Quantum Thermodynamic Innovations In Desalination: An Energy-Information Efficiency Analysis For GCC Region

Abstract

The Gulf Cooperation Council (GCC), responsible for over 45% of global desalination capacity, must transition from fossil-fueled thermal systems to renewable-integrated, entropy-optimized platforms. This study delivers the first quantum thermodynamic assessment of 30+ desalination technologies, introducing information efficiency a metric quantifying entropy minimization and proximity to reversible operation. Evaluation of thermal, membrane, and hybrid systems reveals stark generational disparities. Legacy MSF and MED plants consume 65-90 kWh/m³, achieve <3% information efficiency, and emit 5.2-6.5 kg CO₂/m³. In contrast, advanced quantum-informed systems, such as Quantum-Forward Osmosis, deliver up to 50× lower energy use (1.8 kWh/m³), 500× higher information efficiency (50%), and 325× lower carbon intensity (0.02 kg CO₂/m³).

AI-enhanced platforms with real-time entropy monitoring and photovoltaic integration approach thermodynamic limits via feedback-driven entropy suppression, reflecting quantum heat engine principles. Hybrid configurations, including FO-RO and AI-optimized RO, offer the best balance of readiness (TRL 7–8) and entropy performance, enabling near-term GCC deployment. By reframing desalination performance from energy-only metrics to information–entropy optimization, this framework provides a roadmap for designing climate-aligned, reversible water production infrastructure with high recovery rates and near-zero carbon intensity aligning water security with net-zero and sustainability objectives.