Researchers at CRANN, and the School of Physics at Trinity College Dublin have discovered that a new material can act as a super-fast magnetic switch. When struck by successive ultra-short laser pulses it exhibits ‘toggle switching’ that could potentially increase the capacity of the global fibre optic cable network by an order of magnitude.
Expanding the capacity of the internet
Switching between two states ‘0’ and ‘1’ is the basis of digital technology and the backbone of the internet. The vast majority of the all the data we download is stored magnetically in huge data centres across the world, linked by a network of optical fibres. Obstacles to further progress with the internet are threefold, specifically the speed and energy consumption of the semiconducting or magnetic switches that process and store our data and the capacity of the fibre optic network to handle it. The new discovery of ultra-fast toggle switching using laser light on mirror-like films of an alloy of manganese, ruthenium and gallium known as MRG could help with all three problems. Not only does light offer a great advantage when it comes to speed but magnetic switches need no power to maintain their state. More importantly, they now offer the prospect of rapid time-domain multiplexing of the existing fibre network, which could enable it to handle ten times as much data.
The science behind magnetic switching
Working in the photonics laboratory at CRANN, Trinity’s nanoscience research centre, Dr Chandrima Banerjee and Dr Jean Besbas used ultra-fast laser pulses lasting just a hundred femtoseconds (one ten thousand billionth of a second) to switch the magnetization of thin films of MRG back and forth. The direction of magnetization can point either in or out of the film. With every successive laser pulse, it abruptly flips its direction. Each pulse is thought to momentarily heat the electrons in MRG by about 1000 degrees, which leads to a flip of its magnetization. The discovery of ultra-fast toggle switching of MRG is published this week in Nature Communications.
Dr Karsten Rode, Senior Research Fellow in the ‘Magnetism and Spin Electronics Group’ at Trinity’s School of Physics, suggests that the discovery just marks the beginning of an exciting new research direction.
“We have a lot of work to do to fully understand the behaviour of the atoms and electrons in a solid that is far from equilibrium on a femtosecond timescale. In particular, how can magnetism change so quickly while obeying the fundamental law of physics that says that angular momentum must be conserved? In the spirit of our spintronics team, we will now gather data from new pulsed-laser experiments on MRG, and other materials, to better understand these dynamics and link the ultrafast optical response with electronic transport. We plan experiments with ultra-fast electronic pulses to test the hypothesis that the origin of the toggle switching is purely thermal”.
Next year Chandrima will continue her work at University of Haifa, Israel, with a group who can generate even shorter laser pulses. The TCD researchers, led by Karsten, plan a new joint project with collaborators in the Netherlands, France, Norway and Switzerland aimed at proving the concept of ultrafast time-domain multiplexing of fibre-optic channels.
The work that made the discovery possible was supported by Science Foundation Ireland, The Irish Research Council and the European Commission.
Ireland’s High-Performance Computing authority announced on, Friday September 11, the details of seven academic projects which will be supported by its new Academic Flagship Programme. Two of the seven projects were awarded to Trinity’s School of Physics.
The Academic Flagship Programme will operate under the EuroHPC Competency Centre for Ireland which ICHEC recently launched. It is one of 33 similar centres across Europe which form the ambitious EuroHPC programme. The two year Academic Flagship Programme aims to increase Irish competitiveness in the European supercomputing landscape. The successful projects were selected from a competitive call which received 13 proposals from researchers distributed across 17 universities/institutes across Ireland, UK, Spain, France, Germany, Denmark, Japan and the USA.
Commenting on the success, Prof. Stefano Sanvito, AMBER, Director or CRANN and School of Physics explains his project, Development of a flexible and modularized first-principles machine-learning infrastructure for automatic new materials discovery – application to high-entropy alloys,
“Our project aims at establishing an automatic workflow for materials discovery that will integrate machine learning/artificial intelligence methods with state-of-the-art electronic structure theory. The collaboration with ICHEC computational scientists will allow us to implement such program on massively parallel computational infrastructures, and eventually on the peta-scale facilities that will be soon available in Europe. Our ambition is to be able to map the enormous chemical and structural space available to high-entropy alloys, in the search for ideal compounds for a number of applications. These include high-performance metallurgy, aereospace, precision mechanics and catalysis.”
Prof. John Goold at Trinity’s School of Physics secured an award for his project “Kernel polynomial methods for quantum spin chains”; explaining the project, Prof. Goold commented:
“From a scientific perspective we are interested in a century old fundamental question: how does thermodynamics and thermal behaviour emerge from the unitary dynamics of isolated quantum dynamics. This requires the simulation of complex quantum dynamics for both large systems and long times without any of the usual approximation such as mean field etc. This requires exponential computational resources. Although quantum simulators are currently on the horizon, we will use this support to develop codes on the largest of European computational facilities.”
Commenting on the significance of Euro-HPC Programme for Ireland, J-C Desplat Director, ICHEC said;
“High-Performance Computing is a strategic resource for Europe’s future for academia and business. Coming technology changes will drive competitiveness and Europe is aware that supercomputing is fundamental to this. Ireland, through ICHEC, will gain access for researchers and SMEs to a coordinated, integrated, high level of expertise across Europe in high-performance computing and related disciplines for science and industry, such as high-performance data analytics, classical simulation, and artificial intelligence.”
Dr Alessandro Lunghi, Research Fellow at AMBER, the Trinity Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) and Trinity’s School of Physics, has been awarded prestigious European Research Council (ERC) Starting Grant Awards worth €1.5 million in the latest round of results, which have been released today.
ERC Starting Grants are awarded annually to individual researchers to help them build their own teams and conduct pioneering research across all disciplines, ERC Starting Grant awards are highly competitive.
Dr Alessandro Lunghi will lay the foundations for a major technological breakthrough with his project AI-DEMON: Artificial intelligence design of molecular nano-magnets and molecular qubits. Dr Lunghi will use novel machine-learning techniques in his research, disrupting current systems and methods used in the discovery of new materials which can be a slow and expensive process. With AI-DEMON, machine-learning computational methods will be the used to design new materials, in particular, new magnetic molecules for applications in quantum technology.
The 5-year research project addresses the challenge to make quantum computing and other quantum applications a reality, as Dr Lunghi explains,
“Quantum technologies are becoming increasingly attractive for computational applications, but the actual realisation of quantum devices is still an immense challenge. One of the reasons for this is that the quantum properties of materials only manifest themselves at very low temperatures. Magnetic molecules, for example, have been proposed in recent years for high-density information storage in quantum applications, but to utilise their quantum properties they require low-temperatures to operate. The main objective of AI-DEMON is to unravel the secrets of the quantum world, focusing first on molecular spins and how they interact with the surrounding microscopic world. We will then explore pathways to exploit this knowledge and design new molecules that can operate at higher temperatures. Understanding the details of these microscopic processes is of fundamental importance for the success of quantum technologies and, in the long-term, it will help to deliver all their potential”.
The ambitious AI-DEMON project will shed light on how fundamental quantum entities, such as electronic spins and molecular vibrations, interact with each other opening up possibilities to manifest these interactions through chemical synthesis. This project will enable a better, more comprehensive, understanding of the quantum world that surrounds us which may have consequences also for other branches of physics and chemistry.
Commenting on his success Dr Lunghi said:
“I have always been fascinated by the possibility of designing new materials starting from nothing more than the knowledge of the laws of physics. I am incredibly grateful to the European Research Council for this amazing opportunity. Thanks to this grant I will establish a new research group at Trinity College Dublin and pursue key technological goals related to the design of materials for quantum technologies. I would like to express my gratitude to the School of Physics, the CRANN Institute and the AMBER Research Centre for supporting my application and assisting me during the proposal preparation. I would also like to thank all those colleagues who have contributed to my research endeavors and in particular Prof. Sanvito, Prof. Totti and Prof. Sessoli for their never-ending support”.
Researchers at AMBER, the SFI Research Centre for Advanced Materials and Bioengineering Research, the Trinity Advanced Microscopy Laboratory and the School of Physics at Trinity, have launched a new project to maximise the imaging potential of electron microscopes. The Trinity team, with the support of the public, will create software to dramatically enhance our ability to examine, and visualise, fragile nanostructures.
The team are inviting everybody to visit their website where visitors can click through images of samples taken from an electron microscope and compare these against reconstructed images. The idea is that humans ability for pattern recognition and visual comparison will generate information to teach a computer this very human task. The results of this citizen science project will enable the team to generate software that can recognise the most truthful reconstructed image of a real nanostructure.
Citizen science to help solve a real world challenge
As anyone who has tried to take a picture at night, close-up, or of a moving object, there are constraints to modern photography. You need enough light so that your camera can take an image, and you need to be able to focus your camera on the object you want to capture. If you can’t, then you may end up with a blurry image that doesn’t accurately represent what you can see. The challenge of taking images of tiny particles with electron microscopes is similar, but with an additional issue: if you want to take a clean image that truly reflects the real nanoworld, you need a high-energy electron beam, which in turn can damage, or completely destroy the sample you want to image. Using lower energy can mean that the images created are not that useful for scientists. Teaching a computer to recognise the best, most truthful representations of the nanoworld, in real time, so there is no time lag between taking an image, and being able to see it, is a real world challenge.
The science behind the citizen science
The science behind the machine learning tool created by the team is unique and involves a two-step automated process. Computer software is already used to deconstruct raw data images generated from electron microscopy into their component parts using principal component analysis. The team want to create additional software that will automatically enable a computer to reconstruct the image thereby greatly speeding up the capacity for real time, lower energy, electron microscopy.
Prof. Lewys Jones, AMBER investigator, SFI & Royal Society Research Fellow, and Ussher Assistant Professor in Ultramicroscopy at the School of Physics, says: “The combination of mathematical and computer tools used in this project is entirely new and could transform how we use these microscopes for research. At the Advanced Microscopy Laboratory we house the most powerful microscopes in Ireland, one of which can take images on the scale of individual atoms. But, as with all imaging techniques, there are limitations; one key limitation is the time between taking and processing an image, and then sending this on to the research scientist. With this new machine learning tool we hope to be able to support nanomaterials researchers with no time lag. This will enable the scientists we work with to give us immediate feedback on their image, so that if any adjustments need to be made, such as changing the orientation of sample, to get better results, and get better information, we can do it there and then.”
Michael Mitchell, student at the School of Physics says: “Applying machine learning techniques is not new in the area of image recognition, and is something that many data-scientists are familiar with. What makes our tool different is our two stage machine learning approach; the first phase being the purely mathematical, unsupervised image-component identification, which we then layer on with the second phase; the separation of useful and useless components, which in contrast to the first phase, is supervised and participant-trained. We hope that hundreds of people will take part in this project because this kind of human input will align closely with researcher preference where mathematical input might miss the mark. We can’t teach a computer without hundreds of human teachers!”
Michael Mitchell is an undergraduate in Theoretical Physics entering 3rd year, and studying as an intern at the Advanced Microscopy Laboratory in the summer of 2020 as a Laidlaw Scholar.