aceSustainable Materials for Reducing the Environmental Footprint of Artificial Intelligence Data Centers in the United States
Artificial intelligence (AI) is expanding data-centre infrastructure in the United States, increasing demand for electricity, cooling water, semiconductor materials and electronic equipment. This review examines how sustainable materials and integrated engineering strategies may reduce environmental pressures across the AI data-centre life cycle. It considers operational energy demand, greenhouse-gas emissions, direct and indirect water consumption, critical-material requirements, thermal management, renewable-e…
Improving one environmental metric in AI data centers can worsen others across the energy, water and carbon nexus, so no single material or technology resolves the interdependent impacts.
The source describes options that 'may reduce' environmental pressures and says cooling choices 'require careful assessment', so it offers no measured outcomes for actual facilities.
Evidence
- Peer-reviewedJournal of Materials Science Research and Reviews2026-10-16
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Truvace Impact Record TRV-2026-1753, v1: “Sustainable Materials for Reducing the Environmental Footprint of Artificial Intelligence Data Centers in the United States.” Truvace, 2026-10-17. /record/TRV-2026-1753 (accessed at citation time). sha256 d03e691c8626dcf6…
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