GX Research Hub · English

GX & Decarbonization Research

This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 14 contributing 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 2481–2500 of 37257 papers

Peer-reviewedJournalJournal of Earth and Environmental Sciences Research2026#CCUSDOI

From Oil Palm Residues to Engineered Carbon: Biochar and Activated Carbon Pathways for Carbon Removal, Environmental Purification, and a Circular Bioeconomy

Loso Judijanto

A qualitative review of whether oil-palm residues (EFB, PKS, fibre, fronds, trunks) can become feedstocks for biochar and engineered activated carbon, synthesizing literature from 2020 onward. Feedstock composition and thermochemical condit…

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🇺🇸 USAJournalZenodo (CERN European Organization for Nuclear Research)2026#Carbon AccountingDOI

Carbon-Falcon

Linda

UCST-CCIF is an open-source toolkit linking enterprise Scope 1–3 GHG inventories with process-level ecosystem carbon flux models across land, freshwater, and coastal pools. It ships six MVP kernels (soil carbon, blue carbon, rice-paddy CH₄,…

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Peer-reviewed🇨🇳 ChinaJournalActa Oceanologica Sinica2026#Climate ScienceDOI

Vulnerability assessment of coastal blue carbon ecosystems along the Maritime Silk Road: future projections and key drivers

Jiamiao Chen, Yaqi Zhang, Haitian Jiang +1

A vulnerability assessment projecting future climate-driven risks to coastal blue carbon ecosystems (mangroves, salt marshes, seagrass) along the Maritime Silk Road, identifying key drivers. Details are unavailable as no abstract was provid…

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JournalZenodo (CERN European Organization for Nuclear Research)2026#CCUSDOI

EL-RAKHAWI TOPOLOGICAL-BIOMIMETIC CARBON-HYDROGEN NEXUS FRAMEWORK (TB-CHN) A Unified Architecture for Selective CO2 Capture, Self-Healing Water Splitting, and Dual-Function Resonant Electrolysis

mohamed kamal arafa el-rakhawi

The TB-CHN framework integrates CO2 capture and green hydrogen production into a single electrochemical system. It combines COF-based selective CO2 trapping, self-healing NiFe-LDH catalysts, resonant electrolysis reducing cell voltage below…

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Peer-reviewed🇨🇳 ChinaJournalApplied Energy2026#AI × ESGDOI

Large language model-guided multi-agent reinforcement learning for low-carbon data center scheduling considering distribution-network constraint

Chenyue Xia, Yinliang Xu, Hongbin Sun

This work combines large language models with multi-agent reinforcement learning to schedule data-center workloads for lower carbon emissions while respecting distribution-network constraints. It aims to exploit temporal and spatial load fl…

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🇪🇺 EuropeJournalIET conference proceedings.2026#Energy TransitionDOI

Identifying and mapping shared service cables using artificial intelligence for the adoption of low carbon technology on the LV network of Ireland

Amandeep Singh, Sadaf Zaheer, J. Herring +1

ESB Networks explored AI to distinguish looped (shared) from normal service cables using ~10 million smart-meter rollout photographs, since manual review was impractical. The selected model achieved 95% recall and 64% precision, prioritizin…

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Peer-reviewedJournalZenodo (CERN European Organization for Nuclear Research)2026#Energy EfficiencyDOI

BIM-DRIVEN PARAMETERIZATION FOR OPTIMIZING LOW-CARBON STRUCTURAL MATERIAL ALLOCATION IN HIGH-RISE BUILDINGS

Dr. M. Adil Khan,Dr. M. Shoaib Ashraf,Hafiza Sarah Iqbal,Waleed Arshad,Halar Mustafa,Engr. Ahmed Mujtaba,Md Abu Syed

A study on BIM-driven parameterization to optimize low-carbon structural material allocation in high-rise buildings. It appears to target design-stage reduction of embodied carbon alongside material efficiency. Findings and quantitative res…

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