Nanomaterials and Sustainability

Wiederrecht, Gary P.; Bachelot, Renaud; Xiong, Hui; Termentzidis, Konstantinos; Nominé, Alexandre; Huang, Jier; Kamat, Prashant V.; Rozhkova, Elena A.; Sumant, Anirudha; Ostraat, Michele; Jain, Prashant K.; Heckle, Chris; Li, Jie; Pupek, Krzysztof Z.

doi:10.1021/acsenergylett.3c01303

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…Several groups, in fact, were able to harness plasmon-generated hot carriers to perform different reactions, usually with higher selectivities and rates as compared with their thermal counterparts. Some of these catalyzed reactions, such as nitrogen fixation and water splitting have a remarkable application potential, also considering the global environmental and societal issues posed by global warming and climate change, so that plasmon-driven photocatalysis could play a role toward a green and sustainable future. − In this framework, considering the dramatic impact that carbon dioxide has on our environment, a lot of work is nowadays devoted to control reactions that allow efficient CO 2 conversion to methane or other short chain hydrocarbons, important in a circular economy perspective. − In 2017, Zhang et al demonstrated that in the presence of rhodium nanocubes (with a side length of 37 nm) and a hydrogen-rich environment, CO 2 is reduced to a 60:40 ratio mixture of CH 4 and CO. However, in the presence of an external electromagnetic pulse matching the optical absorption of the nanocubes (a LSPR band in the UV broadened by extensive interband excitation , ), the selectivity toward CH 4 rises to values above 90% .…”

Section: Introductionmentioning

confidence: 99%

Peeking into the Femtosecond Hot-Carrier Dynamics Reveals Unexpected Mechanisms in Plasmonic Photocatalysis

Dall’Osto,

Marsili,

Vanzan

et al. 2024

J. Am. Chem. Soc.

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Plasmonic-driven photocatalysis may lead to reaction selectivity that cannot be otherwise achieved. A fundamental role is played by hot carriers, i.e., electrons and holes generated upon plasmonic decay within the metal nanostructure interacting with molecular species. Understanding the elusive microscopic mechanism behind such selectivity is a key step in the rational design of hot-carrier reactions. To accomplish that, we present state-of-the-art multiscale simulations, going beyond density functional theory, of hot-carrier injections for the rate-determining step of a photocatalytic reaction. We focus on carbon dioxide reduction, for which it was experimentally shown that the presence of a rhodium nanocube under illumination leads to the selective production of methane against carbon monoxide. We show that selectivity is due to a (predominantly) direct hole injection from rhodium to the reaction intermediate CHO. Unexpectedly, such an injection does not promote the selective reaction path by favoring proper bond breaking but rather by promoting bonding of the proper molecular fragment to the surface.

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Section: Introductionmentioning

confidence: 99%

Peeking into the Femtosecond Hot-Carrier Dynamics Reveals Unexpected Mechanisms in Plasmonic Photocatalysis

Dall’Osto,

Marsili,

Vanzan

et al. 2024

J. Am. Chem. Soc.

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Creation of polystyrene nanoparticle patterns for structural color application

Zhao,

Gao,

Wang

et al. 2024

Colloids and Surfaces A: Physicochemical and Engineering Aspect

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Machine Learning-Driven Multidomain Nanomaterial Design: From Bibliometric Analysis to Applications

Wang,

Cao,

Yang

2024

ACS Appl. Nano Mater.

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Machine learning (ML), as an advanced data analysis tool, simulates the learning process of the human brain, enabling the extraction of features, discovery of patterns, and making accurate predictions or decisions from complex data. In the field of nanomaterial design, the application of ML technology not only accelerates the discovery and performance optimization of nanomaterials but also promotes the innovation of materials science research methods. Bibliometrics, as a research method based on quantitative analysis, provides us with a macro perspective to observe and understand the application of ML technology in nanomaterial design by statistically analyzing various indicators in the scientific literature. This paper quantitatively analyzes the literature related to ML-driven nanomaterial design from seven dimensions, revealing the importance and necessity of ML technology in nanomaterial design. It also systematically analyzes the diversified applications of the combination of ML technology and nanomaterial technology with the design of suitable ML algorithms being key to enhancing the performance of nanomaterials. In addition, this paper discusses current challenges and future development directions, including data quality and data set construction, algorithm innovation and optimization, and the deepening of interdisciplinary cooperation. This review not only provides researchers with a macro perspective to observe the current state and development trends of the field but also provides ideas and suggestions for future research. This is of significant importance and value for promoting scientific progress in the field of nanomaterial design, fostering the in-depth development of interdisciplinary research, and accelerating the innovative application of material technologies.

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Nanomaterials and Sustainability

Cited by 3 publications

References 18 publications

Peeking into the Femtosecond Hot-Carrier Dynamics Reveals Unexpected Mechanisms in Plasmonic Photocatalysis

Peeking into the Femtosecond Hot-Carrier Dynamics Reveals Unexpected Mechanisms in Plasmonic Photocatalysis

Creation of polystyrene nanoparticle patterns for structural color application

Machine Learning-Driven Multidomain Nanomaterial Design: From Bibliometric Analysis to Applications

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