AI & the Environment

Thermoregulatory materials: the role of artificial intelligence in combating urban heat

In the face of climate change, cities are particularly vulnerable to heat waves, which are exacerbated by the urban heat island effect. Traditional building materials (asphalt, concrete, glass) absorb heat and contribute to raising ambient temperatures by several degrees1. Air conditioning, in turn, increases energy demand and exacerbates greenhouse gas emissions.

In this context, so-called “thermoregulatory” materials are emerging as a promising structural solution. Their accelerated development is now being driven by an unexpected factor: artificial intelligence.

Thermoregulatory materials are designed to reduce heat transfer between the exterior and interior of a building without consuming electricity. They are sometimes inspired by the natural properties of certain living organisms (bio-inspiration) or make use of complex physical phenomena (spectral reflectance, thermal emissivity).

Recent innovations include:

  • paints that reflect up to 98% of solar radiation,
  • adaptive coatings capable of changing their properties depending on the temperature,
  • nanocomposite structures that modulate thermal conductivity.

These materials are being tested on roofs, walls, and even road surfaces. They promise to lower indoor temperatures by up to 5°C, with a significant impact on comfort and energy consumption.

The development of these complex materials is greatly accelerated by artificial intelligence2. Researchers use machine learning to:

  • predict the thermal properties of new material combinations,
  • optimize structures at the nano- and micro-scale,
  • model thermal behavior across multiple seasons or climate zones,
  • reduce prototyping time through inverse simulation and generative algorithms.

Databases containing thousands of configurations are analyzed by AI, which identifies those that offer the best balance between solar reflection, durability, and architectural integration.

The adoption of these materials could significantly lower urban temperatures, mitigating heat waves and reducing the need for air conditioning. It also leads to a transformation in professional practices:

  • Architects will need to incorporate dynamic thermal criteria from the design phase onward.
  • Materials engineers will work more closely with data scientists.
  • Urban planners will need to develop passive cooling strategies at the neighborhood level.

AI is thus becoming an integral part of the construction industry’s value chain, creating a need for new hybrid skills.

As with any technological development driven by AI, several precautions are necessary:

  • Safety: Materials must meet standards for strength, fire resistance, and toxicity.
  • Life cycle: sustainability and recyclability must be planned for3.
  • Legal framework: Certifications and labels will need to evolve to incorporate “AI-designed” materials.

It is also important to ensure that these innovations do not create new inequalities in access to energy efficiency.

The combination of adaptive materials and artificial intelligence opens up ambitious possibilities:

  • buildings capable of adjusting their thermal response,
  • neighborhoods where the materials used interact with their surroundings,
  • urban planning that incorporates AI simulation in the early stages of decision-making.

This trend heralds a new generation of cities that are more resilient, energy-efficient, and adaptable, where AI becomes an ally in both energy efficiency and indoor climate comfort4.

1. Nature Communications. (2023). A passive cooling paint with superior solar reflectance.
https://www.nature.com/

2. MIT News. (2024). How AI is speeding up materials discovery.
https://news.mit.edu/

3. European Commission. (2024). Sustainable Construction and Energy Performance Regulation.
https://ec.europa.eu/

4. Science Advances. (2025). Thermal metamaterials for urban heat mitigation.
https://www.science.org//

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