Designing bioinspired green nanosilicas using statistical and machine learning approaches

Dewulf, Luc; Chiacchia, Mauro; Yeardley, Aaron S.; Milton, Robert A.; Brown, Solomon; Patwardhan, Siddharth V.

doi:10.1039/d0me00167h

Cited by 7 publications

(20 citation statements)

References 54 publications

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“… Overview of BIS synthesis, formation pathways, their compositional subtypes, and particle structures. (a) The chemical formation of bioinspired silica (image reproduced with permission from Dewulf et al) 16 and (b) the physical formation of bioinspired silica. (c) Three compositional subtypes of bioinspired silica.…”

Section: Overview Of Bioinspired Silicamentioning

confidence: 99%

“…The gray region enables to synthesize silica with the constraints that the yield should exceed 60 mol % and the BET surface area should exceed 100 m 2 /g. Figures reproduced with permission from Dewulf et al 16 …”

Section: Production Capabilitymentioning

confidence: 99%

“… 44 In earlier work, an unproven multistep nonclassical formation pathway was postulated (see Figure 3 b). In terms of understanding the BIS reaction pathways and, more specifically, elucidating the molecular-scale mechanisms that underpin synthesis–property relationships, two avenues of inquiry have been pursued recently: a sequential DoE strategy for systematic and quantitative investigation of the BIS system’s reaction space and 16 a combination of experimental measurements (advanced characterization, including solid state NMR 45 ) and computation (multiscale modeling, including molecular dynamics simulations 46 ) to investigate the additive-silica interface at molecular length-scales. …”

Section: Pathway Understandingmentioning

confidence: 99%

“…a sequential DoE strategy for systematic and quantitative investigation of the BIS system’s reaction space and 16 …”

Section: Pathway Understandingmentioning

confidence: 99%

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Recent Advances in Enabling Green Manufacture of Functional Nanomaterials: A Case Study of Bioinspired Silica

Pilling

Patwardhan

2022

ACS Sustainable Chem. Eng.

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Global specialty silica production is over 3 million tonnes per annum with diverse applications across sectors and an increasing demand for more complex material structures and surface chemistries. Commercial manufacturing of high-value silica nanomaterials is energy and resource intensive. In order to meet market needs and mitigate environmental impacts, new synthesis methods for these porous materials are required. The development of the bioinspired silica (BIS) product system, which is the focus of this review, provides a potential solution to this challenge. BIS is a versatile and greener route with the prospect of good scalability, attractive process economics and well controlled product materials. The potential of the system lies not only in its provision of specific lead materials but also, as itself, a rich design-space for the flexible and potentially predictive design of diverse sustainable silica nanomaterials. Realizing the potential of this design space, requires an integrative mind-set, which enables parallel and responsive progression of multiple and dependent research strands, according to need, opportunities, and emergent knowledge. Specifically, this requires development of detailed understanding of (i) the pathways and extent of material diversity and control, (ii) the influences and mechanisms of scale-up, and (iii) performance, economic and environmental characteristics and sensitivities. Crucially, these need to be developed for the system overall, which sits in contrast to a more traditional research approach, which focuses initially on the discovery of specific material leads at the laboratory scale, leaving scale-up, commercialization, and, potentially, pathway understanding to be considered as distinctly separate concerns. The intention of this review is to present important recent advances made in the field of BIS. Specifically, advances made along three research themes will be discussed: (a) particle formation pathways, (b) product design, and (c) scale-up and manufacture. These advances include first quantitative investigation of synthesis-product relationships, first structured investigation of mixing effects, preparation of a broad range of functionalized and encapsulated silica materials and continued industrial engagement and market research. We identify future challenges and provide an important foundation for the development of new research avenues. These include the need to develop comprehensive and predictive product design models, to understand markets in terms of product cost, performance and environmental considerations, and to develop capabilities enabling rapid prototyping and scale-up of desired nanomaterials.

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Section: Overview Of Bioinspired Silicamentioning

confidence: 99%

Section: Production Capabilitymentioning

confidence: 99%

Section: Pathway Understandingmentioning

confidence: 99%

“…a sequential DoE strategy for systematic and quantitative investigation of the BIS system’s reaction space and 16 …”

Section: Pathway Understandingmentioning

confidence: 99%

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Recent Advances in Enabling Green Manufacture of Functional Nanomaterials: A Case Study of Bioinspired Silica

Pilling

Patwardhan

2022

ACS Sustainable Chem. Eng.

Self Cite

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“…It was shown that Si precursor concentration and Si:N ratio determine the precipitation occurrence. An optimization regarding the reduction of the effort spent in experimental verification was realized by using a sequential design in order to efficiently perform pre-screening and screening, and subsequently the optimization of the experiments [ 69 ].…”

Section: In Silico Materials Developmentmentioning

confidence: 99%

Digital Innovation Enabled Nanomaterial Manufacturing; Machine Learning Strategies and Green Perspectives

Konstantopoulos

Koumoulos²,

Charitidis

2022

Nanomaterials

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Machine learning has been an emerging scientific field serving the modern multidisciplinary needs in the Materials Science and Manufacturing sector. The taxonomy and mapping of nanomaterial properties based on data analytics is going to ensure safe and green manufacturing with consciousness raised on effective resource management. The utilization of predictive modelling tools empowered with artificial intelligence (AI) has proposed novel paths in materials discovery and optimization, while it can further stimulate the cutting-edge and data-driven design of a tailored behavioral profile of nanomaterials to serve the special needs of application environments. The previous knowledge of the physics and mathematical representation of material behaviors, as well as the utilization of already generated testing data, received specific attention by scientists. However, the exploration of available information is not always manageable, and machine intelligence can efficiently (computational resources, time) meet this challenge via high-throughput multidimensional search exploration capabilities. Moreover, the modelling of bio-chemical interactions with the environment and living organisms has been demonstrated to connect chemical structure with acute or tolerable effects upon exposure. Thus, in this review, a summary of recent computational developments is provided with the aim to cover excelling research and present challenges towards unbiased, decentralized, and data-driven decision-making, in relation to increased impact in the field of advanced nanomaterials manufacturing and nanoinformatics, and to indicate the steps required to realize rapid, safe, and circular-by-design nanomaterials.

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Elucidating the prospects of paddy straw as a potential source of nanosilica: A road map towards sustainable agriculture, bioeconomy and entrepreneurship

Singh,

Chowdhary,

Sharma

2024

Journal of Cleaner Production

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Designing bioinspired green nanosilicas using statistical and machine learning approaches

Abstract: This is a first comparison of the sequential design of experiments strategy and global sensitivity analysis for nanomaterials, thus enabling sustainable product and process design in future.

Cited by 7 publications

References 54 publications

Recent Advances in Enabling Green Manufacture of Functional Nanomaterials: A Case Study of Bioinspired Silica

Recent Advances in Enabling Green Manufacture of Functional Nanomaterials: A Case Study of Bioinspired Silica

Digital Innovation Enabled Nanomaterial Manufacturing; Machine Learning Strategies and Green Perspectives

Elucidating the prospects of paddy straw as a potential source of nanosilica: A road map towards sustainable agriculture, bioeconomy and entrepreneurship

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