Tyler O'Neal, Staff Editor CLOUD

University of Tokyo creates material for spintronics in magnetic memory

Computers and smartphones have different kinds of memory, which vary in speed and power efficiency depending on where they are used in the system. Typically, larger supercomputers, especially those in data centers, will use a lot of magnetic hard drives, which are less common in consumer systems now. The magnetic technology these are based on provides very high capacity but lacks the speed of solid state system memory. Devices based on upcoming spintronic technology may be able to bridge that gap and radically improve upon even the theoretical performance of classical electronic devices. Mn3Sn. (Left) A cross-sectional transmission electronic microscope image of the research material on a layer of tungsten (W) and magnesium oxide (MgO). (Right) A top down view of the material with an inset image showing manganese atoms in red and tin atoms in light blue. ©2022 Nakatsuji et al.

Professor Satoru Nakatsuji and Project Associate Professor Tomoya Higo from the Department of Physics at the University of Tokyo, together with their team, explore the world of spintronics and other related areas of solid state physics — broadly speaking, the physics of things that function without moving. Over the years, they have studied special kinds of magnetic materials, some of which have very unusual properties. You’ll be familiar with ferromagnets, as these are the kinds that exist in many everyday applications like computer hard drives and electric motors — you probably even have some stuck to your refrigerator. However, of greater interest to the team are more obscure magnetic materials called antiferromagnets.

“Like ferromagnets, antiferromagnets’ magnetic properties arise from the collective behavior of their component particles, in particular the spins of their electrons, something analogous to angular momentum,” said Nakatsuji. “Both materials can be used to encode information by changing localized groups of constituent particles. However, antiferromagnets have a distinct advantage in the high speed at which these changes to the information-storing spin states can be made, at the cost of increased complexity.”

“Some spintronic memory devices already exist. MRAM (magnetoresistive random access memory) has been commercialized and can replace electronic memory in some situations, but it is based on ferromagnetic switching,” said Higo. “After considerable trial and error, I believe we are the first to report the successful switching of spin states in antiferromagnetic material Mn3Sn by using the same method as that used for ferromagnets in the MRAM, meaning we have coaxed the antiferromagnetic substance into acting as a simple memory device.”

This method of switching is called spin-orbit torque (SOT) switching and it’s cause for excitement in the technology sector. It uses a fraction of the power to change the state of a bit (1 or 0) in memory, and although the researchers’ experiments involved switching their Mn3Sn sample in as little as a few milliseconds (thousandth of a second), they are confident that SOT switching could occur on the picosecond (trillionth of a second) scale, which would be orders of magnitude faster than the switching speed of current state-of-the-art electronic computer chips.

“We achieved this due to the unique material Mn3Sn,” said Nakatsuji. “It proved far easier to work with in this way than other antiferromagnetic materials may have been.”

“There is no rule book on how to fabricate this material. We aim to create a pure, flat crystal lattice of Mn3Sn from manganese and tin using a process called molecular beam epitaxy,” said Higo. “There are many parameters to this process that have to be fine-tuned, and we are still refining the process to see how it might be scaled up if it’s to become an industrial method one day.”

University of Barcelona uses ML to predict the consequences of genomic changes over time that make humans emerge

Tyler O'Neal, Staff Editor CLOUD

The study of the genomes of our closest relatives, the Neanderthals, and Denisovans, has opened up new research paths that can broaden our understanding of the evolutionary history of Homo sapiens. A study led by the University of Barcelona has made an estimation of the time when some of the genetic variants that characterize our species emerged. It does so by analyzing mutations that are very frequent in modern human populations, but not in these other species of archaic humans. 58fcb985 54f2 49ae a391 1c7a5dcc629c humbcronologiajpg1095776142 73902

The results show two moments in which mutations accumulated: one around 40,000 years ago, associated with the growth of the Homo sapiens population and its departure from Africa, and an older one, more than 100,000 years ago, related to the time of the greatest diversity of types of Homo sapiens in Africa.

"The understanding of the deep history of our species is expanding rapidly. However, it is difficult to determine when the genetic variants that distinguish us from other human species emerged. In this study, we have placed species-specific variants on a timeline. We have discovered how these variants accumulate over time, reflecting events such as the point of divergence between Homo sapiens and other human species around 100,000 years ago", says Alejandro Andirkó, first author of this article, which was part of his doctoral thesis at the UB.

The study, led by Cedric Boeckx, ICREA research professor in the section of General Linguistics and member of the Institute of Complex Systems of the UB (UBICS), included the participation of Juan Moriano, UB researcher, Alessandro Vitriolo, and Giuseppe Testa, experts from the University of Milan and the European Institute of Oncology.

The predominance of behavioral and facial-related variations

The results of the research study also show differences between evolutionary periods. Specifically, they highlight the predominance of genetic variants related to behavior and facial structure —key characteristics in the differentiation of our species from other human species— more than 300,000 years ago, a date that coincides with the available fossil and archaeological evidence. "We have discovered sets of genetic variants which affect the evolution of the face and which we have dated between 300,000 and 500,000 years ago, the period just prior to the dating of the earliest fossils of our species, such as the ones discovered at the Jebel Irhoud archaeological site in Morocco", notes Andirkó.

The researchers also analyzed variants related to the brain, the organ that can best help explain key features of the rich repertoire of behaviors associated with Homo sapiens. Specifically, they dated variants that medical studies conducted in present-day humans have linked to the volume of the cerebellum, corpus callosum, and other structures. "We found that brain tissues have a particular genomic expression profile at different times in our history; that is, certain genes related to neural development were more highly expressed at certain times," says the researcher.

Supporting the mosaic nature of the evolution of Homo sapiens

These results complement an idea that is dominant in evolutionary anthropology: that there is no linear history of the human species, but that different branches of our evolutionary tree coexisted and often intersected. "The breadth of the range of human diversity in the past has surprised anthropologists. Even within Homo sapiens, there are fossils, such as the ones I mentioned earlier from Jebel Irhoud, which, because of their features, were thought to belong to another species. That's why we say that human beings have lived a mosaic evolution," he notes.

“Our results,” the researcher continues, “offer a picture of how our genetics changed, which fits this idea, as we found no evidence of evolutionary changes that depended on one or several key mutations," he says.

Application of machine learning techniques

The methodology used in the study was based on a Genealogical Estimation of Variant Age method, developed by researchers at the University of Oxford. Once they had this estimation, they applied a machine learning tool to predict which genes have changed the most in certain time windows and which tissues these genes may have impacted. Specifically, they used ExPecto, a deep learning tool that uses a convolutional network — a type of computational model — to predict gene expression levels and function from a DNA sequence.

"Since there are no data on the genomic expression of variants in the past, this tool is an approach to a problem that has not been addressed until now. Although the use of machine learning prediction is increasingly common in the clinical world, as far as we know, nobody has tried to predict the consequences of genomic changes over time,” notes Andirkó.

The importance of the perinatal phase in the brain development of our species

In a previous study, the same UB team, together with the researcher Raül Gómez Buisán, used genomic information from archaic humans. In that study, they analyzed genomic deserts, regions of the genome of our species where there are no genetic fragments of Neanderthals or Denisovans, and which, moreover, have been subjected to positive pressure in our species: that is, they have accumulated more mutations than would have been expected by neutral evolution. The researchers studied the expression of genes — i.e., which proteins code for different functions — found in desert regions throughout brain development, from prenatal to adult stages, covering sixteen brain structures. The results showed differences in gene expression in the cerebellum, striatum, and thalamus. "These results bring into focus the relevance of brain structures beyond the neocortex, which has traditionally dominated research on the evolution of the human brain," says Juan Moriano.

Moreover, the most striking differences between brain structures were found at prenatal stages. "These findings add new evidence to the hypothesis of a species-specific trajectory of brain development taking place at perinatal stages — the period from 22 weeks to the end of the first four weeks of neonatal life — that would result in a more globular head shape in modern humans, in contrast to the more elongated shape seen in Neanderthals," concludes Moriano.

WAE, Imperial College London support Faraday Institution funded BESAFE project to advance the understanding of the initiation, propagation of thermal runaway

Tyler O'Neal, Staff Editor CLOUD
  • Williams Advanced Engineering and Imperial College London are collaborating  to advance the understanding of the initiation and propagation of thermal runaway
     
  • The project aims to bridge the gap between thermofluid science and battery electrochemistry, developing a multiphase, multiphysics model of battery failure via thermal runaway
     
  • The program complements the Faraday Institution’s Multi-Scale Modelling and SafeBatt projects 

Imperial College London and Williams Advanced Engineering (WAE) are working on a project to bridge the gap between thermofluid science and battery electrochemistry; developing a first-of-a-kind multiphase multiphysics model of battery failure via thermal runaway (a self-sustaining cascade of exothermic reactions that produce large volumes of gas).  The model will consider gas dynamics and their interactions with electrochemical and thermal behaviors, to advance the understanding of initiation and propagation of the thermal runaway processes and accelerate the design of countermeasures. vcsprasset 3689076 334137 f9cc 66bd7

The work that the Electrochemical Science and Engineering research group at Imperial College London has achieved in the battery field aligns with WAE’s interest in offering greater battery safety and longevity. Achieving this will deliver cost-effective electrification solutions to benefit both WAE and the global client base.

Applying the multiphase multiphysics modeling toolsets will enable the design of safer battery packs with fewer iterations and physical tests; saving time, costs, and materials.

As part of this program, WAE will provide thermal runaway/propagation test data which has been developed as a result of numerous Research and Development programs whilst the battery team will provide technical knowledge and industrial experience on battery safety designs helping steer the project to success.

Rob Millar, Head of Electrification, Williams Advanced Engineering commented “We are confident that the proposed study will bring tangible economic and environmental benefits and look forward to building on our long term partnership with the team at Imperial College London.”

Dr. Huizhi Wang of Imperial College London who is leading the project said “Understanding and modeling thermal runaway plays a crucial role in guiding the development of safer batteries but remains challenging due to the complexity of the process. We are excited to be working with Williams Advanced Engineering on this research project to address the key knowledge gaps in battery safety modeling.”