Advanced Characterization and Evaluation of Construction Materials

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Materials, and Repair & Renovation".

Deadline for manuscript submissions: 31 March 2026 | Viewed by 1522

Special Issue Editors


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Guest Editor
Center for Advanced Infrastructure and Transportation, Rutgers University–New Brunswick, New Brunswick, NJ 08901, USA
Interests: GPR; nondestructive examination; transportation; image processing; ANN; physics-informed neural network
Institute of Space and Earth Information Science, Chinese University of Hong Kong, Hong Kong, China
Interests: NDT technologies; structural health monitoring; advanced sensors; remote sensing; deep learning; digital twin
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Special Issue Information

Dear Colleagues,

For the “Advanced Characterization and Evaluation of Construction Materials” Special Issue in Buildings, we invite original and cutting‑edge research that advances our ability to probe, model, and optimize the performances of both traditional and emerging building materials. We welcome studies that bridge scales—from atomic and nano‑scale investigations through mesoscale structure–property relationships to full‑component behavior—using techniques such as high‑resolution imaging, spectroscopy, nano‑/micro‑mechanical testing, rheometry, and in situ monitoring under realistic service conditions. Contributions integrating data‑driven methods, machine learning, and digital‑twin approaches for predictive durability, life‑cycle analysis, and sustainable material design are particularly encouraged.

Thus, we invite researchers to submit original and innovative studies that propel materials science and engineering practice toward smarter, more resilient, and eco‑efficient construction solutions. Articles addressing, but not limited to, the following subtopics are considered suitable for publication:

  • High‑resolution X‑ray CT and 3D imaging of pore networks, aggregate distributions, and damage evolution;
  • Scanning electron microscopy (SEM/EDS) and atomic force microscopy (AFM) for micro‑ and nano‑scale morphology, composition, and mechanical mapping;
  • Spectroscopic techniques (FTIR, Raman, NMR) to elucidate hydration chemistry, polymer cross‑linking, and degradation mechanisms;
  • Nanoindentation and micro‑mechanical testing of cementitious phases, fiber–matrix interfaces, and interfacial transition zones;
  • Advanced rheometry for fresh‑state behavior of high‑performance, self‑consolidating, and 3D‑printable cementitious mixtures;
  • In situ monitoring using digital image correlation (DIC), acoustic emission, ultrasonic methods, and embedded fiber‑optic sensors under environmental and mechanical loads;
  • Computational modeling, machine learning frameworks, and digital twin implementations for predictive performance and optimization;
  • Life‑cycle assessment and sustainability evaluation of recycled, bio‑based, and eco‑efficient construction materials;
  • Multi‑scale structure–property relationship studies coupling experimental data with numerical simulations.

We look forward to receiving your contributions, which will enrich this Special Issue and help to drive the development of advanced, durable, and sustainable construction materials.

Kind regards,

Dr. Tianjie Zhang
Dr. Zhen Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • materials characterization
  • microstructural analysis
  • mechanical testing
  • computational modeling
  • in-situ monitoring
  • durability assessment
  • machine learning
  • sustainable materials
  • lifecycle analysis
  • digital twin

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Published Papers (3 papers)

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Research

54 pages, 11294 KB  
Article
Hybrid ML–XAI Framework for Predicting and Interpreting the Strength of Lime–Silica Fume Stabilized Clay for Sustainable Construction Applications
by Arash Aminaee, Alireza Ardakani, Abolfazl Baghbani, Hossam Abuel-Naga and Firas Daghistani
Buildings 2026, 16(5), 953; https://doi.org/10.3390/buildings16050953 - 28 Feb 2026
Viewed by 238
Abstract
This study presents an advanced experimental–computational framework for the characterization and performance evaluation of low-plasticity kaolin clay soil (CL) stabilized with quicklime (QL) and silica fume (SF), aiming to support sustainable construction and ground improvement applications. A comprehensive laboratory program was conducted, comprising [...] Read more.
This study presents an advanced experimental–computational framework for the characterization and performance evaluation of low-plasticity kaolin clay soil (CL) stabilized with quicklime (QL) and silica fume (SF), aiming to support sustainable construction and ground improvement applications. A comprehensive laboratory program was conducted, comprising 210 unconfined compressive strength (UCS) tests across 14 mix designs and three curing periods (3, 7, and 28 days), alongside index and compaction property measurements. The results show that stabilization decreases plasticity index (PI) and maximum dry density. The QL–SF system showed a synergistic effect, with QL3–SF7 mixture achieving the highest UCS (2783.8 kPa at 28 days), a 6.8-fold increase over untreated clay within the tested range. To enable predictive evaluation and mix optimization, multiple machine learning (ML) models were developed using eight input variables, including Atterberg limits and compaction parameters for each stabilized mixture, along with stabilizer contents and curing time, with hyperparameters tuned via particle swarm optimization (PSO). Among the evaluated models, CatBoost-PSO and back-propagation neural networks delivered the highest generalization performance on the independent testing dataset (R2 ≈ 0.97; RMSE ≈ 105 kPa over a UCS range of 408.88–2783.8 kPa). To enhance interpretability and engineering reliability, explainable artificial intelligence (XAI) using SHAP was employed to quantify feature influence and verify physical consistency. SHAP analysis identified QL content, PI, and curing duration as dominant predictors, and showed that SF contribution depends on its balance with available calcium from QL. Overall, the proposed ML–XAI framework provides a transparent decision-support approach for performance-driven design of chemically stabilized clay materials while reducing reliance on extensive trial-and-error laboratory testing. Full article
(This article belongs to the Special Issue Advanced Characterization and Evaluation of Construction Materials)
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32 pages, 3155 KB  
Article
Experimentally Calibrated Thermal and Economic Optimization of Wall Insulation Systems for Residential Buildings in Cold Regions of Northwest China
by Xue Bai, Dawei Yang and Gehong Zhang
Buildings 2026, 16(3), 470; https://doi.org/10.3390/buildings16030470 - 23 Jan 2026
Viewed by 396
Abstract
Improving the thermal performance of building envelopes is an effective approach for reducing energy consumption and carbon emissions in cold and heating-dominated regions. This study presents an experimentally calibrated thermal–economic optimization of external wall insulation systems for residential buildings in Northwest China, using [...] Read more.
Improving the thermal performance of building envelopes is an effective approach for reducing energy consumption and carbon emissions in cold and heating-dominated regions. This study presents an experimentally calibrated thermal–economic optimization of external wall insulation systems for residential buildings in Northwest China, using Xi’an as a representative cold–dry continental climate. A guarded hot-box apparatus was employed to measure the steady-state thermal transmittance (U-value) of multilayer wall assemblies incorporating expanded polystyrene (EPS), extruded polystyrene (XPS), and rock wool at different insulation thicknesses. The measured U-values were integrated into a dynamic building energy simulation model (DeST-h), and the simulated energy demand was subsequently evaluated through life-cycle cost (LCC) analysis to identify cost-optimal insulation configurations. The results indicate a nonlinear reduction in heating energy demand with increasing insulation thickness, with diminishing marginal returns beyond approximately 50 mm. Among the investigated materials, XPS exhibits the most favorable thermal–economic performance. For the climatic and economic conditions of Xi’an, a 50 mm XPS insulation layer minimizes total life-cycle cost while reducing annual building energy consumption by approximately 23–24% compared with the uninsulated reference case. This experimentally calibrated framework provides practical and policy-relevant guidance for insulation design and retrofit strategies in cold and dry regions. Full article
(This article belongs to the Special Issue Advanced Characterization and Evaluation of Construction Materials)
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18 pages, 23685 KB  
Article
Molecular-Scale Analysis of the Interfacial Adhesion Behavior Between Asphalt Binder and Aggregates with Distinct Chemical Compositions
by Yan Li, Shihao Li, Xinhao Sui, Xinzheng Wang and Yizhen Wang
Buildings 2025, 15(23), 4384; https://doi.org/10.3390/buildings15234384 - 3 Dec 2025
Viewed by 571
Abstract
The asphalt–aggregate interface is the weakest yet most critical component in asphalt mixtures, directly governing the pavement performance. In this study, the interfacial adhesion behavior between asphalt binder and aggregates with different chemical compositions (Al2O3, CaCO3, and [...] Read more.
The asphalt–aggregate interface is the weakest yet most critical component in asphalt mixtures, directly governing the pavement performance. In this study, the interfacial adhesion behavior between asphalt binder and aggregates with different chemical compositions (Al2O3, CaCO3, and SiO2) was investigated under varying conditions using molecular dynamics simulations. The effects of aggregate composition, environmental temperature, and asphalt aging were quantitatively assessed using key metrics, specifically interfacial adhesion energy and molecular concentration profiles near the interface. Results demonstrated that the chemical composition of aggregates fundamentally governed the asphalt–aggregate interfacial adhesion strength. Al2O3 exhibited the highest interfacial adhesion strength with asphalt binder, followed by CaCO3, with SiO2 showing the lowest strength. In terms of asphalt fractions, resins and aromatics were found to dominate the interfacial adhesion behavior due to their high molecular concentrations at the interface, with the contribution ranking as: resin > aromatic > saturate > asphaltene. The interfacial adhesion strength exhibited a non-monotonic temperature dependence. It increased with rising temperature and reached a peak value at 25–45 °C, and therefore declined because of excessive softening of asphalt binder. Furthermore, oxidative aging enhanced interfacial adhesion through strengthened electrostatic interactions. These molecular-level insights provide a fundamental understanding crucial for optimizing asphalt mixture design and enhancing pavement durability. Full article
(This article belongs to the Special Issue Advanced Characterization and Evaluation of Construction Materials)
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