SIBUR increases investments in science, ecology, and digitalization
SIBUR, a leading producer of polymers and rubbers in Russia, has published its integrated annual report for 2025, presenting results across three key areas: environmental responsibility, research and development (R&D), and digital transformation.
Ecology
Environmental responsibility is embedded within all aspects of SIBUR’s operations. The company has been advancing sustainable production by implementing best available technologies and paying particular attention to ecosystem preservation.
For the climate, the Company is executing comprehensive greenhouse gas emission reduction projects. A priority focus is the development of a circular economy, through which SIBUR produces goods incorporating recycled materials.
SIBUR has carried out more than 100 environmental initiatives, reduced emissions by 395,000 tons of CO₂ equivalent, and built a carbon unit portfolio exceeding 12 million units. A third in-house solar power plant has been commissioned at the SIBUR PolyLab site.
R&D
SIBUR’s research and development investments have been growing at a twofold pace in recent years, reaching more than RUB 18 billion in 2025. By the globally accepted metric reflecting R&D investment intensity, SIBUR is on par with industry leaders at 1.7% of revenue.
The Company holds 447 active patents. Over the year, 91 new applications were filed, and 146 product solutions were created. Key projects include Russia’s first hexene production unit and the construction of a catalyst plant in Kazan. The R&D network has expanded to comprise nine centers.
Digital transformation
SIBUR views digitalization as a key driver of operational efficiency and technological independence. The cumulative economic effect of digital projects since 2018 has exceeded RUB 63 billion. More than 130 organizational projects were completed in 2025.
Artificial intelligence technologies are being actively deployed: large language models (LLM) assist in generating training materials, forecasting catalyst characteristics, and automating margin analysis.