Researchers create stable superconductor enhanced by magnetism

An international team including researchers from the University of Würzburg has succeeded in creating a special state of superconductivity. This discovery could advance the development of quantum computers. The results are published in Nature Physics. Superconductors are materials that can conduct electricity without electrical resistance—making them the ideal base material for electronic components in MRI machines, magnetic levitation trains and even particle accelerators. However, conventional superconductors are easily disturbed by magnetism. An international group of researchers has now succeeded in building a hybrid device consisting of a stable proximitized-superconductor enhanced by magnetism and whose function can be specifically controlled. They combined the superconductor with a special semiconductor material known as a topological insulator. "Topological insulators are materials that conduct electricity on their surface but not inside. This is due to their unique topological structure, i.e., the special arrangement of the electrons," explains Professor Charles Gould, a physicist at the Institute for Topological Insulators at the University of Würzburg (JMU). "The exciting thing is that we can equip topological insulators with magnetic atoms so that they can be controlled by a magnet."

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The android robotgirl to topological superconductor girl pipeline

tagged by @the-commonplace-book. Thank you for the tag! It is appreciated, I got to reflect on my recent leisures.

nine things / nine people / nine companions

Last Song: "Do not touch" by MiSaMo

Favorite Color: Green and Blue from its natural shades (like the forests or sea foam) to the pastel (~matcha / aquamarine) variants

Last Movie/TV Show: Last movie watched was "Murder on the Orient Express" (2017), whereas last TV(streaming?) show watched was Jujutsu Kaisen E29 (~S2:E5, iirc)

Sweet/Savory/Spicy: All three would be nice, although if it isn't close to dessert I would not mind mostly savory and a bit spicy.

Last Thing I Googled: "Topological insulators vs topological superconductors"

Current Obsession: I don't have a singular obsession, but I suppose my materials research takes the largest chunk of my time at the moment. Outside of research work, my music rotation currently is Christopher Tin - Twice - Taylor Swift - Red Velvet - Thomas Bergersen. (The idol groups tend to change somewhat more frequently than the composers or the solo act, and also my genres are everywhere, and the rotation loops back ehehehe...). As you can hopefully see by now, I am not built correctly for a satisfactory answer for this category.

Last Book: I'm currently alternating between "To the Lighthouse" by Virginia Woolf, and "This is How You Lose the Time War" by Amal El-Mohtar and Max Gladstone.

Do research articles fall under book? If so, mostly stuff about hexagons. I would like to not spoil my studies further until I have something conclusive to show for it.

Last Fic: "That's what love feels like I think" by Saberin recently posted valentines fanfic re: Bocchi the Rock band poly. It cute.

Looking Forward To: After my undergrad final presentation in a couple weeks, I would like to return playing Star Rail, at least on auto, and exploring a chunk of Genshin beyond Dharma Forest (but also I have to catch up on the story quests from the underground Chasm!!!!) so I can progress a bit into my worldbuilding studies on it, at least for what remains of the spring holidays. In the longer term sense of things, I would like a successful experimental trial please, thank you.

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No pressure tags for this trend: @emanation-aura @astrophyta @istharoth @yuniemaki @berryblooo @craminni @nanbeidou @castaincognito @sunnyy-sunsh1ne

Vortices are an example of topological defect, and also occur in other situations. Quantized vortices are found in type II superconductors, called Abrikosov vortices. Classical vortices are relevant to the Berezenskii–Kosterlitz–Thouless transition in two-dimensional XY model.

Description[edit]

When electrons are confined to two dimensions, cooled to very low temperatures, and subjected to a strong magnetic field, their kinetic energy is quenched due to Landau level quantization. Their behavior under such conditions is governed by the Coulomb repulsion alone, and they produce a strongly correlated quantum liquid. Experiments have shown[1][2][3] that electrons minimize their interaction by capturing quantized vortices to become composite fermions.[5] The interaction between composite fermions themselves is often negligible to a good approximation, which makes them the physical quasiparticles of this quantum liquid.

The signature quality of composite fermions, which is responsible for the otherwise unexpected behavior of this system, is that they experience a much smaller magnetic field than electrons

Quantum Machine Learning for Materials Science

In materials science, complex computational models are crucial to understanding and developing new technologies. These computations often push the limits of conventional high-performance supercomputing centers, and have been identified as one of the areas where quantum computing could make the most impact. Quantum machine learning (QML) – the cutting-edge fusion of classical and quantum AI – is poised to accelerate materials discovery, and is already changing the way we develop and use materials.

Machine learning is well-suited to analyzing massive data sets and making sense of the information they contain. This is especially the case when dealing with large-scale diffraction data, such as that from synchrotron experiments. Cornell physicists and computer scientists have developed an interpretable and unsupervised machine learning algorithm, called X-ray Temperature Clustering (X-TEC), which can analyze voluminous diffraction datasets in minutes and provide an accurate picture of a material’s structure. X-TEC is currently being used at the Cornell High Energy Synchrotron Source and Advanced Photon Source to help physicists and computational scientists understand and analyze complex materials such as the quantum metal Cd2Re2O7. The work settles a decades-long debate about the physics of this particular material, and shows how ML can be paired with synchrotron data to uncover exciting new phases of matter.

The X-TEC algorithm uses a set of fingerprints, which encode the material’s electronic band structure and crystallographic and constitutional information, to predict the critical temperature of a candidate material. The results of the model are compared to experimental data from synchrotron experiments and can guide subsequent explorations, saving time and resources by eliminating unnecessary iterations. The approach can also be applied to other classes of high-temperature Who are techogle? superconductors, and it can be trained to identify potential new superconductors from a database of existing candidates.

More recently, researchers have developed methods to combine DFT calculations and heuristic criteria to discover novel superconductors. These strategies have been augmented with machine-learning algorithms, which can learn from the mistakes and successes of previous experiments to improve the accuracy of future searches. An example of this is a gradient boosting model that can predict topological properties in materials using only coarse-grained chemical composition and crystal symmetry predictions.

The development of these predictive ML models aims to increase the efficiency and speed of materials discovery, moving away from iterative trial-and-error and towards a more automated search for the next generation of technologies. The ultimate goal is to build self-driving laboratories, where artificial intelligence orchestrates multiple synthesis and characterization experiments, updating its knowledge through feedback loops from the experimental results. These systems could then guide technology website the characterization of promising candidates and automatically continue to explore until the desired goal is reached. This would enable the rapid discovery of new quantum materials for applications in aerospace, electronics, biomedicine, and clean energy. The next generation of quantum computers and sensors, for instance, will be built from these materials. To enable this new era of quantum computing, we need to understand and harness its most powerful tool: pattern recognition.

Light-induced topological phase transition via nonlinear phononics in superconductor CsV3Sb5

http://dlvr.it/T0dNJr

Unveiling the Future: Recent Advancements in Advanced Materials Journal

Abstract: This article explores the latest developments and breakthroughs in the realm of advanced materials, shedding light on cutting-edge research that is shaping the future of materials science. From nanotechnology to smart materials, the field is witnessing remarkable progress, offering unprecedented possibilities for innovation across various industries.

Introduction: Advanced materials journal play a pivotal role in the evolution of modern technology, enabling breakthroughs in fields ranging from electronics to medicine. This article aims to provide a comprehensive overview of recent advancements in advanced materials, showcasing their potential impact on various applications.

Nanomaterials Revolution: The advent of nanotechnology has ushered in a new era for advanced materials journal. Nanomaterials, with dimensions on the nanoscale, exhibit unique properties that differ significantly from their bulk counterparts. Researchers are exploring novel synthesis methods and applications for nanomaterials, ranging from enhanced drug delivery systems to ultra-efficient energy storage devices.

Smart Materials and Their Applications: Smart materials, capable of responding to external stimuli, are gaining prominence in fields like aerospace, healthcare, and construction. Shape-memory alloys, piezoelectric materials, and self-healing polymers are just a few examples of materials that are transforming the way we design and engineer products. The article delves into recent breakthroughs in the development and application of smart materials.

Sustainable Materials for a Greener Future: The pursuit of sustainability has driven researchers to explore eco-friendly alternatives in advanced materials. Biodegradable polymers, recycled composites, and materials sourced from renewable resources are at the forefront of this movement. The article discusses how these sustainable materials contribute to reducing environmental impact across industries.

Advances in Energy Storage and Conversion: As the demand for clean energy grows, so does the need for advanced materials in energy storage and conversion technologies. Lithium-ion batteries, supercapacitors, and materials for solar cells are undergoing continuous improvement. The article highlights recent breakthroughs in materials that contribute to more efficient and sustainable energy solutions.

Quantum Materials and Computing: The field of quantum materials is rapidly evolving, with implications for the future of computing. Quantum dots, superconductors, and topological insulators are some of the materials driving advancements in quantum computing and information processing. The article explores the potential of these materials to revolutionize the way we process and store information.

Conclusion: In conclusion, the landscape of advanced materials is continually evolving, with researchers pushing the boundaries of what is possible. This article has provided a glimpse into the recent advancements in nanomaterials, smart materials, sustainable alternatives, energy storage, and quantum materials, showcasing the diverse and exciting avenues that lie ahead in the field of advanced materials.

Keywords: Advanced materials, nanotechnology, smart materials, sustainability, energy storage, quantum materials.

Feel free to modify and expand on each section based on specific research findings or developments in the field.

Hyderabad,Telangana

Research #papers #publish

Researchers Advance Topological Superconductors for Quantum Computing - Technology Org

New Post has been published on https://thedigitalinsider.com/researchers-advance-topological-superconductors-for-quantum-computing-technology-org/

Researchers Advance Topological Superconductors for Quantum Computing - Technology Org

Quantum computers process information using quantum bits, or qubits, based on fragile, short-lived quantum mechanical states. To make qubits robust and tailor them for applications, researchers from the Department of Energy’s Oak Ridge National Laboratory sought to create a new material system.

Materials scientist Robert Moore probes the interface between a topological insulator and a superconductor. Image credit: Carlos Jones/ORNL, U.S. Dept. of Energy

“We are pursuing a new route to create quantum computers using novel materials,” said ORNL materials scientist Robert Moore, who co-led a study published in Advanced Materials with ORNL colleague Matthew Brahlek, also a materials scientist. The work was supported in part by the U.S. National Science Foundation. 

The researchers coupled a superconductor, which offers no resistance to electrical current, with a topological insulator, which has electrically conductive surfaces but an insulating interior. The result is an sharp interface between crystalline thin films with different symmetric arrangements of atoms.

The novel interface the researchers designed and engineered may lead to exotic new physics and host a unique quantum building block with potential as a superior qubit.

Quantum computer. Image credit: IBM

“The idea is to make qubits with materials that have more robust quantum mechanical properties,” Moore said. “What is important is that we have learned how to control the electronic structure of the topological insulator and the superconductor independently so we can tailor the electronic structure at that interface.”

Challenges remain. “We need to improve and better understand the materials at the atomic level,” Moore said. “We now know how to control the materials at the level required to make that happen.”

Source: NSF

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Researchers advance topological superconductors for quantum computing – The Lifestyle Insider

[ad_1] Newswise — Quantum computers process information using quantum bits, or qubits, based on fragile, short-lived quantum mechanical states. To make qubits robust and tailor them for applications, researchers from the Department of Energy’s Oak Ridge National Laboratory sought to create a new material system.“We are pursuing a new route to create quantum computers using novel materials,” said ORNL materials scientist Robert Moore, who co-led a study published in Advanced Materials with ORNL colleague Matthew Brahlek, who is also a materials scientist.They coupled a superconductor, which offers no resistance to electrical current, with a topological insulator, which has electrically conductive surfaces but an insulating interior. The result is an atomically sharp interface between crystalline thin films with different symmetric arrangements of atoms. The novel interface that they designed and engineered may give rise to exotic physics and host a unique quantum building block with potential as a superior qubit.“The idea is to make qubits with materials that have more robust quantum mechanical properties,” Moore said. “What is important is that we have learned how to control the electronic structure of the topological insulator and the superconductor independently, so that we can tailor the electronic structure at that interface. This had never been done.”Controlling the electronic structure on both sides of an interface may create something called Majorana particles inside the material. “In nature, we have particles and antiparticles, for example electrons and positrons, which annihilate each other when they come in contact. A Majorana particle is its own antiparticle,” Moore said. In 1937 Ettore Majorana predicted the existence of these exotic particles, whose existence remains to be proven.In 2008, theorical physicists Liang Fu and Charlie Kane of the University of Pennsylvania proposed that creating a novel interface between a topological insulator and a superconductor would generate topological superconductivity, a new phase of matter predicted to host Majorana particles.“If you have a pair of Majorana particles and move them around each other, there is a memory of this motion. They always know each other’s location,” Moore said. “This process could be used to encode quantum information and compute in new ways.”However, realization of a new phase of matter that can host Majorana particles depends on finding the right material. Such an achievement takes a diverse team of experts.When Moore came to ORNL in 2019, he brought a new expertise in angle-resolved photoemission spectroscopy, or ARPES, a technique for probing the electronic structure of materials. ARPES is based on the photoelectric effect, for which Albert Einstein was awarded the 1921 Nobel Prize in physics. It focuses a light source on a sample and characterizes electrons ejected from the material surface when the electrons absorb energy from the photons. The technique helps scientists understand how electrons behave inside a material.This strategic investment in ARPES expertise helped ORNL win its bid to lead one of five DOE National Quantum Information Science Research Centers, the Quantum Science Center, which launched in 2020. Led by ORNL’s Travis Humble, the QSC aims to realize quantum computing and sensing applications by developing hardware and algorithms and discovering novel materials. Moore and his colleagues focus on topological materials for hardware development. Since April, Moore has also co-directed ORNL’s Interconnected Science Ecosystem, or INTERSECT, with Ben Mintz to develop laboratories of the future — smart, autonomously controlled processes and experiments with the potential to revolutionize research outcomes.Brahlek, who joined ORNL in 2018 and recently received a DOE Early Career Research award, is an expert in precision synthesis of materials. To make superclean interfaces between a superconductor and topological insulator, he used molecular beam epitaxy, a method industry uses for large-scale fabrication of semiconductors for electronic devices.With help from former postdoctoral fellow Tyler Smith, Brahlek performed the synthesis under ultrahigh vacuum. “Inside the chamber, there are fewer molecules bouncing around than in outer space. It is a really clean environment. It must be well controlled,” Brahlek said. “You start with little furnaces, each containing one element. Each furnace heats until the element inside starts to sublimate, or pass from solid to vapor state. This creates beams of elements. They all converge on a crystal substrate and adhere.”He co-deposited iron, selenium and tellurium to make a superconductor that was one atomic layer thick. “If you can get the conditions exactly right, the deposited atoms will chemically bond and assemble, atomic layer by atomic layer, into a crystalline thin film,” Brahlek said.“A key to getting the results was understanding how to combine bismuth telluride with iron selenide telluride at an atomic interface to gain the desired electronic behavior,” Brahlek said.That accomplishment was tricky because the superconductor’s lattice of iron, selenium and tellurium comprises ordered square cells, whereas the topological insulator is a network of adjoining triangles. “We’re putting something square on something triangular, but, surprisingly, the crystalline film grows nicely,” Brahlek said. “This accomplishment requires understanding the physics and chemistry that happen at these interfaces, which is critical to combining topological and superconducting properties in a single platform.”That platform is the topological superconductor. To understand its topological properties, Moore used spin-resolved ARPES, with help from ORNL postdoctoral fellow Qiangsheng Lu, to probe quantum spin-dependent electronic structure at the interface of the topological insulator and the superconductor. Meanwhile, to confirm its superconducting behavior, Brahlek and former ORNL postdoctoral fellows Yun-Yi Pai and Michael Chilcote assisted with measurements of electrical resistance.“We were able to see how the different electronic structures were interacting at the interface, and we were able to control those interactions to ensure all the ingredients for topological superconductivity exist,” Moore said. “We found that the desired topological properties only exist for specific selenium doping ranges. This was a surprise that is crucial for making qubits.”Meanwhile, Hoyeon Jeon and An-Ping Li at ORNL’s Center for Nanophase Materials Sciences used scanning tunneling microscopy to characterize disorder in the materials. ORNL staff scientists Hu Miao and Satoshi Okamoto provided experimental and theoretical guidance throughout the study.Crucial challenges remain. “We need to improve and better understand the materials at the atomic level, which is critical to confirming and using Majorana particles for applications,” Moore said. “The next step will be exploring possible Majorana particles using a newly installed ultralow-temperature scanning tunneling microscope instrument at CNMS.”He added, “Achieving a qubit based on Majorana particles is one of the ultimate goals of the Quantum Science Center. The Majorana particle in materials is such an exotic state. Proving that it exists will require both building and testing a qubit-like device. It is an odd way to think about it, but you have to make a qubit to prove it is a qubit. We now know how to control the materials to the level required to make this happen.”The title of the paper is “Monolayer Superconductivity and Tunable Topological Electronic Structure at the Fe(Te,Se)/Bi2Te3 Interface.”The work’s funding came from the DOE Office of Science — through the QSC, a DOE National Quantum Information Science Research Center, and the Materials Sciences and Engineering Division — along with the National Science Foundation, the Army Research Office and the Gordon and Betty Moore Foundation. The research used resources at CNMS, a DOE Office of Science user facility at ORNL.UT-Battelle manages ORNL for DOE’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. The Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science. — Dawn Levy window.fbAsyncInit = function () FB.init( appId: '890013651056181', xfbml: true, version: 'v2.2' ); ; (function (d, s, id) var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = " fjs.parentNode.insertBefore(js, fjs); (document, 'script', 'facebook-jssdk')); [ad_2]

Throwback Thursday

Trying out a new thing for the blog - let me know if you like it! (Not sure if this should be a throwback Thursday or a Follow-up Friday?)

This last week (between last Thursday to now), several articles feature work that is a followup to previous work:

On May 2nd I posted This alloy is kinky, research about fracture resistance in a medium entropy alloy published in Science in Apr 2024. One of the authors also showed up in a 2014 post I reblogged about improving the strength of 3D printed alloys.

On May 3rd I shared the research Scientists develop novel one-dimensional superconductor, published in Nature in Apr 2024. The last author on the paper is Andre Giem, who received the 2010 Nobel Prize in Physics with one other individual for his work on graphene. Numerous examples of his work have been shared on this blog with a focus on graphene and 2D materials.

On May 4th there was a post on freeze casting, published in Nature Reviews Methods Primers in Apr 2024. The first author on the paper, Ulrike Wegst, previously appeared on the blog in Sep 2023 for his research Structure formation during freeze casting filmed in 3D and real time.

On May 7th there was Researchers improve the plasticity of ceramic materials at room temperature, with one of the authors being Xinghang Zhang, previously seen on the blog for his work in creating high strength aluminum alloy coatings in 2018.

Finally, just yesterday I posted Advances in topological phase transition in organometallic lattices, which was a direct follow up to research published in Oct 2023.

In a series of recent reports, doped lead apatite (LK-99) has been proposed as a candidate ambient temperature and pressure superconductor. However, from both an experimental and theoretical perspective, these claims are largely unsubstantiated. To this end, our synthesis and subsequent analysis of an LK-99 sample reveals a multiphase material that does not exhibit high-temperature superconductivity. We study the structure of this phase with single-crystal X-ray diffraction (SXRD) and find a structure consistent with doped Pb10(PO4)6(OH)2. However, the material is transparent which rules out a superconducting nature. From ab initio defect formation energy calculations, we find that the material likely hosts OH− anions, rather than divalent O2− anions, within the hexagonal channels and that Cu substitution is highly thermodynamically disfavored. Phonon spectra on the equilibrium structures reveal numerous unstable phonon modes. Together, these calculations suggest it is doubtful that Cu enters the structure in meaningful concentrations, despite initial attempts to model LK-99 in this way. However for the sake of completeness, we perform ab initio calculations of the topology, quantum geometry, and Wannier function localization in the Cu-dominated flat bands of four separate doped structures. In all cases, we find they are atomically localized by irreps, Wilson loops, and the Fubini-Study metric. It is unlikely that such bands can support strong superfluidity, and instead are susceptible to ferromagnetism (or out-of-plane antiferromagnetism) at low temperatures, which we find in ab initio studies. In sum, Pb9Cu(PO4)6(OH)2 could more likely be a magnet, rather than an ambient temperature and pressure superconductor.

[2308.05143] Pb$_9$Cu(PO4)$_6$(OH)$_2$: Phonon bands, Localized Flat Band Magnetism, Models, and Chemical Analysis

Unlocking the Potential of Quantum Computing: Exploring the World of Quantum Technology

Quantum computing is a revolutionary technology that promises to transform our world in ways that were once unimaginable. While traditional computers operate using classical bits that store information as either 0 or 1, quantum computers use qubits that can exist in a superposition of both states at the same time. This allows quantum computers to perform certain calculations much faster than classical computers, unlocking new possibilities for everything from cryptography and machine learning to drug discovery and materials science.

One of the most exciting applications of quantum computing is in the field of cryptography. Quantum computers are uniquely suited to break the encryption that currently secures many of our online transactions and communications. This has led to a race to develop new quantum-resistant encryption methods, and has also sparked interest in the development of so-called “quantum key distribution” systems that use the principles of quantum mechanics to securely share cryptographic keys.

Another area where quantum computing is showing great promise is in machine learning. Quantum computers are particularly well-suited to performing certain types of optimization problems, such as finding the shortest route between a large number of points. This has led to the development of quantum machine learning algorithms that could have applications in everything from logistics and supply chain management to personalized medicine.

In addition to these applications, quantum computing is also expected to have a major impact in fields such as finance, energy, and materials science. For example, quantum computers could be used to simulate complex financial models more accurately, leading to better investment decisions. They could also be used to design new materials with desirable properties, such as superconductors that could revolutionize the way we transmit electricity.

Despite the tremendous potential of quantum computing, there are still many challenges that need to be overcome before it becomes a mainstream technology. One of the biggest challenges is developing qubits that are both reliable and scalable. There are currently several different approaches being explored, including superconducting circuits, ion traps, and topological qubits.

Another challenge is developing the software and algorithms needed to program quantum computers. Because quantum computers are so different from classical computers, programming them requires a fundamentally different approach. This has led to the development of new programming languages and tools specifically designed for quantum computing.

In conclusion, quantum computing is a rapidly evolving field with the potential to transform our world in ways we can only begin to imagine. While there are still many challenges to overcome, the progress being made in both hardware and software is extremely promising, and it is likely that we will continue to see significant advancements in this field in the coming years.

Get More insights on this:https://www.persistencemarketresearch.com/market-research/quantum-computing-market.asp

Grain-boundary topological superconductor

http://dlvr.it/SvD5gH