Tyler O'Neal, Staff Editor HEALTH

Unusual magnetic transition in perovskite oxide can help boost spintronics

Transition metal perovskites oxides exhibit several desirable properties, including high-temperature superconductivity and electrocatalysis. Now, scientists at Tokyo Institute of Technology explore the structure and properties of a perovskite oxide, PbFeO3, in anticipation of the unusual charge distribution and exotic magnetic transitions displayed by such systems. They report two of the magnetic transitions, with a distinctive transition above room temperature and look into its causes, opening doors to potential applications in realizing new spintronic devices.

The advent of electronics has revolutionized our lives to an extent where it is impossible to imagine going about our day without relying on an electronic device in some form. What is even more remarkable, however, is that we can improve these devices even further by harnessing the electron's "spin"--a property which makes the electron behave like a magnet--to create memory devices that are faster and use lower power than traditional electronics. Accordingly, the field devoted to this endeavor, aptly called "spintronics", relies on exploiting the "spin state" of the electron. However, controlling spin can be extremely tricky, a fact that often leads scientists on a hunt for materials with ordered spin states.

Their attention has recently turned to lead-based transition metal perovskite oxides, a class of materials represented by PbMO3 (where the "M" indicates 3d transition metal ion), that display rather interesting phase transitions in spin states, making them appealing for practical applications.

In a recent study published in an academic journal, a team of scientists from China, Japan, Taiwan, Switzerland, Germany, France, and USA, examined the perovskite oxide PbFeO3, a compound that has evaded inspection until now, owing to difficulties in synthesizing samples and resolving its crystal structure. "The perovskite family of PbMO3 exhibits complex charge distributions and RFeO3 (R = rare earth) shows several interesting spin-related properties, such as laser-induced ultrafast spin reorientation, so we expect similarly characteristic charge distribution and rich spin-state transitions for PbFeO3," comment Prof. Masaki Azuma from Tokyo Institute of Technology, Japan and Prof. Youwen Long from Chinese Academy of Science, who led the study.

Consequently, the team investigated the structure, charge state, and magnetic properties of PbFeO3 using a variety of characterization techniques and backed up their observation with density functional theory (DFT) calculations.

The team found that PbFeO3 crystallized into a unique "charge-ordered" state in which a layer of Pb2+ ions was interleaved by two layers made up of a mixture of Pb2+ and Pb4+ ions in a 3:1 ratio, along the direction of layer stacking (Figure 1). On cooling the sample from high temperature, the team observed two distinct magnetic phase transitions: a weak ferromagnetic transition occurring at 600 K (327°C) characterized by a "canted antiferromagnetic" spin ordering (oppositely directed neighboring spins), and a continuous spin reorientation (SR) transition at 418 K (145°C) (Figure 2). 260502 web 69c8b

The SR transition, although common in all RFeO3 perovskites, stood out in this case because it occurred at a much higher temperature compared to those for other perovskites, and unlike the R--Fe magnetic interactions usually identified as the cause for this transition, there was no such counterpart in the case of PbFeO3. To resolve the conundrum, scientists turned to DFT calculations, which revealed that the unique charge ordering in PbFeO3 led to the formation of two Fe3+ "sublattices" with competing energies that, in turn, caused the peculiar SR transition. On cooling the sample, scientists first observed a weak ferromagnetic transition (WFM) at 600 K, characterized by a canted antiferromagnetic (CAFM) spin ordering, and then a continuous spin reorientation (SR) transition at 418 K.

The team is thrilled by these findings and their implications for future applications. "Our work provides a new avenue for studying the charge ordering phase and distinctive SR transition with potential applications in spintronic devices due to the high transition temperature and possible tuning," remarks the theoretical team leader, Prof. Hena Das.

One thing's for sure--we're one step closer to making spintronics the reality of tomorrow!

Russian scientists find explanation for abnormally fast release of gas from nuclear fuel

Tyler O'Neal, Staff Editor HEALTH

Scientists at MIPT have found a possible explanation for the anomalously fast release of gas from nuclear fuel. Supercomputer simulations have uncovered an unexpected mechanism for accelerating the escape of gas bubbles from the uranium dioxide crystal matrix to the surface. The result points the way to eliminate the paradoxical discrepancy of several orders of magnitude between existing theoretical models and experimental results. The paper was published in the Journal of Nuclear Materials.

The diffusion of gas bubbles during reactor operation is one of the important topics in nuclear power relating to radiation safety. Bubbles of gaseous fission products (mainly xenon), accumulating in the fuel, affect many of its properties. Therefore, it is important, in the design and operation of reactors, to know how fast the gas escapes from the fuel.

Despite the active work of various scientific groups in this field, there is still no complete understanding of the mechanisms of diffusion of gases in fuels. The recent series of works by French researchers is a striking evidence of this fact. The results shown by their proposed model are dozens of times lower than those measured in special experiments. "The very fact that such contradictory results and, in fact, unworkable theory have been published demonstrates, on the one hand, the scientific community's great interest in this problem and, on the other, the need to find fundamentally new physical mechanisms of ultrafast diffusion," says MIPT professor Vladimir Stegailov. Example of a computational cell: a crystal lattice of uranium dioxide (grey atoms are uranium, red atoms - oxygen) containing a bubble of xenon (yellow atoms). Uranium atoms displaced to inter-nodal positions are shown in black. Such a cluster of interstitial nodes greatly accelerates bubble diffusion. Provided by the authors of the paper.

The MIPT scientists led by Vladimir Stegailov were able to simulate the diffusion of xenon nanobubbles in uranium dioxide over an atomic-scale time period of up to three microseconds (three billion integration steps). This was made possible by the optimal use of supercomputer power and modern codes. Such record-breaking molecular dynamics calculations have enabled direct observation of the Brownian motion of the bubble and discovery of a fundamentally new diffusion mechanism.

It was thought previously that the higher the gas concentration the slower the diffusion, as the gas interferes with the movement of the dioxide on the bubble's surface . The authors showed that upon reaching a certain concentration the gas pushes the atoms of the crystal lattice to inter-nodal positions.

"By accumulating, the inter-nodal atoms form clusters that move rapidly around the bubble. The bubble and the cluster periodically push each other and thus move significantly faster than the bubble on its own. Thus appears a new effect - acceleration of diffusion by gas", explains Alexander Antropov, a postgraduate student at FEFM (Phystech School of Electronics, Photonics and Molecular Physics at MIPT) and one of the authors of the study. The discovered effect will help explain the discrepancy between theory and experiment.

Italian Institute of Technology explores satellite data using AI to discover hidden archaeological sites

Tyler O'Neal, Staff Editor HEALTH

The Cultural Landscapes Scanner pilot project will exploit Artificial Intelligence to detect the archaeological heritage of the subsoil. The project will last three years and will be carried out by IIT in collaboration with the European Space Agency

Today in Venice, Italy, the "Cultural Landscapes Scanner" (CLS) project has been launched from the collaboration between Istituto Italiano di Tecnologia (IIT- Italian Institute of Technology) and the European Space Agency (ESA) in order to detect archaeological sites from above by analyzing satellite images through artificial intelligence (AI). IIT's researchers of the Centre of Cultural Heritage Technology, led by Arianna Traviglia, will introduce AI to help archaeologists trace back the ancient presence of humans by revealing hidden traces in the soil. The AI will be able to recognize even minimal or imperceptible variations in vegetation or other particular signs of the surface that may indicate the presence of remains not yet discovered. The project will last three years and may have as an immediate outcome an improved capacity of identifying cultural heritage sites at risk of looting. The AI developed by IIT researchers will analyzing satellite images in order to detect traces of hidden archaeological sites. CREDIT ESA/IIT

In the last decades, the identification of sub-surface cultural heritage sites has taken advantage of Remote Sensing data, a way of detecting that allows to find buried objects in the sub-soil through images in which is possible to recognize subsoil archaeological deposits from anomalies and traces in bare soils, crops or vegetation. Arianna Traviglia's previous studies have already investigated the potential advantages of developing automated remote sensing, but they have also shown that the current technologies have some limits, being able to detect only very specific objects. In this scenario, web platforms of free remote sensing datasets have known exponential growth and they are amply used by the Cultural Heritage community around the world. Among them, there is Copernicus, the free and open satellite data platform for Earth observation coordinated by the European Commission in partnership with ESA.

However, the visual analysis of data coming from these platforms is extremely complex due to a large amount of data to be managed and because the images must be viewed and human interpreted. For this reason, the real challenge for Traviglia's research group is to add machine learning and computerized artificial vision in order to make this job much easier. The group is one of the few in the world that has designed algorithms for automatic detection of archaeological and cultural heritage sites.

The "Cultural Landscapes Scanner" (CLS) project will have, thus, an innovative approach aiming to overcome the current methods based on subjective observation, making possible a wider and more precise detection thanks to advanced computational methods.

Researchers will define a broad spectrum, adaptable and robust automated recognition procedure, customized for cultural heritage sites using the tele data obtained from the Copernicus platform. Automated Remote Sensing, via machine learning, will produce a more accurate detection of the cultural heritage objects through satellite imagery and clearer identification of ancient land division systems.

Machine learning algorithms can improve automatically by gaining experience in an incremental self-learning process. Therefore, AI will be able to offer an increasingly precise identification of potential underground archaeological sites.

This AI approach will be able to see objects or irregularities that are usually impossible to see for the human eye. The combination of these elements will produce the possibility to observe traces in the vegetation, bare soils, hollows, and crop marks. Thus, AI will support current photo-interpretation practices, based on subjective observations, thanks to its accuracy in analyzing images and the possibility to explore wider spatial areas. Another aspect that will surely profit from the development of Automated Remote Sensing is the increased possibility of cultural heritage preservation. In fact, an immediate outcome will be represented by an improved capacity of response to cultural threats identifying the cultural heritage sites at risk of looting.