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.
Showing 1201–1220 of 1235 papers
Supriya Gandhale, Shashwati Wankar, S. Pohekar +5
This study provides a comprehensive patent landscape analysis of AI integration in carbon capture and utilization (CCUS) technologies, identifying key trends, leading countries and assignees, and innovation hotspots. It highlights how AI ad…
Sandeep R. Sahu, N. Vishwakarma, N. Sharma +5
This review examines the current state of carbon capture, conversion, and utilization (CCCU) technologies, focusing on sustainable chemical production pathways. It covers capture methods and conversion to valuable products such as methanol,…
Ping Yang, Xiaoman Yu, Kyriakos C. Stylianou +2
This paper reviews machine learning applications for amine-based CO2 capture, from molecular screening to process optimization. Key breakthroughs include improved prediction accuracy in liquid systems and identification of novel adsorbents …
P. Saini, U. Biradar, K. Sonawane +4
This paper presents an AI-powered digital solution for real-time monitoring and optimization of the CCUS value chain, integrating machine learning with physics-based models to detect anomalies and leaks automatically. Field tests show a 30–…
Jingheng Liu
This paper systematically reviews the mechanisms of CO2 geological storage in various formations (deep saline aquifers, depleted oil/gas reservoirs, unmineable coal seams, basalts) and summarizes implementation effects and applicable condit…
Junyi Yang, Nikoo Moradpour, Lap Au-Yeung +1
This review highlights microfluidic (lab-on-a-chip) technologies for advancing subsurface fluid dynamics in CCUS, enhanced oil recovery, and underground hydrogen storage. It discusses visualization of pore-scale phenomena, integration with …
Samser Shaikh, Fangming Xiang, Khaled Baamran +6
This paper reports roll-to-roll fabrication of flat-sheet adsorbents using an amidoxime-functionalized polymer (PIM-1-AO) without binders, coated on non-woven supports. The process scales from lab to production, achieving CO2 uptake of 2.5 …
C. Carpenter
This paper reviews simultaneous SCCO2-brine injection and water-alternating-gas (WAG) methods for geological carbon sequestration, proposing a novel integration with saltwater-disposal wells. The SAI-WAG strategy leverages existing infrastr…
Thomas Haase, Christoph Bosch, René Rüter
This study experimentally investigates the effect of hydrogen sulfide (H2S) on hydrogen induced cracking (HIC) in SAWL pipes for CO2 transport in CCUS projects. Resistance limits based on pH and H2S concentration were established for X65 an…
Wen Sun, Liang Teng, Yiming Xuan +2
This study proposes a 'Green Loop Cement Plant' concept using a hybrid-energy driven CO2 capture and utilization system (HE-CCCU) that integrates calcium looping with in situ dry reforming of methane. Process modeling shows 90% CO2 reductio…
Bing Chen, Hong Feng, Chunli Tang +5
This study proposes a leakage detection method for supercritical CO2 pipelines using negative pressure wave and cross-correlation analysis, addressing small leak detection challenges. Validated with Yanchang oilfield model, it achieves rela…
Arnab Sinha
This standard defines a hub-only CCUS architecture where emitters capture CO₂ in solid form and only centralized hubs handle gaseous CO₂. It lowers entry barriers for small emitters, reduces pipeline length and permitting complexity, and pr…
Xiaohua Tan, Xiao Jun Zhou, Peng Xu +1
This study developed a high-temperature, high-pressure microfluidic platform to visualize and quantify gas-phase evolution during CO2 depressurization under reservoir conditions. Three key stages were identified: gas precipitation, coalesce…
Jiatie Cai, Di Wu, Xing Xu +3
This study develops a mathematical and physical model for CO2 flooding and storage in low-permeability reservoirs, analyzes dynamic evolution, and uses multi-objective particle swarm optimization to optimize injection parameters. Results sh…
S. Kamal, R. Nirwana, M. Farhan +3
This study proposes a phased development plan integrating sour gas production (45 mol% CO2) with CO2-EOR in a carbonate reservoir. Using compositional simulation, it shows incremental oil recovery from 25% to 38% and storage of 0.95 TSCF CO…
Chenxi Zhang, Yi Yang, Jing Qiu +2
This paper proposes a two-stage decarbonization framework for power systems that integrates supply-side retrofitting of coal plants with CCUS and power-to-gas, and demand-side carbon response using an enhanced emission flow model for indust…
Krishna Kant, C. Habchi, Martha Hajiw-Riberaud +2
This study investigates supercritical CO2 pipeline leaks for CCUS, analyzing how impurities (N2, CH4, Ar) affect mass flow rate and decompression wave propagation using CFD. A real-fluid model validated against experiments provides insights…
Camilo andres Plata Uribe, Emílio Carlos Nelli Silva
This study applies topology optimization to impeller-diffuser design in centrifugal compressors for CCUS, using a multi-objective function to minimize energy dissipation and maximize pressure recovery. Results show that turbulence modeling …
B. Sennaoui, Kegang Ling
This study presents a numerical investigation of CO2 utilization for enhanced oil recovery (EOR) and associated CO2 retention in unconventional reservoirs, using the Bakken Formation as a case. A compositional reservoir model simulates CO2 …
Kshitij Bhatta, Muhammad Waseem, Mingzhe Liu +3
This paper proposes a digital twin framework for wood drying in desiccant-assisted heat pump (DAHP) systems. Combining high-fidelity physics models with multi-agent reinforcement learning (MARL), it reduces total energy consumption by 43.2%…
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