Modeling CoCu Nanoparticles Using Neural Network-Accelerated Monte Carlo Simulations

Zha, Shenjun; Sharapa, Dmitry I.; Liu, Sihang; Zhao, Zhi‐Jian; Studt, Felix

doi:10.1021/acs.jpca.2c07888

Cited by 3 publications

(4 citation statements)

References 37 publications

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“…Deep learning can also be applied for Monte Carlo simulations. A deep learning-based technique known as neural network accelerated Monte Carlo simulations has recently been employed to investigate the segregation of alloy nanoparticles . These advancements in computational methods and resources could potentially enable the exploration of realistic nanoparticles, leading to a deeper understanding of their behaviors and properties.…”

Section: Opportunities and Challenges In Nanoscaled Carriers For Chem...mentioning

confidence: 99%

“…A deep learning-based technique known as neural network accelerated Monte Carlo simulations has recently been employed to investigate the segregation of alloy nanoparticles. 69 These advancements in computational methods and resources could potentially enable the exploration of realistic nanoparticles, leading to a deeper understanding of their behaviors and properties. The combination of these simulation techniques provides a pathway to efficiently screen and optimize various nanoscaled oxygen carriers for specific chemical looping applications.…”

Section: Nanoscale Simulationsmentioning

confidence: 99%

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Nanoscaled Oxygen Carrier-Driven Chemical Looping for Carbon Neutrality: Opportunities and Challenges

Sunny,

Meng,

Kumar

et al. 2023

Acc. Chem. Res.

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Conspectus Climate change poses unprecedented challenges, demanding efforts toward innovative solutions. Amid these efforts, chemical looping stands out as a promising strategy, attracting attention for its CO2 capture prowess and versatile applications. The chemical looping approach involves fragmenting a single reaction, often a redox reaction, into multiple subreactions facilitated by a carrier, frequently a metal oxide. This innovative method enables diverse chemical transformations while inherently segregating products, enhancing process flexibility, and fostering autothermal properties. An intriguing facet of this novel technique lies in its capacity for CO2 utilization in processes like dry reforming and gasification of carbon-based feeds such as natural gas and biomass. Central to the success of chemical looping technology is a profound understanding of the intricacies of redox chemistry within these processes. Notably, nanoscaled oxygen carriers have proven effective, characterized by their extensive surface area and customizable structure. These carriers hold substantial promise, enabling reactions under milder conditions. This Account offers a concise overview of the mechanisms, benefits, opportunities, and challenges associated with nanoscaled carriers in chemical looping applications, with a focus on CO2 utilization. We delve into the nuances of redox chemistry, shedding light on ionic diffusion and oxygen vacancytwo key elements that are crucial in designing oxygen carriers. This discussion extends to nanospecific factors such as the particle size effect and gas diffusivity. Through the application of density functional theory simulations, insights are drawn regarding the impact of nanoparticle size on syngas production in chemical looping. Interestingly, nanosized iron oxide (Fe2O3) carriers exhibit elevated syngas selectivity and constrained CO2 formation at the nanoscale. Moreover, the reactivity enhancement of mesoporous SBA-16 supported Fe2O3 over mesoporous SBA-15 supported Fe2O3 is elucidated through Monte Carlo simulations that emphasize the superiority of the 3-dimensional interconnected porous network of SBA-16 in enhancing gas diffusion, thereby amplifying reactivity compared to the 2-dimensional SBA-15. Furthermore, we explore prevalent nanoscaled carriers, focusing on their amplified performance in CO2 utilization schemes. These encompass the integration of nanoparticles with mesoporous supports to enhance surface area, the adoption of nanoscale core–shell architectures to enhance diffusion, and the dispersion of nanoscaled active sites on microsized carriers to accelerate reactant activation. Notably, our mesoporous-supported Fe2O3 nanocarrier facilitates methane dissociation and oxidation by reducing energy barriers, thereby promoting methane conversion. The Account proceeds to outline key challenges and prospects for nanoscaled carriers in chemical looping, concluding with a glance into future research directions. We also shine a spotlight on our research group’s efforts in innovati...

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Section: Opportunities and Challenges In Nanoscaled Carriers For Chem...mentioning

confidence: 99%

Section: Nanoscale Simulationsmentioning

confidence: 99%

Nanoscaled Oxygen Carrier-Driven Chemical Looping for Carbon Neutrality: Opportunities and Challenges

Sunny,

Meng,

Kumar

et al. 2023

Acc. Chem. Res.

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“…[ 164,165 ] For instance, many studies on bimetallic NAs combine MLIP with MC or optimization algorithms to delve into their structure–properties relationship, leading to advancements in our understanding of alloy catalyst properties and paving the way for superior heterogeneous catalysts. [ 166–169 ]…”

Section: Applications Of Mlip For Surfaces/interfaces Of Nanomaterialsmentioning

confidence: 99%

“…[164,165] For instance, many studies on bimetallic NAs combine MLIP with MC or optimization algorithms to delve into their structure-properties relationship, leading to advancements in our understanding of alloy catalyst properties and paving the way for superior heterogeneous catalysts. [166][167][168][169] A recent study by Han et al showcases the integration of a symmetry-constrained genetic algorithm (SCGA) with NNP to examine the stability of Pt-Ni bimetallic NAs. [170] The SCGA, tailored for symmetric NAs, works alongside NNP to explore a vast space of homotops and compositions of Pt-Ni NAs with up to 4033 atoms, shedding light on how shape, size, and composition influence dominant chemical ordering patterns.…”

Section: Intrinsic Stability Of Surfaces/interfacesmentioning

confidence: 99%

Construction of High Accuracy Machine Learning Interatomic Potential for Surface/Interface of Nanomaterials—A Review

Wan,

He,

Shi

2023

Advanced Materials

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The inherent discontinuity and unique dimensional attributes of nanomaterial surfaces and interfaces bestow them with various exceptional properties. These properties, however, also introduce difficulties for both experimental and computational studies. The advent of machine learning interatomic potential (MLIP) addresses some of the limitations associated with empirical force fields, presenting a valuable avenue for accurate simulations of these surfaces/interfaces of nanomaterials. Central to this approach is the idea of capturing the relationship between system configuration and potential energy, leveraging the proficiency of machine learning (ML) to precisely approximate high‐dimensional functions. This review offers an in‐depth examination of MLIP principles and their execution, and elaborates on their applications in the realm of nanomaterial surface and interface systems. We also discuss the prevailing challenges faced by this potent methodology.This article is protected by copyright. All rights reserved

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Chemical Orderings in CuCo Nanoparticles: Topological Modeling Using DFT Calculations

Neyman,

Alemany

2024

Nanomaterials

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The orderings of atoms in bimetallic 1.6–2.1 nm-large CuCo nanoparticles, important as catalytic and magnetic materials, were studied using a combination of DFT calculations with a topological approach. The structure and magnetism of Cu50Co151, Cu101Co100, Cu151Co50, and Cu303Co102 nanoparticles; their resistance to disintegrating into separate Cu and Co species; as well as the exposed surface sites, were quantified and analyzed, showing a clear preference for Cu atoms to occupy surface positions while the Co atoms tended to form a compact cluster in the interior of the nanoparticles. The surface segregation of Co atoms that are encapsulated by less-active Cu atoms, induced by the adsorption of CO molecules, was already enabled at a low coverage of adsorbed CO, providing the energy required to displace the entire compact Co species inside the Cu matrices due to a notable adsorption preference of CO for the Co sites over the Cu ones. The calculated adsorption energies and vibrational frequencies of adsorbed CO should be helpful indicators for experimentally monitoring the nature of the surface sites of CuCo nanoparticles, especially in the case of active Co surface sites emerging in the presence of CO.

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Modeling CoCu Nanoparticles Using Neural Network-Accelerated Monte Carlo Simulations

Cited by 3 publications

References 37 publications

Nanoscaled Oxygen Carrier-Driven Chemical Looping for Carbon Neutrality: Opportunities and Challenges

Nanoscaled Oxygen Carrier-Driven Chemical Looping for Carbon Neutrality: Opportunities and Challenges

Construction of High Accuracy Machine Learning Interatomic Potential for Surface/Interface of Nanomaterials—A Review

Chemical Orderings in CuCo Nanoparticles: Topological Modeling Using DFT Calculations

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