MIT Discovers a Superconducting Magnet: A Chiral Breakthrough in Graphene Physics

MIT chiral superconductor graphene

Superconductors and magnets have long been considered incompatible—until now. In a remarkable discovery published in Nature, researchers at MIT have identified a material that defies this dogma: a “chiral superconductor” that conducts electricity with zero resistance and exhibits intrinsic magnetic behavior.

What’s even more astonishing? This exotic quantum phase has been found in a seemingly mundane material—graphite, the same substance in your pencil lead. The MIT team demonstrated that when graphene layers are stacked in a special “rhombohedral” pattern, they exhibit superconductivity and magnetism—simultaneously.

Graphene’s Chiral Surprise

Graphite is composed of millions of stacked graphene sheets. Occasionally, these layers deviate from their typical alignment, forming a staircase-like structure called rhombohedral stacking. The MIT team focused on isolating and testing five-layer rhombohedral graphene structures placed on hexagonal boron nitride substrates.

At ultracold temperatures (~300 millikelvins), they observed that electrical current passed through the material without any resistance—a hallmark of superconductivity. But then came the twist: applying a magnetic field caused the material to switch between two superconducting states, a behavior akin to a magnetic hysteresis loop.

“This is the first time we’ve observed a superconductor that also acts like a magnet with such direct evidence,” said Prof. Long Ju, senior author of the study. “It’s a completely counterintuitive phenomenon.”

From Cooper Pairs to Orbital Magnetism

In conventional superconductors, Cooper pairs of electrons form and flow without resistance. They typically cancel each other’s momentum, producing zero net magnetic effect. In contrast, the MIT researchers propose that in their graphene configuration, electrons pair while occupying the same momentum “valley,” producing a superconducting state with built-in orbital angular momentum.

This type of material is now being classified as a chiral superconductor—one that breaks time-reversal symmetry and may carry quantized angular momentum. Such states are not just novel but may also serve as topological superconductors, offering fault-tolerant platforms for quantum computing.

Implications and Future Research

Key discoveries from the study include:

  • ⚛️ Discovery of magnetic superconductivity in a simple carbon-based system
  • 🌀 Identification of a chiral superconducting state through magnetic field response and resistance switching
  • 🔍 Potential use as a platform for topological qubits in robust quantum information systems

“Everything we’ve found in this material has been unexpected,” said Dr. Zhengguang Lu, now at Florida State University. “But because it’s a simple system, we think we can unravel the deep physics involved.”

The team’s discovery paves the way for broader exploration of exotic phases in layered materials—and could eventually redefine what we expect from superconductors in electronic and quantum applications.

🔗 Original article citation: MIT News – MIT physicists discover new type of superconductor that is also a magnet (May 22, 2025)

📣 Promote Your Scientific Innovations Effectively

Are you leading research in quantum materials, condensed matter, or applied physics? Let QSComputing help you communicate your breakthroughs to the world with expert scientific social media marketing and communication services.

📎 Discover our consultancy offerings

💬 Sponsored ad space is also available within this blog. Fully flexible formats and pricing—contact us to feature your innovation here!

Comments

Post a Comment

Popular posts from this blog

AI Tools for Chemistry: The ‘Death’ of DFT or the Beginning of a New Computational Era?

Image
For decades, Density Functional Theory (DFT) has been the workhorse of quantum chemistry and materials modeling. From predicting electronic structures to optimizing molecular geometries, DFT has powered countless breakthroughs in fields as diverse as catalysis, materials design, and condensed matter physics. But recent announcements in the scientific community have caused ripples: is DFT “dead” — or is this simply the dawn of a new computational era powered by artificial intelligence ? The Shock of Declaring a Field “Dead” The provocative statement came during the EuChemS Inorganic Chemistry Conference , where theoretical chemist Markus Reiher announced the “death of DFT.” His claim wasn’t about obsolescence in a literal sense, but about a paradigm shift: AI models can now deliver DFT-level accuracy at a fraction of the cost , fundamentally changing how chemists approach molecular modeling. This echoes previous moments in scientific history where disruptive technologi...
Read more

Quantum Chemistry Meets AI: A New Era for Molecular Machine Learning

Image
In a powerful leap forward for computational chemistry and materials design, researchers from Carnegie Mellon University have developed a new kind of molecular machine learning model—one that goes beyond simplistic molecular graphs and integrates fundamental principles of quantum chemistry. Their work, published in Nature Machine Intelligence , could radically enhance our ability to predict chemical behavior, optimize catalysts, and discover new drugs, all while using less data and gaining more scientific insight. The Problem: Traditional Molecular Representations Fall Short Molecular machine learning (ML) models underpin key processes in drug discovery, materials science, and catalysis. However, most existing models use simplified representations such as SMILES strings, 2D graphs, or coordinate matrices. These techniques often lack the quantum-chemical information that governs how molecules truly behave—particularly electron interactions that define reactivity, stability, and...
Read more

Revolutionize Your Materials R&D with PWmat

Image
GPU-Accelerated Simulation Software for Cutting-Edge Research Are you working in quantum materials , semiconductors , or energy materials ? Then it’s time to supercharge your research with PWmat by Lonxun Quantum – a leader in GPU-accelerated first-principles simulation software designed to meet the evolving demands of advanced materials science. PWmat offers a powerful suite of high-performance computing tools specifically optimized for modern NVIDIA GPUs , helping researchers: ✅ Simulate complex materials at quantum scale ✅ Accelerate DFT calculations ✅ Reduce time-to-result drastically ✅ Optimize large-scale simulations with intuitive workflows Whether you're in academia, industry, or a national lab , PWmat is trusted by institutions and scientists across the globe pushing the boundaries of what’s possible in computational materials science. 🎁 Clai...
Read more