Advanced & Functional Materials
We invite submissions on advanced materials design, synthesis, processing, characterization, and performance assessment across structural and functional materials.
Topics include (but are not limited to):
- Materials synthesis and scalable processing routes
- Structure–property relationships and microstructure engineering
- Defects, interfaces, grain boundaries, and phase stability
- Functional materials: electrical, magnetic, optical, catalytic, thermal responses
- Mechanical behavior: strength, toughness, fatigue, creep, tribology
- High-temperature and harsh-environment materials performance
- Corrosion/oxidation resistance and protective coatings
- Polymers and polymer-based composites (processing, properties, durability)
- Advanced characterization and operando/in-situ techniques
- Reliability, lifetime prediction, and accelerated testing
Nano-Enabled Materials & Devices
This theme focuses on nanoscale materials and device concepts enabled by size effects, interfaces, and nanostructuring.
Topics include (but are not limited to):
- Nanomaterials synthesis, assembly, and surface functionalization
- Thin films, coatings, and nanostructured surfaces
- Nano-devices for sensing, electronics, photonics, and bio-integrated systems
- Nanostructure metrology and nanoscale characterization
- Interface engineering in nanostructured materials
- Scalability, manufacturability, and device integration challenges
- Reliability and stability of nano-enabled devices
- Nanoelectronics and nanosensors for harsh environments
- Nanocomposites and multifunctional nanostructures
- Nanowires: growth, heterostructures, integration, and device performance
Advanced Manufacturing & Tech Transfer
Submissions are welcomed on manufacturing processes, process-structure-property-performance linkages, and pathways from lab prototypes to industrial impact.
Topics include (but are not limited to):
- Additive manufacturing (metals/ceramics/polymers) and qualification
- Process monitoring, in-situ diagnostics, and quality control
- Design for manufacturability and performance-driven manufacturing
- Scale-up, standardization, certification, and repeatability studies
- Industrial case studies and commercialization strategies
- Supply chain, cost awareness, and lifecycle considerations
- Powder Metallurgy & Related Processes: powder production, compaction, sintering routes (HIP, SPS, MIM, hot pressing)
- Microstructure evolution, densification, porosity control, and defect mitigation
- Boron and Related Compounds: processing, consolidation, and applications (borides, boron-containing alloys/ceramics)
- Technology transfer models and industry–academia collaboration frameworks
Renewable Energy, Storage & Sustainability
This theme covers materials, devices, and system approaches enabling renewable energy deployment and sustainable engineering.
Topics include (but are not limited to):
- Photovoltaics and solar-thermal/thermal management concepts
- Hydrogen production, utilization, and storage systems
- Batteries, supercapacitors, and next-generation storage materials
- Fuel cells and electrochemical energy conversion devices
- Electrocatalysis and photocatalysis for energy applications
- Degradation mechanisms, durability, and long-term stability
- Safety, reliability, and performance under realistic operating conditions
- Energy management and sustainability metrics
- Lifecycle assessment (LCA) and techno-economic analysis (TEA)
- Circularity, eco-design, and sustainable materials strategies
Electronics, Sensors & Photonics
We invite contributions on materials and devices for electronics, sensing, and photonic/optoelectronic technologies.
Topics include (but are not limited to):
- Semiconductors, dielectrics, conductors, and transparent materials
- Sensor technologies: chemical, biological, physical, and environmental sensing
- Optoelectronics and photonics: emitters, detectors, waveguides, photonic structures
- Flexible, wearable, and integrated sensor systems
- Device fabrication, packaging, reliability, and stability
- Noise reduction, calibration, and signal conditioning
- Low-power and high-sensitivity device architectures
- Harsh-environment electronics and sensing
- Multi-modal sensing and sensor fusion
- Smart sensing systems and embedded electronics
Bio & Environmental Engineering
This theme targets engineering and materials solutions for health, environment, agriculture, and food-related systems.
Topics include (but are not limited to):
- Biomedical Engineering: biomaterials, medical devices, implants, biointerfaces
- Diagnostics, biosensing, and point-of-care technologies
- Antimicrobial surfaces and bioactive coatings
- Drug delivery systems and controlled release platforms
- Tissue engineering scaffolds and regenerative approaches
- Biocompatibility, cytotoxicity, sterilization, and standards considerations
- Water treatment and advanced remediation technologies
- Environmental monitoring and pollutant detection
- Sustainable packaging and circular-economy solutions
- Polymers in biomedical and environmental applications (hydrogels, coatings, composites)
Computational Materials Science
We welcome computational and theoretical studies that provide predictive insight and accelerate materials discovery and design.
Topics include (but are not limited to):
- Density Functional Theory (DFT) and electronic structure calculations
- Molecular modeling and molecular/atomistic simulations (MD)
- Monte Carlo methods and statistical modeling
- Thermodynamics, phase diagrams, and kinetic modeling
- Multiscale modeling frameworks and workflow automation
- Defects, diffusion, interfaces, and surface phenomena
- Phonons, thermal transport, and thermomechanical behavior
- Catalysis modeling and reaction mechanism analysis
- High-throughput screening and database-driven discovery
- Reproducibility, verification/validation, and uncertainty quantification
AI for Engineering Systems
This theme focuses on AI and data-driven methods for engineering analysis, design, optimization, and operational decision-making.
Topics include (but are not limited to):
- Machine learning for prediction, classification, and anomaly detection
- Physics-informed learning and hybrid (AI + physics) modeling
- Inverse design and optimization (including multi-objective methods)
- Digital twins for engineered systems and processes
- Uncertainty-aware modeling, robustness, and interpretability
- AI for process control and smart manufacturing systems
- Predictive maintenance and reliability analytics
- Data pipelines, feature engineering, and model deployment practices
- Integration of AI with experimental or sensor data streams
- Benchmarking, validation protocols, and reproducible AI workflows