The number of applications of informatics or data-driven discovery is growing in many fields, including materials science. The large amount of data that is readily available, combined with high-level statistical algorithms, is proving to be extremely useful in developing complex predictive models with little to no human supervision or bias. However, in the field of soft matter, which includes complex materials such as polymers, liquids, emulsions, colloids, and gels, there is a slower adoption of informatics strategies than in adjacent fields. Here, the current state of soft matter informatics is discussed. Challenges specific to soft materials, including data classification, various degrees of organization at multiple length scales, and process-dependent properties require unique approaches by researchers in order to develop robust informatics approaches in soft matter. The current ability to extract and analyze the information from the PoLyInfo database is demonstrated by the fitting of the Flory-Fox equation for glass transition temperature for several polymers. This Progress Report serves to introduce and excite the scientific community about the remarkable potential of informatics for exploring the properties of soft materials.
In contrast to small molar mass compounds, detailed structural investigations of inorganic coreorganic ligand shell hybrid nanoparticles remain challenging. Assessment of batch reaction induced heterogeneities of surface chemical properties and their correlation with particle size has been a particularly long-standing issue. Applying a combination of high performance liquid chromatography (HPLC) and gel permeation chromatography (GPC) to ultrasmall (< 10 nm diameter) poly(ethylene glycol) coated (PEGylated) fluorescent core-shell silica nanoparticles, here we elucidate previously unknown surface heterogeneities resulting from varying dye conjugation to nanoparticle silica cores and surfaces. Heterogeneities are predominantly governed by dye charge as corroborated by molecular dynamics simulations. We demonstrate that this insight enables development of synthesis protocols to achieve PEGylated and targeting ligand functionalized PEGylated silica nanoparticles with dramatically improved surface chemical homogeneity as evidenced by single peak HPLC chromatograms. Since surface chemical properties are key to all nanoparticle interactions, we expect these methods and fundamental insights to become relevant to a number of systems for applications including bioimaging and nanomedicine.
Nanoparticles (NPs) play increasingly important roles in nanotechnology and nanomedicine in which nanoparticle surface chemistry allows for control over interactions with other nanoparticles and biomolecules. In particular, for applications in drug and gene delivery, a fundamental understanding of the NP-nucleic acid interface allows for development of more efficient and effective nanoparticle carriers. Computational modeling can provide insights of processes occurring at the inorganic NP-nucleic interface in detail that is difficult to access by experimental methods. With recent advances such as the use of graphics processing units (GPUs) for simulations, computational modeling has the potential to give unprecedented insight into inorganic-biological interfaces via the examination of increasingly large and complex systems. In this Topical Review, we briefly review computational methods relevant to the interactions of inorganic NPs and nucleic acids and highlight recent insights obtained from various computational methods that were applied to studies of inorganic nanoparticle-nanoparticle and nanoparticle-nucleic acid interfaces.
In this work, an all-atom molecular dynamics simulation technique was employed to gain insight into the dynamic structure of the solvation shell formed around C60 and phenyl-C61-butyric acid methyl ester (PCBM) in nine aromatic solvents. A new method was developed to visualize and quantify the distribution of solvent molecule orientations in the solvation shell. A strong positive correlation was found between the regularity of solvent molecule orientations in the solvation shell and the experimentally obtained solubility limits for both C60 and PCBM. This correlation was extended to predict a solubility of 36 g/L for PCBM in 1,2,4-trimethylbenze. The relationship between solvation-shell structure and solubility provided detailed insight into solvate formation of C60 and solvation in relation to solvent molecular structure and properties. The determined dependence of the solvation-shell structure on the geometric shape of the solvent might allow for enhanced control of fullerene solution-phase behavior during processing by chemically tailoring the solvent molecular structure, potentially diminishing the need for costly and environmentally harmful halogenated solvents and/or additives.
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