for managing the sharp demand peaks associated with electric vehicle charging, whereas growth from data centres and other large industrial loads is most economically met through additional natural gas, wind and solar generation. The study also showed that uncertainty in future demand could lead to dramatically different grid expansion requirements by 2050.

A key impact of this work is demonstrating that the source of future electricity demand can be just as important as its size, since different demand drivers require different investments in generation, storage and grid infrastructure. The framework developed in this study could help planners, investors and policymakers make more informed decisions about future electricity systems.

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How different power plant types contribute to electric grid reliability, resilience, and vulnerability: a comparative analytical framework by K Ramirez-Meyers et al. (2021)

The post Forecasting future demand on the Texas grid appeared first on Physics World.

N = 4 super Yang-Mills is a highly symmetric quantum field theory that physicists use as a model system for exploring ideas in quantum gravity and string theory. The researchers study interactions between small and large excitations of the theory. The small, or light, excitations are super gravitons, which can be thought of as particle-like ripples of spacetime. The large, or heavy, excitations are giant gravitons: extended brane-like objects that arise when a graviton carries a very large amount of angular momentum. The goal is to understand how the light excitations behave in the presence of these heavy objects.

To study this, the authors analyse a four-point correlation function containing two light (L) and two heavy (H) operators, known as an LLHH correlator. These correlators are notoriously difficult to calculate directly because doing so requires detailed knowledge of how the supergravity fields couple to the giant graviton and its fluctuations. The key idea of the paper is to treat the pair of heavy operators as a zero-dimensional defect. This reformulates the four-point function as a two-point function of light probes in the presence of the defect, allowing bootstrap techniques to be applied.

Using this defect framework together with bootstrap techniques, the authors compute all strong-coupling four-point functions involving two maximal giant gravitons and two supergravitons of arbitrary dimension. They also uncover a partially broken higher-dimensional hidden conformal symmetry that organizes these correlators. Finally, they determine the leading interaction-induced energy shifts for a complete class of double-particle states associated with the defect and argue that the defect picture provides the natural description of heavy-light correlators more generally. This establishes a powerful new framework for studying giant gravitons, non-planar effects, and aspects of quantum gravity and strongly coupled quantum field theories.

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Bootstrap and amplitudes: a hike in the landscape of quantum field theory by Henriette Elvang (2021)

The post A new way to study giant gravitons appeared first on Physics World.

Using solar and wind power for clean energy generation relies on the weather, which can be unpredictable. In addition to seasonal changes and daily variability, energy planners must also account for rare and extreme weather events. Traditional planning methods often fail to capture these events accurately, resulting in systems that are either overly expensive or insufficiently reliable.

In this work, the researchers aimed to develop a more effective way of planning energy systems that can cope with real climate variability. They built an artificial intelligence model trained on 30 years of wind and solar data from Pingtan in China. The model generated thousands of realistic weather scenarios, including both typical conditions and extreme events.

The researchers then used these scenarios to determine the most cost-effective and reliable combination of energy technologies. Their Integrated Energy System included solar panels, wind turbines, batteries, hydrogen production and storage, and a connection to the national electricity grid. The optimal system configuration was identified by testing its performance across all of the AI-generated scenarios.

The optimisation showed that the most effective renewable energy system combines several technologies working together. Wind and solar provide the main source of electricity, batteries manage short-term fluctuations in supply and demand, hydrogen storage provides backup during extended periods of low renewable generation, and the grid acts as an additional safety net.

The key finding is that batteries and hydrogen have complementary roles: batteries are best for balancing daily variations, while hydrogen is better suited to storing energy over weeks or months. Together, they help create a renewable energy system that is both reliable and cost-effective.

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Energy policy and public opinion: patterns, trends and future directions by Parrish Bergquist, David M Konisky and John Kotcher (2020)

The post Using AI to plan for climate variability in renewable energy systems appeared first on Physics World.

When light is absorbed by a semiconductor, it first creates an electron-hole pair before free charges can be generated. The electron and hole can remain bound together in a quasiparticle known as an exciton. This intermediate stage is important because excitons determine how light is absorbed and emitted, and how efficiently a material can convert light into electrical current.

Monolayer tungsten diselenide (WSe₂) is a material that researchers are investigating for use in photodetectors, optical computing and quantum technologies. It is an atom-thick semiconductor that interacts very strongly with light. The excitons formed in WSe₂ are unusually stable, allowing quantum effects to be observed particularly strongly. WSe₂ therefore provides a model system for learning how to control light-generated excitons, knowledge that could eventually lead to more efficient solar cells, photodetectors and low-energy photonic technologies.

A key question in this area of research is what causes the WSe₂ exciton energy to shift to a higher energy (blue shift), a lower energy (red shift) or split into two levels. Two leading explanations are the Optical Stark Effect, in which the laser’s electric field directly modifies the exciton energy, and exciton-exciton interactions, in which excitons alter one another’s energies through many-body interactions.

In this work, the researchers used helicity-resolved transient absorption spectroscopy to show that, while the laser pulse is present, the Optical Stark Effect dominates, causing a blue shift, splitting or a red shift depending on the laser detuning. After the pulse ends, exciton-exciton interactions become dominant, producing a blue shift. By varying the laser detuning and tracking the exciton response on femtosecond timescales, the researchers were able to separate the coherent Optical Stark Effect from the later incoherent exciton-exciton interaction. The work provides a clearer picture of how light and excitons interact on ultrafast timescales, which is important for the design of next-generation optoelectronic devices.

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Intercalation in two-dimensional transition metal chalcogenides: interlayer engineering and applications by Dibyendu Ghosh, Pooja Devi and Praveen Kumar (2022)

The post Resolving an exciton debate appeared first on Physics World.

In an antiferromagnet, neighbouring spins prefer to align in opposite directions to minimise their energy. In a geometrically frustrated magnet, this is not always possible; for example, three spins on a triangle cannot all simultaneously be antiparallel to one another. The magnet PdCrO₂ contains chromium (Cr) atoms on a triangular lattice, so that the magnetic moments on the Cr atoms cannot point antiparallel to each other. This compound also contains sheets of palladium (Pd) atoms that have very high electrical conductivity. PdCrO₂ is therefore a system in which the interaction between magnetism and electronic structure can be studied in a precise way.

Previous studies have shown that the Cr-Cr exchange interaction is highly sensitive to inter-atomic spacing. In consequence, the magnetic ordering wavevector shifts rapidly as uniaxial stress is applied to PdCrO₂, distorting the triangular lattice. In this work, the researchers have taken a step further by applying enough stress to qualitatively change the magnetic structure. They use a combination of X-ray diffraction and measurement of the stress-strain relationship to probe the effects on the elastic properties, and elastic neutron scattering to see how the magnetism changes. As the magnetic structure changes, the Young’s modulus changes by around 100 GPa, showing that magnetic interactions have a large effect on the crystal’s mechanical stiffness.

As stress is initially applied to PdCrO₂, the magnetic wavevector changes rapidly, reflecting the sensitivity of the Cr-Cr exchange interaction to strain. The main finding of this work is that, under a uniaxial stress of about 0.6 GPa, the magnetism undergoes a first-order transition into a state where the magnetic wavevector is rigid, that is, no longer responds to continued change in lattice strain. The rigidity of this stress-induced magnetic structure is reflected in the elastic properties: the Young’s modulus almost doubles, and the Poisson ratio falls from about 0.7, an exceptionally high value, to about 0.3, which is more typical. This rigidity may be a consequence of nesting: the wavevector of this stress-induced magnetic phase nests the Fermi surface of the Pd sheets. PdCrO₂ may therefore provide a system in which the thermodynamics of nesting can be studied with quantitative precision. More broadly, the work demonstrates that uniaxial stress is a powerful tool for tuning frustrated magnetism and accessing new magnetic states.

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Unusual ordered phases of highly frustrated magnets: a review by Oleg A Starykh (2015)

The post Tuning frustrated magnetism with stress appeared first on Physics World.

A critical point is where a material changes phase. For example, water turns to ice below 0°C (273 K) at standard pressure. A quantum critical point occurs at absolute zero (0 K) and, instead of being driven by temperature, is caused by changing another property such as a magnetic field, pressure, or interaction strength. One example is the transition between an ordered magnetic state and a disordered quantum state.

Entanglement entropy is a measure of how much quantum information two parts of a system share. If a system is split into two regions, a low entanglement entropy means that knowing about one half tells you little about the other half, while a high entanglement entropy means that the two halves are strongly connected through quantum mechanics. Entanglement entropy provides important information about quantum phases of matter, quantum critical points, and universal properties of quantum systems. However, calculating entanglement entropy accurately at quantum critical points in two-dimensional quantum systems is very difficult. These systems are commonly described as (2+1)-dimensional because their critical theories involve two spatial dimensions and one time dimension.

In this work, the researchers developed a novel Quantum Monte Carlo algorithm to calculate entanglement entropy more accurately. Quantum Monte Carlo methods use random sampling to study quantum systems that are too complex to solve exactly. The researchers started with a standard quantum magnet model, the transverse-field Ising model, and added extra interactions that allowed them to study different types of phase transitions, including ordinary Ising critical points and a tricritical point that, in (2+1) dimensions, is described by a Gaussian free theory.

The researchers compared the second Rényi entanglement entropies of two specially chosen regions with the same boundary length. This directly cancelled the dominant area-law contribution, allowing the much smaller universal corner term to become the leading signal. They then used the same approach to obtain a precise value for the Ising critical point. The results showed that the Ising and tricritical/Gaussian critical points have different universal entanglement fingerprints, demonstrating that entanglement can distinguish between different types of quantum critical behaviour. More broadly, the work provides a powerful new method for studying entanglement in strongly interacting quantum systems and for testing theoretical predictions in two-dimensional quantum materials.

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Dynamical quantum phase transitions: a review by Markus Heyl (2018)

The post Probing quantum critical points appeared first on Physics World.

Quantum dot LEDs (QLEDs) are of interest because they emit bright light with highly pure colours, making them attractive for display and lighting applications. They also have the potential to be manufactured at lower cost using solution-processing techniques. However, producing high-performance QLEDs remains challenging because the quantum dots must be uniformly distributed within a densely packed film. Poor film uniformity can lead to lower efficiency and faster device degradation.

In this study, machine learning was used to identify solvent conditions that produce the most uniform quantum dot films. Several solvents were characterised using five key solvent parameters that influence how quantum dots arrange themselves as the solvent evaporates. Film uniformity was assessed using atomic force microscopy, which provides detailed information about surface morphology and roughness.

Three machine learning models were trained to predict film uniformity from the solvent properties. Support Vector Regression was found to provide the most accurate predictions and was subsequently used to identify an optimal mixed-solvent formulation. Grazing-Incidence Small-Angle X-ray Scattering confirmed that the resulting films exhibited more homogeneous quantum dot packing.

The optimised solvent formulation produced QLEDs with higher efficiency and longer operational lifetimes than devices fabricated using single solvents. Overall, the study demonstrates that film homogeneity is a critical factor in QLED performance and highlights the potential of machine learning as a powerful tool for optimising solution-processed optoelectronic devices.

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Materials, photophysics and device engineering of perovskite light-emitting diodes by Ziming Chen et al. (2021)

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Wireless power transfer systems are used to transfer electricity without a physical cable, for example in wireless electric vehicle charging, medical implants and consumer electronics such as smartwatches. In real systems, poor alignment and variable distances can reduce efficiency, causing some of the transmitted energy to be reflected back towards its source rather than being absorbed by the receiver.

Wireless power transfer research tends to focus on engineering solutions such as improved coil designs, impedance matching and frequency tuning. However, in this work, the researchers investigate a more fundamental question: how can the physics of time-domain wave interference be used to control energy flow within resonant systems?

A phenomenon known as Coherent Perfect Absorption occurs when a system completely absorbs incoming energy with negligible reflection. However, this requires specific conditions and a system that is perfectly matched, operating at a point of equilibrium known as the steady state. Here, the researchers report a new effect called Transient Coherent Perfect Absorption. Rather than relying on a steady state, TCPA operates during the brief transition period immediately after a system is switched on.

During this transient period, a steady wave produced by the source coexists with a temporary, decaying wave created by energy stored within the system. These waves interfere with one another and both contribute to the reflected signal. When they are exactly out of phase, the reflected signals cancel out. As a result, a system that would normally reflect a significant amount of incoming energy can briefly behave as though it were perfectly matched, absorbing almost all of the incoming energy.

While this is fundamentally a physics study of wave behaviour and interference, it introduces a new way to suppress energy reflections in resonant systems. In the future, the approach could help improve the efficiency of wireless power transfer and other energy-delivery technologies by reducing losses under imperfect operating conditions.

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The rise of electric vehicles—2020 status and future expectations by Matteo Muratori et al. (2021)

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A system will generally move towards equilibrium when a change is made to it in a process called relaxation. To predict the state of the system after some period of time, we only need to know its current state and the external conditions. However, some polymers have memory behaviours where the evolution of the system is not only dependent on the current state, but also on previous states. This is known as the Kovacs effect.

In this work, the researchers investigated the Kovacs effect in a system consisting of suspensions of rod-like nanoparticles. By applying an electric field to these nanoparticles they align, therefore the particles change the liquid’s optical anisotropy, which can be measured as birefringence, which is how the liquid changes light polarization. More birefringence means the particles are more aligned. Importantly, there are faster- and slower-relaxing nanoparticles because of their polydispersity and different sizes, meaning they align at different rates. By changing the strength of the electric field, the faster and slower nanoparticles become out of sync with each other. The future behaviour will then depend on the system’s previous history that is overall hidden by the global birefringence measurement; this is the Kovacs effect.

The researchers modelled the orientational dynamics using the Smoluchowski equation, which describes rotational diffusion of particles. They found that relaxation is not determined by a single timescale or relaxation mode. When some of the modes are fast and some are slow, memory effects will occur. The Kovacs effect is important because it shows that a simple strategy of applying a strong electric field before switching to the target field does not necessarily speed up relaxation. Due to memory effects arising from particles relaxing at different rates, the system overshoots the target state, reducing the expected gain in speed.

To overcome this, the researchers designed improved two- and three-step protocols that suppress the slowest relaxation modes rather than simply matching the average birefringence. These protocols reduce the memory effect, produce a smoother approach to equilibrium, and achieve faster relaxation, although the benefit of additional switching steps becomes progressively smaller. This research improves our understanding of memory effects in complex systems and provides a practical strategy for controlling nanoparticle dynamics more quickly and efficiently.

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Scientific developments of liquid crystal-based optical memory: a review by Jai Prakash, Achu Chandran and Ashok M Biradar (2016)

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