This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 381–382 of 382 papers
Hoyas Sergio, Vinuesa Ricardo
This paper quantifies the global emission reduction potential from turbulence-informed design, estimating up to 6 GtCO2-eq per year (10% of global emissions). It highlights that turbulence-related inefficiencies in transport, energy convers…
Kshitij Bhatta, Muhammad Waseem, Mingzhe Liu +3
This paper proposes a digital twin framework for wood drying in desiccant-assisted heat pump (DAHP) systems. Combining high-fidelity physics models with multi-agent reinforcement learning (MARL), it reduces total energy consumption by 43.2%…
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