多目的最適化と技術経済分析の統合：塩化コリン-グリセロール深共晶溶媒による炭素回収の高度化
Integrating Multiobjective Optimization with Technoeconomic Analysis: Advancing Carbon Capture via a Deep Eutectic Solvent of Choline Chloride−Glycerol (原題)
Chenhong Wu, Liping Li, Shuhuan Zheng, Chengmin Gui, Dong Xiang
🤖 gxceed AI 要約
日本語
本研究は、塩化コリン-グリセロール深共晶溶媒を用いたCO2回収プロセスを開発し、単一パラメータ最適化と多目的最適化（遺伝的アルゴリズムと人工ニューラルネットワーク）を統合することで、CO2純度・回収率を高めつつ消費電力を2.02 GJ/t CO2に削減し、回収コストを1.9 $/t CO2低減した。経済性と性能のバランスを示し、石炭火力や排出集約産業への応用可能性を提示する。
English
This study develops a CO2 capture process using choline chloride-glycerol deep eutectic solvent, integrating single-parameter and multiobjective optimization (genetic algorithm + artificial neural network) to achieve high CO2 purity and capture rate while reducing power consumption to 2.02 GJ/t CO2 and capture cost by 1.9 $/t CO2. It demonstrates technoeconomic feasibility for coal-fired power plants and emission-intensive industries.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本のカーボンプライシングやGX政策下で、CCUSは重要な脱炭素オプション。本研究成果は、石炭火力の既存設備を活用する移行期の排出削減策として、コスト低減の可能性を示す。日本のCCS長期ロードマップや、アンモニア混焼などと並ぶ技術選択肢の一つとして参考になる。
In the global GX context
This paper contributes to global CCUS scholarship by demonstrating a cost-effective solvent and optimization framework that balances performance and economics. It offers insights for emission-intensive industries seeking to meet net-zero targets, complementing policy frameworks like the US 45Q tax credit and EU Innovation Fund.
👥 読者別の含意
🔬研究者:Provides a methodological template for integrating multiobjective optimization with technoeconomic analysis in CCUS process design.
🏢実務担当者:Offers a cost-reduction pathway for CO2 capture in power plants and heavy industry, potentially lowering compliance costs.
🏛政策担当者:Highlights the economic viability of advanced solvents, informing support mechanisms for CCUS deployment.
📄 Abstract（原文）
Abstract Deep eutectic solvent is cost-effective, easily available, and ionic liquid-like, making them economical alternatives for CO2 capture. This study develops a CO2 capture process using choline chloride-glycerol as an absorbent, employing single-parameter optimization to narrow variable interval and multiobjective optimization for focusing on CO2 purity, capture rate, and power consumption. The single-parameter optimization scheme first achieves a CO2 purity and capture rate of 99.70% and 94.08%, respectively, with a power consumption of 2.13 GJ/t CO2. Subsequently, the multiobjective optimization scheme combining the genetic algorithm and the artificial neural network reduces power consumption to 2.02 GJ/t CO2, with higher CO2 purity and capture rate. Economically, the CO2 capture cost decreases by 1.9 $/t CO2 compared with the single-parameter optimized scheme. Despite higher solvent consumption, the low price of deep eutectic solvent keeps the absorbent cost at a reasonable level and achieves good technoeconomic performance. The integrated optimization method combining single-parameter and multiobjective strategies effectively balances multiple conflicting performance indicators of the process. These findings offer critical insights for designing and optimizing CO2 capture systems in coal-fired power plants as well as other emission-intensive industries.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1021/acssuschemeng.6c02699first seen 2026-09-02 04:53:52
- semanticscholar https://doi.org/10.1021/acssuschemeng.6c02699first seen 2026-09-08 05:08:21 · last seen 2026-09-21 04:58:20
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