AI-Designed Sustainable Conducting Polymers for Green Electronics
Design the Future: AI-Powered Sustainable Polymers for Green Electronics
About This Course
This advanced workshop on ‘AI-Designed Sustainable Conducting Polymers for Green Electronics’ equips participants with foundational knowledge of conducting polymers, sustainability principles, and AI-driven materials design, followed by hands-on sessions, case studies, and practical strategies for translating AI-optimized green polymers into real-world electronic applications.
Aim
The aim of this workshop is to equip researchers, academicians, and industry professionals with advanced knowledge and practical skills in designing sustainable conducting polymers using AI, enabling the development of eco-friendly, high-performance materials for next-generation green electronics.
Workshop Objectives
- Build a strong understanding of conducting polymers and their applications in green electronics.
- Introduce sustainability principles, eco-design, and regulatory standards for polymer materials.
- Demonstrate AI and ML techniques for predicting polymer properties and guiding material design.
- Provide hands-on experience with datasets, model building, and result interpretation.
- Explore real-world case studies and strategies for translating sustainable polymers from lab to market.
- Promote collaboration, innovation, and knowledge exchange among researchers and professionals.
Workshop Structure
📅 Day 1: Foundations – Conducting Polymers, Sustainability & AI
- Theme: Materials fundamentals + sustainability context + AI basics
- Introduction to conducting polymers for green electronics
- Overview of PEDOT, polyaniline, polypyrrole, and bio-based systems
- Charge transport mechanisms in polymers
- Applications in sensors, flexible devices, and energy storage
- Environmental challenges of conventional conducting polymers
- Bio-based and biodegradable conducting polymers
- Life Cycle Assessment (LCA) for electronic materials
- Toxicity, recyclability, eco-design principles, and regulatory standards
- AI & Materials Informatics fundamentals for polymer design
- Data sources: experiments, simulations, and literature mining
- Overview of ML, DL, generative AI, and end-to-end AI workflow for materials discovery
📅 Day 2: AI-Driven Design & Optimization
- Theme: Prediction, optimization, and sustainability integration
- Machine learning for conducting polymer property prediction
- Feature extraction: structure, dopants, and processing parameters
- Predicting conductivity, bandgap, stability, and mechanical properties
- Regression and classification models for materials performance
- Model evaluation techniques and uncertainty estimation
- AI-guided monomer and dopant selection
- Process optimization for greener synthesis routes
- Reinforcement and composite design (nanocellulose, graphene, CNTs)
- Reducing energy and chemical footprint using AI
- AI-enabled sustainability assessment and carbon footprint prediction
- Design-for-recycling, circular electronics, and trade-off analysis
📅 Day 3: Hands-On, Case Studies & Translation
- Theme: Practical exposure + real-world applications
- Hands-on AI session (Google Colab / Jupyter)
- Working with conducting polymer datasets
- Building ML models to predict conductivity or stability
- Visualization and interpretation of results
- Decision-making for sustainable material selection
- Case studies: AI-designed polymers for flexible and wearable electronics
- Sustainable sensors, bioelectronics, and energy harvesting applications
- Generative AI for novel polymer structure design
- Scaling sustainable conducting polymers from lab to market
- IP strategy, patents, and technology transfer
- Industry–academia collaboration models and funding opportunities
- Open discussion & participant interaction
Who Should Enrol?
- PhD Scholars & Research Students in Materials Science, Polymer Science, Electronics, Chemistry, or related fields.
- Academicians & Faculty Members interested in sustainable materials, green electronics, and AI-driven polymer research.
- Industry Professionals & R&D Experts working in electronics, polymer development, energy storage, or materials innovation.
- Professionals with basic knowledge of polymers, electronics, or AI/ML who wish to apply AI for sustainable material design.
Important Dates
Registration Ends
02/20/2026
IST 4 : 30 PM
Workshop Dates
02/20/2026 – 02/22/2026
IST 5 : 30 PM
Workshop Outcomes
- Understand conducting polymers and their applications in green electronics.
- Apply sustainability principles and eco-design in polymer development.
- Use AI/ML tools for polymer property prediction and design optimization.
- Gain hands-on experience with datasets, modeling, and result interpretation.
- Learn strategies for scaling and commercializing sustainable polymers.
Meet Your Mentor(s)
Fee Structure
Student
₹2499 | $75
Ph.D. Scholar / Researcher
₹3499 | $85
Academician / Faculty
₹4499 | $95
Industry Professional
₹6499 | $120
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
Join Our Hall of Fame!
Take your research to the next level with NanoSchool.
Publication Opportunity
Get published in a prestigious open-access journal.
Centre of Excellence
Become part of an elite research community.
Networking & Learning
Connect with global researchers and mentors.
Global Recognition
Worth ₹20,000 / $1,000 in academic value.
★★★★★
Cancer Drug Discovery: Creating Cancer Therapies
Mario Rigo • ★★★★★
Power BI and Advanced SQL Mastery Integration Workshop, CRISPR-Cas Genome Editing: Workflow, Tools and Techniques
Silvia Santopolo • ★★★★★
Artificial Intelligence for Cancer Drug Delivery
G Jyothi • ★★★★★
Artificial Intelligence for Cancer Drug Delivery
RAVIKANT SHEKHAR • View All Feedbacks →