Sustainable 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…

Sustainable Materials for Reducing the Environmental Footprint of Artificial Intelligence Data Centers in the United States
Final Dome Added to Artemis IV Liquid Oxygen Tank (MAF 20260511 CS4 LoxAftDomeLift05) by NASA Marshall Space Flight Center / NASA/Michael DeMocker. Public domain

In brief

A review published in 2026 examines how sustainable materials and integrated engineering could lessen the environmental pressure from AI data centers in the United States. It surveys the life cycle, from operating energy and emissions to water use, critical materials, cooling, storage and end-of-life equipment.

The review matters because AI-driven expansion is raising demand for electricity, cooling water and hardware, and fixes in one area can shift burdens to another. It is a conceptual assessment, so it does not quantify how much any option would actually cut impacts at real facilities.

Main points

  1. AI is expanding US data-center infrastructure, raising demand for electricity, cooling water, semiconductor materials and electronic equipment.
  2. Thermal materials such as ceramics, composites and phase-change materials can support heat transfer and temperature control.
  3. Direct-to-chip and immersion cooling suit high-density computing but need checks on compatibility, leakage, toxicity, durability and recyclability.
  4. The review calls for life-cycle assessment, transparent facility-level reporting and responsible material sourcing.

The problem

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 rundown

On energy, the review pairs renewable electricity with storage options including supercapacitors, lithium-based batteries, redox-flow systems, hydrogen and thermal storage, choosing among them by the timescale of power demand.

For embodied impacts and e-waste, it points to modular design, longer server service life, repair, component reuse and recovery of critical materials as ways to reduce burdens.

It concludes that materials engineering, electricity supply, cooling design and circular management must be coordinated, because trade-offs arise across the energy-water-carbon nexus.

The debate