Advances in Engineering Advances in Engineering features breaking research judged by Advances in Engineering advisory team to be of key importance in the Engineering field. Papers are selected from over 10,000 published each week from most peer reviewed journals.
Amphiphilic Carbon Nanosheets: Redefining Interfacial Dynamics for Next-Generation Oil Recovery
Civil Engineering
Enhancing Seismic Resilience of Floating Floors with a Variant Tuned Mass Damper Inerter (V-TMDI)
Bridging Expertise and Automation: A Hybrid Framework for Intelligent Pavement Maintenance Decision-Making
Peridotite Carbonation Under Stress: Revealing the Self-Limiting Nature of a Promising CO₂ Sequestration Pathway
Thermodynamic-Experimental Coupling Reveals Design Principles for Lunar Regolith Geopolymers
A Physically Grounded Failure Criterion for Flexible Woven Fabrics in Biaxial Tension
Intelligent Modeling of AA-UHPC: Active Learning-Enhanced Stacked ML for Sustainable Concrete Design
Dual-Scale Enhancement of VOC Removal in Liquid Desiccant Systems: A Hybrid Approach to Healthier Indoor Environments
A Unified Analytical Framework for Predicting Flexural Behavior of Structural Columns Across Material Systems
Adaptive Thermal Optimization for Rack-Based Data Centers Using Predictive Control and Parameter-Varying Models
A Pioneering Granular Thermodynamic Model of Hydrate-Bearing Sediments: Capturing Dissociation and Path-Dependent Deformation
Sustainable Thermal Insulation in Cement Mortar: Optimizing Surface-Modified Silica Aerogel and Recycled PET for Energy-Efficient Masonry Applications
Resilience of Concrete-Filled Steel Tubular Columns Under Repeated Lateral Impacts
Thermal-Driven Moisture and Heavy Metal Transport in Unsaturated Soils: Unveiling Hysteretic Effects and Long-Term Contaminant Mobility
Decoding Freeze-Thaw Impacts: Multi-Scale Crack Propagation and Failure Precursors in Sandstone
Transforming Industrial Byproducts into High-Strength Geopolymers: Innovations in Sustainable Construction Materials
Adaptive Inverse Design of Non-Uniform/Inhomogeneous Periodic Structures Using Reinforcement Learning
