Smart and renewable building materials for sustainable architecture: properties, applications, challenges, future perspectives, systematic review
Abstract
Rapid urbanization, increasing energy consumption, natural resource depletion, and intensifying climate change impacts have positioned the construction industry as a critical sector for sustainable development. Buildings account for substantial global energy consumption, greenhouse gas emissions, and resource utilization, making advanced building materials with smart functionalities and renewable origins essential for reducing environmental impacts while enhancing performance. Smart materials respond to external stimuli, including temperature, humidity, light, mechanical stress, and electric fields, by modifying their physical or chemical properties in controlled ways. Renewable building materials, derived primarily from renewable resources or bio-based feedstocks, contribute to reducing embodied carbon, energy consumption, and environmental pollution. Integrating smart and renewable materials can improve building durability and service life while reducing energy demand, maintenance costs, and carbon emissions. Their convergence with emerging technologies, including the Internet of Things, Building Information Modeling, Artificial Intelligence, and Digital Twin technology, creates opportunities for intelligent, energy-efficient, and low-carbon buildings. This study employs a systematic literature review to examine recent scientific advances in smart and renewable building materials, analyzing their main categories, functional characteristics, applications, advantages, limitations, and future trends. Findings indicate that self-healing concrete, self-sensing concrete, shape memory alloys, smart glazing systems, phase change materials, engineered wood, bio-based composites, and building-integrated photovoltaic systems can enhance structural performance and support sustainable architecture. However, high initial costs, insufficient implementation standards, technical complexity, limited long-term performance data, and constraints in large-scale manufacturing remain significant barriers to their widespread adoption, highlighting the need for further research, standardization, technological development, and interdisciplinary collaboration.