Scientists Develop AI Tool for Designing Novel Materials
An international team of scientists, including researchers from HSE University, has developed a new generative model called the Wyckoff Transformer (WyFormer) for creating symmetrical crystal structures. The neural network will make it possible to design materials with specified properties for use in semiconductors, solar panels, medical devices, and other high-tech applications. The scientists will present their work at ICML, a leading international conference on machine learning, on July 15 in Vancouver. A preprint of the paper is available on arxiv.org, with the code and data released under an open-source license.
New materials form the foundation of modern technologies, from electronics to medicine. Thanks to AI, the development timeline for novel materials has been reduced from decades to just a few months. However, scientists must not only rapidly generate new compounds but also accurately predict their properties—such as whether the material will conduct electricity or be durable.
The properties of a material are primarily determined by the internal symmetry of the crystals that compose nearly all solid substances. However, many modern generative models do not explicitly account for symmetry.
Researchers from HSE University, the National University of Singapore, Nanyang Technological University, and Constructor University have developed the Wyckoff Transformer (WyFormer), a novel machine-learning algorithm that rapidly generates materials with specified symmetries and predicts their stability and performance.
The model is based on representing a crystal using Wyckoff positions—mathematically precise coordinates that specify where atoms can be located based on crystal lattice symmetry. This approach enables a concise and universal representation of the structure
'Imagine your reflection in a mirror. While our face is symmetrical, some features come in pairs belonging to two distinct classes, such as the right and left eyes. Other features belong to a single class, like the tip of the nose. In mathematical terms, the nose corresponds to Wyckoff position A, while the eye corresponds to Wyckoff position B. In other words, Wyckoff positions are the key points that define symmetry and enable us to recognise a human face in the mirror,' explains Ignat Romanov, co-author of the paper and Junior Research Fellow at the Faculty of Computer Science, HSE University.
The new model was trained on an open database of real materials from the Materials Project. The AI leverages a transformer architecture to generate novel crystal synthesis recipes that automatically conform to symmetry rules.
'There are countless ways atoms can combine. Trying to find useful combinations and design new materials without understanding their symmetry rules is like sticking LEGO blocks together without a plan. While such improvisation may occasionally produce interesting results, it often leads to unstable structures,' says Nikita Kazeev, co-author of the paper, Research Fellow at the Institute for Functional Intelligent Materials (I-FIM), National University of Singapore, and graduate of the HSE Faculty of Computer Science. 'Our AI tool has effectively learned from all good LEGO instructions—it knows how to generate models that are stable, aesthetically pleasing, and functional. Returning from the metaphor to materials, it understands the full range of symmetry options and can predict a material's properties even without knowing the exact atomic positions within the unit cell.'
Compared to other models, WyFormer produces a higher proportion of stable and unique structures, generates crystals with more accurate symmetry, and achieves a generation rate an order of magnitude faster.
The researchers plan to apply the model to develop practical materials for solid electrolytes and materials with specified thermal conductivity.
Ignat Romanov
See also:
HSE Develops App for Assessing Phonological Processing in Children
Researchers at the HSE Centre for Language and Brain have developed a new digital tool for assessing children's phonological processing skills—the ZARYA (Sound Analysis of the Russian Language) test battery. It is the first standardised application in Russia designed to provide a fast and reliable assessment of children's ability to distinguish speech sounds, retain them in working memory, and perform phonemic analysis. The app runs on Android tablets and smartphones and is available for download from RuStore. Details of the test validation have been published in the Journal of Speech, Language, and Hearing Research.
Researchers Discover How Spelling Errors Slow Down Reading in Russian
Psycholinguists from the Centre for Language and Brain at HSE University–St Petersburg have shown that words that are frequently misspelled are processed more slowly by readers, even when presented with the correct spelling. The researchers confirmed this effect for the first time using Russian-language materials and found that response speed is most strongly linked to how confidently individuals can distinguish the correct spelling of a word from an incorrect one. The study has been published in The Mental Lexicon.
Scientists Discover Why Europium 'Misbehaves'
Europium is a rare-earth metal responsible for the pure red glow in displays and other luminescent materials. For a long time, however, it refused to emit light when surrounded by certain organic molecules known as acylpyrazolone ligands. Chemists have now uncovered the reason: in europium complexes with these ligands, a 'black window' appears—a charge-transfer state in which the energy absorbed by the ligand is dissipated as heat rather than emitted as light. Understanding this mechanism opens the way to designing more efficient red-emitting materials for displays, fluorescent thermometers, and chemical sensors. The results have been published in Dalton Transactions.
HSE Economists Reveal How the Wage Gap Emerges Among Vocational School Graduates
HSE researchers examined the careers of 600,000 graduates of Russian secondary vocational education programmes and found that at the start of their careers, the gender wage gap reaches 23%, doubling after three years. This disparity is largely due to male and female students choosing different occupations when enrolling in vocational schools. These were the findings made by Sergey Roshchin, Natalya Yemelina, and Ksenia Rozhkova from of the HSE Faculty of Economic Sciences. The article has been published in Educational Studies.
HSE Researchers Make Aldehydes Perform Dual Function
Chemists from HSE University have discovered a way to carry out a reductive addition reaction without using an external reducing agent. Instead, the required 'resource' is supplied by the aldehyde itself, one of the reaction participants. This approach helps prevent unwanted side reactions, reduces toxicity, and simplifies the production and synthesis of organic molecules, including those used in the manufacture of medicines. The study has been published in Journal of Catalysis.
HSE Scientists Explain Why Findings in Autism Research Differ
Researchers from the Cognitive Health and Intelligence Centre at HSE University conducted the first-ever systematic review of studies on the specifics of emotion-from-motion perception in autism. The review showed that differences found between autistic and non-autistic individuals are largely associated with the experimental design and the types of tasks given to study participants. The review findings have been published in Research in Autism.
Tremors: Scientists Develop Method for Real-Time Tracking of Hazardous Underground Vibrations
Researchers from HSE MIEM and IPKON RAS have developed a new mathematical monitoring model that can identify the source of hazardous underground vibrations in real time. The technology could help reduce the risk of damage to buildings, roads, and other infrastructure located near quarries and mining sites. The paper has been published in Russian Mining Industry.
Education in a Changing World: Russian–Chinese Dialogue in Beijing
How are universities, vocational education systems, and researcher training programmes evolving in response to new challenges? These questions were at the heart of the international forum ‘Reconfiguring Education in a Changing World: Russia–China Dialogues on Higher Education, Skills, and Research Training’, held in China in mid-June. The event was jointly organised by the HSE Institute of Education and the Graduate School of Education of Peking University, which hosted the forum on its campus.
HSE Researchers Determine Which Internet Users Are More Likely to Fact-Check
Researchers at HSE University examined the strategies employed by Russian internet users to verify unreliable information and the factors that motivate them to do so. The study found that more than half of users who encounter potentially false information online attempt to verify it by locating the original source. The likelihood of fact-checking is influenced by several factors, including age, place of residence, social status, information literacy skills, and the use of AI. The findings have been published in Monitoring of Public Opinion: Economic and Social Changes.
Tabular Data Anonymisation Solution for Safe Use in AI Systems Developed at HSE University
The AI and Digital Science Institute at the HSE Faculty of Computer Science has developed a tabular data anonymisation service designed to prepare corporate datasets for use in analytics and AI applications. The solution can identify personal data in structured datasets, apply consistent and reproducible anonymisation rules, and generate the artifacts required for quality control, auditing, and subsequent use of data in secure environments.