Optimum glass of the categories Brazilian tulip (left) Imperial pint (center) and American pint (right). Credit: arXiv (2024). DOI: 10.48550/arxiv.2410.12043
Claudio Pellegrini, a professor of thermal and fluid sciences at the Federal University of São João del-Rei in Brazil, has calculated the optimal shape for a beer glass to keep the beer cold for as long as possible. He has written a paper describing his analysis of beer glass shapes and posted it on the arXiv preprint server.
Prior research and a lot of anecdotal evidence suggests that beer consumers prefer their beverage cold—generally as cold as possible. Many such beer drinkers also prefer to consume their beverages from a clear glass—doing so allows for enjoying the look of the beer as it is being consumed and makes for an easy and tasty consumption.
Unfortunately, the two desires represent a conundrum—drinking from a glass allows the beer to lose its chill very quickly. Because of that, beer glass makers have developed a variety of designs meant to retain as much chill as possible, for as long as possible.
In this new effort, Pellegrini put such designs to the test by calculating the optimal glass design, based on physics principles, for keeping a beer cold in a drinking glass.
In his work, Pellegrini did not include external factors, such as the warmth of a hand holding the glass, or the types of glass used. Instead, he went for the basics, testing nothing but shape to determine heat transfer rates.
To determine such a shape, he began by starting with the simplest model—a glass with a smooth curve, fixed around a vertical axis—one with a standard height, radius and base to top ratio. He also assumed an insulated base, ensuring that heat loss would occur only out the top and sides.
He also assumed a fixed starting beer temperature for all testing purposes, and that the glass would have negligible thermal resistance. Such a scenario ensured that changes in heat transfer would be a direct result of changes in shape.
In doing his calculations, Pellegrini found, unsurprisingly, that the best shape is also the one that is the most popular—a glass with a small base that grows wider as it approaches the top, such as the pilsner.
He also acknowledges that the true best result is one where the glass is so small that the beer is consumed in one or two quick gulps, but he insists drinking beer in such an ugly fashion misses the point of drinking beer altogether.
More information: Cláudio C. Pellegrini, Optimizing Beer Glass Shapes to Minimize Heat Transfer — New Results, arXiv (2024). DOI: 10.48550/arxiv.2410.12043
Illustration of the dynamical symmetry in a circularly polarized laser field. The Hamiltonian is invariant under an arbitrary time translation P̂t=t→t+δt combined with a rotation operation P̂φ=φ→φ+δφ with δφ = ωδt. Consequently, an infinite-order continuous dynamical symmetry P̂∞=P̂φP̂t emerges, providing support for the introduction of conservation laws on the subcycle scale. Credit: Ultrafast Science (2024). DOI: 10.34133/ultrafastscience.0071
The conservation law is a fundamental tool that significantly aids our quest to understand the world, playing a crucial role across various scientific disciplines. Particularly in strong-field physics, these laws enhance our comprehension of atomic and molecular structures as well as the ultrafast dynamics of electrons.
For example, when atoms interact with linearly polarized light, the Hamiltonian of the system displays a second-order dynamical symmetry, which stays invariant under the symmetry operation that involves a half-period time translation together with a spatial inversion. This characteristic symmetry is known to result in exclusive odd-order harmonics during high-harmonic generation of rare-gas atoms.
An intriguing phenomenon occurs when atoms interact with circularly polarized light. There, the Hamiltonian exhibits an infinite-order continuous dynamical symmetry, which stays invariant under a symmetry operation that comprises an arbitrary time translation combined with a corresponding rotational operation. The implication of this symmetry for conservation laws presents a compelling topic for exploration.
A team of researchers from the State Key Laboratory of Precision Spectroscopy at East China Normal University has delineated a conservation law between angular momentum and energy at the subcycle level. This was achieved through the analysis of the correlated spectrum of angular momentum and energy (SAME) of photoelectrons, both at the tunnel exit and in the asymptotic region, in the context of strong-field ionization using circularly and elliptically polarized light pulses.
The researchers have confirmed that this conservation law stays applicable down to the subcycle level. They have also introduced a protocol utilizing interference-induced electron vortices to directly visualize the conservation law at the subcycle level. Their findings have been published in the journal Ultrafast Science.
In the case of circular polarization, while the individual distributions of angular momentum and energy are broad, their correlated distribution forms a distinct straight line. This pattern underscores a rigorously obeyed conservation law between angular momentum and energy, represented by the equation.
The team has further substantiated that this conservation law is consistently applicable throughout an entire optical cycle. For elliptical polarization, the conservation law is naturally extended and can be articulated with an effective angular frequency within the optical cycle.
This work introduces a novel conservation law between angular momentum and energy that operates down to the subcycle level during strong-field ionization. The discovery of this subcycle conservation law is attributed to the infinite-order continuous dynamical symmetry inherent in the interaction between atoms and light pulses with circular or elliptical polarization.
This study lays a theoretical groundwork that is instrumental for a profound comprehension of light-matter interactions on the subcycle scale.
More information: Yongzhe Ma et al, Subcycle Conservation Law in Strong-Field Ionization, Ultrafast Science (2024). DOI: 10.34133/ultrafastscience.0071
Overview of the DeepSCF model. Credit: npj Computational Materials (2024). DOI: 10.1038/s41524-024-01433-0
The close relationship between AI and highly complicated scientific computing can be seen in the fact that both the 2024 Nobel Prizes in Physics and Chemistry were awarded to scientists for devising AI for their respective fields of study. KAIST researchers have now succeeded in dramatically shortening the calculation time of highly sophisticated quantum mechanical computer simulations by predicting atomic-level chemical bonding information distributed in 3D space using a novel approach to teach AI.
Professor Yong-Hoon Kim’s team from the School of Electrical Engineering has developed a 3D computer vision artificial neural network-based calculation methodology that bypasses the complex algorithms required for atomic-level quantum mechanical calculations performed using supercomputers to derive the properties of materials.
The density functional theory (DFT) calculations in quantum mechanics using supercomputers have become an essential and standard tool in a wide range of research and development fields, including advanced materials and drug design, as they allow for fast and accurate prediction of quantum properties.
However, in current density functional theory (DFT) calculations, a complex self-consistent field (SCF) process of generating three-dimensional electron densities and solving quantum mechanical equations must be repeated tens to hundreds of times, which limits its application to hundreds or thousands of atoms.
Professor Yong-Hoon Kim’s research team asked whether it would be possible to avoid the self-consistent field process using the artificial intelligence technique that has recently been rapidly developing. As a result, they developed the DeepSCF model to accelerate calculations by learning chemical bond information distributed in three-dimensional space through a neural network algorithm in the field of computer vision.
The research is published in the journal npj Computational Materials.
The research team focused on the fact that according to density functional theory, electron density contains all the quantum mechanical information of electrons, and in addition, the residual electron density, which is the difference between the total electron density and the sum of the electron densities of the constituent atoms, contains chemical bond information, and selected it as a target for machine learning.
Afterwards, the team adopted a data set of organic molecules containing various chemical bond characteristics, and the atomic structures of the molecules included in it were subjected to arbitrary rotations and deformations to further improve the accuracy and generalization performance of the model. Finally, the research team demonstrated the validity and efficiency of the DeepSCF methodology for complex and large systems.
Professor Yong-Hoon Kim, who led this research, said, “We have found a way to correspond quantum mechanical chemical bonding information distributed in three-dimensional space to an artificial neural network. Since quantum mechanical electronic structure calculations are the basis for all-scale material property simulations, we have established the overall basic principles for accelerating material calculations through artificial intelligence.”
More information: Ryong-Gyu Lee et al, Convolutional network learning of self-consistent electron density via grid-projected atomic fingerprints, npj Computational Materials (2024). DOI: 10.1038/s41524-024-01433-0
Schematic diagram of interlayer spin-coupled states between ferromagnetic (FM: Py) and paramagnetic (PM: PANI) layers. Credit: Advanced Electronic Materials (2024). DOI: 10.1002/aelm.202400322
Electrons spin even without an electric charge and this motion in condensed matter constitutes spin current, which is attracting a great deal of attention for next-generation technology such as memory devices. An Osaka Metropolitan University-led research group has been able to gain further insight into this important topic in the field of spintronics.
To investigate the characteristics of spin currents, OMU Graduate School of Science Professor Katsuichi Kanemoto’s group designed a multilayer device consisting of a ferromagnetic layer and an organic semiconductor material.
The findings were published in Advanced Electronic Materials.
By adopting a doped conducting polymer with a long spin relaxation time, the team succeeded in observing the effects of spin transport and spin current generation from the non-magnetic, organic semiconductor side.
The long spin relaxation times not only make for more efficiency in spintronics, but also enable direct observation of phenomena due to spin current generation in the organic layer side. Moreover, the researchers were able to find that, contrary to a theory that has been generally accepted, the width of the ferromagnetic resonance measurements for the layer of the spin current supplier slightly narrowed in the device system using the organic semiconductor with a long spin relaxation time.
“The use of the organic semiconductor makes it possible to pursue physical properties from the non-magnetic layer side, for which there was no information until now,” explained Professor Kanemoto. “Our work can be expected to contribute to a deeper understanding of the properties of spin currents.”
More information: Kohei Takaishi et al, Spin Current Generation at the Hybrid Ferromagnetic Metal/Organic Semiconductor Interface as Revealed by Multiple Magnetic Resonance Techniques, Advanced Electronic Materials (2024). DOI: 10.1002/aelm.202400322
Crystal thermal transport in altermagnets. The left part, which includes the balls, arrows, and spin density isosurfaces, represents a typical altermagnet. When a temperature gradient field is applied, charge and thermal currents are induced in a perpendicular direction, illustrating crystal thermal transport, as shown in the right part. Credit: Zhou et al/Physical Review Letters. DOI: 10.1103/PhysRevLett.132.056701.
In a new study, scientists have investigated the newly discovered class of altermagnetic materials for their thermal properties, offering insights into the distinctive nature of altermagnets for spin-caloritronic applications.
Magnetism is an old and well-researched topic, lending itself to many applications, like motors and transformers. However, new magnetic materials and phenomena are being studied and discovered, one of which is altermagnets.
Altermagnets exhibit a unique blend of magnetic characteristics, setting them apart from conventional magnetic materials like ferromagnets and antiferromagnets. These materials exhibit properties observed in both ferromagnets and antiferromagnets, making their study enticing.
The current research, published in Physical Review Letters, explores the thermal properties of altermagnets and was led by Prof. Wanxiang Feng and Prof. Yugui Yao from the Beijing Institute of Technology.
Speaking of their motivation behind exploring altermagnets, Prof. Feng told Phys.org, “Magnetism is an ancient and fascinating topic in solid-state physics. While exploring non-collinear magnets over the past decades, we encountered a new type of collinear magnet, the altermagnet.”
Prof. Yao added, “With a dual nature resembling both ferromagnets and antiferromagnets, altermagnets intrigued us with the potential for novel physical effects. Our motivation stemmed from the desire to understand and unlock the unique properties of these magnetic materials.”
The emergence of magnetism
Magnetic properties emerge from the behavior of atoms, particularly the arrangement and movement of electrons within a material.
“In magnetic materials, due to the exchange interaction between atoms, the spin magnetic moments arrange parallel or antiparallel, forming the most common ferromagnets and antiferromagnets, respectively, which have been studied for over a century,” explained Prof. Feng.
Altermagnets defy conventional norms by embodying a dual nature—resembling antiferromagnets with zero net magnetization and ferromagnets with non-relativistic spin splitting.
In altermagnets, collinear antiparallel magnetic order combines with non-relativistic spin splitting, resulting in zero net magnetization akin to antiferromagnets and ferromagnetic spin dynamics simultaneously.
This unique behavior emerges from the intricate interplay of atoms within the crystal structure. For instance, ruthenium dioxide, the subject of this research, showcases spin degeneracy induced by nonmagnetic oxygen atoms, breaking spatial and time symmetries. This leads to the unique magnetic properties of the material.
Additionally, altermagnets exhibit a unique spin polarization. The term “spin polarization” means that a preponderance of electron spins tends to align in a particular direction.
The spin polarization is noteworthy in altermagnets because it occurs in the physical arrangement of atoms (real space) and in the momentum space, where the distribution of electron spins in the material is considered.
Nernst and Hall effects
The researchers focused on studying the emergence of crystal Nernst and crystal thermal Hall effects in rubidium dioxide (RuO2), chosen as a showcase representative of altermagnetism.
The crystal Nernst effect (CNE) observed in altermagnets is a result of their distinctive magnetic nature. In simple terms, as the material experiences a temperature difference across its dimensions, it leads to the emergence of a voltage perpendicular to both the temperature gradient and the magnetic field. This phenomenon reveals that the material’s magnetic properties influence its response to temperature changes, providing insights into the intricate connection between thermal and magnetic behaviors in altermagnets.
In altermagnets, this effect is significantly influenced by the direction of the Néel vector, which represents the direction in which neighboring magnetic moments align. This adds an extra layer of complexity to the thermal response.
Similarly, the crystal thermal Hall effect (CTHE) sheds light on how heat moves in altermagnets. Like the traditional thermal Hall effect, it occurs perpendicular to the temperature gradient and magnetic field. In altermagnets, the CTHE shows significant variation depending on the Néel vector direction. This anisotropy is a central factor in understanding the thermal transport behavior unique to altermagnetic materials.
Thermal properties of RuO2
The research methodology employed a dual strategy, combining symmetry analysis and cutting-edge first-principles calculations, to unravel the thermal transport properties of RuO2. Symmetry analysis played a crucial role in unraveling the fundamental reasons behind the emergence of altermagnetism.
Through two symmetry operations involving spatial inversion, time reversal, and lattice translation, the study showcased the intricate interplay of atoms within the crystal structure, demonstrating how nonmagnetic oxygen atoms induced non-relativistic spin splitting in energy bands.
This process resulted in the breaking of crystalline time-reversal symmetry, giving rise to distinct crystal thermal transport properties.
“Through detailed analysis, we identified three physical mechanisms contributing to crystal thermal transport: Weyl pseudo-nodal lines, altermagnetic pseudo-nodal planes, and altermagnetic ladder transitions,” said Prof. Yao.
In simple terms, the Weyl pseudo-nodal lines are pathways that guide heat within the material, altermagnetic pseudo-nodal planes can be pictures as designated zones influencing heat flow, and altermagnetic ladder transitions can be thought of as the material’s way of climbing a heat ladder.
These findings are exciting as they play a significant role in how heat travels within altermagnets.
The researchers discovered an extended Wiedemann-Franz law in RuO2, linking the material’s unusual thermal and electrical transport characteristics. Contrary to conventional expectations, this extended law operates over a broader temperature range, extending beyond 150 Kelvin.
Spin caloritronics
The researchers believe that altermagnets could have a pivotal role in spin caloritronics, a field of research that explores the interplay between spin and heat flow, which are not achievable with ferromagnets or antiferromagnets. This field has potential applications in developing new technologies for information processing and storage.
“Altermagnetic materials with collinear antiparallel magnetic order exhibit faster spin dynamics and lower sensitivity to stray magnetic fields compared to ferromagnetic materials. This makes them promising for achieving higher storage density and faster spin caloritronic devices,” explained Prof. Feng.
The researchers also intend to investigate higher-order crystal thermal transport and magneto-optical effects in the future.
Speaking of this, Prof. Yao said, “We are curious about the differences in higher-order crystal thermal transport and high-order magneto-optical effects in altermagnets compared to antiferromagnets or ferromagnets. We are in the early stages of this technology, and there’s a long journey ahead before it becomes practically achievable.”
A non-chiral, superconducting material and a chiral, non-superconducting material were combined in different element ratios to create a new compound with the properties of both. Credit: Tokyo Metropolitan University
Researchers from Tokyo Metropolitan University have created a new superconductor with a chiral crystalline structure by mixing two materials, one with superconductivity but no chirality, another with chirality but no superconductivity.
The new platinum-iridium-zirconium compound transitions to a bulk superconductor below 2.2 K and was observed to have chiral crystalline structure using X-ray diffraction. Their new solid solution approach promises to accelerate the discovery and understanding of new exotic superconducting materials.
Scientists studying superconductivity are on a mission to understand how the exotic nature of superconducting materials arises from their structure, and how we might control the structure to get desirable properties.
Of the many aspects of structure, an interesting recent development is the issue of chirality. Many structures have a “handedness,” that is, they do not look the same in a mirror. An effect of chirality in superconductors is to trigger something called asymmetric spin-orbit coupling (ASOC), an effect that can make superconductors more robust to high magnetic field exposure.
To understand chirality in more depth, however, scientists need more superconductors with a chiral structure to study. The usual route is to search out chiral compounds, check if they are superconducting or not, rinse and repeat: this is very inefficient.
That is why a team from Tokyo Metropolitan University led by Associate Professor Yoshikazu Mizuguchi has introduced an entirely new approach. Instead of combing through lists of compounds, they mixed two compounds with known physical properties, a platinum-zirconium compound with superconductivity but no chirality, and an iridium-zirconium compound with a chiral structure, but no reports of superconductivity. The work is published in the Journal of the American Chemical Society.
By combining elements in a ratio that matches a certain proportion of each compound, they were able to effectively “mix and match” physical properties, coming up with a new material that had both a chiral crystal structure and superconductivity.
X-ray diffraction patterns at different temperatures (top), and the extracted fraction of chiral compound (bottom) show that the proportion of chiral compound increases at lower temperature. Credit: Tokyo Metropolitan University
As the proportion of iridium is increased, the proportion of P6122, the chiral component, increases. Credit: Tokyo Metropolitan University
Superconductivity can be confirmed below an iridium proportion of around x = 0.85 in (Pt1-xIrx)3Zr5. Credit: Tokyo Metropolitan University
X-ray diffraction patterns at different temperatures (top), and the extracted fraction of chiral compound (bottom) show that the proportion of chiral compound increases at lower temperature. Credit: Tokyo Metropolitan University
As the proportion of iridium is increased, the proportion of P6122, the chiral component, increases. Credit: Tokyo Metropolitan University
A representation of the machine learning approach used to classify sulfur-38 nuclei (38S) from all other nuclei created in a complex nuclear reaction (left) and the resulting ability to gain knowledge of the unique sulfur-38 quantum “fingerprint” (right). Credit: Argonne National Laboratory
Fixed numbers of protons and neutrons—the building blocks of nuclei—can rearrange themselves within a single nucleus. The products of this reshuffling include electromagnetic (gamma ray) transitions. These transitions connect excited energy levels called quantum levels, and the pattern in these connections provide a unique “fingerprint” for each isotope.
Determining these fingerprints provides a sensitive test of scientists’ ability to describe one of the fundamental forces, the strong (nuclear) force that holds protons and neutrons together.
In the laboratory, scientists can initiate the movement of protons and neutrons through an injection of excess energy using a nuclear reaction.
In a paper, published in Physical Review C, researchers successfully used this approach to study the fingerprint of sulfur-38. They also used machine learning and other cutting-edge tools to analyze the data.
The results provide new empirical information on the “fingerprint” of quantum energy levels in the sulfur-38 nucleus. Comparisons with theoretical models may lead to important new insights. For example, one of the calculations highlighted the key role played by a particular nucleon orbital in the model’s ability to reproduce the fingerprints of sulfur-38 as well as neighboring nuclei.
The study is also important for its first successful implementation of a specific machine learning-based approach to classifying data. Scientists are adopting this approach to other challenges in experimental design.
Researchers used a measurement that included a machine learning (ML) assisted analysis of the collected data to better determine the unique quantum energy levels—a “fingerprint” formed through the rearrangement of the protons and neutrons—in the neutron-rich nucleus sulfur-38.
The results doubled the amount of empirical information on this particular fingerprint. They used a nuclear reaction involving the fusion of two nuclei, one from a heavy-ion beam and the second from a target, to produce the isotope and introduce the energy needed to excite it into higher quantum levels.
The reaction and measurement leveraged a heavy-ion beam produced by the ATLAS Facility (a Department of Energy user facility), a target produced by the Center for Accelerator and Target Science (CATS), the detection of electromagnetic decays (gamma-rays) using the Gamma-Ray Energy Tracking Array (GRETINA), and the detection of the nuclei produced using the Fragment Mass Analyzer (FMA).
Due to complexities in the experimental parameters—which hinged between the production yields of the sulfur-38 nuclei in the reaction and the optimal settings for detection—the research adapted and implemented ML techniques throughout the data reduction.
These techniques achieved significant improvements over other techniques. The ML-framework itself consisted of a fully connected neural network that was trained under supervision to classify sulfur-38 nuclei against all other isotopes produced by the nuclear reaction.
by Daegu Gyeongbuk Institute of Science and Technology (DGIST)
A MEMS-based 2 × 2 unitary gate and its measured responses. a,b, Schematic (a) and optical microscopy image (b) of the MEMS-based 2 × 2 unitary gate. The gate consists of one phase shifter and one tunable coupler. The equation in a shows the mathematical description of the ideal 2 × 2 unitary transformation gate without any optical losses. Credit: Nature Photonics (2023). DOI: 10.1038/s41566-023-01327-5
Programmable photonic integrated circuits (PPICs) process light waves for computation, sensing, and signaling in ways that can be programmed to suit diverse requirements. Researchers at Daegu Gyeongbuk Institute of Science and Technology (DGIST), in South Korea, with collaborators at Korea Advanced Institute of Science and Technology (KAIST), have achieved a major advance in incorporating microelectromechanical systems into PPICs.
Their research has been published in the journal Nature Photonics.
“Programmable photonic processors promise to outperform conventional supercomputers, offering faster, more efficient and massively parallel computing capabilities,” says Sangyoon Han of the DGIST team. He emphasizes that, in addition to the increased speeds achieved by using light instead of electric current, the significant reduction in power consumption and size of PPICs could lead to major advances in artificial intelligence, neural networks, quantum computing, and communications.
The microelectromechanical systems (MEMS) at the heart of the new advance are tiny components that can interconvert optical, electronic, and mechanical changes to perform the variety of communication and mechanical functions needed by an integrated circuit.
The researchers believe they are the first to integrate silicon-based photonic MEMS technologies onto PPIC chips that operate with extremely low power requirements.
“Our innovation has dramatically reduced the power consumption to femtowatt levels, which is over a million times an improvement compared to the previous state of the art,” says Han. The technology can also be built onto chips up to five times smaller than existing options.
One key to the dramatic reduction in power requirements was to move away from the dependence on temperature changes required by the dominant “thermo-optic” systems currently in use. The required tiny mechanical movements are powered by electrostatic forces—the attractions and repulsions between fluctuating electric charges.
The components integrated onto the team’s chips can manipulate a feature of light waves called “phase” and control the coupling between different parallel waveguides, which guide and constrain the light. These are the two most fundamental requirements for building PPICs. These features interact with micromechanical “actuators” (essentially switches) to complete the programmable integrated circuit.
The key to the advance has been to apply innovative concepts to the fabrication of the required silicon-based parts. Crucially, the manufacturing process can be used with conventional silicon wafer technology. This makes it compatible with the large-scale production of photonic chips essential to commercial applications.
The team now plans to refine their technology to build and commercialize a photonic computer that will outperform conventional electronic computers in a wide variety of applications. Han says that examples of specific uses include the crucial inference tasks in artificial intelligence, advanced image processing, and high-bandwidth data transmission.
“We expect to continue to push the boundaries of computational technology, contributing further to the field of photonics and its practical applications in modern technology,” Han concludes.
More information: Dong Uk Kim et al, Programmable photonic arrays based on microelectromechanical elements with femtowatt-level standby power consumption, Nature Photonics (2023). DOI: 10.1038/s41566-023-01327-5
The solvent sieve method for high-performance PeLEDs. Credit: NIMTE
Using a simple solvent sieve method, researchers from the Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences (CAS) have taken the lead in developing highly efficient and stable perovskite light-emitting diodes (PeLEDs) with record performance.
Perovskites are one of the most promising optoelectronic materials due to their excellent optoelectronic performance and low preparation cost. Compared with traditional organic light-emitting diodes (OLEDs), PeLEDs have a narrower light-emitting spectrum and superior color purity, thus showing great application potential in display and lighting.
However, despite significant progress in efficiency, low operational stability has long limited the practical application of PeLEDs. In particular, a limited understanding of the cause of perovskite instability has greatly hindered the development and commercialization of PeLEDs.
Based on an in-depth analysis of the fine nanostructures of perovskites, the researchers identified the perovskites’ defective low n-phase as the key source of perovskite instability. The low quality of the low n-phase, which contained only one or two layers of lead ions, originated from the rapid and uncontrollable crystallization process.
Inspired by the process of separating sand of different sizes with a sieve, the researchers proposed a solvent sieve method to screen out these undesirable low n-phases.
According to the researchers, the solvent sieve is a combination of polar and nonpolar solvents. The polar solvent acts as a mesh that interacts with perovskites, while the nonpolar solvent acts as a framework that does not affect perovskites. The researchers adjusted the ratio of polar solvents to effectively remove the defective low n-phases.
The PeLEDs based on the sieved perovskites achieved an operating lifetime of more than 5.7 years under normal conditions (luminance of 100 cd/m2), more than 30 times longer than the untreated device. This record lifetime is also the highest value reported to date for green PeLEDs, reaching the fundamental threshold for commercial application.
In addition, these PeLEDs achieved a record high external quantum efficiency (EQE) of 29.5%, significantly improving the efficiency of converting electricity to light.
When exposed to ambient air (50±10% humidity), the device can maintain 75% of its film photoluminescence quantum yield and 80% of its EQE for more than 100 days, thus showing excellent stability.
This solvent sieve method not only significantly improves the luminescence performance and stability of PeLEDs, but also paves the way for the future development and application of perovskites with unique nanostructures and excellent luminescence performance.
More information: Shuo Ding et al, Phase dimensions resolving of efficient and stable perovskite light-emitting diodes at high brightness, Nature Photonics (2024). DOI: 10.1038/s41566-023-01372-0
The FCC would form a new circular tunnel under France and Switzerland.
Europe’s CERN laboratory revealed more details Monday about its plans for a huge new particle accelerator that would dwarf the Large Hadron Collider (LHC), ramping up efforts to uncover the underlying secrets of the universe.
If approved, the Future Circular Collider (FCC) would start smashing its first particles together around the middle of this century—and start its highest-energy collisions around 2070.
Running under France and Switzerland, it would be more than triple the length of CERN’s LHC, currently the largest and most powerful particle accelerator.
The idea behind both is to send particles spinning around a ring to smash into each at nearly the speed of light, so that the collisions reveal their true nature.
Among other discoveries, the LHC made history in 2012 when it allowed scientists to observe the Higgs boson for the first time.
But the LHC, which cost $5.6 billion and began operating in 2010, is expected to have run its course by around 2040.
The faster and more powerful FCC would allow scientists to continue pushing the envelope. They hope it could confirm the existence of more particles—the building blocks of matter—which so far have only been theorized.
Another unfinished job for science is working out exactly what 95 percent of the universe is made of. About 68 percent of the universe is believed to be dark energy while 27 percent is dark matter—both remain a complete mystery.
Another unknown is why there is so little antimatter in the universe, compared to matter.
CERN hopes that a massive upgrade of humanity’s ability to smash particles could shed light on these enigmas and more.
“Our aim is to study the properties of matter at the smallest scale and highest energy,” CERN director-general Fabiola Gianotti said as she presented an interim report in Geneva.
The report laid out the first findings of a FCC feasibility study that will be finalized by 2025.
$17 billion first stage
In 2028, CERN’s member states, which include the UK and Israel, will decide whether or not to go through with the plan.
If given the green light, construction on the collider would start in 2033.
The project is split into parts.
In 2048, the “electron-positron” collider would start smashing light particles, with the aim of further investigating the Higgs boson and what is called the weak force, one of the four fundamental forces.
The cost of the tunnel, infrastructure and the first stage of the collider would be about 15 billion Swiss Francs ($17 billion), Gianotti said.
The heavy duty hadron collider, which would smash protons together, would only come online in 2070.
Its energy target would be 100 trillion electronvolts—smashing the LHC’s record of 13.6 trillion.
Gianotti said this later collider is the “only machine” that would allow humanity “to make a big jump in studying matter”.
After eight years of study, the configuration chosen for the FCC was a new circular tunnel 90.7 kilometers (56.5 miles) long and 5.5 meters (feet) in diameter.
The tunnel, which would connect to the LHC, would pass under the Geneva region and its namesake lake in Switzerland, and loop round to the south near the picturesque French town of Annecy.
Eight technical and scientific sites would be built on the surface.
CERN said it is consulting with the regions along the route and plans to carry out impact studies on how the tunnel would affect the area.
X-ray diffraction patterns at different temperatures (top), and the extracted fraction of chiral compound (bottom) show that the proportion of chiral compound increases at lower temperature. Credit: Tokyo Metropolitan University
As the proportion of iridium is increased, the proportion of P6122, the chiral component, increases. Credit: Tokyo Metropolitan University
Superconductivity can be confirmed below an iridium proportion of around x = 0.85 in (Pt1-xIrx)3Zr5. Credit: Tokyo Metropolitan University
