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.
Showing 581–600 of 4925 papers
Valenzuela J.M.
This paper frames net-zero as a contested discursive space, analyzed through the concepts of publics and counter-publics. It treats decarbonization not merely as a technical or policy problem but as a site of social and political communicat…
Mahsati Askarova
Using 2005–2023 time-series data and an ARDL model, this study examines determinants of green economic development in Nakhchivan. Innovative investments and renewable energy production show significant positive long-run effects, while short…
Victor Bordejé, Morales Vargas, Antonio Guerrero-Ruiz +2
This review compares biogas upgrading technologies through a net-zero carbon lens, distinguishing pathways that merely separate CO2 from those that valorise it. Electrolytic H2 methanation and syngas routes convert CO2 into additional CH4 o…
Yujia Ji
Mixed-methods study of 20 rural villages in northern China (2023-24) combining interviews with evolutionary game theory and agent-based modelling. Energy poverty is shown to be reproduced through conversion burdens, housing quality, village…
Nurcan Kilinc, Maria Marlein Warong
An empirical study examining how energy transition progress relates to capital inflows and environmental outcomes across BRICS economies. The framing suggests green investment does not automatically attract capital or deliver environmental …
Felix N. Igbeghe
This systematic review examines literature on the dual challenge of expanding energy access while transitioning to cleaner energy sources in developing countries. Using content analysis, it identifies trade-offs and synergies between energy…
Behzad Zamanipour, Padam Adhikari, Farzin Ahmadi +1
This paper proposes a multi-dimensional framework for modeling the resilience of energy system transitions. Without an available abstract, specific contributions and findings cannot be confirmed, but it appears to offer a methodological app…
Тетяна Курбатова, Liliana Smiech, Iryna Mykolaivna Sotnyk +3
Using OLS on Ukrainian macro data (2002–2021), this study assesses how investment, energy efficiency, energy costs, and renewables drive CO₂ emissions. Macro energy efficiency emerges as the strongest decarbonization driver, while gross cap…
Yunita Sopiana, Dyah Maharani, Sutri Destemi Elsi +2
This study analyzes Indonesia's energy policy as a contested arena where decarbonization, power relations and distributive justice collide. Coal generates state revenue and energy security while concentrating socio-ecological costs, and nic…
Alavi SE
This paper reviews the role of deep learning and optimization techniques in smart grids integrating IoT and AI. LSTM networks, reinforcement learning, and Particle Swarm Optimization are presented as solutions for renewable variability, pea…
Mohseni Zonouzi, Seyyed Jamaledin, Aminpour Ghahramani, Pegah
Using a balanced panel of eight high-geopolitical-risk economies (2011–2023) and a gamma log-link GLM, this study tests whether industrial robot adoption drives renewable energy uptake. Robot density, labor participation, and R&D spending s…
Soares Siqueira, Abel, Tejada-Arango, Diego A., Morales-España, Germán +7
The Tulipa Energy Model is a Julia package for energy planning that integrates electricity markets with sector coupling. As an open-source optimization tool, it supports analysis of decarbonization pathways across power and other sectors (h…
Renee Obringer, Mir Matin, Kaveh Madani
This policy brief examines how domain-informed AI can complement traditional long-term energy infrastructure planning under climate uncertainty. It argues that stationary historical weather data and rigid models expose public investments to…
(著者不明)
Using ARDL on 1976–2024 time-series data, this study examines how energy consumption affects Pakistan's industrial growth. Energy use, trade openness, and labor participation boost industrial value added, while inflation harms it. It stress…
G. Okara
This is a review of the 4th edition of a practitioner-focused handbook on oil and gas law, covering contracts, regulation and risk. It addresses geopolitical fragmentation, just transition, sanctions compliance, ESG and climate litigation a…
(著者不明)
This study proposes a route-scale collision risk framework for wind-assisted ship propulsion (WASP), evolving CPA into a spatio-temporal pre-filter for Safe Boundary methods. Using the SOMOS optimal routing simulator over one year on the Sa…
(著者不明)
This study uses AI to optimize hydrothermal liquefaction (HTL) of macroalgae for biofuel production. A bio-oil yield of 23.5% was achieved at 280°C, 30 min, 15% solids, with AI prediction error under 2%. The biochar (55% carbon) supports so…
(著者不明)
This paper analyzes Ukraine's green transition as simultaneously an environmental, macroeconomic, security, and EU-integration agenda. It argues decarbonization, energy efficiency, renewables, and industrial modernization are prerequisites …
(著者不明)
Proposes an integrated framework for transforming ports into sustainable energy hubs, combining renewable generation, battery storage, green hydrogen, port microgrids, and intelligent energy management. It explicitly addresses Mediterranean…
(著者不明)
A machine-learning-assisted framework co-optimizes electricity–heat–hydrogen–storage coupling in grid-connected integrated energy systems. Using K-means and Latin hypercube sampling for scenario generation, a MILP co-optimizes cost, carbon …
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