At QNS — Quantum Computing
for Climate Change Solutions

At QNS (Quantum Net Solutions), we are reimagining the tools available to address one of humanity’s greatest challenges: climate change. By applying the transformative capabilitiesof quantum computing, we deliver next-generation algorithms and simulations that accelerate break throughs in carbon capture, energy systems, climate-resilient materials,and sustainable chemistry.

Our Mission

QNS is dedicated to harnessing quantum technologies to model, predict, and solve complex environmental systems—enabling faster innovation in climate technologies. We believe thatquantum computing is potential approach to represent a pivotal leap forward in our collective effort to reduceemissions, design resilient infrastructure, and unlock cleaner pathways to industrialtransformation.

Our Vision

At QNS, we envision a world where quantum-enhanced computation drives scalableclimate innovation. As global industries race toward net-zero goals, our technology providesthe foundational tools to engineer the future of clean energy, carbon removal, and sustainable infrastructure. We are not just solving equations—we are solving for the planet.

Applications

Climate Data Analysis

Quantum algorithms for enhanced optimization and interpretability of complex geophysical models.

Sustainable Manufacturing

Modeling environmentally benign solvents and catalysts to decarbonize chemical industries.

Green Energy Innovation

Simulation of next-gen photovoltaic and storage materials for renewable power scalability.

Carbon Capture & Utilization (CCU)

Design of high-affinity sorbents, MOFs, and enzymes for direct air capture and industrial CO₂ recycling.

What We Offer via OpenVQA hub

From CO₂ adsorption frameworks to electrocatalysts, we use quantum-enhanced algorithms to model materials at the quantum level with unrivaled accuracy.
Quantum-based discovery of low-carbonreaction pathways, including nitrogen fixation, methane conversion, and CO₂ utilisation.
Simulation and optimization of battery materials, hydrogen carriers, and solid-state electrolytes for clean energy transitions.
Exploratory work on quantum machine learning for climate data interpretation and forecasting.

Scientific Foundations

Our platform builds on a growing body of literature demonstrating the relevance of quantum computing to global sustainability, including:

Ollitrault et al., “Molecular simulations for carbon capture on noisy quantum devices” (Chem. Sci., 2021)
Cao et al., “Quantum Chemistry in the Age of Quantum Computing” (Chem. Rev.,2019)
Peruzzo et al., “A variational eigenvalue solver on a photonic quantum processor” (Nat. Commun., 2014
Bauer et al., “Quantum Algorithms for Quantum Chemistry and Quantum Materials Science” (Chem. Rev., 2020)

These works lay the groundwork for applying quantum methods to simulate highly correlated electron systems, capture energetics, and reaction kinetics that are central to climate technologies.