Competing Effects of Lignocellulosic Garden Waste in Vegetation Concrete: Organic Retardation, Moisture Buffering, and Interfacial Densification

1. Data Overview This dataset contains the complete experimental measurements and analytical outputs that support the findings of the above-mentioned manuscript. The study investigates the competing mechanisms of lignocellulosic garden waste as a partial cement replacement in vegetation concrete, focusing on the trade-off between organic retardation, moisture buffering, and interfacial densification. 2. Experimental Design and Methodology A comprehensive methodological framework was employed, including: Orthogonal Experimental Design: An L9(3⁴) array was used to evaluate four factors at three levels: water-to-binder ratio (w/b), designed porosity, aggregate size, and garden waste content. A verification group, a waste-free control, and an inert filler control (20% limestone powder) were also prepared. Performance Testing: Measurements include 28-day compressive strength (f₂₈), connected porosity, permeability (k₁₅), pore solution pH, water absorption, and 7-day water retention. All tests followed Chinese standards (GB/T, CJJ/T) and were performed in triplicate. Microstructural Characterization: Key pore structure parameters were obtained via Mercury Intrusion Porosimetry (MIP) for critical pore diameter (d~crit~), Nitrogen adsorption (BET/BJH) for specific surface area and mesoporosity, and X-ray Computed Tomography (CT) for 3D pore network analysis. Interfacial Transition Zone (ITZ) morphology was examined by Field-Emission SEM. Chemical Analysis: Leachate from garden waste was characterized for Total Organic Carbon (TOC) and reducing sugars to provide direct evidence of retardation mechanisms. 3. File Description (Complete_Dataset_Garden_Waste_Vegetation_Concrete.xlsx) The dataset is organized into five sheets within a single Excel file. 4. Data Usage and License This dataset is made available to facilitate transparency, reproducibility, and further meta-analysis. All data are original and unprocessed except for standard statistical derivations (e.g., ANOVA, range analysis). Researchers are encouraged to reuse these data under the terms of the Creative Commons Attribution 4.0 International (CC-BY 4.0) license, provided that proper attribution is given to this manuscript and the dataset. 5. Funding Acknowledgment This work was supported by the Key Scientific and Technological Projects in Henan Province (242102320334) and the Henan Provincial University Science and Technology Innovation Team (No. 25IRTSTHN009).