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 41–50 of 50 papers
Zhou Y.
This study applies a real options model to optimize energy efficiency investments in steel firms, considering carbon trading and tax cuts. It derives optimal investment strategies under economic downturns, highlighting the interplay between…
Malik Faisal Ahmad
This review (2020-2025) synthesizes literature on FTTH energy efficiency and sustainable design. FTTH outperforms copper but depends on operational practices like sleep/doze modes, dynamic bandwidth allocation, and renewable integration. A …
Xiaoxuan Ma, Qinghai Guo, Gang Lian +1
This systematic review, following PRISMA, screened 244 articles and analyzed 77 studies. It summarizes the evolution of low-carbon retrofit technologies over the past five decades and identifies climate pressures, policies, stakeholder dema…
Jeff P. Prancevic, Cody E. Finke, Eric Peterson +3
This paper examines the viability of producing ordinary Portland cement using carbon-free silicate rocks like basalt instead of limestone. Thermodynamic analysis shows that producing cement from basalt could reduce total energy demand by 30…
Roger Padullés, Martin Pihl Andersen, Niklas Bagge Mogensen +3
This paper proposes generalized electrification solutions for breweries using Pinch Analysis for heat pump integration and process decarbonization. It offers a practical method to improve energy efficiency and reduce emissions at industrial…
Xiao Lang, Mingyang Zhang, Wengang Mao +2
This paper proposes a physics-guided machine learning approach to assess ship biofouling, which increases drag and fuel consumption. By integrating physical constraints into ML models, it enables more accurate evaluation, supporting operati…
Qiguo Yi, Guiling Ran, Huiting Chen
This study analyzes panel data from 110 Chinese resource-based cities (2013-2022) to examine the impact of digital intelligence transformation (DIT) on carbon emission efficiency (CEE). Using a comprehensive DIT index and SBM-GML approach, …
Tirelli D.
This narrative review comprehensively synthesizes strategies for achieving net zero carbon buildings, including energy efficiency, renewable energy integration, and life-cycle assessment. It identifies key barriers and enablers for adoption…
P. Dutta, Vasileios Paliktzoglou, S. Shambhavi +2
This study proposes an Adaptive Digital Twin (ADT) framework for cement kilns, fusing real-time data with a Markov Chain-based reaction rate model to predict and control chemical transformations. A reinforcement learning controller optimize…
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…
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