gxceed
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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Topic: #Energy Transition (clear)

Showing 1261–1280 of 1975 papers

📚 Peer-reviewed · JournalZenodo (CERN European Organization for Nuclear Research)2026#Energy TransitionDOI

RENEWABLE AND SUSTAINABLE ENERGY SYSTEMS FOR A LOW-CARBON FUTURE: SOURCES, SUSTAINABILITY DIMENSIONS, AND FUTURE CHALLENGES

Muhammad Raza Punjwani, Jaweed Ali Thaheem, Muhammed Ahsan Niaz, Ali Zain Ul Abdeen, Shafique Ahmed Soomro, Mansoor

A comprehensive review of renewable and sustainable energy systems for a low-carbon future, covering energy sources, sustainability dimensions, and future challenges.

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🇨🇳 China📚 Peer-reviewed · JournalInternational Journal of Hydrogen Energy2026#Energy TransitionDOI

Effects of injection strategy on combustion and emission of multiple low-carbon fuel compound injection engine

Shiyi Pan, Xiaojun Yin, Yongcheng Huang +3

This study investigates the effects of injection strategy on combustion and emissions of a compound injection engine using multiple low-carbon fuels. Results suggest that optimal injection strategies can improve combustion efficiency and re…

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🌍 Global📚 Peer-reviewed · JournalBuildings2026#Energy TransitionDOI

The Influence of Mobility Parameters on the Rheological Behaviour and Mechanical Properties of Low-Carbon Mortar Mixtures

Derick Asirvatham, Mayra T. de Grazia, Leandro Sanchez

This study evaluates low-carbon mortar mixtures with high limestone filler content (up to 52%) and reduced cement. It shows that mobility parameters (IPS, MPT) strongly influence rheology and hardened properties, with MPT being the most cri…

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🇨🇳 China📚 Peer-reviewed · JournalInternational Journal of Educational Development2026#Energy TransitionDOI

Low-Carbon Transformation of the Construction Industry and the Construction of a Three-Dimensional Competency Framework for Civil Engineering Professionals Under the Dual Carbon Strategy

Yuyi Liu, Q Wang, Qin Yang +5

This study analyzes the low-carbon transformation of China's construction industry under dual carbon targets and the resulting demands on civil engineers. It quantifies carbon emissions across the building lifecycle and proposes a three-dim…

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🇪🇺 Europe📚 Peer-reviewed · JournalEnergy Policy2026#Energy TransitionDOI

Combined simulation and optimization framework to quantify the impact of policy tools in agents’ decision making in the transition towards a low carbon energy system

Manuel Sánchez Dieguez, Klara Schure, Robert Koelemeijer +2

This paper presents IESA, a hybrid simulation-optimization framework that combines agent-based modeling with cost optimization to evaluate low-carbon policy instruments. Applied to the Netherlands, it shows that while renewables diffuse und…

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📚 Peer-reviewed · JournalChemical Engineering and Processing - Process Intensification2026#Energy TransitionDOI

Strategic planning for low-carbon power systems incorporating small modular reactors

Héctor Quiroga-Barriga, César Ramírez-Márquez, José María Ponce‐Ortega

This paper examines the role of small modular reactors (SMRs) in strategic planning for low-carbon power systems. It analyzes grid integration challenges and policy implications, positioning SMRs as flexible and cost-effective low-carbon so…

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🇨🇳 China📚 Peer-reviewed · JournalOcean Engineering2026#Energy TransitionDOI

Low-carbon path planning for inland vessels using a novel FMORL framework

Xianyu Hou, Langxiong Gan, Lei Zhang +3

This study proposes a novel multi-objective reinforcement learning framework (FMORL) for low-carbon path planning of inland vessels. It optimizes routes to minimize CO2 emissions while considering trade-offs with operational costs and time.…

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