Physicists Propose New Mechanism to Enhance Superconductivity with 'Quantum Glue'
A team of researchers, including scientists from HSE MIEM, has demonstrated that defects in a material can enhance, rather than hinder, superconductivity. This occurs through interaction between defective and cleaner regions, which creates a 'quantum glue'—a uniform component that binds distinct superconducting regions into a single network. Calculations confirm that this mechanism could aid in developing superconductors that operate at higher temperatures. The study has been published in Communications Physics.
Superconductivity is a state in which electric current flows through a material without resistance, losing no energy as heat. In ordinary conductors, electrons move independently and lose energy through collisions with atoms and impurities. In superconductors, however, electrons form Cooper pairs and move in unison, enabling current to flow without loss. Thanks to this property, superconductors are used to create powerful magnets, medical MRI scanners, and particle accelerators, and they also hold promise for developing new types of computing devices.
The challenge is that superconductivity usually occurs only at very low temperatures and is easily disrupted by impurities and defects in the material. These defects fragment superconductivity into isolated regions that fail to connect. Paradoxically, however, such disordered areas can also support the formation of Cooper pairs at higher temperatures. This creates a contradiction: structural disorder can locally enhance superconductivity, yet at the same time prevents it from spreading throughout the entire sample.
A team of researchers from HSE University, the Moscow Centre for Advanced Studies, and the Federal University of Pernambuco has shown that this challenge can be addressed by combining defective ('dirty') and clean subsystems. The team studied a two-band model in which one subsystem is highly disordered: superconductivity emerges there at higher temperatures, but only in isolated regions. The other subsystem remains clean, where superconductivity is weaker but provides connectivity. When the two are combined, a component arises that acts as a 'quantum glue,' linking the isolated islands and enabling current to flow through the entire sample at elevated temperatures.
Alexei Vagov
'Our calculations show that when defective and clean regions are properly connected, the material exhibits both a higher superconducting transition temperature and the ability to carry current without resistance. While disorder usually destroys this effect, we observed the opposite: defects can serve as a resource for creating more stable superconductors that operate at higher temperatures,' explains Alexey Vagov, Professor at HSE MIEM and co-author of the study.
Calculations confirm that this approach is effective for various types of disorder, ranging from random impurities to specially engineered superlattices. It is particularly promising for multilayer materials, where clean and disordered layers can be alternated; for compounds based on magnesium and boron (MgB₂), in which one electronic band enhances local superconductivity while the other facilitates current flow; and for materials with flat electronic bands, where electron pairing occurs more readily. Graphene- and graphite-based systems are also considered promising, as regular superstructures can form that alter electronic properties and promote stronger superconductivity. In the future, this could enable the development of materials in which defects and impurities do not hinder, but rather enhance, superconductivity.
The study was conducted with support from the Russian Science Foundation (Project 075-15-2025-010) and the HSE Basic Research Programme, using the university's HPC cluster.
See also:
Scientists Test Asymmetry Between Matter and Antimatter
An international team, including scientists from HSE University, has collected and analysed data from dozens of experiments on charm mixing—the process in which an unstable charm meson oscillates between its particle and antiparticle states. These oscillations were observed only four times per thousand decays, fully consistent with the predictions of the Standard Model. This indicates that no signs of new physics have yet been detected in these processes, and if unknown particles do exist, they are likely too heavy to be observed with current equipment. The paper has been published in Physical Review D.
HSE Scientists Reveal What Drives Public Trust in Science
Researchers at HSE ISSEK have analysed the level of trust in scientific knowledge in Russian society and the factors shaping attitudes and perceptions. It was found that trust in science depends more on everyday experience, social expectations, and the perceived promises of science than on objective knowledge. The article has been published in Universe of Russia.
Institute for Robotics Systems Established at HSE University
As decided by the HSE University Academic Council, a new Institute for Robotics Systems will be established at HSE, and with a strong fundamental base. It will cooperate with relevant departments across the university and engage students and doctoral candidates in research and development (R&D). First Vice Rector of HSE University and Director of the Institute for Statistical Studies and Economics of Knowledge, Leonid Gokhberg, discussed the expected practical results and the framework for cooperation with an industrial partner.
Scientists Uncover Why Consumers Are Reluctant to Pay for Sugar-Free Products
Researchers at the HSE Institute for Cognitive Neuroscience have investigated how 'sugar-free' labelling affects consumers’ willingness to pay for such products. It was found that the label has little impact on the products’ appeal due to a trade-off between sweetness and healthiness: on the one hand, the label can deter consumers by implying an inferior taste, while on the other, it signals potential health benefits. The study findings have been published in Frontiers in Nutrition.
HSE Tops Ranking of Universities Participating in Priority 2030 Programme
The Russian Ministry of Science and Higher Education has published an updated list of participants in the Priority 2030 programme. A total of 106 universities will receive support this year. HSE University was included in the first group and topped the ranking.
HSE Psycholinguists Launch Digital Tool to Spot Dyslexia in Children
Specialists from HSE University's Centre for Language and Brain have introduced LexiMetr, a new digital tool for diagnosing dyslexia in primary school students. This is the first standardised application in Russia that enables fast and reliable assessment of children’s reading skills to identify dyslexia or the risk of developing it. The application is available on the RuStore platform and runs on Android tablets.
HSE Scientists Optimise Training of Generative Flow Networks
Researchers at the HSE Faculty of Computer Science have optimised the training method for generative flow neural networks to handle unstructured tasks, which could make the search for new drugs more efficient. The results of their work were presented at ICLR 2025, one of the world’s leading conferences on machine learning. The paper is available at Arxiv.org.
Neural Network Trained to Predict Crises in Russian Stock Market
Economists from HSE University have developed a neural network model that can predict the onset of a short-term stock market crisis with over 83% accuracy, one day in advance. The model performs well even on complex, imbalanced data and incorporates not only economic indicators but also investor sentiment. The paper by Tamara Teplova, Maksim Fayzulin, and Aleksei Kurkin from the Centre for Financial Research and Data Analytics at the HSE Faculty of Economic Sciences has been published in Socio-Economic Planning Sciences.
'Even among Geniuses, Luck Plays a Role in Winning a Nobel Prize'
Denis Bodrov studies particle physics and works at one of the four electron–positron colliders in the world. In this interview with the HSE Young Scientists project, he talks about his efforts to go beyond the Standard Model, discusses tau leptons, and shares his affection for Moscow.
Larger Groups of Students Use AI More Effectively in Learning
Researchers at the Institute of Education and the Faculty of Economic Sciences at HSE University have studied what factors determine the success of student group projects when they are completed with the help of artificial intelligence (AI). Their findings suggest that, in addition to the knowledge level of the team members, the size of the group also plays a significant role—the larger it is, the more efficient the process becomes. The study was published in Innovations in Education and Teaching International.