Exploration of Quantum Computing in Materials Discovery for Direct Air Capture Applications
- URL: http://arxiv.org/abs/2404.13122v3
- Date: Sat, 18 May 2024 12:21:43 GMT
- Title: Exploration of Quantum Computing in Materials Discovery for Direct Air Capture Applications
- Authors: Marco Antonio Barroca, Rodrigo Neumann Barros Ferreira, Mathias Steiner,
- Abstract summary: Direct air capture (DAC) of carbon dioxide is a promising method for mitigating climate change.
Solid sorbents, such as metal-organic frameworks, are currently being tested for DAC application.
We apply the qubit-ADAPT-VQE technique to run simulations on both classical computing and quantum computing hardware.
- Score: 0.06827423171182154
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Direct air capture (DAC) of carbon dioxide is a promising method for mitigating climate change. Solid sorbents, such as metal-organic frameworks, are currently being tested for DAC application. However, their potential for deployment at scale has not been fully realized. The computational discovery of solid sorbents is challenging, given the vast chemical search space and the DAC requirements for molecular selectivity. Quantum computing can potentially accelerate the discovery of solid sorbents for DAC by predicting molecular binding energies. In this work, we explore simulation methods and algorithms for predicting gas adsorption in metal-organic frameworks using a quantum computer. Specifically, we simulate the potential energy surfaces of CO2, N2, and H2O molecules at the Mg+2 metal center that represents the binding sites of typical metal-organic frameworks. We apply the qubit-ADAPT-VQE technique to run simulations on both classical computing and quantum computing hardware, and achieve reasonable accuracy while maintaining hardware efficiency.
Related papers
- Calculating the energy profile of an enzymatic reaction on a quantum computer [0.0]
Quantum computing provides a promising avenue toward enabling quantum chemistry calculations.
Recent research efforts are dedicated to developing and scaling algorithms for Noisy Intermediate-Scale Quantum (NISQ) devices.
arXiv Detail & Related papers (2024-08-20T18:00:01Z) - Quantum Simulations for Carbon Capture on Metal-Organic Frameworks [0.0]
DAC is a technical solution that does not rely on natural processes to capture CO2 from the atmosphere.
We aim to leverage the potential of quantum computing to improve the filters used in DAC.
arXiv Detail & Related papers (2023-11-21T07:58:02Z) - Modeling Non-Covalent Interatomic Interactions on a Photonic Quantum
Computer [50.24983453990065]
We show that the cQDO model lends itself naturally to simulation on a photonic quantum computer.
We calculate the binding energy curve of diatomic systems by leveraging Xanadu's Strawberry Fields photonics library.
Remarkably, we find that two coupled bosonic QDOs exhibit a stable bond.
arXiv Detail & Related papers (2023-06-14T14:44:12Z) - A self-consistent field approach for the variational quantum
eigensolver: orbital optimization goes adaptive [52.77024349608834]
We present a self consistent field approach (SCF) within the Adaptive Derivative-Assembled Problem-Assembled Ansatz Variational Eigensolver (ADAPTVQE)
This framework is used for efficient quantum simulations of chemical systems on nearterm quantum computers.
arXiv Detail & Related papers (2022-12-21T23:15:17Z) - Equation-of-motion variational quantum eigensolver method for computing
molecular excitation energies, ionization potentials, and electron affinities [4.21608910266125]
Near-term quantum computers are expected to facilitate material and chemical research through accurate molecular simulations.
We present an equation-of-motion-based method to compute excitation energies following the variational quantum eigensolver algorithm.
arXiv Detail & Related papers (2022-06-21T16:21:04Z) - Accurate Machine Learned Quantum-Mechanical Force Fields for
Biomolecular Simulations [51.68332623405432]
Molecular dynamics (MD) simulations allow atomistic insights into chemical and biological processes.
Recently, machine learned force fields (MLFFs) emerged as an alternative means to execute MD simulations.
This work proposes a general approach to constructing accurate MLFFs for large-scale molecular simulations.
arXiv Detail & Related papers (2022-05-17T13:08:28Z) - Modelling Carbon Capture on Metal-Organic Frameworks with Quantum
Computing [0.0]
Next generation sorbing materials are urgently needed to battle climate change.
Quantum computing is applied to the problem of CO$$ adsorbing in Al-fumarate Metal-Organic Frameworks.
Our work paves the way for the use of quantum computing in the quest of sorbents for more efficient carbon capture and conversion applications.
arXiv Detail & Related papers (2022-03-29T13:28:16Z) - Computing molecular excited states on a D-Wave quantum annealer [52.5289706853773]
We demonstrate the use of a D-Wave quantum annealer for the calculation of excited electronic states of molecular systems.
These simulations play an important role in a number of areas, such as photovoltaics, semiconductor technology and nanoscience.
arXiv Detail & Related papers (2021-07-01T01:02:17Z) - Quantum-Classical Hybrid Algorithm for the Simulation of All-Electron
Correlation [58.720142291102135]
We present a novel hybrid-classical algorithm that computes a molecule's all-electron energy and properties on the classical computer.
We demonstrate the ability of the quantum-classical hybrid algorithms to achieve chemically relevant results and accuracy on currently available quantum computers.
arXiv Detail & Related papers (2021-06-22T18:00:00Z) - Quantum HF/DFT-Embedding Algorithms for Electronic Structure
Calculations: Scaling up to Complex Molecular Systems [0.0]
We propose the embedding of quantum electronic structure calculation into a classically computed environment.
We achieve this by constructing an effective Hamiltonian that incorporates a mean field describing the action of the inactive electrons on a selected Active Space.
arXiv Detail & Related papers (2020-09-03T18:35:50Z) - Simulation of Thermal Relaxation in Spin Chemistry Systems on a Quantum
Computer Using Inherent Qubit Decoherence [53.20999552522241]
We seek to take advantage of qubit decoherence as a resource in simulating the behavior of real world quantum systems.
We present three methods for implementing the thermal relaxation.
We find excellent agreement between our results, experimental data, and the theoretical prediction.
arXiv Detail & Related papers (2020-01-03T11:48:11Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.