We synthesized novel amphiphilic hyperbranched polymers (HBPs) with variable contents of weakly ionically tethered thermoresponsive poly­(N-isopropylacrylamide) (PNIPAM) macrocations in contrast to traditional covalent linking. Their assembling behavior was studied below and above the lower critical solution temperature (LCST). The HBPs underwent a morphological transition under changing temperature and ionic strength due to the LCST transition of PNIPAM and the reduction in the ionization degree of terminal ionic groups, respectively. We suggest that, in contrast to traditional branched polymers, ionically linked PNIPAM macrocations can reversibly disassociate from the sulfonate groups and form mobile coronas, endowing the dynamic micellar morphologies. In addition, assembly at the air–water interface confined PNIPAM macrocations and resulted in the formation of heterogeneous Langmuir–Blodgett (LB) monolayers with diverse surface morphologies for different peripheral compositions with circular domains formed in the condensed state. The HBPs with 25% PNIPAM showed larger and more stable circular domains that were partially preserved at high compression than those of HBPs with 50% PNIPAM. Moreover, the LB monolayers showed variable surface mechanical and surface charge distribution, which can be attributed to net dipole redistribution caused by the behavior of mobile PNIPAM macrocations and core sulfonate groups.

Magnetic nanoparticles (MNPs) can organize into novel structures in solutions with excellent order and unique geometries. However, studies of the self-assembly of smaller MNPs are challenging due to a complicated interplay between external magnetic fields and van der Waals, electrostatic, dipolar, steric, and hydrodynamic interactions. Here, we present a novel all-atom molecular dynamics simulation method to enable detailed studies of the dynamics, self-assembly, structure, and properties of MNPs as a function of core sizes and shapes, ligand chemistry, solvent properties, and external field. We demonstrate the use and effectiveness of the model by simulating the self-assembly of oleic acid ligand-functionalized magnetite (Fe 3 O 4 ) nanoparticles, with spherical and cubic shapes, into rings, lines, chains, and clusters under a uniform external magnetic field. We found that the long-range electrostatic interactions can favor the formation of a chain over a ring, the ligands promote MNP cluster growth, and the solvent can reduce the rotational diffusion of the MNPs. The algorithm has been parallelized to take advantage of multiple processors of a modern computer and can be used as a plugin for the popular simulation software LAMMPS to study the behavior of small MNPs and gain insights into the physics and chemistry of different magnetic assembly processes with atomistic details.

Inorganic colloidal nanoparticle (NP) properties can be tuned by stripping stabilizing ligands using a poor solvent. However, the mechanism behind ligand stripping is poorly understood, in part because in situ measurements of ligand stripping are challenging at the nanoscale. Here, we investigate ethanol solvent-mediated oleylamine ligand stripping from magnetite (Fe3O4) NPs in different compositions of ethanol/hexane mixtures using atomistic molecular dynamics (MD) simulations and thermogravimetric analysis (TGA). Our study elucidates a complex interplay of ethanol interactions with system components and indicates the existence of a threshold concentration of ∼34 vol % ethanol, above which ligand stripping saturates. Moreover, hydrogen bonding between ethanol and stripped ligands inhibits subsequent readsorption of the ligands on the NP surface. A proposed modification of the Langmuir isotherm explains the role of the enthalpy of mixing of the ligands and solvents on the ligand stripping mechanism. A good agreement between the MD predictions and TGA measurements of ligand stripping from Fe3O4 NPs validates the simulation observations. Our findings demonstrate that the ligand coverage of NPs can be controlled by using a poor solvent below the threshold concentration and highlight the importance of ligand–solvent interactions that modulate the properties of colloidal NPs. The study also provides an approach for a detailed in silico study of ligand stripping and exchange from colloidal NPs that are crucial for applications of NPs spanning self-assembly, optoelectronics, nanomedicine, and catalysis.

Since the launch of the Materials Genome Initiative (MGI) the field of materials informatics (MI) emerged to remove the bottlenecks limiting the pathway towards rapid materials discovery. Although the machine learning (ML) and optimization techniques underlying MI were developed well over a decade ago, programs such as the MGI encouraged researchers to make the technical advancements that make these tools suitable for the unique challenges in materials science and engineering. Overall, MI has seen a remarkable rate in adoption over the past decade. However, for the continued growth of MI, the educational challenges associated with applying data science techniques to analyse materials science and engineering problems must be addressed. In this paper, we will discuss the growing use of materials informatics in academia and industry, highlight the need for educational advances in materials informatics, and discuss the implementation of a materials informatics course into the curriculum to jump-start interested students with the skills required to succeed in materials informatics projects.