We present the magnetic, structural, and transport properties of the quaternary Heusler alloys ${\text{Co}}_2{\text{MnSn}}_x{\text{Sb}}_{1-x}$ ($x=0$ , 0.25, 0.50, 0.75, and 1.0), which have been theoretically predicted to be half-metallic. Magnetization measurements as a function of applied field show that the saturation moment for $x=1$ $\left({\text{Co}}_2\text{MnSn}\right)$ is near the Slater–Pauling value of $5{\mu }_B$ ; however, the moment for $x=0$ $\left({\text{Co}}_2\text{MnSb}\right)$ falls far short of its predicted value of $6{\mu }_B$ . Resistivity as a function of temperature was measured from 5 to 400 K, and a phase transition from a half-metallic ferromagnetic phase to a normal ferromagnetic phase was observed between 50 and 80 K for all of the alloys. At low temperature $\left(10\text{K}<T<40\text{K}\right)$ , the resistivity ratio was found to vary as $R\left(T\right)/R\left(T=5\text{K}\right)=A+B{T}^2+C{T}^{9/2}$ , where the $T^2$ term results from electron-electron scattering, whereas the $T^{9/2}$ term is a consequence of double magnon scattering.

Surface ligand activity is a key design parameter for successfully interfacing surfaces with cells—whether in the context of in vitro investigations for understanding cellular signaling pathways or more applied applications in drug delivery and medical implants. Unlike other crucial surface parameters, such as stiffness and roughness, surface ligand activity is typically based on a set of assumptions rather than directly measured, giving rise to interpretations of cell adhesion that can vary with the assumptions made. To fill this void, we have developed a concurrent control technique for directly characterizing in vitro ligand surface activity. Pairs of gold-coated glass chips were biofunctionalized with RGD ligand in a parallel workflow: one chip for in vitro applications and the other for surface plasmon resonance (SPR)-based RGD activity characterization. Recombinant α_Vβ₃ integrins were injected over the SPR chip surface as mimics of the cellular-membrane-bound receptors and the resulting binding kinetics parameterized to quantify surface ligand activity. These activity measurements were correlated with cell morphological features, measured by interfacing MDA-MB-231 cells with the in vitro chip surfaces on the live cell microscope. We demonstrate how the interpretation of a cell phenotype based on direct activity measurements can vary markedly from interpretations based on assumed activity. The SPR concurrent control approach has multiple advantages due to the fact that SPR is a standardized technique and has the sensitivity to measure ligand activity across the most relevant range of extracellular surface densities, while the in vitro chip design can be used with all commonly used light microscopy modalities (e.g., phase contrast, DIC, and fluorescence) so that a wide range of phenotypic and molecular markers can be correlated to the ligand surface activity.

Sm–Co particles have been produced in a W matrix by annealing sputtered Sm–Co/W multilayers with layer thicknesses of 5–28 nm at temperatures of 600–850 °C. The Sm–Co particles had the intermetallic 1:7 and 2:17 structures with sizes below 10 nm and coercivities in the range of 2–10 kOe. A reduction of magnetization with prolonged annealing has been observed and attributed to alloying of Co with both W and Si by interdiffusion through the W layer.

From in vitro cancer research to immunology, single-cell migration assays are among the most common assays for gaining phenotypic insight into the dynamics of adhesion and migration. In general, however, the extracellular environments used in these assays are poorly characterized, which can lead to difficulty interpreting the resulting cellular behavior. Here we introduce a single-cell migration assay which incorporates tunable surfaces that are chemically well-characterized by surface ligand activity (surface activity) quantification. We applied this approach to MDA-MB-231 breast carcinoma cells, measuring single cell morphology, speed, and directionality as a function of cRGD surface activity, controlled via cRGD ligand spacing. Using this approach, we show cell behavior via morphology, migration, and presence of focal adhesions can be directed from amoeboid to mesenchymal-like phenotypes, highlighting tunable surface activity as a reproducible way to direct phenotype.

Nanoscale-engineered surfaces induce regulated strain in atomic layers of 2D materials that could be useful for unprecedented photonics applications and for storing and processing quantum information. Nevertheless, these strained structures need to be investigated extensively. Here, we present texture-induced strain distribution in single-layer WS₂ (1L-WS₂) transferred over Si/SiO₂ (285 nm) substrate. The detailed nanoscale landscapes and their optical detection are carried out through Atomic Force Microscopy, Scanning Electron Microscopy, and optical spectroscopy. Remarkable differences have been observed in the WS₂ sheet localized in the confined well and at the periphery of the cylindrical geometry of the capped engineered surface. Raman spectroscopy independently maps the whole landscape of the samples, and temperature-dependent helicity-resolved photoluminescence (PL) experiments (off-resonance excitation) show that suspended areas sustain circular polarization from 150 K up to 300 K, in contrast to supported (on un-patterned area of Si/SiO₂) and strained 1L-WS₂. Our study highlights the impact of the dielectric environment on the optical properties of two-dimensional (2D) materials, providing valuable insights into the selection of appropriate substrates for implementing atomically thin materials in advanced optoelectronic devices.

Cell segmentation is crucial to the field of cell biology, as the accurate extraction of cell morphology, migration, and ultimately behavior from time-lapse live cell imagery are of paramount importance to elucidate and understand basic cellular processes. Here, we introduce a novel segmentation approach centered around optical flow and show that it achieves robust segmentation by validating it on multiple cell types, phenotypes, optical modalities, and in-vitro environments without the need of labels. By leveraging cell movement in time-lapse imagery as a means to distinguish cells from their background and augmenting the output with machine vision operations, our algorithm reduces the number of adjustable parameters needed for optimization to two. The code is packaged within a MATLAB executable file, offering an accessible means for general cell segmentation typically unavailable in most cell biology laboratories.