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Supramolecular polymer blends (SPBs) represent a versatile class of polymers whose morphology directly determines their macroscopic properties. However, rational design of SPBs remains hindered by the lack of predictive models describing how molecular features and intermolecular interactions determine morphology. Here, we report a data-driven high-throughput workflow integrating modular synthesis, robotic sample formulation and processing, automated morphology characterization, and machine learning (ML) for SPBs discovery. Using a plug-and-play modular synthetic strategy, 33 hydrogen-bonding end-functional homopolymer precursors were prepared and orthogonally paired to fabricate 260 SPBs within one day. A custom automated atomic force microscopy (AFM) protocol enabled systematic morphological characterization, producing 2340 images with little human intervention. Average phase separation sizes (e.g. domain spacings) was extracted from processed AFM data using multiple complementary approaches and applied to ML model training. Leveraging the high-throughput sample formation and characterization, a high-quality database was curated for SPBs, allowing training of ML models. Guided by support vector regression (SVR) model, target morphologies of 50, 100, and 150 nm were successfully predicted and experimentally validated. This work demonstrates the potential of coupling high-throughput experimentation with ML to accelerate polymer blends phase discovery, providing one of the first large-scale, experimentally derived datasets specifically designed for supramolecular polymer research. 

Abstract We study the effect of strain on the magnetic properties and magnetization configurations in nanogranular Fe_xGe ${}_{1-x}$films ( $x=0.53\pm 0.05$) with and without B20 FeGe nanocrystals surrounded by an amorphous structure. Relaxed films on amorphous silicon nitride membranes reveal a disordered skyrmion phase while films near and on top of a rigid substrate favor ferromagnetism and an anisotropic hybridization of Fedlevels and spin-polarized Gespband states. The weakly coupled topological states emerge at room temperature and become more abundant at cryogenic temperatures without showing indications of pinning at defects or confinement to individual grains. These results demonstrate the possibility to control magnetic exchange and topological magnetism by strain and inform magnetoelasticity-mediated voltage control of topological phases in amorphous quantum materials. 

Abstract Metal-organic decomposition epitaxy is an economical wet-chemical approach suitable to synthesize high-quality low-spin-damping films for resonator and oscillator applications. This work reports the temperature dependence of ferromagnetic resonances and associated structural and magnetic quantities of yttrium iron garnet nanofilms that coincide with single-crystal values. Despite imperfections originating from wet-chemical deposition and spin coating, the quality factor for out-of-plane and in-plane resonances approaches 600 and 1000, respectively, at room temperature and 40 GHz. These values increase with temperature and are 100 times larger than those offered by commercial devices based on complementary metal-oxide semiconductor voltage-controlled oscillators at comparable production costs. 

Two-dimensional heterostructures composed of layers with slightly different lattice vectors exhibit new periodic structure known as moiré lattices, which, in turn, can support novel correlated and topological phenomena. Moreover, moiré superstructures can emerge from multiple misaligned moiré lattices or inhomogeneous strain distributions, offering additional degrees of freedom in tailoring electronic structure. High-resolution imaging of the moiré lattices and superstructures is critical for understanding the emerging physics. Here, we report the imaging of moiré lattices and superstructures in graphene-based samples under ambient conditions using an ultrahigh-resolution implementation of scanning microwave impedance microscopy. Although the probe tip has a gross radius of ~100 nm, spatial resolution better than 5 nm is achieved, which allows direct visualization of the structural details in moiré lattices and the composite super-moiré. We also demonstrate artificial synthesis of novel superstructures, including the Kagome moiré arising from the interplay between different layers. 

Abstract The in‐plane packing of gold (Au), polystyrene (PS), and silica (SiO₂) spherical nanoparticle (NP) mixtures at a water–oil interface is investigated in situ by UV–vis reflection spectroscopy. All NPs are functionalized with carboxylic acid such that they strongly interact with amine‐functionalized ligands dissolved in an immiscible oil phase at the fluid interface. This interaction markedly increases the binding energy of these nanoparticle surfactants (NPSs). The separation distance between the Au NPSs and Au surface coverage are measured by the maximum plasmonic wavelength (λ_max) and integrated intensities as the assemblies saturate for different concentrations of non‐plasmonic (PS/SiO₂) NPs. As the PS/SiO₂content increases, the time to reach intimate Au NP contact also increases, resulting from their hindered mobility. λ_maxchanges within the first few minutes of adsorption due to weak attractive inter‐NP forces. Additionally, a sharper peak in the reflection spectrum at NP saturation reveals tighter Au NP packing for assemblies with intermediate non‐plasmonic NP content. Grazing incidence small angle X‐ray scattering (GISAXS) and scanning electron microscopy (SEM) measurements confirm a decrease in Au NP domain size for mixtures with larger non‐plasmonic NP content. The results demonstrate a simple means to probe interfacial phase separation behavior using in situ spectroscopy as interfacial structures densify into jammed, phase‐separated NP films.