Integrated approaches that combine high-throughput experimentation, laboratory automation, and artificial intelligence have the potential to significantly accelerate the discovery of materials for sustainable technologies, including photovoltaics, energy storage, thermoelectrics, and catalysis. This symposium presents an overview of recent advances in such integrated methodologies for sustainable materials discovery. We highlight progress across the full pipeline, from hardware (e.g., robotic synthesis and characterization platforms) to software (e.g., optimization agents and large language models), and how these components contribute to accelerated discovery across diverse materials classes. Particular attention is given to strategies for addressing persistent challenges in closing the experimental loop, such as reliable sample transfer between stations (e.g., synthesis-to-characterization) and resolving geometry mismatches between synthesized samples and measurement requirements (e.g., powder outputs when pelletized samples are needed). By bringing together researchers from multiple disciplines, this symposium aims to foster cross-domain exchange and advance pathways for sustainable materials discovery