Scientists Discover How Correlated Disorder Boosts Superconductivity
Superconductivity is a unique state of matter in which electric current flows without any energy loss. In materials with defects, it typically emerges at very low temperatures and develops in several stages. An international team of scientists, including physicists from HSE MIEM, has demonstrated that when defects within a material are arranged in a specific pattern rather than randomly, superconductivity can occur at a higher temperature and extend throughout the entire material. This discovery could help develop superconductors that operate without the need for extreme cooling. The study has been published in Physical Review B.
Superconductivity is a state in which electric current flows through a material without any energy loss. In conventional conductors, part of the energy is converted into heat, but in superconductors, this does not occur—current flows freely and does not weaken. Today, superconductors are used in applications such as MRI machines, where superconducting coils generate strong magnetic fields. In the future, superconductors may also be integrated into systems that require lossless power transmission and high-speed signal processing. The challenge is that nearly all superconductors function only at temperatures below -140 °C, which limits their practical use. To make them more viable, physicists are working to raise their operating temperature and improve stability.
Researchers from the HSE MIEM Centre for Quantum Metamaterials, in collaboration with colleagues from MEPhI, MIPT, and the Federal University of Pernambuco, Brazil, have shown that superconductivity can be made more stable by controlling the placement of defects. Defects are deviations from a material’s ideal crystal lattice, such as excess or missing atoms, impurities, and distortions. They usually disrupt the movement of electrons and weaken superconductivity, but it is impossible to eliminate them entirely, especially in multicomponent materials. Rather than eliminating these imperfections, the scientists have proposed arranging them in a specific pattern. This type of defect distribution is known as correlated disorder.
Alexei Vagov
'Imagine a crowd of people moving chaotically in different directions—that’s a classic example of disorder. Now imagine the same crowd moving in a complex but coordinated pattern, like a mass dance—that illustrates correlated disorder,' says Alexei Vagov, Professor at the HSE Tikhonov Moscow Institute of Electronics and Mathematics. 'In superconductors, it turns out that this kind of order within disorder causes defects to actually enhance superconductivity.'
In materials with defects, superconductivity typically develops in two stages. First, isolated regions appear where superconductivity begins to emerge. Then, as the temperature drops, these regions connect, allowing current to flow throughout the entire sample. Scientists have modelled a two-dimensional superconductor with varying defect distributions—from random to correlated, where impurities are interconnected. The results show that when disorder in the material is coordinated rather than chaotic, the transition happens immediately: superconductivity emerges simultaneously throughout the entire system.
The scientists believe these findings could aid in the development of thin superconducting films, whose structures closely resemble the model used in the study. When synthesising such films, it is possible to control the placement of defects in advance, which is useful both for testing the theory and for creating materials with specified properties.
'Controlling the placement of defects at the microscopic level could enable the creation of superconductors that operate at much higher temperatures—potentially even at room temperature. This would transform superconductivity from a laboratory rarity into a technology used in everyday devices,' comments Alexei Vagov.
The study was conducted with support from the Ministry of Education and Science, Grant 075-15-2025-010, and HSE University's Basic Research Programme within the framework of the Centres of Excellence project.
See also:
Immersion in Second Language Environment Influences Bilinguals’ Perception of Emotions
Researchers at the Cognitive Health and Intelligence Centre at the HSE Institute for Cognitive Neuroscience have discovered how bilingual individuals process emotional words in their native (first) and non-native (second) languages. It was found that the link between word meaning and bodily sensations is weaker in a second language than in a first language. However, the more a person is immersed in a language environment, the smaller this difference becomes. The article has been published in Language, Cognition and Neuroscience.
HSE Students Among Winners of Yandex High-Tech Startup Accelerator
Yandex has announced the results of its Yandex AI Startup Lab accelerator, whose final round featured 12 IT projects. Over the course of three months, their creators—students and young entrepreneurs—worked alongside the company’s experts to develop their products. Four startups in digital marketing, medicine, and robotics were named the best, with their teams receiving cash prizes and cloud resource grants. Among them was Gradius, a startup founded by students from HSE University.
‘Any Real-Economy Company Can Use Our Products’
The HSE Centre for Financial Research and Data Analytics combines fundamental and applied work, including in areas unique to Russia such as the connection between sentiment in the media and social networks and financial markets. The HSE News Service spoke with the centre’s director, Professor Tamara Teplova, about its work.
Researchers Find More Effective Approach to Revealing Majorana Zero Modes in Superconductors
An international team of researchers, including physicists from HSE MIEM, has demonstrated that nonmagnetic impurities can help more accurately reveal Majorana zero modes—quantum states considered promising building blocks for quantum computing. The researchers found that these impurities shift the energy levels that typically obscure the Majorana signal, while leaving the mode itself largely unaffected, thereby making its spectral peak more distinct. The study has been published in Research.
New Development by HSE Scientists Helps Design Reliable Electronics Faster at a Lower Cost
Scientists from HSE MIEM have developed a new approach to modelling electrothermal processes in high-power electronic circuits on printed circuit boards (PCB). The method allows engineers to quickly and accurately predict how electronic components heat up during operation, helping prevent overheating and potential failures. The results have been published in Russian Microelectronics.
The Future of Cardiogenetics Lies in Artificial Intelligence
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a program capable of analysing regions of the human genome that were previously inaccessible for accurate interpretation in genetic testing. The program adapts large generative AI (GenAI) models for cardiogenetics to predict how specific mutations affect the function of individual genes.
'Where Accurate Prediction of the Outcome Is Impossible, Stochastic Methods Come into Play'
The Laboratory of Stochastic Analysis and its Applications at HSE University studies systems and events in which randomness plays a central role. The goal is to predict various phenomena and how they evolve over time. The HSE News Service interviewed the laboratory's head Vladimir Panov and its academic supervisor Valentin Konakov.
HSE Researchers: Young Russians Have Sufficient Knowledge About Money but Lack Money Management Skills
Adolescents and young adults in Russia today are well versed in financial terminology: they know what bank cards, loans, interest rates, and online payments are. However, as researchers at HSE University have found, real money-management skills remain poorly developed among most young people. The study ‘Financial Literacy, Financial Culture, and Financial Autonomy of Youth’ has been published in Monitoring of Public Opinion: Economic and Social Changes.
Why Weaker Competitors Give Up—and How to Keep Them in the Game
Anastasia Antsygina, Assistant Professor at HSE University’s Faculty of Economic Sciences, has developed a prize distribution model that maximises competitor engagement. She proposed revising the traditional ‘winner-takes-all’ approach and, in certain cases, offering a small reward even to those who have lost. According to her, this could increase participant motivation and make the competition more intense. The findings of her research were published in the Economic Theory journal.
HSE Researchers Compile Scientific Database for Studying Children’s Eating Habits
The database created at HSE University can serve as a foundation for studying children’s eating habits. This is outlined in the study ‘The Influence of Age, Gender, and Social-Role Factors on Children’s Compliance with Age-Based Nutritional Norms: An Experimental Study Using the Dish-I-Wish Web Application.’ The work has been carried out as part of the HSE Basic Research Programme and was presented at the XXVI April International Academic Conference named after Evgeny Yasin.