Quantum computing algorithm could help develop carbon capture method

Scientists aim to leverage the "current quantum computing technology to solve a practical environmental problem."
Chris Young
A stock image of a quantum computer.
A stock image of a quantum computer.

Bartlomiej Wroblewski/iStock

A team of scientists tested an algorithm designed to find the most promising compounds for atmospheric carbon capture.

With the help of quantum computing systems, their algorithm could help accelerate the development of a promising method that could help avert the worst effects of climate change.

Quantum computing algorithm to help fight climate change

Atmospheric carbon capture is a promising potential tool in the fight against climate change. As is the case with most carbon capture technologies, the method is still in the early development phase, meaning a lot of work is required to make it capable of capturing the vast amounts of CO2 required.

So far, the most promising version of the technology has used a class of compounds called amines that chemically bind with carbon dioxide.

Scientists are currently working on identifying the best amine compounds for the job, as even slight variations can have a great impact on the overall efficiency of the technology. Essentially, a slight difference can lead to or prevent the capture of billions of tons of additional carbon dioxide.

Now, in a paper published in the journal AVS Quantum Science, scientists from the National Energy Technology Laboratory and the University of Kentucky outlined how they tested an algorithm that can analyze amine reactions via quantum computing. They say their new algorithm can be used to rapidly determine the most efficient amine compounds for carbon capture.

“We are not satisfied with the current amine molecules that we use for this [carbon capture] process,” study author Qing Shao explained in a press statement. "We can try to find a new molecule to do it, but if we want to test it using classical computing resources, it will be a very expensive calculation. Our hope is to have a fast algorithm that can screen thousands of new molecules and structures."

Quantum computing to "solve a practical environmental problem"

The reason the algorithm would require a quantum computer as opposed to a classical computer is that a simulation of a chemical reaction must account for interactions between every pair of atoms involved. This means that even simple molecules — such as the simple three-atom CO2 molecule — reacting with the simplest of amines, ammonia, which has four atoms, can result in hundreds of atomic interactions.

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Quantum computers are also still in the relatively early development phase. However, the researchers developed their algorithm to work within the limited parameters of existing quantum computers. “We are trying to use the current quantum computing technology to solve a practical environmental problem,” said author Yuhua Duan.

Study abstract:

CO2 capture is critical to solving global warming. Amine-based solvents are extensively used to chemically absorb CO2. Thus, it is crucial to study the chemical absorption of CO2 by amine-based solvents to better understand and optimize CO2 capture processes. Here, we use quantum computing algorithms to quantify molecular vibrational energies and reaction pathways between CO2 and a simplified amine-based solvent model—NH3. Molecular vibrational properties are important to understanding kinetics of reactions. However, the molecule size correlates with the strength of anharmonicity effect on vibrational properties, which can be challenging to address using classical computing. Quantum computing can help enhance molecular vibrational calculations by including anharmonicity. We implement a variational quantum eigensolver (VQE) algorithm in a quantum simulator to calculate ground state vibrational energies of reactants and products of the CO2 and NH3 reaction. The VQE calculations yield ground vibrational energies of CO2 and NH3 with similar accuracy to classical computing. In the presence of hardware noise, Compact Heuristic for Chemistry (CHC) ansatz with shallower circuit depth performs better than Unitary Vibrational Coupled Cluster. The “Zero Noise Extrapolation” error-mitigation approach in combination with CHC ansatz improves the vibrational calculation accuracy. Excited vibrational states are accessed with quantum equation of motion method for CO2 and NH3. Using quantum Hartree–Fock (HF) embedding algorithm to calculate electronic energies, the corresponding reaction profile compares favorably with Coupled Cluster Singles and Doubles while being more accurate than HF. Our research showcases quantum computing applications in the study of CO2 capture reactions.

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