Current heterogeneous catalytic processes for environmental remediation of air, water, and soil

Bahrani, Sonia; Mousavi, Seyyed Mojtaba; Hashemi, Seyyed Alireza

doi:10.1016/b978-0-12-818806-4.00008-5

Cited by 2 publications

(1 citation statement)

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“…Unlike homogeneous catalysis, where the catalyst and reactants exist in the same phase, heterogeneous catalysis leverages the unique properties and high surface area of solid catalysts to facilitate reactions between gas, liquid, or solid reactants. 2 This ability to operate in diverse reaction conditions and effectively couple different phases makes heterogeneous catalysis an indispensable tool in a wide range of industries, including energy production, 3 environmental remediation, 4 and chemical synthesis. 5 A key aspect driving the evolution of heterogeneous catalysis is its central role in sustainable chemistry.…”

Section: Introductionmentioning

confidence: 99%

Modelling Heterogeneous Catalysis using Quantum Computers: An academic and industry perspective

Hariharan,

Kinge,

Visscher

2024

Preprint

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Heterogeneous catalysis plays a critical role in many industrial processes, including the production of fuels, chemicals, and pharmaceuticals, and research to improve current catalytic processes is important to make chemical industry more sustainable. Despite its importance, the challenge of identifying optimal catalysts with the required activity and selectivity persists, demanding a detailed understanding of the complex interactions between catalysts and reactants at various length and time scales. Density functional theory (DFT) has been the workhorse in modelling heterogeneous catalysis for more than three decades. While DFT has been instrumental, this review explores the application of quantum computing algorithms in modelling heterogeneous catalysis, marking a paradigm shift in our approach to understanding catalytic interfaces. Bridging academic and industrial perspectives, focusing on emerging materials such as multi-component alloys, single-atom catalysts, and magnetic catalysts, we delve into the limitations of DFT in capturing strong correlation effects and spin-related phenomena. The review also presents important algorithms and their applications relevant to heterogeneous catalysis modelling, showcasing advancements in the field. Additionally, the review explores embedding strategies where quantum computing algorithms handle strongly correlated regions, while traditional quantum chemistry algorithms address the remainder, offering a promising approach for large-scale heterogeneous catalysis modelling. Looking forward, ongoing investments by academia and industry reflect a growing enthusiasm for quantum computing's potential in heterogeneous catalysis research. The review concludes by envisioning a future where quantum computing algorithms seamlessly integrate into research workflows, propelling us into a new era of computational chemistry and thereby reshaping the landscape of heterogeneous catalysis.

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