AAC

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• Published Subscription Original Research 14 May 2026

  Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques

  By Mr. Rishabh Ray, Mr. Shirshendu Maitra, Ms. Anusri Mukhopadhyay

  Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …

  Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 Read article →