GX Research Hub · English

GX & Decarbonization Research

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.

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Showing 1181–1200 of 23595 papers

Peer-reviewedJournalEcological Engineering & Environmental Technology2026#CCUSDOI

Improving biomass yield in bubble column reactors: A review on cultivation, treatment, and applications of microalgae

Ahmed J. Abd, Shurooq T. Al-Humair, Riyadh S. Al-Mukhtar +4

This review examines bubble column reactors (BCRs) for microalgae cultivation, highlighting their low energy consumption and shear stress, and strategies to improve productivity such as lighting optimization and wastewater use. BCRs offer p…

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Peer-reviewed🇨🇳 ChinaJournalJournal of the European Ceramic Society2026#OtherDOI

Carbon nanotube-reinforced 3D-printed porous geopolymer derived from alkali-activated coal gangue and fly ash: High-temperature phase evolution and mechanical properties

Shu Yan, Xupeng Zhai, Mi Zhou +3

This study investigates carbon nanotube-reinforced 3D-printed porous geopolymers derived from alkali-activated coal gangue and fly ash, focusing on high-temperature phase evolution and mechanical properties. The work demonstrates potential …

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Peer-reviewed🇨🇳 ChinaJournalEnvironmental Science & Technology2026#AI × ESGDOI

WaterMAP: A ScalableMachine Learning Framework forEmission-Factor-Derived Spatiotemporal GHG Prediction and Mitigationin Wastewater Treatment Plants

Jinqi Jiang, Zhijing Wu, guosen zhang +9

WaterMAP is a scalable ML framework for predicting GHG emissions from wastewater treatment plants. Using data from 5155 Chinese WWTPs, it estimates Scope 1/2/3 emissions and suggests 9.6-34.0% reduction potential by 2060.

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