RUDN nanotechnologist creates asphalt modifier from old tires and rubber
Car tires can be recycled for secondary use. For example, the addition of crumb rubber increases the life of asphalt. Typically, tires are shredded to particles as small as a few millimeters. Further shredding is too energy-intensive. However, a new method has emerged — high-temperature shear shredding. It takes place with the help of a rotary disperser. The essence of its work is a strong compression
“Among all possible applications of crumb rubber from worn out tires, the most interesting one is the use in road pavement. Crumb rubber as a modifier of bitumen and asphalt concrete mixtures increases their service life and has great potential in the road industry. This combines the problems of recycling used tires and increasing the durability of roads. In this way it is possible to reduce the consumption of primary natural resources,” — Alexander Vecher, PhD in Biology, Deputy Director of the Nanotechnology Research Center at RUDN.
Nanotechnologists prepared rubber crumbs from car tires and then ground them into powder together with butadiene-styrene rubber on a rotary disperser. The powder was added to hot bitumen heated to a temperature of 120-180℃ and stirred for
RUDN nanotechnologists have studied rubber particles before and after their interaction with hot bitumen using scanning electron microscopy. Grinding together with butadiene-styrene rubber leads to the formation of outwardly homogeneous hybrid particles. After a minute of stirring in hot bitumen, the powder particles split into
“Considering that one minute of mixing time corresponds to the technology of obtaining various asphalt concrete mixtures, it can be recommended to use additive powders in a ‘dry’ way, i.e. to introduce them into the asphalt concrete mixture during its production. This will be more economical. In further research we will conduct rheological studies of bitumen with modifiers,” — Alexander Vecher.
The results were published in the journal Polymers.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.