Innovative development of high-strength concrete with ultrafine metakaolin-heated POFA binders and fine coal bottom ash aggregate: Strength, durability and microstructural performance
超微粉メタカオリンと加熱処理POFA結合材および微粉炭灰骨材を用いた高強度コンクリートの革新的開発：強度、耐久性、微細構造性能 (AI 翻訳)
M. A. Mansour, M. H. Ismail, M. Amran, Honin Alshaer, M. H. W. Ibrahim, A. Alshalif, Omar Alruwaythi, N. Mokhtar
🤖 gxceed AI 要約
日本語
本研究は、セメントと天然砂への依存を減らすため、超微粉メタカオリン（UFM）と加熱処理パーム油燃料灰（HPOFA）を結合材、微粉炭灰（CBA）を細骨材として使用した高強度コンクリート（HSC）を開発した。最適配合はUFM10%、HPOFA20%、CBA10%であり、強度、耐久性、硫酸塩抵抗性が向上し、LCAでも環境負荷が低いことが示された。
English
This study develops high-strength concrete using ultrafine metakaolin (UFM) and heated palm oil fuel ash (HPOFA) as binders and coal bottom ash (CBA) as fine aggregate to reduce cement and sand usage. The optimal mix (10% UFM, 20% HPOFA, 10% CBA) improves strength, permeability, sulfate resistance, and achieves lower environmental impacts according to LCA.
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
日本では建設廃材や産業副産物の有効活用が課題であり、本研究成果は国内のコンクリート製造におけるCO2削減と廃棄物削減に寄与する可能性がある。特に、硫酸塩環境での耐久性向上は、沿岸部やインフラへの応用が期待される。
In the global GX context
This paper addresses the global need to decarbonize construction materials by valorizing waste streams. The integrated ternary binder approach and LCA provide practical guidance for regions with similar industrial waste profiles, contributing to circular economy goals in the built environment.
👥 読者別の含意
🔬研究者:Provides mechanistic insights into pore refinement and sulfate resistance through combined use of UFM, HPOFA, and CBA.
🏢実務担当者:Offers mix-design guidance for producing high-strength concrete with lower environmental impact using locally available waste materials.
🏛政策担当者:Demonstrates life-cycle benefits of waste utilization in construction, supporting policies for circular economy and low-carbon building materials.
📄 Abstract（原文）
The production of high-strength concrete (HSC) remains heavily dependent on cement and natural sand, despite the urgent need to reduce the carbon footprint of construction materials. Meanwhile, substantial quantities of palm oil fuel ash (POFA) and coal bottom ash (CBA) remain underutilized, and most existing studies treat ultrafine metakaolin (UFM), heated POFA (HPOFA), or CBA in isolation rather than as an integrated eco-concrete system. This study develops and evaluates an innovative HSC in which UFM and HPOFA serve as blended binders and CBA partially replaces natural fine aggregate. The main objective is to quantify the influence of ternary system on strength development relating to time, permeability, sulfate resistance and microstructural characteristics. A full factorial experimental program was conducted on HSC mixes containing 10–15% UFM, 20–30% HPOFA, and 0–20% CBA as fine aggregate. The results showed that 15% UFM maximizes compressive strength for binary blend, while a combined 15% UFM and 20% HPOFA is optimal for ternary blend. Overall, optimization of the UFM and HPOFA with CBA as fine aggregate system identified 10% UFM, 20% HPOFA and 10% CBA as the best-performing combination. The incorporation of 10–15% UFM with 20–30% HPOFA reduces permeability to 1.80–1.97 × 10−13 cm/s. The mixer containing 15% UFM and 20% HPOFA exhibits only 14.2, 8.6 and 11% reductions in compressive strength, tensile strength, and UPV, respectively, after 300 days of immersion in 5% Na2SO4 solution. Microstructural analysis confirms that UFM and HPOFA refine the pore structure, limit sulfate ion ingress, and diminish ettringite-induced microcracking. The life cycle assessment (LCA) indicates that mixes with 15% UFM and 30% HPOFA in the presence of 10–20% CBA achieve the lowest environmental impacts. The study offers mechanistic insights and practical mix-design guidance for regions with similar waste profiles and aggressive sulfate environments.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1038/s41598-026-49052-7first seen 2026-06-29 07:36:13
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。