A Quantum Computational Method for Corrosion Inhibition

We present a hybrid classical-quantum computational pipeline for the determination of adsorption energies of a benzotriazole molecule on an aluminum alloy surface relevant for the transport industry, in particular to address the corrosion problem. The molecular adsorbate and substrate alloy were selected by interrogating molecular and materials databases, in search for desired criteria. The protocol can be generalized to other surfaces with arbitrary orientation and chemical composition, as well as to other molecular adsorbates. It includes three main steps based on mean-field electronic structure calculations, embedding theories and quantum algorithms. The quantum computing step demonstrated here with the variational quantum eigensolver is amenable to any other reliable quantum algorithm for ground-state energy estimation. Excited-state energies can also be taken into account in the quantum computing step, if the target reaction involves excited states.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-05-28
DOI
https://doi.org/10.1021/acs.jctc.5c00469
Citations
1
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.52

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article

A Quantum Computational Method for Corrosion Inhibition

Rosa Di Felice, Naman Jain
1 citations
Journal of Chemical Theory and Computation
Machine Learning in Materials Science
0.52
article

A Quantum Computational Method for Corrosion Inhibition

Rosa Di Felice, Naman Jain
article en
1 citations

Abstract

We present a hybrid classical-quantum computational pipeline for the determination of adsorption energies of a benzotriazole molecule on an aluminum alloy surface relevant for the transport industry, in particular to address the corrosion problem. The molecular adsorbate and substrate alloy were selected by interrogating molecular and materials databases, in search for desired criteria. The protocol can be generalized to other surfaces with arbitrary orientation and chemical composition, as well as to other molecular adsorbates. It includes three main steps based on mean-field electronic structure calculations, embedding theories and quantum algorithms. The quantum computing step demonstrated here with the variational quantum eigensolver is amenable to any other reliable quantum algorithm for ground-state energy estimation. Excited-state energies can also be taken into account in the quantum computing step, if the target reaction involves excited states.

Journal of Chemical Theory and ComputationVol. 21(11)
University of Southern California (US), California Southern University (US), Center for NanoScience (DE), Istituto Nanoscienze (IT)
Defense Advanced Research Projects Agency
Openalex Percentile: Top 38%
Machine Learning in Materials Science
0.52
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A Quantum Computational Method for Corrosion Inhibition — Rosa Di Felice, Naman Jain · Journal of Chemical Theory and Computation (2025) | TGRS Research Map | TGRS