Binary transition metal dichalcogenide monolayers share common properties such as a direct optical bandgap, spin-orbit splittings of hundreds of meV, light–matter interaction dominated by robust excitons and coupled spin-valley states. Here we demonstrate spin-orbit-engineering in Mo(1−x)WxSe2 alloy monolayers for optoelectronics and applications based on spin- and valley-control. We probe the impact of the tuning of the conduction band spin-orbit spin-splitting on the bright versus dark exciton population. For MoSe2 monolayers, the photoluminescence intensity decreases as a function of temperature by an order of magnitude (4–300 K), whereas for WSe2 we measure surprisingly an order of magnitude increase. The ternary material shows a trend between these two extreme behaviours. We also show a non-linear increase of the valley polarization as a function of tungsten concentration, where 40% tungsten incorporation is sufficient to achieve valley polarization as high as in binary WSe2.

Peptoids (poly-N-substituted glycines) are a class of synthetic polymers that are regioisomers of peptides (poly-C-substituted glycines), in which the point of side-chain connectivity is shifted from the backbone C to the N atom. Peptoids have found diverse applications as peptidomimetic drugs, protein mimetic polymers, surfactants, and catalysts. Computational modeling is valuable in the understanding and design of peptoid-based nanomaterials. In this work, we report the bottom-up parameterization of coarse-grained peptoid force fields based on the MARTINI peptide force field against all-atom peptoid simulation data. Our parameterization pipeline iteratively refits coarse-grained bonded interactions using iterative Boltzmann inversion and nonbonded interactions by matching the potential of mean force for chain extension. We assure good sampling of the amide bond cis/trans isomerizations in the all-atom simulation data using parallel bias metadynamics. We develop coarse-grained models for two representative peptoidspolysarcosine (poly­(N-methyl glycine)) and poly­(N-((4-bromophenyl)­ethyl)­glycine)and show their structural and thermodynamic properties to be in excellent accord with all-atom calculations but up to 25-fold more efficient and compatible with MARTINI force fields. This work establishes a new rigorously parameterized coarse-grained peptoid force field for the understanding and design of peptoid nanomaterials at length and time scales inaccessible to all-atom calculations.

Solid-binding peptides (SBPs) recognizing inorganic and synthetic interfaces have enabled a broad range of materials science applications and hold promise as adhesive or morphogenetic control units that can be genetically encoded within desirable or designed protein frameworks. To date, the underlying relationships governing both SBP–surface and SBP–SBP interactions and how they give rise to different adsorption mechanisms remain unclear. Here, we combine protein engineering, surface plasmon resonance characterization, and molecular dynamics (MD) simulations initiated from Rosetta predictions to gain insights on the interplay of amino acid composition, structure, self-association, and adhesion modality in a panel of variants of the Car9 silica-binding peptide (DSAR­GFKK­PGKR) fused to the C-terminus of superfolder green fluorescent protein (sfGFP). Analysis of kinetics, energetics, and MD-predicted structures shows that the high-affinity binding of Car9 to the silanol-rich surface of silica is dominated by electrostatic contributions and a spectrum of several persistent interactions that, along with a high surface population of bound molecules, promote cooperative interactions between neighboring SBPs and higher order structure formation. Transition from cooperative to Langmuir adhesion in sfGFP-Car9 variants occurs in concert with a reduction of stable surface interactions and self-association, as confirmed by atomic force microscopy imaging of proteins exhibiting the two different binding behaviors. We discuss the implications of these results for the de novo design of SBP–surface binding systems.

Ice-nucleation active (INA) bacteria can promote the growth of ice more effectively than any other known material. Using specialized ice-nucleating proteins (INPs), they obtain nutrients from plants by inducing frost damage and, when airborne in the atmosphere, they drive ice nucleation within clouds, which may affect global precipitation patterns. Despite their evident environmental importance, the molecular mechanisms behind INP-induced freezing have remained largely elusive. We investigate the structural basis for the interactions between water and the ice-nucleating protein InaZ from the INA bacterium Pseudomonas syringae. Using vibrational sum-frequency generation (SFG) and two-dimensional infrared spectroscopy, we demonstrate that the ice-active repeats of InaZ adopt a β-helical structure in solution and at water surfaces. In this configuration, interaction between INPs and water molecules imposes structural ordering on the adjacent water network. The observed order of water increases as the interface is cooled to temperatures close to the melting point of water. Experimental SFG data combined with molecular-dynamics simulations and spectral calculations show that InaZ reorients at lower temperatures. This reorientation can enhance water interactions, and thereby the effectiveness of ice nucleation.