Soil treatment with natural materials is an effective method to improve the mechanical properties of the original soil for recycling engineering construction. This research aims to evaluate the synergistic effects of lignin fiber and cement on sandy clayey silt stabilization. A factorial experimental design was employed, testing five lignin fiber contents (0%, 2%, 4%, 6%, and 8%) and three cement contents (0%, 2%, and 4%) across four curing periods (1, 7, 14, and 30 days). Unconfined compressive strength (UCS) tests were conducted in triplicate for each combination (total *n* = 180 samples), and failure surfaces were analyzed using Scanning Electron Microscopy with Energy Dispersive X-ray spectroscopy (SEM-EDX). Results indicate a critical lignin fiber threshold of 4%, beyond which UCS decreased by 15–20% due to increased void ratios. Statistical analysis (ANOVA, *p* < 0.05) confirmed significant interactions between lignin fiber, cement content, and curing time. For instance, 4% lignin fiber and 4% cement yielded a 139% UCS increase after 30-day curing compared to untreated soil. SEM-EDX revealed that lignin fiber networks enhance ductility by bridging soil particles, while cement hydration reduced particle detachment. These findings provide a quantitative framework for optimizing lignin fiber-cement stabilization in sustainable geotechnical applications.

Coal liquefaction residues (CLRs), including both indirect (ICLR) and direct (DCLR) variants, represent industrial by-products whose conventional landfill disposal raises environmental concerns. This study comparatively analyzes ICLR and DCLR properties against limestone fine aggregates through physicochemical characterization. Results indicate that ICLR contains predominant SiO₂ crystalline phases (50.05%) with trace Fe-Ti-Al-Mg oxides, demonstrating higher Vickers hardness (615 HV vs. 246 HV for limestone) and elastic modulus (98 GPa vs. 81 GPa for limestone), while its apparent relative density (2.612) closely matches that of limestone (2.783). Conversely, DCLR features abundant carbonaceous components (75.9% C) with olefinic/aromatic structures (asphaltene content 66.2%), exhibiting lower mechanical strength (Vickers hardness 21 HV) but enhanced asphalt affinity, as indicated by strong C=C (1591 cm⁻¹) and aromatic C–H (744 cm⁻¹) absorption peaks in FTIR. Both CLRs share comparable gradation curves and micromorphological characteristics with limestone aggregates, including uniform surface scaly textures. While pore-size distributions differ minimally between CLRs, both present finer porosity than limestone and show no leachate toxicity risks, confirming their viability as sustainable alternatives to asphalt fine aggregates.

Existing evaluations of highway engineering testing and inspection equipment often overemphasize nominal parameters, directly compare non-equivalent indicators, and lack clear criteria for equipment upgrades. Based on a targeted synthesis of publicly available technical specifications, standards and procedures, and the peer-reviewed literature, this study develops a documentary benchmarking and decision framework for nine categories of testing and inspection technologies across five application scenarios: pavement condition, structural performance, internal quality, construction processes, and material testing. The framework evaluates the available evidence in terms of parameter comparability, explicit performance, system integration, data reliability, and data verifiability. Published manufacturer specifications give maximum testing speeds of 120 km/h for the selected ZOYON-LDD and 80 km/h for Greenwood TSD, but these values do not establish equivalent measurement accuracy or repeatability under matched conditions. In contrast, an FHWA-reported 32-laboratory evaluation of AIMS2 aggregate-morphology testing provided independently assessed angularity coefficients of variation of 2.9% within and 4.3% between laboratories for aggregate sizes excluding 0.075 mm. Public evidence remains insufficient for assessing metrological traceability, raw-data access, and algorithm performance in several other categories. A tiered upgrade pathway prioritizes modular improvements where feasible, complemented by complete equipment replacement when justified. Proposed acceptance criteria emphasize raw-data accessibility, independent verification, and separately reported AI detection and measurement errors, shifting attention from nominal parameters toward reproducible and traceable capabilities.