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Abstract Hierarchical plasmonic biomaterials constructed from small nanoparticles (NPs) that combine into larger micron‐sized structures exhibit unique properties that can be harnessed for various applications. Using diffusion‐limited aggregation (DLA) and defined peptide sequences, we developed fractal silver biomaterials with a Brownian tree structure. This method avoids complex redox chemistry and allows precise control of interparticle distance and material morphology through peptide design and concentration. Our systematic investigation revealed how peptide charge, length, and sequence impact biomaterial morphology, confirming that peptides act as bridging motifs between particles and induce coalescence. Characterization through spectroscopy and microscopy demonstrated that arginine‐based peptides are optimal for fractal assembly based on both quantitative and qualitative measurements. Additionally, our study of diffusion behavior confirmed the effect of particle size, temperature, and medium viscosity on nanoparticle mobility. This work also provides insights into the facet distribution in silver NPs and their assembly mechanisms, offering potential advancements in the design of materials for medical, environmental, and electronic applications.
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This content will become publicly available on December 1, 2025
Prediction of the aggregation rate of nanoparticles in porous media in the diffusion-controlled regime
Abstract The fate and aggregation of nanoparticles (NPs) in the subsurface are important due to potentially harmful impacts on the environment and human health. This study aims to investigate the effects of flow velocity, particle size, and particle concentration on the aggregation rate of NPs in a diffusion-limited regime and build an equation to predict the aggregation rate when NPs move in the pore space between randomly packed spheres (including mono-disperse, bi-disperse, and tri-disperse spheres). The flow of 0.2 M potassium chloride (KCl) through the random sphere packings was simulated by the lattice Boltzmann method (LBM). The movement and aggregation of cerium oxide (CeO2) particles were then examined by using a Lagrangian particle tracking method based on a force balance approach. This method relied on Newton's second law of motion and took the interaction forces among particles into account. The aggregation rate of NPs was found to depend linearly on time, and the slope of the line was a power function of the particle concentration, the Reynolds (Re) and Schmidt (Sc) numbers. The exponent for theScnumber was triple that of theRenumber, which was evidence that the random movement of NPs has a much stronger effect on the rate of diffusion-controlled aggregation than the convection.
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- Award ID(s):
- 2317726
- PAR ID:
- 10553440
- Publisher / Repository:
- Nature
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 14
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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