MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641085306 A) filed by Madhankumar C; Dr. P. Janagarathinam; Dr. D. Umapathi; Sengodan R; Dr. Anju Singh; Dr. Preeti Nand Kumar; Sivahari R; Mr C Madhankumar; Ms Angeline Yuvancy S; and Ms Dharhsini D R on July 12, 2026, for Quantum-Chemical Matter Reconfiguration Engine With Adaptive Photonic Control For Autonomous Material Evolution And Sustainable Energy Applications.
Inventors include Dr. P. Janagarathinam; Dr. D. Umapathi; Sengodan R; Dr. Anju Singh; Dr. Preeti Nand Kumar; Sivahari R; Mr C Madhankumar; Ms Angeline Yuvancy S; and Ms Dharhsini D R.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: Quantum-Chemical Matter Reconfiguration Engine with Adaptive Photonic Control for Autonomous Material Evolution and Sustainable Energy Applications Abstract The present invention introduces a Quantum-Chemical Matter Reconfiguration Engine (QCMRE) integrated with an Adaptive Photonic Control System (APCS) to enable autonomous material evolution through real time quantum-level chemical manipulation. Unlike conventional material synthesis methods that rely on fixed reaction pathways and energy-intensive processing, the proposed system employs quantum-state modeling, AI-driven molecular optimization, and dynamically tunable photonic energy sources to precisely control atomic bonding, crystal formation, and molecular rearrangement. The framework continuously monitors material behavior using nanoscale quantum sensors and applies adaptive photon frequencies to guide desired structural transformations while minimizing waste, emissions, and energy consumption. The invention incorporates a hybrid architecture consisting of quantum chemical simulation modules, machine learning-based reaction prediction engines, adaptive laser-photonic controllers, molecular feedback sensors, and sustainable energy optimization algorithms. Through closed-loop autonomous control, the system predicts optimal reaction pathways, adjusts photon intensity and wavelength in real time, and reconfigures material properties such as conductivity, strength, thermal stability, catalytic efficiency, and optical characteristics. This self-learning capability enables rapid discovery and fabrication of advanced functional materials without extensive manual experimentation. The proposed engine has broad applications in next-generation battery materials, hydrogen production, solar energy harvesting, semiconductor manufacturing, carbon capture materials, smart polymers, aerospace composites, biomedical nanomaterials, quantum electronics, and circular manufacturing systems. By combining quantum chemistry, artificial intelligence, adaptive photonics, and sustainable engineering principles, the invention significantly reduces production time, improves material performance, lowers environmental impact, and accelerates the development of intelligent, energy-efficient materials for future industrial and clean- energy ecosystems. It represents a transformative platform for autonomous material innovation, supporting sustainable manufacturing and next-generation energy technologies.
Disclaimer: Curated by HT Syndication.
