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Bifunctional nanomaterial with antibody-like and electrocatalytic activity to facilitate electrochemical biosensor of Escherichia coli. J Electroanal Chem (Lausanne) 2023. [DOI: 10.1016/j.jelechem.2023.117303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
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2
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Akbarzadeh AR, Mesgarzadeh I, Eshaghi Malekshah R. Solution-phase polyol synthesis and coadsorption MD calculations from faceted platinum nanoparticles: NOVEL NPs‒polymer morphology controlling. CHEMICAL PAPERS 2022. [DOI: 10.1007/s11696-022-02272-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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3
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Parker AJ, Motevalli B, Opletal G, Barnard AS. The pure and representative types of disordered platinum nanoparticles from machine learning. NANOTECHNOLOGY 2021; 32:095404. [PMID: 33212430 DOI: 10.1088/1361-6528/abcc23] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The development of interpretable structure/property relationships is a cornerstone of nanoscience, but can be challenging when the structural diversity and complexity exceeds our ability to characterise it. This is often the case for imperfect, disordered and amorphous nanoparticles, where even the nomenclature can be unspecific. Disordered platinum nanoparticles have exhibited superior performance for some reactions, which makes a systematic way of describing them highly desirable. In this study we have used a diverse set of disorder platinum nanoparticles and machine learning to identify the pure and representative structures based on their similarity in 121 dimensions. We identify two prototypes that are representative of separable classes, and seven archetypes that are the pure structures on the convex hull with which all other possibilities can be described. Together these nine nanoparticles can explain all of the variance in the set, and can be described as either single crystal, twinned, spherical or branched; with or without roughened surfaces. This forms a robust sub-set of platinum nanoparticle upon which to base further work, and provides a theoretical basis for discussing structure/property relationships of platinum nanoparticles that are not geometrically ideal.
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Affiliation(s)
| | | | | | - Amanda S Barnard
- ANU Research School of Computer Science, Acton ACT 2601, Australia
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4
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Altantzis T, Lobato I, De Backer A, Béché A, Zhang Y, Basak S, Porcu M, Xu Q, Sánchez-Iglesias A, Liz-Marzán LM, Van Tendeloo G, Van Aert S, Bals S. Three-Dimensional Quantification of the Facet Evolution of Pt Nanoparticles in a Variable Gaseous Environment. NANO LETTERS 2019; 19:477-481. [PMID: 30540912 PMCID: PMC6437648 DOI: 10.1021/acs.nanolett.8b04303] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Pt nanoparticles play an essential role in a wide variety of catalytic reactions. The activity of the particles strongly depends on their three-dimensional (3D) structure and exposed facets, as well as on the reactive environment. High-resolution electron microscopy has often been used to characterize nanoparticle catalysts but unfortunately most observations so far have been either performed in vacuum and/or using conventional (2D) in situ microscopy. The latter however does not provide direct 3D morphological information. We have implemented a quantitative methodology to measure variations of the 3D atomic structure of nanoparticles under the flow of a selected gas. We were thereby able to quantify refaceting of Pt nanoparticles with atomic resolution during various oxidation-reduction cycles. In a H2 environment, a more faceted surface morphology of the particles was observed with {100} and {111} planes being dominant. On the other hand, in O2 the percentage of {100} and {111} facets decreased and a significant increase of higher order facets was found, resulting in a more rounded morphology. This methodology opens up new opportunities toward in situ characterization of catalytic nanoparticles because for the first time it enables one to directly measure 3D morphology variations at the atomic scale in a specific gaseous reaction environment.
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Affiliation(s)
- Thomas Altantzis
- Electron
Microscopy for Materials Research (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
| | - Ivan Lobato
- Electron
Microscopy for Materials Research (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
| | - Annick De Backer
- Electron
Microscopy for Materials Research (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
| | - Armand Béché
- Electron
Microscopy for Materials Research (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
| | - Yang Zhang
- Electron
Microscopy for Materials Research (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
| | - Shibabrata Basak
- DENSsolutions, Informaticalaan 12, Delft, 2628ZD, The Netherlands
| | - Mauro Porcu
- DENSsolutions, Informaticalaan 12, Delft, 2628ZD, The Netherlands
| | - Qiang Xu
- DENSsolutions, Informaticalaan 12, Delft, 2628ZD, The Netherlands
| | - Ana Sánchez-Iglesias
- Bionanoplasmonics
Laboratory, CIC biomaGUNE, Paseo de Miramón 182, 20014 Donostia - San Sebastian, Spain
| | - Luis M. Liz-Marzán
- Bionanoplasmonics
Laboratory, CIC biomaGUNE, Paseo de Miramón 182, 20014 Donostia - San Sebastian, Spain
- Ikerbasque,
Basque Foundation for Science, 48013 Bilbao, Spain
| | - Gustaaf Van Tendeloo
- Electron
Microscopy for Materials Research (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
| | - Sandra Van Aert
- Electron
Microscopy for Materials Research (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
| | - Sara Bals
- Electron
Microscopy for Materials Research (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
- E-mail:
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Sun B, Barron H, Wells B, Opletal G, Barnard AS. Correlating anisotropy and disorder with the surface structure of platinum nanoparticles. NANOSCALE 2018; 10:20393-20404. [PMID: 30376019 DOI: 10.1039/c8nr06450d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Due to the competition between numerous physicochemical variables during formation and processing, platinum nanocatalysts typically contain a mixture of shapes, distributions of sizes, and a considerable degree of surface imperfection. Structural imperfection and sample polydispersivity are inevitable at scale, but accepting bulk and surface diversity as legitimate design features provides new opportunities for nanoparticle design. In recent years disorder and anisotropy have been embraced as useful design parameters but predicting the impact of uncontrollable imperfection a priori is challenging. In the present work we have created an ensemble of uniquely imperfect nanoparticles extracted from classical molecular dynamics trajectories and applied statistical filters to restrict the ensemble in ways that reflect common industrial design principles. We find that targeting different sizes and size distributions may be an effective way of promoting or suppressing internal disorder or crystallinity (as required), but the degree of anisotropy of the particle as a whole has a greater impact on the population of different types of surface ordering and active sites. These results indicate that tuning of disordered and anisotropic Pt nanoparticles is possible, but it is not as straightforward as geometrically ideal nanoparticles with a high degree of crystallinity. It is unlikely that a synthesis strategy could eliminate this diversity entirely, or ensure this type of structural complexity does not develop post-synthesis under operational conditions, but it may be possible to bias the formation of specific bulk structures and the surface anisotropy.
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Affiliation(s)
- Baichuan Sun
- Data61 CSIRO, Door 34 Goods Shed Village St, Docklands, Victoria, Australia.
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Swann E, Sun B, Cleland DM, Barnard AS. Representing molecular and materials data for unsupervised machine learning. MOLECULAR SIMULATION 2018. [DOI: 10.1080/08927022.2018.1450982] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- E. Swann
- Molecular and Materials Modelling, Data61 CSIRO , Docklands, Victoria, Australia
| | - B. Sun
- Molecular and Materials Modelling, Data61 CSIRO , Docklands, Victoria, Australia
| | - D. M. Cleland
- Molecular and Materials Modelling, Data61 CSIRO , Docklands, Victoria, Australia
| | - A. S. Barnard
- Molecular and Materials Modelling, Data61 CSIRO , Docklands, Victoria, Australia
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7
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Electroless Synthesis of Highly Stable and Free-Standing Porous Pt Nanotube Networks and their Application in Methanol Oxidation. ChemElectroChem 2018. [DOI: 10.1002/celc.201701271] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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8
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Barron H, Opletal G, Tilley R, Barnard AS. Predicting the role of seed morphology in the evolution of anisotropic nanocatalysts. NANOSCALE 2017; 9:1502-1510. [PMID: 28067382 DOI: 10.1039/c6nr06765d] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Controlling the structure of nanocrystals is an effective way to tune their properties and improve performance in a wide variety of applications. However, the atomic pathways for achieving this goal are difficult to identify and exercise, due to competing kinetic and thermodynamic influences during formation. In particular, an understanding of how symmetry, and symmetry breaking, determine nanocrystal morphology would significantly advance our ability to produce nanomaterials with prescribed functions. In this study we present results of a detailed computational study into the atomic structure of platinum nanoparticles at early growth stages of formation, as a function of temperature and atomic deposition rates. We investigate the impact of different types of crystalline seeds and characterize the emergent structures via simulated High Resolution Transmission Electron Microscopy (HRTEM) images. We find that the choice of initial seed is an important driver for symmetry breaking, due to a combination of atomic deposition and etching on different seed facets. A mix of low index facets causes the formation of important surface defects, in addition to the absorption/adsorption of single atoms, which can be correlated with different catalytic reactions as the process perpetuates. These findings provide new insights into nanocrystal shape-control mechanisms and suggest new opportunities for future design of this important class of nanomaterials.
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Affiliation(s)
- Hector Barron
- CSIRO, Molecular & Materials Modelling, Data61, Door 34 Goods Shed, Village St, Docklands, Victoria 3008, Australia.
| | - George Opletal
- CSIRO, Molecular & Materials Modelling, Data61, Door 34 Goods Shed, Village St, Docklands, Victoria 3008, Australia.
| | - Richard Tilley
- University of New South Wales, Sydney, 2052, NSW, Australia
| | - Amanda S Barnard
- CSIRO, Molecular & Materials Modelling, Data61, Door 34 Goods Shed, Village St, Docklands, Victoria 3008, Australia.
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Fernandez M, Barron H, Barnard AS. Artificial neural network analysis of the catalytic efficiency of platinum nanoparticles. RSC Adv 2017. [DOI: 10.1039/c7ra06622h] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Accurate predictions of nanocatalyst structure/property relations can be made with large theoretical data sets, rather than limited sets of computational structures, in a fraction of the time using machine learning.
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Affiliation(s)
| | - Hector Barron
- Molecular and Materials Modelling
- Data61 CSIRO
- Docklands
- Australia
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10
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Sun B, Fernandez M, Barnard AS. Statistics, damned statistics and nanoscience - using data science to meet the challenge of nanomaterial complexity. NANOSCALE HORIZONS 2016; 1:89-95. [PMID: 32260631 DOI: 10.1039/c5nh00126a] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
For many years dealing with the complexity of nanoscale materials, the polydispersivity of individual samples, and the persistent imperfection of individual nanostructures has been secondary to our search for novel properties and promising applications. For our science to translate into technology, however, we will inevitably need to deal with the issue of structural diversity and integrate this feature into the next generation of more realistic structure/property predictions. This is challenging in the field of nanoscience where atomic level precision is typically inaccessible (experimentally), but properties can depend on structural variations at the atomic scale. Fortunately there exists a range of reliable statistical methods that are entirely applicable to nanoscale materials; ideal for navigating and analysing enormous amount of information required to accurately describe realistic samples. Combined with advances in automation and information technology the field of data science can assist us in dealing with our big data, characterising our uncertainties, and more rapidly identifying useful structure/property relationships. Taking greater advantage of data-driven methods involves thinking differently about our research, but applied appropriately these methods can accelerate the discovery of nanomaterials that are optimised to make the transition from science to technology.
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Affiliation(s)
- Baichuan Sun
- CSIRO Virtual Nanoscience Laboratory, Parkville, VIC 3052, Australia.
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11
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Barnard AS. Challenges in modelling nanoparticles for drug delivery. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2016; 28:023002. [PMID: 26682622 DOI: 10.1088/0953-8984/28/2/023002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Although there have been significant advances in the fields of theoretical condensed matter and computational physics, when confronted with the complexity and diversity of nanoparticles available in conventional laboratories a number of modeling challenges remain. These challenges are generally shared among application domains, but the impacts of the limitations and approximations we make to overcome them (or circumvent them) can be more significant one area than another. In the case of nanoparticles for drug delivery applications some immediate challenges include the incompatibility of length-scales, our ability to model weak interactions and solvation, the complexity of the thermochemical environment surrounding the nanoparticles, and the role of polydispersivity in determining properties and performance. Some of these challenges can be met with existing technologies, others with emerging technologies including the data-driven sciences; some others require new methods to be developed. In this article we will briefly review some simple methods and techniques that can be applied to these (and other) challenges, and demonstrate some results using nanodiamond-based drug delivery platforms as an exemplar.
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Affiliation(s)
- Amanda S Barnard
- CSIRO Virtual Nanoscience Laboratory, 343 Royal Parade, Parkville, Victoria 3052, Australia
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12
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Barron H, Opletal G, Tilley RD, Barnard AS. Dynamic evolution of specific catalytic sites on Pt nanoparticles. Catal Sci Technol 2016. [DOI: 10.1039/c5cy01205h] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Different types of surface defects are needed for specific types of catalytic reactions, and can be promoted or suppressed by varying the temperature and rates during the early stages of growth.
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Affiliation(s)
- Hector Barron
- CSIRO Virtual Nanoscience Laboratory
- Parkville 3052
- Australia
| | - George Opletal
- CSIRO Virtual Nanoscience Laboratory
- Parkville 3052
- Australia
| | - Richard D. Tilley
- UNSW Mark Wainwright Analytical Centre
- Division of Research
- Sydney 2052
- Australia
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