Catalysis at the Nanoscale: Insights from Theory and Simulation
A special issue of Nanomaterials (ISSN 2079-4991). This special issue belongs to the section "Theory and Simulation of Nanostructures".
Deadline for manuscript submissions: 25 November 2025 | Viewed by 431
Special Issue Editor
Interests: computational catalysis; petrochemical catalysts; fuel cell
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Catalysis lies at the heart of sustainable energy conversion, environmental remediation, and chemical synthesis. At the nanoscale, catalytic processes exhibit unique behaviors governed by quantum effects, surface dynamics, and atomistic interactions, which challenge conventional experimental characterization. Advances in theoretical modeling and computational simulations have emerged as indispensable tools to unravel these complexities, offering mechanistic insights and predictive power for designing next-generation catalysts.
This Special Issue focuses on cutting-edge research at the intersection of nanoscience, catalysis, and computational methodologies. We invite contributions that explore topics such as (1) multiscale modeling of catalytic active sites, (2) machine learning-driven catalyst discovery, (3) reaction pathway analysis under realistic conditions, (4) dynamic evolution of nanostructures during catalysis, and (5) synergy between simulations and in situ/operando experiments. Submissions may address heterogeneous, homogeneous, or enzymatic systems, with an emphasis on energy-related applications.
By bridging theory and practice, this Special Issue aims to accelerate the rational design of efficient, selective, and stable nanocatalysts. We welcome original research articles, reviews, and perspectives that highlight breakthroughs in computational techniques, novel theoretical frameworks, or interdisciplinary approaches to decode nanoscale catalytic phenomena.
Dr. Houyu Zhu
Guest Editor
Manuscript Submission Information
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Keywords
- nanoscale catalysis
- theoretical modeling
- computational chemistry
- machine learning in catalysis
- reaction mechanisms
- multiscale simulation
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