Ambient pressure dried tetrapropoxysilane-based silica aerogels with high specific surface area

Parale, Vinayak G.; Han, Wooje; Jung, Hae Noo Ree; Lee, Kyu Yeon; Park, Hyung Ho

doi:10.1016/j.solidstatesciences.2017.10.016

Cited by 40 publications

(11 citation statements)

References 27 publications

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“…The silica aerogel graph database (SiAGDB) (see the discussion in Supporting Information section 1) includes the synthesis and processing variables of approximately 10 3 silica aerogel materials from previous publications. ,− ,− ,− ,,,,,− …”

Section: Methodsmentioning

confidence: 99%

Silica Aerogel Synthesis/Process–Property Predictions by Machine Learning

et al. 2023

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Silica aerogels are mesoporous high surface area materials with extensive synthetic and processing conditions. To effectively synthesize aerogels, the impact of synthetic pathways on the resulting aerogel properties must be understood prior to experimental investigation. We develop an information architecture, the silica aerogel graph database (10 3 ), and a supervised machine learning neural network regression model to examine these relationships. The property graph database enables rapid queries and visualization of the impact of the synthesis and processing conditions on the final aerogel properties. The model maps from silica aerogel synthetic and processing conditions to predict the aerogel BET surface area with an average error of 109 ± 84 m 2 /g. Following a validation experiment, the model was shown to predict the aerogel surface area from new synthetic and processing conditions with an error of less than 5%. The experiment demonstrates the usefulness of the model in surface area prediction through the compatibility between computational and experimental results. Both in its current form and with further expansion, the developed graph database could reduce experimental dimensionality, time, and resources, enabling the successful synthesis of high surface area silica aerogels, which are advantageous for applications including thermal insulation, sorption media, and catalysis.

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Section: Methodsmentioning

confidence: 99%

Silica Aerogel Synthesis/Process–Property Predictions by Machine Learning

et al. 2023

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“…The hydrophobicity of SA dried at atmospheric pressure gives them structural stability under humidity. [18] If hydrophobic SA is filled in the pore structure of hydrogels, it can achieve a lightweight effect similar to filling with air. [19] Tan et al designed flexible and self-floating PVA-based hybrid hydrogels for solar steam generation and synthesized them by assembling two types of functional particles within the network, which showed low compressive strength (≈0.1 MPa).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ultralight, Heat‐Insulated, and Tough PVA Hydrogel Hybridized with SiO₂@cellulose Nanoclaws Aerogel via the Synergy of Hydrophilic and Hydrophobic Interfacial Interactions

Xie

Zhang

et al. 2023

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Lightweight porous hydrogels provide a worldwide scope for functional soft mateirals. However, most porous hydrogels have weak mechanical strength, high density (>1 g cm−3), and high heat absorption due to weak interfacial interactions and high solvent fill rates, which severely limit their application in wearable soft‐electronic devices. Herein, an effective hybrid hydrogel‐aerogel strategy to assemble ultralight, heat‐insulated, and tough polyvinyl alcohol (PVA)/SiO2@cellulose nanoclaws (CNCWs) hydrogels (PSCG) via strong interfacial interactions with hydrogen bonding and hydrophobic interaction is demonstrated. The resultant PSCG has an interesting hierarchical porous structure from bubble template (≈100 µm), PVA hydrogels networks introduced by ice crystals (≈10 µm), and hybrid SiO2 aerogels (<50 nm), respectively. PSCG shows unprecedented low density (0.27 g cm−3), high tensile strength (1.6 MPa) & compressive strength (1.5 MPa), excellent heat‐insulated ability, and strain‐sensitive conductivity. This lightweight porous and tough hydrogel with an ingenious design provides a new way for wearable soft‐electronic devices.

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“…The advantage of the sol to gel formation technique is better to control over size and microstructure [12,13]. Using this approach, the properties and structures of silica aerogels can be tailored to specific applications by optimizing sol-gel processing parameters [14]. Although the preparation methods, precursor, solvents, silylating agent and different physicochemical parameters of silica aerogels are widely investigated, the reports on the effect of pH on the various physicochemical parameters of silica aerogels are rare.…”

Section: Introductionmentioning

confidence: 99%

Physicochemical properties of ambient pressure dried surface modified silica aerogels: effect of pH variation

et al. 2020

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This work demonstrates the synthesis of hydrophobic silica aerogels from silicic acid with pH variations by using a costeffective and safe ambient pressure drying process. The work aims to evaluate the effect of pH variation on physicochemical properties of silica aerogels by standard techniques. In the present investigation, we have selected hexane as the solvent and trimethylchlorosilane/hexane was used to perform the surface modification of wet gel in order to elude the contraction and disintegration of gel association subsequent to a drying process. The effect pH on gelation in the form hydrolysis and condensation as well as on amorphous structure, physical properties such as density, thermal stability, surface area, pore-volume, pore radius, optical transmittance were investigated. FTIR spectroscopy was used to confirm the silylation (surface modification) of the prepared silica aerogel samples. Water contact angles were measured to verify the hydrphobic behaviour of all the samples. Among the prepared pH varied samples, the sample having pH ~ 5 shows better results such as high optical transmittance, thermal stability, hydrophobicity and high surface area.

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Ambient pressure dried tetrapropoxysilane-based silica aerogels with high specific surface area

Cited by 40 publications

References 27 publications

Silica Aerogel Synthesis/Process–Property Predictions by Machine Learning

Silica Aerogel Synthesis/Process–Property Predictions by Machine Learning

Ultralight, Heat‐Insulated, and Tough PVA Hydrogel Hybridized with SiO₂@cellulose Nanoclaws Aerogel via the Synergy of Hydrophilic and Hydrophobic Interfacial Interactions

Physicochemical properties of ambient pressure dried surface modified silica aerogels: effect of pH variation

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Ambient pressure dried tetrapropoxysilane-based silica aerogels with high specific surface area

Cited by 40 publications

References 27 publications

Silica Aerogel Synthesis/Process–Property Predictions by Machine Learning

Silica Aerogel Synthesis/Process–Property Predictions by Machine Learning

Ultralight, Heat‐Insulated, and Tough PVA Hydrogel Hybridized with SiO2@cellulose Nanoclaws Aerogel via the Synergy of Hydrophilic and Hydrophobic Interfacial Interactions

Physicochemical properties of ambient pressure dried surface modified silica aerogels: effect of pH variation

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Product

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Ultralight, Heat‐Insulated, and Tough PVA Hydrogel Hybridized with SiO₂@cellulose Nanoclaws Aerogel via the Synergy of Hydrophilic and Hydrophobic Interfacial Interactions