Carbon Fiber Reinforced Composites: Study of Modification Effect on Weathering-Induced Ageing via Nanoindentation and Deep Learning

Konstantopoulos, Georgios; Semitekolos, Dionisis; Koumoulos, Elias P.; Charitidis, Costas A.

doi:10.3390/nano11102631

Cited by 7 publications

(8 citation statements)

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“…CNTs can be further assembled into macroscopic materials, such as carbon nanofibers (CNFs), which find many uses, especially in high-performance composites and energy devices [ 332 , 333 , 334 , 335 , 336 ]. In this case, they have been decorated with Fe(III) complexes to mimic oxidases [ 337 ], peroxidases, and catalases for sensing and environmental technology [ 338 ].…”

Section: Cnms For Enzyme Mimicry Inhibition or Monitoringmentioning

confidence: 99%

“…Fullerene derivatives have been envisaged for the inhibition of a variety of enzymes, including recent examples of HIV-1 protease [346], ribonuclease A [347], glycosidases CNTs can be further assembled into macroscopic materials, such as carbon nanofibers (CNFs), which find many uses, especially in high-performance composites and energy devices [332][333][334][335][336]. In this case, they have been decorated with Fe(III) complexes to mimic oxidases [337], peroxidases, and catalases for sensing and environmental technology [338].…”

Section: Cnms As Enzyme Inhibitorsmentioning

confidence: 99%

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Carbon Nanomaterials (CNMs) and Enzymes: From Nanozymes to CNM-Enzyme Conjugates and Biodegradation

et al. 2022

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Carbon nanomaterials (CNMs) and enzymes differ significantly in terms of their physico-chemical properties—their handling and characterization require very different specialized skills. Therefore, their combination is not trivial. Numerous studies exist at the interface between these two components—especially in the area of sensing—but also involving biofuel cells, biocatalysis, and even biomedical applications including innovative therapeutic approaches and theranostics. Finally, enzymes that are capable of biodegrading CNMs have been identified, and they may play an important role in controlling the environmental fate of these structures after their use. CNMs’ widespread use has created more and more opportunities for their entry into the environment, and thus it becomes increasingly important to understand how to biodegrade them. In this concise review, we will cover the progress made in the last five years on this exciting topic, focusing on the applications, and concluding with future perspectives on research combining carbon nanomaterials and enzymes.

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Section: Cnms For Enzyme Mimicry Inhibition or Monitoringmentioning

confidence: 99%

Section: Cnms As Enzyme Inhibitorsmentioning

confidence: 99%

Carbon Nanomaterials (CNMs) and Enzymes: From Nanozymes to CNM-Enzyme Conjugates and Biodegradation

et al. 2022

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“…Koumoulos et al showed that carbon fibers added into poly(methacrylic acid) (PMAA) reinforced the interphasial properties. The modified PMAA had the unique molecular weight of grafted macromolecules and different chain-length brushlike structures, which enabled the composite to maintain better mechanical properties after weathering . Zhang et al introduced hyperbranched polysiloxane (HBPSi) to poly(amic acid) (PAA) through chemical bonds between the amino groups of HBPSi and reactive sites of the polymer.…”

Section: Introductionmentioning

confidence: 99%

Oil-Soluble Ultraviolet-Absorbing Carbon Dots Dispersed in Polyethylene Films as Antiaging Materials

Qiu

et al. 2023

ACS Appl. Nano Mater.

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Ultraviolet (UV) absorbents are widely used in coatings and polymers owing to their remarkable absorbance of UV irradiation. As a new type of organic UV absorbent, carbon dots (CDs) have presented outstanding UV absorption properties. However, the use of water-soluble reactants in the synthesis process of most CDs makes them easy to dissolve in water, which is not conducive to their use in the field of thin films. In this paper, we report an effective hydrothermal method to prepare threecomponent carbon dots (Im-CDs) from sodium citrate, ethylenediamine, and imidazole and then modify the surface to obtain the final product (AOT-CDs) by docusate sodium. The AOT-CDs exhibited a strong UV absorption capacity to UVA and UVB but a transmittance in the visible region both in solution and in polymers. In addition, docusate sodium is regarded as a suitable surface modifier to transfer Im-CDs from water to various organic solvents. When the excellent oil-soluble AOT-CDs are applied to a polyethylene film, the properties of the films, including the efficiency of UV shielding, mechanical property, and aging time, can be effectively tuned by changing the concentration of AOT-CDs. Our full-band UV-shielding films with CDs show no obvious degradation in the process of accelerated UV aging for dozens of days. Due to their ecofriendliness and good chemical and thermal stability in films, AOT-CDs are expected to become competitive candidates for next-generation UV absorbents.

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“…Beyond process control, AI and machine learning hold a lot of promise to bridge this gap with their empirical character, as till today rapid characterization tools have been exploited with high accuracy for the discovery of materials and immunotherapies, materials reinforcement/failure/toxicity mechanism recognition, structural characterization, phase detection and quantification, and anomaly detection [ 3 , 25 , 31 , 33 , 34 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ]. While machine learning and AI are already well established in the fields of statistics, economics, and bioinformatics, their utilization in nanotechnology is relatively new [ 44 ].…”

Section: Introductionmentioning

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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Carbon Fiber Reinforced Composites: Study of Modification Effect on Weathering-Induced Ageing via Nanoindentation and Deep Learning

Cited by 7 publications

References 50 publications

Carbon Nanomaterials (CNMs) and Enzymes: From Nanozymes to CNM-Enzyme Conjugates and Biodegradation

Carbon Nanomaterials (CNMs) and Enzymes: From Nanozymes to CNM-Enzyme Conjugates and Biodegradation

Oil-Soluble Ultraviolet-Absorbing Carbon Dots Dispersed in Polyethylene Films as Antiaging Materials

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

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