A review on microfluidic-assisted nanoparticle synthesis, and their applications using multiscale simulation methods

Discover Nano, Journal Year: 2023, Volume and Issue: 18(1)

Published: Feb. 17, 2023

Abstract Recent years have witnessed an increased interest in the development of nanoparticles (NPs) owing to their potential use a wide variety biomedical applications, including drug delivery, imaging agents, gene therapy, and vaccines, where recently, lipid nanoparticle mRNA-based vaccines were developed prevent SARS-CoV-2 causing COVID-19. NPs typically fall into two broad categories: organic inorganic. Organic mainly include lipid-based polymer-based nanoparticles, such as liposomes, solid polymersomes, dendrimers, polymer micelles. Gold silver NPs, iron oxide quantum dots, carbon silica-based nanomaterials make up bulk inorganic NPs. These are prepared using top-down bottom-up approaches. Microfluidics provide attractive synthesis alternative is advantageous compared conventional methods. The microfluidic mixing-based production methods offer better control achieving desired size, morphology, shape, size distribution, surface properties synthesized technology also exhibits excellent process repeatability, fast handling, less sample usage, yields greater encapsulation efficiencies. In this article, we comprehensive review microfluidic-based passive active mixing techniques for NP synthesis, latest developments. Additionally, summary devices used presented. Nonetheless, despite significant advancements experimental procedures, complete details nanoparticle-based system cannot be deduced from experiments alone, thus, multiscale computer simulations utilized perform systematic investigations. work most common simulation unveiling critical mechanisms involved interaction with other entities, especially therapeutic systems. Finally, analysis provided on challenges microfluidics related future perspectives, large-scale hybrid formulations devices. Graphical abstract

Language: Английский

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Advances in light transverse momenta and optical lateral forces

Advances in Optics and Photonics, Journal Year: 2023, Volume and Issue: 15(3), P. 835 - 835

Published: Aug. 1, 2023

Harnessing linear and angular momenta of light is one the cornerstones in modern optics has found tremendous applications optical circuits, particle manipulation, metrology, quantum information processing, etc. Emerging theoretical protocols experimental explorations have created a surge interest lateral forces, which are perpendicular to wave propagation direction. However, there yet lack comprehensive holistic overview transverse (both angular) as well forces (OLFs). In this article, we first review most recent including spin momentum, skyrmions, from directional side scattering, spin–orbit interaction, surface plasmon polaritons. Since result momentum exchange between matter, consequently gives rise intriguing OLFs, second topic article. Additional non-trivial that combine with other effects thermodynamics, electricity, microfluidics, also discussed. It should be emphasized these ubiquitously exist broad range phenomena often been neglected due their unpredicted underlying physics shortage means, especially prior last decade.

Language: Английский

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Artificial Intelligence for Surface‐Enhanced Raman Spectroscopy

Small Methods, Journal Year: 2023, Volume and Issue: 8(1)

Published: Oct. 27, 2023

Abstract Surface‐enhanced Raman spectroscopy (SERS), well acknowledged as a fingerprinting and sensitive analytical technique, has exerted high applicational value in broad range of fields including biomedicine, environmental protection, food safety among the others. In endless pursuit ever‐sensitive, robust, comprehensive sensing imaging, advancements keep emerging whole pipeline SERS, from design SERS substrates reporter molecules, synthetic route planning, instrument refinement, to data preprocessing analysis methods. Artificial intelligence (AI), which is created imitate eventually exceed human behaviors, exhibited its power learning high‐level representations recognizing complicated patterns with exceptional automaticity. Therefore, facing up intertwining influential factors explosive size, AI been increasingly leveraged all above‐mentioned aspects presenting elite efficiency accelerating systematic optimization deepening understanding about fundamental physics spectral data, far transcends labors conventional computations. this review, recent progresses are summarized through integration AI, new insights challenges perspectives provided aim better gear toward fast track.

Language: Английский

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Bridging Nanomanufacturing and Artificial Intelligence—A Comprehensive Review

Materials, Journal Year: 2024, Volume and Issue: 17(7), P. 1621 - 1621

Published: April 2, 2024

Nanomanufacturing and digital manufacturing (DM) are defining the forefront of fourth industrial revolution—Industry 4.0—as enabling technologies for processing materials spanning several length scales. This review delineates evolution nanomaterials nanomanufacturing in age applications medicine, robotics, sensory technology, semiconductors, consumer electronics. The incorporation artificial intelligence (AI) tools to explore nanomaterial synthesis, optimize processes, aid high-fidelity nanoscale characterization is discussed. paper elaborates on different machine-learning deep-learning algorithms analyzing images, designing nanomaterials, nano quality assurance. challenges associated with application machine- models achieve robust accurate predictions outlined. prospects incorporating sophisticated AI such as reinforced learning, explainable (XAI), big data analytics material process innovation, nanosystem integration

Language: Английский

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High-throughput microfluidic systems accelerated by artificial intelligence for biomedical applications

Lab on a Chip, Journal Year: 2024, Volume and Issue: 24(5), P. 1307 - 1326

Published: Jan. 1, 2024

This review outlines the current advances of high-throughput microfluidic systems accelerated by AI. Furthermore, challenges and opportunities in this field are critically discussed as well.

Language: Английский

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Design of Poly(lactic-co-glycolic acid) nanoparticles in drug delivery by artificial intelligence methods to find the conditions of nanoparticles synthesis

Chemometrics and Intelligent Laboratory Systems, Journal Year: 2025, Volume and Issue: unknown, P. 105335 - 105335

Published: Jan. 1, 2025

Language: Английский

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Machine Learning in Polymer Research

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 9, 2025

Machine learning is increasingly being applied in polymer chemistry to link chemical structures macroscopic properties of polymers and identify patterns the that help improve specific properties. To facilitate this, a dataset needs be translated into machine readable descriptors. However, limited inadequately curated datasets, broad molecular weight distributions, irregular configurations pose significant challenges. Most off shelf mathematical models often need refinement for applications. Addressing these challenges demand close collaboration between chemists mathematicians as must formulate research questions terms while are required refine This review unites both disciplines address curation hurdles highlight advances synthesis modeling enhance data availability. It then surveys ML approaches used predict solid-state properties, solution behavior, composite performance, emerging applications such drug delivery polymer-biology interface. A perspective field concluded importance FAIR (findability, accessibility, interoperability, reusability) integration theory discussed, thoughts on machine-human interface shared.

Language: Английский

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Factors affecting the growth formation of nanostructures and their impact on electrode materials: A systematic review

Materials Today Physics, Journal Year: 2022, Volume and Issue: 27, P. 100844 - 100844

Published: Sept. 14, 2022

Language: Английский

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Computer Vision and Machine Learning Methods for Heat Transfer and Fluid Flow in Complex Structural Microchannels: A Review

Energies, Journal Year: 2023, Volume and Issue: 16(3), P. 1500 - 1500

Published: Feb. 2, 2023

Heat dissipation in high-heat flux micro-devices has become a pressing issue. One of the most effective methods for removing high heat load is boiling transfer microchannels. A novel approach to flow pattern and recognition microchannels provided by combination image machine learning techniques. The support vector method texture characteristics successfully recognizes patterns. To determine bubble dynamics behavior micro-device, features are combined with algorithms applied As result, relationship between evolution established, mechanism revealed.

Language: Английский

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Optimization of microfluidic synthesis of silver nanoparticles: A generic approach using machine learning

Process Safety and Environmental Protection, Journal Year: 2023, Volume and Issue: 193, P. 65 - 74

Published: March 7, 2023

The properties of silver nanoparticles (AgNPs) are affected by various parameters, making optimisation their synthesis a laborious task. This is facilitated in this work concurrent use T-junction microfluidic system and machine learning approach. AgNPs synthesized reducing nitrate with tannic acid the presence trisodium citrate, which has dual role reaction as stabilizing agent. study uses decision tree-guided design experiment method for size AgNPs. developed approach kinetic nucleation growth constants derived from an independent set experiments to account chemistry synthesis, Reynolds number ratio Dean reveal effect hydrodynamics mixing within device storage temperature particle stability after collection. obtained model was used define parameter space additional carried out improve further. numerical results illustrate that well-designed can contribute more effectively development different models (decision tree, random forest XGBoost) opposed randomly added experiments.

Language: Английский

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