Gypsum precipitation is a common process observed in diverse natural settings, offering valuable insights into (paleo)environmental conditions. It also holds significant industrial value, notably in wallboard production. However, its precipitation also poses severe challenges, for example, during water desalination. Despite numerous experimental and computational studies on gypsum since the late 19th century, the growth behavior and crystal habit remain poorly understood. In this work, we studied the nanoscale growth mechanisms controlling the formation of gypsum crystals from supersaturated solutions. We developed a method for obtaining oriented samples of natural idiomorphic gypsum crystals, enabling atomic force microscopy (AFM) imaging and microtopography characterization of all facets. Using this novel approach we (re-)examined the extensively studied {010} form, and, for the first time, the {120}, {-111}, and {011} forms. Remarkably, each form is dominated by a specific growth behavior, including cluster-mediated growth for {010}, stepped face growth for {120}, 2D nucleation and spiral growth for the {-111} form, and rough growth for {011}. These experimental findings differ from theoretical predictions, where all four forms are considered flat faces (F faces). We further demonstrate that the interplay between growth mechanisms of different forms, and the control that external factors exert on these, are the two key factors that dictate the crystal habit. Overall, this study establishes a framework for linking gypsum crystal morphology to the prevailing environmental conditions during growth. This understanding is critical not only for comprehending gypsum deposit formation in the geological record but also for the processing of advanced geomaterials and more effective anti-scaling strategies.
The ability to minimize low-temperature acoustic loss in amorphous materials would have implications in fields as wide-ranging as gravitational wave detection and quantum computing. In this paper, we measure the internal friction between 300 mK and room temperature of several thin silica films deposited by ion beam sputtering onto ultra-high-Q silicon resonators. The measurements reveal internal configurations of as-deposited films that are markedly different from that of bulk silica. Over a broad temperature range, the films' internal frictions differ from one another by a factor of two; by contrast, a review shows that sub-MHz internal friction measurements of bulk silica fall within a 35% band with a pronounced main absorption peak between 20 K and 40 K. This peak is absent in the films presented here, except for one film that had been annealed at 900 degrees C. Annealing at 500 degrees C erased the thermal histories of the other thin films to create internal friction values that are consistent from film-to-film but yet still markedly different from those of the bulk below 100 K, while creating the steep bulk-like drop-off above 100 K that the as-deposited films lacked. In the context of theoretical structural modeling, our results suggest that exposure to temperatures of at least 900 degrees C is needed to form the network of tetrahedra considered characteristic of amorphous silica. The present measurements, especially when compared alongside previous work, appear to show that these structures are suppressed in many thin film preparations. These measurements also show, for as-deposited films, an excess of excitations in the 0.15-0.3 eV range which can be annealed away to bring about the Q-1 drop-off above the main absorption peak. The shear moduli of all the films are qualitatively similar to bulk silica, with a positive temperature coefficient above a minimum near 60 K and a negative temperature coefficient below.
Despite the huge development of machine learning (ML) models to predict molecular properties, ML predictors for the molecular first hyperpolarizability tensors (β) are scarce, and solvation effects are rarely taken into account in the model. In this work, we develop and compare three ML approaches to predict the β tensor of water molecules embedded in an explicit liquid water environment: (1) Convolutional Neural Networks applied to electric field maps (EM-CNNs), (2) Message Passing Graph Neural Networks (MP-GNNs), and (3) Symmetry-Adapted Gaussian Process Regression (SA-GPR). Using a dataset of 150,000 β values computed at the quantum chemistry level for the non-resonant Second Harmonic Generation (SHG) process, we optimize each model’s hyperparameters and evaluate their precision and usability. All three approaches can accurately predict the β tensors for water molecules in a liquid environment. SA-GPR provides an efficient solution for relatively small training datasets, whereas the Neural Network architectures achieve near-reference accuracy (R2 > 0.997) for the largest datasets. Among them, MP-GNNs provide the highest accuracy while requiring fewer trainable parameters than the EM-CNN architecture. We further apply the best-performing model (EquiNNx ) to study its usability to predict Second Harmonic Scattering (SHS) intensities of bulk liquid water. The ML models can successfully capture the molecular first hyperpolarizability fluctuations and correlations essential for interpreting SHS of aqueous solutions. These approaches are generalizable to other embedded molecules, and other embedding solvents.
The experimentally retrieved value of the optical extinction cross section per unit length, sigma L,ext NT, of individual MoS2 multiwall nanotubes (NTs) is here reported over the 440-940 nm wavelength range for light polarization both parallel and perpendicular to the nanotube longitudinal axis. The impact of nanotube diameter and environment on sigma L,ext NT is addressed for individual nanotubes with diameters of 120 and 220 nm in suspended, sapphire-supported, and PMMA-supported configurations. Measuring individual nanotubes is of utmost importance given the wide nanotube size dispersion intrinsic to the synthesis process. The findings are interpreted in conjunction with finite element method simulations, informed by morphological input parameters from electron microscopy, offering insight into the respective contributions of absorption and scattering cross sections per unit length to overall sigma L,ext NT. These quantitative results are of relevance in view of optoelectronics applications involving MoS2 nanotubes while providing benchmark values for theoretical investigations on their nano-optical response.
Being able to measure the chiroptical properties or more generally the specific response of individual nanoparticles with respect to the polarization of light is a major challenge in the domain of nanophotonics, whether for a fundamental purpose or for understanding and shaping the properties of metamaterials built from these entities. The only few published experiments in this field are essentially dedicated to identifying the signature of circular dichroism. On the basis of conventional methods employed in the polarimetric study of macroscopic samples, we propose an alternative experimental technique which allows a complete determination of the relevant optical anisotropy parameters of a single nano-object (circular and linear dichroisms and birefringences). The retrieval of weak signals from bright-field extinction measurements is made possible by the original combination of polarization and spatial modulation spectroscopies. The framework and applicability of the method and data processing are discussed in detail. They are illustrated through the study of two different types of nanoparticles: achiral homodimers of gold nanospheres and chiral gold nanostructures lithographied on a transparent substrate.
