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Beyond PUE: An integrated scenario assessment of electricity, cooling, polymer–elastomer demand, carbon, and circularity in AI data centers
- Truvace record
- TRV-2026-2498raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Benchmark or lab evaluation
- Sources
- 1 sourcePeer-reviewed
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- 439960c38597…check it
Artificial intelligence is transforming data centers into coupled energy–cooling–material systems that cannot be assessed adequately using electricity demand or power usage effectiveness (PUE) alone. This study develops a scenario-based screening framework for 2024–2035 that links institutional electricity pathways, H100 node-level calibration, facility-load decomposition, air/direct-to-chip/immersion cooling transitions, polymer–elastomer requirements, operational carbon, circularity, and uncertainty. Global el…
The problem
A scenario study projects global AI data-center electricity demand rising from 416 TWh in 2024 to 707–1,719 TWh in 2035, with efficiency gains (PUE of 1.13–1.22) outweighed by infrastructure growth.
What this doesn’t fix
The figures are scenario-based screening estimates for 2024–2035, and uncertainty in material coefficients widens the plastic projections considerably.
Sources
1 on file- Results in Engineeringdoi:10.1016/j.rineng.2026.113927
Cite this record
v1Truvace Impact Record TRV-2026-2498, v1: “Beyond PUE: An integrated scenario assessment of electricity, cooling, polymer–elastomer demand, carbon, and circularity in AI data centers.” Truvace, 2026-11-12. /record/TRV-2026-2498 (accessed on the day you copy it). sha256 439960c3859736f7…
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